@article {149, title = {Germline mutation in : a heterogeneous, multi-systemic developmental disorder characterized by transcriptional dysregulation.}, journal = {HGG Adv}, volume = {2}, year = {2021}, month = {2021 Jan 14}, abstract = {

germline variation in was recently reported to associate with a neurodevelopmental disorder. We report twelve individuals harboring putatively pathogenic or inherited variants in , detail their phenotypes, and map all known variants to the domain structure of and crystal structure of RNA polymerase II. Affected individuals were ascertained from a local data lake, pediatric genetics clinic, and an online community of families of affected individuals. These include six affected by missense variants (including one previously reported individual), four clinical laboratory samples affected by missense variation with unknown inheritance-with yeast functional assays further supporting altered function-one affected by a in-frame deletion, and one affected by a C-terminal frameshift variant inherited from a largely asymptomatic mother. Recurrently observed phenotypes include ataxia, joint hypermobility, short stature, skin abnormalities, congenital cardiac abnormalities, immune system abnormalities, hip dysplasia, and short Achilles tendons. We report a significantly higher occurrence of epilepsy (8/12, 66.7\%) than previously reported (3/15, 20\%) (p value = 0.014196; chi-square test) and a lower occurrence of hypotonia (8/12, 66.7\%) than previously reported (14/15, 93.3\%) (p value = 0.076309). -related developmental disorders likely represent a spectrum of related, multi-systemic developmental disorders, driven by distinct mechanisms, converging at a single locus.

}, issn = {2666-2477}, doi = {10.1016/j.xhgg.2020.100014}, author = {Hansen, Adam W and Arora, Payal and Khayat, Michael M and Smith, Leah J and Lewis, Andrea M and Rossetti, Linda Z and Jayaseelan, Joy and Cristian, Ingrid and Haynes, Devon and DiTroia, Stephanie and Meeks, Naomi and Delgado, Mauricio R and Rosenfeld, Jill A and Pais, Lynn and White, Susan M and Meng, Qingchang and Pehlivan, Davut and Liu, Pengfei and Gingras, Marie-Claude and Wangler, Michael F and Muzny, Donna M and Lupski, James R and Kaplan, Craig D and Gibbs, Richard A} } @article {122, 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 {108, title = {Next Generation Sequencing of 134 Children with Autism Spectrum Disorder and Regression.}, journal = {Genes (Basel)}, volume = {11}, year = {2020}, month = {2020 07 25}, abstract = {

Approximately 30\% of individuals with autism spectrum disorder (ASD) experience developmental regression, the etiology of which remains largely unknown. We performed a complete literature search and identified 47 genes that had been implicated in such cases. We sequenced these genes in a preselected cohort of 134 individuals with regressive autism. In total, 16 variants in 12 genes with evidence supportive of pathogenicity were identified. They were classified as variants of uncertain significance based on ACMG standards and guidelines. Among these were recurring variants in and , variants in genes that were linked to syndromic forms of ASD (, , , , , and ), and variants in the form of oligogenic heterozygosity (, , and ).

}, keywords = {Autism Spectrum Disorder, Child, Child, Preschool, Cohort Studies, Disease Progression, Female, Gene Expression Regulation, Genetic Markers, Genetic Predisposition to Disease, High-Throughput Nucleotide Sequencing, Humans, Infant, Male, Mutation}, issn = {2073-4425}, doi = {10.3390/genes11080853}, author = {Yin, Jiani and Chun, Chun-An and Zavadenko, Nikolay N and Pechatnikova, Natalia L and Naumova, Oxana Yu and Doddapaneni, Harsha V and Hu, Jianhong and Muzny, Donna M and Schaaf, Christian P and Grigorenko, Elena L} } @article {128, title = {Phenotypic expansion in KIF1A-related dominant disorders: A description of novel variants and review of published cases.}, journal = {Hum Mutat}, volume = {41}, year = {2020}, month = {2020 12}, pages = {2094-2104}, abstract = {

KIF1A is a molecular motor for membrane-bound cargo important to the development and survival of sensory neurons. KIF1A dysfunction has been associated with several Mendelian disorders with a spectrum of overlapping phenotypes, ranging from spastic paraplegia to intellectual disability. We present a novel pathogenic in-frame deletion in the KIF1A molecular motor domain inherited by two affected siblings from an unaffected mother with apparent germline mosaicism. We identified eight additional cases with heterozygous, pathogenic KIF1A variants ascertained from a local data lake. Our data provide evidence for the expansion of KIF1A-associated phenotypes to include hip subluxation and dystonia~as well as phenotypes observed in only a single case: gelastic cataplexy, coxa valga, and double collecting system. We review the literature and suggest that KIF1A dysfunction is better understood as a single neuromuscular disorder with variable involvement of other organ systems than a set of discrete disorders converging at a single locus.

}, issn = {1098-1004}, doi = {10.1002/humu.24118}, author = {Montenegro-Garreaud, Ximena and Hansen, Adam W and Khayat, Michael M and Chander, Varuna and Grochowski, Christopher M and Jiang, Yunyun and Li, He and Mitani, Tadahiro and Kessler, Elena and Jayaseelan, Joy and Shen, Hua and Gezdirici, Alper and Pehlivan, Davut and Meng, Qingchang and Rosenfeld, Jill A and Jhangiani, Shalini N and Madan-Khetarpal, Suneeta and Scott, Daryl A and Abarca-Barriga, Hugo and Trubnykova, Milana and Gingras, Marie-Claude and Muzny, Donna M and Posey, Jennifer E and Liu, Pengfei and Lupski, James R and Gibbs, Richard A} } @article {54, title = {Atlas-CNV: a validated approach to call single-exon CNVs in the eMERGESeq gene panel.}, journal = {Genet Med}, volume = {21}, year = {2019}, month = {2019 Sep}, pages = {2135-2144}, abstract = {

PURPOSE: To provide a validated method to confidently identify exon-containing copy-number variants (CNVs), with a low false discovery rate (FDR), in targeted sequencing data from a clinical laboratory with particular focus on single-exon CNVs.

METHODS: DNA sequence coverage data are normalized within each sample and subsequently exonic CNVs are identified in a batch of samples, when the target log ratio of the sample to the batch median exceeds defined thresholds. The quality of exonic CNV calls is assessed by C-scores (Z-like scores) using thresholds derived from gold standard samples and simulation studies. We integrate an ExonQC threshold to lower FDR and compare performance with alternate software (VisCap).

RESULTS: Thirteen CNVs were used as a truth set to validate Atlas-CNV and compared with VisCap. We demonstrated FDR reduction in validation, simulation, and 10,926 eMERGESeq samples without sensitivity loss. Sixty-four multiexon and 29 single-exon CNVs with high C-scores were assessed by~Multiplex Ligation-dependent Probe Amplification (MLPA).

CONCLUSION: Atlas-CNV is validated as a method to identify exonic CNVs in targeted sequencing data generated in the clinical laboratory. The ExonQC and C-score assignment can reduce FDR (identification of targets with high variance) and improve calling accuracy of single-exon CNVs respectively. We propose guidelines and criteria to identify high confidence single-exon CNVs.

}, issn = {1530-0366}, doi = {10.1038/s41436-019-0475-4}, author = {Chiang, Theodore and Liu, Xiuping and Wu, Tsung-Jung and Hu, Jianhong and Sedlazeck, Fritz J and White, Simon and Schaid, Daniel and Andrade, Mariza de and Jarvik, Gail P and Crosslin, David and Stanaway, Ian and Carrell, David S and Connolly, John J and Hakonarson, Hakon and Groopman, Emily E and Gharavi, Ali G and Fedotov, Alexander and Bi, Weimin and Leduc, Magalie S and Murdock, David R and Jiang, Yunyun and Meng, Linyan and Eng, Christine M and Wen, Shu and Yang, Yaping and Muzny, Donna M and Boerwinkle, Eric and Salerno, William and Venner, Eric and Gibbs, Richard A} } @article {60, 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.

}, 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 {49, title = {Characterizing reduced coverage regions through comparison of exome and genome sequencing data across 10 centers.}, journal = {Genet Med}, volume = {20}, year = {2018}, month = {2018 08}, pages = {855-866}, abstract = {

PURPOSE: As massively parallel sequencing is increasingly being used for clinical decision making, it has become critical to understand parameters that affect sequencing quality and to establish methods for measuring and reporting clinical sequencing standards. In this report, we propose a definition for reduced coverage regions and describe a set of standards for variant calling in clinical sequencing applications.

METHODS: To enable sequencing centers to assess the regions of poor sequencing quality in their own data, we optimized and used a tool (ExCID) to identify reduced coverage loci within genes or regions of particular interest. We used this framework to examine sequencing data from 500 patients generated in 10 projects at sequencing centers in the National Human Genome Research Institute/National Cancer Institute Clinical Sequencing Exploratory Research Consortium.

RESULTS: This approach identified reduced coverage regions in clinically relevant genes, including known clinically relevant loci that were uniquely missed at individual centers, in multiple centers, and in all centers.

CONCLUSION: This report provides a process road map for clinical sequencing centers looking to perform similar analyses on their data.

}, keywords = {Base Sequence, Chromosome Mapping, Exome, Genome, Human, High-Throughput Nucleotide Sequencing, Humans, Sequence Analysis, DNA, Software, Whole Exome Sequencing, Whole Genome Sequencing}, issn = {1530-0366}, doi = {10.1038/gim.2017.192}, author = {Sanghvi, Rashesh V and Buhay, Christian J and Powell, Bradford C and Tsai, Ellen A and Dorschner, Michael O and Hong, Celine S and Lebo, Matthew S and Sasson, Ariella and Hanna, David S and McGee, Sean and Bowling, Kevin M and Cooper, Gregory M and Gray, David E and Lonigro, Robert J and Dunford, Andrew and Brennan, Christine A and Cibulskis, Carrie and Walker, Kimberly and Carneiro, Mauricio O and Sailsbery, Joshua and Hindorff, Lucia A and Robinson, Dan R and Santani, Avni and Sarmady, Mahdi and Rehm, Heidi L and Biesecker, Leslie G and Nickerson, Deborah A and Hutter, Carolyn M and Garraway, Levi and Muzny, Donna M and Wagle, Nikhil} } @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 {9, title = {Resolution of Disease Phenotypes Resulting from Multilocus Genomic Variation.}, journal = {N Engl J Med}, volume = {376}, year = {2017}, month = {2017 Jan 05}, pages = {21-31}, abstract = {

BACKGROUND: Whole-exome sequencing can provide insight into the relationship between observed clinical phenotypes and underlying genotypes.

METHODS: We conducted a retrospective analysis of data from a series of 7374 consecutive unrelated patients who had been referred to a clinical diagnostic laboratory for whole-exome sequencing; our goal was to determine the frequency and clinical characteristics of patients for whom more than one molecular diagnosis was reported. The phenotypic similarity between molecularly diagnosed pairs of diseases was calculated with the use of terms from the Human Phenotype Ontology.

RESULTS: A molecular diagnosis was rendered for 2076 of 7374 patients (28.2\%); among these patients, 101 (4.9\%) had diagnoses that involved two or more disease loci. We also analyzed parental samples, when available, and found that de novo variants accounted for 67.8\% (61 of 90) of pathogenic variants in autosomal dominant disease genes and 51.7\% (15 of 29) of pathogenic variants in X-linked disease genes; both variants were de novo in 44.7\% (17 of 38) of patients with two monoallelic variants. Causal copy-number variants were found in 12 patients (11.9\%) with multiple diagnoses. Phenotypic similarity scores were significantly lower among patients in whom the phenotype resulted from two distinct mendelian disorders that affected different organ systems (50 patients) than among patients with disorders that had overlapping phenotypic features (30 patients) (median score, 0.21 vs. 0.36; P=1.77{\texttimes}10).

CONCLUSIONS: In our study, we found multiple molecular diagnoses in 4.9\% of cases in which whole-exome sequencing was informative. Our results show that structured clinical ontologies can be used to determine the degree of overlap between two mendelian diseases in the same patient; the diseases can be distinct or overlapping. Distinct disease phenotypes affect different organ systems, whereas overlapping disease phenotypes are more likely to be caused by two genes encoding proteins that interact within the same pathway. (Funded by the National Institutes of Health and the Ting Tsung and Wei Fong Chao Foundation.).

}, keywords = {Exome, Genetic Diseases, Inborn, Genetic Variation, Genotyping Techniques, High-Throughput Nucleotide Sequencing, Humans, Phenotype, Retrospective Studies, Sequence Analysis, DNA}, issn = {1533-4406}, doi = {10.1056/NEJMoa1516767}, author = {Posey, Jennifer E and Harel, Tamar and Liu, Pengfei and Rosenfeld, Jill A and James, Regis A and Coban Akdemir, Zeynep H and Walkiewicz, Magdalena and Bi, Weimin and Xiao, Rui and Ding, Yan and Xia, Fan and Beaudet, Arthur L and Muzny, Donna M and Gibbs, Richard A and Boerwinkle, Eric and Eng, Christine M and Sutton, V Reid and Shaw, Chad A and Plon, Sharon E and Yang, Yaping and Lupski, James R} }