Abstracts from the Human Genome Meeting 2018 Yokohama, Japan, 12-15 March 2018
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Human Genomics 2018, 12(Suppl 1):9 https://doi.org/10.1186/s40246-018-0138-6 MEETINGABSTRACTS Open Access Abstracts from the Human Genome Meeting 2018 Yokohama, Japan, 12-15 March 2018 Published: 09 March 2018 A1 is an intermediate between the genomic DNA and proteins, in TCGA whole-exome sequencing data reveals mutational principle, RNA sequencing (RNA-seq) should be able to reveal the in- parameters in distinguishing potential cancer drivers formation about the genome (e.g., mutations, including single nu- Daniel Wai-Hung Ho1,2 and Irene Oi-Lin Ng1,2 cleotide polymorphism (SNPs)) and the final products (i.e., proteins). 1Department of Pathology, The University of Hong Kong, Hong Kong, Although RNA should serve as exact copies of genomic DNA, in real- Hong Kong; 2State Key Laboratory for Liver Research, The University of ity, RNA can be modified by a variety of enzymes, which results in Hong Kong, Hong Kong, Hong Kong the addition of 5′-cap and poly A tails as well as various forms of Human Genomics 2018, 12(Suppl 1):A1 RNA modifications (e.g., RNA editing). To study these multiple pro- cesses simultaneously, we created a computational pipeline to Background maximize the extraction of information from RNA -seq data. In this With huge amount of genome-wide mutational data generated by pipeline, not only do we measure expression levels of RNA (i.e., cancer genomic sequencing studies, distinguishing cancer drivers genes and isoforms), we further detect A-to-I RNA editing sites and from the vast majority of passengers is important. Existing cancer clusters of editing or “editing islands” using our previously intro- driver prediction methods capture specific mutational aspects in dis- duced tool RNAEditor (John, Brief Bioinform, 2016; Stellos, Nat Med, criminating potential cancer drivers. We explore the possibility of al- 2016)) as well as circular RNAs (circRNAs) (Boeckel, Circ Res, 2015; terative way in doing the task. Militello, Brief Bioinform, 2017), which arise from the backsplicing of Methods exons and/or introns. Our pipeline is implemented in the Snakemake We noted mutational parameters (functional mutation ratio, mutation as workflow management system that confers numerous benefits, frequency and sample mutation recurrence) vary differently among such as easy parallelization on HPC-clusters and cloud computing en- mutant genes of different sizes. This led us to develop our novel al- vironments, advanced error detection, and automatically deleting gorithm (Mutant Gene Ranker - MuGeR), incorporating the compari- intermediate files. Through the detailed analysis for A-to-I RNA edit- son of multiple mutational parameters of target gene against the ing events that result in adenosine (A) to inosine (I) conversion in corresponding background derived from a specific subset of genes RNA but not in genomic DNA, which can be identified as guanine (G) using a sliding window approach, to estimate the likelihood of target as replacement of A in RNA-seq sequencing reads, it is possible to genes for being potential cancer drivers. We applied our MuGeR al- correctly infer the actual mutations in the human genome, which dif- gorithm on the The Cancer Genome Atlas (TCGA) datasets. fers from the reference genome used as template for RNA-seq data Results analysis. These mutations should represent the individuality of Empirical data on the TCGA datasets and comparison with the humans. In this meeting, we would like to share our computational prioritization results of 4 other existing tools (MuSiC, MuSig, TUSON pipeline for the further analysis of RNA-seq data and integrating the explorer and DOTS-Finder) suggested satisfactory performance of our additional extracted information for use in personalized medicine, es- MuGeR algorithm. More importantly, we demonstrated the existence pecially related to cardiovascular disease (“Cardiovascular Personal- of specific pattern for mutational parameters across cancers. ized and Precision Medicine”). Conclusions Empirical data verified the usefulness of our MuGeR algorithm in A3 identifying potential cancer drivers. Moreover, our in-depth appraisal Versatile instrument for single cell analysis and complex tissue of TCGA liver hepatocellular carcinoma datasets further highlighted microdissection the frequent mutational dysregulation of ubiquitin-related proteaso- Stanislav L. Karsten, Zhongcai Ma, Lili C. Kudo mal degradation in driving hepatocarcinogenesis. NeuroInDx, Inc., 20725 S Western Ave, Ste 100, Torrance, CA 90501, USA Human Genomics 2018, 12(Suppl 1):A3 A2 Maximizing the information extraction of RNA-seq data for Collection of specific cells or subanatomical regions from complex achieving personalized medicine heterogeneous tissues is a prerequisite step for understanding com- Tyler Weirick and Shizuka Uchida plex molecular mechanisms underlying health and disease. Single Cardiovascular Innovation Institute, University of Louisville, Louisville, KY cell analysis (SCA) has become an essential part of cutting edge bio- 40202, United States medical research. There are commercially available single cell collec- Human Genomics 2018, 12(Suppl 1):A2 tion and tissue microdissection technologies including laser based systems, and cell sorting instruments. However, these platforms are Through the efforts of large-scale sequencing projects around the typically sample specific, complex and expensive making integration world (e.g., ENCODE, FANTOM), we have learned that 90% of human within standard lab workflows difficult. Moreover, part of SCA is the genome is transcribed as RNA, yet only a minor portion of these investigation of single cell adhesion properties that is a key in sub- RNAs encode for proteins. Similarly, the processes affecting RNA and strate mediated cell behavior essential for understanding cellular functions of RNA have become increasingly complex. Given that RNA properties in health and disease. There are approaches for single cell © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Human Genomics 2018, 12(Suppl 1):9 Page 2 of 53 adhesion measurements including atomic force microscopy, optical microdeletions are enriched in high GC and simple repeats regions. tweezers, and micropipette/capillary aspiration. Unfortunately, none Interestingly, as opposed to duplications, the microdeletions muta- of the existing instruments provide concurrent single cell acquisition tion rates are higher in late replication regions. Next, we show that and adhesion force measurement prior to its preparation for the the smaller microdeletions (<300bp) prefer microhomology sizes be- downstream analysis (e.g. NGS). Based on our vacuum impulse based tween 2 and 3 bp (>30%) around the breakpoint, suggesting nonho- cell and tissue acquisition technology (UP8797644) we have devel- mologous end joining (NHEJ); whereas the larger microdeletions oped a universal platform for single cell acquisition and analysis. De- prefer microhomology length of 4bp (21%), followed by 1bp (19%). veloped system collects individual cells from any adherent cultures Finally, the GC richness and microhomologies underlying the junc- grown in standard cell culture dishes in as small as 15 nl volume, tions of the microdeletions are consistent with the possibility that compatible with downstream SCA and NGS. The system may be used the microdeletions were generated by mechanisms that also produce with a wide range of inverted microscopes, and the cells of interest extrachromosomal circles of DNA called microDNAs. In summary, the can be identified based on morphology, location or labeling, includ- curated set of high quality microdeletions will enhance studies in un- ing fluorescence. Here, individual cells were collected from human derstanding their mutational mechanism, as well as to understand neuroblastoma SH-SY5Y, CHO, 3T3 and neural progenitor cell cul- their disease association and functional impact. tures. Collected single cells were dispensed immediately into individ- ual wells for clonal expansion. Clonal expansion for 7 days of these A5 single cells revealed minimal effect on cellular viability (up to 99% when compared to dilution controls). Moreover, trypan blue assay Genome-wide association study for resistant hypertension in a Japanese population demonstrated survival rates similar with the re-cultivation studies. In 1,2 1 3 3 addition, we extended the use of our technology for single cell adhe- Keiko Yamazaki , Yasuo Takahashi , Yukako Katsura , Yayoi Nishida , Yoichiro Kamatani4,5, Michiaki Kubo6, Satoshi Asai1,3 sion strength measurement. Adhesion strength for individual cells 1 from several cell cultures was measured using a sensor incorporated Division of Genomic Epidemiology and Clinical Trials, Clinical Trials in the collection assembly. Measurement of cell adhesion force was Research Center, Nihon University School of Medicine, Tokyo, Japan; 2Laboratory for Genotyping Development, Center for Integrative Medical performed based on the capillary aspiration techniques reported