Xin He, Ph.D.

Assistant Professor

 Lab Webpage

Research Description

Our lab uses computational approaches to study the genetics of human diseases. A primary focus of our research is to develop novel tools for mapping risk genes of complex diseases in association and family studies. We are also interested in related questions, such as how to predict functional significance of DNA mutations; how genes and environmental factors together influence the disease risks and what is the role of dysregulation of gene expression in diseases.

We develop and employ computational or statistical tools to address our questions, and work closely with geneticists and experimental biologists. A key feature of our strategy is the integration of multiple genomic datasets, such as transcriptome data, epigenetic data, and biological networks. This integrated approach could combine signals in different datasets to increase the power of studies. Furthermore, by putting DNA variations in the context of gene interaction and regulatory networks, it is possible to better understand the mechanism connecting genetic changes to phenotypes. An example of this approach is our method, called Sherlock, that links expression QTL and genome-wide association studies to discover novel disease genes.

We are also interested in computational questions in regulatory genomics. How do cis-regulatory sequences interpret the information in cellular environments to drive spatial-temporal gene expression patterns? How do regulatory sequences change during evolution? We believe a better understanding of these questions will also help the study of human genetics, specifically by improving our ability to interpret variations in non-coding sequences.

Selected Publications

Insights into Autism Spectrum Disorder Genomic Architecture and Biology from 71 Risk Loci.
Sanders SJ, He X, Willsey AJ, Ercan-Sencicek AG, Samocha KE, Cicek AE, Murtha MT, Bal VH, Bishop SL, Dong S, Goldberg AP, Jinlu C, Keaney JF 3rd, Klei L, Mandell JD, Moreno-De-Luca D, Poultney CS, Robinson EB, Smith L, Solli-Nowlan T, Su MY, Teran NA, Walker MF, Werling DM, Beaudet AL, Cantor RM, Fombonne E, Geschwind DH, Grice DE, Lord C, Lowe JK, Mane SM, Martin DM, Morrow EM, Talkowski ME, Sutcliffe JS, Walsh CA, Yu TW, Ledbetter DH, Martin CL, Cook EH, Buxbaum JD, Daly MJ, Devlin B, Roeder K, State MW
(2015 Sep) Neuron. 2015 Sep 23;87(6):1215-33. doi: 10.1016/j.neuron.2015.09.016.26402605 (Full Text)

De novo ChIP-seq analysis.
He X, Cicek AE, Wang Y, Schulz MH, Le HS, Bar-Joseph Z
(2015) Genome Biol. 2015 Sep 23;16:205. doi: 10.1186/s13059-015-0756-4.26400819 (Full Text)

Synaptic, transcriptional and chromatin genes disrupted in autism.
De Rubeis S, He X, Goldberg AP, Poultney CS, Samocha K, Cicek AE, Kou Y, Liu L, Fromer M, Walker S, Singh T, Klei L, Kosmicki J, Shih-Chen F, Aleksic B, Biscaldi M, Bolton PF, Brownfeld JM, Cai J, Campbell NG, Carracedo A, Chahrour MH, Chiocchetti AG, Coon H, Crawford EL, Curran SR, Dawson G, Duketis E, Fernandez BA, Gallagher L, Geller E, Guter SJ, Hill RS, Ionita-Laza J, Jimenz Gonzalez P, Kilpinen H, Klauck SM, Kolevzon A, Lee I, Lei I, Lei J, Lehtimaki T, Lin CF, Ma'ayan A, Marshall CR, McInnes AL, Neale B, Owen MJ, Ozaki N, Parellada M, Parr JR, Purcell S, Puura K, Rajagopalan D, Rehnstrom K, Reichenberg A, Sabo A, Sachse M, Sanders SJ, Schafer C, Schulte-Ruther M, Skuse D, Stevens C, Szatmari P, Tammimies K, Valladares O, Voran A, Li-San W, Weiss LA, Willsey AJ, Yu TW, Yuen RK, Cook EH, Freitag CM, Gill M, Hultman CM, Lehner T, Palotie A, Schellenberg GD, Sklar P, State MW, Sutcliffe JS, Walsh CA, Scherer SW, Zwick ME, Barett JC, Cutler DJ, Roeder K, Devlin B, Daly MJ, Buxbaum JD
(2014 Nov) Nature. 2014 Nov 13;515(7526):209-15. doi: 10.1038/nature13772. Epub 2014 Oct 29.25363760 (Full Text)

Sherlock: detecting gene-disease associations by matching patterns of expression QTL and GWAS.
He X, Fuller CK, Song Y, Meng Q, Zhang B, Yang X, Li H
(2013 May) Am J Hum Genet. 2013 May 2;92(5):667-80. doi: 10.1016/j.ajhg.2013.03.022.23643380 (Full Text)

Integrated model of de novo and inherited genetic variants yields greater power to identify risk genes.
He X, Sanders SJ, Liu L, De Rubeis S, Lim ET, Sutcliffe JS, Schellenberg GD, Gibbs RA, Daly MJ, Buxbaum JD, State MW, Devlin B, Roeder K
(2013) PLoS Genet. 2013;9(8):e1003671. doi: 10.1371/journal.pgen.1003671. Epub 2013 Aug 15.23966865 (Full Text)

Predicting tissue specific transcription factor binding sites.
Zhong S, He X, Bar-Joseph Z
(2013) BMC Genomics. 2013 Nov 15;14:796. doi: 10.1186/1471-2164-14-796.24238150 (Full Text)

Evolutionary origins of transcription factor binding site clusters.
He X, Duque TS, Sinha S
(2012 Mar) Mol Biol Evol. 2012 Mar;29(3):1059-70. doi: 10.1093/molbev/msr277. Epub 2011 Nov 10.22075113 (Full Text)

Thermodynamics-based models of transcriptional regulation by enhancers: the roles of synergistic activation, cooperative binding and short-range repression.
He X, Samee MA, Blatti C, Sinha S
(2010) PLoS Comput Biol. 2010 Sep 16;6(9). pii: e1000935. doi: 10.1371/journal.pcbi.1000935.20862354 (Full Text)

A biophysical model for analysis of transcription factor interaction and binding site arrangement from genome-wide binding data.
He X, Chen CC, Hong F, Fang F, Sinha S, Ng HH, Zhong S
(2009) PLoS One. 2009 Dec 1;4(12):e8155. doi: 10.1371/journal.pone.0008155.19956545 (Full Text)

Alignment and prediction of cis-regulatory modules based on a probabilistic model of evolution.
He X, Ling X, Sinha S
(2009 Mar) PLoS Comput Biol. 2009 Mar;5(3):e1000299. doi: 10.1371/journal.pcbi.1000299. Epub 2009 Mar 13.19293946 (Full Text)

Detecting gene clusters under evolutionary constraint in a large number of genomes.
Ling X, He X, Xin D
(2009 Mar) Bioinformatics. 2009 Mar 1;25(5):571-7. doi: 10.1093/bioinformatics/btp027. Epub 2009 Jan 21.19158161

Evolution of regulatory sequences in 12 Drosophila species.
Kim J, He X, Sinha S
(2009 Jan) PLoS Genet. 2009 Jan;5(1):e1000330. doi: 10.1371/journal.pgen.1000330. Epub 2009 Jan 9.19132088 (Full Text)

Large-scale analysis of transcriptional cis-regulatory modules reveals both common features and distinct subclasses.
Li L, Zhu Q, He X, Sinha S, Halfon MS
(2007) Genome Biol. 2007;8(6):R101.17550599 (Full Text)

Identifying conserved gene clusters in the presence of homology families.
He X, Goldwasser MH
(2005 Jul) J Comput Biol. 2005 Jul-Aug;12(6):638-56.16108708