I'm working with human small RNA-Seq (50 bp, single end). Surprisingly, I'm able to align only tiny fraction of reads (<1% for 3 mismatches, <5% for 6 mismatches). I have tested 2 aligners (bowtie and gem-mapper) and got similar results. Do you have any idea why is that?
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Leszek
3 answers
I'm sure you forgot to trim the 3' adapter ! try trimmomatic, fastx_clipper or cutadapt
When doing small RNA-seq, the main fraction of your reads is around 22-24 nt in length (the miRNA fraction). Without clipping the adapter sequences, there is no way to map most of the reads of your experiment. I would recommend you to clip the used adapter (not only 10 nt) and then take a look at your length distribution. You should see a peak at 22-24nt... if not, there is something wrong with your experiment.
And if you don't know your adapter sequence, hard clip a longer fraction of the 3'end... at least 25nt. Then you be able to map ~80%, I assume.
And if you don't know your adapter sequence, hard clip a longer fraction of the 3'end... at least 25nt. Then you should be able to map ~80%, I assume.
By the way: The adaptor for the Illumina HiSeq 2000 miRNA protocol is TGGAATTCTCGGGTGCCAAGGAACTCCAGTCAC.
Try this: ./fastx_clipper -i SRR324686.fastq -o SRR324686.clipped.fastq -a TGGAATTCTCGGGTGCCAAGGAACTCCAGTCAC -l 15 -M 20 -c
I run it as you said , but many miRNA reads trimmed still too long far from 20nt, what should I do next?
and the adaptor for the Illumina HiSeq 2000 miRNA protocol is TGGAATTCTCGGGTGCCAAGGAACTCCAGTCAC., when I search in miRBase, there appeared some mature miRNA accessions, then how to explain the sequences are adapters or mature miRNA sequences? And why there are different illumina adaptors like TCGTATGCCGTCTTCTGCTTGT(A: Problems with analysis of small RNAseq data - Adapter trimming)?
If the problem is really because of adapters, then I will recommend MicroRazerS: rapid alignment of small RNA reads.paper. Reads can be of arbitrary length and can contain adapter sequence at the 3' end, you can find rest of the information here.
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Have you tried doing a fastqc on the reads? What do the quality look like?
Is it possible that you are missing something really simple? What are bowtie's default options for mapping RNA-seq reads on to a reference genome? Are you mapping to a reference genome or exome? You may want to try Tophat which does Bowtie first for short-read alignment but also allows alignment across splice junctions so it can do splice-junction mapping.
@DK: I trimmed reads at first base having quality <20 and discarded reads shorter than 31 bases @Dan: I'm mapping onto hg18 (bowtie --sam --all -n3 -l21). Optionally hard clipping -5 10 or -3 10
show us a sequence you think should have aligned