Christopher B. Burge - US grants

Most vertebrate genes contain multiple introns which must be precisely removed from the primary transcript prior to its export from the nucleus to create the proper mRNA to direct translation. The process of RNA splicing which is responsible for removal of introns and ligation of exons is therefore an essential step in the expression of most genes. However, the basis for the specificity of this process is not well understood. The goal of this proposal is to understand the rules which are used by the vertebrate RNA splicing machinery to identify exons, introns and splice sites in primary transcripts and to encode these rules in computer programs which predict the splicing pattern of an arbitrary input primary transcript sequence. This will be accomplished by in-depth computational and statistical analysis of available primary transcript and mRNA sequences of vertebrate genes, taking advantage of the recent progress of large-scale genome sequencing and cDNA sequencing efforts. The approach will involve: 1) analysis of the detailed compositional properties of 5' and 3' splice signals and branch signals of vertebrate introns; 2) identification of exonic and intronic splicing enhancers and repressors; and 3) integrated computer models of slicing specificity enhancers and repressors; and 3) integrated computer models of splicing specificity. A variation of the Gibbs sampling algorithm will be used to characterize the branch signal and other signals which occur at a characteristic but variable distance from splice junctions. Clustering algorithms will be used to identify natural subgroups of 5' and 3' splice signals composition and to assign scores to potential splice signals. A statistical approach will be applied for identifying short sequence motifs which are likely to function as exonic or intronic splicing enhancers or repressors based on differences in oligonucleotide composition between exons and introns with weak versus strong splice signals. Conservation of putative splicing enhancers and repressors between homologous exons and introns from different vertebrates will be explored. As knowledge accumulates about splicing specificity, it will be integrated into computer models which predict the splicing patterns of primary transcripts. These models will be adapted to the problems of gene identification in genomic sequences and prediction of the splicing phenotypes of human mutations and polymorphisms. Deciphering the 'splicing code' will be essential to understanding the basis of alternative splicing, an important regulatory mechanism involved in development, differentiation and apoptosis. Computational methods for predicting splicing patterns will also aid in identification of genes including human disease genes and for understanding the effects of disease gene mutations, approximately 15% of which affect splicing.

EIA-0218506
Burge, Christopher B
MIT

CRCNS: Bioinformatics of Alternative Splicing in the Nervous System

Almost every human cell contains a huge instruction manual called the genome with many thousands of pages (the genes), each of which tells the cell how to make a particular building block (protein) that it needs to live or grow or to perform its assigned function in the body. The cell uses this manual in a complicated way, first copying (transcribing) each page that it needs to a piece of scratch paper (the pre-mRNA), and then cutting and pasting (splicing) pieces of the scratch paper (the exons) together to form the final recipe (mRNA) for the protein product. Interestingly, this cutting and pasting is often carried out in different ways in different types of cells or under different conditions in a process called alternative splicing (AS), generating many different varieties of a protein under different conditions. Alternative splicing is particularly common in neurons, helping to generate protein variants whose properties are optimized to the local environment of the neuron. For example, AS is used to tune the electrical properties of ion channels which help different sensory neurons in the inner ear respond to different frequencies of sound. In addition, mutations that affect AS are associated with a number of neurodegenerative diseases. The goal of the proposal is to gain a better understanding of the signals in a gene that determine how that gene will be spliced when it is expressed in a particular part of the brain, and of how alternative splicing is used to modulate brain function.

Abstract:
A grant has been awarded to the BioMicro Center at MIT to acquire high-performance computers for research in biology and biological engineering. The systems will be among the most powerful at MIT and will be dedicated to advancing the research programs of an active group of young faculty. These Assistant and Associate Professors lead research teams working on a wide range of problems in computational biology. The teams are united in their interest in the application of numerical models, computational simulations and large-scale computation to biological problems. The completion of the human genome sequence has emphasized the remarkable complexity of biological processes. While traditional molecular biology and molecular medicine will continue to play an important role in unraveling how these processes work, it seems almost certain that fundamental advances will come from the application of quantitative and rigorous analytic methods.
The research includes Professor Amy Keating's work on protein design. Dr. Keating's goal is to discern the rules governing protein-protein interactions through calculation and simulation and to then apply the rules to actual experiments. Professor Mike Yaffe will use computation to mine the human genome for proteins that play crucial roles in the transmission of signals within cells. Dr. Yaffe hopes to determine how circuits are constructed in cells, and to compare these circuits to electronic and mechanical circuits. Professor Tidor will use large-scale calculations to try to determine how proteins interact with each other and with small molecules (such as drugs). This is a long-standing problem in structural biology, but Dr. Tidor has recently shown that approximations drawn from engineering can be successfully applied to the problems that have proven to be impossible to calculate using conventional methods.
The new facility will not only enhance novel research but also graduate and undergraduate education. A new set of courses have the unusual distinction of being in the curriculum of three different departments: biology, biological engineering, and computer science. The group's intention is to expose students to the very latest computational methods and computer systems. Thus, high-performance computing will not only have a direct impact on world-class science, but also on education and training. With the help of Prof. Amy Keating, the group is working hard to attract additional women to computational biology. In the physical sciences women are significantly under-represented. Computational biology holds great promise as a discipline in which the historically inequitable under-representation of women in physical sciences can be overcome by association with biology.

DESCRIPTION (provided by applicant): Almost all protein coding genes of mammalian organisms have a split structure with several exons and introns. Intronic sequences are removed from the primary transcript by the nuclear pre-mRNA splicing machinery. Often, several functional variants of one transcript can be generated by alternative splicing (AS), ileading to several protein isoforms of a single gene. We propose a pair hidden Markov model (PHMM) to identify conserved AS events, which have so far gone undetected by the standard approach of aligning cDNAs and expressed sequence tags (ESTs) to the genomic sequence. The research in this proposal thus aims at closing the gap between comparative gene finding and gene structure identification by cDNA and EST alignments. Even though current EST libraries contain an abundance of sequences, the scope of each of these libraries is inherently limited to a particular tissue or developmental stage. We will implement efficient PHMM algorithms, and a PHMM to detect AS will align orthologous intron sequences from two species to identify conserved events of AS and intronic regulatory sequences. A few dozen promising candidates will be tested experimentally by RT-PCR. To demonstrate the validity of our PHMM approach, we will concentrate on two test sets: Genes that encode splicing factors, and genes from the ENCODE target regions. The proposed research will result in a more complete picture of alternative gene structures in the human genome. Approximately 15% of mutations which cause human disease are associated with splicing defects, and numerous studies have pointed out links between alternative splicing and cancer and neurological diseases. Our analyses will point out possible new relationships between disease genes and candidate regions and alternative or aberrant splicing.

[unreadable] DESCRIPTION (provided by applicant): The vast majority of human genes require RNA splicing for their expression, and at least 15% of the mutations that cause human diseases do so by disrupting splicing. The long term objective of this project remains: to understand the basis of RNA splicing specificity - the nature of the sequences in primary transcripts which are recognized by the RNA splicing machinery and used in the selection of splice sites in vertebrates and other organisms. This long-term objective is focused on four shorter-term aims: 1) to systematically identify sequences that can act as intronic splicing enhancer (ISE) and silencer (ISS) elements, to refine our knowledge of exonic splicing enhancer (ESE) and silencer (ESS) elements, and to determine rules for the context-dependent activity of these elements; 2) to identify the trans-acting factors responsible for the splicing regulatory activity of a significant proportion of the exonic splicing regulatory elements identified previously; 3) to develop and apply high-throughput technologies to map changes in expression of spliced isoforms that occur genome-wide during development and in response to external stimuli, using the murine hematopoietic system as a model; 4) to determine functional relationships - additivity, sub-additivity, synergism, etc. - between different classes of splicing regulatory elements, to develop associated scoring systems to improve algorithms that simulate splicing and predict splicing phenotypes of mutations or polymorphisms in human genes. In addressing these questions, we will use a synergistic combination of computational methods with molecular genetic and functional genomic approaches. Knowledge of splicing regulatory sequences and proteins will aid in understanding the changes that occur in the expression of RNA versions (isoforms) of genes as cells proliferate, and may identify specific protein or RNA targets for therapuetic intervention in hyperproliferative diseases of the blood such as leukemias, lymphomas and autoimmune diseases. The ability to accurately simulate splicing will enable improved genome annotation and will facilitate identification of specific genes, mutations and polymorphisms associated with human diseases. [unreadable] [unreadable] [unreadable]

Through a grant from the National Science Foundation to the Massachusetts Institute of Technology, six faculty members will collaborate in the purchase and use of high-performance computing equipment for research and education in computational and systems biology. The advent of high-throughput technologies in the life sciences has provided many genome sequences, protein structures and biological interaction networks. The amount of such data will continue to grow, compelling the development of rigorous and quantitative approaches to decipher and understand it. Simultaneously, advances in computing technology are enabling new ways of attacking complex biological problems using modeling and simulation. The projects to be supported cover a wide range of exciting areas, including the study of gene and organism evolution, transcriptional and post-transcriptional gene regulation, molecular signaling, protein conformational modeling, protein design, and the analysis of complex networks. The work will lead to advances in computational methods and provide basic biological insights.

This award will support MIT?s active role in developing computational and systems biology in the United States. The university is establishing novel programs and curricula to train students at the interface of the life sciences, engineering and the physical sciences. The investigators on this award are deeply involved in these activities. Shared computing resources will help attract talented students and provide them with modern, cross-disciplinary training. These students, who come from diverse backgrounds, will assume leadership positions in American universities and companies.

[unreadable] DESCRIPTION (provided by applicant): Most human genes require pre-mRNA splicing for expression, and >15% of the mutations that cause human genetic diseases disrupt splicing. A long term goal of our research is to understand the rules for RNA splicing generally. This proposal seeks to identify the sequence-specific splicing regulatory proteins that bind to exonic splicing silencers (ESSs) and related elements, and to characterize their functions and regulatory targets. In Phase 1 of the project, a system for efficient identification of trans-acting protein factors that act through specific ESS elements will be developed and applied to identify factors for a significant proportion of the FAS- ESS motifs identified previously by our lab. Phase 2 will seek improved understanding of the functions of selected splicing regulators by identifying the exons and transcripts they regulate. In phase 3, we will characterize the binding specificity and identify direct regulatory targets of a subset of these factors using technologies to assess their transcriptome-wide binding locations. A combination of RNAi-based screening, crosslinking and immunoprecipitation, high-throughput sequencing and computational analyses will be used. These studies will enable improved prediction of the consequences of genetic mutations or polymorphisms that alter splicing regulatory elements and will identify potential therapeutic targets in these cases. [unreadable] [unreadable] Public Health Relevance Statement: This project seeks to identify and characterize sequence-specific splicing regulatory proteins in human cells; such factors play important roles in both constitutive and alternative splicing of human genes. Alternative splicing is a gene regulatory mechanism that is used by more than half of all human genes, and genetic mutations or polymorphisms that disrupt splicing are a very common contributor to human disease. Identifying novel splicing regulatory factors and characterizing the specificity and targets of known regulatory factors will improve our ability to predict which genetic variations will have splicing phenotypes, and the factors involved. Knowing the protein factor that recognizes a particular cis-element such as an exonic splicing silencer identifies a potential therapeutic target in cases where a disease results from activity of a cis-element created by a mutation or polymorphism. [unreadable] [unreadable] [unreadable]

DESCRIPTION (provided by applicant): Myotonic dystrophy (DM) is the most common form of adult onset muscular dystrophy, with an incidence of about 1 in 8,000 adults. The most common form of the disease, DM1, is caused by an expanded CTG repeat in the 3'UTR of the DMPK gene, and CUG repeat RNAs from this gene fold into hairpins that accumulate in nuclear foci, resulting in effective depletion of the alternative splicing factor Muscleblind (MBNL1) and hyperactivation of the splicing factor CUG Binding Protein 1 (CUGBP1). Misregulation of splicing by these factors is central in the disease. Thus, characterization of the spectrum of changes in the transcriptomes of DM patients is central to understanding disease pathogenesis. This project seeks to understand the molecular basis of DM and to identify genes and mRNA isoforms suitable for therapeutic intervention using an approach based on next-generation sequencing of mRNAs. The project has the following specific aims: 1) To generate a comprehensive catalog of genes, exons and mRNA isoforms whose expression is altered in DM, and to assess the variability of these changes between individuals. 2) To characterize gene and mRNA isoform expression changes in mouse models of DM. 3) To associate gene and isoform changes with clinical and pathological features in DM. Achieving these aims will lay the foundation for a deeper understanding of DM and will generate leads for future molecular genetics and screening studies and is likely to identify candidate therapeutic targets. PUBLIC HEALTH RELEVANCE: This research project will comprehensively determine the changes in RNA and protein molecules that occur in the muscles of patients affected by myotonic dystrophy, which is the most common adult onset form of muscular dystrophy, affecting 1 in 8,000 adults. Knowledge of these molecular changes will help to identify which molecules and genes underlie specific symptoms of the disease and will aid in identifying targets for therapy.

DESCRIPTION (provided by applicant): The objective is to continue development of MIT's interdisciplinary predoctoral training program in Computational and Systems Biology (CSB), which trains students to become leaders in biomedical research at the interface of biology, computation and engineering. CSB is the primary training program at MIT for students interested in computational and systems biology and is the only program that emphasizes interdisciplinary training and research in the field. Program faculty are concentrated in the three founding departments - Biological Engineering (BE), Biology, and Electrical Engineering & Computer Science (EECS) - with additional involvement of faculty from other departments. Training faculty research interests span a wide range of CSB- related areas including computational molecular biology/regulatory genomics and evolution, molecular and cellular biophysics, systems biology of cancer and other diseases, proteomics, microbial ecology, bioimaging, protein design/engineering, synthetic biology, microfluidics/Bio-MEMS, and toxicogenomics. This proposal seeks to expand the pool of training faculty significantly, including 9 faculty newly hired in the past 5 years who have active research programs in the field. Students apply directly to the CSB Ph.D. program from their undergraduate or Master's institution and receive multi- and inter-disciplinary training in the field of computational and systems biology. The proposal seeks 12 slots to support 6 students for the first two years of the Ph.D., enabling extended research rotations and participation in special program activities. Unique aspects of the program include: (a) unusually diverse collection of research areas across science and engineering, with highly collaborative interdisciplinary faculty; (b) a unique core of recently developed, interdisciplinary classroom subjects that combine biology, engineering, statistics and computation; (c) intensive advising and multi- disciplinary thesis committees to optimize the training experience for students from diverse academic backgrounds; (d) an annual retreat with participation of students and faculty focusing on research, leadership, and challenges to interdisciplinary research.

DESCRIPTION (provided by applicant): Most human genes produce multiple distinct mRNA and protein isoforms through alternative splicing (AS). AS can produce protein isoforms that often have distinct or even antagonistic biological functions, is often tissue- specific, and contributes to various diseases. Our approach to the long-term goal of understanding the regulation and evolution of AS in mammals is organized around the following specific aims: SA1. Understand the evolution of alternative mRNA isoforms in mammals and the nature of genomic changes that alter splicing patterns. SA2. To develop analytical methods for quantitative inference of mRNA isoform abundance and translational activity from RNA-Seq and ribosome footprinting (Ribo-Seq) data, and to develop models to understand quantitative changes in organism- and tissue-specific regulation of mRNA isoforms. SA3. To construct a splicing regulatory network of mouse embryonic stem cells (mESCs). Our lab is generating RNA-Seq data spanning 10 diverse tissues from each of 5 vertebrate species - rhesus macaque, mouse, rat, cow and chicken. We will apply state-of-the art tools for RNA-Seq-based genome annotation to these and available human data, to annotate the transcriptomes of these organisms. These data will be used to trace the evolutionary histories of the exon-intron structures and splicing patterns of mammalian genes. We will extend a Bayesian mixture model we have developed to estimate levels of alternative isoforms from RNA-Seq data in several ways, including integrating with transcriptome annotation tools and extending to Ribo-Seq data, and we will develop models to quantitatively predict alternative isoform abundance. Finally, we will determine auto- and cross-regulatory relationships between 50 major splicing regulatory factors expressed in mESCs in order to construct a network model of splicing regulation in this fundamental cell type, using RNAi and overexpression coupled with RNA-Seq and Ribo-Seq. Together, these studies will provide a comprehensive basis for understanding alternative mRNA isoform regulation in mammals. PUBLIC HEALTH RELEVANCE: This project will provide comprehensive resources, tools and concepts for understanding the different protein forms produced by human genes, including their evolutionary histories and regulation. These resources, tools and concepts will aid in understanding mammalian development and the pathogenic mechanisms of a variety of diseases related to misregulation of alternative splicing, including myotonic dystrophy, spinal muscular atrophy, amyotrophic lateral sclerosis, retinitis pigmentosa and cancer.

DESCRIPTION (provided by applicant): Most human genes produce multiple distinct mRNA and protein isoforms through alternative splicing that may have distinct or even antagonistic biological functions. Alternative splicing is regulated by a set of RNA binding proteins (RBPs) whose functions are important in development and in a number of diseases. Our approach to the long-term goal of understanding the function of RBPs and their roles in alternative splicing is organized around the following specific aims: SA1. To develop a method for determination of the quantitative in vitro RNA binding specificity of a protein at unprecedented depth and to determine the RNA affinity landscape of RBFOX family proteins. SA2. To understand the sequence and RNA structural basis of RNA binding by MBNL and CELF family splicing factors, the extent of cooperativity and competition, and to understand the regulation of distinct subsets of targets in developmental and pathogenic contexts. SA3. To understand the binding affinity landscapes of factors that recognize motifs at the 3' ends of introns and their roles in regulation of alternative 3' splice site (3'SS) choice. We have recently developed a method called HiTS-FLIP, which provides a quantitative description of the in vitro DNA binding affinity landscape of a protein at unprecedented depth. We propose to develop a variation of this method, HiTS-FLIP-R, to assess RNA binding affinity at a similarly high resolution. The essential idea is to sequence tens of millions of DNA clusters on an Illumina Genome Analyzer 2 (GA2) flow cell, to generate the corresponding RNA sequences by primer extension of anchored DNA adapters, to add a fluorescently tagged RNA binding protein to the flow cell at various concentrations and to image binding to RNA clusters using the GA2's optics. This approach will be applied to key factors involved in development and disease, including RBFOX2 and the myotonic dystrophy (DM) related factors MBNL1 and CELF1, as well as major factors that recognize the 3' splice site and contribute to constitutive and alternative splicing. These data will be used to develop quantitative models that predict the effects on binding and regulation of defined perturbations in the levels of specific RBPs, and the roles of these factors in development and in DM. PUBLIC HEALTH RELEVANCE: This project will provide comprehensive resources, tools and concepts for understanding the binding of proteins to RNA. It will also generate comprehensive binding affinity data for several important RNA binding proteins that function in constitutive splicing, which is required for expression of most human genes, or alternative splicing, including analysis of proteins that play central roles in development and in diseases such as myotonic dystrophy and cancer.

DESCRIPTION (provided by applicant): Expression of the full complement of 20,000+ human genes requires splicing of an average of 8-10 introns per mRNA, and most human genes produce multiple distinct mRNA and protein isoforms through alternative splicing. Each of the ~200,000+ introns in the genome contains 3 specific sequence sites - the donor or 5' splice site, the acceptor or 3' splice site and the branch point - that are absolutely required because they participate in the chemistry of splicing. The branch point is a specific nucleotide (usually adenosine) that participates in the first catalytic step of splicing, generating the unique lariat intron structure that is released in the second step of splicing. Mutation of the branch site frequently results in exon skipping, intron retention or other perturbation of normal splicing, which can result in production of truncated or aberrant proteins, and sometimes leads to disease. However, branch points have been mapped for only several dozen human introns. Here, we propose to develop a technology to map RNA branch points on a large scale, using model organisms to test and optimize the method, followed by application of the optimized procedure to map branch points genome-wide in human and mouse. Our proposal is organized around the following specific aims: SA1. Develop a protocol for large-scale identification of branch points and associated mapping software and apply to model organisms (yeast, fly, or worm). SA2. Optimize and apply protocols and software from SA1 to mammalian systems to achieve large- scale identification of branch points in the human and mouse genomes. We have designed two molecular biology protocols that when coupled with second-generation sequencing and associated software pipelines have the potential to identify branch points on a genome-wide scale. Development of this technology and application to the worm, fly, human and mouse genomes has the potential to contribute a critical missing piece in our understanding of RNA splice codes in these organisms, and will enable improved prediction of mutations or other genetic variations that perturb splicing and gene expression by interfering with branch point function.

DESCRIPTION (provided by applicant): The epithelial-mesenchymal transition (EMT) is a complex cell-biological program that operates during the progression of carcinoma cells to high-grade malignancy, conferring on these cells many of the attributes associated with aggressive tumors, including the ability to disseminate to distant sites and to seed metastatic colonies. This program is orchestrated by a series of pleiotropically acting master transcription factors (EMT- TFs) that organize the complex changes in gene expression causing the replacement of a large cohort of epithelial cell proteins with those associated with the mesenchymal cell state. A major, critical level of control required for expression of the aggressive mesenchymal state is poorly understood however: the precursors of many of the mRNAs whose expression changes during the EMT also undergo alternative splicing (AS) that confer on resulting mature, processed mRNAs altered properties, including changes in stability, protein-coding information, and responsiveness to microRNA-mediated inhibition. The current fragmentary insights into the effects of AS on the execution of the EMT program make it impossible to form a reasonably complete understanding of how this critical cell-biological program is effected. The proposed research will begin by enumerating the hundreds of AS events that occur in response to several alternative mechanisms of inducing an EMT program both in cultured cells and in a living tissue. Having done so, bioinformatics algorithms will be employed to determine the sequences adjacent to involved splice sites. Thereafter, using the known nucleotide-recognizing properties of the large array of already-characterized RNA- binding, splice-regulating proteins, predictions will be made by these algorithms about the identities of the splice-regulators that are likely to b responsible for the observed large-scale shifts in AS occurring during passage through an EMT. This experimental strategy should yield the identities of key regulators of AS that are likely to b as important functionally as the EMT-TFs in executing the EMT program. Experimental tests designed to functionally test the candidacies of these AS factors will be performed. These tests will gauge whether the forced or blocked expression of these factors affect execution of critical components of the EMT program, and whether, as predicted, such imposed changes in AS factor expression affect the production of key EMT-associated proteins, i.e., proteins that play key roles in the expression of the epithelial versus mesenchymal cell phenotypes observed during malignant progression. This work also has the potential to identify novel biomarkers of the EMT program that are applicable, for example, for the detections of stem cells in a variety of epithelial tissues.

Computational, bioinformatics and statistical capabilities are essential tools in cancer research, reflecting the widespread reliance on genome-wide approaches and the use of new methodologies, from imaging to highthroughput screening to next generation sequencing to proteomics, that generate increasingly complex data sets. The Bioinformatics & Computing Core (BCC) is a Shared Resource that provides both the computational infrastructure and expert bioinformatics and biostatistical support. The BCC is comprised of an outstanding team of staff scientists who contribute sophisticated bioinformatics and statistical analyses to research projects and/or provide expert training in these methods. Additionally, it provides access to an array of high performance computing, data storage server and software resources, as well as custom programming and database development to support the research programs of Center Members and also data intensive applications of other Koch Institute Cores. During the current period, the Koch Institute BCC was merged with the Bioinformatics efforts of three other MIT groups to create a shared Institutional BCC. Moreover, significant investments were made to update and expand both the high performance computing and data storage capabilities using MIT funds. This resulted in a significant expansion in capabilities and the diversity of staff expertise, including the addition of in-house biostatistical analyses. It also created significant economies of scale. Consequently the requested CCSG budget for Year 44 is 15% less than the requested and recommended budget in Year 39. Importantly, usage of the BCC by Center Members increased from 37% to 59% during the current period. Moreover, Center members account for 74% of the bioinformatics usage of the shared BCC even though the requested CCSG support for this Core is only 52% of the total stakeholder contributions.

Thousands of human genes produce multiple distinct mRNA isoforms through alternative cleavage and polyadenylation (APA). APA is often conserved in other mammals. It can dramatically change protein function, e.g., switching between membrane-bound and secreted forms. It can sometimes produce mRNA isoforms that differ in their stability or translation, but we have found that this is uncommon. Instead, we hypothesize that APA is often regulated for the purpose of producing mRNA isoforms that differ in their subcellular localization, such as localization to axons and dendrites of neurons. Our approach to the long-term goal of understanding the regulation and function of APA in mammals is organized around the following specific aims: SA1. Determine the dynamics and function of mRNA 3' ends in neuronal differentiation. We propose to map the dynamics of alternative 3' UTR expression during neuronal differentiation in vitro and to assess the localization properties of alternative 3' UTRs. SA2. Identify factors that control the neuronal program of alternative 3' UTR isoforms. We will integrate data from SA1 and from an ENCODE project related to RNA binding proteins to identify candidate APA regulatory factors, and will then test them by analysis of mRNA isoforms following RNAi, and by use of a metabolic labeling approach to distinguish regulation of cleavage and polyadenylation (CPA) from regulation of mRNA stability. Fundamentally, this proposal seeks to understand the regulation and function of the 3' ends of genes, and to establish their roles in the nervous system, with potential implications for neurological disease and cancer.

Project Summary Most human genes are regulated after they are transcribed, at the level of splicing, mRNA decay, translation, and/or mRNA localization. The specificity of post-transcriptional regulation is driven mostly by the sequence- or structure-specific recognition of RNA by RNA-binding proteins (RBPs). We described an integrated series of efforts organized around a single but broad-reaching aim: SA1. To understand the extent, nature and evolutionary conservation of sequence context effects on RBP binding to RNA motifs. We have recently developed an assay called RNA Bind-n-Seq (RBNS) for comprehensive, quantitative analysis of an RBP?s affinity for RNA. Here, we propose to extend this approach to study the determinants of binding to natural human and mouse 3' UTR sequence by several important RBPs. Subaims are directed at understanding how RNA secondary structure impacts RBP binding to cognate motifs, understanding the effects of flanking sequence composition, assessing the conservation of RBP affinity to specific RNA regions, and developing and testing a predictive model of RBP/RNA interaction. The project is expected to yield a deeper understanding of how the sequence and structural context of an RNA motif influence its occupancy and regulatory potential, and insights into the functions of RBPs such as FMRP, hnRNP K, MBNL1 and RBFOX1 that play important roles in development and in diseases such as mental retardation, myotonic dystrophy, autism and cancer.

Project Summary Ovarian carcinoma is the fifth deadliest cancer among women in the United States. In spite of advances in surgical resection and platinum-taxane combination therapy over the past several decades, cure rates remain relatively low (~30%) and a majority of women diagnosed with advanced ovarian cancer will die with drug-resistant disease within 5 years. The long-term goal of this project, ?RNA-Binding Proteins as Molecular Integrators that Control the Response of HGSOC to Anti-Cancer Therapies?, is to identify specific RNA-binding proteins that, together with their upstream protein kinase regulators, control the resistance and sensitivity of high-grade serous ovarian cancers to these clinically used first line anti-cancer therapies. The project involves: (1) a detailed computational analysis that queries pre-existing publically available RNA expression data using RNA-BP recognition motifs to identify specific RNA binding proteins whose mRNA targets are up- or down- regulated in ovarian cancer patients with chemo-sensitive versus chemo-resistant tumors; and (2) an independent CRISPR-interference and CRISPR-activation genome-wide screen for RNA-BPs whose manipulation alters the resistance and sensitivity of ovarian cancer cells to platinum and taxane agents in vitro, and in vivo using cell line xenografts and human PDX ovarian cancer mouse models. The RNA-BPs identify by these two complimentary approaches, together with a collection of RNA-BPs that we have already identified in previous experiments and preliminary data, are then directly validated for their effects on drug resistance in these model systems, and the identity of their bound RNAs and their effects on gene expression determined using CLIP technologies and RNA-Seq. In selected cases the importance of specific phosphorylation sites on RNA-BP function is examined to further elucidate the molecular basis for anti-cancer drug resistance through pathway-specific regulation of RNA-BP action. The project builds on a broad foundation of expertise and related work from all of the co-Investigators laboratories. Expected outcomes from the studies include the identification of specific RNA-BPs and upstream regulatory kinase pathways whose targeting can prevent or reverse the resistance of ovarian cancers to current clinically used front-lime therapeutics; the elucidation of new molecular circuits that control gene expression in cancers after chemotherapy treatment; and the creation of a suite of web-based tools available to the entire scientific community that can be used to query any set of differentially expressed genes for RNA-BP-based regulation, particularly in a form that is optimized for analysis of new and existing cancer patient RNA expression datasets.  

Integrated Genomics & Bioinformatics Core: Project Summary/Abstract Modern cancer research relies on a broad array of genome-wide approaches. The mission of the Koch Institute Integrated Genomics & Bioinformatics Core (IGB Core) is to support the acquisition of genomic and gene expression data and the organization and analyses of the resulting large and complex data sets through advanced technology service platforms, state-of-the-art computational infrastructure and expert bioinformatics capabilities. It provides Center Members with integrated and comprehensive services including consultative services and training in experimental design and data analyses and technical pipelines from sample generation and quality control to sequencing and informatic analysis to allow investigation of: mRNA, microRNA and lncRNA expression; splicing events; transcription factor binding sites; epigenetic modifications; point mutations and chromosomal abnormalities; and single cell genomics. In the prior renewal, the Genomics and Bioinformatics Cores were presented as separate entities. We have now combined these into the IGB Core, reflecting the critical importance of integrating genomics data generation with downstream informatic analysis. The IGB Core is an Institutional Shared Resource between the Koch Institute and three other MIT units. During the current period, usage of the IGB Core increased from 80% to 87% of Center Members. To support this demand, the IGB Core expanded sample preparation, quality control and processing, data analysis, and hardware and software capabilities. This includes expanded offerings for ii) sequencing library preparation, including development of multiple high-throughput (HT) protocols; ii) single cell acquisition/sequencing and analysis approaches; iii) long read sequencing services and analysis; and iv) RNAseq and Epigenomics analysis capabilities. The IGB Core also deployed new compute and data storage resources. Core staff provided additional direct support to this CCSG through development of financial and publication database and client-side interfaces. Thus, this Shared Resource is essential to the success of the Koch Institute mission. In the upcoming period, The IGB Core is committed to continued enhancement of genomics technologies and informatics expertise as well as maintaining IT hardware to support these efforts and the KI research community. Planned initiatives include: developing additional HT methods for sequencing library preparation; further strengthening expertise in single cell genomics applications; expanding data storage and compute cluster and/or cloud computing in line with investigator needs; and expanding informatics training offerings to include more hands-on workshop opportunities. This shared Core is of exceptional value to the CCSG because Koch Institute Members account for 47% of the Genomic services usage and 87% of Informatics services usage, but the CCSG contribution to the Core (8%) is comparable to that of the other sponsoring entities (7%) and far less than the costs covered by user chargebacks (78%).