@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 {110, title = {Molecular diagnostic experience of whole-exome sequencing in adult patients.}, journal = {Genet Med}, volume = {18}, year = {2016}, month = {2016 07}, pages = {678-85}, abstract = {

PURPOSE: Whole-exome sequencing (WES) is increasingly used as a diagnostic tool in medicine, but prior reports focus on predominantly pediatric cohorts with neurologic or developmental disorders. We describe the diagnostic yield and characteristics of WES in adults.

METHODS: We performed a retrospective analysis of consecutive WES reports for adults from a diagnostic laboratory. Phenotype composition was determined using Human Phenotype Ontology terms.

RESULTS: Molecular diagnoses were reported for 17.5\% (85/486) of adults, which is lower than that for a primarily pediatric population (25.2\%; P = 0.0003); the diagnostic rate was higher (23.9\%) for those 18-30 years of age compared to patients older than 30 years (10.4\%; P = 0.0001). Dual Mendelian diagnoses contributed to 7\% of diagnoses, revealing blended phenotypes. Diagnoses were more frequent among individuals with abnormalities of the nervous system, skeletal system, head/neck, and growth. Diagnostic rate was independent of family history information, and de novo mutations contributed to 61.4\% of autosomal dominant diagnoses.

CONCLUSION: Early WES experience in adults demonstrates molecular diagnoses in a substantial proportion of patients, informing clinical management, recurrence risk, and recommendations for relatives. A positive family history was not predictive, consistent with molecular diagnoses often revealed by de novo events, informing the Mendelian basis of genetic disease in adults.Genet Med 18 7, 678-685.

}, keywords = {Adult, Exome, Female, Genetic Diseases, Inborn, Genetic Predisposition to Disease, Genetic Testing, Genome, Human, High-Throughput Nucleotide Sequencing, Humans, Male, Pathology, Molecular}, issn = {1530-0366}, doi = {10.1038/gim.2015.142}, author = {Posey, Jennifer E and Rosenfeld, Jill A and James, Regis A and Bainbridge, Matthew and Niu, Zhiyv and Wang, Xia and Dhar, Shweta and Wiszniewski, Wojciech and Akdemir, Zeynep H C and Gambin, Tomasz and Xia, Fan and Person, Richard E and Walkiewicz, Magdalena and Shaw, Chad A and Sutton, V Reid and Beaudet, Arthur L and Muzny, Donna and Eng, Christine M and Yang, Yaping and Gibbs, Richard A and Lupski, James R and Boerwinkle, Eric and Plon, Sharon E} } @article {102, title = {Multiallelic Positions in the Human Genome: Challenges for Genetic Analyses.}, journal = {Hum Mutat}, volume = {37}, year = {2016}, month = {2016 Mar}, pages = {231-234}, abstract = {

As the amount of human genomic sequence available from personal genomes and exomes has increased, so too has the observation of genomic positions having two or more alternative alleles, so-called multiallelic sites. For portions of the haploid genome that are present in more than one copy, including segmental duplications, variation at such multisite variant positions becomes even more complex. Despite the frequency of multiallelic variants, a number of commonly used resources and tools in genomic research and diagnostics do not support these multiallelic variants all together or require special modifications. Here, we explore the frequency of multiallelic sites in large samples with whole exome sequencing and discuss potential outcomes of failing to account for multiple variant alleles. We also briefly discuss some commonly utilized resources that fully support multiallelic sites.

}, keywords = {Alleles, Exome, Genome, Human, Humans}, issn = {1098-1004}, doi = {10.1002/humu.22944}, author = {Campbell, Ian M and Gambin, Tomasz and Jhangiani, Shalini and Grove, Megan L and Veeraraghavan, Narayanan and Muzny, Donna M and Shaw, Chad A and Gibbs, Richard A and Boerwinkle, Eric and Yu, Fuli and Lupski, James R} } @article {177, title = {Assessing structural variation in a personal genome-towards a human reference diploid genome.}, journal = {BMC Genomics}, volume = {16}, year = {2015}, month = {2015 Apr 11}, pages = {286}, abstract = {

BACKGROUND: Characterizing large genomic variants is essential to expanding the research and clinical applications of genome sequencing. While multiple data types and methods are available to detect these structural variants (SVs), they remain less characterized than smaller variants because of SV diversity, complexity, and size. These challenges are exacerbated by the experimental and computational demands of SV analysis. Here, we characterize the SV content of a personal genome with Parliament, a publicly available consensus SV-calling infrastructure that merges multiple data types and SV detection methods.

RESULTS: We demonstrate Parliament{\textquoteright}s efficacy via integrated analyses of data from whole-genome array comparative genomic hybridization, short-read next-generation sequencing, long-read (Pacific BioSciences RSII), long-insert (Illumina Nextera), and whole-genome architecture (BioNano Irys) data from the personal genome of a single subject (HS1011). From this genome, Parliament identified 31,007 genomic loci between 100 bp and 1 Mbp that are inconsistent with the hg19 reference assembly. Of these loci, 9,777 are supported as putative SVs by hybrid local assembly, long-read PacBio data, or multi-source heuristics. These SVs span 59 Mbp of the reference genome (1.8\%) and include 3,801 events identified only with long-read data. The HS1011 data and complete Parliament infrastructure, including a BAM-to-SV workflow, are available on the cloud-based service DNAnexus.

CONCLUSIONS: HS1011 SV analysis reveals the limits and advantages of multiple sequencing technologies, specifically the impact of long-read SV discovery. With the full Parliament infrastructure, the HS1011 data constitute a public resource for novel SV discovery, software calibration, and personal genome structural variation analysis.

}, keywords = {Computational Biology, Databases, Genetic, Diploidy, Genome, Human, Genomic Structural Variation, Humans, Sequence Analysis, DNA, Software}, issn = {1471-2164}, doi = {10.1186/s12864-015-1479-3}, author = {English, Adam C and Salerno, William J and Hampton, Oliver A and Gonzaga-Jauregui, Claudia and Ambreth, Shruthi and Ritter, Deborah I and Beck, Christine R and Davis, Caleb F and Dahdouli, Mahmoud and Ma, Singer and Carroll, Andrew and Veeraraghavan, Narayanan and Bruestle, Jeremy and Drees, Becky and Hastie, Alex and Lam, Ernest T and White, Simon and Mishra, Pamela and Wang, Min and Han, Yi and Zhang, Feng and Stankiewicz, Pawel and Wheeler, David A and Reid, Jeffrey G and Muzny, Donna M and Rogers, Jeffrey and Sabo, Aniko and Worley, Kim C and Lupski, James R and Boerwinkle, Eric and Gibbs, Richard A} } @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} } @article {329, title = {Human genome sequencing in health and disease.}, journal = {Annu Rev Med}, volume = {63}, year = {2012}, month = {2012}, pages = {35-61}, abstract = {

Following the "finished," euchromatic, haploid human reference genome sequence, the rapid development of novel, faster, and cheaper sequencing technologies is making possible the era of personalized human genomics. Personal diploid human genome sequences have been generated, and each has contributed to our better understanding of variation in the human genome. We have consequently begun to appreciate the vastness of individual genetic variation from single nucleotide to structural variants. Translation of genome-scale variation into medically useful information is, however, in its infancy. This review summarizes the initial steps undertaken in clinical implementation of personal genome information, and describes the application of whole-genome and exome sequencing to identify the cause of genetic diseases and to suggest adjuvant therapies. Better analysis tools and a deeper understanding of the biology of our genome are necessary in order to decipher, interpret, and optimize clinical utility of what the variation in the human genome can teach us. Personal genome sequencing may eventually become an instrument of common medical practice, providing information that assists in the formulation of a differential diagnosis. We outline herein some of the remaining challenges.

}, keywords = {Genetic Diseases, Inborn, Genetic Privacy, Genome, Human, HapMap Project, Human Genome Project, Humans}, issn = {1545-326X}, doi = {10.1146/annurev-med-051010-162644}, author = {Gonzaga-Jauregui, Claudia and Lupski, James R and Gibbs, Richard A} } @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} }