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Gene Prediction

1. Evidence Based Gene Prediction

Overview of steps:

The steps for evidence based prediction are as follows:

  1. Map RNAseq reads to the genome
  2. Assemble transcripts using various transcript assemblers
  3. Run Mikado to consolidate transcripts and run programs to identify splice junctions, ORFs and full length matches to SwissProt plants proteins.
  4. Pick transcripts for each locus and finalize evidence based annotations.
  5. Post-processing of evidence based predictions.

Steps in detail:

1. Map RNAseq reads:

The RNAseq reads generated for Ab10 were as follows:

ID PlantStage Tissue Type TotalReads AvgLength
MN02011 8DAS root Paired 29,818,892 152
MN02012 8DAS root Paired 32,543,108 152
MN02021 8DAS shoot Paired 26,420,582 152
MN02022 8DAS shoot Paired 32,247,423 152
MN02031 V11 leaf-base Paired 22,147,809 151
MN02032 V11 leaf-base Paired 27,560,950 151
MN02041 V11 leaf-middle Paired 22,146,843 151
MN02042 V11 leaf-middle Paired 22,466,821 151
MN02051 V11 leaf-tip Paired 26,407,717 151
MN02052 V11 leaf-tip Paired 21,923,046 151
MN02061 V18 tassel Paired 21,278,567 151
MN02062 V18 tassel Paired 22,868,224 151
MN02071 V18 ear Paired 30,154,390 151
MN02072 V18 ear Paired 20,563,411 151
MN02081 R1 anther Paired 17,818,298 151
MN02082 R1 anther Paired 24,882,545 151
MN02091 16DAP endosperm Paired 26,834,976 151
MN02092 16DAP endosperm Paired 26,182,541 151
MN02101 16DAP embryo Paired 14,833,469 151
MN02102 16DAP embryo Paired 26,947,220 151

Reads were mapped using STAR mapping program as follows:

# index
runSTARmap_index.sh B73Ab10.pseudomolecules-v2.fasta
# first round mapping
for read1 in *R1.fq.gz; do
  runSTARmap_round1.sh B73Ab10.pseudomolecules-v2.fasta ${read1}
done
# consolidate splice info
awk -f sjCollapseSamples.awk *_SJ.out.tab | sort -k1,1V -k2,2n -k3,3n > SJ.all
# second round mapping
for read1 in *R1.fq.gz; do
  runSTARmap_round2.sh B73Ab10.pseudomolecules-v2.fasta ${read1}
done
# merge BAM files
merge-bam-files.sh B73_AB10

2. Transcript Assembly

Five different transcript assemblers were ran on the merged BAM file (merged_B73_AB10.bam) as follows:

runStrawberry.sh merged_B73_AB10.bam
runStringtie.sh merged_B73_AB10.bam
runTrinity.sh merged_B73_AB10.bam
runClass2.sh merged_B73_AB10.bam
runCufflinks.sh merged_B73_AB10.bam

Since Trinity generates a fasta file, we will use GMAP to map them and create a GFF3 file.

runGMAPcdna.sh B73Ab10.pseudomolecules-v2.fasta

We will also need splice junctions, that we can generate using PortCullis:

runPortcullis.sh merged_B73_AB10.bam

3. Consolidate transcripts and prepare files

Here, we will use all the transcript assemblies generated in the previous step, along with splice junctions and pool them together. The redundant transcripts are also removed. Using consolidated transcripts, we will find full length trasncritps by BLAST searching against SwissProt proteins, and detect ORFs using TransDecoder.

This is all accomplished using this script:

copy-files-for-mikado.sh B73_Ab10

4. Finalize evidence-based predictions

As a last step, we will run Mikado to finalize the predictions. It is done using this script:

finalize-files-and-pick.sh B73_Ab10

5. Post processing of evidence-based predictions

Kapeel's section