A University of London-led team describes new coding variants associated with a heart trait called cardiac conduction. Using exome-chip-based genotype profiles from nearly 78,000 individuals of European ancestry and nearly 7,700 individuals with African ancestry, the team searched for functional variants contributing to a heart electrical activity measurement known as the QRS interval duration, which provides insights into heart failure or sudden cardiac death. The analysis unearthed dozens of suspicious variants at 28 loci that were tested in another 111,874 European individuals from the UK Biobank and DeCode datasets. After the validation step, the investigators were left with 10 new QRS duration-linked loci, including a site in the secreted metalloprotease enzyme-coding gene called ADAMTS6 that they explored further.
Researchers from Ghent University and elsewhere compare the performance of 25 differential gene expression analysis pipelines, concentrating on long, non-coding RNA (lncRNA) and low abundance messenger RNAs. The team used half a dozen authentic RNA-seq datasets, along with simulated data, to profile 15 performance metrics. In the process, the authors found that roughly half of the approaches led to a rise in false-positive results, "making these methods unreliable for [differential expression] analysis and jeopardizing reproducible science." Likewise, the results suggest that the tools tested "exhibit inferior performance for lncRNAs compared to mRNAs across all simulated scenarios and benchmark RNA-seq datasets."
A team from the University of Washington explores enhancer evolution in primates, starting from a set active enhancer-related H3K27ac peaks detected through prior chromatin immunoprecipitation sequencing that appeared to found in humans but missing in non-primate mammals. After whittling this enhancer set down to 1,015 candidate hominoid-specific enhancers with additional annotation data, the researchers turned to STARR-seq to assess regulatory activity by orthologs from 11 primates and nine computationally reconstructed ancestral sequences. The approach highlighted 84 enhancer changes with functional consequences, the authors note, and helped untangle "how the accumulation of mutations impacts enhancer activity across the [primate] phylogeny."