Titles and Education

Titles

Director, Genome Sciences Centre, BC Cancer Agency
Senior Scientist, BC Cancer Research Centre, BC Cancer Agency
Professor, Department of Medical Genetics, University of British Columbia
Adjunct Professor, Department of Molecular Biology and Biochemistry, Simon Fraser University
Faculty Member, Bioinformatics Graduate Program, University of British Columbia
Associate Member, Michael Smith Laboratories, University of British Columbia

Education

B.Sc., Molecular & Cell Biology, Simon Fraser University
Ph.D., Genetics, Simon Fraser University

Letter from the Director

Research Activities

Research

Over the next five years, I and my colleagues at the GSC will be involved in the design, evaluation and implementation of novel genomics approaches to research problems fundamentally important in health and disease. My personal research program, which is designed to complement those of others at the GSC, will utilize state-of-the-art genomics approaches to focus primarily on (1) identification and analysis of genome variation in health and disease models and (2) expression genomics, in which DNA sequencing and micro-array approaches will be used to identify, clone and sequence differentially expressed transcripts, including alternatively spliced transcripts produced from the same locus but encoding different proteins. Specific examples of projects in both of my two selected areas of emphasis are provided below to illustrate the approaches I will use to study mental retardation, cancers, and embryonic stem cell lines. Much of work is collaborative, and so involves researchers with biological and disease expertise complementary to my own expertise in genomics.

Genome Variation Project I: Improved diagnoses and evaluation of mental retardation

Dr. Jan Friedman of UBC, and I co-lead a project funded by Genome Canada and by the Canada Foundation for Innovation to identify and analyze “copy number variants” (“CNVs”, which we define as losses or amplifications of genomic material) in the genomes of children with idiopathic mental retardation. The purpose of this project is to evaluate high-resolution genomic array technologies as an alternative to conventional cytogenetic analysis (the current standard of clinical care) for the identification of constitutional chromosomal abnormalities in individuals with idiopathic mental retardation. Such technologies have been successfully applied in numerous studies of cancers, but our study is among the first to apply genomic arrays to the study of mental retardation.

Genome Variation Project II: High resolution analysis of follicular lymphoma genomes

I, along with Drs. Joe Connors and Randy Gascoyne, lead the project “High resolution analysis of follicular lymphoma genomes”, which has been approved for funding in the latest Genome Canada competition and has started in early 2006. Co-funding for this project is provided by a National Cancer Institute of Canada Program Project Grant to Drs. Connor, Gascoyne, Horsman, and I, all of whom are the BC Cancer Agency. The primary aims of the effort are to reconstruct entire tumor genomes in sequence-ready clones, and use the clones to identify and sequence genome rearrangements. This high-resolution, novel approach will contribute to a fundamental undestanding of the genetic alterations that underlie neoplastic progression. In this project, we will (1) produce BAC fingerprint whole-genome maps of at least 24 follicular lymphoma genomes, (2) identify recurrent genome rearrangements in these genomes, and (3) sequence Bacterial Artificial Chromosome (BAC) clones bearing such rearrangements. We will apply genomics technologies including BAC library construction, BAC fingerprinting, genomic arrays, BAC end sequencing and BAC shotgun sequencing to identify and sequence genome regions rearranged in lymphoma. We are particularly interested in identifying and sequencing rearrangements correlated with progression from follicular lymphoma to diffuse large B cell lymphoma.

Gene Expression Project I: Identification and characterization of differentially expressed alternatively spliced transcripts in cancer models and embryonic stem cells.

A major challenge in decoding the information content of the human genome is presented by the process of alternatively splicing (AS), which can produce from a single locus different transcripts with different combinations of exons and regualtory sequences. Many if not most of the ~25,000 human genes produce alternative transcripts and this has contributed to estimates of more that 100,000 proteins encoded by these loci. We hypothesize that AS is an important mechanism for encoding a diversity of functions at a single genomic locus and that this diversity is realized in part through alterations in protein-protein interactions or sub-cellular location. Until recently it was not possible to measure the prevalence of AS or detect comprehensively the transcripts produced by it. With the availability of high-density micro-arrays, populated by hundreds of thousands of oligonucleotide probes, these limitations have in large part been addressed. The implications of this technical development and the application of it to study AS in the context of cancers are substantial, for up until this time measurements of gene expression relied largely on the detection of a single transcript for each gene. We speculate that by applying to cancer models micro-arrays designed to detect AS, we will discover novel protein-coding exon combinations that may reveal candidates for development of new therapies including vaccines.

Gene Expression Project II: Analysis of transcripts uniquely expressed in human embryonic stem cell lines

We have an ongoing interest in identifying novel genes that may play a role in the maintenance of pluripotentiality and in self-renewal. Accordingly, in collaboration with Dr. Connie Eaves, and with funding from the National Cancer Institute (USA), we recently conducted a study in which we characterized the human embryonic stem cell (ESC) transcriptome by generating and analyzing 2.5 million LongSAGE tags representing nine human ESC lines (www.transcriptomes.org). We also initiated a project to clone novel transcripts identified by LongSAGE tags, using a high throughput pipeline already in place as part of our involvement in the NIH-sponsored Mammalian Gene Collection Consortium. This effort has the potential to contribute significantly to an understanding of the unique repertoire of genes expressed in the stem cell compartment, and how these may function to regulate self-renewal.

Significant Research Contributions

My most significant contributions to genome sciences are listed below. Publications have been organized into groups of technically or scientifically related topic areas.

My work has been cited more than 9,600 times.

Nucleic Acids Research, 2004 Jul 09;32((12):3651-3660; Nature Genetics, 2004 Mar;36(3):299-303.

These publications describe the bioinformatic selection & large-scale validation of a set of more than 30,000 Bacterial Artificial Chromosome clones spanning the human genome (Krzywinski et al) & the use of the clone set in high resolution microarray CGH (Ishkanian et al). The latter technique is increasingly being used to identify genome copy number changes in clinical samples and ours was the first resource to represent essentially the entire human genome.

Emerging Infectious Diseases, 2004 Dec;19(12):2192-2195; Science, 2003 May;300(5624):1399-1404.

The EID publication describes the sequencing of Avian flu genomes isolated from human patients during an outbreak in BC's Fraser Valley. The Science publication describes the rapid generation of the complete and accurate sequence of the SARS-associated coronavirus. The Genome Sciences Centre generated and end-sequenced cDNAs, and then assembled these sequences into the final ~29 kilobase genome sequence. The entire effort took about six days, demonstrating that genome sequencing of a new viral pathogen could be considered a legitimate part of a "rapid response" to an emerging infectious disease. The Science paper has been cited more than 600 times.

Genome Research, 2006 Jun;16(6):768-775; Science, 2006 Sep 15; 313 (5793):1596-1604; Proc Natl Acad Sci USA, 2005 Dec 20;102(51):18526-18531; Science,  2005 Jul 15;309(5733):436-442; Nature, 2005 Apr 7;434(7034):724-731; Science,  2005 Feb 25;307(5713):1321-1324; Nature, 2004 Apr 1;428(6982):493-521; Nature, 2003 Jul 10;424(6945):157-164; Nature, 2002 Aug 15;418 (6899):743-750; Nature Genetics,  2001Oct;29(2):133-134; Genome Research, 2001 Feb;11(2):274-280; Nature, 2001 Feb 15;409(6822):934-941; Nature, 2001 Feb 15; 409(6822):860-921.Genome Research,  1997;7:1072-1084.  

These publications are selected papers of Dr. Marra’s which describe large-scale high throughput DNA sequencing conducted via a hierarchical map-based approach.  The papers published in the Feb. 15, 2001 issue of Nature, titled "The Human Genome", describe the construction and use of Dr. Marra’s fingerprint map of the human genome.  In this regard, Dr. Marra’s responsibility was to devise and then implement the approach that led to the human whole-genome BAC physical map.  This map served as the centralized coordinating resource for the successful public-domain effort to sequence the human genome.

Nature, 2000 Dec 14;408(6814):796-815; Nature, 2000;408:823-826; Cell, 2000;100:377-386; Nature, 1999; 402:769-776; Science, 1999;286:2468-2474; Nature Genet, 1999;22:265-270; Nature Genet, 1999;22:271-275. 

This series of papers describes the mapping and sequencing of the Arabidopsis thaliana genome.  A. thaliana is an important model plant used widely to address issues relevant to plant developmental genetics.  I was a key member of the Cold Spring Harbor Sequencing Consortium, focused on first leading the effort to map the A. thaliana genome and subsequently coordinating aspects of the whole genome sequencing activity.

Genome Research, 2007 Jan;17(1) 108-116; BMC Genomics, 2006, 7:246; Proc Natl Acad Sci USA,  2005 Dec 20;102 (51):18485-18490; Scienc, 2004 Oct 22;306(5696):636-640; Proc Natl Acad Sci USA, 2002 Dec 24;99(26):16899-16903; Genome Research, 2000;10(9):1393-1402; Am J Pathol, 2000;156(4):1109-1115; Cancer Research, 1999;59: 5403-5407; Trends In Genetics, 1998;14:4-7; Genome Research, 1996;9:807-828. 

These publications describe the generation of very large datasets of human and murine gene sequence and gene expression information.  Also described are applications of these datasets to analysis of clinical samples, which led to the identification of tumor markers and antigens.  Papers in this series have important implications for several areas of cancer research. 

Marco Marra's Complete Publications List including selected links to full text articles.

Trainee Projects

Marra Lab 2009

Summary of Dr. Marra's trainee projects

Current Trainees

Targeting lung cancer genomics: A whole genome approach to predicting response

Trainee: Trevor Pugh

Lung cancer is the leading cause of cancer related death in the world. Only 16% of patients survive for more than five years and additional strategies are needed to treat this disease. A new drug, Tarceva, has been developed which targets EGFR, a protein that plays a major role in lung cancers. Patients responding to Tarceva are typically female, non-smokers of southeast Asian descent with adenocarcinoma. DNA sequence mutations and abnormal additional copies of the EGFR gene have been found in the tumours of many responsive patients further suggesting a genetic basis for response. However, several responders lack these variants limiting the use of EGFR status as a diagnostic predictor of drug response. In a search for novel gene changes that accurately predict drug efficacy, we are applying whole genome approaches as part of an ongoing clinical trial of Tarceva as a first-line therapy. Prior to treatment, lung tumour material and blood samples are collected from all patients. To identify abnormal genetic changes in the lung cancer cells, we are employing a whole transcriptome sequencing technique which looks for genetic changes in nearly every gene expressed by these cells at an unprescended resolution. To test whether these changes are unique to each tumour, mutations in these genes are then tested for in normal DNA isolated from the patients’ blood. We anticipate that these analyses will identify a set of previously unseen mutations unique to treatment-naïve lung tumours. This pre-drug genetic information will then be correlated with post-drug clinical response data to identify which, if any, of these genetic features are associated with successful treatment. Given such knowledge, the potential exists for physicians to accurately screen lung cancer patients and identify only those with the genetic capacity to respond to the drug. By combating cancer more effectively at the molecular level, responsive patients will receive effective first-line treatment while non-candidates will be expedited to receive alternate therapies.

Experimental and bioinformatic approaches for the study of alternative transcript diversity in models of cancer progression

Trainee: Malachi Griffith

Initial studies following from the Human Genome Project have revealed that the apparent number of genes present in a human is much less than expected for such a remarkably complex organism. Recent studies suggest that in fact it is not the number of genes that gives rise to our complexity but rather the number of functionally distinct versions of a gene that can be encoded from a single gene region. Human genes are comprised of DNA sequences called exons seperated by long stretches of DNA sequence called introns which must be removed so that the exons can be assembled into a working copy of the gene. My research focuses on the phenomenon of alternative splicing in which one gene is assembled from its component pieces in many different ways to produce a multitude of different functional products. In particular, changes in the forms of certain genes may be important in the progression of cancer and account for the differences in the severity of cancers and response to treatment observed among individuals. For example, by studying the alternative splicing of genes in models of cancer we hope to identify promising candidates for vaccine and drug development. Specifically, we have selected a series of colon cancer cell lines representing a cancer that is sensitive to chemotherapy or resistant to one of four commonly used chemotherapy drugs. By studying the differences in gene structure correlated with this change in drug response we may gain insight into why chemotherapy initially seems to work well in some patients but becomes less effective over time.

The use of microarray technology to profile mRNA transcripts generated by alternative splicing is an area of rapid development. To facilitate the use of microarrays to study alternative splicing I created an open source array design platform for alternative expression analysis called ‘ALEXA' (www.AlexaPlatform.org). This platform allows the design and use of microarrays of arbitrary density and complexity for alternative transcript expression analysis of most EnsEMBL annotated species.  Creation of ALEXA arrays involves the extraction, scoring, filtering and annotation of oligonucleotide probes corresponding to exons, introns, exon boundaries and exon-exon junctions. I used this platform to pre-compute designs for ten EnsEMBL annotated species. To evaluate the ALEXA approach I generated a design for the human genome and measured differential expression of alternate isoforms between 5-fluorouracil sensitive and resistant colorectal cancer cell lines. Results generated from ALEXA arrays were compared to those from Affymetrix exon arrays.  ALEXA array data was comparable or superior to Affymetrix exon arrays in terms of reproducibility, sensitivity and specificity and provided additional information on the connectivity and boundaries of exons.

My continuing objectives are to catalog exon combinations encoded by alternatively spliced transcripts specific to chemotherapy resistance or other forms of cancer progression and to explore in detail the differential expression, transcript structure and function of a set of transcripts with these exon combinations.

Antisense Transcription in Mammalian Development

Trainee: Sorana Morrissy

Elucidating the mechanisms by which gene expression is regulated is one of the main challenges in understanding mammalian development. Antisense (AS) transcription has recently been recognized as one such mechanism, although fewer than 40 sense-antisense (S-AS) transcripts are known to play roles in development. With the availability of extensive EST and fully-sequenced cDNA libraries, the number of S-AS genes has grown to encompass nearly half of the transcriptome. By using serial analysis of gene expression (LongSAGE), a technology that provides quantitative measurements of transcript levels in a given sample, we are now poised to determine whether these transcripts play a role in regulating gene expression. As part of her thesis project, Sorana is analyzing LongSAGE libraries representing ~100 murine tissues and cell types throughout development. Using clustering methods and custom algorithms, she is able to identify AS transcripts expressed with tissue and temporal specificity, and further analyze the expression of the S and AS transcripts for patterns of expression consistent with regulation.

Informatic approaches for identifying and reducing noise in oligonucleotide probe-level intensity data

Trainee: Noushin Farnoud

Changes in chromosomal copy number (CN) in somatic cells are hallmarks of tumour initiation and progression, as well as other developmental abnormalities such as mental retardation. Such changes can be detected using microarray technologies such as Affymetrix® SNP arrays. Analysis of data generated using this high-resolution, whole-genome analysis technique can reveal both CN changes and uniparental disomy. However, despite improvements in technology, the data are noisy, which adversely affects the sensitivity and specificity of CN change identification, particularly for changes affecting only a few consecutive probe-sets on the array.

The accuracy in assessing CN relies on the sensitivity and specificity of bioinformatics approaches that analyse the array data. Currently no software package can ensure both high accuracy and specificity for CN analysis purposes. We hypothesized and confirmed that one major drawback in available algorithms is that they do not acknowledge the intensity of individual SNP oligonucleotide probes. Instead, these software packages tend to use a normalized and smoothed form of intensity data obtained from averaging groups of probes (PM probes in the SNP probe-set), and use this value for further analysis of CN change. But many such values are likely to be inaccurate as a result of microarray noise. This signal-to-noise ratio (SNR) is the most challenging problem in analysing Affymetrix SNP data and is the key factor in generating false positives and false negatives.

Therefore in order to improve the sensitivity and specificity of CN analysis methods, my project has initially focused on: 1) identifying possible sources of noise in oligonucleotide arrays, and 2) developing an algorithm to bioinformatically improve the SNR. In order to characterize the noise, I have modeled the standard deviation of signal log2-ratios for both SNP probe-sets and individual oligo-probes, and estimated the statistical parameters for this model. The conclusions of this analysis proved that SNPs have a relatively consistent performance between experiments regardless of their CN content. As a result, we concluded that the signal fluctuations must have been generated by the variability in the performance of individual oligonucleotide probes in the probe-sets. Based on this finding, the aim of the rest of the project is to develop and implement a novel algorithm that enables monitoring of CN changes using oligo-level data. The progress so far includes designing a framework for this algorithm, implementing the beta version of the software, and testing it on several known regions of copy number variations (CNVs). All of these CNVs, which ranged from 40Kb to13Mb in size, have been successfully detected by this algorithm. This is a significant success, given that none of the available software packages were able to find “all” of these CNVs.

Unraveling transcriptional regulatory networks in health and disease

Trainee: Olena Morozova

Transcription factors (TFs) are key regulators of gene expression that account for the coordinated regulation of functionally-related genes. A global view of transcriptional regulation is necessary to understand both normal development and disease pathogenesis. The goal of this project is to reconstruct a comprehensive network of mouse TFs governing aspects of development and organogenesis using data from several high throughput experimental platforms available at the GSC. In particular, we use bioinformatics approaches to mine Serial Analysis of Gene Expression (SAGE) data from the Mouse Atlas project to identify co-expression based associations of TFs during mouse development. We also envision incorporating data from the ongoing ChIP-TS (chromatin immunoprecipitation with tag sequencing) experiments that would shed light onto the genome-wide binding patterns of TFs of interest. Ultimately, we hope to be able to achieve a detailed understanding of transcriptional networks that control development and organogenesis and their misregulation during disease.

Characterizing the transcriptomes of  diffuse large B-cell lymphomas using next generation sequencing

Trainee: Ryan Morin

Project summary unavailable at the moment.

Genome analysis of pre- and post-treatment lung cancers from patients in a phase II clinical trial of first-line erlotinib

Trainee: Ian Bosdet 

Lung cancer is the leading cause of cancer mortality, causing over 1 million deaths worldwide each year. The majority of patients with lung cancer are diagnosed with advanced disease due to low rates of early detection. Standard treatments for lung cancer include surgery, radiation and chemotherapy. While these treatments have proven to be effective at reducing the tumor size and extending lifespan, 5-year survival rates are only 10-20%. Improved early diagnosis and better guidance in treatment options can make a significant impact on the number of patients living with, and dying from, this disease.

Genetic changes (mutations) in DNA are thought to be responsible for almost all human cancers. An understanding of how these changes cause cancer will require identification of mutations commonly observed in cancer, an explanation of their biological role in cancer initiation and growth and an exploration of their possible applications for diagnosis and novel anti-cancer treatments. Thus, the first step in the process of understanding the biology of lung cancer is to identify genetic mutations that are commonly observed in these tumors.

Recently, several anti-cancer drugs have been developed to more specifically target cancer cells and have fewer toxic side effects than standard chemotherapy. One of these, Tarceva, has been developed to target EGFR, a protein important for the growth of many lung cancers.  For unknown reasons, Tarceva is most effective in patients that are female non-smokers of southeast Asian decent that have been diagnosed with lung adenocarcinoma.  A genetic characterization of the tumors in these patients may explain why they are sensitive. This knowledge will help to identify other patients who will derive the most benefit from this drug and help in the design of the next generation of therapeutics.

My research asks the following questions:

1. What are the common genetic changes seen in the DNA of lung cancers?

2. Are there genetic changes that are common to lung cancers that are sensitive to Tarceva, and can we use these changes to predict which patients will derive benefit from this drug?

3. Can identification of common genetic changes in lung cancer provide insight into the biological processes that cause lung cancer to start and to grow?

To answer these questions we are applying DNA sequencing to the study of lung cancers isolated from 65 patients enrolled in a clinical trial of Tarceva at the BC Cancer Agency. Tissue samples will be collected from each patient and, using a new generation of sequencing instruments, all the genes expressed in the cancer cells will be analyzed for mutations and expression level. These data will reveal which genes the cancer cells are using and which have mutations. This information can then be correlated to patient treatment outcome to identify genetic changes that effect response of cancer to Tarceva. Genetic changes related to drug response could then be used in the clinic to predict which patients will benefit from this drug and which will not, improving our ability to select the most effective treatment option for all patients.

Retrospective clinical study aimed on improving treatment screening for colorectal cancer patients with respect to mutations of the UMPS gene and the drug 5-fluorouracil

Trainees: Jess Paul, Pierre Cheung (BC Clinical Genomics Network Studentship awardee), and Shaun Drummond

5-fluorouracil (5-FU) is a common chemotherapeutic drug used to combat colorectal cancer, the third most common cancer among Canadians. Though some patients respond positively to 5-FU, others are unaffected or react adversely. In order to metabolize 5-FU into its cancer-fighting form, expression of the UMPS gene is necessary. Therefore mutations in the UMPS gene are believed to confer 5-FU drug resistance to tumour cells.

As part of Malachi Griffith’s work on the characterization of the UMPS locus and its potential relevance to 5-FU resistance, a retrospective clinical study aimed on improving treatment screening for colorectal cancer is in progress. Through collaborations with local hospitals and the Ontario Tumour Bank, 117 pathology samples from colorectal cancer patients were gathered. Sequencing and expression analysis of the UMPS gene isoforms will be analyzed and correlated according to the presence of 5-FU treatment and treatment outcomes. Hopefully, the new insights will help predict treatment response and allow responsible allocation of the drug 5-FU.

Past Trainees

Characterization of novel small-ORF genes in the transcriptome of human ES cells

Trainee: Jaswinder Khattra

Small proteins are important effectors in a variety of biological processes such as cell signalling, immunity, and cellular metabolism. However, their small size has resulted in this class of biomolecules being neglected in mammalian cDNA collections, which is evident by an artificial discontinuity in annotated protein-coding cDNAs at about the 100 amino acid mark. The objectives of this project comprise discovering novel ORFs from rare mRNA transcripts observed in human ES cell transcriptomes as defined by LongSAGE technology, assessing gene regulatory activity of novel protein-coding transcripts via measures of transcript abundance in undifferentiated ES cells versus embryoid bodies, and exploring physical evidence for the expression of novel short proteins in hES cells and embryoid bodies. Full-length novel transcripts recovered using RACE chemistries have been analysed extensively in the context of genomic features, comparison to transcript databases, gene structure, and predicted protein features. Novel ORFs did not exceed a length of 129 amino acids and lacked hits to well characterized protein domains. Candidates deemed interesting from these bioinformatic analyses and differential expression assays are being cloned for further functional evaluation. In addition, physical fractionation and enumeration of the short proteome of hES cells will be conducted in parallel as an alternate experimental approach for gene discovery. Collectively, these studies will contribute towards a more comprehensive catalogue of the biomolecules present within ES cells and a better understanding of their expression pattern and interactions, all of which are prerequisites for the effective application of stem cell products as therapeutic agents or models of tissue development.

Developing algorithms for microRNA expression profiling using a next-generation sequencing strategy

Trainee: Ryan Morin

The emergence of next-generation sequencing technologies has provided means to quickly sequence a population of millions of RNA molecules. When applied to small RNA fractions of cells, these sequences represent a quantitative SAGE-like snapshot of microRNA expression. Owing to the huge amount of sequence data and unique nature of sequence reads, novel software is required to summarize these data into manageable and accessible forms. A database has been developed that efficiently stores these sequences as well as a multitude of programs that perform various annotation and analysis tasks. His analysis pipeline has been applied to three separate research projects to date. The majority analysis has focused on the microRNAs that change during differentiation of human embryonic stem cells. Ongoing research is also revealing many novel microRNA genes and potential key targets of differentially expressed microRNAs.

A functional genomic approach identifies novel players of steroid hormone induced programmed cell death in drosophila

Trainee: Suganthi Chittaranjan

Co-Supervisor: Sharon Gorski

All multicellular organisms begin as a single cell that multiplies and shapes into a fully formed adult.  During this process, millions of cells are produced and their fate is determined by survival and death signals. A genetically regulated program known as Programmed Cell Death (PCD) removes obsolete cells. PCD is an important process because errors in PCD can cause a variety of human diseases including cancer. Drosophila is a model organism that shares many features of PCD with humans.  During Drosophila pupation, larval salivary glands undergo stage-specific PCD. Discovery of new genes involved in the cell death of larval salivary glands and unveiling the function of them will provide new insights into PCD and will provide potential new markers and therapeutic targets for cancer and other diseases. Using the powerful genomic and bioinformatic tools available in our center, we identified 500 candidate genes that were activated prior to PCD.  We determined whether these 500 candidate genes are involved in PCD using a highthroughput technique know as RNA interference (RNAi).  This technique allowed us to identify seven new genes that are involved in PCD as well as 19 genes that are involved in cell survival.  In addition, extensive characterization of a novel gene which we suspect may play a role in PCD and fatty acid metabolism is underway.  Recent evidences suggest that disruptions in fatty acid metabolism can cause cancer.  Understanding a common gene that control both PCD and fatty acid metabolism may ultimately serve as a therapeutic target, which could control cancer and also improve the health of cancer patients.

The fly eye as a tool for cell death gene discovery - cloning and characterizing echinus

Trainee: Ian Bosdet

Co-Supervisor: Sharon Gorski

Programmed cell death (PCD) is a complex biological process in which damaged or unwanted cells in the body die and are removed.  It is important during normal development as well as when cells become sick or damaged.  Defects in PCD play an important role in many human diseases such as cancer, diabetes and neurodegenerative disorders such as Huntington's disease.  In our lab we are using the fruit fly as a model to study PCD because it is known that this process occurs in a very similar way in both flies and in humans.  The fruit fly is a commonly-used experimental organism and much is already known about its biology. Many methods exist for studying aspects of its development, genetics and cellular biology.  The eye of the fruit fly is a collection of almost 800 individual units that are arrayed in a very specific manner. This array is shaped during fly development by PCD and so changes in the extent of cell death in the eye will change the pattern of eye units.  One well-known but previously uncharacterized gene that affects cell death in the eye is called echinus.  We are characterizing this gene to determine what role it plays in PCD.  It is hoped that this knowledge will further our understanding of the process of PCD, which may ultimately lead to better prevention and treatment of many common diseases.

Common regulators of apoptosis and autophagy-an analysis of known cell death genes in starvation induced autophagy

Trainee: Claire Hou

Co-Supervisor: Sharon Gorski

Marcoautophagy (autophagy) is a house-keeping mechanism for the degradation of long-lived proteins and organelles. During autophagy, cytoplasmic components are sequestered into double membrane structures called autophagosomes which then fuse with lysosomes to form autolysosomes, in which degradation occurs. The degraded products can be further recycled for macromolecular synthesis and energy production to sustain cell survival. Recent evidence indicates that regulators of apoptosis, including TRAIL, Bcl-2 and DAPK, can also regulate autophagy. This finding could have important therapeutic implications since the induction of apoptosis is a current strategy of cancer treatment modalities. Modulation of autophagy has similarly been proposed as a therapeutic strategy for cancer. Thus, it is important to understand not only the role of autophagy in cancer, but also the regulatory relationships between apoptosis and autophagy pathways. My study aims to investigate the involvement of cell death genes in starvation-induced autophagy in Dropophila model system.

Common regulators of apoptosis and autophagy-an analysis of known cell death genes in starvation induced autophagy

Trainee: Dianne Wu

MicroRNAs are known regulators of many conserved biological processes in the cell. They are generated from double-stranded RNAs via the cleavage of stem loops formed from pre-miRNA sequences, in a process similar to part of the RNAi pathway. RNA editing is a post-transcriptional event that occurs frequently in the cell, causing single-nucleotides alterations in RNA transcripts, and also operates on double stranded RNAs. The overlap between these two regulatory pathways, both of which are understood only vaguely, poses a high potential of playing a crucial role in the regulation of biological processes. RNA editing in microRNAs may alter the targets, efficiency, or activity of the effected microRNAs. We have utilized Next-Generation sequencing technology to sequence miRNA libraries as an approach to detect miRNA editing events with extremely high sensitivity. Although high-throughput sequencing data is extremely noisy, and this poses a difficult challenge for finding single-nucleotide editing events in short miRNA sequences of on average 22 nucleotides in length, we have employed several methods to recognize miRNA editing events with improved specificity and sensitivity. Examining the molecular composition of a pathway for which the exact biological mechanism is still uncertain and few assumptions can be made, our goal is to reveal new insights into the activity and composition of microRNAs in the cell and develop a novel, robust method for detection of miRNA editing events using high-throughput sequencing technology.

Follicular Lymphoma

Trainee: Alison Lee

Alison Lee is working with Tesa Severson in a project identifying single nucleotide polymorphisms (SNPs) in follicular lymphoma tumour cells. Her role is to assist in verifying SNPs throughout a variety of different methods including Illumina sequencing and capillary sequencing. Through this project, Alison hopes to identify novel mutations that play an integral role in causing follicular lymphoma.

Validation of candidate mutations in lymphoma

Trainee: Jasmine Lin

Jasmine is providing research assistance to Dr. Andrew Mungall. Projects underway include the verification of large-scale rearrangements in follicular lymphoma patients. These projects involve PCR, agarose gel electrophoresis and traditional Sanger sequencing technologies, followed by manual analysis of gel and sequence data to determine whether these mutations are derived from germline or somatic cells.

Honors and Awards

• Frontiers in Research Award, British Columbia Innovation Council, 2008
• Fellow, Royal Society of Canada, 2007
• Merck Frosst Prize, Canadian Society of Biochemistry and Molecular & Cellular Biology, 2007
• Career Investigator Award (Senior Scholar level), Michael Smith Foundation for Health Research, 2006-2011
• Distinguished Achievement Award, Faculty of Medicine, University of British Columbia, 2006-2007
• President's 40th Anniversary Award, Simon Fraser University, 2006
• Honorary Degree, Doctor of Laws,  University of Calgary, 2005
• The Best of the Best of Canada's Top 40 Under 40, The Caldwell Partners Int'l, 2005
• Terry Fox Young Investigator Award, National Cancer Institute of Canada, 2004
• Honorary Degree, Doctor of Science, Simon Fraser University, 2004
• Innovation and Achievement Award (to entire GSC staff), LifeSciences BC (formerly BC Biotech), 2004
• Career Investigator Award (Scholar level), Michael Smith Foundation for Health Research, 2001-2006
• Top 40 Under 40 Award, The Caldwell Partners Int'l, 2000
• Notable Canadian 35 and Under, The Globe and Mail, 2000
• Outstanding Alumni Award for Academic Achievement, Simon Fraser University, 1999