Hertweck Monocots V Presentation

Estimation of divergence times in Asparagales in the presence of hybridization

Kate L. Hertweck, Michael R. McKain

Monocots V

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Objectives

1) Describing lynchpins of monocot evolution

2) Informing Asparagales divergence times with lessons from monocots

3) Applications of dating estimates

What are the most important considerations in determining the context of diversification in monocots?

K. Hertweck, NESCent, Asparagales divergence 1. Monocots 2. Asparagales 3. Applications

Kate L. Hertweck, Michael S. Kinney, Sarah Mathews, Mark W. Chase, M. A. Gandolfo, J. Chris Pires

Divergence time estimation in monocots

● Improved Chase et al. (2006) dataset with 8 genes (11459 bp)● 1 mt, 4 cp, 2 nrDNA, 1 LCNG (PHYC)● 151 total taxa (27 outgroup, including 10 eudicots)● MUSCLE, RAxML/MrBayes (partitioned, GTRGAMMA) ● r8s (13 fossil constraints), PL (TN) with cross validation, BEAST

● Does a dataset representing all three genomic partitions accurately reconstruct evolutionary relationships?

● Can we improve divergence time estimations in monocots using comprehensive taxon sampling?


Fossil calibrations for Asparagales

constraint Age (Ma) taxon

1 CG angiosperms 110.4 (Early-Middle Albian) Carpestella lacunata

2 SL Nymphaeales 110.4 (Early-Middle Albian) Microvictoria svitkoana

3 SL Schisandraceae 89.3 (Cenomanian-Turonian) Illiciospermum pusillum

4 SL Chloranthaceae 130 (Hauterivian, Helez Fm.) Clavatipollenites minutus

5 SL Magnoliales 112 (Late Aptian) Endressinia brasiliana

6 SL Calycanthaceae 118.5 (Late Barremian-Early Aptian) Jerseyanthus calycanthoides

7 SL Lactoridaceae 70.6 (Early Turonian-Campanian) Lactoripollenites africanus

8 CG eudicots 99.6 (Late Albian) Spanomera marylandensis

9 SL Araceae 118.5 (Late Barremain-Early Aptian) Cobbania corrugata

10 CG Pandanales 89.3 (Turonian) Mabelia, Nuhliantha

11 SL Arecales 70.6 (Campanian) Sabalites magothiensis,Palmoxylon cliffwoodensis

12 SL Zingiberales 72.5 (Campanian, absolute age) Tricostatocarpon silvapinedae,Striatornata sanantoniensis

13 SL Poaceae 65.5 (Maastrichtian) phytoliths

(Gandolfo, pers. comm.)

K. Hertweck, NESCent, Asparagales divergence 1. Challenges 2. Data 3. Applications

Monocot timetree

Single data partitions fail to reconstruct deep relationships

Combined dataset yields high confidence at most nodes (except commelinids)


Monocot timetree: Maxage of angiosperms at 170 Ma

Outgroups constrained for proper fossil placement

Confidence intervals:Maxage of angiosperms=200 and 150 Ma

CG monocots: 153 Ma (134-127)


Lynchpins in monocot divergence time estimation

● Taxonomic sampling

● Even sampling across lineages● Represent early diverging taxa in each lineage● Sample lineages which are both species rich and poor● Select optimal lineages for fossil calibrations




● Molecular sequence sampling

● Combining data partitions more reliably estimates phylogeny, although constraining topology may still be necessary

● Variation in life history may affect rates of molecular evolution

● Multiple independent data partitions may smooth rate variation in individual genes





● Fossil calibrations

● Incongruence between molecular and fossil dates for divergence

● Most variation in divergence time estimation comes from implementation of fossil calibrations

● Calibrations at shallow nodes can be influential





● Fossil calibrations

● Some lynchpins are exacerbated in Asparagales

● What lessons learned from dating monocots can assist in improving divergence time estimates in Asparagales?


Objectives




How can studies in monocots improve divergence time estimates in Asparagales?


Basic Asparagales divergence times


Monocot 8 gene dataset (Hertweck et al., unpub.)

CG Asparagales: 113 Ma (125-105)

CG “Core” Asparagales: 61 Ma (67-58)CG Asparagaceae: 52 Ma (58-49)CG Amaryllidaceae: 50 Ma (55-47)CG Xanthorrhoeaceae: 47 Ma (52-44)

Broad taxonomic divergence time analyses(Janssen and Bremer 2004, Magallon and Castillo 2009, Bell et al. 2010)CG Asparagales: 92-127 my

Datasets:Chen et al. 2013: many taxa, 4 cpDNA lociSeberg et al. 2013: many taxa, 3 cpDNA and 2 mtDNA loci* McKain plastome: some taxa, complete plastomes* McKain orthologs: fewer taxa, 19 nuclear orthologs

Lynchpin 1: Taxonomic sampling in Asparagales

Chen S, Kim D-K, Chase MW, Kim J-H (2013) Networks in a Large-Scale Phylogenetic Analysis: Reconstructing Evolutionary History of Asparagales (Lilianae) Based on Four Plastid Genes. PLoS ONE 8(3): e59472. doi:10.1371/journal.pone.0059472http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059472


● Chen et al. 2013: ● 253 species, 201 genera, all families in Asparagales● 29 species from monocot outgroups● Three calibrations: CG Asparagales and two outgroups

Effect of many taxa


Monocot 8 gene Chen BEAST

CG Asparagales 113 Ma (125-105) 93 Ma (101-93)

CG “Core” Asparagales 61 Ma (67-58) 63 Ma (75-53)

CG Asparagaceae 52 Ma (58-49) 56 Ma (65-48)

CG Amaryllidaceae 50 Ma (55-47) 51 Ma (62-42)

CG Xanthorrhoeaceae 47 Ma (52-44) 56 Ma (66-48)

More taxa increases accuracy of dating estimates?

• Variation in genome size• Karyotype (chromosome structure, bimodality)• Polyploidy (auto-, allo-, aneu- ploidy)• Hybridization (and other historically confounding

evolutionary events)

How do these genomic phenomena affect our ability to reconstruct phylogeny and other evolutionary patterns?

Lynchpin 2: Molecular sequence sampling


Application of nuclear data to divergence time estimates

• ITS

• Low copy nuclear genes

• Transcriptomes

• PHYTOCHROME C (PHYC)– Well characterized; red/far red light sensing

– Single copy in almost all groups studied; orthology established– Phylogenetically informative

– Degenerate primers in exon 1 of PHYC (Mathews et al., 1995)


PHYC reconstructs relationships between families


Intrafamilial relationships from PHYC are messy

Androstephium (Brodiaeoideae)Brodiaea (Brodiaeoideae)Drimia (Scilloideae)Dianella (Hemerocallidoideae)Geitonoplesium (Hemerocallidoideae)Arthropodium (Laxmanniaceae)


Intrafamilial relationships from PHYC are messy

Androstephium (Brodiaeoideae)Brodiaea (Brodiaeoideae)Drimia (Scilloideae)Dianella (Hemerocallidoideae)Geitonoplesium (Hemerocallidoideae)Arthropodium (Laxmanniaceae)


• Hybridization and other types of reticulate networks may require a different approach to divergence time estimation

• No methods explicitly incorporating networks for divergence times

Lynchpin 3: Fossil calibrations

constraint Age (Ma) taxon

CG Orchidaceae 15 (Early-Middle Miocene) Meliorchis caribea

CG Agavoideae 12 (Middle Miocene) Protoyucca


● Most botanists aren't paleobotanists

● Applying secondary calibrations might be problematic

● Evidence for additional fossil calibrations in Asparagales lineages

● Emerging support for both deep and shallow fossil calibrations across the phylogeny (except this requires representative taxon sampling)

Ramirez et al. 2007

Secondary calibrations can have unexpected results!


Monocot 8 gene McKain 19 single copy nuclear genes(two applicable fossils)

McKain 19 single copy nuclear genes

CG Asparagales 113 Ma (125-105) 87 Ma (102-72) 113 Ma (fixed age)

CG “Core” Asparagales

61 Ma (67-58) 63 Ma (75-53) 78 Ma (74-81)

CG Asparagaceae 52 Ma (58-49) 52 Ma (62-43) 63 Ma (60-66)

CG Amaryllidaceae 50 Ma (55-47) 48 Ma (57-40) 59 Ma (56-61)

CG Xanthorrhoeaceae 47 Ma (52-44) 56 Ma (66-46) 69 Ma (66-71)

Recommendations for dating estimates in Asparagales

● Can any of uncertainty in three lynchpins be accommodated by analytical techniques?

– Easier to make comparisons with r8s (or other non-Bayesian algorithms)

– *BEAST: explicitly incorporates coalescent to infer “species” tree, divergence times, population sizes

– Different approach to prior assignment of fossils (exponential distribution, Chen et al. 2013)

– Uncertainty better managed by Bayesian methods, but this benefit nullified by priors which are too complex!

– Congruification (Eastman 2013): an alternative to running complete analysis

– Look at relative diversification rather than absolute


Objectives





Where do we go from here?

Genomic changes occur repeatedly in Asparagales phylogeny

Hertweck, Genome, 2013


Dating transposable element proliferation

Hertweck, Genome, 2013


Black: copiaWhite: gypsyRectangles: total repeats

Divergence times provide the context for inferring evolutionary patterns

● From monocot 8 gene dataset:

● SymmeTREE (Chan et al. 2005): tree topology and tree-wide species diversity

● One significant and one marginally significant shift in diversification, both in subfamily Agavoideae

● Other methods

● Incorporating divergence times

● Exploring relationships with morphological or life history traits

● Compounding uncertainty


Summary

● My personally favored estimate for CG Asparagales: 113 Ma (125-105)

● Problems with dating in monocots are exacerbated in Asparagales

● Taxonomic sampling● Molecular sequence sampling● Fossil calibrations

● Can any of these problems be accommodated by analytical techniques?

● Careful balance between appropriate sampling and possibly compounding problems

● Think creatively, and try multiple approaches


Basic Asparagales divergence times


Monocot 8 gene dataset

CG Asparagales: 113 Ma (125-105)

CG “Core” Asparagales: 61 Ma (67-58)CG Asparagaceae: 52 Ma (58-49)CG Amaryllidaceae: 50 Ma (55-47)CG Xanthorrhoeaceae: 47 Ma (52-44)

Acknowledgements

• J. Chris Pires and lab (U of Missouri)

• Victoria Docktor

• NESCent science and bioinformatics folks

• Fossil consultation

• S. Magallon

• E. Friis

• M. Beilstein

• N. Nagalingum

• Matt Dorrance

K. Hertweck, NESCent, Asparagales divergence

Repetitive elements in Asparagales:Poster 46!

Blog:k8hert.blogspot.com

Twitter @k8hertGoogle+ [email protected] available:http://www.slideshare.net/katehertweck

http://k8hert.blogspot.com/

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Hertweck Monocots V Presentation

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