William G. FairbrotherAssociate Professor of Biology, Director of Graduate Studies for the Center for Computational Molecular Biology
Dr. Fairbrother majored in Chemistry at Oberlin College (Oberlin, OH) and received his PhD from Columbia University in 2000. Dr. Fairbrother was a PhRMA Post-doctoral Fellow in Informatics at Massachusetts Institute of Technology (MIT) under mentorship of Christopher Burge and Nobel Laureate Phillip Sharp. Dr Fairbrother is currently a tenured, associate professor in the MCB Department and the Director of Graduate Studies for the Center for Computational Molecular Biology at Brown. His research has focused on precision medicine and RNA genomics. the Fairbrother lab is using high-throughput biochemical screens and computational methods to understand the specificity of RNA processing. Results from Dr. Fairbrother's lab suggest 1/3 of all hereditary disease mutations affect the processing of genes. More recently, Dr. Fairbrother and his laboratory have become interested in developing methods for analyzing clinical sequencing experiments (e.g., whole-genome and whole-exome sequencing data). To this end, he is active with the Mendelian Genetics Research Group at Harvard.
Brownstein CA, Beggs AH, Homer N, Merriman B, Yu TW, Flannery KC, DeChene ET, Towne MC, Savage SK, Price EN, Holm IA, Luquette LJ, Lyon E, Majzoub J, Neupert P, McCallie D Jr, Szolovits P, Willard HF, Mendelsohn NJ, Temme R, Finkel RS, Yum SW, Medne L, Sunyaev SR, Adzhubey I, Cassa CA, de Bakker PI, Duzkale H, Dworzyński P, Fairbrother W, Francioli L, Funke BH, Giovanni MA, Handsaker RE, Lage K, Lebo MS, Lek M, Leshchiner I, MacArthur DG, McLaughlin HM, Murray MF, Pers TH, Polak PP, Raychaudhuri S, Rehm HL, Soemedi R, Stitziel NO, Vestecka S, Supper J, Gugenmus C, Klocke B, Hahn A, Schubach M, Menzel M, Biskup S, Freisinger P, Deng M, Braun M, Perner S, Smith RJ, Andorf JL, Huang J, Ryckman K, Sheffield VC, Stone EM, Bair T, Black-Ziegelbein EA, Braun TA, Darbro B, DeLuca AP, Kolbe DL, Scheetz TE, Shearer AE, Sompallae R, Wang K, Bassuk AG, Edens E, Mathews K, Moore SA, Shchelochkov OA, Trapane P, Bossler A, Campbell CA, Heusel JW, Kwitek A, Maga T, Panzer K, Wassink T, Van Daele D, Azaiez H, Booth K, Meyer N, Segal MM, Williams MS, Tromp G, White P, Corsmeier D, Fitzgerald-Butt S, Herman G, Lamb-Thrush D, McBride KL, Newsom D, Pierson CR, Rakowsky AT, Maver A, Lovrečić L, Palandačić A, Peterlin B, Torkamani A, Wedell A, Huss M, Alexeyenko A, Lindvall JM, Magnusson M, Nilsson D, Stranneheim H, Taylan F, Gilissen C, Hoischen A, van Bon B, Yntema H, Nelen M, Zhang W, Sager J, Zhang L, Blair K, Kural D, Cariaso M, Lennon GG, Javed A, Agrawal S, Ng PC, Sandhu KS, Krishna S, Veeramachaneni V, Isakov O, Halperin E, Friedman E, Shomron N, Glusman G, Roach JC, Caballero J, Cox HC, Mauldin D, Ament SA, Rowen L, Richards DR, San Lucas FA, Gonzalez-Garay ML, Caskey CT, Bai Y, Huang Y, Fang F, Zhang Y, Wang Z, Barrera J, Garcia-Lobo JM, González-Lamuño D, Llorca J, Rodriguez MC, Varela I, Reese MG, De La Vega FM, Kiruluta E, Cargill M, Hart RK, Sorenson JM, Lyon GJ, Stevenson DA, Bray BE, Moore BM, Eilbeck K, Yandell M, Zhao H, Hou L, Chen X, Yan X, Chen M, Li C, Yang C, Gunel M, Li P, Kong Y, Alexander AC, Albertyn ZI, Boycott KM, Bulman DE, Gordon PM, Innes AM, Knoppers BM, Majewski J, Marshall CR, Parboosingh JS, Sawyer SL, Samuels ME, Schwartzentruber J, Kohane IS, Margulies DM.
An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge.
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The research focus of the Fairbrother laboratory is the discovery and analysis of protein-nucleic acid interactions and the processing of RNA. Results from Dr. Fairbrother's studies have contributed to evidence supporting that the disruption of pre-mRNA splicing is a common causal mechanism for many disease mutations (> 30% of all hereditary disease mutations may affect RNA splicing) (Lim et al., 2011). Despite this prevalence, this class of mutation remains an understudied area of disease. To this end, the Fairbrother laboratory has developed high-throughput assays incorporating deep sequencing-based experimental and computational methods that allow for unbiased measurement of the effects of thousands of mutations and single nucleotide variants on splicing, spliceosome assembly, and binding of RNA-binding proteins (e.g., splicing factors) (Soemedi et al., 2014). This assay is being currently used to annotate common variants and disease alleles and is also being developed as a drug screening platform. Extending on results from experimental assays, the Fairbrother laboratory has also developed computational tools, such as Spliceman (Lim and Fairbrother, 2012), to predict the effects of genetic variants on the processing of RNA.
A strong emphasis of the laboratory is on developing hybrid approaches to understanding clinical sequencing data - combining genome analysis and computational biology with experimentation. Using the recently developed high-throughput assays and computational methods, the Fairbrother laboratory is currently in an excellent position to perform comprehensive annotation of deep sequencing data regarding protein-nucleic acid interactions and the processing of RNA. Implementation of this combined experimental and computational approach is allowing for greater accuracy in deciphering the effects of genetic mutations. In agreement with the Fairbrother laboratory's role in the larger effort to produce tools to standardize precision medicine analysis pipelines (Brownstein et al., 2014), the group is now at a stage to fully integrate the annotation into mutational analysis pipelines that will increase the diagnostic performance of clinical sequencing.
The approach of the Fairbrother laboratory is based on the belief that large-scale computational analysis in conjunction with functional assays is, and will continue to be, an effective way to answer questions about gene expression. More detailed descriptions of projects in the Fairbrother laboratory and the approaches taken are provided below.
DISCOVERING RARE INTERMEDIATES OF SPLICING IN DEEP SEQUENCING DATA
The basic multi-step biochemical mechanism of pre-mRNA splicing was determined more than two decades ago using in vitro experiments on minimal RNA substrates and extensive genetic characterization in yeast. Results from these studies demonstrated that, during the splicing process, pre-mRNA proceeds through a branched RNA intermediate (i.e., the lariat) to a fully spliced message. The degree to which these types of biochemical assays can model splicing in vivo is unclear. Splicing occurs co-transcriptionally, often conditionally on multi-intron transcripts. In vitro, the branched lariat RNA is fairly abundant and the precise branchpoint can be readily mapped by a primer extension assay. In vivo, lariats are transient and difficult to characterize. As such, prior to 2012, few branchpoints had been identified. In an effort to reduce this knowledge gap, the Fairbrother laboratory developed a high-throughput method of mapping branchpoints in deep sequencing data and used this approach to discover more than two thousand lariats in vivo (Taggart et al., 2012). This novel genomic method allows for a system-level approach to determining the role of this intermediate in splice site selection. Furthermore, results from this project demonstrate that the branchsite location is an important determinant in splice site selection. Indeed, the branchpoints upstream from alternatively spliced exons are often in a suboptimal location. Alternative 3 prime splice site (3'ss) selection is often restricted by branchpoint formation on or downstream of the proximal "AG". In addition, results from this study indicate that skipped exons are associated with unusually distal branchpoints. This exon-distal branchpoint association implies a mechanism to weaken 3'ss definition, which may be necessary to create a skippable exon. Research currently being conducted in the Fairbrother laboratory regarding this project involves combining experimental approaches and computational methods to isolate lariats, further map branchpoints in the human genome, and explore the effects of branchpoint location and selection on splice site utilization.
One of the most fundamental goals of genetics is to connect variations in genomic sequence to a phenotype or trait. In the context of human disease, an analysis of hereditary disease alleles illustrates the types of variations that have been associated with disease. Conservative estimates list splicing defects as responsible for about 15% of all hereditary diseases; however, results from Dr. Fairbrother's studies have contributed to evidence supporting that > 30% of all hereditary disease mutations may affect RNA splicing (Lim et al., 2011). Furthermore, many mutations classified as "missense" are also exacerbated by splicing defects. In addition to disease alleles, genetic variants, such as single nucleotide polymorphisms (SNPs), may influence disease phenotypes through a splicing-related mechanism.
To increase the efficiency of discovering variants that cause or contribute to disease through altered pre-mRNA processing, the Fairbrother laboratory has developed high-throughput splicing and spliceosome assembly assays to screen variants identified in existing sequencing data (Soemedi et al., 2014). These assays reflect massively parallel reporter systems utilizing RNA substrates that incorporate a library of potential and known disease-causing alleles. Each of the entries in the library represents an allelic pair of a mutant allele and a reference sequence. The assays provide for testing of splicing in vitro and in vivo (i.e., cultured cells), and the results are analyzed using deep sequencing. On the computational side, results from the studies are analyzed using various bioinformatics approaches and sequence databases. Additionally, the results will be integrated into a software package intended for use in analyzing deep sequencing data to predict genetic variants highly likely to be causal or predisposing of disease.
Alternative splicing plays a major role in creating the complexity and diversity observed in higher eukaryotic proteomes. The Fairbrother laboratory has an interest and experience in mapping regulatory elements around alternatively spliced exons. Unlike location studies, which map all the genomic targets of a particular driver, the focus here is on creating, within limited regions of the genome, complete high-resolution maps of targets for all the relevant drivers. The ultimate goal is to define modules (i.e., particular arrangements of cis-elements) that regulate splice site selection. With RNA, protein binding events can be further modulated by secondary structure. To date, Dr. Fairbrother's research group has contributed to mapping binding sites for splicing factors such as polypyrimidine tract binding protein (PTB) and SF2/ASF around 4000 alternatively spliced exons (Reid et al., 2009; Chang et al., 2010). Results from these studies demonstrate how features of RNA structure modulate protein accessibility. Comparing these mappings shows very little overlap between the repressor PTB and the activator ASF - perhaps reflecting their antagonistic functions. Interestingly, protein interactome maps indicate that PTB associates with about 20 other RNA-binding proteins, possibly creating RNPs with their own distinct specificity and function. Repeating the PTB binding assays after perturbing the levels of these interacting protein should identify scenarios of combinatorial binding or competition.
As part of efforts of the Fairbrother laboratory to understand the regulatory circuitry of the core set of promoters that are important in maintaining pluripotency in stem cells, Dr. Fairbrother's research group has developed a high-throughput, high-resolution method to screen large genomic regions for DNA-protein complexes (Ferraris, Stewart, Gemberling et al., 2011; Ferraris, Stewart, Kang et al., 2011). Results from use of these assays has revealed several interesting features of the transcriptional circuitry that may be important to understanding stem cells and stem cell reprogramming events. As examples, an apparent pervasive competiton exists between Oct4 and FoxO1 for genomic targets upstream of genes that maintain "stemness". Also, results from the Fairbrother laboratory suggest that the paralog Oct1 modulates Oct4 specificity in embryonic stem cells. Features learned from the high-throughput in vitro binding assay can be used to successsfully predict in vivo binding events. Future directions will be to extend these findings on a genomic scale in stem cells and to complete the characterization of the pluripotency transcriptional control network.
Ongoing Research Support
NIH/NIGMS R01GM105681 (Fairbrother, PI)
7/16/14 – 3/31/18
"A Genomic Approach to Studying the Life Cycle of Intron Lariats"
The major goals of this project are to: (1) map branchpoints in human transcripts; (2) map branchpoints around known targets of heterogeneous nuclear ribonucleoprotein (hnRNP) protein-binding and regulatory sites; and (3) discover determinants of branchpoint turnover and regulation.
NIH/NHGRI R21HG007905 (Fairbrother, PI; Neretti, Co-PI)
7/14/14 – 6/30/16
"Developing in vitro High-throughput Splicing Assays"
The main goal of this exploratory pilot project is to further develop and implement in vitro mechanistic splicing assays at a genomic scale. Using these assays, we propose to map the splicing-related functional elements, such as 3' splice sites and branchpoints, for all introns of the human genome. We also propose to repurpose exome sequencing libraries as substrates for the developed in vitro splicing assays.
NIH/NIGMS R01GM095612 (Fairbrother, PI)
9/30/10 – 8/31/15
"A Discovery Tool for Variations that Affect Splicing"
The major goals of this project are to: (1) analyze polypyrimidine tract binding protein (PTB) binding sites in the genome; (2) analyze variants that are important in autoimmune disorders; and (3) validate candidate functional variants that are misprocessed in patient-derived lymphoblastoid cell lines.
Research Seed Funding (Fairbrother, Knopik, McGeary, Raphael, Co-PIs)
Brown University Internal Award
7/1/14 – 6/30/15
"Creating a Providence-based Working Group in Precision Medicine to Identify the Genetic Determinants of Marijuana Sensitivity"
The goal of this project is to use results from participant behavioral assessments together with deep sequencing data to identify genetic variants associated with increased risk of addiction to marijuana.
National Ataxia Foundation (Fairbrother, PI)
1/1/14 – 12/31/14
"Single Nucleotide Resolution Mutation Annotation in Ataxia Genes"
The major goals of this project are to: (1) annotate genes considered causal of various inherited ataxias with respect to pre-mRNA splicing elements; (2) use in vitro and in vivo assays to test the effects of mutations and polymorphisms reported for ataxia genes on the splicing process; and (3) integrate experimental and computational data into a software that aids in predicting the effects of mutations in ataxia-related genes.
Recently Completed Research Support
NSF MCB1020552 (Fairbrother, PI)
9/1/10 – 8/31/13
"Cis-regulatory Circuitry of Polypyrimidine Binding Proteins"
The splicing-related trans-factor polypyrimidine tract binding protein (PTB) is the prominent splicing repressor in humans. PTB has typically been regarded as an RNA-binding protein of low specificity, interacting fairly promiscuously with RNA. Additionally, PTB binds many other RNA-binding proteins. The project goals were (1) to provide a mechanistic description of the gene target network of PTB and (2) to create a comprehensive map of pre-mRNA regions that undergo PTB-mediated regulation.
COBRE Center for Cancer Signaling Networks Pilot Project Funds (Fairbrother, PI)
7/1/11 – 3/31/12
"Deep Sequencing Analysis of a High Throughput Splicing Assay"
The goals of this project were to: (1) begin subjecting samples obtained from a newly developed high-throughput splicing assay to deep sequencing-based analysis, (2) analyze the resulting sequence data, and (3) optimize the assay as needed in order to obtain high-quality sequence data.
NIH R21HG004524 (Fairbrother, PI)
4/26/10 – 1/31/12
"Discovering and Validating Functional Elements in the Genome"
The goal of this project was to develop efficient methods to identify the sequence elements that govern splicing in the genome and to understand how these elements work together, focusing exclusively on the splicing repressor polypyrimidine tract binding protein (PTB). Overall, the project sought to define the sequence, structural, and higher-order architectures of PTB-binding sites in human cells.
2014 UTRA Summer Fellowship
2014 Research Seed Fund Award
2012 Winner – CLARITY Challenge
2009 Research Seed Fund Award
2008 CCMB Research Award "Incorporating Statistical Mechanics in Motif Finding"
2008 UTRA Summer Fellowship
2007 UTRA Summer Fellowship
2007 CCMB Scholarship Innovator Award
2006 UTRA Summer Fellowship
2005 UTRA Summer Fellowship
2005 Richard Salomon Award "Discovering Combinatorial Codes in Splicing"
2003 PhRMA Post-doctoral Fellowship in Informatics
2000 James Howard McGregor Teaching Award
International Society for Computational Biology
Clare Hall, Life Member (University of Cambridge, Cambridge, UK)
Center for Computational Molecular Biology (Brown University)
Center for Genomics and Proteomics (Brown University)
Center for Biomedical Engineering (Brown University)
The various fields of basic research, including molecular biology and genetics, are increasingly more interdisciplinary and reliant on complementary, collaborative approaches. As for Dr. Fairbrother's research, his teaching and mentoring activities are based on the belief that large-scale computational analysis in conjunction with functional assays is, and will continue to be, an effective way to answer questions about gene expression. To this end, in addition to Dr. Fairbrother's appointment as Associate Professor of Biology in 2011, as of 2013 he is Director of Graduate Studies for the Center for Computational Molecular Biology. The Center's mission is to make breakthrough discoveries in the life sciences through the development and application of novel computational, mathematical, and statistical techniques. In relation to the Department of Molecular Biology, Cell Biology and Biochemistry, and at times also the Center for Computational Molecular Biology, Dr. Fairbrother mentors post-doctoral research associates, doctoral candidate graduate trainees, Master of Science candidate graduate trainees, and undergraduate students. He is also involved in teaching and presenting workshops and seminars in areas bridging biology, "big data", and computational methods.
BIOL 0980 - Introduction to Computational Biology. Fall 2015.
BIOL 2000E - Topics in MCDB: The Genomics Revolution and its Impact on Genetics, Medicine and Society. Spring 2015.
BIOL 2010 - Quantitative Approaches to Biology. Spring 2016.