Researchers from the Wellcome Sanger Institute, Oslo University, and elsewhere retrace recombination in Neisseria meningitidis, using genome sequences for thousands of meningococcal isolates spanning a serogroup A vaccine program between 2009 and 2012. Based on some 2,839 meningococcal genomes collected before, during, and after this vaccination effort, the team saw dynamic N. meningitidis genomes marked by high rates of recombination and gene swapping, though the extent of this recombination varied between lineages. "In general, we show the importance of recombination in the evolution of a geographically expansive population with deep population structure in a short timescale," the authors report, noting that "[t]his has important consequences for our ability to both foresee the outcomes of vaccination programs and, using surveillance data, predict when lineages of the meningococcus are likely to become a public health concern."
A team from China, Denmark, and the US searches for protein-truncating variants with potential ties to psoriasis in tens of thousands of individuals from China. Based on targeted sequences for more than 1,300 genes in 9,434 individuals of Han Chinese ancestry with psoriasis and more than 10,500 unaffected controls, the researchers found 8,720 protein-truncating variants, including thousands of variants not described in the past. The protein-truncating variants appeared to be over-represented in the psoriasis cases, they report, noting that population differentiation was particularly pronounced for 18 protein-truncating variants in more than a dozen genes.
Investigators at the J. Craig Venter Institute and other centers in the US and Netherlands report on an NS-Forest 2.0 machine learning method for analyzing single-cell RNA sequence or single-nucleus RNA-seq data to search for marker genes. The algorithm combines non-linear random forest feature selection and binary expression score features to focus in on potential expression markers, the team notes — an approach they applied to get single-nucleus transcriptome profiles from post-mortem and surgically resected samples from the middle temporal gyrus of the human brain. "The marker genes selected provide an expression barcode that serves as both a useful tool for downstream biological investigation and the necessary and sufficient characteristics for semantic cell type definition," the authors note, adding that "use of NS-Forest to identify marker genes for human brain middle temporal gyrus cell types reveals the importance of cell signaling and non-coding RNAs in neuronal cell type identity."