Massive haplotypes underlie ecotypic differentiation in sunflowers
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Massive haplotypes underlie ecotypic differentiation in sunflowers. / Todesco, Marco; Owens, Gregory L.; Bercovich, Natalia; Légaré, Jean Sébastien; Soudi, Shaghayegh; Burge, Dylan O.; Huang, Kaichi; Ostevik, Katherine L.; Drummond, Emily B. M.; Imerovski, Ivana; Lande, Kathryn; Pascual-Robles, Mariana A.; Nanavati, Mihir; Jahani, Mojtaba; Cheung, Winnie; Staton, S. Evan; Muños, Stéphane; Nielsen, Rasmus; Donovan, Lisa A.; Burke, John M.; Yeaman, Sam; Rieseberg, Loren H.
I: Nature, Bind 584, Nr. 7822, 2020, s. 602-607.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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T1 - Massive haplotypes underlie ecotypic differentiation in sunflowers
AU - Todesco, Marco
AU - Owens, Gregory L.
AU - Bercovich, Natalia
AU - Légaré, Jean Sébastien
AU - Soudi, Shaghayegh
AU - Burge, Dylan O.
AU - Huang, Kaichi
AU - Ostevik, Katherine L.
AU - Drummond, Emily B. M.
AU - Imerovski, Ivana
AU - Lande, Kathryn
AU - Pascual-Robles, Mariana A.
AU - Nanavati, Mihir
AU - Jahani, Mojtaba
AU - Cheung, Winnie
AU - Staton, S. Evan
AU - Muños, Stéphane
AU - Nielsen, Rasmus
AU - Donovan, Lisa A.
AU - Burke, John M.
AU - Yeaman, Sam
AU - Rieseberg, Loren H.
N1 - Publisher Copyright: © 2020, The Author(s), under exclusive licence to Springer Nature Limited.
PY - 2020
Y1 - 2020
N2 - Species often include multiple ecotypes that are adapted to different environments1. However, it is unclear how ecotypes arise and how their distinctive combinations of adaptive alleles are maintained despite hybridization with non-adapted populations2–4. Here, by resequencing 1,506 wild sunflowers from 3 species (Helianthus annuus, Helianthus petiolaris and Helianthus argophyllus), we identify 37 large (1–100 Mbp in size), non-recombining haplotype blocks that are associated with numerous ecologically relevant traits, as well as soil and climate characteristics. Limited recombination in these haplotype blocks keeps adaptive alleles together, and these regions differentiate sunflower ecotypes. For example, haplotype blocks control a 77-day difference in flowering between ecotypes of the silverleaf sunflower H. argophyllus (probably through deletion of a homologue of FLOWERING LOCUS T (FT)), and are associated with seed size, flowering time and soil fertility in dune-adapted sunflowers. These haplotypes are highly divergent, frequently associated with structural variants and often appear to represent introgressions from other—possibly now-extinct—congeners. These results highlight a pervasive role of structural variation in ecotypic adaptation.
AB - Species often include multiple ecotypes that are adapted to different environments1. However, it is unclear how ecotypes arise and how their distinctive combinations of adaptive alleles are maintained despite hybridization with non-adapted populations2–4. Here, by resequencing 1,506 wild sunflowers from 3 species (Helianthus annuus, Helianthus petiolaris and Helianthus argophyllus), we identify 37 large (1–100 Mbp in size), non-recombining haplotype blocks that are associated with numerous ecologically relevant traits, as well as soil and climate characteristics. Limited recombination in these haplotype blocks keeps adaptive alleles together, and these regions differentiate sunflower ecotypes. For example, haplotype blocks control a 77-day difference in flowering between ecotypes of the silverleaf sunflower H. argophyllus (probably through deletion of a homologue of FLOWERING LOCUS T (FT)), and are associated with seed size, flowering time and soil fertility in dune-adapted sunflowers. These haplotypes are highly divergent, frequently associated with structural variants and often appear to represent introgressions from other—possibly now-extinct—congeners. These results highlight a pervasive role of structural variation in ecotypic adaptation.
U2 - 10.1038/s41586-020-2467-6
DO - 10.1038/s41586-020-2467-6
M3 - Journal article
C2 - 32641831
AN - SCOPUS:85087687619
VL - 584
SP - 602
EP - 607
JO - Nature
JF - Nature
SN - 0028-0836
IS - 7822
ER -
ID: 336610678