Day 1 :
University of South Alabama, USA
Time : 09:30-09:55
Glen M Borchert has completed his PhD in Genetics from University of Iowa in the year 2006. He did his first postdoctorate in Structural Biology from University of California in the year 2008 and the second one in Immunology from Illinois State University in the year 2012. After which he joined as Assistant Professor in University of South Alabama and currently working as Assistant Professor, Pharmacology in USA College of Medicine. He has been honored by NIH with a Research award to study hypoxia induced mutation. Also, National Science Foundation (NSF) gave him the CAREER award of $533,000 to research miRNA targeting.
Breast cancer is the leading cause of female cancer mortality. Strikingly, the two most widely utilized breast cancer cell lines, primary MCF-7 and metastatic MDA-MB-231 breast cancer cells, have been used in over half of all the breast cancer studies in the primary literature. Since these cell lines differ in several well established ways in terms of morphology, invasiveness and physiological responses, we recently performed a RNA-seq analysis examining both their total RNA and small RNA populations in order to identify novel gene candidates responsible for their phenotypic differences. Having successfully generated over 150 million transcript sequencing reads from these cells, we now have extensive coverage of the mRNA and small RNA transcriptomes for each of these lines allowing us to identify specific regulations responsible for characteristic differences between them. To our surprise, distinct examinations of this data have generated three major new lines of investigation for our research. While we find little to no change in the expressions of over 2,500 human microRNAs between these cell lines, we identify 25 miRNAs significantly overexpressed in MDA-MB-231 cells as well as 19 miRNAs overexpressed in MCF-7s. Strongly corroborating the importance of these miRNAs in breast cancer, 39 of these 45 miRNAs have been previously reported as being directly involved with breast cancer pathology and/or the modulation of breast cancer cellular response to chemotherapeutic agents. As such, we are now actively engaged in determining cellular functions for the six new miRNAs we find differentially expressed between MCF-7 and MDA-MB-231 cells likely playing uncharacterized roles in breast cancer pathology. Further computational analyses of our RNA-Seq data identified over 250,000 A-to-I edit sites primarily located in mRNA 3’ UTRs. When these locations were screened against the list of currently annotated miRNAs we discovered that these A-to-I editing events caused a subset (~5%) of human miRNAs to have significantly altered mRNA complementarities leading us to propose that modulating the targets of miRNAs via mRNA editing plays a direct role in the pathology of many carcinomas. And , in a more recent analysis of our RNA-Seq data we compared the snoRNA derived RNA (sdRNA) expression profiles of MCF-7 and MBA-MD-231 cell lines. Excitingly, we find 13 snoRNAs significantly overexpressed (≥10 fold) in MBA-MD-231 cells as compared to MCF-7s. To our surprise, we found microRNA-like fragments derived from all 13 snoRNAs were expressed in MBA-MD-231s. Moreover, additional experimentation finds small RNA reads from 10 of 13 small RNA-generating snoRNAs are complexed with Ago following immunoprecipitation suggesting their active involvement in RNAi and potential relevance to breast cancer pathology. In summary, we find RNA-Seq provides a comprehensive, quantitative, and unbiased view of RNA sequences allowing for the ready discovery of novel observations unobtainable with previous technologies and that the data generated by a single RNA-Seq can lead to numerous new lines of investigation.
Cold Spring Harbor Laboratory, USA
Time : 09:55-10:20
W. Richard McCombie, Ph.D., is a Professor at Cold Spring Harbor Laboratory and the Watson School of Biological Sciences. He is the Director of the Stanley Institute of Cognitive Genomics at Cold Spring Harbor Laboratory in New York and Program Leader for the Cancer Genetics at CSHL. He received his B.A. in Biology from Wabash College and his Ph.D. in Cellular and Molecular Biology in the Health Sciences from the University of Michigan. As a Senior Staff Fellow in Craig Venter’s section at the National Institutes of Health, he was a leader of one of the first groups to carry out large-scale automated sequencing of genomic DNA and helped to organize the first large-scale EST (expressed sequence tag) sequencing projects. He has been on the faculty at CSHL since 1992 and was named a professor in 2001. Professor McCombie’s lab has contributed to the efforts to sequence the genomes of several organisms, including the flowering plant Arabidopsis thaliana, the fission yeast S. pombe, rice, mouse and human. The McCombie lab has also focused considerable effort on the development of methods and strategies for genome analysis. These have included development of exome sequencing methyl filtration in plants and as well as contributing to the first single cell analysis of cancer. An author of many published papers in the field of genomics, Professor McCombie has developed and taught courses on applications of genome sequencing and on genomics and proteomics at the Watson School of Biological Sciences at CSHL. He has also organized an intensive DNA sequencing course at CSHL. Professor McCombie and colleagues are currently developing optimized ways to carry out de novo assemblies of plant genomes using next generation sequencing approaches and newer, long read base sequencing instruments. They are also using these approaches to determine the salient variation contributing to human disease.
The development of short read sequencing on Illumina platforms has created an explosion of information about genome structure as well as transcriptome variability. However, the short reads have led to limitations in understanding of both the genomes and transcriptomes. In general terms the short reads require mapping back to a reference genome rather than doing an assembly, de novo, from the raw data. This is inherently problematic since structural rearrangements which are very important in instances like cancer may be lost since they are not represented in the reference. In addition, there are regions of the genome which do not map well and are difficult to interpret their structure based on the short reads. Likewise, while counting reads from transcriptome data has provided powerful statistical analyses of the variability of gene expression, the short reads give a limited view of alternate splice isoforms. Very long reads (in excess of 10kb average) as are now possible on the Pacific Biosciences platform and are shedding new light on the possible impact of these limitations. We have sequenced the genome of a breast cancer cell line SKBR3 as well as carried out analysis of transcriptome data from the same cell line using very long reads. This has shown a very different view of the genome than we see with short reads including a number of structural rearrangements, insertions and deletions that appear to be missed in the short read sequence and a significant number of gene fusions that are missed in the transcriptome analyses. These discrepancies and our further studies of them and how they might impact our understanding of the biology of this cancer cell line will be elaborated.