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This Week in Cell: Mar 6, 2019

Members of a team led by investigators at the Broad Institute present a mitochondrial DNA mutation-based strategy for teasing out relationships between cell types and lineages in normal and cancerous samples. The researchers demonstrated the veracity of their somatic mtDNA mutation-based "genetic barcode" method, identifying tissue-specific mitochondrial genotypes with diverse tissue samples from hundreds of donors and mutation profiling done with approaches such as single-cell RNA sequencing, single-cell ATAC sequencing, and single-cell Mito-seq. The results suggest that "scRNA- and scATAC-seq provide reliable measurements of mtDNA genetic variation," they report, "and demonstrate how these mutations can be used as endogenous genetic barcodes to retrospectively infer cellular relationships in clonal mixtures of native hematopoietic cells, T lymphocytes, leukemia, and solid tumors."

A Baylor College of Medicine-led team takes a look at molecular mechanisms behind recurrent and sporadic de novo structural variants in the chromosome 17 region 17p11.2. The researchers used array comparative genomic hybridization to search for de novo copy number variants at 17p11.2 in members of 55 parent-child trios, identifying 26 trios with non-recurrent 17p11.2 rearrangements, 19 trios with recurrent CNVs at 17p11.2, and 10 trios without CNVs in the region. With exome sequencing and targeted capture long-read sequencing, the authors searched for corresponding breakpoints, identifying single nucleotide variant clusters, small insertions and deletions, and breakpoint patterns that lined up structural variants stemming from microhomology-mediated break-induced replication (MMBIR). "Our data show an additional mutational burden of MMBIR consisting of hypermutation confined to the locus and manifesting as [single-nucleotide variants] and indels predominantly within genes," they write.

Finally, researchers from Massachusetts General Hospital, the Ludwig Center, and elsewhere explore acute myeloid leukemia (AML) cell types and sub-clones with parallel single-cell RNA sequencing and genotyping on samples from individuals with or without the blood cancer. Using modified nanowell approaches, short-read sequencing, long read sequencing, and machine learning, the team considered expression and mutation clusters formed with 30,700 individual cells from 16 individuals with AML and nearly 7,700 single bone marrow cells from five unaffected controls. The analysis pointed to half a dozen malignant AML cell types, which fell along a gradient of primitive to more differentiated cells that appear to have distinct immune interactions. GenomeWeb has more on the study, here.