THE VISUAL OPSIN AND PHOTOTRANSDUCTION PATHWAY GENES ASSOCIATED WITH EYEREDUCTION AND LOSS IN BAT FLIES (STREBLIDAE, NYCTERIBIIDAE)

A THESIS SUBMITTED TO THE GRADUATE DIVISION OF THE UNIVERSITY OF HAWAIʻI ATMĀNOA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF

MASTER OF SCIENCE

IN

ZOOLOGY (ECOLOGY, EVOLUTION AND CONSERVATION BIOLOGY)

JULY 2021

By

Melissa Atkins

Thesis Committee:

Megan Porter, Chairperson

Floyd Reed

Masato Yoshizawa

Keywords: parasitic arthropod, evolutionary genomics, evolutionary loss, opsin, transcriptomics, bat fly

ACKNOWLEDGEMENTS

I would like to thank my amazing advisor, Dr. Megan Porter who has guided me throughthis whole process and supported me in a change of direction when I lost all of my samples ayear into the degree. Without her help, knowledge, and endless patience for me none of thiswould have been possible. I would also like to acknowledge my committee members who havegiven me their time and expertise on certain portions of this project. In addition, other invaluablepeople who spent countless hours with me annotating genomes, helping me understand certainprograms, allotting me example data, collecting bat flies, and giving me motivation in times ofneed. These people include my mentor, Mirelle Steck along with my collaborators; KatharinaDittmar, Carl Dick, Holly Lutz, Kelly Speer, Steve Davis, and Matthew Aardema

A huge mahalo to my friends, family, and Oʻhana who have stood by me in all the upsand downs of this graduate work and have made my life in Hawai’i so incredibly rich. Learningto kiteboard, compete in races and triathlons, exploration of these beautiful islands by foot andboat, and the many game nights and family dinners mean more to me than I could ever explain inwords. A special thanks to my mom who spent hours on zoom “coworking” with me during thepandemic so I didn’t feel alone and had the motivation to continue on. Thank you to my mom,dad, and Aunt Marian who answered almost every one of my phone calls and consoled me fromafar. I love and appreciate every single person I am lucky enough to consider family, withoutwhom I am not sure how I would have completed this.

This thesis and graduate work is dedicated to my dog, Riley, who passed away July 30th,2020 right in the midst of the pandemic. At 17 years old, he was my companion and best friendfor over half of my life. He saw me through every tough time and any instability that I hadfinancially and otherwise while loving me as only he knew how, unconditionally. He was mybright star at the end of the day and made my life worth living. We had a special bond,understanding, and care for each other that can never be replaced. I know he stayed with me aslong as he could, knowing how difficult the pandemic and graduate school combination was. Iwill forever be grateful to him and his love.

2

Abstract

Evolutionary reduction of visual sensing ability is common in troglobiont species where

no light filters into the habitat. Independent of light environments, parasitism is also well-known

to be associated with a reduction in eye structures. The combination of these two ecological

features is exhibited in the aptly named bat fly, a parasitic arthropod that feeds on bat hosts,

many of which are cave-roosting. In line with other parasitic arthropods, bat flies exhibit

rudimentary development of their visual system. They are derived from fully visual, free-living

ancestors, but the varying degrees of eye reduction observed throughout the clade make them a

unique group of species to study. Although both parasitic and troglobitic species are well-known

to be associated with a reduction in eye structures, the extent of gene loss and transcription

attenuations that are accompanied with eye-loss are not well-studied. In insect compound eyes,

visual perception is dependent on the number of ommatidia present and how light is focused onto

the underlying receptors. Thus far, studies of bat fly macro-morphology from different species

have described eyes containing from 0 to 57 facets. This diverse macro-morphology is thought to

reflect microstructural changes associated with low light levels such as rhabdomere

rearrangement of photoreceptor cells. In order to investigate changes in the molecular

components associated with these anatomical changes, I assembled de novo transcriptomes from

eight bat fly species and de novo genomes from seven bat fly species. These 15 samples

represent a taxonomically diverse set of species with facet numbers ranging 0 to 12. All

assemblies were annotated for opsin genes, which encode proteins that are responsible for light

detection. Thus far, our analyses of genomes reveal that a common dipteran rhodopsin, Rh1, is

present in all bat fly species, with an additional rhodopsin, Rh6, present in Cyclopodia dubia,

though Rh1 was the only opsin to have expression at the transcriptome level. Multi-level

analyses using both transcriptomes and genomes allows for confirmation of sequences and a

more comprehensive understanding of the RNA transcript expression levels in reduced eyes.

This work aims to elucidate the evolutionary trajectories of broader ectoparasite and troglobiont

trends in visual system reductions through the absence of rhodopsin paralogs and

phototransduction cascade genes.

3

TABLE OF CONTENTS

ACKNOWLEDGEMENTS 2

Abstract 3

TABLE OF CONTENTS 4

List of Tables 5

List of Figures 6

Chapter 1: Arthropod Visual Ecology and Opsin Evolution 8Arthropod Visual Systems 9Eye Evolution and Diversity in Cave Habitats 10Light Environment and Opsin Proteins 11Phototransduction Cascade 11Nycteribiidae and Streblidae 12Research Objectives 13

Chapter 2: Phototransduction Cascade Genes and Rhodopsin Paralogs found in a groupof Parasitic Troglobiont bat fly species (Streblidae, Nycteribiidae). 17

Introduction: 17Methods and Materials: 20Genome Sequencing 20Genome Assembly and Annotation of Phototransduction Genes 20Results: 22Discussion: 24Summary 28

Chapter 3: Rhodopsin Expression and Phototransduction Cascade Genes 34Introduction: 34Methods and Materials: 36Transcriptomes 36Analyses 36Results: 38Discussion: 40Summary 43

Appendix A: Macro-anatomy & Immunohistochemistry of Paratrichobius longicrus 50

Literature Cited 52

4

List of TablesTable 2.1 Genome specimen collection information. The Old World Nycteribiidae are in grey and the New World

Streblidae are in blue. 28

Table 2.2 Statistics for genome assembly of bat flies using SPAdes, ABySS, Velvet, and BUSCO. OW denotes the Old

World in grey and NW denotes the New World in blue. 28

Table 2.3 Identification of genes involved in the rhabdomeric phototransduction cascade. Data for species in green

were obtained from MinION reads. 29

Table 3.1 Transcriptome specimen collection information. Three Nycteribiidae species are colored in grey and five

Streblidae species are colored in blue. 45

Table 3.2 Statistics for transcriptome assembly of three Nycteribiidae species in grey and five Streblidae species in

blue using Trinity and BUSCO. 45

Table 3.3 Identified rhodopsin paralogs with their relative TPM from Trinity assembled bat fly transcriptomes. 46

5

List of FiguresFigure 1.1 Fly phototransduction cascade response in order to amplify a single photon of light. Rhodopsin

stimulates energy production and the G-protein-signalling pathway through the Gq protein. Arrestin binds to

rhodopsin to terminate the signal. Rhodopsin (Rh); Transient receptor potential (TRP); TRP-like (TRPL); G-protein

receptor kinase 1 or 2 (RK); Gq protein (Gq); Phospholipase C (PLC); Arrestin 1 or 2 (Arr); Protein C kinase (PKC);

Retinal degeneration C (RdgC); Diacylglycerol lipase (DAGL); Calcium/calmodulin-dependent protein kinase

II(CamKII); (CaM); Neither inactivation nor afterpotential C (NINAC); Inactivation no afterpotential D (INAD); IP3

receptor (IP3R). 15

Figure 1.2 New World (NW) and Old World (OW) bat fly distribution in the Americas and in Eurasia and Africa,

respectively. Bat fly species collected for this study from the NW region are represented by purple markers on the

left side of the map. Bat fly collections made from the OW region are represented on the right side of the map by

dark red markers. 16

Figure 2.1 Rhodopsin tree as a phylogram from Rh1-Rh7 clades with bat fly opsins identified in bold. Bootstrap

values above 60 for nodes are shown. Onychopsins were used as an outgroup in RAxML. Long wavelength sensitive

(LWS) clade includes rhodopsin paralogs Rh1, Rh2, and Rh6. Ultra violet (UV) sensitive clade includes rhodopsin

paralogs Rh3 and Rh4. Short wavelength sensitive (SWS) clade includes rhodopsin paralog Rh5. 31

Figure 2.2 Species tree as a cladogram for rhodopsin paralogs using the 18s gene of each species. Bat fly species

are identified in bold. Bootstrap values above 60 for nodes are shown. Anopheles species are used as an outgroup

using RAxML. 32

Figure 2.3 Comparison of intron splice sites and intron length of identified rhodopsins in bat flies to Glossina

fuscipes and Drosophila melanogaster. Numbers above hatch marks indicate the position of the splice site relative

to Drosophila melanogaster full Rh1 and Rh6 opsins starting at the first base pair. A) Rh1 comparison of intron

splice sites and length. Greyed out portions up to 563bp indicate the beginning of the 5’ sequence which is too

variable in opsins to make an inference. *Old world (OW) denotes all four species with an assembled genome:

Archinycteribia actena, Cyclopodia dubia, Phthridium hoogstraali, Eucampsipoda africana. New world species not

shown, Aspidoptera delatorrei, had a partial opsin sequence with no introns. B) Rh6 comparisons of intron splice

sites and length. Only one Rh6 was found in the assembled bat fly genome, Cyclopodia dubia. 33

Figure 3.1 A) Rhodopsin tree as a phylogram with select closely related species with Onychopsin as an outgroup.

Bat flies are in bold, transcriptome opsin data has been added with genomes that are identified by *. Clades

Rh2-Rh5 and Rh7 have been collapsed. B) A heatmap showing Rh1 expression in relation to facet number. The Rh1

opsin TPM column has a mean of 8.45 and the facet column has a mean of 3.63 facets. Colors are based on the

z-score indicated in the color key, showing the standard deviations away from the mean. The facet color for

Trichobius sp. indicates an unknown amount. 47

6

Figure 3.2 Fly phototransduction cascade. All transcriptome assemblies were run through PIA to identify

phototransduction components in each species. Circles represent identification of a gene; Rhodopsin (Rh, blue);

Transient receptor potential (TRP, indigo); TRP-like (TRPL, purple); Phospholipase C (PLC, yellow); Gq protein (Gq,

salmon); Protein C kinase (PKC, green); Arrestin 1 or 2 (Arr, pink); G-protein receptor kinase 1 or 2 (RK); Retinal

degeneration C (RdgC, red). 48

Figure 3.3 3D protein modeling of Trichobius corynorhini Rh1. The conserved motifs and indel are shown. DRY is on

the 4th helix (position 121) before the strand and coil. HEK is on the 6th helix (position 218) directly before

REQAKKMN (position 223) partially on the 6th helix and intracellular loop. 49

Figure A1 THUNDER image of a Paratrichobius longicrus species cleared bat fly head at a zoom of 11:1 ratio.

Antibody staining for Synapsin (488), GPCR (594), and DAPI (405). Nuclei are fluorescing at the rhabdom level. 51

7

Chapter 1: Arthropod Visual Ecology and Opsin Evolution

Arthropods inhabiting dim-light environments have eyes that have evolved hallmark

macro-morphological and micromorphological specializations. In contrast, evolution in

troglobiont species, i.e., those living in no-light environments, selectively lead to a reduction or

complete loss in visual systems (Cooper et al., 2001; Klaus et al., 2013). Light environments

have been shown to drive evolution of both eye reduction and opsins (Klaus et al., 2013; Sondhi

et al., 2021). Recent work shows higher rates of selection, including 75% of opsin duplications,

in diurnal species in comparison to their nocturnal counterparts (Sondhi et al., 2021). In a cave

setting, types of selection are mixed based on the visual features changing. Underlying genetic

and developmental mechanisms of eye reduction show select genes being changed countering

relaxed selection, while loss of pigmentation was proposed to be caused by neutral mutations

(Jeffery & Strickler, 2010; M. Protas et al., 2007). Strong directional selection has been proposed

in cave crabs where eye reduction evolves at the same pace as traits that are deemed constructive

(Klaus et al., 2013). While dim-light specializations such as wider rhabdoms, larger facets, and

optical structures optimized for increased sensitivity are seen in many nocturnal arthropods,

troglobiont species are thought to transition to complete eye loss while focusing the conserved

energy into other non-visual features that improve sensory capabilities related to resource finding

and are termed ‘constructive traits’ (Greiner, 2006; Greiner et al., 2004; Klaus et al., 2013). In a

cave setting, examples of constructive traits include those used for non-visual orientation,

navigation, and communication through enhanced chemosensory and auditory capacities (Klaus

et al., 2013; L. Mejía-Ortíz & Hartnoll, 2006).

Parasitism is also well-known to cause eye reduction and loss following a similar trend to

troglobiont species (Marshall, 1981, 1982). Ecological factors like dark environments and the

ability to perform basic needs such as feeding and reproduction with limited movement have

contributed to the eye reduction and loss trend seen in both troglobiont and parasitic species,

respectively. As separate entities, these ecological factors each lead to arthropod eye reduction.

The general question that influenced the research presented here was, how many opsin genes

remain in reduced compound eyes and are the opsin paralogs identified still functional,

especially in the complete loss of an eye? In order to answer this question, the main goal of this

thesis is to characterize what type of molecular changes are happening in species that are

experiencing the combination of the two ecological features, cave habitats and parasitism, and

8

how combined they lead to an extreme example of variation in eye reduction in the visual

systems of bat flies. In this introduction, I will review topics related to these themes, such as eye

evolution and diversity of arthropods in cave habitats and the effect of the environment on trends

at the molecular level, including the opsin proteins and the phototransduction cascade, in the

context of eye loss in the bat fly families, Streblidae and Nycteribiidae.

Arthropod Visual Systems

Arthropod visual systems can be categorized into three optical types: apposition, optic

superposition, and neural superposition (Land, 2005). These three optical types depend on facet

numbers and overall eye size, which are directly related to the amount of light captured that is

then processed as visual information. A superposition arrangement allows for high light

sensitivity at the cost of spatial resolution because each receptor receives light from multiple

facets (Agi et al., 2014). In contrast, an apposition arrangement maximizes spatial resolution by

focusing light from each individual facet through a crystalline cone structure onto a structure

found in the center of the ommatidia, called a rhabdom. Thus far, all true flies (Diptera) possess a

special type of apposition eye called neural superposition that has anatomical differences in the

retina. The hallmark specialization for neural superposition is the inter-rhabdomerial space (Agi

et al., 2014; Zelhof et al., 2006).

Rhabdoms are composed of microvilli extending from retinula cells which contribute to

the formation of compound eyes. Rhabdomeres are, at the cellular level, rod-like parts of the

rhabdom (Wolken et al., 1957). Fused rhabdoms, a key feature in the apposition eyes of most

insects, transitioned to an open rhabdom formation to create the microstructural basis for neural

superposition eyes (Mahato et al., 2018). Open rhabdoms are thought to have evolved five times

independently in both crustacean and insect lineages via nocturnal intermediates (Osorio, 2007).

Throughout the order Diptera, there are known examples of loss; for example, the mosquito,

Anopheles gambiae, evolved to have a fused rhabdom confirmed by the loss of expression from

the gene eyes shut/spacemaker (Agi et al., 2014; Mahato et al., 2018). Fused rhabdoms increase

light sensitivity through optical coupling which greatly benefits nocturnal and dim-light insects

(Agi et al., 2014; Mahato et al., 2018). The size of the rhabdom limits the amount of photon

absorption and thus sensitivity, therefore fusing rhabdomeres at a cellular level to increase

rhabdom size would increase sensitivity at the cost of resolution (Mahato et al., 2018). Studies in

9

nocturnal arthropods show a larger rhabdom in comparison to their diurnal relatives (Greiner et

al., 2004; Greiner, 2006; Land, 2005).

Eye Evolution and Diversity in Cave Habitats

While eye reduction in parasitic invertebrates is well studied, eye loss in invertebrate

cave species is not. The cave invertebrate, the crayfish species Orconectes australis packardi,

has been found to have complete ommatidia loss and a highly disorganized retina with more

neural processes moving toward olfaction. In contrast, a surface crayfish counterpart,

Procambarus clarkii, still has vision and ommatidia (Cooper et al., 2001; L. M. Mejía-Ortíz &

Hartnoll, 2005). In reference to eye evolution of Diptera in the dark, the closest studied species

are nocturnal wasps, mosquitoes, and bees, which specifically looked at retinal and optical

adaptations for nocturnal vision in comparison to diurnal relatives. While the retinal and optical

adaptations in nocturnal wasps, mosquitoes, and bees have been investigated, there have been

few studies focusing on adaptations to different types of dark habitats in Diptera. From these

studies there were generally two main functions for these adaptations related to dim light vision:

to increase the amount of light entering the eye and the ability to trap or increase the photon

signal once it hits the rhabdom. All of the studied nocturnal species exhibited enlarged eyes

relative to body size, larger facet sizes, and larger rhabdoms, some of which were fused together

depending on the type of optics in the eye (Greiner, 2006; Greiner et al., 2004; Jander & Jander,

2002; Land, 1997; Land et al., 1999). These invertebrate eyes span different optical types which

lead to differences in adaptations. The superposition eye of the halictid bee combined the above

traits with a ratio of corneal thickness to crystalline cone length that is up to 4.5x larger than its

diurnal counterpart and may contain a tapetum, a reflective layer within the choroid, which gives

the retina another chance to absorb photons of light (Greiner et al., 2004). Nocturnal mosquitoes

contain an atypical version of the apposition type eye where they use spatial summation from an

unusually dense packing of ommatidia and larger lens. In addition, the cornea to lens and cornea

to rhabdom distance is shortened to increase the amount of light provided while wide, fused

rhabdoms absorb it effectively (Land, 1997; Land et al., 1999). Nocturnal wasps with apposition

type optics follow the hallmark features seen in eyes from species living in dim environments:

larger eye size and rhabdom diameter; instead of larger facets, they maintain facet size and add

more facets, approximately 2000 (Greiner, 2006).

10

Light Environment and Opsin Proteins

Many studies illustrate that light availability within the environment has a large role in

eye evolution and more specifically, opsin sequence evolution. Opsins are, at a molecular level,

the protein essential to vision. When bound to a chromophore, opsins are sensitive to specific

wavelengths of light (Romhányi & Molnar, 1974; Zuker et al., 1985). Opsins are G-protein

coupled receptors (GPCRs) with seven transmembrane helices, typically characterized by a

chromophore attached to a lysine in the seventh helix (Porter et al., 2012). The wavelength that

isomerizes this chromophore, triggering the intracellular phototransduction cascade, depends on

the suite of amino acids that it interacts with (Wakakuwa et al., 2010). Evolutionary studies have

shown that arthropod visual opsins typically fall into three major clades based on the peak

absorbance of the photopigments formed. In Diptera and most insects, this process is mediated

by R-opsins classified by their wavelength sensitivity: Long Wavelength Sensitive (LWS) opsins

that form visual pigments which absorb green wavelengths of light, Short Wavelength Sensitive

(SWS) opsins that form visual pigments absorbing blue wavelengths of light, and UV-sensitive

opsins (UV) for ultraviolet light (Feuda et al., 2020; Sakai et al., 2017). The non-visual Rh7

opsin has been found to respond to a broad spectrum of light (Sakai et al., 2017). Opsin paralogs

for Drosophila melanogaster, a well-studied dipteran species, that are used for vision have been

characterized within each wavelength clade: LWS (Rh1, Rh2, and Rh6), SWS (Rh5), and UV

(Rh3 and Rh4) (Sakai et al., 2017). While ancestral arthropods are thought to have one opsin

from each clade and therefore the possibility of trichromatic vision (Koyanagi et al., 2008), this

trait isn’t advantageous for nocturnal species or those inhabiting low-light to no-light

environments, such as caves. In these types of environments species typically have

monochromatic vision, showing selective constraints on opsin gene functionality, for example

gene expression, or even gene loss (Niemiller et al., 2013; Tierney et al., 2015).

Phototransduction Cascade

The phototransduction cascade is a G-protein-signalling pathway that responds to a single

photon of light and amplifies it using a molecular process in order for varying levels of light

intensity to be transmitted to neuronal cells (Figure 1.1)(Montell, 2012). The photoactivated

visual pigment, known as rhodopsin, stimulates the GDP/GTP exchange where release of

11

guanosine diphosphate allows binding of guanosine triphosphate. The Gq protein activates

phospholipase C encoded by norepinephrine A which hydrolyzes phosphatidylinositol

4,5-bisphosphate or PIP2. This protein activation leads to the opening of transient receptor

potential (TRP) and TRP-like cation channels in the photoreceptor cells. Retinal degeneration C

contributes to calcium signaling and dephosphorylation of rhodopsin. Arrestin2 binds to the

rhodopsin and contributes to termination of signaling by blocking the rhodopsin/Gq interaction

(Figure 1.1). Drosophila visual pigments are bistable, requiring the absorption of a photon of

light to activate the rhodopsin and a second photon to convert the metarhodopsin back to the

non-activated state (Montell, 2012). Fly photoreceptors detect single photons in addition to light

adaptation by activating a certain number of channels that are closed at rest instead of the

10,000’s of channels that are open in vertebrate rods, needing to close several hundred to get a

detectable response (R. C. Hardie, 2001). The typical invertebrate photoreceptor is able to have a

rapid response to a wide range of wavelengths, while keeping sensitivity. This pathway

determines what genes are responsible for this high function and whether or not other

invertebrates have functioning vision in comparison to this model organism, Drosophila

melanogaster.

Nycteribiidae and Streblidae

Bat flies, an ectoparasite that feeds on bats, are an extreme example of a troglobiont

species (Dittmar et al., 2006). The extreme ecology of cave dwelling organisms that lead to a loss

of visual morphology coupled with the rudimentary development of visual systems seen in other

parasitic arthropods, makes bat flies a unique study organism (Dick & Patterson, 2006). While

currently both cave-dwelling and parasitic, bat flies are derived from free-living ancestors that

had complex visual systems (R. Hardie et al., 1989). It can be inferred that bat flies have reduced

eyes given that closely related taxa in the Hippoboscidae and Glossinidae have large,

well-developed eyes comprising thousands of facets (Buschbeck and Friedrich, 2008; Hardie,

1986). The observed reduction of eyes in this group leads to the question of how they are being

used and therefore what molecular components are present in each type of eye reduction.

Glossinidae, a family that is closely related to the bat flies, contains a lineage specific loss of the

dipteran Rh2 and Rh4 opsins. The common ancestors of Glossinidae, Muscidae and

Calliphoridae, show a loss of the Rh4 opsin, and the more distantly related Diopsidae has lost all

12

opsins except for Rh2 and Rh6 (Feuda et al., 2020; Kutty et al., 2010). In bat flies, the rhodopsin

paralogs expressed in reduced eyes are unknown, but given the sister clades, it is inferred that

some opsin copies are already missing (i.e., Rh2 and Rh4). A recent bat fly study confirmed this

pattern by only finding a partial Rh1 opsin in a Trichobius frequens transcriptome (Porter et al.,

2020). The following bat fly study allows for further understanding of evolutionary gene loss

across multiple species in order to extrapolate to broader ectoparasite eye loss trends. Yet, this

evolution of loss balanced with continued functionality is not well understood.

A split of ancestral bat flies created two geologically distinct groups at an early stage of

bat fly speciation, contributing to some diversification. Although bat flies have a worldwide

distribution, they are largely categorized under New World (NW) and Old World (OW) fauna

(Figure 1.2). There are main geographical differences that contribute to NW and OW, which

generally have no taxa in common. NW Streblidae are largely found in subtropical and tropical

climates while OW Nycteribidae occur in temperate climates (Dittmar et al., 2006). This

geographical split supports two distinct groups aside from the genus Basilia. Dispersal of the

genus Basilia occured after the geographical split, creating a highly variable genus (Dittmar et

al., 2006). Basilia is therefore the only NW Nycteribiidae in addition to species being identified

in the OW (Dittmar et al., 2006; Mayberry, 2014). Basilia are an incredibly variable genus that

are phylogenetically quite diverse with eyes that have zero to two facets.

Research Objectives

Bat flies all have reduced eyes and facet numbers, likely because they are parasites that

live in dim light habitats. Thus far, studies of bat fly macromorphology across species have

described eyes containing 0 up to 57 facets (Wenzel, 1975). For this study I sampled a

taxonomically diverse set of bat fly species that also have variation in the degree of eye

reduction, with total numbers of facets ranging from 0 to 12 between the species. Although

parasitism and low light environments are well-known to be associated with a reduction in eye

structures, the molecular processes involved in the evolution of eye reduction are not

well-known. Thus, this thesis aims to use a multi-level comparison of visual system molecular

components, using both genomes and transcriptomes to answer the proposed question by

identifying opsin and related phototransduction cascade genes. The objective of this study was to

elucidate whether visual macro-morphology, primarily facet number, and geographic distribution

13

corresponded to the level of reduction seen in the loss of opsin paralogs. Finally, this thesis

answers the question, are the identified opsins functional at the transcriptome level. The second

chapter of this work characterizes rhodopsin paralogs and phototransduction cascade genes in the

genomes of Streblidae and Nycteribiidae species. The final chapter looks at the functionality of

rhodopsins and phototransduction cascade genes through expression. Bat flies present an

opportunity to fill in the molecular knowledge gap in vision loss of invertebrates by studying the

evolution of genes involved in light signaling in the context of varying levels of compound eye

reduction.

14

15

16

Chapter 2: Phototransduction Cascade Genes and Rhodopsin Paralogs found in a group of

Parasitic Troglobiont bat fly species (Streblidae, Nycteribiidae).

Introduction:

Bat flies, composed of the families Nycteribiidae and Streblidae, are highly specialized

ectoparasites in the order Diptera, superfamily Hippoboscoidea (Dittmar et al., 2006). This

unique group of species is a product of two ecological features that contribute to extreme eye

loss - parasitism and cave-dwelling - making them an ideal candidate to understand the

molecular evolutionary trajectory of eye loss. The overall diversity in eye size of bat fly species

ranges from 0 - 57 facets. While bat flies are a diverse clade that are globally distributed, specific

trends in eye size exist between New World (NW) and Old World (OW) species, with the broad

range of facet numbers (0-57) occurring exclusively in the NW species and OW species

containing a narrow range (0-3) (Dittmar et al., 2015). Despite major reduction trends in

macromorphology, five morphological types of eyes have been characterized across the two

families (Dittmar et al., 2015). Facet number is thought to correlate with visual function, yet in a

light deprived environment specializations that enhance function are not based on facet number.

The main adaptations include larger facets and wider rhabdoms (Greiner, 2006; Greiner et al.,

2004; Klaus et al., 2013), a structure found in each ommatidium that is made up of microvilli

from retinula cells. A recent study described fused rhabdoms in the species Trichobius frequens

(Porter et al., 2020), a member of the genus with the least reduced compound eyes. Given the

number of facets in bat flies’ eyes are variable across species, with 57 facets as the largest

number recorded in any bat fly, comparison of facet numbers is only a starting point in

determining the evolutionary patterns involved in vision loss.

Dipteran visual systems can evolve to match environmental constraints across multiple

biological levels. Compound eye type and visual function are determined by

macromorphological and microanatomical structures, such as number of facets and rhabdomere

arrangement, respectively. Phylogenetic studies of dipterans showed that bat flies evolved from

fully visual species with open rhabdoms, a multitude of facets and multiple opsin paralogs.

Within the suborder Brachycera, species such as Lucilia cuprina and Musca domestica have

neural superposition type eyes composed of ~3,000 facets containing open rhabdoms that each

express four to five rhodopsin paralogs (Agi et al., 2014; Feuda et al., 2020; Lunau, 2014;

17

Sukontason et al., 2008), while hippoboscid species that are more closely related to bat flies have

neural superposition type eyes that only contain hundreds of facets (Jobling, 1926; Mayberry,

2014). Bat flies evolved to have rudimentary vision based on a small number or no ommatidia

and possible loss of rhodopsin paralogs (Feuda et al., 2020; Kutty et al., 2010; Mayberry, 2014).

Drosophila contain eight light sensing photoreceptor cells in each ommatidium labelled

R1-R8 (Earl & Britt, 2006; Rister & Desplan, 2011; Wernet & Desplan, 2004), that in total

express five opsin proteins (Rh1, Rh3-Rh6). The outer photoreceptors R1-R6 are arranged in a

trapezoidal shape with R7 and R8 making up the inner distal and proximal portion, respectively

(Nilsson & Kelber, 2007; Wernet et al., 2015). The photoreceptors R1-R6 are optically

independent from one another while R7 and R8 have the same optical path (Briscoe, 1999).

There are two ommatidial subtypes that, combined, express either UV-sensitive Rh3 or Rh4 in

R7, either blue sensitive Rh5 or green sensitive Rh6 in R8, and Rh1 in all R1-6 photoreceptors

(Wernet et al., 2015). In Drosophila, Rh2 is typically expressed in the ocelli, a simple eye

comprised of a single lens. The six outer photoreceptors are responsible for motion detection and

image formation and span the entire thickness of the retina, while the R7 and R8 cells are stacked

one on top of the other and primarily transmit color information (Agi et al., 2014; Kelber, 2003;

Rister & Desplan, 2011). Based on reconstructions of opsin gene loss across the dipteran

phylogeny, the Rh4 gene was lost in Hippoboscoidea, which includes the bat flies (Feuda et al.,

2020). Based on the lack of ocelli in bat flies, it is predicted that the ocelli-specific Rh2 gene is

also likely lost in this group (Dittmar et al., 2015; Kutty et al., 2010). These losses lead to the

question of whether bat flies have lost additional opsins during the evolutionary reduction of

their visual systems, which is the focus of this study.

Visual genes are highly conserved across taxonomic groups, allowing for visual opsins to

easily be identified. Opsins are a monophyletic gene family that code for proteins which are

essential to the visual response to a photon of light (Porter et al., 2012). Genes in the

phototransduction pathway, especially those in important positions related to amplification and

signalling, are critical in determining the exact mutations responsible for vision loss. Disruptions

to the G-protein signalling pathway, such as gene loss or a mutation to a protein coding region

that causes a loss of function, will result in vision loss (Yang et al., 2016). Once a visual pigment

in a fly photoreceptor cell becomes photoactivated, it stimulates GDP/GTP exchange in the Gq

protein, which activates the rest of the pathway. Essentially, phototransduction cascades serve to

18

amplify single photon responses, and to allow the cells to adapt to light intensities that differ

over many orders of magnitude (R. C. Hardie, 2001). Possession in the genome of specific,

vision related genes in this pathway, such as rhodopsin, kinases, Gq, and termination

components, imply that the visual components will be functionally expressed.

Rhodopsin paralogs identified in genomes require further analyses to determine visual

function; in addition to characterizing opsin genomic sequences, this chapter focuses on both

comparison of opsin intron structure and identification of additional phototransduction

components as proxies for functionality. Introns tend to be highly conserved in splice site

position, only varying in length; therefore, a non-functional opsin may include a loss of intron or

a change in position in comparison to closely related species (Chorev & Carmel, 2012).

Analyzing the structure of introns, a non-coding region of DNA between exons that is removed

before translation, is helpful in analysis of bat fly opsins because they tend to be highly spatially

conserved within the three opsin classes in Diptera (Spaethe, 2004; Taylor et al., 2005). For

instance, intron splice sites of Diptera, fleas and lepidopterans have a high degree of similarity

both among species and across long-wavelength sensitive opsins with varying intron length

(Briscoe, 1999; Spaethe, 2004; Taylor et al., 2005).

While a number of studies have focused on visual capability through macromorphology

of troglobiont arthropods, the associated evolution and patterns of loss in the molecular

components of vision haven’t been studied yet. In terms of eye loss, genetic work has

substantially only been done on vertebrates. Herein lies the gap of knowledge this study intends

to fill using a troglobitic arthropod, the bat fly, that has a secondary environmental pressure (e.g.

parasitism) inducing eye loss. This study sequenced the genomes of seven different species

within Nycteribiidae and Streblidae that contained eyes with varying numbers of facets ranging

from 1-12 among species. By identifying rhodopsins and phototransduction pathway components

within each, this work aims to address whether the loss at the molecular level corresponds to

either geographic distribution or reductionary trends at the morphological level. These analyses

will add to our understanding of the evolution of eye loss in both parasitic and cave invertebrates

by identifying which opsins still remain and have functional support genes for visual

phototransduction.

19

Methods and Materials:

Genome Sequencing

Genomes were sequenced from four species of Nycteribiidae and three species of

Streblidae. This sampling included both New World and Old World species (Table 2.1) (Dittmar

et al., 2006). For each species of bat fly sequenced, collected individuals were preserved in

ethanol for approximately one year stored at 4℃. DNA was extracted from individual bat flies

using the Qiagen DNeasy Blood & Tissue kit (Qiagen) following the manufacturer protocols for

tissue with the following exceptions: (1) the whole bat fly body was homogenized using a glass

mortar and pestle with liquid nitrogen prior to lysis; (2) the volume of proteinase was doubled;

and (3) the incubation time was increased to one hour. For DNA yield optimization, the sample

was eluted twice with 64ul of AE buffer. Extracted DNA quality was assessed initially using a

Qubit 3.0 Fluorometer (Thermo Fisher Scientific) or a nanodrop (ND1000) and confirmed via a

2100 Bioanalyzer system (Agilent Technologies). Only DNA with a quantifiable concentration

on the Qubit and a 260/280 value within ± 0.3 of 1.8 was sent for more precise quantification.

Five samples in total were sent to Novogene (Sacramento, CA, USA) for whole-genome

sequencing using a NovaSeq 6000 platform (Illumina® Inc.).

The remaining two samples were sequenced with MinION technology on a Nanopore

Flow Cell (Oxford Nanopore Technologies, San Francisco, CA, USA). Libraries were created

following the Native Barcoding Genomic DNA protocol using a SQK-LSK 109 ligation

sequencing kit (Oxford Nanopore Technologies) with NEBNext reagents stated in the protocol.

In a novel technique adapted to multiplex the low concentration DNA samples, each tagged

DNA library was pipetted into the primed flow cell port (EXP-FLP002) during the initial run,

and subsequent libraries were individually spiked in either every four hours, upon acquiring 1GB

of data, or when sequencing dropped off to ensure the least amount of nanopores were lost. Once

the sixth sample was pipetted in a dropwise fashion in the SpotOn port, the flow cell was allowed

to run the remainder of the 24 hours to acquire all nucleotide reads. The last sample spike was

completed if at least 800 nanopores remained active at the time of the spike.

Genome Assembly and Annotation of Phototransduction Genes

For each set of Illumina raw reads, fastQC (v0.11.9, Babraham Bioinformatics) was used

to assess sequence quality scores, sequence length distributions, and adaptor content. Raw

20

paired-end reads were trimmed with Trimmomatic and TrimGalore (v0.6.5;

https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/). Trimmomatic (Bolger et al.,

2014) was used to remove any sequences below a phred score of 33 and both were used to be

sure that all adapters were removed. These reads were then processed through fastQC (v0.11.9)

again for confirmation and used as clean reads. Without any reference genomes available, reads

were de novo assembled from Illumina libraries through the National Center of Genome

Analysis Support’s (NCGAS; Indiana University, Bloomington, IN, USA) Mason Linux cluster

using ABySS (Jackman et al., 2017), SPAdes (Bankevich et al., 2012), and Velvet (Zerbino &

Birney, 2008). Although the SPAdes default settings combine kmer values for best output

already, comparison with the two other programs allowed for the best quality assembly to be

used. Best quality was determined through a combination of factors using QUAST (Gurevich et

al., 2013): number of contigs, N50, and maximum contig length. The highest combination of

these factors with priority given to N50 determined which kmer value, ranging from k50 to k90

(every odd kmer), from which assembly program was used. A second quality check was

performed using BUSCO (v3.0.2)(Simão et al., 2015) with the arthropoda_odb9 lineage using

default settings. Assemblies that met the cutoff standard, a >93% similarity threshold, were used

for the rest of the bioinformatics pipeline.

Genomes were assessed using Phylogenetically Informed Annotation (PIA) using an

e-value of 1x10＾-5 and allow maximum hits up to 100 to identify any R opsins (Speiser et al.,

2014). PIA is a tool included in the Galaxy Bioinformatics Platform with servers based out of the

University of California Santa Barbara. It contains 102 vision genes in a Light Interaction

Toolkit (LIT). R opsin PIA hits were confirmed using Geneious software (Geneious Prime,

v2020.0.3). In using Geneious, known Rh1-Rh7 fly opsins from Glossina and Drosophila

mRNA transcripts were used to query assembled genome scaffolds using tblastn with a max

e-value of 1x10＾-5 to identify the top 10 hits for each genome. Hits with a bit score higher than

100 were then BLAST against the nucleotide collection database in NCBI to confirm the gene as

an opsin, using a max e-value of 1x10＾-10 as a significant match. Any hits that were not opsins

were removed from the dataset and the single longest representative sequence was chosen for

each isoform group. Opsin hits were then annotated using the Geneious edit feature to remove

introns and stop codons by aligning the genome sequences with annotated opsin transcriptome

sequences either from closely related Glossina species or that were assembled from bat flies

21

(Chapter 3). These sequences were confirmed with the phylogeny created by LIT using the tab to

tree function by using the rhodopsin landmarks, which are genes from model organisms. Queries

that landed within the same clade as the rhodopsin Drosophila melanogaster landmarks were

confirmed as visual opsins. Amino acid sequences were then aligned in Geneious using MAFFT

and used to reconstruct a phylogenetic tree and opsin tree through CIPRES (Miller et al., 2015)

servers using RAxML (Stamatakis, 2014; Stamatakis et al., 2005) with Onychopsins as an

outgroup. Intron identification was done through a tool in Geneious called Augustus, using a

combination of mRNA and nucleotide sequences from related species. Intron comparisons were

made through an alignment of opsin genes from all bat fly species’ assembled genomes,

Glossina fuscipes, and Drosophila melanogaster.

MinION raw reads were BLAST against known bat fly opsins as well as those of closely

related species. In addition, MinION raw reads were BLAST against landmark genes from the

PIA phototransduction cascade of both bat flies and other Diptera in Geneious software.

Specifically, this analysis looked through the phototransduction rhabdomeric pathway for visual

opsins, Gq proteins that allow the signal to be transduced, regulatory proteins such as lipase,

permeable cation channels (TRP and TRPL), and arrestins, which terminate the pathway.

Results:

Sequencing and de-novo assembly of genomes was completed for five species of bat

flies, generating unique contiguation sequences (contigs) between 16,462 bp for Phthiridium

hoogstraali and 83,414 bp for Cyclopodia dubia (Table 2.1). Sequencing coverage ranged from

41X to 62X with genome sizes from .111 to .308 Gbp. The best SPAdes program assemblies,

based on N50 values, total length, GC content, and number of contigs over 500 bp, configured

for Archinycteribia actena, Cyclopodia dubia, and Trichobius intermedius had kmer values of

K74, K66, and K82 respectively. Abyss assemblies for Nycterophilia parnelli and P. hoogstraali

had kmer values of K60 and K74 respectively. N50’s for all genomes ranged from 3460 contigs

to 35602 contigs with GC content from 16.8% to 36.14%. BUSCO, a tool to assess completeness

of the genomes through highly conserved single-copy orthologs, recovered scores above 90% for

all species, ranging from 93.0% to 98.8%. Percent fragmented sequences ranged from 0.8% to

4.1% while missing sequences ranged from 0.4% to 2.9% (Table 2.2).

22

Components of the phototransduction cascade were identified by the PIA workflow,

including all opsin hits. By conservative estimates, all five Illumina generated genomes

contained one opsin sequence in the Rh1 clade and for four of these genomes, this Rh1 was the

only opsin found. The Rh1 found in Aspidoptera delatorrei was only a partial opsin. In addition

to the Rh1 clade, Cyclopodia dubia also had an opsin sequence in the Rh6 clade of the dipteran

opsin phylogeny (Figure 2.1, 2.2). Although macromorphology was a primary portion of the

hypothesis, facet number did not appear to correlate with the number of identified opsins,

considering Cyclopodia dubia has two facets and Phthridium hoogstraali has zero facets. In

addition to opsins, all five species had transient receptor potential (TRP) and TRP-like channels,

phospholipase C (PLC), Gq protein, protein C kinase (PKC), and G-protein receptor kinase 1 or 2

(RK) present in the genome. In two of the five species, Trichobius intermedius and Nycterophilia

parnelli, signal termination proteins retinal degeneration C (RdgC) were also identified.

Rh1 genes were also identified in the MinION reads for Eucampsipoda africana and

Aspidoptera delatorrei that were BLAST separately from the assembled Illumina genomes. In

addition to this, all reads from E. africana and A. delatorrei run through PIA found only three

and four vision related phototransduction genes identified in total, respectively (Table 2.3).

These two species using MinION data only had Rh and PLC phototransduction genes in common

(Table 2.3).

Intron comparisons were made through an alignment with bat fly species to the closely

related species, Glossina fuscipes, and the model organism, Drosophila melanogaster. All intron

analyses are relative to full opsin sequences of Drosophila melanogaster (Figure 2.3). Splice

sites of the two introns found in the Rh1 opsin were the same in all OW bat fly species at 1113bp

and 1805bp (Figure 2.3A). In contrast, the NW species Nycterophilia parnelli lost the first intron

all together while maintaining the same splice site of the second intron, 1805bp. For the other

NW species, Aspidoptera delatorrei, only a partial Rh1 opsin was recovered that didn’t span any

of the conserved intron sites. Glossina fuscipes Rh1 had a total of three introns, two of which had

the same splice sites as the OW bat flies and only one of those had the same splice site as the

NW bat flies. G. fuscipes also had an additional intron in between the two with a splice site at

1385bp. All of these introns are in comparison to the four identified introns in Rh1 of Drosophila

melanogaster, with splice sites at 360bp, 1035bp, 1385bp, and 1808bp. Intron splice sites for

Rh6 of Cyclopodia dubia, 896bp and 1270bp, matched identically to Glossina fuscipes and were

23

only a few base pairs off to Drosophila melanogaster (Figure 2.3B). D. melanogaster, G.

fuscipes, and C. dubia identified only two introns each for this rhodopsin paralog.

Discussion:

The dipteran families Streblidae and Nytceribiidae are a speciose group. All of the

species in this troglobitic and parasitic group of insects have reduced eyes, but exhibit variable

degrees of reduction and loss between species. Troglobiont arthropods show an evolutionary

reduction in eye-related macromorphological features as well as genetic factors controlling

visual capacity (Feuda et al., 2020; Klaus et al., 2013). This pattern is most clearly seen in

extensive research of the fish species, Astyanax mexicanus, where fully visual surface fish are

compared to their cave counterparts adapted to perpetual darkness (Keene et al., 2016). The basis

for eye loss is easily studied in this model species where the cave fish diverges from normal

vertebrate eye development when it is first born, leading to complete eye loss from the

downregulation of Pax and hedgehog gene families (Krishnan & Rohner, 2017; Yamamoto et al.,

2004). These genetic factors controlling the development and maintenance of vision undergo

mutations that favor vision loss in cave vertebrates and have evolved in parallel across divergent

taxonomic groups (Culver, 1982; Wilkens et al., 2000). This type of genetic mutation is not well

known for cave dwelling invertebrates. A recent publication that studied the genetics of the

isopod Asellus aquaticus compared two independent origins of cave population to a surface

population of the same species (M. E. Protas et al., 2011; Re et al., 2018). Despite evolving

independently, both cave taxa have characteristic eye loss and depigmentation in comparison to

the surface species (Re et al., 2018).

The identified opsins from the seven bat fly genomes presented here are in line with the

rhodopsin losses documented in closely related hippoboscid species (Feuda et al., 2020; Taylor et

al., 2005). While the model organism, Drosophila melanogaster, has visual rhodopsin paralogs

(Rh1-Rh6) that respond to SWS (Rh5), LWS (Rh1, Rh2, and Rh6), and UV light (Rh3 and Rh4),

the more closely related ancestors to Streblidae and Nycteribiidae have lost some of these

paralogs (Sakai et al., 2017). For example, species in the Tephritidae lineage lost the SWS opsin,

Rh5, and the ocelli based opsin, Rh2. In Diopsidae there was an even more extensive opsin loss

with the loss of both SWS, UV and one LWS opsin (Feuda et al., 2020; Kutty et al., 2010). In the

Glossinidae, the sister clade to Hippoboscidae, there was a lineage specific loss of Rh4 and a

24

species specific loss in Glossina morsitans of Rh2 (Feuda et al., 2020). Comparatively, bat flies

do not have ocelli therefore there is a specific morphological loss that corresponds to the loss of

Rh2 (Dittmar et al., 2015). As troglobiont species, the loss of the UV and SWS clade rhodopsins

(Rh3-Rh5) in bat flies suggests that those wavelengths are no longer present in the environment.

Correspondingly, the rhodopsin paralog still present is likely being tuned to the dominant

wavelengths in the environment. Thus far, the results show that Rh6 is still present in one species

and therefore has been lost in most of the bat fly lineage; Rh1 is present in all studied species and

is clustering in the dipteran Rh1 clade in the rhodopsin phylogeny (Figure 2.1). Because

Rh2-Rh5 were not identified, the phylogenetic timeline of their loss would indicate before

diversification in the bat fly lineage.

In order to make accurate inferences from the presence or absence of genes, genome

quality and coverage need to be assessed. Of the seven study species, only two that were

sequenced through MinION and had FastQC that was below the phred threshold of 33 were not

assembled and therefore do not have quality statistics. The genome length metrics that provide a

standard measure of quality include N50, which calculates the summation of all sequence lengths

that are above 50% of the total assembly length, and the largest contig (Bradnam et al., 2013).

Both of these metrics, which show the ability of the assembler to combine reads into large

sequences without a high rate of fragmentation or misalignment, in combination with the high

percent completed and low percent fragmented BUSCO statistics suggest that these genomes

have been properly sequenced and assembled. Genome coverage, another important statistic in

relation to quality, showed all genomes were deeply sequenced in order to attain available reads

from the sample with the largest contig just under 3.0 kbp. These metrics are important in order

to help assess the validity of rhodopsins identified as well as attribute meaning to those not

identified. One of the metrics that seems to be uniformly skewed is the GC content. While in

most Diptera, GC content tends to be on the lower side, meaning below 50% (Mizuno &

Kanehisa, 1994), bat flies in this study are uniformly at 40% or below. GC content is highly

correlated to genome size and chromosomal structure leading to variability among species. In

particular, small genomes and those from species dependent on a host tend to be GC poor due to

the environment and metabolic resources (Foerstner et al., 2005; Rocha & Danchin, 2002).

Lower GC content is also correlated with higher mutations and substitutions from selection

(Chen et al., 2014; Hershberg, 2016), suggesting that these genomes have higher mutation rates.

25

This bias is an interesting finding in bat flies given higher mutation rates in combination with

relaxed constraint and relaxed environmental pressures in the dark suggests a possible

mechanism to rhodopsin or phototransduction gene function and loss.

The genome quality metrics will also enable a better understanding of phototransduction

genes identified. Functionality of the identified opsins will be partially attributed to identification

of supporting genes in visual signal transmission. For all of the assembled genomes, all PIA

pathway components were identified except for arrestin and rdgC. The components missing in

the MinION sequences, including Gq, do not signify a loss due to the poor quality identified via

the FastQC. Both of these components have to do with termination of signal from the

photoactivated rhodopsin. Although rdgC was identified in the genomes of two species (Table

2.4), the overall lack of these genes suggests that either the signal is continuously being

amplified or that the lifetime of the activated rhodopsin is increased (Yau & Hardie, 2009).

Loosely related studies in vertebrates link loss of these termination components to deterioration

of functional performance and slower photoresponse recovery (Song et al., 2011). Tying these

two ideas together, the opsins could be in a state of functional decline. This hypothesis will be

further investigated by quantifying opsin expression levels in the next chapter (Chapter 3).

The developmental determination of the eight photoreceptor cells in Drosophila

ommatidia are done in a pairwise fashion after the founder cell R8: R2 and R5, R3 and R4, R1

and R6, and finally R7. Given this order of photoreceptor cell development Rh3 and Rh4 have a

similar onset of expression as do Rh5 and Rh6 (Earl & Britt, 2006; Wernet et al., 2015; Wernet &

Desplan, 2004). Since Rh4 from R8 cells were lost in all previously studied species of

Hippoboscoidae, it is probable that this gene was lost before the bat fly lineage. The lack of

identification of Rh3 and Rh5 in bat flies, though both are found in other species of

Hippoboscoidae, could be attributed to receptor cell loss and, in part, the loss of Rh4 from R8

cells. If R7 and R8 cells fused, evolving from open to closed rhabdoms in bat flies, then loss of

any of Rh3-Rh5 paralogs is a possibility considering their close onset. The loss of these

rhodopsins, Rh3-Rh5, in an aphotic environment implies they are no longer needed in terms of

visual tasks, more specifically in terms of color vision. During the evolution of open to fused

rhabdoms the inner R7 and R8 cells, that are responsible for color vision, could have been lost in

favor of R1-R6 which are responsible for motion detection and image formation. Though there

needs to be more work done in bat flies to ascertain the loss of R7 and R8 cells, the evolutionary

26

microstructural response to aphotic environment pressures is in line with the loss of UV and

SWS opsins.

In addition to looking at developmental progression, another way to assess opsin

functionality is by looking at introns. In Diptera, introns tend to be highly conserved within the

three opsin clades with splice sites phylogenetically conserved across species (Taylor et al.,

2005). This conservation allowed for a comparison of introns across species to identify any

possible functional issues (Chorev & Carmel, 2012). In particular, three splice sites seem to be

conserved across insect short wavelength sensitive (SWS) and long wavelength sensitive (LWS)

groups (Briscoe, 1999; Taylor et al., 2005). Being that both Rh1 and Rh6 are LWS, even if the

introns are varying length, they would be expected to have similar splice sites within the bat fly

lineage. Intron numbers in the LWS Rh1 varied between species, with two present in OW species

and only one in the NW species in comparison to three in Glossina and four in Drosophila

(Figure 2.3). The only large variation in splice site is between the second intron of the

Drosophila species and the first of both Glossina and bat flies. Given Glossina and bat flies are

consistent, this difference could be because of how distant Drosophila is in relation to the other

two species. Intron numbers in the LWS Rh6 were consistent among species with little variation

in splice sites. While automorphies are present in some species, they are seen only in intron

insertions and could be the case for Rh6 if another intron was identified at the beginning of the

variable 3’ sequence. Although many species lack introns for specific rhodopsins, bat flies

contain introns in every opsin gene. It is possible that the intron is in the process of being lost,

which is seen as a pattern in Diptera (Courgeon & Desplan, 2019; Roy & Gilbert, 2005). Even

though an intron is lost, as seen in the NW species Nycterophilia parnelli, the opsin may still

remain functional. In Drosophila, while Rh3 and multiple Rh6 paralogs are intronless, there is

still evidence that all are expressed and functional in both photoreceptors and visual neural

circuits (Courgeon & Desplan, 2019). Introns in pre-cursor mRNA must be spliced precisely in

order for the mRNA to remain functional. The differences in splice sites and positions in what is

usually a highly conserved sequence could cause functional issues, though this cannot be

determined without expression analysis.

27

Summary

The bat fly visual system may have functioning rhodopsins based on analysis of

molecular components in the genomes of both Nycteribiidae and Streblidae species. Given

genome assembly quality and Rh1 and Rh6 phylogenetic clustering among closely related

species in dipteran rhodopsin clades, the rhodopsins identified are real. Functionality of these

opsins may be preliminarily determined via introns and phototransduction cascade genes. While

most genomes were lacking the terminating components of the cascade, all other components

involved in photoactivation and amplification of the rhodopsin signal were identified, though this

pattern of gene absence may signify a deterioration in the functional performance. Another

analysis of functionality - intron comparison - showed a disparity in the splice site of Rh6 when

comparing bat fly LWS opsins to closely related species. Based on phylogenetic reconstructions,

two LWS opsins were found in these bat fly species (Rh1 and Rh6), while Rh2 is expected to

have been lost early in the lineage based on morphology (e.g. loss of ocelli). Neither blue nor

UV-sensitive opsins (Rh3-Rh5) were identified in any of the bat fly genomes investigated. This

loss may be due to environmental constraints or the changes in photoreceptor cells when the

rhabdoms transitioned from open to a fused configuration. Given the calculated BUSCO

statistics, the genomes were properly assembled suggesting the low GC content may be

indicative of mutations and substitutions or a product of the small size of the genome. The

transcriptome level of analysis in the next chapter will help to elucidate the visual function of

these rhodopsins more fully.

28

Table 2.1 Genome specimen collection information. The Old World Nycteribiidae are in grey and

the New World Streblidae are in blue.

Family Genus Species Facet #

Geographic

Range Collection Site

Nycteribiidae Archinycteribia actena 1 OW Greater Sunda Islands

Nycteribiidae Cyclopodia dubia 2 OW Madagascar

Nycteribiidae Eucampsipoda africana 1 OW Kenya

Nycteribiidae Phthiridium hoogstraali 0 OW Kenya

Streblidae Aspidoptera delatorrei 8 NW Belize

Streblidae Nycterophilia parnelli 1 NW Belize

Streblidae Trichobius intermedius 7 to 12* NW Puerto Rico

*Range based facets seen in multiple Trichobius intermedius species

OW = Old World, NW = New World

Table 2.2 Statistics for genome assembly of bat flies using SPAdes, ABySS, Velvet, and BUSCO. OW denotes the Old World

in grey and NW denotes the New World in blue.

Species

Geographic

Range

Genome

Coverage

Genome

Size (Gbp) N50

Kmer

Value Complete Fragmented Missing

GC

Content

Largest

Contig (bp)

Archinycteribia

actena OW 60X 0.133 8982 K74 97.50% 1.10% 1.40% 16.80% 2971818

Cyclopodia

dubia OW 41X 0.308 2460 K66 93.00% 4.10% 2.90% 26.69% 81918

Phthiridium

hoogstraali OW 58X 0.126 19861 K74 98.80% 0.80% 0.40% 29.77% 594335

Nycterophilia

parnelli NW 62X 0.111 24824 K60 97.30% 1.80% 0.90% 35.47% 430720

Trichobius

intermedius NW 59X 0.147 35602 K82 96.80% 1.90% 1.30% 36.14% 512805

29

Table 2.3 Identification of genes involved in the rhabdomeric phototransduction cascade.

Species in green were obtained from MinION reads.

Genus, Species Facet # Rh TRP TRPL PLC Gq PKC Arr RK RdgC

Archinycteribia actena 1 Օ Օ Օ Օ Օ Օ X Օ X

Cyclopodia dubia 2 Օ Օ Օ Օ Օ Օ X Օ X

Eucampsipoda africana 1 Օ X X Օ X Օ X X X

Phthridium hoogstraali 0 Օ Օ Օ Օ Օ Օ X Օ X

Aspidoptera delatorrei 8 Օ Օ Օ Օ X X X X X

Nycterophilia parnelli 1 Օ Օ Օ Օ Օ Օ X Օ Օ

Trichobius intermedius 7 to 12* Օ Օ Օ Օ Օ Օ X Օ Օ

*Range based facets seen in multiple Trichobius intermedius species

Օ = Presence, X = Absence

Rh = rhodopsin, TRP = transient receptor potential, TRPL = TRP-like, PLC = phospholipase C, Gq = Gq

protein, PKC = protein C kinase, Arr = arrestin 1 or 2, RK = receptor kinase 1 or 2, RdgC = retinal

degeneration C

30

31

32

33

Chapter 3: Rhodopsin Expression and Phototransduction Cascade Genes

Introduction:

Loss of complex visual traits including hallmark structural changes (e.g. strongly curved,

thickened lenses, and a closed rhabdom) are prominently seen in cave dwelling (e.g. troglobiont)

and parasitic arthropods (Warrant, 2019). The perpetual darkness in caves coupled with a

parasite's limited need to be mobile leads to both macro-morphologic eye loss and a reduction in

visual genes (Chapter 2) across divergent taxonomic groups. Bat flies (Diptera; Streblidae and

Nycteribiidae), being both parasitic and cave-dwelling arthropods, have a unique set of macro

and micro-morphological features related to vision. Loss at the level of macromorphology is seen

through the numbers of facets within each eye, which is thought to correlate directly with visual

function in arthropods. In bat fly species, facets range from zero (e.g. no eyes) up to 57 facets

largely based on taxonomy and either Old World (OW) or New World (NW) geographic

distributions (Dittmar et al., 2015). At the level of micromorphology, flies typically have

structures found at the center of each ommatidium, called rhabdoms, which consist of eight cells

arranged in an open trapezoidal pattern (Rister & Desplan, 2011; Wernet & Desplan, 2004). In

contrast, based on the one species that has been studied, bat flies have more retinula cells (11-18)

and fused rhabdoms (Porter et al., 2020). Both of these trends are also observed more broadly in

troglobiont species, which tend to have fewer facets of larger sizes and wider or fused rhabdoms

(Greiner, 2006; Greiner et al., 2004; Klaus et al., 2013).

These morphologic trends of reduction and loss in bat flies are paralleled at the molecular

level (Chapter 2). Rhodopsins, or R-type opsins, are proteins in the G-protein coupled receptor

(GPCR) superfamily that are generally expressed in rhabdomeric photoreceptors of arthropods

and molluscs (Lampel et al., 2005; Porter et al., 2012). Multiple rhodopsin paralogs have been

characterized from hippoboscid taxa closely related to the bat flies (Kunz, 2013). The dipteran

rhodopsin phylogeny showed a loss of Rh4 in the superfamily Hippoboscoidea, suggesting that,

as members of this group, bat flies will likely not have this paralog (Feuda et al., 2020). In

addition to this loss, bat flies also lack ocelli, and correspondingly should lack the

ocelli-dependent Rh2 opsin (Rister & Desplan, 2011). Studies of bat fly genomes confirmed the

absence of these two opsin genes, as well as the loss of the UV-sensitive rhodopsins Rh3 and

Rh4, and the blue-sensitive rhodopsin Rh5 (Chapter 2). At the genome level, the loss of

34

rhodopsin paralogs in each bat fly species did not correlate with their facet number, yet visual

function is implied by the lack of nonsense mutations in the remaining gene sequences (Rh1,

Rh6) as well as the presence of phototransduction pathway genes, including Gq proteins that

allow the signal to be transduced and regulatory proteins such as lipase and arrestins, which

terminate the pathway (Chapter 2). There is another trend at the molecular level identified in

Chapter two regarding the number of introns in batfly Rh1 genes in comparison to the closely

related species, Glossina fuscipes. In OW bat fly species the Rh1 gene had two introns, while in

the NW species Nycterophilia parnelli only one was identified (Chapter 2). Considering introns

in Diptera are highly conserved, the loss of an intron or the change in a splice site could cause

issues regarding function. Expression data is key to understanding whether these opsins are still

being transcribed.

The convergence of traits in response to an aphotic environmental pressure is seen in the

macromorphological loss of eyes across a wide taxonomic group of subterranean animals

(Culver, 1982; Wilkens et al., 2000). Considering the processes underlying trait reduction (e.g.

eye and facet size) and augmentation (e.g. wider rhabdoms) seem to be different (e.g. directional

selection and purifying selection) (Klaus et al., 2013; McGaugh et al., 2014; M. E. Protas et al.,

2011; Sondhi et al., 2021), expression levels will vary based on which process is at play. Given

one ommatidium can contain as many as 18 retinula cells (Porter et al., 2020) that each express

opsins, the loss of a whole facet will presumably have a substantial effect on expression levels.

To date, visual function has been determined through transcriptome studies in a number of

publications for subterranean arthropods. Expression patterns are most clearly seen through

comparison of drastic environments of a well-studied freshwater crayfish, with an estimated 450

species, of which approximately 45 are obligate cave-dwellers (Stern et al., 2017).

All bat fly species are parasites that live in dim light and have reduced eyes, but exhibit

variable degrees of reduction and loss between species. In this study I sampled a taxonomically

diverse set of bat fly species with a total number of facets ranging from 0 to 9 among species.

The overall aim of this research was to determine if the opsin paralogs identified in bat fly

genomes were still functional, especially in species that have completely lost eyes, and whether

the identified opsins evolved under selection. Towards this goal, this chapter explores whether

the opsins and phototransduction genes identified in bat fly genomes are expressed, and whether

expression levels correlated to the degree of eye reduction (i.e. facet number). Additionally,

35

expression levels of genes shown to control the fused versus open arrangement of the rhabdom,

including extracellular matrix protein spacemaker (EYS) and Prominin homologs (Mahato et al.,

2018; Zelhof et al., 2006), will be investigated across species to correlate expression with

potential changes in micromorphology. Identification of genes in the phototransduction cascade

and visual opsins, Rh1 and Rh6, from bat fly genomes indicate that their eyes are likely to be

functional (Chapter 2); however, expression data are needed from transcriptomes to verify that

DNA is being transcribed. This study will contribute to our understanding of the process of

reduction in compound eyes through a multi-level analysis of the genome and transcriptome.

Methods and Materials:

Transcriptomes

Transcriptomes were sequenced from three species of Nycteribiidae and five species of

Streblidae (Table 3.1). Opportunistic sampling allowed for sequencing of multiple individuals in

only one Streblidae species, Trichobius johansonae, while all other species had one sample.

Upon collection, individuals were placed in RNAlater and shipped on dry ice before being frozen

at -80 degrees celsius to ensure long-term preservation. RNA from each homogenized individual

was extracted using the Qiagen RNeasy Mini Kit (Qiagen) following manufacturer protocols

including the optional second elution and DNase digestion. RNA quality was preliminarily

determined using a Qubit 3.0 Fluorometer (Thermo Fisher Scientific) high sensitivity solution

and then confirmed via a 2100 Bioanalyzer system (Agilent Technologies). RNA quality showed

an arthropod characteristic collapse of the 28S peak and 18S was used as a proxy for RNA

integrity (DeLeo et al., 2018). Eukaryotic transcriptome libraries were created using rRNA

depletion and sequenced at a Novogene facility (Sacramento, CA, USA) for whole-transcriptome

sequencing using a NovaSeq 6000 S4 platform (Illumina® Inc.), generating 30-32M reads for

each species.

Analyses

For each set of Illumina raw reads, fastQC (v0.11.9, Babraham Bioinformatics) was used

to assess sequence quality scores, sequence length distributions, and adaptor content. Raw reads

were trimmed using Trimmomatic (Bolger et al., 2014) and any sequences under a phred score of

28 were removed. Cleaned reads for each species were assembled into a de novo assembly using

36

Trinity software with built in fastQC (v2.6.6) (Bolger et al., 2014) on the National Center of

Genome Analysis Support’s (NCGAS; Indiana University, Bloomington, IN, USA) Mason Linux

cluster. Default settings were used to remove non-random base pairs added by primers and the

minimum contig base pair length was changed to 300bp. Best quality was determined through a

combination of factors using the Trinity software and QUAST (Gurevich et al., 2013): number of

reads, GC content, N50, and maximum contig length. A second quality check was performed

using BUSCO (v3.0.2)(Simão et al., 2015) with the arthropoda_odb9 lineage using default

settings (Table 3.2). Assemblies that met a similarity threshold in a range (6.2%-92%)

determined by other diptera transcriptomes in the focal BUSCO (Simão et al., 2015) were used

for the rest of the bioinformatics pipeline.

Using Geneious software (Geneious Prime, v2020.0.3), known Rh1-Rh7 fly opsins from

Glossina and Drosophila sequences were used to query assembled transcriptome scaffolds using

tblastn with a max e-value of 1x10＾-5 to identify the top 10 hits for each genome. Hits with a bit

score higher than 100 were then BLAST against the nucleotide collection database in NCBI to

confirm the gene as an opsin, using a max e-value of 1x10＾-10 as a significant match. A single

representative sequence was used in the case of isoforms and any hits that were not opsins were

removed from the dataset. These hits were then confirmed via the assessment of the whole

transcriptome assembly using Phylogenetically Informed Annotation (PIA) in order to identify

any R opsins and phototransduction cascade genes (Speiser et al., 2014). PIA is a tool included

in the Galaxy Bioinformatics Platform with servers based out of the University of California

Santa Barbara (UCSB). In the phototransduction cascade, Gqɑ subunit binds to the

photoactivated opsin and initiates the amplification via downstream components such as

phospholipase C (PLC), protein kinase (PKC), and transient receptor protein (TRP &

TRPL)(Fein & Cavar, 2000; R. C. Hardie, 2001). The termination of this signal by

phosphorylation of rhodopsin and blocking the rhodopsin-Gq interaction is done by retinal

degeneration C (rdgC) and arrestin (Arr or Arr2)(Montell, 2012). The phylogeny created by PIA

using the tab to tree function confirmed all identified genes through the landmarks, which are

genes from model organisms. Queries that landed within the same clade as the rhodopsin

Drosophila melanogaster landmarks, were confirmed as visual opsins. Opsin hits were then

annotated using the Geneious edit feature and transcriptome sequences from closely related

37

Glossina species. Geneious software was also used to search for EYS and prominin via BLAST

and NCBI.

Dipteran opsins that totaled 485 sequences were pulled out of NCBI. All amino acid

sequences from identified opsins in the transcriptomes and genomes with select species from

NCBI were then aligned in Geneious software using MAFFT and used to reconstruct an opsin

tree through CIPRES (Miller et al., 2015) servers using RAxML (Stamatakis, 2014; Stamatakis

et al., 2005) with Onychopsins as an outgroup (Hering et al., 2012). Kallisto on Galaxy was used

under default settings to check expression levels for opsin sequences and a pseudo alignment was

used to quantify the abundance of transcripts from clean reads (Afgan et al., 2018). Reads per

kilobase of transcript per million (TPM) mapped reads were calculated for six out of the eight

transcriptomes where opsins were present using default settings and without normalization

(Mortazavi et al., 2008)(Table 3.3). TPM for Trichobius johansonae was calculated as the mean

of the TPM values from the two sequenced individuals. A heatmap of expression levels in

comparison to facets numbers was made using RStudio (V.1.2.1335). Bowtie (Afgan et al., 2018)

on Galaxy was used to check for Rh6 in Basilia species due to collaborators' unpublished data

identifying Rh6 in a Basilia species (Aradema, pers comm.).

Tests of neutrality were conducted on the patterns of codon substitutions in the protein

coding regions of Rh1 of the bat fly clade using MEGA X (overall average option)(Kumar et al.,

2018; Stecher et al., 2020). The Nei-Gojobori Z-test (Nei & Gojobori, 1986) with 1,000

bootstrapping replicates was used to compare the relative per-site abundance of amino acid

altering (nonsynonymous) and non-altering (synonymous) substitutions.

Results:

Sequencing and de-novo transcriptome assembly was generated for eight bat fly species

for a total of between 20,076 and 53,151 contiguation sequences (contigs) across species (Table

3.2). N50’s for all transcriptomes ranged from 1738 bp to 3115 bp, a normal range for non-model

invertebrates (Riesgo et al., 2012). The average contig length ranged from 1400 to 2276 bp with

GC content from 32.6% to 40.1%. BUSCO, a tool to assess completeness of genomes through

highly conserved single-copy orthologs, scores ranged from 72.2% to 94.3%, with only two

species below 80% among the sequenced species. Those two species, Trichobius corynorhini and

Trichobius sp., had 11% fragmented sequences and 13.6-16.8% missing sequences. Another

38

transcriptome to note, Speiseria ambiqua, had a high percentage of missing sequences ( >10%)

and 8.3% fragmentation (Table 3.2).

Phototransduction pathway components mediated by R opsins and Gqɑ subunits were

identified by the PIA workflow. Through conservative estimates, one Rh1 opsin sequence was

present in six of the eight species (Figure 3.1A). Of the eight species, only two did not have

rhodopsin present, Nycteribia schmidlii and Speiseria ambigua, confirmed through analyses in

PIA, phylogeny, and BLAST (Table 3.3). In addition to not having rhodopsins present, TRP-like

cation channel mediated components were not identified in the N. schmidlii and S. ambigua

transcriptomes. N. schmidlii is also missing Gq subunits from the PIA pathway (Figure 3.2). All

species had TRP channels, phospholipase C (PLC), protein C kinase (PKC), G-protein receptor

kinase 1 or 2 (RK) present. In three of the eight species - Megistopoda aranea, Speiseria

ambigua, and Trichobius corynorhini - signal termination proteins retinal degeneration c and

arrestin 2 were identified. Opsins identified through PIA were found only in the Rh1 rhodopsin

clade of the dipteran opsin phylogeny. All rhodopsins clustered closely in the genomes and

transcriptomes with strong bootstrap values (e.g. > 90%) for each clade (Figure 3.1). All

rhodopsins were identified without stop codons and with hallmarks of a functional opsin at the

sequence level, including the g-protein coupled receptor binding site and a lysine where the

chromatophore attaches. Expression levels of the Rh1 opsin varied among species, with the two

Basilia species and Trichobius johansonae having the lowest TPMs (1.39 - 3.69)(Table 3.3).

Trichobius johansonae’s final TPM was the mean of the two individual sample TPMs for Rh1

(4.12 and 3.25). Two of the transcriptomes did not contain rhodopsin transcripts. The Rh1 in the

final three transcriptomes ranged from 13.4 to 29 TPM (Table 3.3). Rhodopsins were assessed to

have biologically relevant expression levels with a TPM greater than 1. The heatmap (Figure

3.1B) shows expression levels across species in comparison to facet number. The TPM column

has a mean of 8.45 and the facet column has a mean of 3.63 facets with colors based on standard

deviations away from the mean (Figure 3.1B).

Bowtie did not yield any matches for Diptera Rh6 in either Basilia anceps or Basilia sp.

even though it was identified in unpublished genome data from a different Basilia species

(Aradema, pers comm.). Neither the extracellular matrix protein EYS nor prominin were

identified in any of the assembled transcriptomes.

39

The selection analyses of the Rh1 genes in all bat fly species, amounting to 12 nucleotide

sequences and a total of 574 positions, reject neutrality with a probability of dN = dS of 0.00 and a

-4.3025 statistic. The negative statistic indicated more dS, or more synonymous substitutions,

which is consistent with purifying selection removing a subset of amino acid altering mutations

that disrupt the gene product’s function.

Discussion:

This study allows for an interesting look at the intermediary molecular processes

happening in troglobiont species’ vision loss at the transcriptome level. Given that the

transcriptomes are high quality assemblies, opsin functionality can be inferred up to the

transcription level. The expression of the Rh1 opsins indicate further evidence that one rhodopsin

paralog is present and is likely being tuned to the dominant wavelengths in the environment. Rh1

makes up a vast majority (~90%) of the visual pigments in the arthropod compound eye

(Johnson & Pak, 1986; Paulsen, 1984; Salcedo et al., 1999) making it the likely candidate to be

the rhodopsin paralog being tuned to whatever wavelengths are left in the environment. Rh1 is

also structurally significant for the development of rhabdomeres (Wang & Montell, 2007).

Without microvilli arrangement in the retinula cell, photoreceptor structure and ability is lost all

together. Rh6 was not identified in any of the transcriptomes meaning it is not being expressed in

these species, although preliminary data has shown Rh6 is still present in the genome of some

Basilia species (Aradema, pers comm.). Specifically, R opsins have been found to use only Gq

mediated pathways (Fein & Cavar, 2000). The phototransduction cascade is a way to amplify the

response to a single photon of light needing both a rhodopsin and Gq for initiation. N. schmidlii is

a good example of loss, where no rhodopsin paralogs are expressed, verified by a lack of

expression of Rh and Gq in the phototransduction pathway in addition to the expression of fewer

phototransduction genes (Figure 3.2). A similar finding is observed with S. ambigua which has

also lost any opsin expression, though the expression pattern across phototransduction pathway

genes differs (Figure 3.2). In absence of a rhodopsin, it seems the phototransduction pathway is

functioning as if one were identified. This is only feasible if a rhodopsin is present to

photoisomerize in response to a photon of light and activate the channel.

Similar to the identification of phototransduction genes in the genomes (Chapter 2), the

transcriptomes lacked Arr and RdgC expression in most species, although Rh1 is clearly being

40

transcribed. Considering these components are involved in the termination of the cascade this

suggests that the activated rhodopsin signal is repeatedly being amplified (Yau & Hardie, 2009).

The functional implications of this are unknown; it could be that the rhodopsin lifetime in these

species was increased or the opsin was in an intermediary state of decline with a slower recovery

time after the degradation of rhodopsin (Song et al., 2011; Wang & Montell, 2007).

Alternatively, it is also possible that the amount of opsin quenched by arrestin was at

undetectable levels. TPM indicates functional Rh1 opsins in all species in which it was

identified. Comparison through TPM may be skewed because opsins are not only expressed in

photoreceptors, but other tissues with non-visual functions (Terakita, 2005; Velarde et al., 2005).

Another study regarding TPM showed an artificial deflation of all genes outside the top three

expressed when protocols used rRNA depletion (Zhao et al., 2020). Considering opsin

expression is not among the top three genes, this gives a margin of safety when inferring that

expression over one TPM is biologically relevant (Table 3.3).

In order to make accurate inferences regarding biologically relevant expression levels,

sequence verification of opsin functionality is important. Coupled with the clustering of the

identified opsins in the dipteran Rh1 clade (Figure 3.1), the rhodopsin paralogs display certain

conserved sequences and putative phosphorylation sites. There is a conserved indel

(insertion-deletion) among functional arthropod opsins, REQAKKMN, in the the third loop of

the cytoplasmic domain linked to G-protein signaling (Porter et al., 2006). All Rh1 opsins

identified contain this indel except B. anceps, that has Serine (S) instead of Arginine (R) at the

beginning of the indel due to a point mutation in the nucleotide sequence. In addition, all Rh1

opsins contain two conserved motifs, HEK and DRY. The conserved motif HEK found in the

third cytoplasmic loop is involved in an interaction between rhodopsin and the Gq protein

(Gärtner, 2000). The DRY motif found in the third helix of the opsin, is highly conserved in

arthropod GPCRs, and is likely a control site keeping rhodopsin in an inactive conformation

(Palczewski, 2006).

For an eye to remain functional, natural selection should maintain expression levels, with

variations within species being from differences in environmental factors, because it tends to

favor mutations that decrease expression variance (Bedford & Hartl, 2009; Gilad et al., 2006). If

selection is relaxed and is not maintaining functional eyes, then mutations may cause an increase

in expression variance given evidence that random mutations change expression levels (Hinaux

41

et al., 2013; Metzger et al., 2015, 2016; Stern & Crandall, 2018). Theoretically, expression levels

should have little variance in a troglobiont species if the eyes are functional since they are

exposed to the same aphotic environment. Yet, this doesn’t hold true for bat flies and it may not

be because of loss of function. Bat flies are ideal candidates for this study because of their range

of visual loss and intermediary phenotypes. Generally, altered expression patterns in vision

related gene families, pax and hedgehog are clearly important in the reduction of eyes of

cave-dwelling animals (Yamamoto et al., 2004). In a transcriptome-wide expression analysis, one

study found four independent vision loss events with individual expression patterns shown to

cluster by eye function over phylogeny (Gross et al., 2019; Stern & Crandall, 2018). Even

though all sequence-based signatures looked at in this study show function in the data, without

antibody labeling it is not possible to conclude that these transcribed opsin genes are being

translated. Ambylopsid eyeless cave fish appear to have a loss of function in rhodopsin given the

increased rates of nonsynonymous mutations in comparison to their surface cave fish counterpart

(Niemiller et al., 2013).

Yet, bat flies have increased rates of synonymous substitutions indicating strong

purifying selection which has been shown to reduce genetic diversity and has the ability to cause

a transient increase in frequency of mutations (Cvijović et al., 2018). This is consistent with the

lack of stop codons and intron conservation identified in Chapter 2 and with Rh1 transcript

presence in this chapter. Overall, this finding implies that the bat fly Rh1 clade is both functional

and being maintained by purifying selection.

Reduced numbers of facets have clade specific trends; NW species’ facets span the whole

0-57 range while OW species contain three facets at most (Dittmar et al., 2015). The number of

facets is directly correlated to opsin expression levels because of the large number of retinula

cells per facet each expressing rhodopsin. While eye specific augmentation (e.g. fewer facets of

larger sizes which typically have fused rhabdoms - Greiner, 2006; Greiner et al., 2004; Klaus et

al., 2013), also correlates with rhodopsin expression, the effect is relatively reduced. As

described above in Drosophila, R1-R8 cells are arranged in a trapezoidal pattern in each

ommatidium with R7 and R8 cells, responsible for color vision, creating the inner portion (Rister

& Desplan, 2011). R7 expresses the UV-sensitive Rh3 and Rh4 while R8 expresses the Rh5 or

Rh6, blue or green-sensitive respectively (Wernet et al., 2015). Three of these rhodopsin

paralogs, Rh3-Rh5, were not identified in the genome chapter (Chapter 2), leading to the idea

42

that evolution of fused rhabdoms caused a possible loss of the inner R7 and R8 cells. Loss of

EYS expression leads to a fused arrangement, while an open arrangement requires an expression

pattern in photoreceptors in both adult and developmental stages of life (Mahato et al., 2018).

Considering neither EYS nor prominin expression was identified in the transcriptome

assemblies, this suggests that all of the studied bat fly species have closed rhabdoms. This can be

further analyzed in future studies through expression of transcription factors by looking at the

markers prospero, senseless, and spalt during developmental transition from pupal to adult life

stages (Wernet et al., 2015).

Bat flies are an inherently difficult model to work with as there is no way to maintain a

population in a lab and instead require opportunistic sampling. Given this, most species had only

one sample for expression and could have been collected in variable environmental conditions

that may result in light-induced gene expression (Stern & Crandall, 2018). All species but one,

Trichobius johansonae, had only one sample making it difficult to ascertain whether these

expression data are species specific or individual specific. In addition to this, the small, varying

size of the bat fly required RNA extractions to be done using a whole bat fly in lieu of only eye

structures, making comparisons between species relatively difficult. This type of size-constraint

also includes the eye size to body size ratio where larger eyes lead to a higher expression (Wu et

al., 2020). The most important quality metric here is the N50 value (Riesgo et al., 2012)

considering BUSCO scores for 42 arthropod transcriptomes were all lower than the ideal 95%

standard (< 92%) (Simão et al., 2015). Quality transcriptome assessment of assemblies are

important when making conclusions regarding expression.

Summary

At the transcription level, most of the studied bat fly species expressed a verified

rhodopsin paralog (Rh1) with functionality based on identified phosphorylation sites and

conserved regions used in the initial rhodopsin-based interactions of the phototransduction

cascade. Toward the termination of Rh1 signal in the cascade, the loss of RdgC and arrestin in

most species suggests a degradation of rhodopsin and a slower recovery from

photoisomerization. Given this, identified rhodopsins contained biologically relevant expression

levels (>1) assessed through TPM. Though expression levels were variable between each

species, there was a trend directly related to facet number (0-9). The lack of expression levels for

43

EYS and prominin suggests that all of the studied species possessed closed rhabdoms, although

future anatomical studies are needed to confirm this hypothesis. Further functional studies should

use multiple replicates of species to focus on the number of retinula cells in each facet in order to

correlate rhodopsin expression and use antibody labeling to attribute function. Though more

work needs to be done, this study has produced a solid molecular foundation in order to

understand both broader ectoparasite trends and intermediary molecular processes for the

evolution of eye loss through a multi-level analysis of the genome and transcriptome.

44

Table 3.1 Transcriptome specimen collection information. Three Nycteribiidae species arecolored in grey and five Streblidae species are colored in blue.

Family Genus Species Facet #Geographic

Range Collection Site

Nycteribiidae Nycteribia schmidlii 0 OW Kenya

Nycteribiidae Basilia anceps 2 NW Belize

Nycteribiidae Basilia sp 0 to 2* NW Belize

Streblidae Megistopoda aranea 9 NW Belize

Streblidae Speiseria ambigua 9 NW Costa Rica

Streblidae Trichobius corynorhini 6 NW Virgina, USA

Streblidae Trichobius johansonae 1 NW Belize

Streblidae Trichobius sp. Unknown NW Puerto Rico

*Range based on closely related speciesOW = Old World, NW = New World

Table 3.2 Statistics for transcriptome assembly of three Nycteribiidae species in grey and five Streblidae species inblue using Trinity and BUSCO.

SpeciesGeographic

Range

AverageContig

Length (bp) N50 GC Content

LargestContig

(bp) Complete Fragment Missing

Nycteribia schmidlii OW 1656 2127 36.66% 28050 94.30% 2.50% 3.20%

Basilia anceps NW 2078.86 2834 35.99% 18772 91.80% 2.40% 5.80%

Basilia sp. NW 1804.06 2457 35.42% 16621 92.10% 3.40% 4.50%

Megistopoda aranea NW 1956.69 2587 32.60% 15023 88.50% 4.20% 7.30%

Speiseria ambigua NW 1708.01 2238 40.12% 13486 81.30% 8.30% 10.40%

Trichobius corynorhini NW 1400.28 1738 36.47% 14440 72.20% 11.00% 16.80%

Trichobius johansonae NW 2275.65 3115 39.70% 18178 87.30% 2.70% 10.00%

Trichobius sp. NW 1596.5 2042 39.15% 9589 74.90% 11.50% 13.60%

OW = Old World, NW = New World

45

Table 3.3 Identified rhodopsin paralogs with their relativeTPM from Trinity assembled bat fly transcriptomes.

Species Facet # Opsin TPM

Nycteribia schmidlii 0 X NA

Basilia anceps 2 Rh1 1.39372

Basilia sp. 0 to 2* Rh1 2.47739

Megistopoda aranea 9 Rh1 28.9629

Speiseria ambigua 9 X NA

Trichobius corynorhini 6 Rh1 13.3776

Trichobius johansonae 1 Rh1 3.69274

Trichobius sp. Unknown Rh1 22.5069

*Range based on closely related speciesTPM = transcripts per million, X = nothing identified, NA = not

applicable

46

47

48

49

Appendix A: Macro-anatomy & Immunohistochemistry of Paratrichobius longicrus

Preliminary antibody labeling was done in a Paratrichobius longicrus species in the

family Streblidae in order to ascertain the function of rhodopsin at the translational level. The

rhabdom was targeted for G-protein coupled receptors (GPCR) to confirm opsins, DAPI in order

to confirm separate cells via nuclei, and synapses to look at the neuronal network.

Bat flies collected from Belize were preserved in paraformaldehyde (PFA). Bat fly heads

were separated from the thorax and cleared overnight using TDE dilution (10-90%, 97%) and

placed in H2O2 for four hours. Cleared heads were fixed with 4% PFA by creating a small

non-intrusive puncture in the head with a needle. Samples were left in PFA overnight before

starting cryosection preservation 15% sucrose and 30% sucrose each left in 4℃ overnight.

Samples were frozen in tissue embedding material and sectioned at 10 microns and placed on a

slide. P. longicrus was stained with primary antibodies for synapsin (SYN1, A-6442, rabbit host)

and GPCRs (RGS21, SAB1408534, mouse host) at a 1:500 dilution with blocking buffer for at

least 8 hours at 4℃. Secondary antibodies, anti-rabbit 594 and anti-mouse 488, in blocking

buffer at a 1:500 dilution were left for 8 hours at 4℃. Slides were mounted with DAPI prolong

gold and imaged with Leica THUNDER using 405, 488, and 594 channels with a zoom factor

11:1.

P. longicrus THUNDER images identified 24 facets with labeled nuclei in the rhabdom

showing cell structure (Figure A1). This imaging adds to the knowledge regarding degrees of

reduction and specifically, morphology.

50

51

Literature CitedAfgan, E., Baker, D., Batut, B., van den Beek, M., Bouvier, D., Čech, M., Chilton, J., Clements,

D., Coraor, N., Grüning, B. A., Guerler, A., Hillman-Jackson, J., Hiltemann, S., Jalili, V.,

Rasche, H., Soranzo, N., Goecks, J., Taylor, J., Nekrutenko, A., & Blankenberg, D.

(2018). The Galaxy platform for accessible, reproducible and collaborative biomedical

analyses: 2018 update. Nucleic Acids Research, 46(W1), W537–W544.

https://doi.org/10.1093/nar/gky379

Agi, E., Langen, M., Altschuler, S. J., Wu, L. F., Zimmermann, T., & Hiesinger, P. R. (2014). The

Evolution and Development of Neural Superposition. Journal of Neurogenetics, 28(3–4),

216–232. https://doi.org/10.3109/01677063.2014.922557

Bankevich, A., Nurk, S., Antipov, D., Gurevich, A. A., Dvorkin, M., Kulikov, A. S., Lesin, V. M.,

Nikolenko, S. I., Pham, S., Prjibelski, A. D., Pyshkin, A. V., Sirotkin, A. V., Vyahhi, N.,

Tesler, G., Alekseyev, M. A., & Pevzner, P. A. (2012). SPAdes: A New Genome

Assembly Algorithm and Its Applications to Single-Cell Sequencing. Journal of

Computational Biology, 19(5), 455–477. https://doi.org/10.1089/cmb.2012.0021

Bedford, T., & Hartl, D. L. (2009). Optimization of gene expression by natural selection.

Proceedings of the National Academy of Sciences, 106(4), 1133–1138.

https://doi.org/10.1073/pnas.0812009106

Bolger, A. M., Lohse, M., & Usadel, B. (2014). Trimmomatic: A flexible trimmer for Illumina

sequence data. Bioinformatics, 30(15), 2114–2120.

https://doi.org/10.1093/bioinformatics/btu170

Bradnam, K. R., Fass, J. N., Alexandrov, A., Baranay, P., Bechner, M., Birol, I., Boisvert, S.,

Chapman, J. A., Chapuis, G., Chikhi, R., Chitsaz, H., Chou, W.-C., Corbeil, J., Del

Fabbro, C., Docking, T. R., Durbin, R., Earl, D., Emrich, S., Fedotov, P., … Korf, I. F.

(2013). Assemblathon 2: Evaluating de novo methods of genome assembly in three

vertebrate species. GigaScience, 2(1), 10. https://doi.org/10.1186/2047-217X-2-10

52

Briscoe, A. D. (1999). Intron splice sites of Papilio glaucus PglRh3 corroborate insect opsin

phylogeny k. 9.

Chen, H., Sun, S., Norenburg, J. L., & Sundberg, P. (2014). Mutation and Selection Cause

Codon Usage and Bias in Mitochondrial Genomes of Ribbon Worms (Nemertea). PLoS

ONE, 9(1), e85631. https://doi.org/10.1371/journal.pone.0085631

Chorev, M., & Carmel, L. (2012). The Function of Introns. Frontiers in Genetics, 3.

https://doi.org/10.3389/fgene.2012.00055

Cooper, R. L., Li, H., Long, L. Y., Cole, J. L., & Hopper, H. L. (2001). Anatomical comparisons of

neural systems in sighted epigean and troglobitic crayfish species. JOURNAL OF

CRUSTACEAN BIOLOGY, 21(2), 15.

Courgeon, M., & Desplan, C. (2019). Coordination of neural patterning in the Drosophila visual

system. Current Opinion in Neurobiology, 56, 153–159.

https://doi.org/10.1016/j.conb.2019.01.024

Culver, D. C. (1982). Cave Life: Evolution and Ecology. Harvard University Press.

https://doi.org/10.4159/harvard.9780674330214

Cvijović, I., Good, B. H., & Desai, M. M. (2018). The Effect of Strong Purifying Selection on

Genetic Diversity. Genetics, 209(4), 1235–1278.

https://doi.org/10.1534/genetics.118.301058

DeLeo, D. M., Pérez-Moreno, J. L., Vázquez-Miranda, H., & Bracken-Grissom, H. D. (2018).

RNA profile diversity across arthropoda: Guidelines, methodological artifacts, and

expected outcomes. Biology Methods and Protocols, 3(1), bpy012.

https://doi.org/10.1093/biomethods/bpy012

Dick, C. W., & Patterson, B. D. (2006). Bat flies: Obligate ectoparasites of bats. In S. Morand, B.

R. Krasnov, & R. Poulin (Eds.), Micromammals and Macroparasites (pp. 179–194).

Springer Japan. https://doi.org/10.1007/978-4-431-36025-4_11

Dittmar, K., Morse, S. F., Dick, C. W., & Patterson, B. D. (2015). Bat fly evolution from the

53

Eocene to the Present (Hippoboscoidea, Streblidae and Nycteribiidae). In S. Morand, B.

R. Krasnov, & D. T. J. Littlewood (Eds.), Parasite Diversity and Diversification (pp.

246–264). Cambridge University Press. https://doi.org/10.1017/CBO9781139794749.017

Dittmar, K., Porter, M. L., Murray, S., & Whiting, M. F. (2006). Molecular phylogenetic analysis of

nycteribiid and streblid bat flies (Diptera: Brachycera, Calyptratae): Implications for host

associations and phylogeographic origins. Molecular Phylogenetics and Evolution, 38(1),

155–170. https://doi.org/10.1016/j.ympev.2005.06.008

Earl, J. B., & Britt, S. G. (2006). Expression of Drosophila rhodopsins during photoreceptor cell

differentiation: Insights into R7 and R8 cell subtype commitment. Gene Expression

Patterns, 6(7), 687–694. https://doi.org/10.1016/j.modgep.2006.01.003

Fein, A., & Cavar, S. (2000). Divergent mechanisms for phototransduction of invertebrate

microvillar photoreceptors. Visual Neuroscience, 17(6), 911–917.

https://doi.org/10.1017/S0952523800176102

Feuda, R., Goulty, M., Zadra, N., Gasparetti, T., Rosato, E., Segata, N., Rizzoli, A., Pisani, D.,

Ometto, L., & Stabelli, O. R. (2020). The diverging evolutionary history of opsin genes in

Diptera [Preprint]. Evolutionary Biology. https://doi.org/10.1101/2020.06.29.177931

Foerstner, K. U., von Mering, C., Hooper, S. D., & Bork, P. (2005). Environments shape the

nucleotide composition of genomes. EMBO Reports, 6(12), 1208–1213.

https://doi.org/10.1038/sj.embor.7400538

Gärtner, W. (2000). Invertebrate visual pigments. In Handbook of Biological Physics (Vol. 3, pp.

297–388). Elsevier. https://doi.org/10.1016/S1383-8121(00)80010-X

Gilad, Y., Oshlack, A., & Rifkin, S. A. (2006). Natural selection on gene expression. Trends in

Genetics, 22(8), 456–461. https://doi.org/10.1016/j.tig.2006.06.002

Greiner, B. (2006). Visual adaptations in the night-active waspApoica pallens. The Journal of

Comparative Neurology, 495(3), 255–262. https://doi.org/10.1002/cne.20882

Greiner, B., Ribi, W. A., & Warrant, E. J. (2004). Retinal and optical adaptations for nocturnal

54

vision in the halictid bee Megalopta genalis. Cell and Tissue Research, 316(3), 377–390.

https://doi.org/10.1007/s00441-004-0883-9

Gross, J. B., Sun, D. A., Carlson, B. M., Brodo-Abo, S., & Protas, M. E. (2019). Developmental

transcriptomic analysis of the cave-dwelling crustacean, Asellus aquaticus [Preprint].

Genetics. https://doi.org/10.1101/845990

Gurevich, A., Saveliev, V., Vyahhi, N., & Tesler, G. (2013). QUAST: Quality assessment tool for

genome assemblies. Bioinformatics, 29(8), 1072–1075.

https://doi.org/10.1093/bioinformatics/btt086

Hardie, R. C. (2001). Phototransduction in Drosophila melanogaster. Journal of Experimental

Biology, 204(20), 3403–3409. https://doi.org/10.1242/jeb.204.20.3403

Hardie, R., Vogt, K., & Rudolph, A. (1989). The compound eye of the tsetse fly (Glossina

morsitans morsitans and Glossina palpalis palpalis). Journal of Insect Physiology, 35(5),

423–431. https://doi.org/10.1016/0022-1910(89)90117-0

Hering, L., Henze, M. J., Kohler, M., Kelber, A., Bleidorn, C., Leschke, M., Nickel, B., Meyer, M.,

Kircher, M., Sunnucks, P., & Mayer, G. (2012). Opsins in Onychophora (Velvet Worms)

Suggest a Single Origin and Subsequent Diversification of Visual Pigments in

Arthropods. Molecular Biology and Evolution, 29(11), 3451–3458.

https://doi.org/10.1093/molbev/mss148

Hershberg, R. (2016). Codon Usage and Translational Selection. In Encyclopedia of

Evolutionary Biology (pp. 293–298). Elsevier.

https://doi.org/10.1016/B978-0-12-800049-6.00178-5

Hinaux, H., Poulain, J., Da Silva, C., Noirot, C., Jeffery, W. R., Casane, D., & Rétaux, S. (2013).

De Novo Sequencing of Astyanax mexicanus Surface Fish and Pachón Cavefish

Transcriptomes Reveals Enrichment of Mutations in Cavefish Putative Eye Genes. PLoS

ONE, 8(1), e53553. https://doi.org/10.1371/journal.pone.0053553

Jackman, S. D., Vandervalk, B. P., Mohamadi, H., Chu, J., Yeo, S., Hammond, S. A., Jahesh,

55

G., Khan, H., Coombe, L., Warren, R. L., & Birol, I. (2017). ABySS 2.0:

Resource-efficient assembly of large genomes using a Bloom filter. Genome Research,

27(5), 768–777. https://doi.org/10.1101/gr.214346.116

Jander, U., & Jander, R. (2002). Allometry and resolution of bee eyes (Apoidea). Arthropod

Structure & Development, 30(3), 179–193.

https://doi.org/10.1016/S1467-8039(01)00035-4

Jeffery, W., & Strickler, A. (2010). Development as an Evolutionary Process in Astyanax

Cavefish. In E. Trajano, M. Bichuette, & B. Kapoor (Eds.), Biology of Subterranean

Fishes (pp. 141–168). Science Publishers. https://doi.org/10.1201/EBK1578086702-c6

Jobling, B. (1926). A Comparative Study of the Structure of the Head and Mouth Parts in the

Hippoboscidae (Diptera Pupipara). Parasitology, 18(3), 319–349.

https://doi.org/10.1017/S003118200000528X

Johnson, E. C., & Pak, W. L. (1986). Electrophysiological study of Drosophila rhodopsin

mutants. Journal of General Physiology, 88(5), 651–673.

https://doi.org/10.1085/jgp.88.5.651

Keene, A. C., Yoshizawa, M., & McGaugh, S. E. (Eds.). (2016). Biology and evolution of the

Mexican cavefish. Academic Press/Elsevier.

Kelber, A. (2003). Colour Vision in Diurnal and Nocturnal Hawkmoths. Integrative and

Comparative Biology, 43(4), 571–579. https://doi.org/10.1093/icb/43.4.571

Klaus, S., Mendoza, J. C. E., Liew, J. H., Plath, M., Meier, R., & Yeo, D. C. J. (2013). Rapid

evolution of troglomorphic characters suggests selection rather than neutral mutation as

a driver of eye reduction in cave crabs. Biology Letters, 9(2), 20121098.

https://doi.org/10.1098/rsbl.2012.1098

Koyanagi, M., Nagata, T., Katoh, K., Yamashita, S., & Tokunaga, F. (2008). Molecular Evolution

of Arthropod Color Vision Deduced from Multiple Opsin Genes of Jumping Spiders.

Journal of Molecular Evolution, 66(2), 130–137.

56

https://doi.org/10.1007/s00239-008-9065-9

Krishnan, J., & Rohner, N. (2017). Cavefish and the basis for eye loss. Philosophical

Transactions of the Royal Society B: Biological Sciences, 372(1713), 20150487.

https://doi.org/10.1098/rstb.2015.0487

Kumar, S., Stecher, G., Li, M., Knyaz, C., & Tamura, K. (2018). MEGA X: Molecular Evolutionary

Genetics Analysis across Computing Platforms. Molecular Biology and Evolution, 35(6),

1547–1549. https://doi.org/10.1093/molbev/msy096

Kunz, T. H. (2013). Ecology of Bats. Springer.

https://public.ebookcentral.proquest.com/choice/publicfullrecord.aspx?p=5588034

Kutty, S. N., Pape, T., Wiegmann, B. M., & Meier, R. (2010). Molecular phylogeny of the

Calyptratae (Diptera: Cyclorrhapha) with an emphasis on the superfamily Oestroidea

and the position of Mystacinobiidae and McAlpine’s fly. Systematic Entomology, 35(4),

614–635. https://doi.org/10.1111/j.1365-3113.2010.00536.x

Lampel, J., Briscoe, A. D., & Wasserthal, L. T. (2005). Expression of UV-, blue-,

long-wavelength-sensitive opsins and melatonin in extraretinal photoreceptors of the

optic lobes of hawkmoths. Cell and Tissue Research, 321(3), 443–458.

https://doi.org/10.1007/s00441-004-1069-1

Land, M. F. (1997). VISUAL ACUITY IN INSECTS. Annual Review of Entomology, 42(1),

147–177. https://doi.org/10.1146/annurev.ento.42.1.147

Land, M. F. (2005). The optical structures of animal eyes. Current Biology, 15(9), R319–R323.

https://doi.org/10.1016/j.cub.2005.04.041

Land, M. F., Gibson, G., Horwood, J., & Zeil, J. (1999). Fundamental differences in the optical

structure of the eyes of nocturnal and diurnal mosquitoes. Journal of Comparative

Physiology A: Sensory, Neural, and Behavioral Physiology, 185(1), 91–103.

https://doi.org/10.1007/s003590050369

Lunau, K. (2014). Visual ecology of flies with particular reference to colour vision and colour

57

preferences. Journal of Comparative Physiology A, 200(6), 497–512.

https://doi.org/10.1007/s00359-014-0895-1

Mahato, S., Nie, J., Plachetzki, D. C., & Zelhof, A. C. (2018). A mosaic of independent

innovations involving eyes shut are critical for the evolutionary transition from fused to

open rhabdoms. Developmental Biology, 443(2), 188–202.

https://doi.org/10.1016/j.ydbio.2018.09.016

Marshall, A. G. (1981). The ecology of ectoparasitic insects. Academic Press.

Marshall, A. G. (1982). Ecology of Insects Ectoparasitic on Bats. In T. H. Kunz (Ed.), Ecology of

Bats (pp. 369–401). Springer US. https://doi.org/10.1007/978-1-4613-3421-7_10

Mayberry, J. R. (2014). Through the Eyes of Bat Flies. 162.

McGaugh, S. E., Gross, J. B., Aken, B., Blin, M., Borowsky, R., Chalopin, D., Hinaux, H., Jeffery,

W. R., Keene, A., Ma, L., Minx, P., Murphy, D., O’Quin, K. E., Rétaux, S., Rohner, N.,

Searle, S. M. J., Stahl, B. A., Tabin, C., Volff, J.-N., … Warren, W. C. (2014). The

cavefish genome reveals candidate genes for eye loss. Nature Communications, 5(1),

5307. https://doi.org/10.1038/ncomms6307

Mejía-Ortíz, L., & Hartnoll, R. (2006). A new use for useless eyes in cave crustaceans.

Crustaceana, 79(5), 593–600. https://doi.org/10.1163/156854006777584313

Mejía-Ortíz, L. M., & Hartnoll, R. G. (2005). Modifications of Eye Structure and Integumental

Pigment in Two Cave Crayfish. Journal of Crustacean Biology, 25(3), 480–487.

https://doi.org/10.1651/C-2569

Metzger, B. P. H., Duveau, F., Yuan, D. C., Tryban, S., Yang, B., & Wittkopp, P. J. (2016).

Contrasting Frequencies and Effects of cis—And trans -Regulatory Mutations Affecting

Gene Expression. Molecular Biology and Evolution, 33(5), 1131–1146.

https://doi.org/10.1093/molbev/msw011

Metzger, B. P. H., Yuan, D. C., Gruber, J. D., Duveau, F., & Wittkopp, P. J. (2015). Selection on

noise constrains variation in a eukaryotic promoter. Nature, 521(7552), 344–347.

58

https://doi.org/10.1038/nature14244

Miller, M. A., Schwartz, T., Pickett, B. E., He, S., Klem, E. B., Scheuermann, R. H., Passarotti,

M., Kaufman, S., & O’Leary, M. A. (2015). A RESTful API for Access to Phylogenetic

Tools via the CIPRES Science Gateway. Evolutionary Bioinformatics, 11, EBO.S21501.

https://doi.org/10.4137/EBO.S21501

Mizuno, M., & Kanehisa, M. (1994). Distribution profiles of GC content around the translation

initiation site in different species. FEBS Letters, 352(1), 7–10.

https://doi.org/10.1016/0014-5793(94)00898-1

Montell, C. (2012). Drosophila visual transduction. Trends in Neurosciences, 35(6), 356–363.

https://doi.org/10.1016/j.tins.2012.03.004

Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008). Mapping and

quantifying mammalian transcriptomes by RNA-Seq. Nature Methods, 5(7), 621–628.

https://doi.org/10.1038/nmeth.1226

Nei, M., & Gojobori, T. (1986). Simple methods for estimating the numbers of synonymous and

nonsynonymous nucleotide substitutions. Molecular Biology and Evolution, 3(5),

418–426. https://doi.org/10.1093/oxfordjournals.molbev.a040410

Niemiller, M. L., Fitzpatrick, B. M., Shah, P., Schmitz, L., & Near, T. J. (2013). Evidence for

repeated loss of selective constraint in rhodopsin of Amblyopsidae cavefishes (Teleostei:

Amblyopsidae): Loss of function in rhodopsin of cavefishes. Evolution, 67(3), 732–748.

https://doi.org/10.1111/j.1558-5646.2012.01822.x

Nilsson, D.-E., & Kelber, A. (2007). A functional analysis of compound eye evolution. Arthropod

Structure & Development, 36(4), 373–385. https://doi.org/10.1016/j.asd.2007.07.003

Osorio, D. (2007). Spam and the evolution of the fly’s eye. BioEssays, 29(2), 111–115.

https://doi.org/10.1002/bies.20533

Palczewski, K. (2006). G Protein–Coupled Receptor Rhodopsin. Annual Review of

Biochemistry, 75(1), 743–767.

59

https://doi.org/10.1146/annurev.biochem.75.103004.142743

Paulsen, R. (1984). Spectral characteristics of isolated blowfly rhabdoms. Journal of

Comparative Physiology A, 155(1), 47–55. https://doi.org/10.1007/BF00610930

Porter, M. L., Blasic, J. R., Bok, M. J., Cameron, E. G., Pringle, T., Cronin, T. W., & Robinson, P.

R. (2012). Shedding new light on opsin evolution. Proceedings of the Royal Society B:

Biological Sciences, 279(1726), 3–14. https://doi.org/10.1098/rspb.2011.1819

Porter, M. L., Cronin, T. W., Dick, C. W., Simon, N., & Dittmar, K. (2020). Visual system

characterization of the obligate bat ectoparasite Trichobius frequens (Diptera:

Streblidae). Arthropod Structure & Development, 101007.

https://doi.org/10.1016/j.asd.2020.101007

Porter, M. L., Cronin, T. W., McClellan, D. A., & Crandall, K. A. (2006). Molecular

Characterization of Crustacean Visual Pigments and the Evolution of Pancrustacean

Opsins. Molecular Biology and Evolution, 24(1), 253–268.

https://doi.org/10.1093/molbev/msl152

Protas, M., Conrad, M., Gross, J. B., Tabin, C., & Borowsky, R. (2007). Regressive Evolution in

the Mexican Cave Tetra, Astyanax mexicanus. Current Biology, 17(5), 452–454.

https://doi.org/10.1016/j.cub.2007.01.051

Protas, M. E., Trontelj, P., & Patel, N. H. (2011). Genetic basis of eye and pigment loss in the

cave crustacean, Asellus aquaticus. Proceedings of the National Academy of Sciences,

108(14), 5702–5707. https://doi.org/10.1073/pnas.1013850108

Re, C., Fišer, Ž., Perez, J., Tacdol, A., Trontelj, P., & Protas, M. E. (2018). Common Genetic

Basis of Eye and Pigment Loss in Two Distinct Cave Populations of the Isopod

Crustacean Asellus aquaticus. Integrative and Comparative Biology, 58(3), 421–430.

https://doi.org/10.1093/icb/icy028

Riesgo, A., Andrade, S. C. S., Sharma, P. P., Novo, M., Pérez-Porro, A. R., Vahtera, V.,

González, V. L., Kawauchi, G. Y., & Giribet, G. (2012). Comparative description of ten

60

transcriptomes of newly sequenced invertebrates and efficiency estimation of genomic

sampling in non-model taxa. Frontiers in Zoology, 9(1), 33.

https://doi.org/10.1186/1742-9994-9-33

Rister, J., & Desplan, C. (2011). The retinal mosaics of opsin expression in invertebrates and

vertebrates. Developmental Neurobiology, 71(12), 1212–1226.

https://doi.org/10.1002/dneu.20905

Rocha, E. P. C., & Danchin, A. (2002). Base composition bias might result from competition for

metabolic resources. Trends in Genetics, 18(6), 291–294.

https://doi.org/10.1016/S0168-9525(02)02690-2

Romhányi, G., & Molnar, L. (1974). Optical polarisation indicates linear arrangement of

rhodopsin oligosaccharide chain in rod disk membranes of frog retina. Nature,

249(5456), 486–488. https://doi.org/10.1038/249486a0

Roy, S. W., & Gilbert, W. (2005). The pattern of intron loss. Proceedings of the National

Academy of Sciences, 102(3), 713–718. https://doi.org/10.1073/pnas.0408274102

Sakai, K., Tsutsui, K., Yamashita, T., Iwabe, N., Takahashi, K., Wada, A., & Shichida, Y. (2017).

Drosophila melanogaster rhodopsin Rh7 is a UV-to-visible light sensor with an

extraordinarily broad absorption spectrum. Scientific Reports, 7(1), 7349.

https://doi.org/10.1038/s41598-017-07461-9

Salcedo, E., Huber, A., Henrich, S., Chadwell, L. V., Chou, W.-H., Paulsen, R., & Britt, S. G.

(1999). Blue- and Green-Absorbing Visual Pigments of Drosophila: Ectopic Expression

and Physiological Characterization of the R8 Photoreceptor Cell-Specific Rh5 and Rh6

Rhodopsins. The Journal of Neuroscience, 19(24), 10716–10726.

https://doi.org/10.1523/JNEUROSCI.19-24-10716.1999

Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V., & Zdobnov, E. M. (2015).

BUSCO: Assessing genome assembly and annotation completeness with single-copy

orthologs. Bioinformatics, 31(19), 3210–3212.

61

https://doi.org/10.1093/bioinformatics/btv351

Sondhi, Y., Ellis, E. A., Bybee, S. M., Theobald, J. C., & Kawahara, A. Y. (2021). Light

environment drives evolution of color vision genes in butterflies and moths.

Communications Biology, 4(1), 177. https://doi.org/10.1038/s42003-021-01688-z

Song, X., Vishnivetskiy, S. A., Seo, J., Chen, J., Gurevich, E. V., & Gurevich, V. V. (2011).

Arrestin-1 expression level in rods: Balancing functional performance and photoreceptor

health. Neuroscience, 174, 37–49. https://doi.org/10.1016/j.neuroscience.2010.11.009

Spaethe, J. (2004). Early Duplication and Functional Diversification of the Opsin Gene Family in

Insects. Molecular Biology and Evolution, 21(8), 1583–1594.

https://doi.org/10.1093/molbev/msh162

Speiser, D. I., Pankey, M. S., Zaharoff, A. K., Battelle, B. A., Bracken-Grissom, H. D., Breinholt,

J. W., Bybee, S. M., Cronin, T. W., Garm, A., Lindgren, A. R., Patel, N. H., Porter, M. L.,

Protas, M. E., Rivera, A. S., Serb, J. M., Zigler, K. S., Crandall, K. A., & Oakley, T. H.

(2014). Using phylogenetically-informed annotation (PIA) to search for light-interacting

genes in transcriptomes from non-model organisms. BMC Bioinformatics, 15(1), 350.

https://doi.org/10.1186/s12859-014-0350-x

Stamatakis, A. (2014). RAxML version 8: A tool for phylogenetic analysis and post-analysis of

large phylogenies. Bioinformatics, 30(9), 1312–1313.

https://doi.org/10.1093/bioinformatics/btu033

Stamatakis, A., Ludwig, T., & Meier, H. (2005). RAxML-III: A fast program for maximum

likelihood-based inference of large phylogenetic trees. Bioinformatics, 21(4), 456–463.

https://doi.org/10.1093/bioinformatics/bti191

Stecher, G., Tamura, K., & Kumar, S. (2020). Molecular Evolutionary Genetics Analysis (MEGA)

for macOS. Molecular Biology and Evolution, 37(4), 1237–1239.

https://doi.org/10.1093/molbev/msz312

Stern, D. B., Breinholt, J., Pedraza‐Lara, C., López‐Mejía, M., Owen, C. L., Bracken‐Grissom,

62

H., Fetzner, J. W., & Crandall, K. A. (2017). Phylogenetic evidence from freshwater

crayfishes that cave adaptation is not an evolutionary dead‐end. Evolution, 71(10),

2522–2532. https://doi.org/10.1111/evo.13326

Stern, D. B., & Crandall, K. A. (2018). The Evolution of Gene Expression Underlying Vision Loss

in Cave Animals. Molecular Biology and Evolution, 35(8), 2005–2014.

https://doi.org/10.1093/molbev/msy106

Sukontason, K. L., Chaiwong, T., Piangjai, S., Upakut, S., Moophayak, K., & Sukontason, K.

(2008). Ommatidia of blow fly, house fly, and flesh fly: Implication of their vision

efficiency. Parasitology Research, 103(1), 123–131.

https://doi.org/10.1007/s00436-008-0939-y

Taylor, S. D., de la Cruz, K. D., Porter, M. L., & Whiting, M. F. (2005). Characterization of the

Long-Wavelength Opsin from Mecoptera and Siphonaptera: Does a Flea See?

Molecular Biology and Evolution, 22(5), 1165–1174.

https://doi.org/10.1093/molbev/msi110

Terakita, A. (2005). The opsins. Genome Biology, 6(3), 213.

https://doi.org/10.1186/gb-2005-6-3-213

Tierney, S. M., Cooper, S. J. B., Saint, K. M., Bertozzi, T., Hyde, J., Humphreys, W. F., & Austin,

A. D. (2015). Opsin transcripts of predatory diving beetles: A comparison of surface and

subterranean photic niches. Royal Society Open Science, 2(1), 140386.

https://doi.org/10.1098/rsos.140386

Velarde, R. A., Sauer, C. D., O. Walden, K. K., Fahrbach, S. E., & Robertson, H. M. (2005).

Pteropsin: A vertebrate-like non-visual opsin expressed in the honey bee brain. Insect

Biochemistry and Molecular Biology, 35(12), 1367–1377.

https://doi.org/10.1016/j.ibmb.2005.09.001

Wakakuwa, M., Terakita, A., Koyanagi, M., Stavenga, D. G., Shichida, Y., & Arikawa, K. (2010).

Evolution and Mechanism of Spectral Tuning of Blue-Absorbing Visual Pigments in

63

Butterflies. PLoS ONE, 5(11), e15015. https://doi.org/10.1371/journal.pone.0015015

Wang, T., & Montell, C. (2007). Phototransduction and retinal degeneration in Drosophila.

Pflügers Archiv - European Journal of Physiology, 454(5), 821–847.

https://doi.org/10.1007/s00424-007-0251-1

Warrant, E. (2019). Invertebrate Vision. In Encyclopedia of Animal Behavior (pp. 64–79).

Elsevier. https://doi.org/10.1016/B978-0-12-809633-8.01303-0

Wenzel, R. L. (1975). The streblid batflies of Venezuela (Diptera: Streblidae). Brigham Young

University Science Bulletin., 20, 1–177. https://doi.org/10.5962/bhl.part.5666

Wernet, M. F., & Desplan, C. (2004). Building a retinal mosaic: Cell-fate decision in the fly eye.

Trends in Cell Biology, 14(10), 576–584. https://doi.org/10.1016/j.tcb.2004.09.007

Wernet, M. F., Perry, M. W., & Desplan, C. (2015). The evolutionary diversity of insect retinal

mosaics: Common design principles and emerging molecular logic. Trends in Genetics,

31(6), 316–328. https://doi.org/10.1016/j.tig.2015.04.006

Wilkens, H., Culver, D. C., & Humphreys, W. F. (Eds.). (2000). Subterranean ecosystems (1st

ed). Elsevier.

Wolken, J. J., Capenos, J., & Turano, A. (1957). PHOTORECEPTOR STRUCTURES. The

Journal of Biophysical and Biochemical Cytology, 3(3), 441–448.

https://doi.org/10.1083/jcb.3.3.441

Wu, M., Bao, R., & Friedrich, M. (2020). Evolutionary conservation of opsin gene expression

patterns in the compound eyes of darkling beetles. Development Genes and Evolution,

230(5–6), 339–345. https://doi.org/10.1007/s00427-020-00669-2

Yamamoto, Y., Stock, D. W., & Jeffery, W. R. (2004). Hedgehog signalling controls eye

degeneration in blind cavefish. Nature, 431(7010), 844–847.

https://doi.org/10.1038/nature02864

Yang, J., Chen, X., Bai, J., Fang, D., Qiu, Y., Jiang, W., Yuan, H., Bian, C., Lu, J., He, S., Pan,

X., Zhang, Y., Wang, X., You, X., Wang, Y., Sun, Y., Mao, D., Liu, Y., Fan, G., … Shi, Q.

64

(2016). The Sinocyclocheilus cavefish genome provides insights into cave adaptation.

BMC Biology, 14(1), 1. https://doi.org/10.1186/s12915-015-0223-4

Yau, K.-W., & Hardie, R. C. (2009). Phototransduction Motifs and Variations. Cell, 139(2),

246–264. https://doi.org/10.1016/j.cell.2009.09.029

Zelhof, A. C., Hardy, R. W., Becker, A., & Zuker, C. S. (2006). Transforming the architecture of

compound eyes. Nature, 443(7112), 696–699. https://doi.org/10.1038/nature05128

Zerbino, D. R., & Birney, E. (2008). Velvet: Algorithms for de novo short read assembly using de

Bruijn graphs. Genome Research, 18(5), 821–829. https://doi.org/10.1101/gr.074492.107

Zhao, S., Ye, Z., & Stanton, R. (2020). Misuse of RPKM or TPM normalization when comparing

across samples and sequencing protocols. RNA, 26(8), 903–909.

https://doi.org/10.1261/rna.074922.120

Zuker, C. S., Cowman, A. F., & Rubin, G. M. (1985). Isolation and structure of a rhodopsin gene

from D. melanogaster. Cell, 40(4), 851–858.

https://doi.org/10.1016/0092-8674(85)90344-7

65