Ecogen2013

Evolutionary genetics of adaptation to high altitude in Zea mays

Jeff Ross-Ibarra www.rilab.org @jrossibarra

http://www.rilab.org

Acknowledgements

Ed Buckler (USDA/Cornell) Norm Ellstrand (UC Riverside)

Collaborators

R-I Lab

Acknowledgements

Ed Buckler (USDA/Cornell) Norm Ellstrand (UC Riverside)

Collaborators

Tanja Pyhäjärvi (U. Oulu)

Shohei Takuno (Sokendai)

MaIhew Hufford (Iowa State)

R-I Lab

How do plants adapt to new environments?

Clausen, Keck, Heisey

What is the geneRc basis of adaptaRon?

Lowry & Willis 2010 PLoS Biology

How common is parallel adaptaRon?

Teqing Wild rice

Supplementary Figure 1

Supplementary Figure 1. The phenotypes of Teqing and wild rice (Hainan in China).

Genetic control of rice plant architecture domestication

Jian Jin, Wei Huang, Ji-Ping Gao, Jun Yang, Min Shi, Mei-Zhen Zhu, Da Luo, Hong-Xuan Lin

Supplementary Information

Jin et al. 2008 Nat. Gen.

©20

11 N

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Inc.

All

righ

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2 ADVANCE ONLINE PUBLICATION NATURE GENETICS

L E T T E R S

ORF, diversity rises in both maize and teosinte. The rise in nucleotide diversity in maize beyond −65 kb suggests that the selective sweep ends near this point.

We applied the HKA test16 to address whether individual segments of the control region show evidence of past selection (Supplementary Table 4). Our results confirm previous findings17 that the region from −65.6 to −67.6 kb (segments A and B in Fig. 3a) does not depart significantly from neutral expectations, but the neutral model can be rejected for the region from −58.8 to −57.4 kb (segment D). We also tested, for the first time, an additional segment (segment C, from −65.6 to −63.7 kb) in the middle of the control region, which our data show departs significantly the neutral model. Prior results15 demon-strated that the sweep extends from −58 kb to the tb1 ORF; thus, overall, the sweep includes approximately 65.6 kb from the control region to the ORF.

Phenotypic fine-mapping with recombinant chromosomes indicated that the factors controlling phenotype lie between 58.7 and 69.5 kb upstream of the ORF. Population genetic analysis indicates that the selective sweep extends only to −65.6 kb. Together, these two sources of information suggest that the causative polymorphism(s) lies between −58.7 and −65.6 kb of the ORF. We looked in greater detail at sequence diversity for maize and teosinte in the ~7-kb seg-ment that these two methods define. A minimum spanning tree for a sample of 16 diverse maize and 17 diverse teosintes in this region revealed two distinct clusters of haplotypes, one composed mostly of maize sequences and the other composed mostly of teosinte sequences (Fig. 3b). We designated these clusters as the maize cluster haplotype (MCH) and the teosinte cluster haplotype (TCH), respectively. There are four fixed differences between the sequences in the maize and teosinte clusters (Fig. 3a). Two of these fixed differences are single- nucleotide polymorphisms (SNPs), and two are large insertions in the maize cluster haplotype relative to the teosinte cluster haplo-type. BLAST searches of the insertion sequences revealed that one

is a Hopscotch retrotransposon and the other is a Tourist miniature inverted-repeat transposable element (MITE). Of the four fixed dif-ferences, Hopscotch and one SNP are in the proximal component, whereas Tourist and the other SNP are in the distal component, as delineated by phenotypic fine-mapping.

To estimate the frequency of the two haplotype groups in maize and teosinte, we assayed 139 additional diverse maize chromosomes and 148 additional diverse teosinte chromosomes (Supplementary Table 5). For this purpose, we used the Hopscotch and Tourist insertions as markers for the haplotype groups (Supplementary Table 2b). The MCH is present in >95% of the maize chromosomes assayed but in <5% of teosinte chromo-somes. The fact that the MCH is not fixed in maize suggests either that the initial selective sweep was not complete or that post-domestication gene flow from teosinte to maize has reintroduced the TCH into the maize gene pool. Correspondingly, the presence of the MCH in teosinte may represent either a haplotype variant that existed in teosinte before domestication or post-domestication gene flow from maize into teosinte, which is known to occur18.

Inspection of the sequence alignment of the Hopscotch-Tourist region suggests that the two insertions differ in relative age. The Tourist insertion has accumulated greater nucleotide diversity ( = 0.0054) since insertion, including a pair of sites that fail the four-gamete test, which is indicative of recombination among Tourist sequences. Nucleotide diversity in the Hopscotch insertion is much lower ( = 0.0016) and shows no evidence of past recombination. These observations point to the Hopscotch insertion being more recent than the Tourist. Our sequences do show evidence of recombination between Hopscotch and a SNP in the flanking sequence between the two insertions, likely explaining how the Hopscotch insertion has come to be associated with multiple alleles of the Tourist element.

These nucleotide diversity data allow us to ask whether the Hopscotch insertion arose before or during domestication. Following Thomson et al.19 and Hudson20, we estimate a most recent common ancestor for the Hopscotch alleles at ~28,000 years before present (BP), with a 95% lower bound of ~15,000 BP. A more conservative approach, which counts only singletons and assumes a star phylogeny, yields a slightly lower estimate of ~23,000 BP, with a 95% lower bound of ~13,000 BP. Both estimates conservatively use a relatively high

a b c d

Figure 1 Teosinte and maize plants. (a) Highly branched teosinte plant. (b) Teosinte lateral branch with terminal tassel. (c) Unbranched maize plant. (d) Maize ear shoot (that is, lateral branch).

pg3 tb1

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Figure 2 The phenotypic additive effects for seven intervals across the tb1 genomic region. The horizontal axis represents the tb1 genomic region to scale. Base-pair positions are relative to AGPv2 position 265,745,977 of the maize reference genome sequence. The tb1 ORF and the nearest upstream predicted gene (pg3) are shown. The previously defined control region (CR)14 is shown in red and is divided into its proximal and distal components. Vertical columns represent the additive effects shown with standard error bars for each of the three traits in each of the seven intervals that were tested for an effect on phenotype. Black columns are statistically significant (P (Bonferroni) < 0.05); white bars are not statistically significant (P (Bonferroni) > 0.05).

©20

11 N

atur

e A

mer

ica,

Inc.

All

righ

ts r

eser

ved.

2 ADVANCE ONLINE PUBLICATION NATURE GENETICS

L E T T E R S

ORF, diversity rises in both maize and teosinte. The rise in nucleotide diversity in maize beyond −65 kb suggests that the selective sweep ends near this point.

We applied the HKA test16 to address whether individual segments of the control region show evidence of past selection (Supplementary Table 4). Our results confirm previous findings17 that the region from −65.6 to −67.6 kb (segments A and B in Fig. 3a) does not depart significantly from neutral expectations, but the neutral model can be rejected for the region from −58.8 to −57.4 kb (segment D). We also tested, for the first time, an additional segment (segment C, from −65.6 to −63.7 kb) in the middle of the control region, which our data show departs significantly the neutral model. Prior results15 demon-strated that the sweep extends from −58 kb to the tb1 ORF; thus, overall, the sweep includes approximately 65.6 kb from the control region to the ORF.

Phenotypic fine-mapping with recombinant chromosomes indicated that the factors controlling phenotype lie between 58.7 and 69.5 kb upstream of the ORF. Population genetic analysis indicates that the selective sweep extends only to −65.6 kb. Together, these two sources of information suggest that the causative polymorphism(s) lies between −58.7 and −65.6 kb of the ORF. We looked in greater detail at sequence diversity for maize and teosinte in the ~7-kb seg-ment that these two methods define. A minimum spanning tree for a sample of 16 diverse maize and 17 diverse teosintes in this region revealed two distinct clusters of haplotypes, one composed mostly of maize sequences and the other composed mostly of teosinte sequences (Fig. 3b). We designated these clusters as the maize cluster haplotype (MCH) and the teosinte cluster haplotype (TCH), respectively. There are four fixed differences between the sequences in the maize and teosinte clusters (Fig. 3a). Two of these fixed differences are single- nucleotide polymorphisms (SNPs), and two are large insertions in the maize cluster haplotype relative to the teosinte cluster haplo-type. BLAST searches of the insertion sequences revealed that one

is a Hopscotch retrotransposon and the other is a Tourist miniature inverted-repeat transposable element (MITE). Of the four fixed dif-ferences, Hopscotch and one SNP are in the proximal component, whereas Tourist and the other SNP are in the distal component, as delineated by phenotypic fine-mapping.

To estimate the frequency of the two haplotype groups in maize and teosinte, we assayed 139 additional diverse maize chromosomes and 148 additional diverse teosinte chromosomes (Supplementary Table 5). For this purpose, we used the Hopscotch and Tourist insertions as markers for the haplotype groups (Supplementary Table 2b). The MCH is present in >95% of the maize chromosomes assayed but in <5% of teosinte chromo-somes. The fact that the MCH is not fixed in maize suggests either that the initial selective sweep was not complete or that post-domestication gene flow from teosinte to maize has reintroduced the TCH into the maize gene pool. Correspondingly, the presence of the MCH in teosinte may represent either a haplotype variant that existed in teosinte before domestication or post-domestication gene flow from maize into teosinte, which is known to occur18.

Inspection of the sequence alignment of the Hopscotch-Tourist region suggests that the two insertions differ in relative age. The Tourist insertion has accumulated greater nucleotide diversity ( = 0.0054) since insertion, including a pair of sites that fail the four-gamete test, which is indicative of recombination among Tourist sequences. Nucleotide diversity in the Hopscotch insertion is much lower ( = 0.0016) and shows no evidence of past recombination. These observations point to the Hopscotch insertion being more recent than the Tourist. Our sequences do show evidence of recombination between Hopscotch and a SNP in the flanking sequence between the two insertions, likely explaining how the Hopscotch insertion has come to be associated with multiple alleles of the Tourist element.

These nucleotide diversity data allow us to ask whether the Hopscotch insertion arose before or during domestication. Following Thomson et al.19 and Hudson20, we estimate a most recent common ancestor for the Hopscotch alleles at ~28,000 years before present (BP), with a 95% lower bound of ~15,000 BP. A more conservative approach, which counts only singletons and assumes a star phylogeny, yields a slightly lower estimate of ~23,000 BP, with a 95% lower bound of ~13,000 BP. Both estimates conservatively use a relatively high

a b c d

Figure 1 Teosinte and maize plants. (a) Highly branched teosinte plant. (b) Teosinte lateral branch with terminal tassel. (c) Unbranched maize plant. (d) Maize ear shoot (that is, lateral branch).

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cts

Tillering

Internodelength

Kernels

per rank

0.4

0.2

0

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CR

–60 –40 –20 0

Figure 2 The phenotypic additive effects for seven intervals across the tb1 genomic region. The horizontal axis represents the tb1 genomic region to scale. Base-pair positions are relative to AGPv2 position 265,745,977 of the maize reference genome sequence. The tb1 ORF and the nearest upstream predicted gene (pg3) are shown. The previously defined control region (CR)14 is shown in red and is divided into its proximal and distal components. Vertical columns represent the additive effects shown with standard error bars for each of the three traits in each of the seven intervals that were tested for an effect on phenotype. Black columns are statistically significant (P (Bonferroni) < 0.05); white bars are not statistically significant (P (Bonferroni) > 0.05).

Studer et al. 2011 Nat. Gen.

Rose Andrew

Does parallel phenotype = parallel genotype?

Kovach et al. 2009 PNAS

Colosimo et al. 2005 Science

•Highland adapta-on in teosinte

•AdapRve introgression in highland maize

•Parallel adaptaRon in highland maize

•Future direcRons

Zea mays ssp. mays

Zea mays ssp. parviglumis

Zea mays ssp. mexicana

Zea nicaraguensis

Zea luxurians

Tripsacum dactyloides

Zea mays ssp. huehuetenangensis

Zea perennis

Zea diploperennis

Zea: teosinte & maize

Hufford et al. (2012) Trends in Gene.cs

mexicana and parviglumis in Mexico

Hufford et al. (2012) PLoS ONE

masl

Bradburd et al. Evolution 2013

mexicana parviglumis

Lauter et al. (2004) Genetics

Barthakur (1974) Int. J Biomet

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Climate Alelle Freq. Morphology (maize)

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•Highland adaptaRon in teosinte

•Adap-ve introgression in highland maize


•Future direcRons

Maize colonizaRon of highlands

domestication in Mexico lowland

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Hufford et al. 2013 PLoS Gene-cs

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maize into mexicana

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Santa Clara

San Pedro

Allopatric

Shared introgression from teosinte into maize

El Porvenir

Opopeo

Xochimilco

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Tenango del Aire

Ixtlan

Nabogame

Santa Clara

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Inv4n


Inv4n

El Porvenir

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Tenango del Aire

Ixtlan

Nabogame

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Allopatric


El Porvenir

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Tenango del Aire

Ixtlan

Nabogame

Santa Clara

San Pedro

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Fst high vs. low elevation maize

6 of 9 introgressions overlap with teosinte QTL

b1 in maizeLauter et al. 2004 Genetics

Inv4n

Moose et al. 2004 Genetics

Introgressed pops show highland phenotypes, cold adaptaRonIntrogression

No Introgression



•Parallel adapta-on in highland maize

•Future direcRons



Mexico lowland

9,000 BP




S. America lowland

6,000 BP

Mexico lowland

9,000 BP




S. America lowland

6,000 BP

S. America Highland

4,000 BP

Mexico lowland

9,000 BP


Mexico

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ResultsPatterns of Genetic Structure and Differentiation. Principal com-ponents analysis (PCA) (17) of the maize SNP data identifies 58significant principal components (PCs) (explaining 37.6% oftotal variance), probably reflecting isolation by distance (18) andlinkage effects (19). We use the first nine PCs, which present thestrongest spatial autocorrelation (Fig. S2) and explain a largeportion of the total variance (18.7%), to cluster the accessionsinto 10 geographically distinct groups (Fig. 1A). Meso-Americanmaize falls into three groups: the Meso-American Lowlandgroup, which includes predominantly lowland accessions fromsoutheast Mexico and the Caribbean; the West Mexico group,representing both lowlands and highlands; and the MexicanHighland group, encompassing most of Matsuoka et al.’s high-land Mexican accessions (5) as well as accessions from highlandGuatemala. These clusters also confirm the presence of US-de-rived varieties in South America (20); we excluded these acces-sions from further analysis.In the joint PCA analysis of the three subspecies, the first PC

(10.8% of variance) separates maize from its wild relatives andconfirms the similarity between maize from the Mexican Highlandgroup and parviglumis (Fig. 1B). The second PC (4.8%of variance)mainly separates the genetic groups of maize along a north–southaxis, with the Northern United States and Andean Highlands atthe extremes. The third PC (2.7% of variance) predominatelyreflects the difference between parviglumis and mexicana. TheMexican Highland cluster extends toward mexicana along bothPC 1 and 3, suggesting that the similarity of highland maize toparviglumis may reflect admixture with mexicana.

Admixture Analysis. Simulation of gene flow of mexicana into theMeso-American Lowland maize group suggests that 13% cu-mulative historical introgression is sufficient to explain observeddifferences between lowland and highland maize in terms ofheterozygosity and differentiation from parviglumis (Fig. S3).Structure analysis (21) of all Mexican accessions lends supportfor this magnitude of introgression (Fig. 2). The three subspeciesform clearly separated clusters, but evidence of admixture is

evident in all three groups, and the two wild relatives show clearsigns of bidirectional introgression at altitudes where theirranges overlap (Fig. 2). Highland maize shows strong signs ofmexicana introgression, with 20% admixture observed in theMexican Highland cluster, but below 1,500 m mexicana in-trogression drops to less than 1%. Introgression from parviglumisinto maize is much lower overall, reaching its highest averagevalue (3%) in the lowland West Mexico group.

Drift Analysis. Because introgression from mexicana may affectancestry inference based on genetic distance from parviglumis, wetook an approach that does not require reference to the wild rel-atives. Under models of historical range expansion, genetic dif-ferentiation increases away from the population of origin (22, 23),and estimates of drift from ancestral frequencies have been appliedsuccessfully to identify ancestral populations (24). We thereforeapplied the method of Nicholson et al. (25) to estimate simulta-neously ancestral frequencies and F, a measure of genetic drift ofaway from these frequencies, for sets of predefined populations.To illustrate the potential impact ofmexicana introgression, we

first performed a standard analysis that includes each maizepopulation in turn in conjunction with the two wild relatives.Average drift away from the inferred common ancestor of maize,parviglumis, and mexicana is higher for maize (F = 0.24) than formexicana (F = 0.15) or parviglumis (F = 0.07), probably due tochanges in allele frequency following the domestication bottle-neck. Because the inferred ancestral frequencies are closer tothose of the wild relatives than to present-day maize, comparisonwith this ancestor is sensitive to introgression from these sub-species. It therefore is not surprising that estimates of F betweenindividual maize populations and the common ancestor of allthree taxa identify the Mexican Highland group as being mostsimilar (Fig. 3A). This pattern is maintained in an analysis ex-cluding mexicana, in which Mexican Highland maize is tied withtheWestMexico group as themost ancestral population (Fig. 3B).To mitigate the impact of introgression, we used a slightly

modified approach that excludes both parviglumis and mexicanaand calculates genetic drift with respect to ancestral frequenciesinferred from domesticated maize alone. Because the genetic

Fig. 1. (A) Map of sampled maize accessions colored by genetic group. (B) First three genetic PCs of all sampled accessions.

van Heerwaarden et al. PNAS | January 18, 2011 | vol. 108 | no. 3 | 1089

EVOLU

TION

• shared phenotypes between Mexico and Andes

• geneRc data supports independent origin

• independent mutaRons? adapRve gene flow?

van Heerwaarden et al. 2011 PNAS

Mexican/Andean maize data

• 96 samples from four highland/lowland populaRons

• 100K SNPS (GBS & Maize SNP50 array)

Shohei Takuno

Modeling demography to idenRfy outliers

• Demographic models fit with joint site freq. spectrum (δa/δi)

• Simulate to generate null allele frequency distribuRon

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of altitude adaptation. The strongest such signalsinclude several genes with known roles in oxy-gen transport and regulation (Table 1 and tableS3). Overall, the 34 genes in our data set thatfell under the gene ontology category “responseto hypoxia” had significantly greater PBS valuesthan the genome-wide average (P = 0.00796).

The strongest signal of selection came from theendothelial Per-Arnt-Sim (PAS) domain protein1 (EPAS1) gene. On the basis of frequency dif-ferences among the Danes, Han, and Tibetans,EPAS1 was inferred to have a very long Tibetanbranch relative to other genes in the genome (Fig.2). In order to confirm the action of natural selec-tion, PBS values were compared against neutralsimulations under our estimated demographicmodel. None of one million simulations surpassedthe PBS value observed for EPAS1, and this resultremained statistically significant after accountingfor the number of genes tested (P < 0.02 afterBonferroni correction). Many other genes had un-corrected P values below 0.005 (Table 1), and,although none of these were statistically significantafter correcting for multiple tests, the functionalenrichment suggests that some of these genes mayalso contribute to altitude adaptation.

EPAS1 is also known as hypoxia-induciblefactor 2a (HIF-2a). The HIF family of transcrip-tion factors consist of two subunits, with three

Fig. 1. Two-dimensional unfolded site frequency spectrum for SNPs in Tibetan (x axis) and Han (y axis)population samples. The number of SNPs detected is color-coded according to the logarithmic scaleplotted on the right. Arrows indicate a pair of intronic SNPs from the EPAS1 gene that show stronglyelevated derived allele frequencies in the Tibetan sample compared with the Han sample.

Table 1. Genes with strongest frequency changes in the Tibetan population. The top 30 PBS values for the Tibetan branch are listed. Oxygen-relatedcandidate genes within 100 kb of these loci are noted. For FXYD, F indicates Phe; Y, Tyr; D, Asp; and X, any amino acid.

Gene Description Nearby candidate PBS P valueEPAS1 Endothelial PAS domain protein 1 (HIF-2a) (Self) 0.514 <0.000001C1orf124 Hypothetical protein LOC83932 EGLN1 0.277 0.000203DISC1 Disrupted in schizophrenia 1 EGLN1 0.251 0.000219ATP6V1E2 Adenosine triphosphatase (ATPase), H+ transporting, lysosomal 31 kD, V1 EPAS1 0.246 0.000705SPP1 Secreted phosphoprotein 1 0.238 0.000562PKLR Pyruvate kinase, liver, and RBC (Self) 0.230 0.000896C4orf7 Chromosome 4 open reading frame 7 0.227 0.001098PSME2 Proteasome activator subunit 2 0.222 0.001103OR10X1 Olfactory receptor, family 10, subfamily X SPTA1 0.218 0.000950FAM9C Family with sequence similarity 9, member C TMSB4X 0.216 0.001389LRRC3B Leucine-rich repeat–containing 3B 0.215 0.001405KRTAP21-2 Keratin-associated protein 21-2 0.213 0.001470HIST1H2BE Histone cluster 1, H2be HFE 0.212 0.001568TTLL3 Tubulin tyrosine ligase-like family, member 3 0.206 0.001146HIST1H4B Histone cluster 1, H4b HFE 0.204 0.001404ACVR1B Activin A type IB receptor isoform a precursor ACVRL1 0.198 0.002041FXYD6 FXYD domain–containing ion transport regulator 0.192 0.002459NAGLU Alpha-N-acetylglucosaminidase precursor 0.186 0.002834MDH1B Malate dehydrogenase 1B, nicotinamide adenine dinucleotide (NAD) (soluble) 0.184 0.002113OR6Y1 Olfactory receptor, family 6, subfamily Y SPTA1 0.183 0.002835HBB Beta globin (Self), HBG2 0.182 0.003128OTX1 Orthodenticle homeobox 1 0.181 0.003235MBNL1 Muscleblind-like 1 0.179 0.002410IFI27L1 Interferon, alpha-inducible protein 27-like 1 0.179 0.003064C18orf55 Hypothetical protein LOC29090 0.178 0.002271RFX3 Regulatory factor X3 0.176 0.002632HBG2 G-gamma globin (Self), HBB 0.170 0.004147FANCA Fanconi anemia, complementation group A (Self) 0.169 0.000995HIST1H3C Histone cluster 1, H3c HFE 0.168 0.004287TMEM206 Transmembrane protein 206 0.166 0.004537

2 JULY 2010 VOL 329 SCIENCE www.sciencemag.org76

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• 95% loci differ, 80% from standing variaRon

• No enrichment of shared genes

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Ralph and Coop 2010 Genetics

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•Future direc-ons

Full genomes, new highlands

MaL HuffordVince Buffalo

Full genomes, new highlands

MaL Hufford

Years

NeLi & Durbin 2011 Nature

Vince Buffalo

In progress: mapping pops & more genomes

M Hufford (ISU), R. Sawers (Langebio) Summer 2013

S. Flint-Garcia (MU) Winter 2012

MX x MX F2

SA x SA F2

Highland Landrace (PT) x B73 BC2 NILs

Highland x Lowland Landrace F2 populations

Sharon Strauss Anna O’Brien

ElevaRon paIerns teosinte-‐mycorrhizae coevoluRon

Cor

rela

tion

Coe

ffici

ent

Sofiane Mezmouk

In progress: GWAS on temperature phenotypes

Gitanshu Munjal

Bloom Root Signals

5

x Yellowing of rice leaves under rhizosphere chilling, which is associated with wilting (Cruz et al. 2013), was correlated with latitude of origin (Fig. 3). Generally, rice genotypes that are chilling tolerant are also drought tolerant (Cruz et al. 2013; Zhang et al. 2013).

Hydraulic conductance does not appear to be responsible for the differences among genotypes. Root hydraulic conductance showed a similar response to rhizosphere chilling in maize genotypes that differed in chilling tolerance, whereas the chilling–tolerant genotype had smaller stomatal conductance than the chilling-sensitive one at all temperatures (Aroca et al. 2001). The temperature response of hydraulic conductance, assessed by two different methods, was similar in chilling-sensitive S. lycopersicum cv. T5 (L) and chilling-tolerant S. habrochaites accession LA1778 (H) (Table 1). These species differed, however, in stomatal behavior: L kept its stomata open until its leaves lost turgor and suffered damage, whereas H closed its stomata as it became water limited, water potential remained relatively constant, and its shoots maintained turgor (Fig. 4).

One explanation for such stomatal behavior is that stomata respond to altered water status within the leaf as water flow changes (Cowan 1994; Saliendra et al. 1995; Hubbard et al. 2001; Matzner & Comstock 2001). This explanation, however, is not consistent with our data for tomato. As shoot water status began to decline in both species (Fig. 4A), stomatal conductance increased slightly before it decreased more than three-fold (Fig. 4C). Moreover, shoot water status did not recover even several hours after stomatal closure (Fig. 4).

Another explanation — one that is consistent with the timing of stomatal closure observed in H (Fig. 4) — is that rhizosphere chilling induces roots of chilling-tolerant genotypes to generate a chemical signal that flows in the xylem stream to the shoots and prompts stomatal closure. A compound that serves as a signal for rhizosphere stress should appear in the xylem sap of only tolerant genotypes and only under chilling stress. Furthermore, adding this

Fig. 1. Shoot wilting of plants after 2h of rhizosphere chilling at 6°C as a function of June mean daily minimum temperature for the site of origin of different wild Solanum sect. Lycopersicon species (red) or as a function of annual precipitation for the site of origin of different wild cherry tomato S. lycopersicum accessions (blue). A wilting score of ‘0’ designates that the shoots were fully turgid (lower picture), whereas ‘3’ designates that they were fully flaccid (upper picture). Shown are mean ± SE, n = 9 – 11. (Easlon et al. 2013)

Fig. 2. Shoot wilting during root chilling at 6°C for Zea mays genotypes of temperate or tropical ancestry. A wilting score of ‘3’ designates that shoots were fully flaccid, whereas ‘0’ designates fully turgid. Shown are mean ± SE for 8 and 13 genotypes of temperate and tropical ancestry, respectively. (unpublished)

Fig. 3. Chilling sensitivity as a function of latitude of origin for Oryza sativa genotypes of japonica (temperate or tropical) or indica ancestry. A chilling sensitivity score of ‘9’ designates that all leaves were yellow as a result of water stress at root temperatures below 13°C, whereas ‘1’ designates that none were. Data for yellowing from Mackill & Lei (1997) and data for latitude from Zhao et al. (2011).

Table 1. Response of hydraulic conductance to root temperatures and Arrhenius activation energy in S. lycopersicum cv. T5 (L) and S. habrochaites LA1778 (H) in excised roots or intact plants. Hydraulic conductance of excised roots is per root (mean ± SE, n = 5), whereas that of intact plants is per leaf area (means ± SE, n = 3). For reference, activation energy for water traversing a water-filled pore is about 4 kcal mol–1. (Bloom et al. 2004)

Excised Roots Intact Plants Hydraulic

conductance mg root-1 s-1 kPa-1

Activation energy

kcal mol-1

Hydraulic conductance

mg m-2 s-1 kPa-1

Activationenergy

kcal mol-1

Species 20°C 10°C 20°C 10°C

L 97 ± 37 58 ± 22 9.0 0.31 ± 0.03 0.18 ± 0.03 9.5 H 76 ± 18 44 ± 8 9.4 0.10 ± 0.01 0.06 ± 0.01 8.4

–10 0 10 20

Wilt

ing

scor

e

0

1

2

3

r = 0.935

S. lycopersicumSolanum species

June mean daily minimum temperature (°C)

0 2000 4000

r = 0.875

Annual precipitation (mm y–1)

Temperate Tropical

Wilt

ing

scor

e

0

1

2

Chi

lling

sens

itivi

ty

0

2

4

6

8

10

0 20 40 60Latitude (°)

Japonica temperateJaponica tropicalIndica

Arnold Bloom

Plant Height, Highland Temperatures

• Parallel phenotypic adaptaRon of Zea to highlands

• Important roles for inversions, regulatory mutaRons

• AdaptaRon to high alRtude quanRtaRve

• Parallel geneRcs in highland Mexico via adapRve gene flow

• Different geneRcs in S. America, likely from standing variaRon

Conclusions

Ecogen2013

Technology

Transcript of Ecogen2013