The methylation imbalances at thousands of loci are explainable by different relative frequencies of the methylated and unmethylated states for the two alleles. Our data from yeast and mammalian cells are in excellent agreement with known messenger RNA structures and with the high-resolution crystal structure of the Saccharomyces cerevisiae ribosome10. Manolis Kellis is a professor at MIT and head of the MIT Computational Biology Group. However, knowledge of the global structure of the transcriptome is limited to cellular systems at steady state, thus hindering the understanding of RNA structure dynamics during biological transitions and how it influences gene function. We study the relationship between recombination rate and gene regulatory domains, defined by a gene and its linked control elements. 2007 Dec;17(12):1823-36. Finally, GWAS-based enrichment analysis identifies glia, vascular cells, and cone photoreceptors to be associated with the risk of AMD. We annotate 30,247 genetic variants associated with 534 traits, recognize principal and partner tissues underlying each trait, infer trait-tissue, tissue-tissue and trait-trait relationships, and partition multifactorial traits into their tissue-specific contributing factors. The approach can increase predictive power for specific tasks, integrate diverse datasets across data types, and provide greater generalization given the focus on representation learning and not simply classification accuracy. However, reference organismal interactomes do not capture the tissue- and cell type-specific context in which proteins and modules preferentially act. Biophysical models that directly predict these interactions are incomplete and confined to specific types of structures, but computational analysis of large-scale experimental datasets allows regulatory motifs to be identified by their over- representation in target sequences. Epub 2009 Mar 18, Nature. We demonstrate that these 'sub-threshold' signals represent novel loci, and that epigenomic maps are effective at discriminating true biological signals from noise. It is an NIH-sponsored project that seeks to characterize genetic variation in human tissues with roles in diabetes, heart disease, and cancer. Lin, Carlson, Crosby, Matthews, Yu, Park, Wan, Schroeder, Gramates, St, Roark, Wiley, Kulathinal, Zhang, Myrick, Antone, Celniker, Gelbart, Kellis. We demonstrated only our approach can accurately redeem causal genes, even without knowing actual individual-level data, despite the presence of competing non-causal trails. We observed that on a global level, translation guides structure rather than structure guiding translation. The availability of sequenced genomes from 12 Drosophila species has enabled the use of comparative genomics for the systematic discovery of functional elements conserved within this genus. The AI Podcast Dashboard. Although a large number of methods and approaches exist, robustly identifying underlying cell states and their associations is still a major challenge; given the nonexclusive and dynamic influence of multiple unknown sources of variability, the existence of state continuum at the time-scale of observation, and the inevitable snapshot nature of experiments. Surprisingly, key components of the mating and meiosis pathways are missing from several species. May 20, 2019.  He started 6.881: Computational Personal Genomics: Making sense of complete genomes. Boyle, Araya, Brdlik, Cayting, Cheng, Cheng, Gardner, Hillier, Janette, Jiang, Kasper, Kawli, Kheradpour, Kundaje, Li, Ma, Niu, Rehm, Rozowsky, Slattery, Spokony, Terrell, Vafeados, Wang, Weisdepp, Wu, Xie, Yan, Feingold, Good, Pazin, Huang, Bickel, Brenner, Reinke, Waterston, Gerstein, White, Kellis, Snyder, Despite the large evolutionary distances between metazoan species, they can show remarkable commonalities in their biology, and this has helped to establish fly and worm as model organisms for human biology. Professor, Computer Science, MIT Head, MIT Computational Biology Group Institute Member, Broad Institute of MIT and Harvard Principal Investigator, Computer Science and Artificial Intelligence Lab Stata Center - 32D.524 - 617.253.2419 Awards: - US Presidential Early Career Award - Alfred P. Sloan Foundation Award Relative to evolutionarily young lincRNAs, mammalian-expressed lincRNAs show higher primary sequence conservation in their promoters and exons, increased proximity to protein-coding genes enriched for tissue-specific functions, fewer repeat elements, and more frequent single-exon transcripts. Here we report a new approach to identifying large non-coding RNAs using chromatin-state maps to discover discrete transcriptional units intervening known protein-coding loci. Overlap with disease-associated variants indicates that our findings will be relevant for studies of human biology, health and disease. Lastly, new massively parallel reporter experiments can systematically validate regulatory predictions. However, although it has long been appreciated that population-related effects such as incomplete lineage sorting (ILS) can dramatically affect the gene tree, many of the most popular reconciliation methods consider discordance only due to gene duplication and loss (and sometimes horizontal gene transfer).  They showed that this mechanism operates in the fat cells of both humans and mice and detailed how changes within the relevant genomic regions cause a shift from dissipating energy as heat (thermogenesis) to storing energy as fat. We observed that the chromatin state at promoters and CTCF-binding at insulators is largely invariant across diverse cell types.  A major focus of his work is understanding the effects of genetic variations on human disease, with contributions to obesity, diabetes, Alzheimer's disease, schizophrenia, and cancer. ChromHMM uses these signatures to generate a genome-wide annotation for each cell type by calculating the most probable state for each genomic segment. We find that species at a broad range of distances are comparably effective informants for pairwise comparative gene identification, but that these are surpassed by multi-species comparisons at similar evolutionary divergence. In contrast, enhancers are marked with highly cell-type-specific histone modification patterns, strongly correlate to cell-type-specific gene expression programs on a global scale, and are functionally active in a cell-type-specific manner. The resource we provide is accessible both for browsing a small number of factors and for performing large-scale systematic analyses. Manolis Kellis received his B.S., M.S. We have previously developed a chromatin-immunoprecipitation-based microarray method (ChIP-chip) to locate promoters, enhancers and insulators in the human genome. , To date, his lab has developed specific domain expertise in obesity, diabetes, Alzheimer's disease, schizophrenia, and cancer.. Manolis Kellis, Ph.D. We find a coordinated downregulation of synaptic plasticity genes and regulatory regions, and upregulation of immune response genes and regulatory regions, which are targeted by factors that belong to the ETS family of transcriptional regulators, including PU.1. The virus spreads asymptomatically. Manolis Kellis Despite large experimental and computational efforts aiming to dissect the mechanisms underlying disease risk, mapping cis-regulatory elements to target genes remains a challenge.  A full understanding of the phenomenon may lead to treatments for people whose 'slow metabolism' cause them to gain excessive weight. Our single-cell transcriptomic resource provides a blueprint for interrogating the molecular and cellular basis of Alzheimer's disease, Wang, He, Goggin, Saadat, Wang, Sinnott-Armstrong, Claussnitzer*, Kellis*, Genome-wide epigenomic maps have revealed millions of putative enhancers and promoters, but experimental validation of their function and high-resolution dissection of their driver nucleotides remain limited. Chromatin states are learned, annotations are produced, and enrichments are computed within 1 day. Overall, myelination-related processes were recurrently perturbed in multiple cell types, suggesting that myelination has a key role in Alzheimer's disease pathophysiology. Andreas joined Carnegie Mellon University in 2016 after completing training with Dr. Manolis Kellis as a postdoctoral associate in a joint position between the Computer Science and Artificial Intelligence Laboratory of the Massachusetts Institute of Technology and the … Several years after the initial sequencing of the genomes from human and other organisms, the vast majority of each genome remains unannotated, and it is still unclear how to translate genomic information into a functional map of cellular and developmental programs. We apply our method to a biological dataset of approximately 4700 gene trees from 100 taxa and observe that 93% of event assignments and 73% of mappings remain consistent across different multiple optima. Existing methods utilize genotypic data and summary statistics to identify putative disease genes, but cannot distinguish pleiotropy from causal mediation and are limited by overly strong assumptions about the data. The variation of recombination rate at both fine and large scales cannot be fully explained by DNA sequences alone. Moreover, the variants from the 95% credible sets exhibited high conservation and enrichments for GTEx whole-blood eQTLs located within transcription-factor-binding-sites and DNA-hypersensitive-sites. Even thermostable RNA structures are often denatured in cells, highlighting the importance of cellular processes in regulating RNA structure. Follow. Interestingly, Eric Lander (one of the founding fathers in this country on large-scale genomic research) was Kellis’s phd advisor and was in the thesis committee of Pachter when he did his phd in math at MIT. Kellis and colleagues used epigenomic data to investigate the mechanistic basis of the strongest genetic association with obesity. New England Journal of Medicine 373(10):895-907. Manolis Kellis 583 views Zuo worked with a postdoc in Kellis' group to use algorithms to identify related clusters of genes in a single cell type within a specific tissue. Such loci are enriched for stochastic switching, which is defined as random transitions between fully methylated and unmethylated states of DNA. We also developed a functional genomics approach that assigns putative functions to each lincRNA, demonstrating a diverse range of roles for lincRNAs in processes from embryonic stem cell pluripotency to cell proliferation. Unlike existing methods rely on strong and unrealistic assumptions, we tackle practical challenges within a principled summary-based causal inference framework. We develop a novel computational model to classify exosomal transcripts into tumor and non-tumor components and establish relevance in immune checkpoint blockade therapy. Our algorithm relies on a new reconciliation structure, the labeled coalescent tree (LCT), that simultaneously describes coalescent and duplication-loss history. Using both simulation and real data, we show that mixEHR outperforms previous methods and reveals meaningful multi-disease insights, Park, Sarkar, He, Davila-Velderrain, De Jager, Kellis. bioRxiv 810291; October 19, 2019; doi.org/10.1101/810291. The latter function is enabled by RNA's ability to adopt complex secondary and tertiary folds and thus has motivated extensive computational1, 2 and experimental3, 4, 5, 6, 7, 8 efforts for determining RNA structures. We define multi-cell activity profiles that reflect the patterns of enhancer state activity across cell types, as well as analogous profiles for gene expression, regulatory motif enrichments, and expression of the corresponding regulators. 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