@article {145, title = {Population sequencing data reveal a compendium of mutational processes in the human germ line.}, journal = {Science}, volume = {373}, year = {2021}, month = {2021 08 27}, pages = {1030-1035}, abstract = {

Biological mechanisms underlying human germline mutations remain largely unknown. We statistically decompose variation in the rate and spectra of mutations along the genome using volume-regularized nonnegative matrix factorization. The analysis of a sequencing dataset (TOPMed) reveals nine processes that explain the variation in mutation properties between loci. We provide a biological interpretation for seven of these processes. We associate one process with bulky DNA lesions that are resolved asymmetrically with respect to transcription and replication. Two processes track direction of replication fork and replication timing, respectively. We identify a mutagenic effect of active demethylation primarily acting in regulatory regions and a mutagenic effect of long interspersed nuclear elements. We localize a mutagenic process specific to oocytes from population sequencing data. This process appears transcriptionally asymmetric.

}, keywords = {Algorithms, CpG Islands, DNA Damage, DNA Demethylation, DNA Mutational Analysis, DNA Replication, Genetic Variation, Genome, Human, Germ Cells, Germ-Line Mutation, Humans, Long Interspersed Nucleotide Elements, Mutagenesis, Oocytes, Transcription, Genetic}, issn = {1095-9203}, doi = {10.1126/science.aba7408}, author = {Seplyarskiy, Vladimir B and Soldatov, Ruslan A and Koch, Evan and McGinty, Ryan J and Goldmann, Jakob M and Hernandez, Ryan D and Barnes, Kathleen and Correa, Adolfo and Burchard, Esteban G and Ellinor, Patrick T and McGarvey, Stephen T and Mitchell, Braxton D and Vasan, Ramachandran S and Redline, Susan and Silverman, Edwin and Weiss, Scott T and Arnett, Donna K and Blangero, John and Boerwinkle, Eric and He, Jiang and Montgomery, Courtney and Rao, D C and Rotter, Jerome I and Taylor, Kent D and Brody, Jennifer A and Chen, Yii-Der Ida and de Las Fuentes, Lisa and Hwu, Chii-Min and Rich, Stephen S and Manichaikul, Ani W and Mychaleckyj, Josyf C and Palmer, Nicholette D and Smith, Jennifer A and Kardia, Sharon L R and Peyser, Patricia A and Bielak, Lawrence F and O{\textquoteright}Connor, Timothy D and Emery, Leslie S and Gilissen, Christian and Wong, Wendy S W and Kharchenko, Peter V and Sunyaev, Shamil} } @article {103, title = {Multi-Ethnic Genome-Wide Association Study of Decomposed Cardioelectric Phenotypes Illustrates Strategies to Identify and Characterize Evidence of Shared Genetic Effects for Complex Traits.}, journal = {Circ Genom Precis Med}, volume = {13}, year = {2020}, month = {2020 08}, pages = {e002680}, abstract = {

BACKGROUND: We examined how expanding electrocardiographic trait genome-wide association studies to include ancestrally diverse populations, prioritize more precise phenotypic measures, and evaluate evidence for shared genetic effects enabled the detection and characterization of loci.

METHODS: We decomposed 10 seconds, 12-lead electrocardiograms from 34 668 multi-ethnic participants (15\% Black; 30\% Hispanic/Latino) into 6 contiguous, physiologically distinct (P wave, PR segment, QRS interval, ST segment, T wave, and TP segment) and 2 composite, conventional (PR interval and QT interval) interval scale traits and conducted multivariable-adjusted, trait-specific univariate genome-wide association studies using 1000-G imputed single-nucleotide polymorphisms. Evidence of shared genetic effects was evaluated by aggregating meta-analyzed univariate results across the 6 continuous electrocardiographic traits using the combined phenotype adaptive sum of powered scores test.

RESULTS: We identified 6 novels (, and ) and 87 known loci (adaptive sum of powered score test <5{\texttimes}10). Lead single-nucleotide polymorphism rs3211938 at was common in Blacks (minor allele frequency=10\%), near monomorphic in European Americans, and had effects on the QT interval and TP segment that ranked among the largest reported to date for common variants. The other 5 novel loci were observed when evaluating the contiguous but not the composite electrocardiographic traits. Combined phenotype testing did not identify novel electrocardiographic loci unapparent using traditional univariate approaches, although this approach did assist with the characterization of known loci.

CONCLUSIONS: Despite including one-third as many participants as published electrocardiographic trait genome-wide association studies, our study identified 6 novel loci, emphasizing the importance of ancestral diversity and phenotype resolution in this era of ever-growing genome-wide association studies.

}, issn = {2574-8300}, doi = {10.1161/CIRCGEN.119.002680}, author = {Baldassari, Antoine R and Sitlani, Colleen M and Highland, Heather M and Arking, Dan E and Buyske, Steve and Darbar, Dawood and Gondalia, Rahul and Graff, Misa and Guo, Xiuqing and Heckbert, Susan R and Hindorff, Lucia A and Hodonsky, Chani J and Ida Chen, Yii-Der and Kaplan, Robert C and Peters, Ulrike and Post, Wendy and Reiner, Alex P and Rotter, Jerome I and Shohet, Ralph V and Seyerle, Amanda A and Sotoodehnia, Nona and Tao, Ran and Taylor, Kent D and Wojcik, Genevieve L and Yao, Jie and Kenny, Eimear E and Lin, Henry J and Soliman, Elsayed Z and Whitsel, Eric A and North, Kari E and Kooperberg, Charles and Avery, Christy L} }