Sridhar Hannenhalli, Ph.D.
Sridhar Hannenhalli is a computational biologist with broad interests in gene regulatory mechanisms and evolution, with special focus on eukaryotic transcriptional regulation. His lab harnesses a variety of high-throughput omics data to address fundamental biological questions as they pertain to both normal organismal functions, as well as diseases, with a special emphasis on cancer. Their work involves both methodological development as well as collaborative basic science and clinical applications.
1) bioinformatics, 2) transcriptional regulation, 3) cancer genomics
Regulatory driver mutations in cancer. In the broader context of deciphering mechanistic links between genotype and the phenotype, we have developed mechanism-aware statistical models to identify functional genotype-gene expression (i.e., functional eQTL) links. In the context of cancer, the focus has largely been on coding mutations and as such the role of regulatory mutations are only beginning to be deciphered. We are interested in developing mechanism-based models to identify functional, and potentially ‘driver’ regulatory mutations in cancer.
Gene-environment interaction. Gene-environment interaction is of substantial interest in the context of complex diseases as well as cancer. However, a lack of a molecular proxies of ‘environment’ hinders statistical power as well as functional interpretation. In the case of SNP-Age interaction, we have shown that by using TFs whose expression vary strongly with age in a tissue-specific fashion as a proxy for age, and by focusing on SNPs within binding sites of such age-associated TFs, we can not only identify SNP-Age interactions in regulating gene expression with greater power, but the identified interactions can be functionally interpreted and generate experimentally testable hypotheses. Along these lines, epigenomic marks present an additional potent proxy of age and diseases, including cancer. We are interested in developing mechanism-based models of SNP-Environment interactions in cancer.
Epigenomics and 3D chromatin structure. Criticality of epigenomic marks and chromatin structure in transcriptional regulation is well established, however, the precise mechanisms are only starting to be worked out. We are interested in investigating the dysregulation of genes and pathways in cancer in the background of disrupted epigenome and chromatin structures.
Contextual function of genes. Certain regulatory proteins have been shown to drastically change their function during evolution, mediated by small changes to their sequences affecting their interaction partners. Broadly, a protein’s context-specific function is likely to be informed by its context-specific interaction partners, which can change either via transcriptional changes, or via coding mutations. We are interested in investigating the context/tissue-specific function of genes and exploring the utility of such an approach to explain tissue-specific manifestation of various disease phenotypes. Similar functional rewiring in the evolutionary context is also of interest to us.
Genetic interactions in cancer. P53 mutation is highly associated with cancer; however, it is neither sufficient nor required, which points to other, likely genomic or transcriptomic, dependencies. Synthetic lethality is a widely studied gene interaction mechanism in the context of selective cancer therapy. We are interested in generalizing synthetic lethality to other types of interactions, and more broadly, in characterizing the mutational and transcriptional landscape that lends itself to tumorigenic effects of well-established cancer-associated ‘driver’ mutations.
Single-cell omics. One can think of organisms and tissues as organizations of cooperative and coordinating single cells. Recent technological advances have made this viewpoint amenable to principled exploration. Single-cell omics represents the next frontier in the investigation of development and cancer. We are interested in developing methodologies to exploit single-cell omics data to collaboratively probe a variety of questions in development and in cancer.
View Dr. Hannenhalli's Google Scholar page.
View Dr. Hannenhalli's Researchgate page.
Selected Recent Publications
Beyond Synthetic Lethality: Charting the Landscape of Pairwise Gene Expression States Associated with Survival in Cancer.Cell Reports. 28(4): 938-948, 2019. [ Journal Article ]
Single-Cell Profiling Defines Transcriptomic Signatures Specific to Tumor-Reactive versus Virus-Responsive CD4+ T Cells.Cel Reports. 29(10): 3019-3032, 2019. [ Journal Article ]
A network diffusion approach to inferring sample-specific function reveals functional changes associated with breast cancer.PLoS Comput Biol. 13(11): e1005793, 2017. [ Journal Article ]
Distal CpG islands can serve as alternative promoters to transcribe genes with silenced proximal promoters.Genome Res. 27(4): 553-566, 2017. [ Journal Article ]
Bayesian integration of genetics and epigenetics detects causal regulatory SNPs underlying expression variability.Nat Commun. 6: 8555, 2015. [ Journal Article ]
Dr. Hannenhalli obtained a B. Tech from the Indian Institute of Technology (1990) and his Ph.D. in Computer Science from the Pennsylvania State University (1995). After a postdoctoral fellowship at the University of California-San Diego (1996-1997), he worked as a Senior Scientist at Glaxo Smith-Kline (1997-2000) and then at Celera Genomics (2000-2003), where he was involved in the work reporting the first human genome sequence. He was a faculty member in the Department of Genetics at the University of Pennsylvania (2003-2010), and then at the University of Maryland (UMD) with joint appointments in the Department of Cell Biology and Molecular Genetics, and the University of Maryland Institute for Advanced Computer Studies (2010-2019). Dr. Hannenhalli served as Interim Director of the Center for Bioinformatics and Computational Biology at UMD (2012-2013) and was a Fulbright Scholar and Visiting Professor at the Indian Institute of Sciences and the National Center for Biological Sciences, Bengaluru (2017-2018). The Hannenhalli lab is broadly interested in developing computational and statistical approaches to harness the huge amount of biological data to ultimately answer specific biological questions pertaining to gene regulation and evolution, both from the basic science as well as translational perspective, with specific applications to development and diseases, with an emphasis on cancer.
|Position||Degree Required||Contact Name||E-mail Address|
|Post-doctoral Fellow - bioinformatics, epigenomics||Ph.D. or equivalent||Nadia Nimleyfirstname.lastname@example.org|
|Piyush Agrawal Ph.D.||Postdoctoral Fellow (Visiting)|
|Shan Li, Ph.D.||Staff Scientist|
|Gulden Olgun Ph.D.||Postdoctoral Fellow (Visiting)|
|Arati Rajeevan||Postbaccalaureate Fellow (CRTA)|
|Mohd Omar Sikder Ph.D.||Postdoctoral Fellow (CRTA)|
|Arashdeep Singh Ph.D.||Postdoctoral Fellow (Visiting)|
|Vishaka Datta Sreenivasa Gopalan Ph.D.||Postdoctoral Fellow (Visiting)|
|Annan Jinga Timon||Postbaccalaureate Fellow (CRTA)|