Decomposing Additive Genetic Variance Revealed Novel Insights into Trait Evolution in Synthetic Hexaploid Wheat

Abstract

Whole genome duplication (WGD) is an evolutionary phenomenon, which causes significant changes to genomic structure and trait architecture. In recent years, a number of studies decomposed the additive genetic variance explained by different sets of variants. However, they investigated diploid populations only and none of the studies examined any polyploid organism. In this research, we extended the application of this approach to polyploids, to differentiate the additive variance explained by the three subgenomes and seven sets of homoeologous chromosomes in synthetic allohexaploid wheat (SHW) to gain a better understanding of trait evolution after WGD. Our SHW population was generated by crossing improved durum parents (Triticum turgidum; 2n = 4x = 28, AABB subgenomes) with the progenitor species Aegilops tauschii (syn Ae. squarrosa, T. tauschii; 2n = 2x = 14, DD subgenome). The population was phenotyped for 10 fungal/nematode resistance traits as well as two abiotic stresses. We showed that the wild D subgenome dominated the additive effect and this dominance affected the A more than the B subgenome. We provide evidence that this dominance was not inflated by population structure, relatedness among individuals or by longer linkage disequilibrium blocks observed in the D subgenome within the population used for this study. The cumulative size of the three homoeologs of the seven chromosomal groups showed a weak but significant positive correlation with their cumulative explained additive variance. Furthermore, an average of 69% for each chromosomal group's cumulative additive variance came from one homoeolog that had the highest explained variance within the group across all 12 traits. We hypothesize that structural and functional changes during diploidization may explain chromosomal group relations as allopolyploids keep balanced dosage for many genes. Our results contribute to a better understanding of trait evolution mechanisms in polyploidy, which will facilitate the effective utilization of wheat wild relatives in breeding.

Boosting Genetic Gain in Allogamous Crops via Speed Breeding and Genomic Selection

“…Thus, the diversity within crosses is essential. Other strategies to reduce inbreeding involve importing cultivars from outside the breeding program (Reif et al, 2005) or introducing new variation from wild relatives (Harlan, 1976; Hajjar and Hodgkin, 2007; Jighly et al, 2018a; Jighly et al, 2019). However, introducing new non-elite materials may reduce the genetic gain on the short term but improve it on the long term.…”

Insights into population genetics and evolution of polyploids and their ancestors

“…Similar to migration effect in diploids, speciation also leads to larger LD blocks and higher relatedness (Ardlie et al., ) (Supporting Information Tables S1 and S2). Although it is unlikely that such high geneflow rates are observed in nature, for example, the 0.01 simulated here, similarly high gene flow has been induced in laboratories for many allopolyploids such as wheat (e.g., Jighly, Joukhadar, Singh, & Ogbonnaya, ; Jighly et al., ) and autopolyploids such as potato (Stupar et al., ) to introduce new variation to the breeding populations. PolySim allows for additional gene flow during the expansion of newly emerged polyploid populations, which had not been tested previously.…”

Subgenome contributions to quantitative genetic variation in bread wheat and durum wheat populations

“…• Wheat genome markers were used to estimate subgenome contributions to variation • Contributions of the A, B, & D subgenomes varied for different traits & populations • The square of subgenome predictive ability was a useful indicator of contribution • In diverse lines, marker nonindependence in different subgenomes was a hindrance mosomes (Visscher et al, 2007;Yang et al, 2011). Single nucleotide polymorphism (SNP) markers located in the A, B, and D subgenomes have been used to partition the total genetic variance into subgenome genetic variances in bread wheat (Santantonio, Jannink, & Sorrells, 2019) and in synthetic wheat (Jighly, Joukhadar, Singh, & Ogbonnaya, 2018). In a collection of soft winter wheat lines, subgenome additive variance was largest for the B genome for yield, test weight, and plant height and was largest for the D genome for heading date (Santantonio et al, 2019).…”

“…In a collection of soft winter wheat lines, subgenome additive variance was largest for the B genome for yield, test weight, and plant height and was largest for the D genome for heading date (Santantonio et al, 2019). In a collection of synthetic hexaploid wheat lines, subgenome additive variance for traits related to biotic and abiotic stress tolerance was largest for the D genome (Jighly et al, 2018). Genomewide prediction has become routine in multiple crop species (Bernardo, 2020a).…”