Drivers of linkage disequilibrium across a species’ geographic range
Autoři:
Kay Lucek aff001; Yvonne Willi aff001
Působiště autorů:
Department of Environmental Sciences, University of Basel, Basel, Switzerland
aff001
Vyšlo v časopise:
Drivers of linkage disequilibrium across a species’ geographic range. PLoS Genet 17(3): e1009477. doi:10.1371/journal.pgen.1009477
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1009477
Souhrn
While linkage disequilibrium (LD) is an important parameter in genetics and evolutionary biology, the drivers of LD remain elusive. Using whole-genome sequences from across a species’ range, we assessed the impact of demographic history and mating system on LD. Both range expansion and a shift from outcrossing to selfing in North American Arabidopsis lyrata were associated with increased average genome-wide LD. Our results indicate that range expansion increases short-distance LD at the farthest range edges by about the same amount as a shift to selfing. However, the extent over which LD in genic regions unfolds was shorter for range expansion compared to selfing. Linkage among putatively neutral variants and between neutral and deleterious variants increased to a similar degree with range expansion, providing support that genome-wide LD was positively associated with mutational load. As a consequence, LD combined with mutational load may decelerate range expansions and set range limits. Finally, a small number of genes were identified as LD outliers, suggesting that they experience selection by either of the two demographic processes. These included genes involved in flowering and photoperiod for range expansion, and the self-incompatibility locus for mating system.
Klíčová slova:
Arabidopsis thaliana – Genetic drift – Genetic loci – Genomics – Linkage disequilibrium – Plant genomics – Population genetics – Single nucleotide polymorphisms
Zdroje
1. Lewontin RC, Kojima K. The evolutionary dynamics of complex polymorphisms. Evolution. 1960;14: 458–472.
2. Slatkin M. Linkage disequilibrium—understanding the evolutionary past and mapping the medical future. Nat Rev Genet. 2008;9: 477–485. doi: 10.1038/nrg2361 18427557
3. Mackay I, Powell W. Methods for linkage disequilibrium mapping in crops. Trends Plant Sci. 2007;12: 57–63. doi: 10.1016/j.tplants.2006.12.001 17224302
4. Hill WG. Estimation of effective population size from data on linkage disequilibrium. Genet Res. 1981;38: 209–216.
5. Jakobsson M, Scholz SW, Scheet P, Gibbs JR, VanLiere JM, Fung H-C, et al. Genotype, haplotype and copy-number variation in worldwide human populations. Nature. 2008;451: 998–1003. doi: 10.1038/nature06742 18288195
6. Kemppainen P, Knight CG, Sarma DK, Hlaing T, Prakash A, Maung Maung YN, et al. Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions, local adaptation and geographic structure. Mol Ecol Resour. 2015;15: 1031–1045. doi: 10.1111/1755-0998.12369 25573196
7. Ohta T, Kimura M. Linkage disequilibrium due to random genetic drift. Genet Res. 1969;13: 47–55. 5365295
8. Schaper E, Eriksson A, Rafajlovic M, Sagitov S, Mehlig B. Linkage disequilibrium under recurrent bottlenecks. Genetics. 2012;190: 217–229. doi: 10.1534/genetics.111.134437 22048021
9. Kirkpatrick M, Barton NH. Chromosome inversions, local adaptation and speciation. Genetics. 2006;173: 419–434. doi: 10.1534/genetics.105.047985 16204214
10. Excoffier L, Foll M, Petit RJ. Genetic consequences of range expansions. Annu Rev Ecol Evol S. 2009;40: 481–501.
11. Ohta T. Linkage disequilibrium due to random genetic drift in finite subdivided populations. P Natl Acad Sci USA. 1982;79: 1940–1944. doi: 10.1073/pnas.79.6.1940 16593171
12. Dapper AL, Payseur BA. Effects of demographic history on the detection of recombination hotspots from linkage disequilibrium. Mol Biol Evol. 2017;35: 335–353.
13. McVean GAT. A genealogical interpretation of linkage disequilibrium. Genetics. 2002;162: 987–991. 12399406
14. Barton NH, Otto SP. Evolution of recombination due to random drift. Genetics. 2005;169: 2353–2370. doi: 10.1534/genetics.104.032821 15687279
15. Hill WG, Robertson A. Linkage disequilibrium in finite populations. Theor Appl Genet. 1968;38: 226–231. doi: 10.1007/BF01245622 24442307
16. Comeron JM, Williford A, Kliman RM. The Hill–Robertson effect: evolutionary consequences of weak selection and linkage in finite populations. Heredity. 2007;100: 19–31. doi: 10.1038/sj.hdy.6801059 17878920
17. Peischl S, Kirkpatrick M, Excoffier L. Expansion load and the evolutionary dynamics of a species range. Am Nat. 2015;185: E81–93. doi: 10.1086/680220 25811091
18. Barton NH. Genetic linkage and natural selection. Phil Trans R Soc B. 2010;365: 2559–2569. doi: 10.1098/rstb.2010.0106 20643746
19. Reich DE, Cargill M, Bolk S, Ireland J, Sabeti PC, Richter DJ, et al. Linkage disequilibrium in the human genome. Nature. 2001;411: 199–204. doi: 10.1038/35075590 11346797
20. Sousa V, Peischl S, Excoffier L. Impact of range expansions on current human genomic diversity. Curr Opin Genet Dev. 2014;29: 22–30. doi: 10.1016/j.gde.2014.07.007 25156518
21. Bray SM, Mulle JG, Dodd AF, Pulver AE, Wooding S, Warren ST. Signatures of founder effects, admixture, and selection in the Ashkenazi Jewish population. P Natl Acad Sci USA. 2010;107: 16222–16227.
22. Parmesan C. Ecological and evolutionary responses to recent climate change. Annu Rev Ecol Evol S. 2006;37: 637–669.
23. Igic B, Lande R, Kohn JR. Loss of self-incompatibility and its evolutionary consequences. Int J Plant Sci. 2008;169: 93–104.
24. Goodwillie C, Kalisz S, Eckert CG. The evolutionary enigma of mixed mating systems in plants: occurrence, theoretical explanations, and empirical evidence. Annu Rev Ecol Evol Syst. 2005;36:47–79.
25. Willi Y, Määttänen K. Evolutionary dynamics of mating system shifts in Arabidopsis lyrata. J Evol Biol. 2010;23: 2123–2131. doi: 10.1111/j.1420-9101.2010.02073.x 20840308
26. Pollak E. On the theory of partially inbreeding finite populations. I. Partial selfing. Genetics. 1987;117: 353–360. 3666446
27. Nordborg M. Linkage disequilibrium, gene trees and selfing: an ancestral recombination graph with partial self-fertilization. Genetics. 2000;154: 923–929. 10655241
28. Cutter AD, Payseur BA. Selection at linked sites in the partial selfer Caenorhabditis elegans. Mol Biol Evol. 2003;20: 665–673. doi: 10.1093/molbev/msg072 12679551
29. Slotte T. The impact of linked selection on plant genomic variation. Brief Funct Genom. 2014;13: 268–275. doi: 10.1093/bfgp/elu009 24759704
30. Ross-Ibarra J, Wright SI, Foxe JP, Kawabe A, DeRose-Wilson L, Gos G, et al. Patterns of polymorphism and demographic history in natural populations of Arabidopsis lyrata. PLoS ONE. 2008;3. doi: 10.1371/journal.pone.0002411 18545707
31. Nordborg M, Borevitz JO, Bergelson J, Berry CC, Chory J, Hagenblad J, et al. The extent of linkage disequilibrium in Arabidopsis thaliana. Nat Genet. 2002;30: 190–193. doi: 10.1038/ng813 11780140
32. Foxe JP, Slotte T, Stahl EA, Neuffer B, Hurka H, Wright SI. Recent speciation associated with the evolution of selfing in Capsella. P Natl Acad Sci USA. 2009;106: 5241–5245. doi: 10.1073/pnas.0807679106 19228944
33. Hartfield M, Bataillon T, Glémin S. The evolutionary interplay between adaptation and self-fertilization. Trends Genet. 2017;33: 420–431. doi: 10.1016/j.tig.2017.04.002 28495267
34. Charlesworth D. Balancing selection and its effects on sequences in nearby genome regions. PLoS Genet. 2006;2: e64. doi: 10.1371/journal.pgen.0020064 16683038
35. Buckley J, Holub EB, Koch MA, Vergeer P, Mable BK. Restriction associated DNA-genotyping at multiple spatial scales in Arabidopsis lyrata reveals signatures of pathogen-mediated selection. BMC Genom. 2018; 1–21. doi: 10.1186/s12864-018-4806-7 29945543
36. Zeng K, Charlesworth B. The joint effects of background selection and genetic recombination on local gene genealogies. Genetics. 2011;189: 251–266. doi: 10.1534/genetics.111.130575 21705759
37. Kim Y, Nielsen R. Linkage disequilibrium as a signature of selective sweeps. Genetics. 2004;167: 1513–1524. doi: 10.1534/genetics.103.025387 15280259
38. Barton NH. Genetic hitchhiking. Phil Trans R Soc B. 2000;355: 1553–1562. doi: 10.1098/rstb.2000.0716 11127900
39. Feder JL, Egan SP, Nosil P. The genomics of speciation-with-gene-flow. Trends Genet. 2012;28: 342–350. doi: 10.1016/j.tig.2012.03.009 22520730
40. Lee-Yaw JA, Fracassetti M, Willi Y. Environmental marginality and geographic range limits: a case study with Arabidopsis lyrata ssp. lyrata. Ecography. 2018;41: 622–634.
41. Hohmann N, Schmickl R, Chiang T-Y, Lučanová M, Kolář F, Marhold K, et al. Taming the wild: resolving the gene pools of non-model Arabidopsis lineages. BMC Evol Biol. 2014;14: 224. doi: 10.1186/s12862-014-0224-x 25344686
42. Griffin PC, Willi Y. Evolutionary shifts to self-fertilisation restricted to geographic range margins in North American Arabidopsis lyrata. Ecol Lett. 2014;17: 484–490. doi: 10.1111/ele.12248 24428521
43. Willi Y, Fracassetti M, Zoller S, Van Buskirk J. Accumulation of mutational load at the edges of a species range. Mol Biol Evol. 2018;35: 781–791. doi: 10.1093/molbev/msy003 29346601
44. Mable BK, Robertson AV, Dart S, Di Berardo C, Witham L. Breakdown of self-incompatibility in the perennial Arabidopsis lyrata (Brassicaceae) and its genetic consequences. Evolution. 2005;59: 1437–1448. 16153030
45. Koski MH, Layman NC, Prior CJ, Busch JW, Galloway LF. Selfing ability and drift load evolve with range expansion. Evol Lett. 2019;3: 500–512. doi: 10.1002/evl3.136 31636942
46. Nordborg M, Hu TT, Ishino Y, Jhaveri J, Toomajian C, Zheng H, et al. The pattern of polymorphism in Arabidopsis thaliana. Plos Biol. 2005;3: e196. doi: 10.1371/journal.pbio.0030196 15907155
47. Hu TT, Pattyn P, Bakker EG, Cao J, Cheng J-F, Clark RM, et al. The Arabidopsis lyrata genome sequence and the basis of rapid genome size change. Nat Genet. 2011;43: 476–481. doi: 10.1038/ng.807 21478890
48. Zapata L, Ding J, Willing E-M, Hartwig B, Bezdan D, Jiao W-B, et al. Chromosome-level assembly of Arabidopsis thaliana Ler reveals the extent of translocation and inversion polymorphisms. P Natl Acad Sci USA. 2016;113: E4052–E4060. doi: 10.1073/pnas.1607532113 27354520
49. Kofler R, Orozco-terWengel P, De Maio N, Pandey RV, Nolte V, Futschik A, et al. PoPoolation: a toolbox for population genetic analysis of next generation sequencing data from pooled individuals. PLoS ONE. 2011;6: e15925. doi: 10.1371/journal.pone.0015925 21253599
50. Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXivorg. 2013. Available: http://arxiv.org/abs/1303.3997
51. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25: 2078–2079. doi: 10.1093/bioinformatics/btp352 19505943
52. Koboldt DC, Zhang Q, Larson DE, Shen D, McLellan MD, Lin L, et al. VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res. 2012;22: 568–576. doi: 10.1101/gr.129684.111 22300766
53. Lynch M, Bost D, Wilson S, Maruki T, Harrison S. Population-genetic inference from pooled-sequencing data. Genome Biol Evol. 2014;6: 1210–1218. doi: 10.1093/gbe/evu085 24787620
54. Fracassetti M, Griffin PC, Willi Y. Validation of pooled whole-genome re-sequencing in Arabidopsis lyrata. PLoS ONE. 2015;10: e0140462. doi: 10.1371/journal.pone.0140462 26461136
55. Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26: 841–842. doi: 10.1093/bioinformatics/btq033 20110278
56. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call format and VCFtools. Bioinformatics. 2011;27: 2156–2158. doi: 10.1093/bioinformatics/btr330 21653522
57. Feder AF, Petrov DA, Bergland AO. LDx: estimation of linkage disequilibrium from high-throughput pooled resequencing data. PLoS ONE. 2012;7: e48588. doi: 10.1371/journal.pone.0048588 23152785
58. Rawat V, Abdelsamad A, Pietzenuk B, Seymour DK, Koenig D, Weigel D, et al. Improving the annotation of Arabidopsis lyrata using RNA-seq data. PLoS ONE. 2015;10: e0137391. doi: 10.1371/journal.pone.0137391 26382944
59. Ferretti L, Ramos-Onsins SE, Perez-Enciso M. Population genomics from pool sequencing. Mol Ecol. 2013;22: 5561–5576. doi: 10.1111/mec.12522 24102736
60. Vaser R, Adusumalli S, Leng SN, Sikic M, Ng PC. SIFT missense predictions for genomes. Nat Protoc. 2016;11: 1–9. doi: 10.1038/nprot.2015.123 26633127
61. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30: 2114–2120. doi: 10.1093/bioinformatics/btu170 24695404
62. Haubold B, Pfaffelhuber P, Lynch M. mlRho—a program for estimating the population mutation and recombination rates from shotgun-sequenced diploid genomes. Mol Ecol. 2010;19: 277–284. doi: 10.1111/j.1365-294X.2009.04482.x 20331786
63. Lynch M, Xu S, Maruki T, Jiang X, Pfaffelhuber P, Haubold B. Genome-wide linkage-disequilibrium profiles from single individuals. Genetics. 2014;198: 269–281. doi: 10.1534/genetics.114.166843 24948778
64. Adrion JR, Galloway JG, Kern AD. Predicting the landscape of recombination using deep learning. Mol Evol Biol. 2020;526: 68. doi: 10.1093/molbev/msaa038 32077950
65. Ossowski S, Schneeberger K, Lucas-Lledó JI, Warthmann N, Clark RM, Shaw RG, et al. The rate and molecular spectrum of spontaneous mutations in Arabidopsis thaliana. Science. 2010;327: 92–94. doi: 10.1126/science.1180677 20044577
66. Kelleher J, Etheridge AM, McVean G. Efficient coalescent simulation and genealogical analysis for large sample sizes. PLoS Comput Biol. 2016;12: e1004842. doi: 10.1371/journal.pcbi.1004842 27145223
67. Soria-Carrasco V, Gompert Z, Comeault AA, Farkas TE, Parchman TL, Johnston JS, et al. Stick insect genomes reveal natural selection’s role in parallel speciation. Science. 2014;344: 738–742. doi: 10.1126/science.1252136 24833390
68. Baum LE, Petrie T, Soules G, Weiss N. A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains. Ann Math Stat. 1970;41: 164–171.
69. Wilson AJ, Réale D, Clements MN, Morrissey MM, Postma E, Walling CA, et al. An ecologist’s guide to the animal model. J Anim Ecol. 2010;79: 13–26. doi: 10.1111/j.1365-2656.2009.01639.x 20409158
70. Runcie DE, Crawford L. Fast and flexible linear mixed models for genome-wide genetics. PLoS Genet. 2019;15: e1007978. doi: 10.1371/journal.pgen.1007978 30735486
71. Korte A, Vilhjálmsson BJ, Segura V, Platt A, Long Q, Nordborg M. A mixed-model approach for genome-wide association studies of correlated traits in structured populations. Nat Genet. 2012;44: 1066–1071. doi: 10.1038/ng.2376 22902788
72. Bates D, Mächler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. J Stat Softw. 2015;67.
73. The R Core Team. R 3.5.1: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Available: https://www.R-project.org/
74. Hagenblad J, Bechsgaard J, Charlesworth D. Linkage disequilibrium between incompatibility locus region genes in the plant Arabidopsis lyrata. Genetics. 2006;173: 1057–1073. doi: 10.1534/genetics.106.055780 16582433
75. Buckley J, Kilbride E, Cevik V, Vicente JG, Holub EB, Mable BK. R-gene variation across Arabidopsis lyrata subspecies: effects of population structure, selection and mating system. BMC Evol Biol. 2016;16. doi: 10.1186/s12862-016-0665-5 27150007
76. Schomburg FM, Patton DA, Meinke DW, Amasino RM. FPA, a gene involved in floral induction in Arabidopsis, encodes a protein containing RNA-recognition motifs. Plant Cell. 2001;13: 1427–1436. doi: 10.1105/tpc.13.6.1427 11402170
77. Mable BK, Brysting AK, Jorgensen MH, Carbonelli AKZ, Kiefer C, et al. Adding complexity to complexity: gene family evolution in polyploids. Front Ecol Evol. 2018: 1–20.
78. Takou M, Hämälä T, Koch EM, Steige KA, Dittberner H, Yant L, et al. Maintenance of adaptive dynamics and no detectable load in a range-edge out-crossing plant population. bioRxiv. 2020;9: 347. doi: 10.3732/apps.1600094 28224055
79. Sexton JP, McIntyre PJ, Angert AL, Rice KJ. Evolution and ecology of species range limits. Annu Rev Ecol Evol S. 2009;40: 415–436.
80. Wright SI, Kalisz S, Slotte T. Evolutionary consequences of self-fertilization in plants. P R Soc B. 2013;280: 20130133. doi: 10.1098/rspb.2013.0133 23595268
81. Eberle MA, Rieder MJ, Kruglyak L, Nickerson DA. Allele frequency matching between SNPs reveals an excess of linkage disequilibrium in genic regions of the human genome. PLoS Genet. 2006;2: e142. doi: 10.1371/journal.pgen.0020142 16965180
82. Berger S, Schlather M, de Los Campos G, Weigend S, Preisinger R, Erbe M, et al. A scale-corrected comparison of linkage disequilibrium levels between genic and non-genic regions. PLoS ONE. 2015;10: e0141216. doi: 10.1371/journal.pone.0141216 26517830
83. Vergara-Lope A, Ennis S, Vorechovsky I, Pengelly RJ, Collins A. Heterogeneity in the extent of linkage disequilibrium among exonic, intronic, non-coding RNA and intergenic chromosome regions. Europ J Hum Genet. 2019;27: 1436–1444. doi: 10.1038/s41431-019-0419-0 31053778
84. Glémin S. Mating systems and the efficacy of selection at the molecular level. Genetics. 2007;177: 905–916. doi: 10.1534/genetics.107.073601 17954924
85. Eckert CG, Samis KE, Lougheed SC. Genetic variation across species’ geographical ranges: the central–marginal hypothesis and beyond. Mol Ecol. 2008;17: 1170–1188. doi: 10.1111/j.1365-294X.2007.03659.x 18302683
86. Willi Y, Fracassetti M, Bachmann O, Van Buskirk J. Demographic processes linked to genetic diversity and positive selection across a species’ range. Plant Comm. 2020; 100111. doi: 10.1016/j.xplc.2020.100111 33367266
87. Slatkin M, Excoffier L. Serial founder effects during range expansion: a spatial analog of genetic drift. Genetics. 2012;191: 171–181. doi: 10.1534/genetics.112.139022 22367031
88. da Silva J, Galbraith JD. Hill-Robertson interference maintained by Red Queen dynamics favours the evolution of sex. J Evol Biol. 2017;30: 994–1010. doi: 10.1111/jeb.13068 28295769
89. Samuk K, Owens GL, Delmore KE, Miller SE, Rennison DJ, Schluter D. Gene flow and selection interact to promote adaptive divergence in regions of low recombination. Mol Ecol. 2017;26: 4378–4390. doi: 10.1111/mec.14226 28667780
90. Pironon S, Papuga G, Villellas J, Angert AL, García MB, Thompson JD. Geographic variation in genetic and demographic performance: new insights from an old biogeographical paradigm. Biol Rev. 2017;92: 1877–1909. doi: 10.1111/brv.12313 27891813
91. Zhou J-X, Liu Z-W, Li Y-Q, Li L, Wang B, Chen S, et al. Arabidopsis PWWP domain proteins mediate H3K27 trimethylation on FLC and regulate flowering time. J Integr Plant Biol. 2018;60: 362–368. doi: 10.1111/jipb.12630 29314758
92. Mattila TM, Aalto EA, Toivainen T, Niittyvuopio A, Piltonen S, Kuittinen H, et al. Selection for population-specific adaptation shaped patterns of variation in the photoperiod pathway genes in Arabidopsis lyrata during post-glacial colonization. Mol Ecol. 2016;25: 581–597. doi: 10.1111/mec.13489 26600237
93. Hämälä T, Mattila TM, Savolainen O. Local adaptation and ecological differentiation under selection, migration, and drift in Arabidopsis lyrata. Evolution. 2018;72: 1373–1386.
94. Kamau E, Charlesworth B, Charlesworth D. Linkage disequilibrium and recombination rate estimates in the self-incompatibility region of Arabidopsis lyrata. Genetics. 2007;176: 2357–2369. doi: 10.1534/genetics.107.072231 17565949
95. Goubet PM, Bergès H, Bellec A, Prat E, Helmstetter N, Mangenot S, et al. Contrasted patterns of molecular evolution in dominant and recessive self-incompatibility haplotypes in Arabidopsis. PLoS Genet. 2012;8: e1002495. doi: 10.1371/journal.pgen.1002495 22457631
96. Mable BK, Hagmann J, Kim S-T, Adam A, Kilbride E, Weigel D, et al. What causes mating system shifts in plants? Arabidopsis lyrata as a case study. Heredity. 2017;118: 52–63. doi: 10.1038/hdy.2016.99 27804968
97. Roux C, Pauwels M, Ruggiero M-V, Charlesworth D, Castric V, Vekemans X. Recent and ancient signature of balancing selection around the S-locus in Arabidopsis halleri and A. lyrata. Mol Biol Evol. 2013;30: 435–447. doi: 10.1093/molbev/mss246 23104079
Článek vyšel v časopise
PLOS Genetics
2021 Číslo 3
- S diagnostikou Parkinsonovy nemoci může nově pomoci AI nástroj pro hodnocení mrkacího reflexu
- Proč při poslechu některé muziky prostě musíme tančit?
- Chůze do schodů pomáhá prodloužit život a vyhnout se srdečním chorobám
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- „Jednohubky“ z klinického výzkumu – 2024/44
Nejčtenější v tomto čísle
- DNA polymerase theta suppresses mitotic crossing over
- IKAROS is required for the measured response of NOTCH target genes upon external NOTCH signaling
- activin-2 is required for regeneration of polarity on the planarian anterior-posterior axis
- The etiology of Down syndrome: Maternal MCM9 polymorphisms increase risk of reduced recombination and nondisjunction of chromosome 21 during meiosis I within oocyte
