RNA-Seq data analysis Xuhua Xia University of Ottawa

RNA-Seq Gene2Gene1 Gene3 Genome Transcriptome FASTQ GATTTGGGGTTCAAAGCA... + GATTTGGGGTTCAAAGCA... + !''*((((***+))%% RNA-Seq SRA files for Data storage, transmission and analysis

Next-Generation sequencing FASTQ NATTTGGGGTTCAAAGCA... + GATTTGGGGTTCAAAGCA... + %''*((((***+))%% De novo genome assembly Sequence reads matching/aligning against a known genome Key research objectives: Differential gene expression Ribosomal profiling Alternative splicing Gene discovery Signal at TSS and TTS …… Submission to one of the three data centers (NCBI, DDBJ, EBI): SRA (sequence read archive) compressed files Download by researchers Submission Storage, transmission and analysis Quality assessment Phred quality score Q=-10log 10 p, where p is base-calling error probability. 1.Global quality assessment 2.Read-specific quality assessment 3.Site-specific quality assessment

Quality assessment: Nucleotide SRR : Single, ReadLen = 50SRR892245: Paired, ReadLen = 100SRR : Paired, ReadLen = 250

Read-based quality SRR : Paired, excluding N-containing read SRR : Single, ReadLen = 50

Site-specific quality by nucleotide Fully resolved paired readsPaired reads containing unresolved nucleotides SRR Read 1 Read 2 Read 1 Read 2

Gene expression Gene2Gene1 Gene3 Genome Transcriptome Count N 1 = 6 N 2 = 29 N 3 = 4 N TMR = (TMR: total mapped reads); L 1 = 500 nt, L 2 = 3000 nt, L 3 = 400 nt GE: FPKM 1 = (1000*N 1 /L 1 )*( /N TMR ) FPKM 2 = (1000*29/3000)/2.23 FPKM 3 = (1000*4/400)/2.23 = 5.38 = 4.33 = 4.48 FPKM: Fragments Per Kilobase of exon per Million reads: "per kilobase": fair comparison among genes; "per million reads": fair comparison among samples BLAST, FASTA, etc. (more details later)

Paralogue B Identical segment Different but with clear homology Homology lost in evolution Paralogue A N A.H = 6 N B.H = 3 N A.U = 4 N B.U = 3 N I = 29 P A = (N A.H + N A.U )/(N A.H + N B.H + N A.U + N B.U ) = (6+4)/( ) = N A = N A.H + N A.U + N I *P A = *0.625 = N B = N B.H + N B.U + N I *(1-P A ) = *0.375 = Scale N A and N B to FPKM Subscripts: H - different but homologous; I - identical segment; U - unique/divergent segment Gene expression with duplicated genes

Paralogue B Identical segment Different but with clear homology Homology lost in evolution Paralogue A N A.H = 6 N B.H = 3 N A.U = 4 N B.U = 3 N I = 29 Two alternatives: 1. P A = N A.H /(N A.H + N B.H ) = 6/(6+3) = n A.H = 6/L H ; n B.H = 3/L H ; n A.U = 4/L A.U ; n B.U = 3/L B.U P A = (n A.H + n A.U )/(n A.H + n B.H + n A.U + n B.U ) N A = N A.H + N A.U + N I *P A N B = N B.H + N B.U + N I *(1-P A ) Duplicated genes of different lengths L B.U L A.U

Paralogue B Identical segment Different but with clear homology Homology lost in evolution Paralogue A N A.H = 6 N B.H = 2 N C.H = 1 N A.U = 4 N B.U = 2 N C.U = 1 N I = 29 P A = (N A.H + N A.U )/(N A.H + N B.H + N A.U + N B.U + N B.H + N A.U + N B.U ) = (6+4)/( ) = N A = N A.H + N A.U + N I *P A = *0.625 = N B = N B.H + N B.U + N I *P B N C = N C.H + N C.U + N I *P C Subscripts: H - different but homologous; I - identical segment; U - unique/divergent segment Gene expression with duplicated genes Paralogue C

Multiple paralogues Slide 11 PG1309 PG2204 PG3101 GeneN H N I N U PG3 PG2 PG N 3 = *P 3 N 2 = *204/( )+600*P 2 N 1 = *309/( )+600*P 1 P 3 = ( )/( )  P 2 = (1-P 3 )*204/( ) = P 1 = (1-P 3 )*309/( ) = N 3 = N 2 = N 1 = More details later on tree reconstruction

Ribosomal density Xuhua Xia Slide 12 Mean density adjusted for mRNA length. The confounding effect of elongation efficiency Xia et al Genetics

Poly(A) length & protein synthesis Xuhua Xia Slide 13 Xia et al Genetics

Transcription: TSS and TTS AUG… …UAA TSS 1 TSS 2 TTS 1 TTS 2 Exp. 1 Exp. 2

Alternative splicing E3E3 E1E1 E2E2 I1I1 I2I2 5'SS 3'SS E3E3 E1E1 E2E2 E3E3 E1E1 Alternative splicing Cell type 1 Cell type 2

New approaches in data analysis RNA-Seq data files are too large: –Among the 4717 RNA-Seq studies on human, available at NCBI on Jun. 10, 2015, 141 studies each contributed more than 1TB of nucleotide bases. –Even NCBI has found it difficult to keep pace with the explosive growth of RNA-Seq data. The RNA-Seq data do not need to be so huge. – SRR sra (E. coli K12) contains 6,503,557 sequences of 50 nt each, but sequences are all identical, all from sites in E. coli 23S rRNA genes. There is no information lost if all these identical sequences is listed by a single sequence with a sequence ID such as SeqID_ Xuhua Xia Slide 16

Most frequent 50-mers in SRR sra GeneN copy GeneN copy LSU rRNA195310LSU rRNA14193 LSU rRNA86308hisR (2) S rRNA73440hisR (2) LSU rRNA58400LSU rRNA13615 SSU rRNA47323LSU rRNA13012 LSU rRNA456955S rRNA13001 LSU rRNA36258LSU rRNA S rRNA33674LSU rRNA12695 SSU rRNA30417LSU rRNA12523 LSU rRNA29508SSU rRNA S rRNA28187LSU rRNA11298 LSU rRNA24982glnX_V (1) SSU rRNA232865S rRNA10968 LSU rRNA199915S rRNA10890 SSU rRNA192685S rRNA10750 glnX_V (1) 18652b3555|b3556 (3) LSU rRNA18381LSU rRNA10362 hisR (2) 18354LSU rRNA10164 LSU rRNA18300LSU rRNA10000 LSU rRNA17113trpT9955 glnX_V (1) 16902rpsE (4) 9877 LSU rRNA16796LSU rRNA9090 LSU rRNA14642rplV (4) 9071

Next-Generation sequencing FASTQ NATTTGGGGTTCAAAGCA... + GATTTGGGGTTCAAAGCA... + %''*((((***+))%% De novo genome assembly Sequence reads matching/aligning against a known genome Key research objectives: Differential gene expression Ribosomal profiling Alternative splicing Gene discovery Signal at TSS and TTS …… Submission to one of the tree data centers (NCBI, DDBJ, EBI): SRA (sequence read archive) compressed files FASTAQ+ file: >SeqGroup1_3 GATTTGGGGTTCA >SeqGroup2_391 GATTTGGGGTTCAAAGCA >SeqGroup3_92 GATTTGGGGTTCAAAGCA >SeqGroup4_512 GATTTGGGGTTCAAAGCA Download by researchers Submission Download Storage, transmission and analysis

Formatted BLAST output Xuhua Xia Slide 19 b0001|190_255,SeqGr49062_16,100.00,49,0,0,18,66,1,49,3e-019,91.6 b0001|190_255,SeqGr382517_1,100.00,48,0,0,19,66,1,48,1e-018,89.8 b0001|190_255,SeqGr536414_1,100.00,46,0,0,21,66,1,46,2e-017,86.1 b0001|190_255,SeqGr181138_10,100.00,45,0,0,22,66,1,45,5e-017,84.2 b0001|190_255,SeqGr138539_1,100.00,44,0,0,23,66,1,44,2e-016,82.4 b0001|190_255,SeqGr297866_1,100.00,42,0,0,25,66,1,42,3e-015,78.7 b0002|337_2799,SeqGr935243_1,100.00,50,0,0,185,234,1,50,4e-018,93.5 b0002|337_2799,SeqGr925087_1,100.00,50,0,0,1398,1447,1,50,4e-018,93.5 b0002|337_2799,SeqGr922536_1,100.00,50,0,0,2050,2099,1,50,4e-018,93.5 b0002|337_2799,SeqGr918509_1,100.00,50,0,0,201,250,1,50,4e-018,93.5 ……

Gene expression output Xuhua Xia Slide 20 GeneSeqLenCountCount/KbFPKM thrL|190_ thrA|337_ thrB|2801_ thrC|3734_ yaaX|5234_ yaaA|C5683_ yaaJ|C6529_ talB|8238_ mog|9306_ yaaH|C9928_ yaaW|C10643_ yaaI|C11382_ dnaK|12163_ dnaJ|14168_ insL1|15445_ mokC|C16751_ hokC|C16751_ nhaA|17489_ ……………