A handful of mutation processes operate on the human germline to form small insertions and deletions (indels), large copy number variants (CNVs), inversions, translocations and more complex changes in chromosome structure. These diverse mutations are collectively referred to as structural variation (SV). Assessing the functional and pathogenic impact of singleton and rare structural variants in disease is one of the most pressing and understudied problems in human genetics today. Here we describe methodological innovations for integrating structural variation into eQTL studies, and then transforming knowledge learned from GTEx data into a probabilistic pathogenicity assessment tool that can be used by a wide range of researchers. We will pilot new approaches for integrating SVs and single nucleotide variants (SNVs) in a coherent framework. The centerpiece of this integrative effort will be a new model- based pathogenicity assessment method that will integrate (i) knowledge gleaned from GTEx analyses, (ii) recent breakthroughs in classification of Mendelian disease genes, and (iii) the rapidly expanding set of known disease mutations matriculating from array- and sequencing-based studies of severe Mendelian and other pediatric diseases. This method will be the first tool for generic functional assessment of both SVs and SNVs and will interpret variation affecting coding and/or non-coding regions.

Public Health Relevance

It is estimated that approximately 15% of cases of idiopathic intellectual disability and congenital defects are caused by chromosomal rearrangements. This number is certainly an underestimate, as no tools exist to evaluate the functional impact of most chromosomal rearrangements. In this project we will develop novel model-based methods for improved interpretation of this class of mutation, driven in part by the new availability of extensive gene expression data from multiple human tissues.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH101810-02
Application #
8706981
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Addington, Anjene M
Project Start
2013-08-01
Project End
2016-06-30
Budget Start
2014-07-01
Budget End
2015-06-30
Support Year
2
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Washington University
Department
Genetics
Type
Schools of Medicine
DUNS #
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Zhang, Mingfeng; Lykke-Andersen, Soren; Zhu, Bin et al. (2018) Characterising cis-regulatory variation in the transcriptome of histologically normal and tumour-derived pancreatic tissues. Gut 67:521-533
Kasak, Laura; Punab, Margus; Nagirnaja, Liina et al. (2018) Bi-allelic Recessive Loss-of-Function Variants in FANCM Cause Non-obstructive Azoospermia. Am J Hum Genet 103:200-212
Agrawal, A; Chou, Y-L; Carey, C E et al. (2018) Genome-wide association study identifies a novel locus for cannabis dependence. Mol Psychiatry 23:1293-1302
McCoy, Rajiv C; Wakefield, Jon; Akey, Joshua M (2017) Impacts of Neanderthal-Introgressed Sequences on the Landscape of Human Gene Expression. Cell 168:916-927.e12
Tsai, Teresa; Veitinger, Sophie; Peek, Irina et al. (2017) Two olfactory receptors-OR2A4/7 and OR51B5-differentially affect epidermal proliferation and differentiation. Exp Dermatol 26:58-65
Ho, Nicholas R Y; Usmani, Abul R; Yin, Yan et al. (2017) Multiplex shRNA Screening of Germ Cell Development by in Vivo Transfection of Mouse Testis. G3 (Bethesda) 7:247-255
Collado-Torres, Leonardo; Nellore, Abhinav; Kammers, Kai et al. (2017) Reproducible RNA-seq analysis using recount2. Nat Biotechnol 35:319-321
Benítez-Buelga, Carlos; Baquero, Juan Miguel; Vaclova, Tereza et al. (2017) Genetic variation in the NEIL2 DNA glycosylase gene is associated with oxidative DNA damage in BRCA2 mutation carriers. Oncotarget 8:114626-114636
Tukiainen, Taru; Villani, Alexandra-Chloé; Yen, Angela et al. (2017) Landscape of X chromosome inactivation across human tissues. Nature 550:244-248
Chiang, Colby; Scott, Alexandra J; Davis, Joe R et al. (2017) The impact of structural variation on human gene expression. Nat Genet 49:692-699

Showing the most recent 10 out of 49 publications