In this week's Nature, a group from New York University School of Medicine reports a new method to detect extremely rare genetic variants in any region of interest in a population of cells and avoid the limitations of polymerase chain reaction-based approaches. Called maximum-depth sequencing (MDS), the technique involves synthesizing unique barcodes directly onto the region of interest of a genomic DNA molecule then copying that molecule using linear amplification, which increases yield and decreases polymerase and sequencing errors. The investigators demonstrate MDS by measuring the locus-specific mutation rates in Escherichia coli and showing that they vary across the genome by at least an order of magnitude.
And in Nature Genetics, a team of Japanese scientists describes the use of whole-genome sequencing in a genome-wide association study to identify genes that influence agronomic traits in rice. While GWASs are useful in finding genes associated with traits of interest, they can be limited by population structure and the large extent of linkage disequilibrium. To overcome these issues, the researchers based their GWAS on whole-genome sequencing, followed by the screening of candidate genes based on the estimated effect of nucleotide polymorphisms. They identified four new rice genes associated with agronomic traits such as panicle number, some of which were undetectable by standard SNP analysis.