Dumpster diving in RNA-Seq to find the source of 1 trillion reads across adult human tissues
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1 Dumpster diving in RNA-Seq to find the source of 1 trillion reads across adult human tissues Serghei Mangul University of California, Los Angeles Eskin Lab (ZarLab)
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3 RNA-Seq RNA molecules Genome A B C D E A B C A C D E (Differential) gene expressions RNA splicing Assemble novel transcripts
4 RNA-Seq reads In-silicoseparation Human references Mapped human reads Read Origin Protocol
5 Datasets in-house RNA-Seq data (n=86) Genotype-Tissue Expression (GTEx v6) (n=8555) Sequence Read Archive (SRA) (n=2000) Brain Anterior cingulate cortex (BA24) 938/0 (n = 72) Caudate nucleus (basal ganglia) 1,967/0 (n = 100) Cerebellar hemisphere 2,557/0 (n = 89) Cerebellum Pituitary 3,454/0 (n = 103) 1,607/0 Cortex (n = 87) 2,086/0 (n = 96) Frontal cortex (BA9) Thyroid 1,588/0 (n = 92) 7,976/21 Hippocampus (n = 278) 853/0 (n = 81) Hypothalamus 879/0 (n = 81) Nucleus accumbens (basal ganglia) 1,617/0 (n = 93) Putamen (basal ganglia) 1,238/3 (n = 82) Liver 1,231/0 (n = 97) Stomach 2,938/0 (n = 170) Adrenal gland 2,693/1 (n = 126) Subcutaneous adipose 6,963/2 (n = 298) Visceral omentum 3,571/0 (n = 185) Small intestine terminal ileum 1,002/0 (n = 77) Prostate 1,045/0 (n = 87) Vagina 582/4 (n = 79) Whole blood 5,862/1 (n = 338) Tibial nerve 8,087/0 (n = 256) Tibial artery 6,736/0 (n = 285) Oesophagus muscularis 5,731/0 (n = 218) Gastroesophageal junction 2,237/0 (n = 127) Oesophagus mucosa 6,169/3 (n = 241) Left ventricle 3,855/0 (n = 190) Atrial appendage 3,284/0 (n = 159) Breast mammary tissue 3,271/0 (n = 183) Aorta 5,162/1 (n = 197) Coronary artery 1,882/0 (n = 118) Lung 5,884/2 (n = 278) Spleen 2,163/0 (n = 89) Pancreas 3,621/2 (n = 149) Transverse colon 3,723/2 (n = 169) Ovaries 1,167/0 (n = 85) Sigmoid colon 2,269/0 (n = 124) Uterus 655/0 (n = 70) Not sun-exposed skin (suprapubic) 4,499/1 (n = 196) Testis 6,796/35 (n = 157) Skeletal muscle 6,049/9 (n = 361) Sun-exposed skin (lower leg) 7,109/6 (n = 302) Fibroblasts 7,513/1 (n = 272) EBV-transformed lymphocytes 2,360/0 (n = 114) 1 trillion reads 10,641 samples at least 54 tissues
6 1 trillion RNA-Seq reads Read Origin Protocol Map to the human genome (tophat2) Mapped reads (82.9%) Unmapped reads (17.1%) Genomic profile of mapped reads Genomic profile of mapped reads (gprofile) Genomic profile of repeat elements (rprofile) CDS+ UTR LTR LINE SINE others introns others
7 1 trillion RNA-Seq reads Read Origin Protocol Genomic profile of unmapped reads 1. Quality control (FASTQC, SEQCLEAN) 2. Remap to human references (Megblast) low quality reads (7%) rrna repeat (2.4%) lost human reads (5.7%)
8 ROP protocol can find lost human reads mapped human reads reads within the threshold of tophat2 reads with additional mismatches and/or short gaps Percentage of lost human reads (%) 25% 20% 15% 10% 5% 15% 7% 3% 22% 12% 9% 7% 6% 6% 6% 6% 0% edit distance lost human reads
9 1 trillion RNA-Seq reads Read Origin Protocol Genomic profile of unmapped reads a. Quality control (FASTQC, SEQCLEAN) b. Remap to human references (Megblast) c. Map to repeat sequences (Megablast) low quality reads (7%) rrna repeat (2.4%) lost human reads (5.7%) lost repeat elements (0.2%)
10 1 trillion RNA-Seq reads Read Origin Protocol Genomic profile of unmapped reads a. Quality control (FASTQC, SEQCLEAN) b. Remap to human references (Megblast) c. Map to repeat sequences (Megablast) d. Non-co-linear (NCL) RNA profiling (TopHap-Fusion, CIRexplorer2) low quality reads (7%) rrna repeat (2.4%) lost human reads (5.7%) lost repeat elements (0.2%) NCL RNA (0.3%) Gene A Gene B RNA Junction point
11 1 trillion RNA-Seq reads Read Origin Protocol Genomic profile of unmapped reads a. Quality control (FASTQC, SEQCLEAN) b. Remap to human references (Megblast) Mapped reads c. Map to repeat sequences (Megablast) d. Non-co-linear (NCL) RNA profiling (TopHap-Fusion, CIRexplorer2) e. B and T cell receptors profiling (IgBLAST/ImReP) low quality reads (7%) rrna repeat (2.4%) lost human reads (5.7%) lost repeat elements (0.2%) NCL RNA (0.3%) immune reads (0.02%) S. Mangul,, et al. "Profiling adaptive immune repertoires across multiple human tissues by RNA Sequencing." biorxiv(2017):
12 Adaptive immune repertoires TCRA TCRD Mapped reads Unmapped reads IGK TCRG IGL V N D N J C TCRB IGH CDR1 CDR2 CDR3 mrna encoding for T and B cell receptor chains chr2 chr7 chr14 chr22
13 Diversity of IGK differentiates disease status (a) Blood Nasal-Controls Nasal-Asthma (b) p=1.0x10-3 J genes J genes J genes 100% 0% Percentage of samples V genes V genes V genes (c) p=3.7x p=2.5x 10-9
14 ROP(ImReP) assembles 3.6 million CDR3s 1200 DIVERSITY OF IMMUNOGLOBULIN REPETORE, CPM Mucosal, exocrine and endocrine organs Spleen Small Intestine - Terminal Ileum Whole Blood Artery - Coronary Artery - Aorta Artery - Tibial Minor Salivary Gland Colon - Transverse Stomach Colon - Sigmoid Lung Breast - Mammary Tissue Esophagus - Mucosa Thyroid Kidney - Cortex Bladder Fallopian Tube Vagina Cervix - Endocervix Liver Cervix - Ectocervix Prostate Uterus Ovary Pancreas Pituitary Skin - Not Sun Exposed Skin - Sun Exposed (Lower leg) Adrenal Gland Testis Cells - EBV-transformed Cells - Transformed fibroblasts Adipose - Visceral (Omentum) Esophagus - Adipose - Subcutaneous Heart - Atrial Appendage Esophagus - Muscularis Heart - Left Ventricle Muscle - Skeletal Nerve - Tibial Brain (n=13) IGL IGK IGH GTEX TISSUES (N=53) CPM : clonotypes per one million RNA-Seq reads
15 Individual- and tissue-specific Ig clonotypes IGH IGK IGL Number of clonotypes IGH IGK IGL b IGHV3-53 IGKV3-20 IGLV3-1 CARGHYGMDVW CQQYGSSPRTF CQAWDSSTVVF IGHJ6 IGKJ2 IGLJ Number of individuals sharing the clonotype Tissue specific Shared across tissues Individual specific (private) 3.1 x x 10 6 Shared across individuals (public) 0.4 x x 10 6
16 ROP is able to identify samples with high activity of lymphocytes Disease severity Histological images LATE STAGE HASHIMOTOS HASHIMOTOS EARLY HASHIMOTOS 496 PATCHY HASHIMOTOS FOCAL HASHIMOTOS Number of IGH clonotypes Number of IGH clonotypes male female sex_s Gynecomastia
17 Genomic profile of unmapped reads RNA-Seq a. Quality control (FASTQC, SEQCLEAN) b. Remap to human references (Megblast) c. Map to repeat sequences (Megablast) d. Non-co-linear (NCL) RNA profiling (ncsplice) e. B and T lymphocytes profiling (ImReP) f. Microbiome profiling (Megablast) 1 trillion RNA-Seq reads low quality reads (7%) rrna repeat (2.4%) lost human reads (5.7%) lost repeat elements (0.2%) NCL RNA (0.3%) V(D)J recombinations (0.02%) microbial reads (1.4%) unaccounted reads (0.1%) template jumping Read Origin Protocol
18 Human microbiome of GTEx tissues a. a. Superkindom Epstein-Barr Virus (EBV) Bacteria b. Proteobacteria Actinobacteria b. Phyla 67% 24% 8% c. Firmicutes Betaproteobacteria Gammaproteobacteria Actinobacteria Bacilli c. Class 53% d. Order 53% 16% 11% 5% 24% 13% 11% d. Burkholderiales Pseudomonadales Enterobacteriales Actinomycetales Bifidobacteriales Lactobacillales Positive Control : Cells - EBV-transformed lymphocytes samples r=-0.60, p-value =2.0 x10-9 Alpha diversity, IGK Obtained by MetaPhlAn2 Viral load, %
19 The effect of RNA-Seq aligners on the fraction of reads accounted by ROP Number of mapped reads (%) ROP variable GSNAP HISAT2 Number of categorized reads (%) immune reads microbial reads repeat reads transcriptomic reads Read type Novoalign STAR immune reads microbiome reads repeat reads transcriptomic reads Read type TopHat2 STAR.tuned Novoalign.tuned HISAT2.tuned
20 Don t let your unmapped reads go to waste Human references Mapped human reads
21 Summary 1 trillion reads 82.9% ROP 7.0% 2.4% 5.7% 0.1% 0.2% 0.3% 0.02% 1.4% 0.1%
22 Acknowledgment Harry Taegyun Yang Maura Rossetti Roberto Spreafico Roel A. Ophoff Eleazar Eskin Igor Mandric Alex Zelikovsky Noah Zaitlen Mark Ansel Nicolas Strauli Stephanie Christenson Ryan D. Hernandez Prescott G. Woodruff Kevin Hsieh Linus Chen Jeremy Rotman Sagiv Shifman GTEx Consortium David Koslicki Franziska Gruhl
23 ROP is an easy to use package with no dependencies! ROP is available at
24 Microbiome diversity is significantly different across tissues 3 p<10-16 Alpha diversity Adrenal gland Heart LCL Lung Hypophysis Thyroid Negative Controls Obtained by MetaPhlAn2
25 Soft clipped reads across RNA-Seq aligners 1800 Number of mapped reads Aligner GSNAP HISAT2 Novoalign STAR TopHap Number of soft clipped reads
Comprehensive analysis of RNA-sequencing to find the source of every last read across 544 individuals from 53 tissues
Comprehensive analysis of RNA-sequencing to find the source of every last read across 544 individuals from 53 tissues Serghei Mangul Eskin Lab (ZarLab) University of California, Los Angeles sergheimangul.wordpress.com
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