UCLA Bioinformatics: The Philosophy of the Training Environment and Programs

(This post is jointly authored with Alexander Hoffmann, Hilary Coller, Matteo Pellegrini, and Nelson Freimer.)

UCLA has a rich training environment for Bioinformatics that extends beyond the core academic programs.  For structured academic learning, UCLA offers an Undergraduate Bioinformatics Minor and a Bioinformatics Ph.D. Program.  In addition, UCLA coordinates multiple training programs, several of which are open to researchers from other institutions who are at all stages of their careers.  Many of these programs are either hosted or jointly sponsored by the Institute for Quantitative and Computational Biology (QCB) at UCLA, which is directed by Alexander Hoffmann (UCLA).

Over the past 10 years, driven by the ubiquity of genomics throughout the field, biology has become a data science. Every biomedical research institution has been challenged with supporting the analysis of genomic data generated by groups who traditionally have not cultivated substantial computational expertise. Many of our peer institutions delegate genomic data analyses to a specific Bioinformatics core group that operates on a “fee-for-service” model.

The Bioinformatics core “fee-for-service” model poses many problems.  First, complex issues that arise during analysis of genomic data are difficult to predict in advance.  Projects often require much more effort than anticipated by research groups, leading core groups to struggle with insufficient funds to cover the actual time spent on analysis.  Second, research groups utilizing the core often want to move the project in different directions than what was originally proposed.  In the long term, exploring additional aspects of data can be inefficient when data analysis is delegated to a core group on an as-needed basis.

At UCLA we follow a different approach.  We believe that research groups should receive the training and resources to analyze the genomic data that they generate.  This “training and collaboration” model is the best solution for efficiently completing projects and advancing skills in a research group.  Over the past ten years, UCLA has significantly invested in this training and collaboration model.  For example, UCLA’s Bioinformatics programs are explicitly organized to connect research groups with core groups across campus and provide infrastructure and training to students, faculty, and staff working in many different fields.

Bioinformatics training programs held at UCLA include:

    1. The Collaboratory. The Collaboratory of postdoctoral fellows, directed by Matteo Pellegrini (UCLA), provides an experimental and empirical research environment for bioscientists and computational scientists to collaboratively design and conduct experiments. Most bioscience laboratories have limited capabilities in large-scale data analysis. The Collaboratory’s main mission is to advance genomic data analysis by connecting UCLA bioscience faculty with QCB faculty and fellows.  The Collaboratory fellows are a select group of postdocs funded by the Collaboratory to engage in collaborative projects that leverage their specific expertise.

      The Collaboratory fellows are also responsible for organizing intensive tutorials designed to train UCLA students and postdocs in the latest next-generation sequence analysis techniques. In addition to providing computational expertise to bioscience researchers at UCLA, the Collaboratory also sets up and maintains a next-generation sequence data analysis server, and participants develop methodologies to process new types of data. The Collaboratory has a year-round schedule of workshops open to the Bioinformatics community.

 

    1. Bruins in Genomics Undergraduate Summer Research Program (B.I.G. Summer). B.I.G. Summer is an integrated undergraduate training and research program in genomics and bioinformatics at UCLA. Participants gain an intensive, practical experience in integrating quantitative and biological knowledge while learning how to pursue graduate degrees in the biological, biomedical or health sciences.  The program begins with two weeks of hands-on tutorial workshops that cover fundamental concepts in genomics critical to participation in today’s research.  The remaining weeks are focused on research.  Students work in pairs under the supervision of UCLA faculty mentors and QCB postdoctoral fellows.

      B.I.G. Summer offers unique opportunities that are often not available to undergraduates, including next generation sequencing analysis workshops, weekly science talks by senior researchers, a weekly journal club, professional development seminars, social activities, concluding poster sessions, and a GRE test prep course.  In addition, a special NIH-funded curriculum in neurogenomics, directed by Nelson Freimer and Eleazar Eskin, provides B.I.G. Summer participants with an intensive exposure to this rapidly growing field, in which UCLA is among the leading centers worldwide. B.I.G. Summer is organized by Alexander Hoffmann, Hilary Coller, Tracy Johnson, and Eleazar Eskin. This year, B.I.G. Summer is held from June 19th to August 11th, 2017.  The B.I.G. Summer Program is sponsored by the following generous institutions:

      UCOP for a UC-HBCU partnership Program in Genomics and Systems
      NIH NIBIB for NGS Data Analysis Skills for the Biosciences Pipeline R25EB022364
      NIH NIMH for Undergraduate Research Experience in Neuropsychiatric Genomics R25MH109172

 

    1. Undergraduate and MS Research Program. One of the best ways for faculty to provide training to undergraduate and graduate students is through mentorship in research labs. A substantial challenge to this approach is the increasing number of undergraduate students who want to get involved in research.  For example, there are many more Computer Science majors interested in research than can be absorbed by the number of faculty presently in the Department of Computer Science.  In order to meet rising undergraduate demand for research opportunities, we created an Undergraduate and Master’s student research program.

      This program connects researchers across campus with interested students from a variety of majors.  In doing so, we leverage UCLA’s strength in Bioinformatics to offer a greater number of research opportunities available to undergraduates with and outside of the Department of Computer Science.  Each research opportunity posted on the webpage has a list of requirements, ranging from “one course in Bioinformatics or programming” to “a full year of coursework in programming.”  For students who have completed relevant coursework or are planning their academic schedule, this program provides a clearly defined path to become involved in research projects on campus.

 

    1. Informatics Center for Neurogenetics and Neurogenomics (ICNN). As with other areas of biomedical science, the post-genome era raises the prospect of transformational advances in neuroscience research. However, neuroscience faces special challenges in analysis, interpretation, and management of the vast quantities of information generated by genetic and genomic technologies. The phenotypic and organizational complexity of the nervous system calls for distinct analytical and informatics strategies and expertise.

      The ICNN, directed by Nelson Freimer and Giovanni Coppola, provides advanced analysis and informatics support to a highly interactive group of neuroscientists at UCLA who conduct basic, clinical, and translational research.  Generally, today’s lack of corresponding resources in analysis and informatics constitutes a bottleneck in their research; ICNN provides for these investigators access to excellent facilities for genetics and genomics experimentation.  ICNN faculty are experts in statistical genetics, gene expression analysis, and bioinformatics, and they oversee the activities of highly-trained staff members in  accomplishing three goals: (1) Providing expert consultation and analyses for neurogenetics and neurogenomics projects;  (2) Developing and maintaining a shared computing resource that is incorporated within the large campus-wide computational cluster for computation-intensive analyses, web-servers, and state of the art software tools for a wide range of applications (including user-friendly versions of public databases, as well as workstations on which ICNN users will be trained to employ these tools); (3) Providing hands-on training in analysis and informatics to group users.

 

  1. Computational Genomics Summer Institute (CGSI). In 2015, Profs. Eleazar Eskin (UCLA), Eran Halperin (UCLA), John Novembre (The University of Chicago), and Ben Raphael (Princeton University) created CGSI. A collaboration with the Institute for Pure and Applied Mathematics (IPAM), led by Russ Caflisch, CGSI is developing a flexible program for improving education and enhancing collaboration in Bioinformatics research. The goal of this summer research program is to bring together mathematical and computational scientists, sequencing technology developers in both industry and academia, and the biologists who use the instruments for particular research applications.

    CGSI is a unique opportunity for junior and senior scholars in Bioinformatics to foster collaborative relationships, accelerate problem-solving, and unleash the full potential of their projects.  The program facilitates interdisciplinary collaboration and training with a mix of formal and informal events. For example, senior scholars present traditional research talks and tutorials, while junior scholars present mini-presentations and organize journal clubs.  CGSI fosters interactions over an extended period of time and is laying crucial groundwork to advance the mathematical foundations of this exciting field.  This year, CGSI will be held from July 6th-26th, 2017. CGSI is made possible by National Institutes of Health grant GM112625.

 

“Give a Man a Fish, and You Feed Him for a Day. Teach a Man to Fish, and You Feed Him for a Lifetime.”

UCLA Bioinformatics: The Philosophy of the Undergraduate Program

Bioinformatics is an important interdisciplinary research area with tremendous opportunities in graduate training and industry employment.  Yet, few academic institutions offer undergraduate programs designed to prepare students for opportunities in Bioinformatics.

The UCLA Undergraduate Bioinformatics Minor is an academic program established in Fall 2012 at UCLA.  Undergraduates in any Major can obtain a Bioinformatics Minor by completing an additional 8 courses. Since Fall 2012, approximately 80 students have joined the Minor program. These students represent Majors in over a dozen UCLA departments, including: Computer Science; Chemistry; Molecular, Cell, & Developmental Biology; Microbiology, Immunology, and Molecular Genetics; Ecology and Evolutionary Biology; and Computational and Systems Biology.

Over 45 faculty specializing in computational and experimental biology are associated with the Bioinformatics Minor, spanning the fields of biology, mathematics, engineering, and medicine. Course offerings from more than 12 unique departments allow the Minor program to encompass the breadth of the growing Bioinformatics field.

Here we describe the principles and philosophy that guided the design of our Minor.

  1. Our Core Bioinformatics Courses Teach Interdisciplinary Computation. The foundation of our program is the cluster of three integrated core courses in Bioinformatics. These courses are truly interdisciplinary; they satisfy elective requirements in multiple departments and recruit students from different Majors to the Minor program. These core courses build upon the philosophy that students must first learn fundamental concepts in computation in order to later explore problems in Bioinformatics.  These courses offer basic skills and appeal to many students beyond those interested in Bioinformatics.
  1. Rigorous Background in Computation. To be successful in Bioinformatics, students must have a solid background in both computation and Biology. Our core courses require as prerequisites a substantial background in computation and statistics. To enter the Minor, we require that students have completed one year of programming and one upper division Statistics course.  To complete the Minor, our students take Linear Algebra and one upper division course on Algorithms taught by the Computer Science or Math Department.  Our students also take a Molecular Biology course taught by the Life Sciences Department. We believe that it is important for faculty in Computer Science and Program in Computing to teach programming, and for faculty in the Life Sciences to teach Biology. Further, it is important for students to take the same programming classes as do their peers in Engineering majors, and for students to take the same Biology classes alongside their peers in Life Sciences.
  1. The Bioinformatics Minor Builds upon the Students’ Major. Every student graduating from UCLA with a Bioinformatics Minor also completes an academic Major program. While we do adjust the Minor curriculum to help students efficiently complete both their Major and Minor requirements within 4 years, each of our graduates has exactly the same amount of training in their Major as fellow Majors who are not in the Minor.  This avoids a common pitfall in interdisciplinary education: students only receive a superficial background in each academic area.
  1. Bioinformatics is a Research Oriented Field. Our Minor is closely integrated with our undergraduate research program, which places students in the labs of Bioinformatics faculty. Most of the Bioinformatics Minors at UCLA are working in a research lab.  Undergraduates are strongly encouraged to engage in research. The Minor allows for a substantial amount of research credits, an allowance that helps students complete their Major and Minor requirements in four years.  In addition, many of our undergraduates participate in the Bruins-in-Genomics Summer (B.I.G. Summer) program or similar undergraduate education experience summer programs.
  1. Bioinformatics is an Increasingly Diverse Field. The core courses in Bioinformatics are designed to be interesting and accessible to students from a wide variety of educational backgrounds. Each course typically has enrollment approaching 100. Far more students who are not in the Bioinformatics Minor take these courses as electives to fulfill their Major requirements. Student enthusiasm is high for these accessible interdisciplinary courses that combine computational sciences and Biology. We find that this approach boosts broader undergraduate engagement in the field and encourages students from traditionally underrepresented groups to pursue research, graduate school, or careers in STEM fields.
  1. Let Excitement Foster Program Growth. Bioinformatics is an exciting area, and specialized training is critical for the next generation of biomedical researchers. However, undergraduate Bioinformatics programs, when offered by a college or university, are typically quite small.  Such programs are often limited in size and engagement as students are unaware of the field or become aware of Bioinformatics late in their college career. We strategized the Bioinformatics Minor program at UCLA specifically to attract students at any stage of their college career and to maximize curricular flexibility so students can easily complete Minor requirements. Many students are attracted to the Minor when they enroll in Bioinformatics core courses to fulfill elective requirements for their Major; some develop a keen interest in the field and then join the Minor. Even students who are unable to complete all Minor requirements benefit from our program; they complete key coursework and join a research lab, gaining knowledge and experience crucial for gaining employment or admission to graduate school.

Our current goal for the Bioinformatics Minor is to graduate 50 students per year.  We hope that 10 to 20 of them will enter graduate studies in Bioinformatics.  We are not there yet, but are growing. This year, around 10 graduates applied to Ph.D. programs in Bioinformatics.  Many of our students recently began or are applying to Ph.D. programs in Bioinformatics and related areas.  We expect that they will do very well in the admissions process and have great backgrounds for starting Ph.D. study in Bioinformatics.

bioinformatics-minor-graphical-element-the-minor

Read more about the Bioinformatics Minor on the official website:
http://bioinformatics.ucla.edu/undergradute-bioinformatics-minor/

Check out a list of research opportunities available for undergrads at UCLA:
http://bioinformatics.ucla.edu/undergraduate-research/

Learn more about 2016 undergraduate research and B.I.G. Summer activities at ZarLab:
zarlab.cs.ucla.edu/b-i-g-summer-in-zarlab/

Applications to the 2017 B.I.G. Summer program are due January 27:
http://qcb.ucla.edu/big-summer/

Profiling adaptive immune repertoires across multiple human tissues by RNA Sequencing

In a project led by Serghei Mangul, members of our lab recently developed and tested a novel computational method that uses regular RNA-Seq data to rapidly and accurately profile the human immune system. Mangul and his collaborators, including UCLA graduate student Harry (Taegyun) Yang and 2016 B. I. G. Summer undergraduate participants Jeremy Rotman, Benjamin Statz, and Will Van Der Wey, recently published their results in a paper on bioRxiv.

Discoveries in human immunology and advancements in development of treatments for many common human diseases depend on detailed reconstructions of the adaptive immune repertoire. The “adaptive” immune repertoire recognizes pathogens and toxins that the “innate” defense system misses. Assay-based genetic studies provide a detailed view of these adaptive systems by profiling the genetic expression and repertoires of B and T cell receptors. Assay-based approaches have accurately characterized the immune repertoire of peripheral blood.

However, these methods are expensive and smaller in scale when compared to standard RNA sequencing (RNA-seq). Characterizing the immunological repertoires of other tissues, including barrier tissues like skin and mucosae, requires large-scale study. RNA-Seq can capture the entire cellular population of a sample, including B and T cell and their receptors.

ImReP is the first method to efficiently extract B and T cell receptor derived reads from RNA-Seq data, accurately assemble CDR3 sequences, the most variable regions of these receptors, and determine their antigen specificity. Mangul and his team used simulated data to test the feasibility of using RNA-Seq to study the adaptive immune repertoire. ImReP is able to identify 99% CDR3-derived reads from the RNA-Seq mixture, suggesting it is a powerful tool for profiling RNA-Seq samples of immune-related tissues.

They also compared methods and investigated the sequencing depth and read length required to reliably assemble B and T cell receptor sequences from RNA-Seq data. ImReP consistently outperformed existing methods in both recall and precision rates for the majority of simulated parameters. Notably, ImReP was the only method with acceptable performance at 50bp read length, reconstructing with higher precision rate significantly more CDR3 clonotypes.

Mangul and his team applied ImReP to 8,555 samples across 544 individuals from 53 tissues obtained from Genotype-Tissue Expression study (GTEx v6). The data was derived from 38 solid organ tissues, 11 brain subregions, whole blood, and three cell lines. ImRep identified over 26 million reads overlapping 3.8 million distinct CDR3 sequences that originate from diverse human tissues.

Using ImReP, they created a systematic atlas of immunological sequences for B and T cell repertoires across a broad range of tissue types, most of which were not previously studied for B and T cell repertoires. They also examined the compositional similarities of clonal populations between tissues to track the flow of B and T clonotypes across immune-related tissues, including secondary lymphoid and organs encompassing mucosal, exocrine, and endocrine sites.

Advantages of using RNA-Seq to study immune repertoires include the ability to simultaneously capture both B and T cell clonotype populations during a single run, simultaneously detect overall transcriptional responses of the adaptive immune system, and scaling up the atlas of B and T cell receptors that will provide valuable insights into immune responses across various autoimmune diseases, allergies, and cancers.

Read more about ImReP in the full article, which is available for download on bioRxivhttp://biorxiv.org/content/early/2016/11/22/089235.article-metrics

ImReP was created by Igor Mandric and Serghei Mangul. ImReP is freely available at: https://sergheimangul.wordpress.com/imrep/

The atlas of T and B cell receptors, the largest collection of CDR3 sequences and tissue types, is freely available at https://sergheimangul.wordpress.com/atlas-immune-repertoires/. This resource has potential to enhance future studies in areas such as immunology and advance development of therapies for human diseases.

The full citation to our paper is:

Mangul, S., Mandric, I., Yang, H.T., Strauli, N., Montoya, D., Rotman, J., Van Der Wey, W., Ronas, J.R., Statz, B., Zelikovsky, A. and Spreafico, R., 2016. Profiling adaptive immune repertoires across multiple human tissues by RNA Sequencing. bioRxiv, p.089235.

 

Figure 1. Overview of ImReP.

Figure 1. Overview of ImReP. (See full paper for details.)

 

Figure 6. Flow of T and B cell clonotypes across diverse human tissues.

Figure 6. Flow of T and B cell clonotypes across diverse human tissues. (See full paper for details.)