James and the Giant Corn Genetics: Studying the Source Code of Nature

March 13, 2012

qTeller part 2: Eye candy!

Filed under: Uncategorized — James @ 4:31 pm

qTeller isn’t just for generating spreadsheets full of data on genes within an genomic region. It can also visualize published expression data for a single gene. For example here is the expression pattern of a gene called golden plant2 involved in regulating photosynthetic development in maize which was first  described all the way back in 1926 in an article in the american naturalist:

As you can see golden plant2 is expressed at high levels in photosynthetic tissues and not expressed at all in tissues like roots, endosperm, and pollen. Do you know how long it would have taken me to profile the plant-wide expression pattern of a gene this comprehensively by isolating RNA from different tissues using qPCR? WEEKS! Do you know how long it took for me to get the same level of insight with qTeller? 90 seconds!

Do you know how long it’ll take you to regenerate this same analysis? 30 seconds. Just click this link. There have been so many awesome RNA-seq papers coming out recently for maize. I know when I arrive in Portland on Thursday for the Maize Genetics Conference I’m going to see a whole lot more even bigger/better RNA-seq datasets which people haven’t finished writing up yet. Some of these datasets have been on posters since the very first maize meeting I went to back in 2009 when I was a wide-eyed first year and may _never_ get published.* But others will be published weeks or months from now, making this visualization all the more powerful.

But for now, MORE EYE CANDY:

Anther ear1

Expression of anther ear1, a mutant in the gibberellic acid biosynthetic pathway

Link to regenerate analysis


Link to regenerate analysis. 

Glossy1 mutants change the type of wax produced on the leaves of developing maize seedlings, so it makes sense that the gene shows high expression in both maize seedlings and mature leaves. I can even sort of explain away the high expression in developing seeds and embryos since the the primordia which will eventually become the first leaves of the next generation of corn plants are beginning to form, But why in the world does glossy1 show such high levels of expression in anthers?

*Here is the relevant excerpt from my previous rant on data analysis:

I recently did the math on a PLoS Genetics paper published in late 2009 based on on a single in-depth analysis of RNA-seq comparisons of mutant and non-mutant siblings. Today we could generate the same dataset, with twice the depth of sequencing for less than $1000 dollars. (INCLUDING regent costs). The takeaway lesson here: just because your dataset was expensive to generate doesn’t mean you don’t have to worry about the competition stealing the glory if you take more than a year to publish. 

qTeller: an easier way to find candidate genes

Filed under: Uncategorized — James @ 3:13 pm

Hunting for good candidate genes is something biologists spend a lot of their time doing. Here are a couple of hypothetical examples:

A) Suzzy the grad student is mapping a recessive mutant which makes the pollen of cornplants shrivel up and die. By examining a bunch of known genetic markers in plants with dead pollen and normal pollen producing siblings of those plants she has narrowed the location of the gene responsible for her trait down to a region of only a couple of megabases on the fifth chromosome of maize. Since the whole maize genome contains over 2,300 megabases of sequence that means she’s already ruled out 99.9% of the genome. But her region still contains, say, a dozen genes and she needs to know which one she should check first to see if mutation in it is responsible for her mutant phenotype.

B) Johnny is another grad student. He wants to understand how corn plants genetically regulate how wide their leaves will grow to be. By measuring a lot of plants descended from two parents, each with known genotypes, he can identify regions of the genome where inheriting information from one parent or the other seems to be correlated with either wider or narrower leaves. He calls these regions quantitative trait loci (or QTLs). Now he has picked the genetic region that seems to have the biggest effect, and he wants to know what gene within the region is actually responsible for the effect.

There are a number of ways for both Johnny and Suzzy to narrow down their lists to the genes most likely responsible for the changes they are each observing in corn plants: (more…)

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