Selection signatures across seven decades of hard winter wheat breeding in the Great Plains of the United States

Abstract

Classical plant breeding has been instrumental in changing the genetic makeup of crop plants for better ecological adaptation and improved quality. This paper provides insights of the genomic changes effected in hard winter wheat (Triticum aestivum L.) through decades of breeding and selection in the Great Plains of the United States. Population structure and differentiation analyses were conducted on 185 wheat cultivars released from 1943 to 2013. Cultivars were grouped into four distinct clusters using discriminant analysis of principal components (DAPC). One of the clusters was unique in that 15 out of the 18 individuals were recent releases (2000-2010), while 12 of the 18 shared the cultivar 'Jagger' in their genetic background. Jagger carries a 2NS/2AS translocation segment from Aegilops ventricosa, an important segment for resistance to several foliar diseases. Using the outlier approach, Wright's population fixation index (Fst) identified 450 loci that were directionally selected. The largest signature of selection was found on chromosome 2A. Genetic diversity was high while the inbreeding coefficient was low, indicating extensive hybridization and germplasm exchange among breeding programs within the region. Foliar disease pressure and selection for resistance helped shape the microevolution of wheat in the southern Great Plains. The results showed that high genetic diversity remains in hard winter wheat cultivars adapted to the Great Plains of the USA, and modern plant breeding did not cause any sizable reduction in genetic diversity of the crop in this region.

Selection signatures in the CIMMYT International Elite Spring and Semi‐arid Wheat Yield Trials

“…(N'Diaye et al., 2018) with clear differences in pedigree and breeding program sources in Canada involving relatively little introduction of new material. Similarly, clear clusters were observed across 185 commercially released cultivars across the Great Plains in the United States (Ayalew et al., 2020). The CIMMYT is known for the consistent use of diverse parents and substantial genetic resources (e.g., landraces and synthetic hexaploid wheat) that have been vital to meet the requirements of global adaptation and enable the adoption of newly developed lines by cooperating wheat research programs globally (Dreisigacker et al., 2004; Rosyara et al., 2019).…”

“…Cultivars with the CIMMYT line 'Milan' in their pedigree are known to contain the 2NS translocation, which recently also showed high levels of resistance to wheat blast under field conditions (Cruz et al, 2016;Juliana et al, 2018). Interestingly the same genomic region was also identified as selection sweeps in the studies by (Ayalew et al, 2020;Dadshani et al, 2021). On chromosome 4, the waxy gene Wx-B1 was physically located close to markers under temporal selection.…”

“…For instance, Dreisigacker et al (2012) looked at the ESWYT and found instability using diversity array tech-nology (DArT) markers and the software STRUCTURE on determining that the optimal number of K subpopulations also suggested strong relatedness of ESWYT germplasm. Another study using the same DArT marker technology and software determined the population stratification within individual ESWYT trials and found an overall pattern of unstructured populations (Crossa et al, 2007) (Ayalew et al, 2020). The CIMMYT is known for the consistent use of diverse parents and substantial genetic resources (e.g., landraces and synthetic hexaploid wheat) that have been vital to meet the requirements of global adaptation and enable the adoption of newly developed lines by cooperating wheat research programs globally (Dreisigacker et al, 2004;Rosyara et al, 2019).…”

Genotyping-by-sequencing and genomic selection applications in hexaploid triticale

“…Information in the first three PCs showed structuring patterns emerging, but it also did not use the larger proportion of genomic information in remaining PCs ( Figure 2 ). Therefore, PCs were further analyzed using DAPC to extract more information from nearly all of the PCs ( Jombart et al 2010 ; Ayalew et al 2020 ). In addition to the larger amount of information used in DAPC, it enables to interpret loading of individual markers along discriminant axes (Supplementary Figure S3).…”

Advances in identifying GM plants: toward the routine detection of ‘hidden’ and ‘new’ GMOs

“…GWAS studies allow the analysis of the many past events that have affected genomes. New elements are expected to become available with the sequencing in progress (1000 and 10 000 genome projects) followed by the 1000 epigenomes already proposed (Ashapkin et al, 2016;Koch, 2016 evolutionary selection signatures 16 can then differentiate between natural and artefactual mutations (Ayalew et al, 2020;Stephan, 2019;Xie et al, 2015). More generally speaking, the cell lines can be distinguished by the inheritance of certain traits almost independently of (back)crosses (Bertheau, 2019;Braatz et al, 2017;Burian et al, 2016;McKenna et al, 2016;Yuan et al, 2018a,b).…”