@article {881, title = {Copy number variants~and fixed duplications among 198 rhesus macaques (Macaca mulatta).}, journal = {PLoS Genet}, volume = {16}, year = {2020}, month = {2020 05}, pages = {e1008742}, abstract = {

The rhesus macaque is an abundant species of Old World monkeys and a valuable model organism for biomedical research due to its close phylogenetic relationship to humans. Copy number variation is one of the main sources of genomic diversity within and between species and a widely recognized cause of inter-individual differences in disease risk. However, copy number differences among rhesus macaques and between the human and macaque genomes, as well as the relevance of this diversity to research involving this nonhuman primate, remain understudied. Here we present a high-resolution map of sequence copy number for the rhesus macaque genome constructed from a dataset of 198 individuals. Our results show that about one-eighth of the rhesus macaque reference genome is composed of recently duplicated regions, either copy number variable regions or fixed duplications. Comparison with human genomic copy number maps based on previously published data shows that, despite overall similarities in the genome-wide distribution of these regions, there are specific differences at the chromosome level. Some of these create differences in the copy number profile between human disease genes and their rhesus macaque orthologs. Our results highlight the importance of addressing the number of copies of target genes in the design of experiments and cautions against human-centered assumptions in research conducted with model organisms. Overall, we present a genome-wide copy number map from a large sample of rhesus macaque individuals representing an important novel contribution concerning the evolution of copy number in primate genomes.

}, keywords = {Animals, Chromosome Mapping, DNA Copy Number Variations, Female, Gene Duplication, Genetics, Population, Genome, High-Throughput Nucleotide Sequencing, Humans, Macaca mulatta, Male, Open Reading Frames, Phylogeny, Sequence Analysis, DNA, Species Specificity}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1008742}, author = {Bras{\'o}-Vives, Marina and Povolotskaya, Inna S and Hartas{\'a}nchez, Diego A and Farr{\'e}, Xavier and Fernandez-Callejo, Marcos and Raveendran, Muthuswamy and Harris, R Alan and Rosene, Douglas L and Lorente-Galdos, Belen and Navarro, Arcadi and Marques-Bonet, Tomas and Rogers, Jeffrey and Juan, David} } @article {878, title = {Discovery and population genomics of structural variation in a songbird genus.}, journal = {Nat Commun}, volume = {11}, year = {2020}, month = {2020 07 07}, pages = {3403}, abstract = {

Structural variation~(SV) constitutes an important type of genetic mutations providing the raw material for evolution. Here, we uncover the genome-wide spectrum of intra- and interspecific SV segregating in natural populations of seven songbird species in the genus Corvus. Combining short-read (N = 127) and long-read re-sequencing (N = 31), as well as optical mapping (N = 16), we apply both assembly- and read mapping approaches to detect SV and characterize a total of 220,452 insertions, deletions and inversions. We exploit sampling across wide phylogenetic timescales to validate SV genotypes and assess the contribution of SV to evolutionary processes in an avian model of incipient speciation. We reveal an evolutionary young (~530,000 years) cis-acting 2.25-kb LTR retrotransposon insertion reducing expression of the NDP gene with consequences for premating isolation. Our results attest to the wealth and evolutionary significance of SV segregating in natural populations and highlight the need for reliable SV genotyping.

}, keywords = {Animals, Chromosome Inversion, Gene Deletion, Genetic Variation, Genetics, Population, Genome, Genomic Structural Variation, Genotype, Phylogeny, Polymorphism, Single Nucleotide, Retroelements, Sequence Analysis, DNA, Songbirds}, issn = {2041-1723}, doi = {10.1038/s41467-020-17195-4}, author = {Weissensteiner, Matthias H and Bunikis, Ignas and Catal{\'a}n, Ana and Francoijs, Kees-Jan and Knief, Ulrich and Heim, Wieland and Peona, Valentina and Pophaly, Saurabh D and Sedlazeck, Fritz J and Suh, Alexander and Warmuth, Vera M and Wolf, Jochen B W} } @article {905, title = {Dominant-negative mutations in human IL6ST underlie hyper-IgE syndrome.}, journal = {J Exp Med}, volume = {217}, year = {2020}, month = {2020 06 01}, abstract = {

Autosomal dominant hyper-IgE syndrome (AD-HIES) is typically caused by dominant-negative (DN) STAT3 mutations. Patients suffer from cold staphylococcal lesions and mucocutaneous candidiasis, severe allergy, and skeletal abnormalities. We report 12 patients from 8 unrelated kindreds with AD-HIES due to DN IL6ST mutations. We identified seven different truncating mutations, one of which was recurrent. The mutant alleles encode GP130 receptors bearing the transmembrane domain but lacking both the recycling motif and all four STAT3-recruiting tyrosine residues. Upon overexpression, the mutant proteins accumulate at the cell surface and are loss of function and DN for cellular responses to IL-6, IL-11, LIF, and OSM. Moreover, the patients{\textquoteright} heterozygous leukocytes and fibroblasts respond poorly to IL-6 and IL-11. Consistently, patients with STAT3 and IL6ST mutations display infectious and allergic manifestations of IL-6R deficiency, and some of the skeletal abnormalities of IL-11R deficiency. DN STAT3 and IL6ST mutations thus appear to underlie clinical phenocopies through impairment of the IL-6 and IL-11 response pathways.

}, keywords = {Adolescent, Alleles, C-Reactive Protein, Cell Membrane, Cells, Cultured, Child, Cytokine Receptor gp130, Cytokines, Female, Fibroblasts, Genes, Dominant, Genetics, Population, HEK293 Cells, Humans, Job Syndrome, Kinetics, Loss of Function Mutation, Male, Middle Aged, Models, Biological, Mutation, Pedigree, Phenotype, Th2 Cells, Up-Regulation, Young Adult}, issn = {1540-9538}, doi = {10.1084/jem.20191804}, author = {B{\'e}ziat, Vivien and Tavernier, Simon J and Chen, Yin-Huai and Ma, Cindy S and Materna, Marie and Laurence, Arian and Staal, Jens and Aschenbrenner, Dominik and Roels, Lisa and Worley, Lisa and Claes, Kathleen and Gartner, Lisa and Kohn, Lisa A and De Bruyne, Marieke and Schmitz-Abe, Klaus and Charbonnier, Louis-Marie and Keles, Sevgi and Nammour, Justine and Vladikine, Natasha and Maglorius Renkilaraj, Majistor Raj Luxman and Seeleuthner, Yoann and Migaud, M{\'e}lanie and Rosain, J{\'e}r{\'e}mie and Jeljeli, Mohamed and Boisson, Bertrand and Van Braeckel, Eva and Rosenfeld, Jill A and Dai, Hongzheng and Burrage, Lindsay C and Murdock, David R and Lambrecht, Bart N and Avettand-Fenoel, V{\'e}ronique and Vogel, Tiphanie P and Esther, Charles R and Haskologlu, Sule and Dogu, Figen and Ciznar, Peter and Boutboul, David and Ouach{\'e}e-Chardin, Marie and Amourette, Jean and Lebras, Marie-No{\"e}lle and Gauvain, Cl{\'e}ment and Tcherakian, Colas and Ikinciogullari, Aydan and Beyaert, Rudi and Abel, Laurent and Milner, Joshua D and Grimbacher, Bodo and Couderc, Louis-Jean and Butte, Manish J and Freeman, Alexandra F and Catherinot, Emilie and Fieschi, Claire and Chatila, Talal A and Tangye, Stuart G and Uhlig, Holm H and Haerynck, Filomeen and Casanova, Jean-Laurent and Puel, Anne} } @article {839, title = {Mapping and characterization of structural variation in 17,795 human genomes.}, journal = {Nature}, volume = {583}, year = {2020}, month = {2020 07}, pages = {83-89}, abstract = {

A key goal of whole-genome sequencing for studies of human genetics is to interrogate all forms of variation, including single-nucleotide variants, small insertion or deletion (indel) variants and structural variants. However, tools and resources for the study of structural variants have lagged behind those for smaller variants. Here we used a scalable pipeline to map and characterize structural variants in 17,795 deeply sequenced human genomes. We publicly release site-frequency data to create the largest, to our knowledge, whole-genome-sequencing-based structural variant resource so far. On average, individuals carry 2.9 rare structural variants that alter coding regions; these variants affect the dosage or structure of 4.2 genes and account for 4.0-11.2\% of rare high-impact coding alleles. Using a computational model, we estimate that structural variants account for 17.2\% of rare alleles genome-wide, with predicted deleterious effects that are equivalent to loss-of-function coding alleles; approximately 90\% of such structural variants are noncoding deletions (mean 19.1 per genome). We report 158,991 ultra-rare structural variants and show that 2\% of individuals carry ultra-rare megabase-scale structural variants, nearly half of which are balanced or complex rearrangements. Finally, we infer the dosage sensitivity of genes and noncoding elements, and reveal trends that relate to element class and conservation. This work will help to guide the analysis and interpretation of structural variants in the era of whole-genome sequencing.

}, keywords = {Alleles, Case-Control Studies, Continental Population Groups, Epigenesis, Genetic, Female, Gene Dosage, Genetic Variation, Genetics, Population, Genome, Human, High-Throughput Nucleotide Sequencing, Humans, Male, Molecular Sequence Annotation, Quantitative Trait Loci, Software, Whole Genome Sequencing}, issn = {1476-4687}, doi = {10.1038/s41586-020-2371-0}, author = {Abel, Haley J and Larson, David E and Regier, Allison A and Chiang, Colby and Das, Indraniel and Kanchi, Krishna L and Layer, Ryan M and Neale, Benjamin M and Salerno, William J and Reeves, Catherine and Buyske, Steven and Matise, Tara C and Muzny, Donna M and Zody, Michael C and Lander, Eric S and Dutcher, Susan K and Stitziel, Nathan O and Hall, Ira M} } @article {836, title = {A structural variation reference for medical and population genetics.}, journal = {Nature}, volume = {581}, year = {2020}, month = {2020 05}, pages = {444-451}, abstract = {

Structural variants (SVs) rearrange large segments of DNA and can have profound consequences in evolution and human disease. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD) have become integral in the interpretation of single-nucleotide variants (SNVs). However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54\% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25-29\% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9\% of samples, and estimate that 0.13\% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings. This SV resource is freely distributed via the gnomAD browser and will have broad utility in population genetics, disease-association studies, and diagnostic screening.

}, keywords = {Continental Population Groups, Disease, Female, Genetic Testing, Genetic Variation, Genetics, Medical, Genetics, Population, Genome, Human, Genotyping Techniques, Humans, Male, Middle Aged, Mutation, Polymorphism, Single Nucleotide, Reference Standards, Selection, Genetic, Whole Genome Sequencing}, issn = {1476-4687}, doi = {10.1038/s41586-020-2287-8}, author = {Collins, Ryan L and Brand, Harrison and Karczewski, Konrad J and Zhao, Xuefang and Alf{\"o}ldi, Jessica and Francioli, Laurent C and Khera, Amit V and Lowther, Chelsea and Gauthier, Laura D and Wang, Harold and Watts, Nicholas A and Solomonson, Matthew and O{\textquoteright}Donnell-Luria, Anne and Baumann, Alexander and Munshi, Ruchi and Walker, Mark and Whelan, Christopher W and Huang, Yongqing and Brookings, Ted and Sharpe, Ted and Stone, Matthew R and Valkanas, Elise and Fu, Jack and Tiao, Grace and Laricchia, Kristen M and Ruano-Rubio, Valentin and Stevens, Christine and Gupta, Namrata and Cusick, Caroline and Margolin, Lauren and Taylor, Kent D and Lin, Henry J and Rich, Stephen S and Post, Wendy S and Chen, Yii-Der Ida and Rotter, Jerome I and Nusbaum, Chad and Philippakis, Anthony and Lander, Eric and Gabriel, Stacey and Neale, Benjamin M and Kathiresan, Sekar and Daly, Mark J and Banks, Eric and MacArthur, Daniel G and Talkowski, Michael E} } @article {873, title = {A variant-centric perspective on geographic patterns of human allele frequency variation.}, journal = {Elife}, volume = {9}, year = {2020}, month = {2020 12 22}, abstract = {

A key challenge in human genetics is to understand the geographic distribution of human genetic variation. Often genetic variation is described by showing relationships among populations or individuals, drawing inferences over many variants. Here, we introduce an alternative representation of genetic variation that reveals the relative abundance of different allele frequency patterns. This approach allows viewers to easily see several features of human genetic structure: (1) most variants are rare and geographically localized, (2) variants that are common in a single geographic region are more likely to be shared across the globe than to be private to that region, and (3) where two individuals differ, it is most often due to variants that are found globally, regardless of whether the individuals are from the same region or different regions. Our variant-centric visualization clarifies the geographic patterns of human variation and can help address misconceptions about genetic differentiation among populations.

}, keywords = {Gene Frequency, Genetic Variation, Genetics, Population, Geography, Humans}, issn = {2050-084X}, doi = {10.7554/eLife.60107}, author = {Biddanda, Arjun and Rice, Daniel P and Novembre, John} } @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 {40, title = {Characterization of Greater Middle Eastern genetic variation for enhanced disease gene discovery.}, journal = {Nat Genet}, volume = {48}, year = {2016}, month = {2016 09}, pages = {1071-6}, abstract = {

The Greater Middle East (GME) has been a central hub of human migration and population admixture. The tradition of consanguinity, variably practiced in the Persian Gulf region, North Africa, and Central Asia, has resulted in an elevated burden of recessive disease. Here we generated a whole-exome GME variome from 1,111 unrelated subjects. We detected substantial diversity and admixture in continental and subregional populations, corresponding to several ancient founder populations with little evidence of bottlenecks. Measured consanguinity rates were an order of magnitude above those in other sampled populations, and the GME population exhibited an increased burden of runs of homozygosity (ROHs) but showed no evidence for reduced burden of deleterious variation due to classically theorized {\textquoteright}genetic purging{\textquoteright}. Applying this database to unsolved recessive conditions in the GME population reduced the number of potential disease-causing variants by four- to sevenfold. These results show variegated genetic architecture in GME populations and support future human genetic discoveries in Mendelian and population genetics.

}, keywords = {Asian Continental Ancestry Group, Cohort Studies, Consanguinity, Disease, European Continental Ancestry Group, Exome, Genes, Recessive, Genetic Markers, Genetic Variation, Genetics, Population, Genome, Human, Genome-Wide Association Study, Homozygote, Human Migration, Humans, Middle East}, issn = {1546-1718}, doi = {10.1038/ng.3592}, author = {Scott, Eric M and Halees, Anason and Itan, Yuval and Spencer, Emily G and He, Yupeng and Azab, Mostafa Abdellateef and Gabriel, Stacey B and Belkadi, Aziz and Boisson, Bertrand and Abel, Laurent and Clark, Andrew G and Alkuraya, Fowzan S and Casanova, Jean-Laurent and Gleeson, Joseph G} } @article {123, title = {PRIMUS: improving pedigree reconstruction using mitochondrial and Y haplotypes.}, journal = {Bioinformatics}, volume = {32}, year = {2016}, month = {2016 Feb 15}, pages = {596-8}, abstract = {

UNLABELLED: PRIMUS is a pedigree reconstruction algorithm that uses estimates of genome-wide identity by descent to reconstruct pedigrees consistent with observed genetic data. However, when genetic data for individuals within a pedigree are missing, often multiple pedigrees can be reconstructed that fit the data. We report a major expansion of PRIMUS that uses mitochondrial (mtDNA) and non-recombining Y chromosome (NRY) haplotypes to eliminate many pedigree structures that are inconsistent with the genetic data. We demonstrate that discordances in mtDNA and NRY haplotypes substantially reduce the number of potential pedigrees, and often lead to the identification of the correct pedigree.

AVAILABILITY AND IMPLEMENTATION: We have implemented PRIMUS updates in PERL and it is available at primus.gs.washington.edu.

}, keywords = {Algorithms, Chromosomes, Human, Y, Computer Simulation, DNA, Mitochondrial, Genetics, Population, Haplotypes, Humans, Linkage Disequilibrium, Pedigree, Software}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btv618}, author = {Staples, Jeffrey and Ekunwe, Lynette and Lange, Ethan and Wilson, James G and Nickerson, Deborah A and Below, Jennifer E} } @article {210, title = {PRIMUS: rapid reconstruction of pedigrees from genome-wide estimates of identity by descent.}, journal = {Am J Hum Genet}, volume = {95}, year = {2014}, month = {2014 Nov 06}, pages = {553-64}, abstract = {

Understanding and correctly utilizing relatedness among samples is essential for genetic analysis; however, managing sample records and pedigrees can often be error prone and incomplete. Data sets ascertained by random sampling often harbor cryptic relatedness that can be leveraged in genetic analyses for maximizing power. We have developed a method that uses genome-wide estimates of~pairwise identity by descent to identify families and quickly reconstruct and score all possible pedigrees that fit the genetic data by using up to third-degree relatives, and we have included it in the software package PRIMUS (Pedigree Reconstruction and Identification of the~Maximally Unrelated Set). Here, we validate its performance on simulated, clinical, and HapMap pedigrees. Among these samples, we demonstrate that PRIMUS can verify reported pedigree structures and identify cryptic relationships. Finally, we show that PRIMUS reconstructed pedigrees, all of which were previously unknown, for 203 families from a cohort collected in Starr County, TX (1,890 samples).

}, keywords = {Base Sequence, Computer Simulation, Exome, Gene Frequency, Genetics, Population, Humans, Molecular Sequence Data, Pedigree, Pulmonary Disease, Chronic Obstructive, Sequence Analysis, DNA, Software, Texas}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2014.10.005}, author = {Staples, Jeffrey and Qiao, Dandi and Cho, Michael H and Silverman, Edwin K and Nickerson, Deborah A and Below, Jennifer E} } @article {331, title = {Clan genomics and the complex architecture of human disease.}, journal = {Cell}, volume = {147}, year = {2011}, month = {2011 Sep 30}, pages = {32-43}, abstract = {

Human diseases are caused by alleles that encompass the full range of variant types, from single-nucleotide changes to copy-number variants, and these variations span a broad frequency spectrum, from the very rare to the common. The picture emerging from analysis of whole-genome sequences, the 1000 Genomes Project pilot studies, and targeted genomic sequencing derived from very large sample sizes reveals an abundance of rare and private variants. One implication of this realization is that recent mutation may have a greater influence on disease susceptibility or protection than is conferred by variations that arose in distant ancestors.

}, keywords = {Genetic Predisposition to Disease, Genetic Variation, Genetics, Population, Genome, Human, Genomics, Humans, Pedigree, Pilot Projects, Precision Medicine}, issn = {1097-4172}, doi = {10.1016/j.cell.2011.09.008}, author = {Lupski, James R and Belmont, John W and Boerwinkle, Eric and Gibbs, Richard A} }