Genetic relatedness of previously Plant-Variety-Protected commercial maize inbreds

Abstract

The emergence of high-throughput, high-density genotyping methods combined with increasingly powerful computing systems has created opportunities to further discover and exploit the genes controlling agronomic performance in elite maize breeding populations. Understanding the genetic basis of population structure in an elite set of materials is an essential step in this genetic discovery process. This paper presents a genotype-based population analysis of all maize inbreds whose Plant Variety Protection certificates had expired as of the end of 2013 (283 inbreds) as well as 66 public founder inbreds. The results provide accurate population structure information and allow for important inferences in context of the historical development of North American elite commercial maize germplasm. Genotypic data was obtained via genotyping-by-sequencing on 349 inbreds. After filtering for missing data, 77,314 high-quality markers remained. The remaining missing data (average per individual was 6.22 percent) was fully imputed at an accuracy of 83 percent. Calculation of linkage disequilibrium revealed that the average r2 of 0.20 occurs at approximately 1.1 Kb. Results of population genetics analyses agree with previously published studies that divide North American maize germplasm into three heterotic groups: Stiff Stalk, Non-Stiff Stalk, and Iodent. Principal component analysis shows that population differentiation is indeed very complex and present at many levels, yet confirms that division into three main sub-groups is optimal for population description. Clustering based on Nei’s genetic distance provides an additional empirical representation of the three main heterotic groups. Overall fixation index (FST), indicating the degree of genetic divergence between the three main heterotic groups, was 0.1361. Understanding the genetic relationships and population differentiation of elite germplasm may help breeders to maintain and potentially increase the rate of genetic gain, resulting in higher overall agronomic performance.

Reimagining Maize Inbred Potential: Identifying Breeding Crosses Using Genetic Variance of Simulated Progeny

“…Distribution across heterotic groups (HGs) shows 48 inbreds in the Iodent HG, 139 in the non‐stiff stalk HG, and 99 in the stiff stalk HG. Further information about the inbreds used in this study is found in Supplemental Tables S1 and S2, and in Beckett et al (2017). All 285 inbreds were test crossed to PHP02, an ex‐PVP inbred developed by Pioneer Hi‐Bred and located in the Iodent HG.…”

“…The genotypic dataset is identical to that used in Beckett et al (2017). Briefly, the data came from two different genotype‐by‐sequencing (GBS) runs, with single nucleotide polymorphism (SNP) calls aligned to the B73v2 reference genome.…”

Diversity and heterotic patterns in North American proprietary dent maize germplasm

“…Nelson et al (2008) found that 92 ex-PVP inbreds separated into six primary genetic clusters founded by inbreds B73, B37, A632 (derived from B14), Oh43, PH207, and Mo17. Recent studies with larger sets of ex-PVP inbreds and single nucleotide polymorphisms (SNPs) continue to support the primary heterotic pools forming subpopulations represented best by the B14, B37, B73, Oh43, Iodent, Iodent Mixed, Lancaster, and Mixed populations (Beckett et al, 2017).…”

“…This set of materials represents commercialized elite proprietary germplasm protected prior to 1997. In addition, eight public inbreds (B14, B37, B73, B84, H99, Mo17, Oh07, and Oh43) were included for reference based on previous studies of key public founder inbreds (Beckett et al, 2017;Melchinger & Gumber, 1998;Mikel & Dudley, 2006;Nelson et al, 2008;Troyer, 1999).…”

“…With ∼750 new ex-PVP inbreds becoming publicly available by 2028, the task of test-crossing new materials against multiple testers to confidently sort germplasm would be daunting for public and small-share breeding programs. Rather, genotyping new germplasm using low-cost molecular markers and implementing genomic tools, such as those outlined in this paper, have the potential to expedite the process of sorting germplasm into established heterotic patterns (Bari & Carena, 2016;Beckett et al, 2017Beckett et al, , 2019. Through the utilization of admixture and other clustering methods to sort new germplasm into workable families of diversity, researchers can efficiently source new germplasm to initiate or improve existing populations while attempting to maintain the desirable heterotic scheme.…”