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Brian Oliver, Ph.D.

Photo of Brian Oliver
Scientific Focus Areas: Computational Biology, Developmental Biology, Genetics and Genomics, Systems Biology, Stem Cell Biology

Professional Experience

  • Postdoctoral, Stanford University
  • Ph.D., Case Western Reserve University School of Medicine
  • M.S., Iowa State University of Science and Technology
  • B.A., Gustavus Adolphus College

Research Goal

Our ultimate goal is to determine how the collective action of genes results in an individual with specific characteristics, development, and disease susceptibilities.

Current Research

Drosophila melanogaster is an important functional model system, boasting facile genetics, complex organ systems, complex behaviors, and a sequenced genome. Our long-term goal is to develop predictive models of gene function with a specific focus on sex differentiation in the germline. Our approach relies on high-throughput techniques used to profile biological processes such as expression, promoter occupancy, and chromatin status, in conjunction with computational analysis and genetics.

Applying our Research

Subtle perturbations in gene networks are likely to cause much of inherited disease susceptibility, but understanding how complex genotypes and environmental interactions result in disease will require experimental systems biology using model organisms. Predictive models for gene and pathway function will be important for diagnosis and ultimately intervention, fulfilling the promise of the human genome project.

Need for Further Study

We have a reasonable understanding of the functions of some individual genes, but we know very little about how they work together.

Select Publications

Fly Cell Atlas: A single-nucleus transcriptomic atlas of the adult fruit fly.
Li H, Janssens J, De Waegeneer M, Kolluru SS, Davie K, Gardeux V, Saelens W, David FPA, Brbić M, Spanier K, Leskovec J, McLaughlin CN, Xie Q, Jones RC, Brueckner K, Shim J, Tattikota SG, Schnorrer F, Rust K, Nystul TG, Carvalho-Santos Z, Ribeiro C, Pal S, Mahadevaraju S, Przytycka TM, Allen AM, Goodwin SF, Berry CW, Fuller MT, White-Cooper H, Matunis EL, DiNardo S, Galenza A, O'Brien LE, Dow JAT, FCA Consortium§., Jasper H, Oliver B, Perrimon N, Deplancke B, Quake SR, Luo L, Aerts S, Agarwal D, Ahmed-Braimah Y, Arbeitman M, Ariss MM, Augsburger J, Ayush K, Baker CC, Banisch T, Birker K, Bodmer R, Bolival B, Brantley SE, Brill JA, Brown NC, Buehner NA, Cai XT, Cardoso-Figueiredo R, Casares F, Chang A, Clandinin TR, Crasta S, Desplan C, Detweiler AM, Dhakan DB, Donà E, Engert S, Floc'hlay S, George N, González-Segarra AJ, Groves AK, Gumbin S, Guo Y, Harris DE, Heifetz Y, Holtz SL, Horns F, Hudry B, Hung RJ, Jan YN, Jaszczak JS, Jefferis GSXE, Karkanias J, Karr TL, Katheder NS, Kezos J, Kim AA, Kim SK, Kockel L, Konstantinides N, Kornberg TB, Krause HM, Labott AT, Laturney M, Lehmann R, Leinwand S, Li J, Li JSS, Li K, Li K, Li L, Li T, Litovchenko M, Liu HH, Liu Y, Lu TC, Manning J, Mase A, Matera-Vatnick M, Matias NR, McDonough-Goldstein CE, McGeever A, McLachlan AD, Moreno-Roman P, Neff N, Neville M, Ngo S, Nielsen T, O'Brien CE, Osumi-Sutherland D, Özel MN, Papatheodorou I, Petkovic M, Pilgrim C, Pisco AO, Reisenman C, Sanders EN, Dos Santos G, Scott K, Sherlekar A, Shiu P, Sims D, Sit RV, Slaidina M, Smith HE, Sterne G, Su YH, Sutton D, Tamayo M, Tan M, Tastekin I, Treiber C, Vacek D, Vogler G, Waddell S, Wang W, Wilson RI, Wolfner MF, Wong YE, Xie A, Xu J, Yamamoto S, Yan J, Yao Z, Yoda K, Zhu R, Zinzen RP.
Science (2022 Mar 4) 375:eabk2432. Abstract/Full Text
Dynamic sex chromosome expression in Drosophila male germ cells.
Mahadevaraju S, Fear JM, Akeju M, Galletta BJ, Pinheiro MMLS, Avelino CC, Cabral-de-Mello DC, Conlon K, Dell'Orso S, Demere Z, Mansuria K, Mendonça CA, Palacios-Gimenez OM, Ross E, Savery M, Yu K, Smith HE, Sartorelli V, Yang H, Rusan NM, Vibranovski MD, Matunis E, Oliver B.
Nat Commun (2021 Feb 9) 12:892. Abstract/Full Text
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Research in Plain Language

Many diseases run in families due to the inheritance of particular sets of genes. If scientists can predict how genes function, we will be able to greatly improve the diagnosis and treatment of disease. Studying model species can make this possible. Cells follow a genetic blueprint composed of complex webs of interacting genes. These networks function to ultimately “turn on,” “turn off,” and “fine-tune” particular sets of genes for specific conditions, times, or locations. Our experiments are helping us understand how these gene networks function. Based on our understanding of regulatory networks, we are developing models that predict gene function.