My Research

Research Projects:

To achieve my research goals, I use genomics (functional and comparative) and computational biology tools (bioinformatic approaches). Here's a list of our efforts - including past and present and those in pipeline also.

Comparative Genomics Tools: Complexity of an organism is not correlated to its number of genes, but to the evolution of diverse modes of intricate gene regulatory mechanisms. 98% of the human genome is non-coding and only 1.5% encodes protein. It is this 98% noncoding DNA that harbors the control switches that turn on or off the 30,000 odd genes represented by the 1.5% protein coding DNA. These modular control switches are called enhancers or silencers depending on how they assist the gene promoters in the transcription. Since these control keys are involved in critical functions, even minute variations resulting from, say, a single nucleotide substitution or mutation, may prove harmful and have the propensity to manifest as a disease process. The paucity of published information about these control regions only highlights the difficulties involved to identify them using traditional wet lab methods. However, the availability of near-complete human and mouse genomes, and comparative genomics-based computational approaches are proving to be invaluable in tackling this problem.

The idea that animal development is controlled by cis-regulatory DNA elements (such as enhancers and silencers) is well established. These elements are thought to comprise clustered target sites for large numbers of transcription factors and collectively form the genomic instructions for developmental gene regulatory networks (GRNs). However, relatively little is known about GRNs in vertebrates. Any approach to elucidate such networks necessitates the discovery of all constituent cis-regulatory elements and their genomic locations. The development of user-friendly computational approaches for the prediction and functional implications of regulatory elements continues to be an important goal also due to the labor-intensive nature of the existing wet-biology methods. In that direction, we have developed a suite of tools to decipher the gene regulatory networks. These include:

  • Trafac: Signal finding or pattern discovery in DNA is like identifying the proverbial needle in the haystack. The only problem is there are too many needles of manifold shapes, colors and sizes! Identification of transcription factor binding sites (TFBS) or cis-elements is a fundamental problem in both computer science and molecular biology with important applications in locating regulatory sites and drug target identification. In spite of several studies and approaches, this problem is far from being resolved. Trafac is one of my very first projects based on the phylogenetic fingerprinting approach that proved to be successful in identifying the regulatory keys.
  • GenomeTrafac - Gene Regulatory Region Repository: The success of Trafac spurred us to develop a regulatory database for all the entries in the human RefSeq database. The human and mouse ortholog information and the exon annotations are based on MGI homology tables and UCSC Golden Path respectively. The genomic sequences (both human and mouse) used for comparative sequence analysis include upstream and downstream flanking 40 kb. Trafac server is used to find out the conserved cis-regulatory regions. The results are stored and can be visualized through graphical presentation, viz., "Regulogram" and "Trafacgram". We have analyzed 9000 human-mouse ortholog gene pairs and are in the process of uploading 6000 more. Though harboring human-mouse orthologous genes currently, the server is adaptable for analyzing any orthologous pair of genes
  • ConCisE Scanner (Conserved Cis-Element Scanner): Concise Scanner was developed primarily as an answer to the question as to what are the potential additional target genes for an identified regulatory module(s). Tools based on the phlyogenetic footprinting like TraFaC (and GenomeTraFaC, the human-mouse gene regulatory region repository created using TraFaC server), and others while helping in identification of potential regulatory regions provide little or no information as to through what genes the transcription factors (TFs) exert their function in the living system. Providing a complement to the above listed phylogenetic approaches, we developed Concise (Conserved Cis Element) Scanner that undertakes a more targeted search, finding phylogenetically conserved regulatory targets of defined transcription factors whose DNA binding site specificity is known. It identifies potential targets of one or more clusters of transcription factors with a defined cis-regulatory target specificity, using human and mouse genomes. It enables you to select one or more transcription binding sites and search all genes in the GenomeTrafac database for clusters containing the selected site(s). Within each cluster, you can view the exact position of each binding site.
  • Cis-Mols: "How often have I said to you that when you have eliminated the impossible, whatever remains, however improbable, must be the truth?" - Sherlock Holmes, A Study in Scarlet. Filtering candidate cis-element clusters based on phylogenetic conservation is helpful for an individual ortholog gene pair, but combining data from cis-conservation and coordinate expression across multiple genes is a more difficult problem. To approach this, we have extended an ortholog gene pair database with additional analytical architecture to allow for the analysis and identification of maximal numbers of compositionally similar and phylogenetically conserved cis-regulatory element clusters from a list of user-selected genes. Starting with identification of cis-clusters in phylogenetic footprints, we intend to extend the query to identify compositionally similar cis regulatory element clusters that occur in groups of co-regulated genes within each of their ortholog-pair evolutionarily conserved cis-regulatory regions. These computationally predicted cis-clusters, which we call as cismols, could serve as valuable probes for genome wide identification of regulatory regions and novel gene targets.

Functional Genomics Server and Repository

  • PolyDoms: There is a wide gap between the growing number of reported nsSNPs in human population and the functional consequences of these nsSNPs, and the major challenge lies in distinguishing the functionally significant and potentially disease-related ones from the rest. PolyDoms is based on the hypothesis that if an nsSNP alters the ability of gene products to function normally within the biological pathways or processes, the consequences might either alter disease susceptibility or resistance or result in disease itself or affect the therapeutic regimen. We mapped the coding SNPs (synonymous and non-synonymous) of all the proteins onto their know protein 3D structure and functional domains. We used the SNP data from the dbSNP, Utah and EGP and for the structure and domains, PDB and Pfam/Smart databases. The database is also supplemented with known protein-protein interactions, mutations (from OMIM and SwissChange) and links to literature references implicating the SNPs with any diseases. We strongly believe that the nsSNPs that are predicted to be functional upon evolutionary conservation analysis and are located in functional protein domains and motifs constitute an excellent resource for specific molecular studies to elucidate the direct consequences of these variations on protein function and interaction, which could also help the molecular epidemiology and genetic studies aiming to reveal the genetic variation-disease risk association.

Systems Biology

  • GKP: Development of a unified Genome Knowledge Platform as part of the BRTT (Biomedical Research and Technology Transfer) Commission, a cooperative venture between Cincinnati Children's Research Foundation, University of Cincinnati, Procter & Gamble Pharmaceuticals, Secant Technologies, Wright State University and the Air Force Research Laboratory. The aims of this grant also include building a Genomic Research Institute, an Ohio state and regional hub for gene and protein profile analysis, bioinformatics software development and medicinal chemistry.
  • Text-processing (Abstrainer):
    1. Extracting protein-protein interactions from biomedical literature (XPrInt): We are using the PreBIND, OMIM, GeneRIF (from LocusLink), MINT, DIP, MIPS, BIND and MedLine abstracts to harvest all available information about protein-protein interactions. Most importantly, we are currently working in storing the validated results in compliance with the HUPO-PSI (HUman Proteomics Organization - Proteomics Standards Inititative) standards. This would overcome the tedious work of combining the data from different data sources again and again, every time there is a new release from any or all of the resources. We are also working on representing the validated protein-protein interactions (all such interactions occurring in more than one of the resource databases used) in a user-friendly graphical output.
    2. Extracting disease-gene associations from biomedical literature, principally from MedLine abstracts (PatholoGene)
    3. Identifying and extracting cis-regulatory and related information by systematic analysis of biomedical literature.

Others:

  • CMGCC (Cincinnati Comparative Mouse Genomics Centers Consortium): The Comparative Mouse Genomics Centers Consortium (CMGCC) was initiated by the EGP (Environmental Genome Project) to develop transgenic and knockout mouse models based on human DNA sequence variants in environmentally responsive genes. These mouse models are tools to improve understanding of the biological significance of human DNA polymorphism. Initially, CMGCC is focusing on variation in genes involved in DNA repair or cell cycle control, because many of these are well characterized environmentally responsive genes.

Representative Publication(s):

Published

2008

  1. Jegga AG and Aronow BJ 2008 Evolutionarily Conserved Noncoding DNA. In: Encyclopedia of Life Sciences (ELS). John Wiley & Sons, Ltd: Chichester. DOI: 10.1002/9780470015902.a0006126.pub2
  2. Takemoto CM, Lee YN, Jegga AG, Zablocki D, Brandal S, Shahlaee A, Huang S, Ye Y, Gowrisankar S, Huynh J, McDevitt MA. Mast cell transcriptional networks. Blood Cells Mol Dis. 2008 Apr 10; [Epub ahead of print]
  3. Kamath MB, Houston IB, Janovski AJ, Zhu X, Gowrisankar S, Jegga AG and DeKoter RP 2008. Myeloid gene activation and T cell/natural killer cell gene repression in cells expressing two distinct PU.1 concentrations. Leukemia; doi:10.1038/leu.2008.67.
  4. Sinha AU, Kaimal V, Chen J and Jegga AG 2008. Dissecting microregulation of a master regulatory network. BMC Genomics 9:88; doi:10.1186/1471-2164-9-88.
  5. Jegga AG, Inga A, Menendez D, Aronow BJ and Resnick MA 2008. Functional evolution of the p53 regulatory network through its target response elements. Proc Natl Acad Sci U S A. 105 (3): 945-950. Epub 2008 Jan 10.

2007

  1. Chen J, Xu H, Aronow BJ, Jegga AG 2007. Improved human disease candidate gene prioritization using mouse phenotype. BMC Bioinformatics 8(1): 392 [Epub ahead of print]; doi:10.1186/1471-2105-8-392
  2. Jegga AG, Chen J, Gowrisankar S, Deshmukh M, Kaimal V, Gudivada R, Kong S and Aronow BJ 2007. GenomeTrafac: A genome-wide database for the detection of conserved transcription factor binding site clusters in both conventional and microRNA mouse-human gene orthologs. Nucleic Acids Research 35 (Database issue): D116-D121; doi:10.1093/nar/gkl1011.
  3. Jegga AG, Gowrisankar S, Chen J and Aronow BJ 2007. PolyDoms: a whole genome database for the identification of non-synonymous coding SNPs with the potential to impact disease. Nucleic Acids Research 35 (Database issue): D700-D706; doi:10.1093/nar/gkl826.
  4. Liu C, Aronow BJ, Jegga AG, Wang N, Miethke A, Mourya R, Bezerra JA 2007. Novel resequencing chip customized to diagnose mutations in patients with inherited syndromes of intrahepatic cholestasis. Gastroenterology 132(1):119-126. Epub 2006 Oct 21.
  5. Diwan A, Koesters AG, Odley AM, Pushkaran S, Baines CP, Spike BT, Daria D, Jegga AG, Geiger H, Aronow BJ, Molkentin JD, Macleod KF, Kalfa TA, Dorn GW 2nd. 2007. Unrestrained erythroblast development in Nix-/- mice reveals a mechanism for apoptotic modulation of erythropoiesis. Proc Natl Acad Sci U S A. 2007 104(16):6794-6799 [Epub ahead of print] [Pdf].
  6. Markey MP, Bergseid J, Bosco EE, Stengel K, Xu H, Mayhew CN, Schwemberger SJ, Braden WA, Jiang Y, Babcock G, Jegga AG, Aronow BJ, Reed MF, Wang JYJ and Knudsen ES 2007. Loss of the retinoblastoma tumor suppressor: differential action on transcriptional programs related to cell cycle control and immune function. Oncogene 26(43): 6307-6318 [Epub ahead of print].
  7. Kaiser S, Park YK, Franklin JL, Halberg RB, Yu M, Jessen WJ, Freudenberg J, Chen X, Haigis K, Jegga AG, et al. 2007. Transcriptional recapitulation and subversion of embryonic colon development by
    mouse colon tumor models and human colon cancer. Genome Biol. 8(7): R131 [Epub ahead of print]
  8. Jegga AG, Aronow B, Handwerger 2007. Microarray-based Gene Expression Analysis of Endocrine Systems: Principles of Experimental Design and Interpretation In Genomics in Endocrinology: DNA Microarray Analysis in Endocrine Health and Disease Series (Contemporary Endocrinology) Handwerger S and Aronow B (Eds.). Humana Press, USA (October 1, 2007) (In press) (Hardcover ISBN: 978-1-58829-651-1).
  9. Jegga AG, Chen J, Gowrisankar S, Deshmukh M and Aronow BJ. GenomeTrafac: A Whole-Genome Resource for the Detection of Conserved Transcription Factor Binding Site Motifs and Clusters in Promoters and Flanking Regions of Known Human-Mouse Gene Orthologs. In Applications of Statistical and Machine Learning Methods in Bioinformatics; Series: Advances in Computational and Systems Biology, Vol 1 (eds. Meller J and Nowak W), 2007 Peter Lang Publishing Group.

2006

  1. Miller SJ, Rangwala F, Williams J, Ackerman P, Kong S, Jegga AG, Kaiser S, Aronow BJ, Frahm S, Kluwe L, Mautner V, Upadhyaya M, Muir D, Wallace M, Hagen J, Quelle DE, Watson MA, Perry A, Gutmann DH, and Ratner N. 2006. Large-Scale molecular comparison of human schwann cells to malignant peripheral nerve sheath tumor cell lines and tissues. Cancer Research 66 (5): 2584-91.

2005

  1. Jegga AG, Gupta A, Gowrisankar S, Deshmukh MA, Connolly S, Finley K, Aronow BJ 2005. CisMols Analyzer: identification of compositionally similar cis-element clusters in ortholog conserved regions of coordinately expressed genes. Nucleic Acids Research 33 (Web Server Issue): W408-W11. [Pdf]
  2. Jegga AG, Kong S, Zhang J, Moseley A, Gupta A, Williams SS, Genter MB and Aronow1 BJ 2005. Comparative Genomics of Tissue Specific Gene Expression In Gene Expression and Regulation (ed. J, Ma), Springer, USA. (see at amazon.com)
  3. Vukkadapu SS, Belli JM, Ishii K, Jegga AG, Hutton JJ, Aronow BJ, Katz JD. Dynamic interaction between T cell-mediated beta cell damage and beta cell repair in the run-up to autoimmune diabetes of the NOD mouse 2005. Physiol Genomics. 21(2): 201-11.

2004

  1. Hutton JJ, Jegga AG, Kong S, Gupta A, Ebert C, Williams S, Katz JD and Aronow BJ 2004. Microarray and comparative genomics-based identification of genes and gene regulatory regions of the mouse immune system. BMC Genomics 5(1): 82 [Oct 25, 2004; Epub ahead of print].
  2. Zhang J, Moseley A, Jegga AG, Gupta A, Witte DP, Sartor M, Medvedovic M, Williams SS, Ley-Ebert C, Coolen L, Egnaczyk G, Genter MB, Lehman M, Lingrel J, Maggio J, Parysek L, Walsh R, Xu M, Aronow BJ. 2004. Neural system-enriched gene expression, relationship to biological pathways and neurological diseases. Physiological Genomics 18:167-83 [Pdf].
  3. Livingston RJ, Von Niederhausern A, Jegga AG, Crawford DC, Carlson CS, Rieder MJ, Gowrisankar S, Aronow BJ, Weiss RB, Nickerson DA. 2004. Pattern of Sequence Variation Across 213 Environmental Response Genes. Genome Res. 14:1821-31. Epub 2004 Sep 13 [Pdf].
  4. Kim J.-w., Zeller KI, Wang Y, Jegga AG, Aronow BJ, O'Donnell KA, and Dang CV 2004. Evaluation of Myc E-Box Phylogenetic Footprints in Glycolytic Genes by Chromatin Immunoprecipitation Assays. Mol. Cell. Biol. 24: 5923-5936 [Pdf].
  5. Bonizzi G, Bebien M, Otero DC, Johnson-Vroom KE, Cao Y, Vu D, Jegga AG, Aronow BJ, Ghosh VG, Rickert RC and Karin M 2004. Activation of IKKalpha target genes depends on recognition of specific kappaB binding sites by RelB:p52 dimers. EMBO J. 23(21): 4202-4210 [Pdf].

2003

  1. Jegga AG and Aronow BJ 2003. Evolutionarily Conserved Noncoding DNA. In Nature Encyclopedia of the Human Genome, Vol 2, pp 347-354. Nature Publishing Group, England and In Encycyclopedia of Life Sciences. John Wiley and Sons, Ltd: Chichester [Pdf].
  2. Zeller KI, Jegga AG, Aronow BJ, O'Donnell KA and Dang CV 2003. An integrated database of genes responsive to the Myc oncogenic transcription factor: identification of direct genomic targets. Genome Biology 4: R69 [Pdf].
  3. Genter MB, Van Veldhoven PP, Jegga AG, Sakthivel B, Kong S, Stanley K, Witte DP, Ebert CL, Aronow BJ. 2003. Microarray-based discovery of highly expressed olfactory mucosal genes: potential roles in the various functions of the olfactory system. Physiol Genomics 16: 67-81. Epub 2003 Oct 21. [Pdf].

2002

  1. Jegga AG, Sherwood SP, Carman JW, Pinski AT, Phillips JL, Pestian JP and Aronow BJ 2002. Detection and Visualization of Compositionally Similar Cis-Regulatory Element Clusters in Orthologous and Coordinately Expressed Genes. Genome Research 12 (9): 1408-1417 [Pdf].
  2. Bates MD, Erwin CR, Sanford LP, Wiginton D, Bezerra JA, Schatzman LC, Jegga AG, Ley-Ebert C, Williams SS, Steinbrecher KA, Warner BW, Cohen MB and Aronow BJ. 2002. Novel genes and functional relationships in the adult mouse gastrointestinal tract identified by microarray analysis. Gastroenterology 122 (5):1467-1482 [Pdf].
  3. Warren MA, Koshoffer A, Aronow BJ, Jegga AG, Brackenbury R (2002). Structure of the 5' Portion of the Human Plakoglobin Gene. J Invest Dermatol 119 (1):196-197.

<2002

  1. Jegga AKG and Raghavender KBP 1997. Abdominal wall reconstruction with external abdominal oblique myofascial flap in dogs: an experimental study. Indian Journal of Veterinary Surgery 18 (1): 12-14.

 

 

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This profile last updated on April 29, 2008

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