Taller práctico sobre uso, manejo y gestión de recursos genómicos de abril de 2013 Assembling long-read Transcriptomics

Transcription

1 Taller práctico sobre uso, manejo y gestión de recursos genómicos de abril de 2013 Assembling long-read Transcriptomics Rocío Bautista

2 Outline Introduction How assembly Tools assembling long-read Assembly exercise Hypophysis sample (RL5-454 reads)

3 Reference-based assembly Next-generation transcriptome assembly Jeffrey A. Martin & Zhong Wang Nature Reviews Genetics 12, (October 2011)

4 De novo assembly Next-generation transcriptome assembly Jeffrey A. Martin & Zhong Wang Nature Reviews Genetics 12, (October 2011)

5 Reference-based vs De novo Approach Advantages Disadvantages Referencebased de novo alignment tolerates seq errors repeats are detected through alignment no reference needed detection of non-collinear transcripts (trans-splicing) reference seq. needed assumes transcripts are collinear with the genome. lowly expressed genes indistinguishible from seq. errors. missassemblies due to repeats.

6 Read library type

7 Sequence file type.fna file (sequence fasta format).fastq file (sequence + quality format).qual file (quality fasta format)

8 What is assembly? Merge the reads into long contigs (ideally a full transcripts) by finding the best sequence overlaps between reads Reads Contig 1 (full-length) Contig 2 (full-length)

9 Assembly approach Overlap-consensus Sanger reads (long reads) most effective with fewer reads more computationally intensive de Bruijn graph short reads Able to work with million reads Reduce the computational intensity

10 Assembler type Assembler reads graphs preclusters TiCL full OLC yes CLOBB full OLC yes MIRA full OLC no CAP3 full OLC no Newbler fragment OLC no Velvet fragment de Bruijn no ABySS fragment de Bruijn no SOAPdenovo fragment de Bruijn no EULER-SR fragment de Bruijn no

11 De novo assembly optimization of 454 reads

12 De novo assembly

13 Optimality criteria for De Novo transciptome Assembly What Optimality criteria Nº reads used more reads used = better Nº of contigs N50 of contigs Mapping of reads Comparison to a reference conserved proetome set number of contigs should be LESS than the number of transcripts expect in the genome this should approach the expected median length for full length transcripts in the speices studied the best assembler will have the minimum number of naked bases when reads are mapped back. the better assembler will produce contigs that match to a greater proportion of the reference conserved proteome.

14 Validation of genomes assemblies Assemblathons or GAGE with the intention of identifying the best assembler and their features.

15 Validation of transcriptomes assemblies??

16 FullLenghterNext Classification among complete or incomplete transcripts Construction of an fixed ORF Discovery of putative species-specific unigenes Extraction of putative non-coding RNAs Discarding artefactual unigenes

17 How FullLengtherNext works Up to 3 databases User DB - Optional database provided by user SwisProt DB - SwissProt database split by divisions fungi, human, invertebrates, mammals, plants, rodents, vertebrates - Filtered for complete genes Databases TrEMBL DB - TrEMBL (non redundant with SwissProt) - Filtered for complete genes 17 TestCode - Detection for new genes

18 Validation of transcriptomics assemblies 454 data MIRA3 Euler-SR CAP3 Euler-SR MIRA3 CAP3 1 #seqs % #seqs % #seqs % Unigenes % % % Unigenes > 500 bp % % % Longest unigene (bp) With ortologue % % % Different ortologue IDs % % % Complete transcripts % % % Different complete transcripts % % % Misassembled % % % Without ortologue % % % Coding % % % Putative coding % % % Putative ncrna % % % Unknown % % % Mapped reads % % % 1 Due to its overlap-layout-consensus design for Sanger sequencing, CAP3 cannot be used with the huge amount of reads provided by any NGS method. It has been therefore used for reconciliation of the assemblies obtained from Euler-SR and MIRA3. 2 Percents for subclassifications of this category were calculated using this line as 100% reference. 3 Mapping was performed with Bowtie 2.0 using the default parameters (Langmead et al., 2009) and the useful reads as input.

19 Uses of Full-LengtherNext Classification among complete or incomplete transcripts Construction of a fixed ORF Discovery of putative species-specific unigenes Extraction of putative non-coding RNAs Selection of the best de novo transcriptome assembly Discarding artefactual unigenes

20 FullLengtherNext

21 FullLengtherNext web Provide a job name Provide a sequences file in fasta format Select a taxon group from the menu

22 Let s practice with our remote desktop machine

23 Connecting to picasso.scbi.uma.es

24 You are logged in

25 Some commands you should remember sbatch xxxxx.sh Parallel run of software by means of shell commands Help: «sbatch -h» squeue Queue status module load xxxxx Initialise software

26 Transcriptomics workflow NGS Reads SeqTrimNext Pre-processing Pre-processing data Assembly Do not mix all reads (454, Debris MIRA3 EULER-SR Illumina, Solid..) Assemble them separately Bowtie2 Verification Unmapped with different aproach Full-LengtherNext Non- Coding Full-LengtherNext Non- Coding OLC Coding Reads Mapped Coding Contig Merge De Bruijin graph CAP3 Combine assembles UNIGENES

27 Why MIRA? NGS Reads SeqTrimNext Pre-processing Assembly MIRA3 EULER-SR Debris Bowtie2 Verification Unmapped Full-LengtherNext Full-LengtherNext Non- Coding Non- Coding Open source Coding Reads CAP3 Mapped Coding Contig Merge UNIGENES (Very) Well document and well maintained Overlap-layout-consensus paradigm (OLC) Does not deal well with high coverage Assembler/Mapper --- Can call SNPs

28 MIRA3 Options GENERAL (-GE) LOADREADS options (-LR) ASSEMBLY (-AS) STRAIN/BACKBONE (-SB) CLIPPING (-CL) SKIM (-SK) ALIGN (-AL) CONTIG (-CO)

29 Why Euler-SR NGS Reads SeqTrimNext Pre-processing Assembly MIRA3 EULER-SR Debris Based de Bruijin graph Bowtie2 Verification Unmapped Full-LengtherNext Full-LengtherNext Non- Coding Non- Coding Incorporate system error correction Coding Reads Mapped Coding Contig Merge CAP3 Easy to run UNIGENES Kmer Kmer => low-abundance transcripts => high-abundance transcripts

30 Where are the datasets?

31 Sending jobs Remember: batch mode! You need a xxxx.sh file > sbatch xxxxx.sh project_assembly folder besides.sh file

32 E1: run MIRA # copy file Assembly project_in.454.fastq Debris MIRA3 EULER-SR # To load software module load mira/3.2.0 # the program to execute with its parameters >mira -fastq -project=cleaned_hyp_rl5 --job=denovo,est,normal,454 -CL:ascdc 454_SETTINGS -CO:fnicpst=yes -notraceinfo COMMON_SETTINGS -GE:not=16 -DI:lrt=$SCRATCH Chimera detection Force non- IUPAC consensus Number of CPU

33 MIRA3_result alignment.ace result.padded.fasta result.unpadded.fasta

34 MIRA3_info

35 Alignment visualization

36 ACE file

37 E2: run EULER # copy fasta reads: MIRA3 EULER-SR Assembly cleaned_hyp_rl5.fasta Debris # To load software module load euler # the program to execute with its parameters >Assemble.pl cleaned_hyp_rl5.fasta 29 > result_euler.txt 29 : kmer

38 E: extract debris reads Assembly MIRA3 EULER-SR # copy files: Debris cleaned_hyp_rl5_info_debrislist.txt # extract debris reads: lista_to_fasta.rb cleaned_hyp_rl5.fasta cleaned_hyp_rl5_info_debrislist.txt > mira_debris.fasta # count reads: grep -c > mira_debris.fasta

39 E3: FLN debris fasta Assembly # copy fasta reads: MIRA3 EULER-SR mira_debris.fasta Debris Bowtie2 Verification # To load software Unmapped module load full_lengther_next Full-LengtherNext Non- Full-LengtherNext #the program to execute with its parameters full_lengther_next -f mira_debris.fasta -g vertebrates Taxon -u /mnt/home/soft/full_lengther_next/db/user_db/actinopterygii/actinopterygii.fasta -c 100 -w 8 -s contig g>oup Workers IP User DB

40 FullLengtherNext result Annotation file (13824)

41 E4: Mapping reads Assembly MIRA3 EULER-SR # copy files: cleaned_hyp_rl5.fastq (1_Mira_assembly) cleaned_hyp_rl5.fasta.contig (2_Euler_assembly) Debris Bowtie2 Unmapped NGS Reads Verification Full-LengtherNext Full-LengtherNext Non- # To load software module load bowtie/v2_2.0.0-beta7 # the program to executa with parameters # index reference bowtie2-build -f cleaned_hyp_rl5.fasta.contig ref # lanzar mapeo bowtie2 ref -q -p 32 -U cleaned_hyp_rl5_in.454.fastq --very-fast -S euler.sam

42 How many sequences have been mapped? reads; of these: (100.00%) were unpaired; of these: (67.41%) aligned 0 times (32.57%) aligned exactly 1 time 44 (0.02%) aligned >1 times 32.59% overall alignment rate

43 Extract mapped/unmapped Visualization NGS data

44 Alignment visualization SAM file reference file

45 E: extract un/mapped reads Assembly MIRA3 EULER-SR # copy files (long_read/4_mapping_euler): Debris mapped_euler.txt unmapped_euler.txt Full-LengtherNext Bowtie2 Verification Unmapped Full-LengtherNext Non- # extract unmapped contigs: lista_to_fasta.rb cleaned_hyp_rl5.fasta.contig unmapped_euler.txt > contig_euler_unmapped.fasta # extract mapped contigs: lista_to_fasta.rb cleaned_hyp_rl5.fasta.contig mapped_euler.txt > contig_euler_mapped.fasta # count reads: grep -c > contig_euler_unmapped.fasta

46 E5: FLN unmapped Assembly MIRA3 EULER-SR # copy fasta reads: contig_euler_unmapped.fasta Debris Full-LengtherNext Bowtie2 Verification Unmapped Full-LengtherNext Non- # To load software module load full_lengther_next #the program to execute with its parameters full_lengther_next -f contig_euler_unmapped.fasta -g vertebrates Taxon -u /mnt/home/soft/full_lengther_next/db/user_db/actinopterygii/actinopterygii.fasta -c 100 -w 8 -s contig g>oup Workers IP User DB

47 E6: merge CAP3 # copy files: cleaned_hyp_rl5_mira.fasta contig_euler_mapped.fasta contig_euler_unmapped_conding.fasta mira_debris_coding.fasta # join files: cat *.fasta > Reassembly_hyp.fasta # To load software module load cap3 # the program to execute with its parameters: cap3 Reassembly_hyp.fasta -p 95 -o 40 > resultcap3.txt

48 ACE file

49 E7: FLN unigenes # join contig+single: >cat Reassembly_hyp.fasta.cap.contig Reassembly_hyp.fasta.cap.singles > Unigenes_hp.fasta # To load software module load full_lengther_next #the program to execute with its parameters User DB full_lengther_next -f Unigenes_hp.fasta -g vertebrates Taxon -u /mnt/home/soft/full_lengther_next/db/user_db/actinopterygii/actinopterygii.fasta -c 100 -w 8 -s