Labelling Selective Sweeps Used in Durum Wheat Breeding from a Diverse and Structured Panel of Landraces and Cultivars

Abstract

A panel of 387 durum wheat genotypes including Mediterranean landraces and modern cultivars was characterized with 46,161 diversity arrays technology (DArTseq) markers. Analysis of population structure uncovered the existence of five subpopulations (SP) related to the pattern of migration of durum wheat from the domestication area to the west of the Mediterranean basin (SPs 1, 2, and 3) and further improved germplasm (SPs 4 and 5). The total genetic diversity (HT) was 0.40 with a genetic differentiation (GST) of 0.08 and a mean gene flow among SPs of 6.02. The lowest gene flow was detected between SP 1 (presumably the ancient genetic pool of the panel) and SPs 4 and 5. However, gene flow from SP 2 to modern cultivars was much higher. The highest gene flow was detected between SP 3 (western Mediterranean germplasm) and SP 5 (North American and European cultivars). A genome wide association study (GWAS) approach using the top ten eigenvectors as phenotypic data revealed the presence of 89 selective sweeps, represented as quantitative trait loci (QTL) hotspots, widely distributed across the durum wheat genome. A principal component analysis (PCoA) using 147 markers with −log10 p >5 identified three regions located on chromosomes 2A, 2B and 3A as the main drivers for differentiation of Mediterranean landraces. Gene flow between SPs offers clues regarding the putative use of Mediterranean old durum germplasm by the breeding programs represented in the structure analysis. EigenGWAS identified selective sweeps among landraces and modern cultivars. The analysis of the corresponding genomic regions in the ‘Zavitan’, ‘Svevo’ and ‘Chinese Spring’ genomes discovered the presence of important functional genes including Ppd, Vrn, Rht, and gene models involved in important biological processes including LRR-RLK, MADS-box, NAC, and F-box.

Agronomic, Physiological and Genetic Changes Associated With Evolution, Migration and Modern Breeding in Durum Wheat

“…All landraces except two of them (cultivars “Carlantino” and “Verdiel”) had spring growth habit (Royo et al, 2020 ). The genetic structure of the panel used has been recently described by Soriano et al ( 2021 ) using 46,161 DArTseq markers. A first classification, related to the main historical breeding periods, separated landraces and modern cultivars, but a further analysis structured the collection in five subpopulations (SP) ( Supplementary Table 1 ).…”

“…The MIXED procedure of the SAS statistical package (SAS Institute Inc, Cary, NC, USA) was used with the Kenward-Roger correction due to the unbalanced number of genotypes within subpopulations. Multiple linear regression was performed for the 372 genotypes among the genetic structure coefficients (Soriano et al, 2021 ) and the average values across years of the phenotypic traits using JMP V.14 software (SAS Institute Inc.). To compare mean values of the analyzed traits between landraces and modern cultivars and between subpopulations, the sum of squares of the genotype effect in the ANOVAs was partitioned into differences between the two types of germplasm or subpopulations, and the genotypic variance retained within them, which was used as error term.…”

“…A further study identified 23 marker alleles with a differential frequency in landraces from east and west regions of the Mediterranean Basin, which affected important agronomic traits (Soriano et al, 2018 ). More recently, a GWAS approach employing eigenvectors has been used to identify 89 selective sweeps, represented as QTL hotspots, among landraces and modern cultivars and to quantify gene flow among them (Soriano et al, 2021 ).…”

“…In the present study, we have used a panel of 172 Mediterranean landraces from 21 countries and 200 modern cultivars of diverse origin, previously structured in five genetic subpopulations by Soriano et al ( 2021 ), to: (i) document important quantitative agronomic and physiological attributes differentiating landraces from modern cultivars, (ii) explore the relationship between the genetic structure and the agronomic performance of the accessions included in the collection, and (iii) identify genomic regions controlling agronomic performance that differentiate between the main germplasm pools identified in the panel.…”

Identification of QTL hotspots affecting agronomic traits and high-throughput vegetation indices in rainfed wheat

“…A mixed linear model (MLM) was fitted using a principal component analysis (PCA) matrix with 6 principal components as the fixed effect and a kinship (k) matrix as the random effect (PCA + K model) at the optimum compression level. In addition, the anthesis date was incorporated as a cofactor in the analysis, as reported in previous studies (Crowell et al 2016; Condorelli et al 2018; Soriano et al 2021). Manhattan plots were generated using the R script CMplot (https://github.com/YinLiLin/CMplot).…”