Biomedical subjects

Weikai Yan

Publications and source records attributed to Weikai Yan.

3 recordsLinked to original sources

PubMed2025

Global genomic population structure of wild and cultivated oat reveals signatures of chromosome rearrangements.

The genus Avena consists of approximately 30 wild and cultivated oat species. Cultivated oat is an important food crop, yet the broader genetic diversity within the Avena gene pool remains underexplored and underexploited. Here, we characterize over 9000 wild and cultivated hexaploid oat accessions of global origin using genotyping-by-sequencing and explore population structure using multidimensional scaling and population-based clustering methods. We also conduct analyses to reveal chromosome regions associated with local adaptation, sometimes resulting from large-scale chromosome rearrangements. We report four distinct genetic populations within the wild species A. sterilis, a distinct population of cultivated A. byzantina, and multiple populations within cultivated A. sativa. Some chromosome regions associated with local adaptation are also associated with confirmed structural rearrangements on chromosomes 1A, 1C, 3C, 4C, and 7D. This work provides evidence suggesting multiple polyploid origins, multiple domestications, and/or reproductive barriers amongst Avena populations caused by differential chromosome structure.

Avena↗

PubMed2002

Biplot Analysis of Diallel Data.

Diallel crosses have been used in genetic research to determine the inheritance of important traits among a set of genotypes and to identify superior parents for hybrid or cultivar development. Conventional diallel analysis is limited to partitioning the total variation of the data into general combining ability (GCA) of each genotype and specific combining ability (SCA) of each cross. In this paper we formulate a biplot approach for graphical diallel analysis. The biplot is constructed by the first two principal components (PCs) derived from subjecting the tester-centered diallel data to singular value decomposition. It displays the most important entry by tester patterns of the data and allows the following information to be extracted visually: (i) GCA of each genotype; (ii) SCA of each genotype; (iii) groups of parents with similar genetics; and (iv) superior hybrids. In addition, the biplot allows hypotheses to be formulated concerning the genetics of the genotypes. Three published diallel data sets of wheat (Triticum aestivum L.) and maize (Zea mays L.) were used to demonstrate the biplot approach and detailed procedures were provided for constructing and interpreting a biplot.

Journal Article↗

PubMed2002

Biplot Analysis of Test Sites and Trait Relations of Soybean in Ontario.

Superior crop cultivars must be identified through multi-environment trials (MET) and on the basis of multiple traits. The objectives of this paper were to describe two types of biplots, the GGE biplot and the GT biplot, which graphically display genotype by environment data and genotype by trait data, respectively, and hence facilitate cultivar evaluation on the basis of MET data and multiple traits. Genotype main effect plus genotype by environment interaction effect (GGE) biplot analysis of the soybean [Glycine max (L.) Merr.] yield data for the 2800 crop heat unit area of Ontario for MET in the period 1994-1999 revealed yearly crossover genotype by site interactions. The eastern Ontario site Winchester showed a different genotype response pattern from the three southwestern Ontario sites in four of the six years. The interactions were not large enough to divide the area into different mega-environments as when analyzed over years, a single cultivar yielded the best in all four sites. The southwestern site, St. Pauls, was found to always group together with at least one of the other three sites; it did not provide unique information on genotype performance. Therefore, in future cultivar evaluations, Winchester should always be used but St. Pauls can be dismissed. Applying GT biplot to the 1994-1999 multiple trait data illustrated that GT biplots graphically displayed the interrelationships among seed yield, oil content, protein content, plant height, and days to maturity, among other traits, and facilitated visual cultivar comparisons and selection. It was found that selection for seed yield alone was not only the simplest, but also the most effective strategy in the early stages of soybean breeding.

Journal Article↗