Transcript Document
Introduction to the Tsinghua University ENCODE Journal Club Monica C. Sleumer (苏漠) 2012-09-24 Tsinghua ENCODE Journal Club Objectives • Read and discuss all 31 ENCODE papers • Discuss the 13 “Threads” in the ENCODE explorer • Discuss the overall meaning of the ENCODE project – Media reactions • Understand how to apply ENCODE findings to our own research • Generate a long-term repository for our findings on our journal club website: bioinfo.au.tsinghua.edu.cn/encode/ Human Genome • • • • • 3,101,804,739 base pairs 22 chromosomes plus X and Y 21,224 protein-coding genes 15,952 ncRNA genes 3–8% of bases are under selection – From comparative genomic studies • Question: What is the genome doing? ENCODE Project Objectives • Find all functional elements – – – – Bound by specific proteins Transcribed Histone modifications DNA methylation • Use this information to annotate functional regions – – – – – – – Genes (coding and non-coding) Promoters Enhancers Specific transcription factor binding sites Silencers Insulators Chromatin states • Cross-reference data from other studies – Comparative genomics – 1000 Genomes Project – Genome-wide association studies (GWAS) Different combination in each cell type ENCODE projects • • • • ENCODE pilot project: 1% of the genome 2003-2007 modENCODE: Drosophila and C. elegans Mouse ENCODE in progress? ENCODE main project 2007-2012 – – – – – 1649 dataset-generating experiments 147 cell types 235 antibodies and assay protocols 450 authors 32 institutes • 31 publications 2012-09-06 – – – – 6 in Nature – all discussed on 2012-09-19 18 in Genome Research 6 in Genome Biology – one of these discussed today 1 in BMC Genetics www.nature.com/encode/category/research-papers Materials • 147 types of human cell lines, 3 priority levels • Tier 1 cell lines: top priority for all experiments Name Description Lineage Tissue Karyotype GM12878 B-lymphocyte, lymphoblastoid, Epstein-Barr Virus, mesoderm 1000 Genomes Project blood normal H1-hESC embryonic stem cells inner cell mass embryonic stem cell normal K562 leukemia, 53-year-old female with chronic myelogenous leukemia mesoderm blood cancer • Tier 2 cell lines to be done after Tier 1 (next slide) • Tier 3: any other cell lines Tier 2 Cell Lines Name Description Lineage lung carcinoma epithelium, 58-yearendoderm old caucasian male donor B cells: RO01778 and CD20+ mesoderm RO01794 CD20+_RO01778 B cells, caucasian mesoderm CD20+_RO01794 B cells, African American mesoderm neurons derived from H1 H1-neurons ectoderm embryonic stem cells HeLa-S3 cervical carcinoma ectoderm HepG2 hepatocellular carcinoma endoderm HUVEC umbilical vein endothelial cells mesoderm IMR90 fetal lung fibroblasts endoderm skeletal myoblasts from pectoralis LHCN-M2 mesoderm major muscle, 41 year old caucasian MCF-7 mammary gland, adenocarcinoma ectoderm MonocytesMonocytes-CD14+, leukapheresis mesoderm CD14+ from RO 01746 and RO 01826 SK-N-SH neuroblastoma, 4 year old ectoderm A549 Tissue Karyotype epithelium cancer blood normal blood blood normal normal neurons normal cervix liver blood vessel lung skeletal muscle myoblast breast cancer cancer normal normal monocytes normal brain cancer http://encodeproject.org/ENCODE/cellTypes.html cancer Methods RNA-Seq Different fractions of RNA -> sequencing CAGE 5’ Capped RNA sequencing RNA-PET Sequencing 5’ Cap plus poly-A tail ChIP-seq Chromatin immunoprecipitation of a DNA binding protein -> sequencing DNase-seq Cut exposed DNA with DNase I -> sequencing FAIRE-seq Nucleosome-depleted DNA -> sequencing RRBS Bisulphite treatment: unmethylated C->U -> sequencing 3C,5C, ChIA-PET Chromatin interactions -> sequencing Wu Dingming 2012-09-19 Ma Xiaopeng 2012-09-19 Guo Weilong He Chao 2012-09-19 Li Yanjian 2012-09-19 • All methods (DNA or RNA sequencing) can be traced back to a genomic location • Findings vary between cell types Primary Findings • 80.4% of the human genome is doing at least one of the following: – Bound by a transcription factor – Transcribed – Modified histone • 99% is within 1.7 kb of at least one of the biochemical events • 95% within 8 kb of a DNA–protein interaction or DNase I footprint • 7 chromatin states: – 399,124 enhancer-like regions – 70,292 promoter-like regions • Correlation between transcription, chromatin marks, and TF binding • Functional regions contain lots of SNPs – Disease-associated SNPs in non-coding regions tend to be in functional elements Applications • Visible as genome tracks in UCSC • Gene or pathway of interest • Mutation from – Cancer sequencing – Genome-wide association studies – Find out what that part of the genome is doing • Compare with your cancer data (RNA-seq) • Comparative genome analysis Online Resources • Interactive app on Nature ENCODE main page www.nature.com/encode/ • Journal club website: bioinfo.au.tsinghua.edu.cn/encode/ bioinfo.au.tsinghua.edu.cn/encode/ Next ENCODE Journal Club Meeting Suggested meeting day: Thursday (周四) 2012-10-11 LIANG Zhengyu? One more volunteer speaker needed