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Nature Papers Present Computational Approach to Detect Mosaic Mutations, Cobra Genome

Researchers from Harvard University and Boston Children's Hospital have developed a computational method for detecting mosaic mutations in sequencing data. While such mutations may play a significant role in disease, their detection in genome sequencing data is challenging, in part because they tend to be present in only a small number of cells, the scientists write in Nature Biotechnology. To address this issue, they developed MosaicForecast, a machine-learning method that uses read-based phasing and read-level features to accurately detect mosaic single-nucleotide variants and indels. Using single-cell sequencing and targeted sequencing, the team validated 80 percent to 90 percent of mosaic single-nucleotide variants and 60 percent to 80 percent of indels detected in human brain whole-genome sequencing data. "Identification of mosaic mutations in various nontumor tissues by the proposed method will help gain insights into the origin and propagation of somatic mutations in development and disease," they write.

The genome of the venomous Indian cobra Naja naja is published in Nature Genetics this week, providing insights into the genetics underlying venom biology and potential avenues for the development of new antivenom drugs. In the study, a team led by scientists from Genentech and the SciGenom Research Foundation report a de novo near-chromosomal genome assembly of the snake with a scaffold N50 of 223.35 Mb, with 19  scaffolds containing 95 percent of the genome. Among the findings are 12,346 venom gland-expressed genes constituting the "venom-ome," which includes 139  genes from 33  toxin families. Of these 139 genes, 19  are venom-ome-specific toxins that show venom gland-specific expression and likely encode the minimal core venom effector proteins. According to the researchers, the work will enable evolutionary studies of venomous organisms and help in the development of antivenom agents, as well as drugs for hypertension, pain, and other disorders. GenomeWeb has more on this study, here.


Harvard University and Boston Children's Hospital Seq, Informatics, single- cll, applied, gene expression, genetic research, Asia, North America

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