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Genome Research Studies Address GBM Genome Architecture, Allele-Specific Selection Effects, More

A team from the University of Calgary, University of Toronto, and elsewhere takes a look at genomic architecture in the brain cancer glioblastoma (GBM). Using in situ Hi-C, RNA sequence data, and other approaches, the researchers developed three-dimensional maps of GBM stem cells from three individuals with the disease, focusing on interactions going down to a resolution below 5,000 bases and their effects on gene regulation and expression. Their structural genomic study highlighted DNA looping differences in cells from one GBM patient to the next, and provided clues to the interaction hubs that "stemness" genes contribute to in GBM stem cells. "Our results demonstrate that integrated structural genomics datasets can be employed to rationally identify therapeutic vulnerabilities in self-renewing cells," the authors write.

A pair of researchers from the Cold Spring Harbor Laboratory's Simons Center for Quantitative Biology presents a predictive computational approach to estimate the fitness effects of known or possible SNPs. The method — called "Linear Allele-Specific Selection Inference," or LASSIE — combines machine learning-based genomic prediction with population genetics, the team says. Using LASSIE, the investigators mapped allele-specific selection coefficients for variants in protein-coding portions of the genome in 51 high-coverage genome sequences, for instance, uncovering more than 1,100 central nervous system expressed genes or autism spectrum disorder-related genes that appeared to be subject to strong negative selection. Based on their results, the authors conclude that "estimated selection coefficients are highly predictive of inherited pathogenic variants and cancer driver mutations, outperforming state-of-the art variant prioritization methods." 

Finally, a St. Jude Children's Research Hospital-led team explores potential circadian clock gene contributions to longevity in long-lived Drosophila melanogaster populations. After sequencing the genomes of fruit flies from lines selected for pronounced longevity, the researchers compared those sequences to those from flies in D. melanogaster parental and reference genotypes, incorporating transcriptomic and proteomic data to see genetic variants, gene expression shifts, and transcription factors involved in longevity. Their results "indicate that the muscle circadian clock is important for longevity, and that circadian gene variants contribute to the evolutionary divergence in longevity across populations."