Positions
- Professor and Director of Graduate Studies
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Graduate Program in Genetics & Genomics
ÌÇÐÄvlogÃÛÌÒ of Medicine
- Professor
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Graduate Program in Immunology & Microbiology
ÌÇÐÄvlogÃÛÌÒ of Medicine
- Professor and Vice Chair for Graduate Education Affairs
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Molecular and Human Genetics
Department of Molecular and Human Genetics
Houston, Texas, United States
Addresses
- BCM-Smith Medical Research Bldg (Lab)
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Room: BCMS-S930
Houston, TX, 77030
United States
Phone: (713) 798-8082
gadi@bcm.edu
- BCM-Smith Medical Research Bldg (Office)
-
Room: BCMS-S930
Houston, TX, 77030
United States
Phone: (713) 798-8082
gadi@bcm.edu
Education
- BSc from Tel Aviv University
- 09/1985 - Tel Aviv, Israel
- MSc from Tel Aviv University
- 09/1986 - Tel Aviv, Israel
- PhD from Weizmann Institute of Science
- 05/1991 - Rehovot, Israel
- Post-Doctoral Fellowship at University Of California, San Diego
- 06/1997 - La Jolla, California, United States
Honors & Awards
- Barbara & Corbin J. Robertson, Jr. Presidential Award for Excellence In Education
- ÌÇÐÄvlogÃÛÌÒ of Medicine (05/2020)
- Michael E. DeBakey, M.D., Excellence in Research Award
- ÌÇÐÄvlogÃÛÌÒ of Medicine (05/2011)
- Michael E. DeBakey, M.D., Excellence in Research Award
- ÌÇÐÄvlogÃÛÌÒ of Medicine (05/2006)
- Kenneth Scott Graduate Mentor Award
- Molecular and Human Genetics Department, BCM (01/2019)
Professional Interests
- Functional Genomics and Transcriptome analysis
- The evolution of social behavior in Dictyostelium
- Allorecognition in Dictyostelium
- Developmental genetics in Dictyostelium
Professional Statement
Allorecognition: Investigating the mechanisms that underlie Dictyostelium kin discrimination revealed two polymorphic cell-surface proteins, TgrB1 and TgrC1, which are required for allorecognition (Benabentos, 2009). The sequence polymorphism is sufficient to explain allorecognition in Dictyostelium (Hirose, 2011) and this kin-recognition system protects cooperators against cheaters (Ho, 2013). We are investigating the mechanisms that regulate allorecognition under the hypothesis that TgrB1 and TgrC1 function as a ligand-receptor pair (Hirose, 2017), which is at the top of a signal transduction cascade that regulates development and allorecognition. We used genetic suppressor analysis to identify elements that mediate the TgrB1-C1 signal transduction, including the rapgapB signal transduction gene (Li, 2016). We recently found that TgrB1 and TgrC1 are components of a greenbeard mechanism: activation of TgrB1 induces altruistic behavior, inactivation of TgrB1 causes cheating (Katoh-Kurasawa, 2024), and inactivation of RapGAPB causes falsebeard cheating (Lehmann, 2024).
The evolution of social behavior in Dictyostelium: Social organisms must deal with cheaters - individuals that reap the benefits of sociality without paying the full cost. In Dictyostelium, some cells sacrifice themselves and benefit others that may be genetically different, providing a fertile ground for cheating. We found over 100 genes that participate in social interactions (Santorelli, 2008), characterized some of the underlying mechanisms, and tested how cooperators resist cheating (Khare and Shaulsky, 2006; Khare, 2009; Khare and Shaulsky, 2010). We are investigating the role of the TgrB1-C1 pathway in cheating (Katoh-Kurasawa, 2024; Lehmann, 2024).
Functional Genomics: We use transcriptomes to discover gene function in Dictyostelium (Booth, 2005; Van Driessche, 2007). We have shown that the transcriptome is a good phenotyping tool for discovering epistatic relationships (Van Driessche, 2005). Using RNA-seq, we compared the developmental transcriptomes of D. discoideum and D. purpureum, two species that diverged ~350MYA, but whose developmental morphologies are similar. We found vast similarities between the two transcriptomes (Parikh, 2010). We analyzed many mutants, and we developed a system for analysis of transcription factors with RNA-seq and ChIP-seq (Santhanam, 2015). We found complex regulation of transcriptional activity during development (Rosengarten, 2015) and described the long-non-coding transcriptome (Rosengarten, 2017). We analyzed the major transcriptional transitions that characterize Dictyostelium development using RNA-seq profiles of 20 mutants (Katoh-Kurasawa, 2021). We are also developing tools for Dictyostelium genome exploration, including a deep coverage genomic DNA library (Rosengarten, 2015), gene discovery by chemical mutagenesis at low level and whole-genome sequencing to identify mutations (Li, 2016), and an adaptation of GoldenBraid as a synthetic biology tool for Dictyostelium (Kundert, 2020).
Data Mining: We are collaborating with Dr. Zupan’s group at the University of Ljubljana, Slovenia, to develop new concepts in genetic analysis. 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, 2015). We developed dictyExpress, a web tool that can access and analyze transcriptome data (Stajdohar, 2017). We also developed scOrange, a tool for analyzing single cell RNA-seq data (Stražar, 2019) and an image analysis platform that utilizes deep models in a visual programming environment (Godec, 2019).
The evolution of social behavior in Dictyostelium: Social organisms must deal with cheaters - individuals that reap the benefits of sociality without paying the full cost. In Dictyostelium, some cells sacrifice themselves and benefit others that may be genetically different, providing a fertile ground for cheating. We found over 100 genes that participate in social interactions (Santorelli, 2008), characterized some of the underlying mechanisms, and tested how cooperators resist cheating (Khare and Shaulsky, 2006; Khare, 2009; Khare and Shaulsky, 2010). We are investigating the role of the TgrB1-C1 pathway in cheating (Katoh-Kurasawa, 2024; Lehmann, 2024).
Functional Genomics: We use transcriptomes to discover gene function in Dictyostelium (Booth, 2005; Van Driessche, 2007). We have shown that the transcriptome is a good phenotyping tool for discovering epistatic relationships (Van Driessche, 2005). Using RNA-seq, we compared the developmental transcriptomes of D. discoideum and D. purpureum, two species that diverged ~350MYA, but whose developmental morphologies are similar. We found vast similarities between the two transcriptomes (Parikh, 2010). We analyzed many mutants, and we developed a system for analysis of transcription factors with RNA-seq and ChIP-seq (Santhanam, 2015). We found complex regulation of transcriptional activity during development (Rosengarten, 2015) and described the long-non-coding transcriptome (Rosengarten, 2017). We analyzed the major transcriptional transitions that characterize Dictyostelium development using RNA-seq profiles of 20 mutants (Katoh-Kurasawa, 2021). We are also developing tools for Dictyostelium genome exploration, including a deep coverage genomic DNA library (Rosengarten, 2015), gene discovery by chemical mutagenesis at low level and whole-genome sequencing to identify mutations (Li, 2016), and an adaptation of GoldenBraid as a synthetic biology tool for Dictyostelium (Kundert, 2020).
Data Mining: We are collaborating with Dr. Zupan’s group at the University of Ljubljana, Slovenia, to develop new concepts in genetic analysis. 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, 2015). We developed dictyExpress, a web tool that can access and analyze transcriptome data (Stajdohar, 2017). We also developed scOrange, a tool for analyzing single cell RNA-seq data (Stražar, 2019) and an image analysis platform that utilizes deep models in a visual programming environment (Godec, 2019).
Websites
An interactive search and exploration tool for the BCM Dictyostelium gene expression database. Developed in collaboration with the Bioinformatics Laboratory, University of Ljubljana, Slovenia
GenePath is a web-enabled intelligent assistant for the analysis of genetic data and for discovery of genetic networks. Developed in collaboration with the Bioinformatics Laboratory, University of Ljubljana, Slovenia
Selected Publications
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Katoh-Kurasawa, Mariko Trnovec, Lena Lehmann, Peter Zupan, Blaž Shaulsky, Gad. " " 2025 Jun 5; 26 (1) : 563.
Pubmed PMID: . -
Lehmann, P. Katoh-Kurasawa, M. Kundert, P. Shaulsky, G.. " " iScience. 2024 Oct ; 27 (11) : 111125.
Pubmed PMID: . -
Katoh-Kurasawa, M., Lehmann, P., Shaulsky, G.. " " Nat Commun. 2024 May 11; 15 (1) : 3984.
Pubmed PMID: . -
Katoh-Kurasawa M, Hrovatin K, Hirose S, Webb A, Ho HI, Zupan B, Shaulsky G. " " Genome Res. 2021 Aug ; 31 : 1498-1511.
Pubmed PMID: .
Funding
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Genetics & Genomics Training Program
#T32 GM139534 - $3,901,030.00 (07/01/2021 - 06/30/2026)
- Grant funding from NIH/NIGMS
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Developmental Synchrony in Dictyostelium discoideum
#NSF 2319686 - $562,484.00 (08/15/2023 - 07/30/2026)
- Grant funding from NSF
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Mechanistic analysis of a pathway that integrates allorecognition and altruism in Dictyostelium
#R35GM152113 - $1,467,652.00 (07/01/2024 - 04/30/2029)
- Grant funding from NIH/NIGMS
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