Premium
Molecular diversity and landscape genomics of the crop wild relative Triticum urartu across the Fertile Crescent
Author(s) -
Brunazzi Alice,
Scaglione Davide,
Talini Rebecca Fiorella,
Miculan Mara,
Magni Federica,
Poland Jesse,
Enrico Pè Mario,
Brandolini Andrea,
Dell'Acqua Matteo
Publication year - 2018
Publication title -
the plant journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.058
H-Index - 269
eISSN - 1365-313X
pISSN - 0960-7412
DOI - 10.1111/tpj.13888
Subject(s) - crop , diversity (politics) , biology , genomics , geography , genetic diversity , botany , evolutionary biology , ecology , genome , genetics , gene , sociology , anthropology , demography , population
Summary Modern plant breeding can benefit from the allelic variation that exists in natural populations of crop wild relatives that evolved under natural selection in varying pedoclimatic conditions. In this study, next‐generation sequencing was used to generate 1.3 million genome‐wide single nucleotide polymorphisms ( SNP s) on ex situ collections of Triticum urartu L., the wild donor of the A u subgenome of modern wheat. A set of 75 511 high‐quality SNP s were retained to describe 298 T. urartu accessions collected throughout the Fertile Crescent. Triticum urartu showed a complex pattern of genetic diversity, with two main genetic groups distributed sequentially from west to east. The incorporation of geographical information on sampling points showed that genetic diversity was correlated to the geographical distance ( R 2 = 0.19) separating samples from Jordan and Lebanon, from Syria and southern Turkey, and from eastern Turkey, Iran and Iraq. The wild emmer genome was used to derive the physical positions of SNP s on the seven chromosomes of the A u subgenome, allowing us to describe a relatively slow decay of linkage disequilibrium in the collection. Outlier loci were described on the basis of the geographic distribution of the T. urartu accessions, identifying a hotspot of directional selection on chromosome 4A. Bioclimatic variation was derived from grid data and related to allelic variation using a genome‐wide association approach, identifying several marker–environment associations ( MEA s). Fifty‐seven MEA s were associated with altitude and temperature measures while 358 were associated with rainfall measures. The most significant MEA s and outlier loci were used to identify genomic loci with adaptive potential (some already reported in wheat), including dormancy and frost resistance loci. We advocate the application of genomics and landscape genomics on ex situ collections of crop wild relatives to efficiently identify promising alleles and genetic materials for incorporation into modern crop breeding.