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PNAS Papers on Mutation-Phenotype Machine Learning Method, Microviruses, More

Editor's Note: Some of the articles described below are not yet available at the PNAS site, but they are scheduled to be posted this week.

A University of Texas Southwestern Medical Center-led team presents a machine learning approach for matching chemically induced mutations with specific phenotypes in forward genetic studies using a combination of meiotic mapping and machine learning. The "Candidate Explorer" (CE) method brings genetic mapping features together into a score for assessing potential germline mutation-phenotype ties, the investigators say — an approach they used to find more than 2,300 mutations with flow cytometry-based circulating immune cell features in a screen of mutagenized mice. "In the future, the data from other screens will be released for public users of CE to interpret a wide range of phenotypic consequences that emanate from each mutation," the authors note, adding that "biomedically relevant phenotypic screens may ultimately enlighten the study of human phenotype and help to distinguish mechanisms of phenotypes caused by certain alleles."

University of Texas at Austin researchers characterize phage defense mechanisms and other features in small single-stranded viruses from the Microviridae family. Using Escherichia coli bacteria as a host, the team assessed microvirus models containing different genomic segment combinations, uncovering an apparent role for hypervariable pilot protein coding regions in defending against host infection by additional microviruses from other lineages. "Our results emphasize that competition between viruses is a considerable and often overlooked source of selective pressure," the authors report, "and by producing similar evolutionary outcomes in distinct lineages, it underlies the prevalence of hypervariable regions in the genomes of microviruses and perhaps beyond."

A team from France, Germany, and Spain tracks viral infection consequences in bacterial cells, focusing on alterations in Bacillus subtilis cells infected with the SPP1 bacteriophage. With imaging and other experiments done over time on B. subtilis cells infected with a fluorescently tagged version of the phage, the researchers saw signs that SPP1 quickly ramps up DNA content in infected cells, while taking over cell machinery and compartmentalizing viral processes into different parts of the cell's cytoplasm. "This spatial partition responds to the requirements for exponential replication of SPP1 genomes and for the assembly of hundreds of viral particles," they write. "Its similarities to remodeling of the cell nucleus by herpesviruses to invade the cell space were conserved to infect hosts of different domains of life."

The Scan

Genome Sequences Reveal Range Mutations in Induced Pluripotent Stem Cells

Researchers in Nature Genetics detect somatic mutation variation across iPSCs generated from blood or skin fibroblast cell sources, along with selection for BCOR gene mutations.

Researchers Reprogram Plant Roots With Synthetic Genetic Circuit Strategy

Root gene expression was altered with the help of genetic circuits built around a series of synthetic transcriptional regulators in the Nicotiana benthamiana plant in a Science paper.

Infectious Disease Tracking Study Compares Genome Sequencing Approaches

Researchers in BMC Genomics see advantages for capture-based Illumina sequencing and amplicon-based sequencing on the Nanopore instrument, depending on the situation or samples available.

LINE-1 Linked to Premature Aging Conditions

Researchers report in Science Translational Medicine that the accumulation of LINE-1 RNA contributes to premature aging conditions and that symptoms can be improved by targeting them.