#The presence full#

Assuming that sequencing reads are uniformly distributed along a transcript, we would expect 33 to 38% of 100 bp reads from an RNA-seq experiment to span two or more exons. The average number of exons per transcript is 9.5. In the most recent Ensembl GRCh37 gene annotations, the average length of a mature mRNA transcript in the human genome is 2,227 bp long, and the average exon length is 235 bp. This is particularly acute for the human genome, which contains over 14,000 pseudogenes. Second, the presence of processed pseudogenes, from which some or all introns have been removed, may cause many exon-spanning reads to map incorrectly. In mammalian genomes, introns span a very wide range of lengths, typically from 50 to 100,000 bases, which the alignment algorithm must accommodate. First, because genes in eukaryotic genomes contain introns, and because reads sequenced from mature mRNA transcripts do not include these introns, any RNA-seq alignment program must be able to handle gapped (or spliced) alignment with very large gaps. In contrast to DNA-sequence alignment, RNA-seq mapping algorithms have two additional challenges. The first step in the analysis process is to map the RNA-sequence (RNA-seq) reads against the reference genome, which provides the location from which the reads originated. In addition to the transcript structures, experimenters need to estimate the expression levels for all transcripts.

#The presence full#

One of the primary goals of RNA-sequencing analysis software is to reconstruct the full set of transcripts (isoforms) of genes that were present in the original cells.

RNA-sequencing technologies, which sequence the RNA molecules being transcribed in cells, allow exploration of the process of transcription in exquisite detail.