@article {776, title = {Estimation of the carrier frequency of fumarate hydratase alterations and implications for kidney cancer risk in hereditary leiomyomatosis and renal cancer.}, journal = {Cancer}, volume = {126}, year = {2020}, month = {2020 08 15}, pages = {3657-3666}, abstract = {

BACKGROUND: Hereditary leiomyomatosis and renal cancer (HLRCC) is a cancer syndrome associated with a germline mutation in fumarate hydratase (FH). The syndrome is associated with cutaneous and uterine leiomyomas, and some patients develop a lethal form of kidney cancer. This study provides estimates for the FH carrier frequency and kidney cancer penetrance.

METHODS: Data sets containing sequencing data for the FH gene were used: the 1000 Genomes Project (1000GP) and the Exome Aggregation Consortium (ExAC). Alterations in the FH gene were characterized on the basis of different variant risk tiers: 1) ClinVar annotated variants, 2) loss-of-function alterations, and 3) highly impactful missense alterations. The cumulative incidence of FH alterations overall and by different world populations was evaluated in 1000GP and ExAC. A lifetime penetrance of HLRCC kidney cancer risk was generated with 3 estimates of the annual incidence.

RESULTS: The overall allele frequencies of tier 1 to 3 FH alterations in the ExAC and 1000GP data sets were 2.54 {\texttimes} 10 (1 in 393) and 1.20 {\texttimes} 10 (1 in 835), respectively. There were differences in the allele frequencies of FH alterations between world populations. Based on various estimates of the percentage of kidney cancers with FH alterations, the lifetime kidney cancer penetrance for carrier estimate 3 in ExAC was 1.7\% to 5.8\%.

CONCLUSIONS: FH alterations are common and are carried by approximately 1 in 1000 individuals according to the more conservative estimates. The lifetime kidney cancer penetrance appears lower than previously estimated. Although databases are not population cohorts, they provide a useful quantitative estimate of rare variants with low penetrance.

}, keywords = {Adult, Exome, Female, Fumarate Hydratase, Gene Frequency, Genetic Predisposition to Disease, Germ-Line Mutation, Heterozygote, Humans, Kidney, Kidney Neoplasms, Leiomyomatosis, Male, Middle Aged, Neoplastic Syndromes, Hereditary, Risk Factors, Skin Neoplasms, Uterine Neoplasms}, issn = {1097-0142}, doi = {10.1002/cncr.32914}, author = {Shuch, Brian and Li, Shantao and Risch, Harvey and Bindra, Ranjit S and McGillivray, Patrick D and Gerstein, Mark} } @article {595, title = {Insights into genetics, human biology and disease gleaned from family based genomic studies.}, journal = {Genet Med}, volume = {21}, year = {2019}, month = {2019 04}, pages = {798-812}, abstract = {

Identifying genes and variants contributing to rare disease phenotypes and Mendelian conditions informs biology and medicine, yet potential phenotypic consequences for variation of >75\% of the ~20,000 annotated genes in the human genome are lacking. Technical advances to assess rare variation genome-wide, particularly exome sequencing (ES), enabled establishment in the United States of the National Institutes of Health (NIH)-supported Centers for Mendelian Genomics (CMGs) and have facilitated collaborative studies resulting in~novel "disease gene" discoveries. Pedigree-based genomic studies and rare variant analyses in families with suspected Mendelian conditions have led to the elucidation of hundreds of novel disease genes and highlighted the impact of de novo mutational events, somatic variation underlying nononcologic traits, incompletely penetrant alleles, phenotypes with high locus heterogeneity, and multilocus pathogenic variation. Herein, we highlight CMG collaborative discoveries that have contributed to understanding both rare and common diseases and discuss opportunities for future discovery in single-locus Mendelian disorder genomics. Phenotypic annotation of all human genes; development of bioinformatic tools and analytic methods; exploration of non-Mendelian modes of inheritance including reduced penetrance, multilocus variation, and oligogenic inheritance; construction of allelic series at a locus; enhanced data sharing worldwide; and integration with clinical genomics are explored. Realizing the full contribution of rare disease research to functional annotation of the human genome, and further illuminating human biology and health, will lay the foundation for the Precision Medicine Initiative.

}, keywords = {Databases, Genetic, Genetic Diseases, Inborn, Genetic Heterogeneity, Genetic Predisposition to Disease, Genome, Human, Genomics, Humans, National Institutes of Health (U.S.), Pedigree, United States, Whole Exome Sequencing}, issn = {1530-0366}, doi = {10.1038/s41436-018-0408-7}, author = {Posey, Jennifer E and O{\textquoteright}Donnell-Luria, Anne H and Chong, Jessica X and Harel, Tamar and Jhangiani, Shalini N and Coban Akdemir, Zeynep H and Buyske, Steven and Pehlivan, Davut and Carvalho, Claudia M B and Baxter, Samantha and Sobreira, Nara and Liu, Pengfei and Wu, Nan and Rosenfeld, Jill A and Kumar, Sushant and Avramopoulos, Dimitri and White, Janson J and Doheny, Kimberly F and Witmer, P Dane and Boehm, Corinne and Sutton, V Reid and Muzny, Donna M and Boerwinkle, Eric and G{\"u}nel, Murat and Nickerson, Deborah A and Mane, Shrikant and MacArthur, Daniel G and Gibbs, Richard A and Hamosh, Ada and Lifton, Richard P and Matise, Tara C and Rehm, Heidi L and Gerstein, Mark and Bamshad, Michael J and Valle, David and Lupski, James R} } @article {352, title = {Intensification: A Resource for Amplifying Population-Genetic Signals with Protein Repeats.}, journal = {J Mol Biol}, volume = {429}, year = {2017}, month = {2017 02 03}, pages = {435-445}, abstract = {

Large-scale genome sequencing holds great promise for the interpretation of protein structures through the discovery of many, rare functional variants in the human population. However, because protein-coding regions are under high selective constraints, these variants occur at low frequencies, such that there is often insufficient statistics for downstream calculations. To address this problem, we develop the Intensification approach, which uses the modular structure of repeat protein domains to amplify signals of selection from population genetics and traditional interspecies conservation. In particular, we are able to aggregate variants at the codon level to identify important positions in repeat domains that show strong conservation signals. This allows us to compare conservation over different evolutionary timescales. It also enables us to visualize population-genetic measures on protein structures. We make available the Intensification results as an online resource (http://intensification.gersteinlab.org) and illustrate the approach through a case study on the tetratricopeptide repeat.

}, keywords = {Amino Acid Sequence, Chromosome Mapping, Codon, Computational Biology, Databases, Genetic, Evolution, Molecular, Genetics, Population, Humans, Internet, Molecular Structure, Protein Conformation, Proteins, Signal Processing, Computer-Assisted, X-Rays}, issn = {1089-8638}, doi = {10.1016/j.jmb.2016.12.003}, author = {Chen, Jieming and Wang, Bo and Regan, Lynne and Gerstein, Mark} } @article {68, title = {Identifying Allosteric Hotspots with Dynamics: Application to Inter- and Intra-species Conservation.}, journal = {Structure}, volume = {24}, year = {2016}, month = {2016 05 03}, pages = {826-837}, abstract = {

The rapidly growing volume of data being produced by next-generation sequencing initiatives is enabling more in-depth analyses of conservation than previously possible. Deep sequencing is uncovering disease loci and regions under selective constraint, despite the fact that intuitive biophysical reasons for such constraint are sometimes absent. Allostery may often provide the missing explanatory link. We use models of protein conformational change to identify allosteric residues by finding essential surface pockets and information-flow bottlenecks, and we develop a software tool that enables users to perform this analysis on their own proteins of interest. Though fundamentally 3D-structural in nature, our analysis is computationally fast, thereby allowing us to run it across the PDB and to evaluate general properties of predicted allosteric residues. We find that these tend to be conserved over diverse evolutionary time scales. Finally, we highlight examples of allosteric residues that help explain poorly understood disease-associated variants.

}, keywords = {Allosteric Site, Animals, Conserved Sequence, Humans, Proteome, Sequence Analysis, Protein, Software}, issn = {1878-4186}, doi = {10.1016/j.str.2016.03.008}, author = {Clarke, Declan and Sethi, Anurag and Li, Shantao and Kumar, Sushant and Chang, Richard W F and Chen, Jieming and Gerstein, Mark} } @article {535, title = {Localized structural frustration for evaluating the impact of sequence variants.}, journal = {Nucleic Acids Res}, volume = {44}, year = {2016}, month = {2016 12 01}, pages = {10062-10073}, abstract = {

Population-scale sequencing is increasingly uncovering large numbers of rare single-nucleotide variants (SNVs) in coding regions of the genome. The rarity of these variants makes it challenging to evaluate their deleteriousness with conventional phenotype-genotype associations. Protein structures provide a way of addressing this challenge. Previous efforts have focused on globally quantifying the impact of SNVs on protein stability. However, local perturbations may severely impact protein functionality without strongly disrupting global stability (e.g. in relation to catalysis or allostery). Here, we describe a workflow in which localized frustration, quantifying unfavorable local interactions, is employed as a metric to investigate such effects. Using this workflow on the Protein Databank, we find that frustration produces many immediately intuitive results: for instance, disease-related SNVs create stronger changes in localized frustration than non-disease related variants, and rare SNVs tend to disrupt local interactions to a larger extent than common variants. Less obviously, we observe that somatic SNVs associated with oncogenes and tumor suppressor genes (TSGs) induce very different changes in frustration. In particular, those associated with TSGs change the frustration more in the core than the surface (by introducing loss-of-function events), whereas those associated with oncogenes manifest the opposite pattern, creating gain-of-function events.

}, keywords = {Computational Biology, Databases, Protein, Evolution, Molecular, Genes, Tumor Suppressor, Genetic Variation, Humans, Neoplasms, Oncogenes, Polymorphism, Single Nucleotide, Proteins, Workflow}, issn = {1362-4962}, doi = {10.1093/nar/gkw927}, author = {Kumar, Sushant and Clarke, Declan and Gerstein, Mark} } @article {104, title = {Reads meet rotamers: structural biology in the age of deep sequencing.}, journal = {Curr Opin Struct Biol}, volume = {35}, year = {2015}, month = {2015 Dec}, pages = {125-34}, abstract = {

Structure has traditionally been interrelated with sequence, usually in the framework of comparing sequences across species sharing a common fold. However, the nature of information within the sequence and structure databases is evolving, changing the type of comparisons possible. In particular, we now have a vast amount of personal genome sequences from human populations and a greater fraction of new structures contain interacting proteins within large complexes. Consequently, we have to recast our conception of sequence conservation and its relation to structure-for example, focusing more on selection within the human population. Moreover, within structural biology there is less emphasis on the discovery of novel folds and more on relating structures to networks of protein interactions. We cover this changing mindset here.

}, keywords = {High-Throughput Nucleotide Sequencing, Humans, Isomerism, Mutation, Proteins}, issn = {1879-033X}, doi = {10.1016/j.sbi.2015.11.003}, author = {Sethi, Anurag and Clarke, Declan and Chen, Jieming and Kumar, Sushant and Galeev, Timur R and Regan, Lynne and Gerstein, Mark} } @article {325, title = {The Centers for Mendelian Genomics: a new large-scale initiative to identify the genes underlying rare Mendelian conditions.}, journal = {Am J Med Genet A}, volume = {158A}, year = {2012}, month = {2012 Jul}, pages = {1523-5}, abstract = {

Next generation exome sequencing (ES) and whole genome sequencing (WGS) are new powerful tools for discovering the gene(s) that underlie Mendelian disorders. To accelerate these discoveries, the National Institutes of Health has established three Centers for Mendelian Genomics (CMGs): the Center for Mendelian Genomics at the University of Washington; the Center for Mendelian Genomics at Yale University; and the Baylor-Johns Hopkins Center for Mendelian Genomics at Baylor College of Medicine and Johns Hopkins University. The CMGs will provide ES/WGS and extensive analysis expertise at no cost to collaborating investigators where the causal gene(s) for a Mendelian phenotype has yet to be uncovered. Over the next few years and in collaboration with the global human genetics community, the CMGs hope to facilitate the identification of the genes underlying a very large fraction of all Mendelian disorders; see http://mendelian.org.

}, keywords = {Academies and Institutes, Genetic Diseases, Inborn, Genetics, Medical, Genome, Human, Genome-Wide Association Study, Genomics, High-Throughput Nucleotide Sequencing, Humans}, issn = {1552-4833}, doi = {10.1002/ajmg.a.35470}, author = {Bamshad, Michael J and Shendure, Jay A and Valle, David and Hamosh, Ada and Lupski, James R and Gibbs, Richard A and Boerwinkle, Eric and Lifton, Richard P and Gerstein, Mark and G{\"u}nel, Murat and Mane, Shrikant and Nickerson, Deborah A} }