Blog Series: Workshop on Genomics, Cesky Krumlov; Preparation--Transcriptomics

Section 3: Transcriptomics

Four readings were suggested for this section which sadly are not open access, I'll link them below and then we'll dive into some crash-course transcriptomics and explore other resources available to round out your knowledge base on the subject.

• Garber, M et al., 2011. Computational methods for transcriptome annotation and quantification using RNA-seq. Nature Methods. 8:469-477.
• Pepke, S; B Wold and A Mortazavi. 2009. Computation for ChIP-seq and RNA-seq studies. Nature Methods. 6(11 Suppl):S22-S32.
• Mortazavi, A et al., 2008. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nature Methods. 5:621-628.
• Johnson, DS et al., 2007. Genome-wide mapping of in vivo protein-DNA interactions. Science. 316:1497-1502.

Richard Twyman writes a nice short sum up of Transcriptomics and it's applications on the Wellcome Trust site. He defines transcriptomics as the global study of gene expression at the RNA level. So now we are not only talking about genes and their nucleotides, we are now talking about what those genes are doing, when those genes are active and to what degree those genes are active and regulated. All of this is measured through various forms of RNA (mRNA, tRNA, rRNA, ncRNA, siRNA or total RNA). The type of RNA you are interested in depends on what question are you asking. Richard Twyman has assisted in many research publications involving bioinformatic analysis and his recent publications can be found on the writescience site.

In terms of more articles to sift through that explore transcriptomics you can try the OmicsGateway with subject: Transcriptomics through Nature Publishing, though I cannot guarantee they'll be open access. Alternatively you can go to BMC Genomics which has a whole section on Transcriptomics where many of the articles are open access.

From the list of read-mes above there are a  couple different technologies/methods in place for looking at transcriptomics from a next generation sequencing bent: RNA-Seq and ChIP-Seq

RNA-Seq

• In short: This technique utilizes RNA (usually total RNA, but protocols can target mRNA or other RNA or interest) that has been converted to cDNA fragments to which adaptors are attached. These fragments are then sequenced using whatever flavor of sequencing technology you prefer. Short reads can then be assembled/mapped to a reference or de novo assembled to create maps of expression a long a whole genome or genomic region of interest.
• A great introduction would be Wang, Gerstein and Snyder's article from 2009. Again the technology has come forward since 2009, but this will give you a nice primer. Wang, Z; M Gerstein and M Snyder. 2009. RNA-Seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics 10:57-63 (Open Access). The article also draws comparison between sequence-based and microarray-based expression mapping.
• A nice set of slides to accompany your read through of Wang et al., can be found here as compiled by Lalit Ponnala from Cornell (simpler) and another set compiled at MIT (author unknown) (a bit more in depth). Programs are mentioned in these slides that may not necessarily be used in the workshop but feel free to explore as you see fit.
• Another slide overview of RNA-Seq that was presented recently (this past year) was compiled by Markus Kreuz from Universitat Leipzig.
• There are quite a few applications and software packages that deal with RNA-seq analysis such as CLCbio, GenomeQuest, BioConductor and SeqMonk; however I am not going expound on these until the session at the workshop on transcriptomics where a different pipeline of analysis may be suggested. But for you over-achievers (videos are linked instead of embedded), SeqMonk is the only one I am sure is free, the others you'll have to take a look.

1. CLCbio Tutorial on RNA-seq analysis Part 1-pdf document
2. CLCbio Tutorial via Video
3. RNA-seq using SeqMonk video
4. SeqMonk Website
5. GenomeQuest wiki on RNA-seq
6. Bioconductor

Moving on...

ChIP-Seq

• In short: ChIP-seq is a way of determining how proteins interact with DNA to regulate gene expression. Genomic fragments that co-precipitate with DNA-binding proteins are sequenced. Often the DNA-binding protein of interest is a transcription factor but not always. This allows you to study all DNA fragments that are associated with your binding protein.
• A good run down Q&A about ChIP-seq can be found via BMC Biology: ChIP-seq technologies and the study of gene regulation at the end of which is a wealth of articles related to ChIP-seq and it's applications, most of which are open access. Figure 1 in the Q&A provides a schematic flow for ChIP-seq analysis.
• Nature Review Genetics also provides a nice primer article for ChIP-seq from 2009. Park, PJ. 2009. ChIP-seq: advantages and challenges of a maturing technology. Nature Reviews Genetics 10:669-680. (free)
• The ENCODE project (NCBI link to ENCODE and modENCODE) has also dabbled in quite a bit if ChIP-seq and developed some guidelines that might be of interest. Nature has an ENCODE explorer if you'd like to venture into the project from there.
• Slideshare set on ChIP-seq: Alba Jene Sanz from Biomedical Genomics Lab compiles a nice set, make sure to maximize your screen to see the small text on some of the slides. Slides 18 and 19 are nice in that they compare the different analysis tools for ChIP-seq data in table format.
• As with RNA-seq here are some tools and packages for over-achievers to get started on for ChIP-seq, not sure whats free and what's not so take a look and make sure to read manuals. Some of the papers and presentations I've already linked also discuss tools for analysis so refer to those presentations for additional information and links.

1. Bioconductor
2. ChIP-seq online analysis tools site
3. SeqMonk video tutorial for ChIP-seq analysis see above website in RNA-seq section for SeqMonk.

Now how about a Review?

Though Pepke, Wold and Mortazavi's paper from Nature Methods (linked above) is not freely available, slides based on the paper are! Huzzah and Thank You Princeton!

As inferred by the title of this blog--We all seq (sequence) to Seek (Seq)...looks like we'll have a fun information overloaded future ahead of us as we add transcriptomics...RNA-seq and ChIP-seq to the Seqs that help us to Seek (Seq).

I hope everyone had a lovely new year, happy 2013...I'll be back with more preparation blogs tomorrow.

Next Up: Preparation--Assembly