Molecular confirmation of varietal status in bottle gourd (Lagenaria siceraria) using genotyping-by-sequencing.

Bottle gourd (Lagenaria siceraria) is an important food, medicinal, and utilitarian crop with a large pan-tropical distribution. Two morphologically different types in the siceraria subspecies are sufficiently different to be considered as varieties, but they are assigned into different taxonomic ranks. Genotyping-by-sequencing (GBS) of 95 different accessions from the Nangui Abrogoua University collection was used to confirm the varietal status in bottle gourd. This analysis produced 22 575 single-nucleotide polymorphisms (SNPs). Cluster analyses conducted with 2250 (9.96%) SNPs distinctly separated hard-shelled from soft-shelled types. Analysis of 23 SNPs located in 11 genes coding for traits that differentiate the two types of gourds revealed that genes in the soft-shelled types had about 21% fewer SNPs than genes within hard-shelled gourds, but the latter had more non-synonymous SNPs. Cluster analyses conducted with the 23 SNPs fitted well with the structure defined by the 2250 SNPs, suggesting the implication of these SNPs in the varietal differentiation of bottle gourd. These nucleotide changes along with the genetic relationships between the accessions provide molecular proof supporting the status of two varieties. To prevent the confusion inherent in the use of synonyms and homonyms in bottle gourd, we suggest the terms hard-shelled and soft-shelled to designate, respectively, the varieties used as utensils and those grown for their edible seeds.

A unified mixed-model method for association mapping that accounts for multiple levels of relatedness.

As population structure can result in spurious associations, it has constrained the use of association studies in human and plant genetics. Association mapping, however, holds great promise if true signals of functional association can be separated from the vast number of false signals generated by population structure. We have developed a unified mixed-model approach to account for multiple levels of relatedness simultaneously as detected by random genetic markers. We applied this new approach to two samples: a family-based sample of 14 human families, for quantitative gene expression dissection, and a sample of 277 diverse maize inbred lines with complex familial relationships and population structure, for quantitative trait dissection. Our method demonstrates improved control of both type I and type II error rates over other methods. As this new method crosses the boundary between family-based and structured association samples, it provides a powerful complement to currently available methods for association mapping.