@article {657, title = {GGC Repeat Expansion and Exon 1 Methylation of XYLT1 Is a Common Pathogenic Variant in Baratela-Scott Syndrome.}, journal = {Am J Hum Genet}, volume = {104}, year = {2019}, month = {2019 Jan 03}, pages = {35-44}, abstract = {

Baratela-Scott syndrome (BSS) is a rare, autosomal-recessive disorder characterized by short stature, facial dysmorphisms, developmental delay, and skeletal dysplasia caused by pathogenic variants in XYLT1. We report clinical and molecular investigation of 10 families (12 individuals) with BSS. Standard sequencing methods identified biallelic pathogenic variants in XYLT1 in only two families. Of the remaining cohort, two probands had no variants and six probands had only a single variant, including four with a heterozygous 3.1 Mb 16p13 deletion encompassing XYLT1 and two with a heterozygous truncating variant. Bisulfite sequencing revealed aberrant hypermethylation in exon 1 of XYLT1, always in trans with the sequence variant or deletion when present; both alleles were methylated in those with no identified variant. Expression of the methylated XYLT1 allele was severely reduced in fibroblasts from two probands. Southern blot studies combined with repeat expansion analysis of genome sequence data showed that the hypermethylation is associated with expansion of a GGC repeat in the XYLT1 promoter region that is not present in the reference genome, confirming that BSS is a trinucleotide repeat expansion disorder. The hypermethylated allele accounts for 50\% of disease alleles in our cohort and is not present in 130 control subjects. Our study highlights the importance of investigating non-sequence-based alterations, including epigenetic changes, to identify the missing heritability in genetic disorders.

}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2018.11.005}, author = {LaCroix, Amy J and Stabley, Deborah and Sahraoui, Rebecca and Adam, Margaret P and Mehaffey, Michele and Kernan, Kelly and Myers, Candace T and Fagerstrom, Carrie and Anadiotis, George and Akkari, Yassmine M and Robbins, Katherine M and Gripp, Karen W and Baratela, Wagner A R and Bober, Michael B and Duker, Angela L and Doherty, Dan and Dempsey, Jennifer C and Miller, Daniel G and Kircher, Martin and Bamshad, Michael J and Nickerson, Deborah A and Mefford, Heather C and Sol-Church, Katia} } @article {149, title = {The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities.}, journal = {Am J Hum Genet}, volume = {97}, year = {2015}, month = {2015 Aug 06}, pages = {199-215}, abstract = {

Discovering the genetic basis of a Mendelian phenotype establishes a causal link between genotype and phenotype, making possible carrier and population screening and direct diagnosis. Such discoveries also contribute to our knowledge of gene function, gene regulation, development, and biological mechanisms that can be used for developing new therapeutics. As of February 2015, 2,937 genes underlying 4,163 Mendelian phenotypes have been discovered, but the genes underlying \~{}50\% (i.e., 3,152) of all known Mendelian phenotypes are still unknown, and many more Mendelian conditions have yet to be recognized. This is a formidable gap in biomedical knowledge. Accordingly, in December 2011, the NIH established the Centers for Mendelian Genomics (CMGs) to provide the collaborative framework and infrastructure necessary for undertaking large-scale whole-exome sequencing and discovery of the genetic variants responsible for Mendelian phenotypes. In partnership with 529 investigators from 261 institutions in 36 countries, the CMGs assessed 18,863 samples from 8,838 families representing 579 known and 470 novel Mendelian phenotypes as of January 2015. This collaborative effort has identified 956 genes, including 375 not previously associated with human health, that underlie a Mendelian phenotype. These results provide insight into study design and analytical strategies, identify novel mechanisms of disease, and reveal the extensive clinical variability of Mendelian phenotypes. Discovering the gene underlying every Mendelian phenotype will require tackling challenges such as worldwide ascertainment and phenotypic characterization of families affected by Mendelian conditions, improvement in sequencing and analytical techniques, and pervasive sharing of phenotypic and genomic data among researchers, clinicians, and families.

}, keywords = {Genetic Diseases, Inborn, Genetics, Medical, Humans, Phenotype, Proteins}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2015.06.009}, author = {Chong, Jessica X and Buckingham, Kati J and Jhangiani, Shalini N and Boehm, Corinne and Sobreira, Nara and Smith, Joshua D and Harrell, Tanya M and McMillin, Margaret J and Wiszniewski, Wojciech and Gambin, Tomasz and Coban Akdemir, Zeynep H and Doheny, Kimberly and Scott, Alan F and Avramopoulos, Dimitri and Chakravarti, Aravinda and Hoover-Fong, Julie and Mathews, Debra and Witmer, P Dane and Ling, Hua and Hetrick, Kurt and Watkins, Lee and Patterson, Karynne E and Reinier, Frederic and Blue, Elizabeth and Muzny, Donna and Kircher, Martin and Bilguvar, Kaya and L{\'o}pez-Gir{\'a}ldez, Francesc and Sutton, V Reid and Tabor, Holly K and Leal, Suzanne M and G{\"u}nel, Murat and Mane, Shrikant and Gibbs, Richard A and Boerwinkle, Eric and Hamosh, Ada and Shendure, Jay and Lupski, James R and Lifton, Richard P and Valle, David and Nickerson, Deborah A and Bamshad, Michael J} } @article {266, title = {A general framework for estimating the relative pathogenicity of human genetic variants.}, journal = {Nat Genet}, volume = {46}, year = {2014}, month = {2014 Mar}, pages = {310-5}, abstract = {

Current methods for annotating and interpreting human genetic variation tend to exploit a single information type (for example, conservation) and/or are restricted in scope (for example, to missense changes). Here we describe Combined Annotation-Dependent Depletion (CADD), a method for objectively integrating many diverse annotations into a single measure (C score) for each variant. We implement CADD as a support vector machine trained to differentiate 14.7 million high-frequency human-derived alleles from 14.7 million simulated variants. We precompute C scores for all 8.6 billion possible human single-nucleotide variants and enable scoring of short insertions-deletions. C scores correlate with allelic diversity, annotations of functionality, pathogenicity, disease severity, experimentally measured regulatory effects and complex trait associations, and they highly rank known pathogenic variants within individual genomes. The ability of CADD to prioritize functional, deleterious and pathogenic variants across many functional categories, effect sizes and genetic architectures is unmatched by any current single-annotation method.

}, keywords = {Genetic Variation, Genome, Human, Genome-Wide Association Study, Humans, INDEL Mutation, Models, Genetic, Molecular Sequence Annotation, Polymorphism, Single Nucleotide, Selection, Genetic, Support Vector Machine}, issn = {1546-1718}, doi = {10.1038/ng.2892}, author = {Kircher, Martin and Witten, Daniela M and Jain, Preti and O{\textquoteright}Roak, Brian J and Cooper, Gregory M and Shendure, Jay} }