Abstract
The prevalence of genetic diversity in switchgrass germplasm can be exploited to capture favorable alleles that increase its range of adaptation and biomass yield. The objectives of the study were to analyze the extent of polymorphism and patterns of segregation distortion in two F1 populations and use the linkage maps to locate QTL for biomass yield. We conducted genotyping-by-sequencing on two populations derived from crosses between the allotetraploid lowland genotype AP13 (a selection from “Alamo”) and coastal genotype B6 (a selection from PI 422001) with 285 progeny (AB population) and between B6 and the allotetraploid upland VS16 (a selection from “Summer”) with 227 progeny (BV population). As predictable from the Euclidean distance between the parents, a higher number of raw variants was discovered in the coastal × upland BV cross (6 M) compared to the lowland × coastal AB cross (2.5 M). The final number of mapped markers was 3,107 on the BV map and 2,410 on the AB map. More segregation distortion of alleles was seen in the AB population, with 75% distorted loci compared to 11% distorted loci in the BV population. The distortion in the AB population was seen across all chromosomes in both the AP13 and B6 maps and likely resulted from zygotic or post-zygotic selection for increased levels of heterozygosity. Our results suggest lower genetic compatibility between the lowland AP13 and the coastal B6 ecotype than between B6 and the upland ecotype VS16. Four biomass QTLs were mapped in the AB population (LG 2N, 6K, 6N, and 8N) and six QTLs in the BV population [LG 1N (2), 8N (2), 9K, and 9N]. The QTL, with the largest and most consistent effect across years, explaining between 8.4 and 11.5% of the variation, was identified on 6N in the AP13 map. The cumulative effect of all the QTLs explained a sizeable portion of the phenotypic variation in both AB and BV populations and the markers associated with them may potentially be used for the marker-assisted improvement of biomass yield. Since switchgrass improvement is based on increasing favorable allele frequencies through recurrent selection, the transmission bias within individuals and loci needs to be considered as this may affect the genetic gain if the favorable alleles are distorted.
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