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Dr. Keiichi Mochida is the Deputy Team Leader at Biomass Research Platform Team, RIKEN Center for Sustainable Resource Science, in Japan. Dr. Mochida’s laboratory has established an infrastructure to promote the discovery of functional genes using Brachypodium distachyon as a model species. The team is creating basic genomic resources by collecting full-length cDNAs, developing next-generation sequencing (NGS) applications, and performing RNA-Seq analysis. They also perform metabolome analysis, work towards improving transformation efficiency, and generate mutant resources.

Dr. Mochida recently collaborated with Life Technologies to conduct a Brachypodium distachyon RNA-Seq study using the Ion PGM™ Sequencer.* He shares his work on this topic in a recent interview captured below. 

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Tell us a little bit more about your lab, your background, the plants you are interested in, and your research goals.

In graduate school, I cytogenetically analyzed the mechanism of how a wheat haploid results from a hybrid embryo of wheat and corn. During that time, I started getting involved in the large-scale analysis of wheat cDNAs and began using a computer for genome research. I am currently specialized in genome informatics.

Brachypodium belongs to the Pooideae subfamily of the grass family Poaceae.  Included in the Pooideae subfamily are key cereal species such as wheat and barley. Brachypodium has important features that make it a model plant for studying the properties of such grass species in temperate regions. We believe it is important to accelerate the discovery of key genes in wheat in conjunction with Brachypodium research.

Our immediate research goals are to discover useful genes that will increase the biomass productivity of grass species and elucidate the functions of such genes, and to develop base technologies that will accelerate the discovery of key genes in wheat.

Why is Brachypodium distachyon important?  What questions are you trying to answer in particular?

As I mentioned above, Brachypodium plays an especially important role as a model wheat species. (Mochida et al. 2013, in press). Using Brachypodium, we attempt to identify genes involved in environment adaptability and to unravel the functions of such genes. And we aim to improve the productivity of plants by reinforcing their environmental adaptative ability. 

What other technologies do you use today for your genomic and transcriptomic studies?

We use HiSeq® 2000 sequencing technology. We have also used oligo microarrays for transcriptome analysis, but we now mainly use RNA-Seq on HiSeq® 2000 or the Ion PGM.*

What do you need to achieve your research goal?  What are the key requirements for a sequencing platform to fit those needs?

What we needed was a platform that would allow us to routinely perform transcriptome analysis with RNA-seq and genotyping with amplicon-Seq, and so forth. As we also focus on the prediction of accurate genetic makeup or transcription of antisense RNAs, we believe directional RNA-Seq is a highly effective technology.

Sequencing technology has been developing rapidly. Do you see other applications that will be enabled by the future higher throughput, longer read length, and lower cost technology?

We look toward the Ion Proton which we are planning to adopt in our lab. We plan to scale up several analysis protocols that we have developed on the Ion PGM. We are, for example, planning to apply them to genotyping by sequencing (GBS). We also want to apply them to research areas where we could capitalize on the advantage of scale, such as for whole-genome resequencing and whole-genome bisulfate sequencing.

Why did you choose the Ion PGM™ Sequencer?

One of the main reasons is that the Ion PGM gives us directional RNA-Seq data in a short time. This is very attractive when contract service with large NGS platforms, such as the HiSeq® 2000 system, can take close to two months before delivery. Another point which some people may or may not like is Torrent Server, where the computer for analysis is independent of the sequencer. This makes it easier to have it work together with analysis pipelines already implemented on other computers, which I personally find appealing.