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Faculty Profile Last Modified Time: 02:01:04 PM Wed, 19 May 2021   Contact Information Gad Shaulsky Associated Profiles  Professor, Molecular and Human Genetics, Director of Graduate Studies, Molecular and Human Genetics, Baylor College of Medicine   Mail Box: BCM225, BCM-Smith Medical Research Bldg, Room No.: S930    gadi@bcm.edu     713-798-8082    Web Link    Functional Genomics and Transcriptome Analysis, The Evolution of Social Behavior in Dictyostelium, Allorecognition in Dictyostelium, Developmental Genetics in Dictyostelium    Associated Profiles Research and Expertise Affiliations Appointments  Research and Expertise Research Interests   Functional Genomics: In the past we have used microarrays to discover gene function in development, de-differentiation, spore germination, drug resistance, and chemotaxis. We also showed that the transcriptome is a good phenotyping tool for discovering epistatic relationships between genes in the cAMP-dependent Protein Kinase regulatory pathway. More recently, we adapted the use of RNA-sequencing to Dictyostelium and began to use it as our main platform for transcriptional profiling. We compared the developmental transcriptomes of D. discoideum and D. purpureum, two Dictyostelium species whose genomes are as different from each other as the genomes of humans and jawed fish, but whose developmental morphologies are very similar. We found vast similarities between the two transcriptomes (Parikh et al., 2010). We have analyzed many mutants in our lab and in collaboration with others (Cai et al., 2014), and we have developed a system for analysis of transcription factors with RNA-seq and ChIP-seq (Santhanam et al., 2015). Using frequent sampling and RNA-seq we found complex regulation of transcriptional activity during D. discoideum development (Rosengarten et al., 2015) and we described the long-non-coding transcriptome as well (Rosengarten et al., 2017). The transcriptome data are available for interactive exploration on dictyExpress. We have developed several new tools for exploration of the D. discoideum genome. The most recent ones include a deep coverage genomic DNA library (Rosengarten et al., 2015) and a method for gene discovery by chemical mutagenesis at low level and whole-genome sequencing to identify mutations (Li et al., 2016). The evolution of social behavior in Dictyostelium: Social organisms must deal with cheaters - individuals that reap the benefits of sociality without paying the costs. In Dictyostelium, some cells sacrifice themselves and benefit other cells that may be genetically different, providing a fertile ground for cheating. In collaboration with Drs. Strassmann and Queller at Rice University and with Dr. Adam Kuspa at BCM, we found over 100 genes that participate in social interactions (Santorelli et al., 2008). We are using genetic tools to characterize mechanisms that determine social interactions and test how cooperators resist cheating (Khare and Shaulsky, 2006; Khare et al., 2009; Khare and Shaulsky, 2010). Allorecognition in Dictyostelium: Multicellular organisms can distinguish self from non-self through various mechanisms. We have found that D. discoideum cells preferentially cooperate with their relatives (Ostrowski et al., 2008), possibly reducing their exposure to strains that can cheat on them. We are now investigating the molecular mechanisms that underlie kin discrimination. We found two cell-cell adhesion genes, tgrB1 and tgrC1, that are highly polymorphic in natural populations and are required for allorecognition (Benabentos et al., 2009). We are investigating the cellular and genetic mechanisms that regulate allorecognition under the hypothesis that the TgrB1 and TgrC1 proteins function as a ligand-receptor pair (Hirose et al., 2017), which is at the top of a signal transduction mechanism that regulates development and allorecognition. Data Mining: We are collaborating with Dr. Blaz Zupan and his group at the University of Ljubljana in Slovenia to develop new concepts in genetic analysis. Previously we have developed a tool that performs automated epistasis analysis, GenePath (Demsar, 2001). We developed a gene function prediction system that relies on compressive data fusion and chaining and demonstrated its utility in predicting the function of bacterial-recognition genes in D. discoideum (Zitnik et al., 2015). We also developed dictyExpress, a web tool that can access and analyze our transcriptional profiling data (Stajdohar et al., 2017).  Publications/Creative Works Click here to search for this faculty member's publications on PubMed.  Affiliations  Training Grants NLM Training Program in Biomedical Informatics & Data Science for Predoctoral and Postdoctoral Fello  Research Consortia Gulf Coast Cluster for Single Cell Omics  Appointments Title Department / School Institution Professor Molecular and Human Genetics Baylor College of Medicine

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