Researchers from the European Bioinformatics Institute, Broad Institute, and elsewhere identify previously unappreciated protein-coding using a "Phylogenetic Codon Substitution Frequencies" (PhyloCSF) tool that takes into account evolutionary and sequence conservation clues by lining up genome sequences from several species. Using human, mouse, chicken, fly, worm, and mosquito genome sequences — together with machine learning approaches — the team tracked down and curated dozens of protein-coding genes, along with additional conserved coding sequences and pseudogenes. After lining these genes up against parts of the human genome implicated in prior genome-wide association studies, the authors suggested at least 188 disease-related variants might fall in protein-coding sequences rather than non-coding parts of the genome as previously thought. Based on these and other results, they suggest "PhyloCSF datasets and algorithms will help researchers seeking to interpret these genomes, while our new annotations present exciting loci for further experimental characterization."
A UT Southwestern Medical Center team outlines a droplet digital PCR-based assay it came up with to quantify mitochondrial DNA copy number in individual cells. The high-throughput "droplet digital mitochondrial DNA measurement" (ddMDM) approach makes it possible to discern mtDNA copy number in bulk cell samples or single cells using 96-well plates, the researchers say, adding that it can reportedly produce data from cell lysates without purification steps within a few hours. "ddMDM may be useful for epidemiologic studies, clinical monitoring of mitochondrial diseases, and for much needed studies aimed at understanding the contribution that mtDNA plays in aging and disease," they write, "not only for its role in metabolism but also as a signaling molecule."
Finally, investigators at Stanford University, McGill University, and the University of Montreal present a strategy for teasing gene expression information out of individual cells in formalin-fixed, paraffin-embedded (FFPE) tissue samples using a combination of laser-capture microdissection and Smart-3SEQ. The latter protocol builds on and combines features from earlier RNA sequencing and single-cell RNA-seq methods, the team explains, using targeted sequence tags to quantify transcripts in small or degraded samples. "[S]mart-3SEQ's compatibility with FFPE tissue unlocks an enormous number of archived clinical samples," authors of that paper suggest, "and combined with [laser-capture microdissection], it allows unprecedented studies of small cell populations and single cells isolated by their in situ context."