Cited by 145Genetic diversity and population structureGenetic Mapping and Diversity in Plants and AnimalsEvolution and Genetic Dynamics

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

A major locus controls local adaptation and adaptive life history variation in a perennial plant

Open access

Published version of a preprint

Abstract

BACKGROUND: The initiation of growth cessation and dormancy represent critical life-history trade-offs between survival and growth and have important fitness effects in perennial plants. Such adaptive life-history traits often show strong local adaptation along environmental gradients but, despite their importance, the genetic architecture of these traits remains poorly understood. RESULTS: We integrate whole genome re-sequencing with environmental and phenotypic data from common garden experiments to investigate the genomic basis of local adaptation across a latitudinal gradient in European aspen (Populus tremula). A single genomic region containing the PtFT2 gene mediates local adaptation in the timing of bud set and explains 65% of the observed genetic variation in bud set. This locus is the likely target of a recent selective sweep that originated right before or during colonization of northern Scandinavia following the last glaciation. Field and greenhouse experiments confirm that variation in PtFT2 gene expression affects the phenotypic variation in bud set that we observe in wild natural populations. CONCLUSIONS: Our results reveal a major effect locus that determines the timing of bud set and that has facilitated rapid adaptation to shorter growing seasons and colder climates in European aspen. The discovery of a single locus explaining a substantial fraction of the variation in a key life-history trait is remarkable, given that such traits are generally considered to be highly polygenic. These findings provide a dramatic illustration of how loci of large-effect for adaptive traits can arise and be maintained over large geographical scales in natural populations.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s13059-018-1444-y

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • By determining the timing of flowering, homologs of FLOWERING LOCUS T have been shown to facilitate ecotype formation in aspen and sunflower.

    “For example, by determining the timing of flowering, homologs of FLOWERING LOCUS T have been shown to facilitate ecotype formation in aspen (Wang et al., 2018) and sunflower (Todesco et al., 2020).”

    From Genomics of plant speciation (2023) · cites this paper as Wang et al., 2018

    The Backgrounds and Results identify PtFT2 as a FLOWERING LOCUS T homolog that affects bud-set timing and local adaptation in European aspen. They do not show that it determines flowering time or facilitates ecotype formation. The separate sunflower citation is not being assessed here. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 77

  1. Richardson JL, Urban MC, Bolnick DI, Skelly DK. Microgeographic adaptation and the spatial scale of evolution. Trends Ecol Evol. 2014;29:165–76. · DOI
  2. Savolainen O, Lascoux M, Merilä J. Ecological genomics of local adaptation. Nat Rev Genet. 2013;14:807–20. · DOI
  3. Yeaman S, Whitlock MC. The genetic architecture of adaptation under migration-selection balance. Evolution. 2011;65:1897–911. · DOI
  4. Neale DB, Ingvarsson PK. Population, quantitative and comparative genomics of adaptation in forest trees. Curr Opin Plant Biol. 2008;11:149–55. · DOI
  5. Neale DB, Kremer A. Forest tree genomics: growing resources and applications. Nat Rev Genet. 2011;12:111–22. · DOI
  6. Savolainen O, Pyhajarvi T, Knurr T. Gene flow and local adaptation in trees. Annu Rev Ecol Evol Syst. 2007;21:5530–45.
  7. Aitken SN, Whitlock MC. Assisted gene flow to facilitate local adaptation to climate change. Ann Rev Ecol Evol Syst. 2013;44:367–88. · DOI
  8. Rohde A, Bhalerao RP. Plant dormancy in the perennial context. Trends Plant Sci. 2007;12:217–23. · DOI
  9. Singh RK, Svystun T, AlDahmash B, Jönsson AM, Bhalerao RP. Photoperiod- and temperature-mediated control of phenology in trees - a molecular perspective. New Phytol. 2017;213:511–24. · DOI
  10. Hall D, Luquez V, Garcia MV, St Onge KR, Jansson S, Ingvarsson PK. Adaptive population differentiation in phenology across a latitudinal gradient in European aspen (Populus tremula, L.): a comparison of neutral markers, candidate genes and phenotypic traits. Evolution. 2007;61:2849–60. · DOI
  11. Ma X-F, Hall D, Onge KRS, Jansson S, Ingvarsson PK. Genetic differentiation, clinal variation and phenotypic associations with growth cessation across the Populus tremula photoperiodic pathway. Genetics. 2010;186:1033–44. · DOI
  12. Luquez V, Hall D, Albrectsen BR, Karlsson J, Ingvarsson P, Jansson S. Natural phenological variation in aspen (Populus tremula): the SwAsp collection. Tree Genet Genomes. 2008;4:279–92. · DOI
  13. De Carvalho D, Ingvarsson PK, Joseph J, Suter L, Sedivy C, Macaya-Sanz D, et al. Admixture facilitates adaptation from standing variation in the European aspen (Populus tremula L.), a widespread forest tree. Mol Ecol. 2010;19:1638–50. · DOI
  14. Duforet-Frebourg N, Bazin É, Blum MGB. Genome scans for detecting footprints of local adaptation using a Bayesian factor model. Mol Biol Evol. 2014;31:2483–95. · DOI
  15. Frichot É, Schoville SD, Bouchard G, François O. Testing for associations between loci and environmental gradients using latent factor mixed models. Mol Biol Evol. 2013;30:1687–99. · DOI
  16. Ding J, Nilsson O. Molecular regulation of phenology in trees-because the seasons they are a-changin. Curr Opin Plant Biol. 2016;29:73–9. · DOI
  17. Böhlenius H, Huang T, Charbonnel-Campaa L, Brunner AM, Jansson S, Strauss SH, et al. CO/FT regulatory module controls timing of flowering and seasonal growth cessation in trees. Science. 2006;312:1040–3. · DOI
  18. Evans LM, Slavov GT, Rodgers-Melnick E, Martin J, Ranjan P, Muchero W, et al. Population genomics of Populus trichocarpa identifies signatures of selection and adaptive trait associations. Nat Genet. 2014;46:1089–96. · DOI
  19. Hormozdiari F, Kostem E, Kang EY, Pasaniuc B, Eskin E. Identifying causal variants at loci with multiple signals of association. Genetics. 2014;198:497–508. · DOI · Paper page
  20. Voight BF, Kudaravalli S, Wen X, Pritchard JK. A map of recent positive selection in the human genome. PLoS Biol. 2006;4:e72. · DOI
  21. Ferrer-Admetlla A, Liang M, Korneliussen T, Nielsen R. On detecting incomplete soft or hard selective sweeps using haplotype structure. Mol Biol Evol. 2014;31:1275–91. · DOI
  22. Sabeti PC, Reich DE, Higgins JM, Levine HZP, Richter DJ, Schaffner SF, et al. Detecting recent positive selection in the human genome from haplotype structure. Nature. 2002;419:832–7. · DOI · Paper page
  23. Bragg JG, Supple MA, Andrew RL, Borevitz JO. Genomic variation across landscapes: insights and applications. New Phytol. 2015;207:953–67. · DOI
  24. Nielsen R. Molecular signatures of natural selection. Annu Rev Genet. 2005;39:197–218. · DOI
  25. Garud NR, Messer PW, Buzbas EO, Petrov DA. Recent selective sweeps in North American Drosophila melanogaster show signatures of soft sweeps. PLoS Genet. 2015;11:e1005004. · DOI
  26. Hermisson J, Pennings PS. Soft sweeps and beyond: understanding the patterns and probabilities of selection footprints under rapid adaptation. Methods Ecol Evol. 2017;8:700–16. · DOI
  27. Ormond L, Foll M, Ewing GB, Pfeifer SP, Jensen JD. Inferring the age of a fixed beneficial allele. Mol Ecol. 2016;25:157–69. · DOI
  28. Ingvarsson PK, Garcia MV, Hall D, Luquez V, Jansson S. Clinal variation in phyB2, a candidate gene for day-length-induced growth cessation and bud set, across a latitudinal gradient in European aspen (Populus tremula). Genetics. 2006;172:1845–53. · DOI
  29. Ingvarsson PK, Garcia MV, Luquez V, Hall D, Jansson S. Nucleotide polymorphism and phenotypic associations within and around the phytochrome B2 Locus in European aspen (Populus tremula, Salicaceae). Genetics. 2008;178:2217–26. · DOI
  30. Turck F, Fornara F, Coupland G. Regulation and identity of florigen: FLOWERING LOCUS T moves center stage. Annu Rev Plant Biol. 2008;59:573–94. · DOI
  31. Klopfstein S, Currat M, Excoffier L. The fate of mutations surfing on the wave of a range expansion. Mol Biol Evol. 2006;23:482–90. · DOI · Paper page
  32. Excoffier L, Ray N. Surfing during population expansions promotes genetic revolutions and structuration. Trends Ecol Evol. 2008;23:347–51. · DOI
  33. Yeaman S. Local adaptation by alleles of small effect. Am Nat. 2015;186(Suppl 1):S74–89. · DOI
  34. Orr HA. The population genetics of adaptation: the distribution of factors fixed during adaptive evolution. Evolution. 1998;52:935–49. · DOI
  35. Kirkpatrick M, Barton N. Chromosome inversions, local adaptation and speciation. Genetics. 2006;173:419–34. · DOI · Paper page
  36. Yeaman S. Genomic rearrangements and the evolution of clusters of locally adaptive loci. Proc Natl Acad Sci U S A. 2013;110:E1743–51. · DOI
  37. Supple MA, Hines HM, Dasmahapatra KK, Lewis JJ, Nielsen DM, Lavoie C, et al. Genomic architecture of adaptive color pattern divergence and convergence in Heliconius butterflies. Genome Res. 2013;23:gr150615.112-1257. · DOI
  38. Feder JL, Gejji R, Yeaman S, Nosil P. Establishment of new mutations under divergence and genome hitchhiking. Phil Trans Roy Soc B. 2012;B367:461–74. · DOI
  39. Yeaman S, Aeschbacher S, Bürger R. The evolution of genomic islands by increased establishment probability of linked alleles. Mol Ecol. 2016;25:2542–58. · DOI
  40. Pin PA, Nilsson O. The multifaceted roles of FLOWERING LOCUS T in plant development. Plant Cell Environ. 2012;35:1742–55. · DOI
  41. Stern DL, Orgogozo V. Is genetic evolution predictable? Science. 2009;323:746–51. · DOI
  42. Stern DL, Orgogozo V. The loci of evolution: how predictable is genetic evolution? Evolution. 2008;62:2155–77. · DOI
  43. Li P, Filiault D, Box MS, Kerdaffrec E, van Oosterhout C, Wilczek AM, et al. Multiple FLC haplotypes defined by independent cis-regulatory variation underpin life history diversity in Arabidopsis thaliana. Genes Dev. 2014;28:1635–40. · DOI
  44. Stinchcombe JR, Weinig C, Ungerer M, Olsen KM, Mays C, Halldorsdottir SS, et al. A latitudinal cline in flowering time in Arabidopsis thaliana modulated by the flowering time gene FRIGIDA. Proc Natls Acad Sci USA. 2004;101:4712–7. · DOI
  45. Huo H, Wei S, Bradford KJ. DELAY OF GERMINATION1 (DOG1) regulates both seed dormancy and flowering time through microRNA pathways. Proc Natl Acad Sci U S A. 2016;113:E2199–206. · DOI
  46. Kerdaffrec E, Filiault DL, Korte A, Sasaki E, Nizhynska V, Seren Ü, et al. Multiple alleles at a single locus control seed dormancy in Swedish Arabidopsis. elife. 2016;5:e22502. · DOI
  47. Bolger AM, Lohse M, Usadel B. Trimmomatic a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20. · DOI · Paper page
  48. Sundell D, Mannapperuma C, Netotea S, Delhomme N, Lin Y-C, Sjödin A, et al. The Plant Genome Integrative Explorer Resource: PlantGenIE.org. New Phytol. 2015;208:1149–56. · DOI
  49. Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv. 2013;1303:3997. http://arxiv.org/abs/1303.3997 · arXiv
  50. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25:2078–9. · DOI · Paper page
  51. DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat Genet. 2011;43:491–8. · DOI
  52. Tarailo-Graovac M, Chen N. Using RepeatMasker to identify repetitive elements in genomic sequences. Curr Protoc Bioinformatics. 2009;Chapter 4:Unit 4.10.
  53. Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly. 2012;6:80–92. · DOI · Paper page
  54. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–75. · DOI · Paper page
  55. Weir BS, Cockerham CC. Estimating F-statistics for the analysis of population structure. Evolution. 1984;38:1358–70.
  56. Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al. The variant call format and VCFtools. Bioinformatics. 2011;27:2156–8. · DOI
  57. Duforet-Frebourg N, Luu K, Laval G, Bazin É, Blum MGB. Detecting genomic signatures of natural selection with principal component analysis: application to the 1000 Genomes Data. Mol Biol Evol. 2016;33:1082–93. · DOI
  58. Storey JD, Tibshirani R. Statistical significance for genomewide studies. Proc Natl Acad Sci U S A. 2003;100:9440–5. · DOI · Paper page
  59. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol. 2005;25:1965–78. · DOI
  60. Frichot E, François O. LEA an R package for Landscape and Ecological Association studies. Methods Ecol Evol. 2015;6:925–9. · DOI
  61. Vilhjálmsson BJ, Nordborg M. The nature of confounding in genome-wide association studies. Nat Rev Genet. 2013;14:1–2. · DOI
  62. Shim H, Chasman DI, Smith JD, Mora S, Ridker PM, Nickerson DA, et al. A multivariate genome-wide association analysis of 10 LDL subfractions, and their response to statin treatment, in 1868 Caucasians. PLoS One. 2015;10:e0120758. · DOI
  63. Grabherr MG, Russell P, Meyer M, Mauceli E, Alföldi J, Di Palma F, et al. Genome-wide synteny through highly sensitive sequence alignment: Satsuma. Bioinformatics. 2010;26:1145–51. · DOI · Paper page
  64. Wang J, Street NR, Scofield DG, PK I. Natural selection and recombination rate variation shape nucleotide polymorphism across the genomes of three related Populus species. Genetics. 2016;202:1185–200. · DOI
  65. Wang Z, Du S, Dayanandan S, Wang D, Zeng Y, Zhang J. Phylogeny reconstruction and hybrid analysis of Populus (Salicaceae) based on nucleotide sequences of multiple single-copy nuclear genes and plastid fragments. PLoS One. 2014;9:e103645. · DOI
  66. Remington DL, Thornsberry JM, Matsuoka Y, Wilson LM, Whitt SR, Doebley J, et al. Structure of linkage disequilibrium and phenotypic associations in the maize genome. Proc Natl Acad Sci U S A. 2001;98:11479–84. · DOI
  67. Szpiech ZA, Hernandez RD. Selscan an efficient multi-threaded program to perform EHH-based scans for positive selection. Mol Biol Evol. 2014;31:2824–7. · DOI
  68. Tajima F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics. 1989;123:585–95. · DOI
  69. Kim Y, Stephan W. Detecting a local signature of genetic hitchhiking along a recombining chromosome. Genetics. 2002;160:765–77. · DOI
  70. DeGiorgio M, Huber CD, Hubisz MJ, Hellmann I, Nielsen R. SweepFinder2: increased sensitivity, robustness and flexibility. Bioinformatics. 2016;32:1895–7. · DOI
  71. Huber CD, DeGiorgio M, Hellmann I, Nielsen R. Detecting recent selective sweeps while controlling for mutation rate and background selection. Mol Ecol. 2016;25:142–56. · DOI
  72. Ewing G, Hermisson J. MSMS a coalescent simulation program including recombination, demographic structure and selection at a single locus. Bioinformatics. 2010;26:2064–5. · DOI
  73. Ingvarsson PK. Multilocus patterns of nucleotide polymorphism and the demographic history of Populus tremula. Genetics. 2008;180:329–40. · DOI
  74. Xu M, Zang B, Yao HS, Huang MR. Isolation of high quality RNA and molecular manipulations with various tissues of Populus. Russ J Plant Physiol. 2009;56:716–9. · DOI
  75. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) Method. Methods. 2001;25:402–8. · DOI · Paper page
  76. Michelson IH, Ingvarsson PK, Robinson KM, Edlund E, Eriksson ME, Nilsson O, et al. Autumn senescence in aspen is not triggered by day length. Physiol Plant. 2018;162:123–34. · DOI
  77. Wang J, Ding J, Tan B, Robinson KM, Michelson IH, Johansson A, et al. A major locus controls local adaptation and adaptive life history variation in a perennial plant. NCBI SRA; 2017. BioProject Accession: PRJNA297202. https://www.ncbi.nlm.nih.gov/bioproject/PRJNA297202/ . Accessed 4 Oct 2016. · DOI

Cited by

Sorted by citations

  • Genomics of plant speciation

    Bock, D. G., Cai, Z., Elphinstone, C., González-Segovia, E., Hirabayashi, K., Huang, K., Keais, G. L., Kim, A., Owens, G. L., & Rieseberg, L. H. (2023) · Plant Communications · doi:10.1016/j.xplc.2023.100599 · Cited by 84

    “For example, by determining the timing of flowering, homologs of FLOWERING LOCUS T have been shown to facilitate ecotype formation in aspen (Wang et al., 2018) and sunflower (Todesco et al.”

Metadata

Authors
Wang, J., Ding, J., Tan, B., Robinson, K. M., Michelson, I. H., Johansson, A., Nystedt, B., Scofield, D. G., Nilsson, O., Jansson, S., Street, N. R., & Ingvarsson, P. K.
Affiliations
  • Umeå Plant Science Centre (SE)
  • Swedish University of Agricultural Sciences (SE)
  • Stora Enso (Sweden) (SE)
  • Uppsala University (SE)
Corresponding author
  • Wang, Jing
  • Ingvarsson, Pär K.
Venue
Genome Biology
Published
2018-06-04
Volume
19
Issue
1
Pages
72-72
ISSN
  • 1465-6906 (ISSN-L)
  • 1474-760X
OpenAlex
W2805786695
Cited by
145
References
4
Citations by year
2026: 9 · 2025: 11 · 2024: 14 · 2023: 15 · 2022: 46 · 2021: 20 · 2020: 13 · 2019: 13 · 2018: 4
FWCI
7.80
Type
journal article
Language
en
Open access
Locations
  • Genome biology (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DiVA at Umeå University (Umeå University) (submittedVersion, other-oa)
  • Uppsala University Publications (Uppsala University) (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by-nc-nd)
Funders
  • Vetenskapsrådet
  • Knut och Alice Wallenbergs Stiftelse
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
Keywords
local adaptation, Populus tremula, dormancy, growth cessation, latitudinal gradient, selective sweeps, genetic architecture, gene expression, cold adaptation, postglacial colonization
MeSH terms
Life History Traits, Adaptation, Physiological, Phenotype, Plants, Genetic Variation, Genes, Plant, Genome, Plant, Populus, Genetic Loci

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review