@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 {526, title = {The coexistence of copy number variations (CNVs) and single nucleotide polymorphisms (SNPs) at a locus can result in distorted calculations of the significance in associating SNPs to disease.}, journal = {Hum Genet}, volume = {137}, year = {2018}, month = {2018 Jul}, pages = {553-567}, abstract = {

With the recent advance in genome-wide association studies (GWAS), disease-associated single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) have been extensively reported. Accordingly, the issue of incorrect identification of recombination events that can induce the distortion of multi-allelic or hemizygous variants has received more attention. However, the potential distorted calculation bias or significance of a detected association in a GWAS due to the coexistence of CNVs and SNPs in the same genomic region may remain under-recognized. Here we performed the association study within a congenital scoliosis (CS) cohort whose genetic etiology was recently elucidated as a compound inheritance model, including mostly one rare variant deletion CNV null allele and one common variant non-coding hypomorphic haplotype of the TBX6 gene. We demonstrated that the existence of a deletion in TBX6 led to an overestimation of the contribution of the SNPs on the hypomorphic allele. Furthermore, we generalized a model to explain the calculation bias, or distorted significance calculation for an association study, that can be {\textquoteright}induced{\textquoteright} by CNVs at a locus. Meanwhile, overlapping between the disease-associated SNPs from published GWAS and common CNVs (overlap 10\%) and pathogenic/likely pathogenic CNVs (overlap 99.69\%) was significantly higher than the random distribution (p < 1 {\texttimes} 10 and p = 0.034, respectively), indicating that such co-existence of CNV and SNV alleles might generally influence data interpretation and potential outcomes of a GWAS. We also verified and assessed the influence of colocalizing CNVs to the detection sensitivity of disease-associated SNP variant alleles in another adolescent idiopathic scoliosis (AIS) genome-wide association study. We proposed that detecting co-existent CNVs when evaluating the association signals between SNPs and disease traits could improve genetic model analyses and better integrate GWAS with robust Mendelian principles.

}, keywords = {Adolescent, Congenital Abnormalities, DNA Copy Number Variations, Female, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Genomics, Genotype, Haplotypes, Humans, Phenotype, Polymorphism, Single Nucleotide, Scoliosis}, issn = {1432-1203}, doi = {10.1007/s00439-018-1910-3}, author = {Liu, Jiaqi and Zhou, Yangzhong and Liu, Sen and Song, Xiaofei and Yang, Xin-Zhuang and Fan, Yanhui and Chen, Weisheng and Akdemir, Zeynep Coban and Yan, Zihui and Zuo, Yuzhi and Du, Renqian and Liu, Zhenlei and Yuan, Bo and Zhao, Sen and Liu, Gang and Chen, Yixin and Zhao, Yanxue and Lin, Mao and Zhu, Qiankun and Niu, Yuchen and Liu, Pengfei and Ikegawa, Shiro and Song, You-Qiang and Posey, Jennifer E and Qiu, Guixing and Zhang, Feng and Wu, Zhihong and Lupski, James R and Wu, Nan} } @article {357, title = {Lessons learned from additional research analyses of unsolved clinical exome cases.}, journal = {Genome Med}, volume = {9}, year = {2017}, month = {2017 03 21}, pages = {26}, abstract = {

BACKGROUND: Given the rarity of most single-gene Mendelian disorders, concerted efforts of data exchange between clinical and scientific communities are critical to optimize molecular diagnosis and novel disease gene discovery.

METHODS: We designed and implemented protocols for the study of cases for which a plausible molecular diagnosis was not achieved in a clinical genomics diagnostic laboratory (i.e. unsolved clinical exomes). Such cases were recruited to a research laboratory for further analyses, in order to potentially: (1) accelerate novel disease gene discovery; (2) increase the molecular diagnostic yield of whole exome sequencing (WES); and (3) gain insight into the genetic mechanisms of disease. Pilot project data included 74 families, consisting mostly of parent-offspring trios. Analyses performed on a research basis employed both WES from additional family members and complementary bioinformatics approaches and protocols.

RESULTS: Analysis of all possible modes of Mendelian inheritance, focusing on both single nucleotide variants (SNV) and copy number variant (CNV) alleles, yielded a likely contributory variant in 36\% (27/74) of cases. If one includes candidate genes with variants identified within a single family, a potential contributory variant was identified in a total of ~51\% (38/74) of cases enrolled in this pilot study. The molecular diagnosis was achieved in 30/63 trios (47.6\%). Besides this, the analysis workflow yielded evidence for pathogenic variants in disease-associated genes in 4/6 singleton cases (66.6\%), 1/1 multiplex family involving three affected siblings, and 3/4 (75\%) quartet families. Both the analytical pipeline and the collaborative efforts between the diagnostic and research laboratories provided insights that allowed recent disease gene discoveries (PURA, TANGO2, EMC1, GNB5, ATAD3A, and MIPEP) and increased the number of novel genes, defined in this study as genes identified in more than one family (DHX30 and EBF3).

CONCLUSION: An efficient genomics pipeline in which clinical sequencing in a diagnostic laboratory is followed by the detailed reanalysis of unsolved cases in a research environment, supplemented with WES data from additional family members, and subject to adjuvant bioinformatics analyses including relaxed variant filtering parameters in informatics pipelines, can enhance the molecular diagnostic yield and provide mechanistic insights into Mendelian disorders. Implementing these approaches requires collaborative clinical molecular diagnostic and research efforts.

}, keywords = {Adenosine Triphosphatases, ATPases Associated with Diverse Cellular Activities, Computational Biology, DNA Copy Number Variations, DNA-Binding Proteins, Exome, Female, Genetic Diseases, Inborn, Genomics, GTP-Binding Protein beta Subunits, Humans, Male, Membrane Proteins, Metalloendopeptidases, Mitochondrial Proteins, Pilot Projects, Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Transcription Factors}, issn = {1756-994X}, doi = {10.1186/s13073-017-0412-6}, author = {Eldomery, Mohammad K and Coban-Akdemir, Zeynep and Harel, Tamar and Rosenfeld, Jill A and Gambin, Tomasz and Stray-Pedersen, Asbj{\o}rg and K{\"u}ry, S{\'e}bastien and Mercier, Sandra and Lessel, Davor and Denecke, Jonas and Wiszniewski, Wojciech and Penney, Samantha and Liu, Pengfei and Bi, Weimin and Lalani, Seema R and Schaaf, Christian P and Wangler, Michael F and Bacino, Carlos A and Lewis, Richard Alan and Potocki, Lorraine and Graham, Brett H and Belmont, John W and Scaglia, Fernando and Orange, Jordan S and Jhangiani, Shalini N and Chiang, Theodore and Doddapaneni, Harsha and Hu, Jianhong and Muzny, Donna M and Xia, Fan and Beaudet, Arthur L and Boerwinkle, Eric and Eng, Christine M and Plon, Sharon E and Sutton, V Reid and Gibbs, Richard A and Posey, Jennifer E and Yang, Yaping and Lupski, James R} }