A Chinese Academy of Sciences-led team takes a look at blood transcriptomes profiles in samples from dozens of centenarians and their family members. The researchers did RNA sequencing on peripheral white blood cell samples from 76 from China's Hainan province, along with samples from 41 centenarian spouses, and 54 children of centenarians. Their results suggest that genes from the autophagy and lysosomal pathway are among those with the most pronounced expression differences in the exceptionally long-lived individuals relative to their loved ones. "[W]e provide evidence demonstrating that the autophagy-lysosomal function is significantly enhanced in [centenarians]," the authors report, noting that other longevity-linked genes turned up as well.
Researchers from the Ontario Institute for Cancer Research and the University of Toronto report on a role for PRDM9 expression across tumors from dozens of cancer types. Using available RNA sequence data nearly 1,900 tumor and hundreds of matched normal samples from the Cancer Genome Atlas and the Pan-Cancer Analysis of Whole Genomes projects, the team saw enhanced expression of the chromatin binding protein-coding PRDM9 gene in tumors from 32 cancer types, leading to altered expression of genes involved in meiosis and other processes. Those involved say the study "is the first to provide evidence of an association between aberrant expression of the meiosis-specific gene PRDM9 with genomic instability in cancer."
Finally, a University of California, San Diego, team describes a computational method called adVNTR that is designed for genotyping specific variable tandem number repeats (VNTR) based on whole-genome sequence or exome sequence data. Along with their description of the tool, which takes repeat unit counts and other features into account, the researchers applied adVNTR to simulated and real sequence data generated with short- or long-read technologies. "Although existing tools recognize VNTR carrying sequence, genotyping VNTRs … from whole-genome sequencing reads remains challenging," the authors write, explaining that adVNTR "uses hidden Markov models to model each VNTR, count repeat units, and detect sequence variation."