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A Few Good Posts on Transcriptome Assembly and Analysis

Homolog.us blog is written by professional janitors dedicated to clean up US science. During lunch breaks and other time off from the job, we discuss bioinformatics. The name 'homolog.us' is not a spelling mistake, but is derived by taking Arabic translation of the 'O' in the original word.

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In the PacBio-related commentary, we wrote -

PacBio developed a terrific transcriptome assembler – ‘CRAZY’. It assembles the transcripts and isoforms easily and to a high degree of accuracy. Bye bye Trinity !!

If you are wondering about it, ‘CRAZY’ is not an acronym. One has to be crazy to think about assembling transcripts from PacBio reads, given that the reads themselves are longer than typical genes. You sequence and you get your genes. No assembly needed.

Researchers are yet to reach that nirvana and the current reality is to do Illumina sequencing and reconstruct transcriptomes from the short reads. Two good commentaries are helpful in that respect.

Biocompare blog covers -

Transcriptome Assembly, No Reference Required!

There’s no denying the impact of whole-genome sequencing for basic research and in the clinic. Reference genomes provide a scaffold upon which to map traits, trace evolutionary relationships, assess genetic diversity and more, and for researchers studying well-characterized organisms like Drosophila, mouse, rat and human, they are invaluable resources.

But for the vast majority of species, whole-genome sequencing is a nonstarter. Perhaps there are too few investigators interested in the organism to get the ball rolling. Or maybe it’s a matter of money. Whatever the reason, despite deep cost decreases in next-gen sequencing, many researchers simply cannot justify reading and interpreting every base in their organism of interest.

Fortunately, they don’t necessarily have to. A growing number of researchers are leveraging RNA-seq data to produce a sort of low-rent, partial-genome assembly, a process called de novo transcriptome assembly. The result doesn’t capture every base, but it does provide information on expressed genes. All it takes is an RNA-seq dataset, some specialized open-source software tools and the bioinformatics chops to use them.

Getting Genetics Done has another helpful commentary on Trinity with videos.

De Novo Transcriptome Assembly with Trinity: Protocol and Videos

One of the clearest advantages RNA-seq has over array-based technology for studying gene expression is not needing a reference genome or a pre-existing oligo array. De novo transcriptome assembly allows you to study non-model organisms, cancer cells, or environmental metatranscriptomes. One of the challenges with de novo transcriptome assembly, above and beyond all the challenges associated with genome assembly, is the highly varying abundance (and thus uneven sequencing depth) of different transcripts in a cell.

Several tools have been developed for de novo transcriptome assembly. One of the most widely used is Trinity, developed at the Broad Institute. Trinity is free and open-source, and a recent Nature Protocols article walks through using Trinity for de novo RNA-seq:

Haas, Brian J., et al. “De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis.” Nature protocols 8.8 (2013): 1494-1512.

You can also check our earlier series from two years back -

De Novo Transcriptome Assemblers – Oases, Trinity, etc.

De Novo Transcriptome Assemblers – Oases, Trinity, etc. – II

De Novo Transcriptome Assemblers – Oases, Trinity, etc. – III

De Novo Transcriptome Assemblers – Oases, Trinity, etc. – IV

Explaining Output of Trinity Component – Inchworm




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