@article {124, title = {Chromosome-scale, haplotype-resolved assembly of human genomes.}, journal = {Nat Biotechnol}, volume = {39}, year = {2021}, month = {2021 03}, pages = {309-312}, abstract = {

Haplotype-resolved or phased genome assembly provides a complete picture of genomes and their complex genetic variations. However, current algorithms for phased assembly either do not generate chromosome-scale phasing or require pedigree information, which limits their application. We present a method named diploid assembly (DipAsm) that uses long, accurate reads and long-range conformation data for single individuals to generate a chromosome-scale phased assembly within 1 day. Applied to four public human genomes, PGP1, HG002, NA12878 and HG00733, DipAsm produced haplotype-resolved assemblies with minimum contig length needed to cover 50\% of the known genome (NG50) up to 25 Mb and phased ~99.5\% of heterozygous sites at 98-99\% accuracy, outperforming other approaches in terms of both contiguity and phasing completeness. We demonstrate the importance of chromosome-scale phased assemblies for the discovery of structural variants (SVs), including thousands of new transposon insertions, and of highly polymorphic and medically important regions such as the human leukocyte antigen (HLA) and killer cell immunoglobulin-like receptor (KIR) regions. DipAsm will facilitate high-quality precision medicine and studies of individual haplotype variation and population diversity.

}, keywords = {Algorithms, Chromosomes, Human, Genome, Human, Haplotypes, Heterozygote, Humans, Polymorphism, Single Nucleotide}, issn = {1546-1696}, doi = {10.1038/s41587-020-0711-0}, author = {Garg, Shilpa and Fungtammasan, Arkarachai and Carroll, Andrew and Chou, Mike and Schmitt, Anthony and Zhou, Xiang and Mac, Stephen and Peluso, Paul and Hatas, Emily and Ghurye, Jay and Maguire, Jared and Mahmoud, Medhat and Cheng, Haoyu and Heller, David and Zook, Justin M and Moemke, Tobias and Marschall, Tobias and Sedlazeck, Fritz J and Aach, John and Chin, Chen-Shan and Church, George M and Li, Heng} } @article {150, title = {Efficient phasing and imputation of low-coverage sequencing data using large reference panels.}, journal = {Nat Genet}, volume = {53}, year = {2021}, month = {2021 01}, pages = {120-126}, abstract = {

Low-coverage whole-genome sequencing followed by imputation has been proposed as a cost-effective genotyping approach for disease and population genetics studies. However, its competitiveness against SNP arrays is undermined because current imputation methods are computationally expensive and unable to leverage large reference panels. Here, we describe a method, GLIMPSE, for phasing and imputation of low-coverage sequencing datasets from modern reference panels. We demonstrate its remarkable performance across different coverages and human populations. GLIMPSE achieves imputation of a genome for less than US$1 in computational cost, considerably outperforming other methods and improving imputation accuracy over the full allele frequency range. As a proof of concept, we show that 1{\texttimes} coverage enables effective gene expression association studies and outperforms dense SNP arrays in rare variant burden tests. Overall, this study illustrates the promising potential of low-coverage imputation and suggests a paradigm shift in the design of future genomic studies.

}, keywords = {Genome, Human, Genotype, Humans, Likelihood Functions, Polymorphism, Single Nucleotide, Reference Standards, Sequence Analysis, DNA}, issn = {1546-1718}, doi = {10.1038/s41588-020-00756-0}, author = {Rubinacci, Simone and Ribeiro, Diogo M and Hofmeister, Robin J and Delaneau, Olivier} } @article {155, title = {Whole-genome sequencing of African Americans implicates differential genetic architecture in inflammatory bowel disease.}, journal = {Am J Hum Genet}, volume = {108}, year = {2021}, month = {2021 03 04}, pages = {431-445}, abstract = {

Whether or not populations diverge with respect to the genetic contribution to risk of specific complex diseases is relevant to understanding the evolution of susceptibility and origins of health disparities. Here, we describe a large-scale whole-genome sequencing study of inflammatory bowel disease encompassing 1,774 affected individuals and 1,644 healthy control Americans with African ancestry (African Americans). Although no new loci for inflammatory bowel disease are discovered at genome-wide significance levels, we identify numerous instances of differential effect sizes in combination with divergent allele frequencies. For example, the major effect at PTGER4 fine maps to a single credible interval of 22 SNPs corresponding to one of four independent associations at the locus in European ancestry individuals but with an elevated odds ratio for Crohn disease in African Americans. A rare variant aggregate analysis implicates Ca-binding neuro-immunomodulator CALB2 in ulcerative colitis. Highly significant overall overlap of common variant risk for inflammatory bowel disease susceptibility between individuals with African and European ancestries was observed, with 41 of 241 previously known lead variants replicated and overall correlations in effect sizes of 0.68 for combined inflammatory bowel disease. Nevertheless, subtle differences influence the performance of polygenic risk scores, and we show that ancestry-appropriate weights significantly improve polygenic prediction in the highest percentiles of risk. The median amount of variance explained per locus remains the same in African and European cohorts, providing evidence for compensation of effect sizes as allele frequencies diverge, as expected under a highly polygenic model of disease.

}, keywords = {African Americans, Aged, Aged, 80 and over, Calbindin 2, Colitis, Ulcerative, Crohn Disease, European Continental Ancestry Group, Female, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Inflammatory Bowel Diseases, Male, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Receptors, Prostaglandin E, EP4 Subtype, Whole Genome Sequencing}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2021.02.001}, author = {Somineni, Hari K and Nagpal, Sini and Venkateswaran, Suresh and Cutler, David J and Okou, David T and Haritunians, Talin and Simpson, Claire L and Begum, Ferdouse and Datta, Lisa W and Quiros, Antonio J and Seminerio, Jenifer and Mengesha, Emebet and Alexander, Jonathan S and Baldassano, Robert N and Dudley-Brown, Sharon and Cross, Raymond K and Dassopoulos, Themistocles and Denson, Lee A and Dhere, Tanvi A and Iskandar, Heba and Dryden, Gerald W and Hou, Jason K and Hussain, Sunny Z and Hyams, Jeffrey S and Isaacs, Kim L and Kader, Howard and Kappelman, Michael D and Katz, Jeffry and Kellermayer, Richard and Kuemmerle, John F and Lazarev, Mark and Li, Ellen and Mannon, Peter and Moulton, Dedrick E and Newberry, Rodney D and Patel, Ashish S and Pekow, Joel and Saeed, Shehzad A and Valentine, John F and Wang, Ming-Hsi and McCauley, Jacob L and Abreu, Maria T and Jester, Traci and Molle-Rios, Zarela and Palle, Sirish and Scherl, Ellen J and Kwon, John and Rioux, John D and Duerr, Richard H and Silverberg, Mark S and Zwick, Michael E and Stevens, Christine and Daly, Mark J and Cho, Judy H and Gibson, Greg and McGovern, Dermot P B and Brant, Steven R and Kugathasan, Subra} } @article {117, title = {Analysis of cardiac magnetic resonance imaging in 36,000 individuals yields genetic insights into dilated cardiomyopathy.}, journal = {Nat Commun}, volume = {11}, year = {2020}, month = {2020 05 07}, pages = {2254}, abstract = {

Dilated cardiomyopathy (DCM) is an important cause of heart failure and the leading indication for heart transplantation. Many rare genetic variants have been associated with DCM, but common variant studies of the disease have yielded few associated loci. As structural changes in the heart are a defining feature of DCM, we report a genome-wide association study of cardiac magnetic resonance imaging (MRI)-derived left ventricular measurements in 36,041 UK Biobank participants, with replication in 2184 participants from the Multi-Ethnic Study of Atherosclerosis. We identify 45 previously unreported loci associated with cardiac structure and function, many near well-established genes for Mendelian cardiomyopathies. A polygenic score of MRI-derived left ventricular end systolic volume strongly associates with incident DCM in the general population. Even among carriers of TTN truncating mutations, this polygenic score influences the size and function of the human heart. These results further implicate common genetic polymorphisms in the pathogenesis of DCM.

}, keywords = {Cardiomyopathy, Dilated, Genome-Wide Association Study, Heart, Humans, Magnetic Resonance Imaging, Myocardium, Polymorphism, Single Nucleotide}, issn = {2041-1723}, doi = {10.1038/s41467-020-15823-7}, author = {Pirruccello, James P and Bick, Alexander and Wang, Minxian and Chaffin, Mark and Friedman, Samuel and Yao, Jie and Guo, Xiuqing and Venkatesh, Bharath Ambale and Taylor, Kent D and Post, Wendy S and Rich, Stephen and Lima, Joao A C and Rotter, Jerome I and Philippakis, Anthony and Lubitz, Steven A and Ellinor, Patrick T and Khera, Amit V and Kathiresan, Sekar and Aragam, Krishna G} } @article {110, 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 {111, title = {Evaluation of the VISAGE Basic Tool for Appearance and Ancestry Prediction Using PowerSeq Chemistry on the MiSeq FGx System.}, journal = {Genes (Basel)}, volume = {11}, year = {2020}, month = {2020 06 26}, abstract = {

The study of DNA to predict externally visible characteristics (EVCs) and the biogeographical ancestry (BGA) from unknown samples is gaining relevance in forensic genetics. Technical developments in Massively Parallel Sequencing (MPS) enable the simultaneous analysis of hundreds of DNA markers, which improves successful Forensic DNA Phenotyping (FDP). The EU-funded VISAGE (VISible Attributes through GEnomics) Consortium has developed various targeted MPS-based lab tools to apply FDP in routine forensic analyses. Here, we present an evaluation of the VISAGE Basic tool for appearance and ancestry prediction based on PowerSeq chemistry (Promega) on a MiSeq FGx System (Illumina). The panel consists of 153 single nucleotide polymorphisms (SNPs) that provide information about EVCs (41 SNPs for eye, hair and skin color from HIrisPlex-S) and continental BGA (115 SNPs; three overlap with the EVCs SNP set). The assay was evaluated for sensitivity, repeatability and genotyping concordance, as well as its performance with casework-type samples. This targeted MPS assay provided complete genotypes at all 153 SNPs down to 125 pg of input DNA and 99.67\% correct genotypes at 50 pg. It was robust in terms of repeatability and concordance and provided useful results with casework-type samples. The results suggest that this MPS assay is a useful tool for basic appearance and ancestry prediction in forensic genetics for users interested in applying PowerSeq chemistry and MiSeq for this purpose.

}, keywords = {DNA Fingerprinting, Eye Color, Forensic Genetics, Genetic Markers, Genotype, Hair Color, High-Throughput Nucleotide Sequencing, Humans, Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Skin Pigmentation, Software}, issn = {2073-4425}, doi = {10.3390/genes11060708}, author = {Palencia-Madrid, Leire and Xavier, Catarina and de la Puente, Mar{\'\i}a and Hohoff, Carsten and Phillips, Christopher and Kayser, Manfred and Parson, Walther} } @article {104, title = {Genome-wide association meta-analysis for early age-related macular degeneration highlights novel loci and insights for advanced disease.}, journal = {BMC Med Genomics}, volume = {13}, year = {2020}, month = {2020 08 26}, pages = {120}, abstract = {

BACKGROUND: Advanced age-related macular degeneration (AMD) is a leading cause of blindness. While around half of the genetic contribution to advanced AMD has been uncovered, little is known about the genetic architecture of early AMD.

METHODS: To identify genetic factors for early AMD, we conducted a genome-wide association study (GWAS) meta-analysis (14,034 cases, 91,214 controls, 11 sources of data including the International AMD Genomics Consortium, IAMDGC, and UK Biobank, UKBB). We ascertained early AMD via color fundus photographs by manual grading for 10 sources and via an automated machine learning approach for > 170,000 photographs from UKBB. We searched for early AMD loci via GWAS and via a candidate approach based on 14 previously suggested early AMD variants.

RESULTS: Altogether, we identified 10 independent loci with statistical significance for early AMD: (i) 8 from our GWAS with genome-wide significance (P~< 5 {\texttimes} 10), (ii) one previously suggested locus with experiment-wise significance (P~< 0.05/14) in our non-overlapping data and with genome-wide significance when combining the reported and our non-overlapping data (together 17,539 cases, 105,395 controls), and (iii) one further previously suggested locus with experiment-wise significance in our non-overlapping data. Of these 10 identified loci, 8 were novel and 2 known for early AMD. Most of the 10 loci overlapped with known advanced AMD loci (near ARMS2/HTRA1, CFH, C2, C3, CETP, TNFRSF10A, VEGFA, APOE), except two that have not yet been identified with statistical significance for any AMD. Among the 17 genes within these two loci, in-silico functional annotation suggested CD46 and TYR as the most likely responsible genes. Presence or absence of an early AMD effect distinguished the known pathways of advanced AMD genetics (complement/lipid pathways versus extracellular matrix metabolism).

CONCLUSIONS: Our GWAS on early AMD identified novel loci, highlighted shared and distinct genetics between early and advanced AMD and provides insights into AMD etiology. Our data provide a resource comparable in size to the existing IAMDGC data on advanced AMD genetics enabling a joint view. The biological relevance of this joint view is underscored by the ability of early AMD effects to differentiate the major pathways for advanced AMD.

}, keywords = {Case-Control Studies, Genetic Loci, Genetic Markers, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Macular Degeneration, Polymorphism, Single Nucleotide}, issn = {1755-8794}, doi = {10.1186/s12920-020-00760-7}, author = {Winkler, Thomas W and Grassmann, Felix and Brandl, Caroline and Kiel, Christina and G{\"u}nther, Felix and Strunz, Tobias and Weidner, Lorraine and Zimmermann, Martina E and Korb, Christina A and Poplawski, Alicia and Schuster, Alexander K and M{\"u}ller-Nurasyid, Martina and Peters, Annette and Rauscher, Franziska G and Elze, Tobias and Horn, Katrin and Scholz, Markus and Ca{\~n}adas-Garre, Marisa and McKnight, Amy Jayne and Quinn, Nicola and Hogg, Ruth E and K{\"u}chenhoff, Helmut and Heid, Iris M and Stark, Klaus J and Weber, Bernhard H F} } @article {141, title = {Non-parametric Polygenic Risk Prediction via Partitioned GWAS Summary Statistics.}, journal = {Am J Hum Genet}, volume = {107}, year = {2020}, month = {2020 07 02}, pages = {46-59}, abstract = {

In complex trait genetics, the ability to predict phenotype from genotype is the ultimate measure of our understanding of genetic architecture underlying the heritability of a trait. A complete understanding of the genetic basis of a trait should allow for predictive methods with accuracies approaching the trait{\textquoteright}s heritability. The highly polygenic nature of quantitative traits and most common phenotypes has motivated the development of statistical strategies focused on combining myriad individually non-significant genetic effects. Now that predictive accuracies are improving, there is a growing interest in the practical utility of such methods for predicting risk of common diseases responsive to early therapeutic intervention. However, existing methods require individual-level genotypes or depend on accurately specifying the genetic architecture underlying each disease to be predicted. Here, we propose a polygenic risk prediction method that does not require explicitly modeling any underlying genetic architecture. We start with summary statistics in the form of SNP effect sizes from a large GWAS cohort. We then remove the correlation structure across summary statistics arising due to linkage disequilibrium and apply a piecewise linear interpolation on conditional mean effects. In both simulated and real datasets, this new non-parametric shrinkage (NPS) method can reliably allow for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS improves the identification of groups at high risk for breast cancer, type 2 diabetes, inflammatory bowel disease, and coronary heart disease, all of which have available early intervention or prevention treatments.

}, keywords = {Aged, Cohort Studies, Diabetes Mellitus, Type 2, Female, Genome-Wide Association Study, Genotype, Humans, Linkage Disequilibrium, Male, Middle Aged, Models, Genetic, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2020.05.004}, author = {Chun, Sung and Imakaev, Maxim and Hui, Daniel and Patsopoulos, Nikolaos A and Neale, Benjamin M and Kathiresan, Sekar and Stitziel, Nathan O and Sunyaev, Shamil R} } @article {114, 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 {52, title = {A multi-task convolutional deep neural network for variant calling in single molecule sequencing.}, journal = {Nat Commun}, volume = {10}, year = {2019}, month = {2019 03 01}, pages = {998}, abstract = {

The accurate identification of DNA sequence variants is an important, but challenging task in genomics. It is particularly difficult for single molecule sequencing, which has a per-nucleotide error rate of ~5-15\%. Meeting this demand, we developed Clairvoyante, a multi-task five-layer convolutional neural network model for predicting variant type (SNP or indel), zygosity, alternative allele and indel length from aligned reads. For the well-characterized NA12878 human sample, Clairvoyante achieves 99.67, 95.78, 90.53\% F1-score on 1KP common variants, and 98.65, 92.57, 87.26\% F1-score for whole-genome analysis, using Illumina, PacBio, and Oxford Nanopore data, respectively. Training on a second human sample shows Clairvoyante is sample agnostic and finds variants in less than 2 h on a standard server. Furthermore, we present 3,135 variants that are missed using Illumina but supported independently by both PacBio and Oxford Nanopore reads. Clairvoyante is available open-source ( https://github.com/aquaskyline/Clairvoyante ), with modules to train, utilize and visualize the model.

}, keywords = {Base Sequence, Computational Biology, DNA Mutational Analysis, Genome, Human, Genome-Wide Association Study, Genomics, Genotype, Genotyping Techniques, Humans, INDEL Mutation, Nanopores, Neural Networks (Computer), Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Software}, issn = {2041-1723}, doi = {10.1038/s41467-019-09025-z}, author = {Luo, Ruibang and Sedlazeck, Fritz J and Lam, Tak-Wah and Schatz, Michael C} } @article {31, title = {Genetic variants in microRNA genes and targets associated with cardiovascular disease risk factors in the African-American population.}, journal = {Hum Genet}, volume = {137}, year = {2018}, month = {2018 Jan}, pages = {85-94}, abstract = {

The purpose of this study is to identify microRNA (miRNA) related polymorphism, including single nucleotide variants (SNVs) in mature miRNA-encoding sequences or in miRNA-target sites, and their association with cardiovascular disease (CVD) risk factors in African-American population. To achieve our objective, we examined 1900 African-Americans from the Atherosclerosis Risk in Communities study using SNVs identified from whole-genome sequencing data. A total of 971 SNVs found in 726 different mature miRNA-encoding sequences and 16,057 SNVs found in the three prime untranslated region (3{\textquoteright}UTR) of 3647 protein-coding genes were identified and interrogated their associations with 17 CVD risk factors. Using single-variant-based approach, we found 5 SNVs in miRNA-encoding sequences to be associated with serum Lipoprotein(a) [Lp(a)], high-density lipoprotein (HDL) or triglycerides, and 2 SNVs in miRNA-target sites to be associated with Lp(a) and HDL, all with false discovery rates of 5\%. Using a gene-based approach, we identified 3 pairs of associations between gene NSD1 and platelet count, gene HSPA4L and cardiac troponin T, and gene AHSA2 and magnesium. We successfully validated the association between a variant specific to African-American population, NR_039880.1:n.18A>C, in mature hsa-miR-4727-5p encoding sequence and serum HDL level in an independent sample of 2135 African-Americans. Our study provided candidate miRNAs and their targets for further investigation of their potential contribution to ethnic disparities in CVD risk factors.

}, keywords = {3{\textquoteright} Untranslated Regions, Adult, Black or African American, Cardiovascular Diseases, Female, Genetic Predisposition to Disease, Genotyping Techniques, Humans, Male, MicroRNAs, Middle Aged, Polymorphism, Single Nucleotide, Risk Factors, Whole Genome Sequencing}, issn = {1432-1203}, doi = {10.1007/s00439-017-1858-8}, author = {Li, Chang and Grove, Megan L and Yu, Bing and Jones, Barbara C and Morrison, Alanna and Boerwinkle, Eric and Liu, Xiaoming} } @article {28, title = {Exome sequencing reveals novel genetic loci influencing obesity-related traits in Hispanic children.}, journal = {Obesity (Silver Spring)}, volume = {25}, year = {2017}, month = {2017 Jul}, pages = {1270-1276}, abstract = {

OBJECTIVE: To perform whole exome sequencing in 928 Hispanic children and identify variants and genes associated with childhood obesity.

METHODS: Single-nucleotide variants (SNVs) were identified from Illumina whole exome sequencing data using integrated read mapping, variant calling, and an annotation pipeline (Mercury). Association analyses of 74 obesity-related traits and exonic variants were performed using SeqMeta software. Rare autosomal variants were analyzed using gene-based association analyses, and common autosomal variants were analyzed at the SNV level.

RESULTS: (1) Rare exonic variants in 10 genes and 16 common SNVs in 11 genes that were associated with obesity traits in a cohort of Hispanic children were identified, (2) novel rare variants in peroxisome biogenesis factor 1 (PEX1) associated with several obesity traits (weight, weight z score, BMI, BMI z score, waist circumference, fat mass, trunk fat mass) were discovered, and (3) previously reported SNVs associated with childhood obesity were replicated.

CONCLUSIONS: Convergence of whole exome sequencing, a family-based design, and extensive phenotyping discovered novel rare and common variants associated with childhood obesity. Linking PEX1 to obesity phenotypes poses a novel mechanism of peroxisomal biogenesis and metabolism underlying the development of childhood obesity.

}, keywords = {Adolescent, ATPases Associated with Diverse Cellular Activities, Body Mass Index, Body Weight, Child, Child, Preschool, Cohort Studies, Exome, Genetic Loci, Genome-Wide Association Study, Hispanic or Latino, Humans, Membrane Proteins, Pediatric Obesity, Polymorphism, Single Nucleotide, Risk Factors, Sequence Analysis, DNA, Software, Waist Circumference, Young Adult}, issn = {1930-739X}, doi = {10.1002/oby.21869}, author = {Sabo, Aniko and Mishra, Pamela and Dugan-Perez, Shannon and Voruganti, V Saroja and Kent, Jack W and Kalra, Divya and Cole, Shelley A and Comuzzie, Anthony G and Muzny, Donna M and Gibbs, Richard A and Butte, Nancy F} } @article {23, title = {Genomic Patterns of De Novo Mutation in Simplex Autism.}, journal = {Cell}, volume = {171}, year = {2017}, month = {2017 Oct 19}, pages = {710-722.e12}, abstract = {

To further our understanding of the genetic etiology of autism, we generated and analyzed genome sequence data from 516 idiopathic autism families (2,064 individuals). This resource includes >59 million single-nucleotide variants (SNVs) and 9,212 private copy number variants (CNVs), of which 133,992 and 88 are de novo mutations (DNMs), respectively. We estimate a mutation rate of \~{}1.5~{\texttimes} 10 SNVs per site per generation with a significantly higher mutation rate in repetitive DNA. Comparing probands and unaffected siblings, we observe several DNM trends. Probands carry more gene-disruptive CNVs and SNVs, resulting in severe~missense mutations and mapping to predicted fetal brain promoters and embryonic stem cell enhancers. These differences become more pronounced for autism genes (p~= 1.8~{\texttimes} 10, OR~= 2.2). Patients are more likely to carry multiple coding and noncoding DNMs in different genes, which are enriched for expression in striatal neurons (p~= 3~{\texttimes} 10), suggesting a path forward for genetically characterizing more complex cases of autism.

}, keywords = {Animals, Autistic Disorder, DNA Copy Number Variations, DNA Mutational Analysis, Female, Genome-Wide Association Study, Humans, INDEL Mutation, Male, Mice, Polymorphism, Single Nucleotide}, issn = {1097-4172}, doi = {10.1016/j.cell.2017.08.047}, author = {Turner, Tychele N and Coe, Bradley P and Dickel, Diane E and Hoekzema, Kendra and Nelson, Bradley J and Zody, Michael C and Kronenberg, Zev N and Hormozdiari, Fereydoun and Raja, Archana and Pennacchio, Len A and Darnell, Robert B and Eichler, Evan E} } @article {16, title = {The impact of structural variation on human gene expression.}, journal = {Nat Genet}, volume = {49}, year = {2017}, month = {2017 May}, pages = {692-699}, abstract = {

Structural variants (SVs) are an important source of human genetic diversity, but their contribution to traits, disease and gene regulation remains unclear. We mapped cis expression quantitative trait loci (eQTLs) in 13 tissues via joint analysis of SVs, single-nucleotide variants (SNVs) and short insertion/deletion (indel) variants from deep whole-genome sequencing (WGS). We estimated that SVs are causal at 3.5-6.8\% of eQTLs-a substantially higher fraction than prior estimates-and that expression-altering SVs have larger effect sizes than do SNVs and indels. We identified 789 putative causal SVs predicted to directly alter gene expression: most (88.3\%) were noncoding variants enriched at enhancers and other regulatory elements, and 52 were linked to genome-wide association study loci. We observed a notable abundance of rare high-impact SVs associated with aberrant expression of nearby genes. These results suggest that comprehensive WGS-based SV analyses will increase the power of common- and rare-variant association studies.

}, keywords = {Algorithms, Chromosome Mapping, Gene Expression Regulation, Genetic Variation, Genome, Human, Genome-Wide Association Study, Humans, INDEL Mutation, Linear Models, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Sequence Analysis, DNA}, issn = {1546-1718}, doi = {10.1038/ng.3834}, author = {Chiang, Colby and Scott, Alexandra J and Davis, Joe R and Tsang, Emily K and Li, Xin and Kim, Yungil and Hadzic, Tarik and Damani, Farhan N and Ganel, Liron and Montgomery, Stephen B and Battle, Alexis and Conrad, Donald F and Hall, Ira M} } @article {7, title = {Practical Approaches for Whole-Genome Sequence Analysis of Heart- and Blood-Related Traits.}, journal = {Am J Hum Genet}, volume = {100}, year = {2017}, month = {2017 Feb 02}, pages = {205-215}, abstract = {

Whole-genome sequencing (WGS) allows for a comprehensive view of the sequence of the human genome. We present and apply integrated methodologic steps for interrogating WGS data to characterize the genetic architecture of 10 heart- and blood-related traits in a sample of 1,860 African Americans. In order to evaluate the contribution of regulatory and non-protein coding regions of the genome, we conducted aggregate tests of rare variation across the entire genomic landscape using a sliding window, complemented by an annotation-based assessment of the genome using predefined regulatory elements and within the first intron of all genes. These tests were performed treating all variants equally as well as with individual variants weighted by a measure of predicted functional consequence. Significant findings were assessed in 1,705 individuals of European ancestry. After these steps, we identified and replicated components of the genomic landscape significantly associated with heart- and blood-related traits. For two traits, lipoprotein(a) levels and neutrophil count, aggregate tests of low-frequency and rare variation were significantly associated across multiple motifs. For a third trait, cardiac troponin T, investigation of regulatory domains identified a locus on chromosome 9. These practical approaches for WGS analysis led to the identification of informative genomic regions and also showed that defined non-coding regions, such as first introns of genes and regulatory domains, are associated with important risk factor phenotypes. This study illustrates the tractable nature of WGS data and outlines an approach for characterizing the genetic architecture of complex traits.

}, keywords = {Black or African American, C-Reactive Protein, Cholesterol, HDL, Cholesterol, LDL, Chromosomes, Human, Pair 9, Gene Frequency, Genome, Human, Genome-Wide Association Study, Genomics, Hemoglobins, Humans, Introns, Leukocyte Count, Lipoprotein(a), Magnesium, Natriuretic Peptide, Brain, Neutrophils, Peptide Fragments, Phosphorus, Platelet Count, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Troponin T, White People}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2016.12.009}, author = {Morrison, Alanna C and Huang, Zhuoyi and Yu, Bing and Metcalf, Ginger and Liu, Xiaoming and Ballantyne, Christie and Coresh, Josef and Yu, Fuli and Muzny, Donna and Feofanova, Elena and Rustagi, Navin and Gibbs, Richard and Boerwinkle, Eric} } @article {20, title = {SVScore: an impact prediction tool for structural variation.}, journal = {Bioinformatics}, volume = {33}, year = {2017}, month = {2017 Apr 01}, pages = {1083-1085}, abstract = {

SUMMARY: Here we present SVScore, a tool for in silico structural variation (SV) impact prediction. SVScore aggregates per-base single nucleotide polymorphism (SNP) pathogenicity scores across relevant genomic intervals for each SV in a manner that considers variant type, gene features and positional uncertainty. We show that the allele frequency spectrum of high-scoring SVs is strongly skewed toward lower frequencies, suggesting that they are under purifying selection, and that SVScore identifies deleterious variants more effectively than alternative methods. Notably, our results also suggest that duplications are under surprisingly strong selection relative to deletions, and that there are a similar number of strongly pathogenic SVs and SNPs in the human population.

AVAILABILITY AND IMPLEMENTATION: SVScore is implemented in Perl and available freely at {{ http://www.github.com/lganel/SVScore }} for use under the MIT license.

CONTACT: ihall@wustl.edu.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

}, keywords = {Gene Frequency, Genomic Structural Variation, Genomics, Humans, Polymorphism, Single Nucleotide, Sequence Deletion, Software}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btw789}, author = {Ganel, Liron and Abel, Haley J and Hall, Ira M} } @article {15, title = {Concerted Genetic Function in Blood Traits.}, journal = {Cell}, volume = {167}, year = {2016}, month = {2016 Nov 17}, pages = {1167-1169}, abstract = {

The hematopoietic system plays a major role in human health. Two studies by Astle et~al. and Chen~et~al. published in this issue of Cell use genome-wide association and functional genomics approaches to provide deep insights into the role of genetic variants in hematological traits. We~discuss these discoveries and future strategies toward completing our understanding of the genetic basis for variation in human traits.

}, keywords = {Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Phenotype, Polymorphism, Single Nucleotide}, issn = {1097-4172}, doi = {10.1016/j.cell.2016.10.055}, author = {Kim-Hellmuth, Sarah and Lappalainen, Tuuli} } @article {10, title = {Genome Sequencing of Autism-Affected Families Reveals Disruption of Putative Noncoding Regulatory DNA.}, journal = {Am J Hum Genet}, volume = {98}, year = {2016}, month = {2016 Jan 07}, pages = {58-74}, abstract = {

We performed whole-genome sequencing (WGS) of 208 genomes from 53 families affected by simplex autism. For the majority of these families, no copy-number variant (CNV) or candidate de novo gene-disruptive single-nucleotide variant (SNV) had been detected by microarray or whole-exome sequencing (WES). We integrated multiple CNV and SNV analyses and extensive experimental validation to identify additional candidate mutations in eight families. We report that compared to control individuals, probands showed a significant (p = 0.03) enrichment of de novo and private disruptive mutations within fetal CNS DNase I hypersensitive sites (i.e., putative regulatory regions). This effect was only observed within 50 kb of genes that have been previously associated with autism risk, including genes where dosage sensitivity has already been established by recurrent disruptive de novo protein-coding mutations (ARID1B, SCN2A, NR3C2, PRKCA, and DSCAM). In addition, we provide evidence of gene-disruptive CNVs (in DISC1, WNT7A, RBFOX1, and MBD5), as well as smaller de novo CNVs and exon-specific SNVs missed by exome sequencing in neurodevelopmental genes (e.g., CANX, SAE1, and PIK3CA). Our results suggest that the detection of smaller, often multiple CNVs affecting putative regulatory elements might help explain additional risk of simplex autism.

}, keywords = {Autistic Disorder, DNA, Exome, Female, Genome, Human, Humans, Male, Pedigree, Polymorphism, Single Nucleotide}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2015.11.023}, author = {Turner, Tychele N and Hormozdiari, Fereydoun and Duyzend, Michael H and McClymont, Sarah A and Hook, Paul W and Iossifov, Ivan and Raja, Archana and Baker, Carl and Hoekzema, Kendra and Stessman, Holly A and Zody, Michael C and Nelson, Bradley J and Huddleston, John and Sandstrom, Richard and Smith, Joshua D and Hanna, David and Swanson, James M and Faustman, Elaine M and Bamshad, Michael J and Stamatoyannopoulos, John and Nickerson, Deborah A and McCallion, Andrew S and Darnell, Robert and Eichler, Evan E} }