Abstract
A fundamental goal of evolutionary biology is to understand how environment shapes genetic variation through its effect on demographic processes and through natural selection. In non-model species, transcriptome sequencing generates large single nucleotide polymorphism (SNP) panels to disentangle these influences. Quercus lobata (valley oak) offers an excellent system for such analyses because it has stably occupied a climatically heterogeneous landscape throughout California. We used 220,427 diallelic SNPs from 22 individuals identified against a recently assembled reference transcriptome to (1) quantify transcriptome-wide associations of SNPs with climate indicative of demographic responses to climate, (2) identify SNPs especially associated with climate and thus potential targets of natural selection, and (3) test the hypothesis that genetic diversity is high in climate-adaptive candidate genes. Constrained ordinations (redundancy analysis) and variance partitioning showed that genetic structure in Q. lobata was explained by spatial location (49 %) and climate (24 %), especially minimum temperature and summer/spring precipitation balance, suggesting that climate influences neutral demographic processes and gene flow. After accounting for underlying structure, individual-based environmental association analyses identified 79 SNPs from 49 transcripts as candidates under natural selection by climate. These candidate genes had significantly higher SNP rates per base pair per locus (θ W), nucleotide diversity (π), and gene diversity (G) than non-candidate genes. These results provide preliminary support for the hypothesis that balancing selection maintains diversity in climate-adaptive genes. Climate has likely shaped both population demography and local adaptation in valley oak.
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References
Alberto FJ, Derory J, Boury C, Frigerio J-M, Zimmermann NE, Kremer A (2013) Imprints of natural selection along environmental gradients in phenology-related genes of Quercus petraea. Genetics 195:495–512. doi:10.1534/genetics.113.153783
Ashburner M et al (2000) Gene ontology: tool for the unification of biology. Nat Genet 25:25–29
Atwell S et al (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines. Nature 465:627–631. doi:10.1038/nature08800
Balding D, Nichols R (1995) A method for quantifying differentiation between populations at multi-allelic loci and its implications for investigating identity and paternity. Genetica 96:3–12. doi:10.1007/bf01441146
Barrett LW, Fletcher S, Wilton SD (2012) Regulation of eukaryotic gene expression by the untranslated gene regions and other non-coding elements. Cell Mol Life Sci 69:3613–3634. doi:10.1007/s00018-012-0990-9
Begun DJ et al (2007) Population genomics: whole-genome analysis of polymorphism and divergence in Drosophila simulans. Plos Biol 5:e310. doi:10.1371/journal.pbio.0050310
Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol 57:289–300. doi:10.2307/2346101
Borcard D, Legendre P, Drapeau P (1992) Partialling out the spatial component of ecological variation. Ecology 73:1045–1055. doi:10.2307/1940179
Brown GR, Gill GP, Kuntz RJ, Langley CH, Neale DB (2004) Nucleotide diversity and linkage disequilibrium in loblolly pine. Proc Natl Acad Sci U S A 101:15255–15260. doi:10.1073/pnas.0404231101
Cánovas A, Rincon G, Islas-Trejo A, Wickramasinghe S, Medrano J (2010) SNP discovery in the bovine milk transcriptome using RNA-Seq technology. Mamm Genome 21:592–598. doi:10.1007/s00335-010-9297-z
Cleland EE, Chuine I, Menzel A, Mooney HA, Schwartz MD (2007) Shifting plant phenology in response to global change. Trends Ecol Evol 22:357–365. doi:10.1016/J.Tree.2007.04.003
Cokus SJ, Gugger PF, Sork VL (2015) Evolutionary insights from de novo transcriptome assembly and SNP discovery in California white oaks. BMC Genomics 16:552
Coop G, Witonsky D, Di Rienzo A, Pritchard JK (2010) Using environmental correlations to identify loci underlying local adaptation. Genetics 185:1411–1423. doi:10.1534/genetics.110.114819
Davis MB (1976) Pleistocene biogeography of temperate deciduous forests. Geosci Man 13:13–26
De Mita S, Thuillet A-C, Gay L, Ahmadi N, Manel S, Ronfort J, Vigouroux Y (2013) Detecting selection along environmental gradients: analysis of eight methods and their effectiveness for outbreeding and selfing populations. Mol Ecol 22:1383–1399. doi:10.1111/mec.12182
Derory J et al (2006) Transcriptome analysis of bud burst in sessile oak (Quercus petraea). New Phytol 170:723–738. doi:10.1111/J.1469-8137.2006.01721.X
Derory J et al (2010) Contrasting relationships between the diversity of candidate genes and variation of bud burst in natural and segregating populations of European oaks. Heredity 104:438–448. doi:10.1038/Hdy.2009.134
Eckert AJ, Bower AD, González-Martínez SC, Wegrzyn JL, Coop G, Neale DB (2010a) Back to nature: ecological genomics of loblolly pine (Pinus taeda, Pinaceae). Mol Ecol 19:3789–3805. doi:10.1111/j.1365-294X.2010.04698.x
Eckert AJ, van Heerwaarden J, Wegrzyn JL, Nelson CD, R-I J, González-Martínez SC, Neale DB (2010b) Patterns of population structure and environmental associations to aridity across the range of loblolly pine (Pinus taeda L., Pinaceae). Genetics 185:969–982. doi:10.1534/genetics.110.115543
Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460–2461. doi:10.1093/bioinformatics/btq461
Endler JA (1986) Natural selection in the wild. Princeton University Press, Princeton
Finn RD et al (2014) Pfam: the protein families database. Nucleic Acids Res 42:D222–D230. doi:10.1093/nar/gkt1223
Frichot E, Schoville SD, Bouchard G, François O (2013) Testing for associations between loci and environmental gradients using latent factor mixed models. Mol Biol Evol 30:1687–1699. doi:10.1093/molbev/mst063
Furlotte NA, Kang HM, Ye C, Eskin E (2011) Mixed-model coexpression: calculating gene coexpression while accounting for expression heterogeneity. Bioinformatics 27:i288–i294. doi:10.1093/bioinformatics/btr221
Geraldes A et al (2011) SNP discovery in black cottonwood (Populus trichocarpa) by population transcriptome resequencing. Mol Ecol Resour 11:81–92. doi:10.1111/j.1755-0998.2010.02960.x
Grivet D, Deguilloux M-F, Petit RJ, Sork VL (2006) Contrasting patterns of historical colonization in white oaks (Quercus spp.) in California and Europe. Mol Ecol 15:4085–4093
Gugger PF, Ikegami M, Sork VL (2013) Influence of late quaternary climate change on present patterns of genetic variation in valley oak, Quercus lobata Née. Mol Ecol 22:3598–3612. doi:10.1111/mec.12317
Günther T, Coop G (2013) Robust identification of local adaptation from allele frequencies. Genetics 195:205–220. doi:10.1534/genetics.113.152462
Hancock AM, Di Rienzo A (2008) Detecting the genetic signature of natural selection in human populations: models, methods, and data. Annu Rev Anthropol 37:197–217
Holliday JA, Ritland K, Aitken SN (2010) Widespread, ecologically relevant genetic markers developed from association mapping of climate-related traits in Sitka spruce (Picea sitchensis). New Phytol 188:501–514. doi:10.1111/j.1469-8137.2010.03380.x
Hunter AF, Lechowicz MJ (1992) Predicting the timing of budburst in temperate trees. J Appl Ecol 29:597–604
James PMA, Coltman DW, Murray BW, Hamelin RC, Sperling FAH (2011) Spatial genetic structure of a symbiotic beetle-fungal system: toward multi-taxa integrated landscape genetics. PLoS One 6:e25359. doi:10.1371/journal.pone.0025359
Jones P et al (2014) InterProScan 5: genome-scale protein function classification. Bioinformatics 30:1236–1240. doi:10.1093/bioinformatics/btu031
Kang HM, Zaitlen NA, Wade CM, Kirby A, Heckerman D, Daly MJ, Eskin E (2008) Efficient control of population structure in model organism association mapping. Genetics 178:1709–1723. doi:10.1534/genetics.107.080101
Kang HM et al (2010) Variance component model to account for sample structure in genome-wide association studies. Nat Genet 42:348–354
Karkkäinen K, Løe G, ÅGren J (2004) Population structure in Arabidopsis lyrata: evidence for divergent selection on trichome production. Evolution 58:2831–2836. doi:10.1111/j.0014-3820.2004.tb01634.x
Keller SR, Levsen N, Ingvarsson PK, Olson MS, Tiffin P (2011) Local selection across a latitudinal gradient shapes nucleotide diversity in balsam poplar Populus balsamifera L. Genetics. doi:10.1534/genetics.1111.128041
Knight TM et al (2005) Pollen limitation of plant reproduction: pattern and process. Annu Rev Ecol Evol Syst 36:467–497. doi:10.1146/annurev.ecolsys.36.102403.115320
Kremer A et al (2012) Genomics of Fagaceae. Tree Genetics Genomes 8:583–610. doi:10.1007/s11295-012-0498-3
Lasky JR, Des Marais DL, McKay JK, Richards JH, Juenger TE, Keitt TH (2012) Characterizing genomic variation of Arabidopsis thaliana: the roles of geography and climate. Mol Ecol 21:5512–5529. doi:10.1111/j.1365-294X.2012.05709.x
Lasky JR et al (2014) Natural variation in abiotic stress responsive gene expression and local adaptation to climate in Arabidopsis thaliana. Mol Biol Evol 31:2283–2296. doi:10.1093/molbev/msu170
Legendre P, Fortin M-J (2010) Comparison of the Mantel test and alternative approaches for detecting complex multivariate relationships in the spatial analysis of genetic data. Mol Ecol Resour 10:831–844. doi:10.1111/j.1755-0998.2010.02866.x
Legendre P, Legendre L (1998) Numerical ecology, 2nd edn. Elsevier, Amsterdam
Lohmueller Kirk E et al (2013) Whole-exome sequencing of 2,000 Danish individuals and the role of rare coding variants in type 2 diabetes. Am J Hum Genet 93:1072–1086. doi:10.1016/j.ajhg.2013.11.005
McLaughlin BC, Zavaleta ES (2012) Predicting species responses to climate change: demography and climate microrefugia in California valley oak (Quercus lobata). Glob Chang Biol 18:2301–2312. doi:10.1111/j.1365-2486.2011.02630.x
Neale DB, Savolainen O (2004) Association genetics of complex traits in conifers. Trends Plant Sci 9:325–330. doi:10.1016/J.Plants.2004.05.006
Nei M, Li WH (1979) Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc Natl Acad Sci U S A 76:5269–5273
Nei M, Roychoudhury AK (1974) Sample variances of heterozygosity and genetic diversity. Genetics 76:379–390
Nizinski JJ, Saugier B (1988) A model of leaf budding and development for a mature Quercus forest. J Appl Ecol 25:643–652
Økland RH (1999) On the variation explained by ordination and constrained ordination axes. J Veg Sci 10:131–136
Oksanen J et al. (2015) vegan: Community Ecology Package, 2.3 edn.
Ortego J, Riordan EC, Gugger PF, Sork VL (2012) Influence of environmental heterogeneity on genetic diversity and structure in an endemic southern Californian oak. Mol Ecol 21:3210–3223. doi:10.1111/j.1365-294X.2012.05591.x
Porth I, Koch M, Berenyi M, Burg A, Burg K (2005) Identification of adaptation-specific differences in mRNA expression of sessile and pedunculate oak based on osmotic-stress-induced genes. Tree Physiol 25:1317–1329
Rehfeldt G (2006) A spline model of climate for the western United States. USDA Forest Service, Port Collins
Schork AJ et al (2013) All SNPs are not created equal: genome-wide association studies reveal a consistent pattern of enrichment among functionally annotated SNPs. PLoS Genet 9:e1003449. doi:10.1371/journal.pgen.1003449
Sexton JP, Hangartner SB, Hoffmann AA (2014) Genetic isolation by environment or distance: which pattern of gene flow is most common? Evolution 68:1–15. doi:10.1111/evo.12258
Sork VL, Davis FW, Westfall R, Flint A, Ikegami M, Wang H, Grivet D (2010) Gene movement and genetic association with regional climate gradients in California valley oak (Quercus lobata Née) in the face of climate change. Mol Ecol 19:3806–3823. doi:10.1111/j.1365-294X.2010.04726.x
Sork VL, Aitken SN, Dyer RJ, Eckert AJ, Legendre P, Neale DB (2013) Putting the landscape into the genomics of trees: approaches for understanding local adaptation and population responses to changing climate. Tree Genetics Genomes 9:901–911. doi:10.1007/s11295-013-0596-x
Sork VL, Squire KC, Gugger PF, Levy E, Steele S, Eckert AJ (2016) Landscape genomic analysis of candidate genes for climate adaptation in a California endemic oak, Quercus lobata Née (Fagaceae). Am J Bot 103:1–13
Spieß N et al (2012) Ecophysiological and transcriptomic responses of oak (Quercus robur) to long-term drought exposure and rewatering. Environ Exp Bot 77:117–126. doi:10.1016/j.envexpbot.2011.11.010
Storey JD, Tibshirani R (2003) Statistical significance for genomewide studies. Proc Natl Acad Sci U S A 100:9440–9445
Sul JH, Eskin E (2013) Mixed models can correct for population structure for genomic regions under selection. Nat Rev Genet 14:300–300
Swarbreck D et al (2008) The Arabidopsis Information Resource (TAIR): gene structure and function annotation. Nucleic Acids Res 36:D1009–D1014. doi:10.1093/nar/gkm965
ter Braak CJF (1986) Canonical correspondence analysis: a new eigenvector technique for multivariate direct gradient analysis. Ecology 67:1167–1179. doi:10.2307/1938672
Vitasse Y, François C, Delpierre N, Dufrêne E, Kremer A, Chuine I, Delzon S (2011) Assessing the effects of climate change on the phenology of European temperate trees. Agric For Meteorol 151:969–980. doi:10.1016/j.agrformet.2011.03.003
Wang Z, Gerstein M, Snyder M (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10:57–63. doi:10.1038/nrg2484
Watterson GA (1975) Number of segregating sites in genetic models without recombination. Theor Popul Biol 7:256–276
Weir BS (1996) Genetic data analysis II: methods for discrete population genetic data. Sinauer Associates, Sunderland
Yoder JB, Stanton-Geddes J, Zhou P, Briskine R, Young ND, Tiffin P (2014) Genomic signature of adaptation to climate in Medicago truncatula. Genetics 196:1263–1275. doi:10.1534/genetics.113.159319
Yu JM et al (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208
Acknowledgments
We thank E. Eskin, K. Lohmueller, M. Pellegrini, and A. Platt for helpful discussion. This project was funded by seed money from UCLA to VLS.
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Communicated by A. Kremer
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Illumina RNA sequence reads and SNP data are available through NCBI project accession PRJNA282155 and http://genomes.mcdb.ucla.edu/OakTSA/, following Cokus et al. (2015).
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Gugger, P.F., Cokus, S.J. & Sork, V.L. Association of transcriptome-wide sequence variation with climate gradients in valley oak (Quercus lobata). Tree Genetics & Genomes 12, 15 (2016). https://doi.org/10.1007/s11295-016-0975-1
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DOI: https://doi.org/10.1007/s11295-016-0975-1