Population sequencing data reveal a compendium of mutational processes in human germline

Mechanistic processes underlying human germline mutations remain largely unknown.Variation in mutation rate and spectra along the genome is informative about the biological mechanisms. We statistically decompose this variation into separate processes using a blind source separation technique. The analysis of a large-scale whole genome sequencing dataset (TOPMed) reveals nine processes that explain the variation in mutation properties between loci. Seven of these processes lend themselves to a biological interpretation. One process is driven by bulky DNA lesions that resolve asymmetrically with respect to transcription and replication. Two processes independently track direction of replication fork and replication timing. We identify a mutagenic effect of active demethylation primarily acting in regulatory regions. We also demonstrate that a recently discovered mutagenic process specific to oocytes can be localized solely from population sequencing data. This process is spread across all chromosomes and is highly asymmetric with respect to the direction of transcription, suggesting a major role of DNA damage

Publisher Correction:Germline de novo mutation clusters arise during oocyte aging in genomic regions with high double-strand-break incidence (Nature Genetics, (2018), 50, 4, (487-492), 10.1038/s41588-018-0071-6)

In the HTML version of the article originally published, the figures for Supplementary Figures 1–15 were incorrect and did not match the correct figures in the PDF of Supplementary Text and Figures. The error has been corrected in the HTML version of the article

Author Correction: Parent-of-origin-specific signatures of de novo mutations.

In the version of this article published, the P values for the enrichment of single mutation categories were inadvertently not corrected for multiple testing. After multiple-testing correction, only two of the six mutation categories mentioned are still statistically significant. To reflect this, the text More specifically, paternally derived DNMs are enriched in transitions in A[.]G contexts, especially ACG\u3eATG and ATG\u3eACG (Bonferroni-corrected P = 1.3 × 1

Human genomics. The human transcriptome across tissues and individuals

Transcriptional regulation and posttranscriptional processing underlie many cellular and organismal phenotypes. We used RNA sequence data generated by Genotype-Tissue Expression (GTEx) project to investigate the patterns of transcriptome variation across individuals and tissues. Tissues exhibit characteristic transcriptional signatures that show stability in postmortem samples. These signatures are dominated by a relatively small number of genes—which is most clearly seen in blood—though few are exclusive to a particular tissue and vary more across tissues than individuals. Genes exhibiting high interindividual expression variation include disease candidates associated with sex, ethnicity, and age. Primary transcription is the major driver of cellular specificity, with splicing playing mostly a complementary role; except for the brain, which exhibits a more divergent splicing program. Variation in splicing, despite its stochasticity, may play in contrast a comparatively greater role in defining individual phenotypes

Germline de novo mutation clusters arise during oocyte aging in genomic regions with high double-strand-break incidence

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