Pennsylvania State University's Marylyn Ritchie and her colleagues report in PLOS Genetics that the natural frequency of rare variants is a common confounder of genetic analyses. The researchers applied a collapsing method called BioBin to whole-genome population data from individuals from 1000 Genomes Project Phase I data to search for aggregate differences in low frequency variation between populations. "[W]e were able to expose the magnitude of low frequency population stratification between all populations available in 1000 Genomes Project Phase I release across multiple interesting biological features," Ritchie and her colleagues write. "The magnitude of low frequency stratification appeared to be dependent on the functional location of the variation and the genomic size of the pertinent features.
Also in PLOS Genetics, Harvard University researchers present their calculation of the so-called missing heritability through a variance components analysis. They examined and quantified the heritability explained by SNPs at known GWAS loci in nine diseases from the WTCCC1 and WTCCC2 datasets. From this, they observed an increase in local heritability, likely due to multiple common causal variants at an average locus. Additionally, they calculated that, on average, all SNPs at known GWAS loci explain 1.29 fold more heritability than GWAS-associated SNPs "Our results have important implications for fine-mapping study-design as well as the broader understanding of disease architecture and allelic heterogeneity," the researchers add.
Over in PLOS One, a trio of researchers from Nanjing Agricultural University in China reports that it uncovered a number of alleles associated with lint yield in Chinese upland cotton cultivars. By constructing an association-mapping panel of 356 Upland cotton cultivars grown in three different environments and that were genotyped, the researchers found 41 associations and 23 favorable alleles. "The QTLs detected in this study will be helpful in further understanding the genetic basis of lint yield and its components, and the favorable alleles may facilitate future high-yield breeding by genomic selection in Upland cotton," the trio adds.