Ni Huang, Ph.D.
Year in Program: Second Year
Donald F. Conrad, Ph.D.
Department of Genetics
Washington University School of Medicine
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Dr. Ni Huang's project involves the extension of program initially developed by his primary mentor Dr. Conrad to discover de novo CNVs in family-based genetic data.
DenovoGear is a tool developed by Dr. Don Conrad originally for discovering germ line de novo SNPs from trio sequencing data . This project includes developing statistical methods adapted to data generated from single-cell DNA sequencing and RNAseq of a variety of tissues from a large cohort of individuals produced by the GTEx (Genotype-Tissue Expression) project . The method uses a tree-based Bayesian model to call de novo mutations and infer their mutation history. The method has been applied to simulated and existing single-cell DNA sequencing dataset and a small set of GTEx RNAseq data for proof of principle. We will continue to develop the methods and apply them to the full GTEx and other dataset. Ultimately the aim is to have a suite of programs under DenovoGear that have wide support for different types of data and variants and be able to test for differences in mutation rate in different tissues and at different developmental stages.
Recently, de novo mutation has emerged as an extremely important risk factor for a variety of neuropsychiatric diseases such as autism, schizophrenia and epilepsy. For instance, a recent study identified de novo CNVs in 7.9% of children affected with autism but 2% of control children . These findings suggest de novo mutation may play an important role in other psychiatric disease such as addiction. In addition to the de novo mutations that arise in the germ line, somatic variation in cell populations within an individual, traditionally thought to be only significant in tumor tissues, have recently been found to be prevalent in normal tissues and contribute to diseases such as hemimegalencephaly [2,3]. The recent application of NGS at tissue and single-cell level, provides good opportunities to directly assess these somatic de novo mutations and to shed light on the mechanism and developmental history of mutations as well as their pathogenic potentials [4,5].
 Sebat J, Lakshmi B, et al. Strong association of de novo copy number mutations with autism. Science, 316(5823):445–9, Apr 2007.
 Abyzov A, Mariani J, et al. Somatic copy number mosaicism in human skin revealed by induced pluripotent stem cells. Nature, 492(7429):438–42, Dec 2012.
 Evrony GD, Cai X, et al. Single-neuron sequencing analysis of l1 retro- transposition and somatic mutation in the human brain. Cell, 151(3):483–96, Oct 2012.
 Voet T, Kumar P, et al. Single-cell paired-end genome sequencing reveals structural variation per cell cycle. Nucleic Acids Res, Apr 2013.
 Newburger DE, Kashef-Haghighi D, et al. Genome evolution during progression to breast cancer. Genome Res, May 2013.
 Conrad DF, Keebler JEM, et al. Variation in genome-wide mutation rates within and between human families. Nat Genet, 43(7):712–4, Jul 2011.
 Website: Genotype-Tissue Expression (GTEx). http://commonfund.nih.gov/GTEx/ Accessed: 07/15/2013.
Huang, N. (Oral Presentation): Model-based analysis of transcriptome sequence variation across dozens of human tissues. R25 Fellowship Symposium: Statistical and Computational Innovation in Addiction Genetics, Washington University School of Medicine, Saint Louis, MO, December 2013.
Wheeler E, Huang N, Bochukova EG, Keogh JM, Lindsay S, Garg S, Henning E, Blackburn H, Loos RJ, Wareham NJ, O'Rahilly S, Hurles ME, Barroso I, Farooqi IS. Genome-wide SNP and CNV analysis identifies common and low-frequency variants associated with severe early-onset obesity. Nat Genet. 2013 May; 45(5):513-7. doi: 10.1038/ng.2607. Epub 2013 Apr 7. PMID: 23563609.
Lopes AM, Aston KI, Thompson E, Carvalho F, Gonçalves J, Huang N, Matthiesen R, Noordam MJ, et al. Human spermatogenic failure purges deleterious mutation load from the autosomes and both sex chromosomes, including the gene DMRT1. PLoS Genet. 2013 Mar; 9(3):e1003349. PMID: 23555275. PMCID: PMC3605256.