Weeks 6 and 7: July 13 – 26

I am grouping these weeks together because what I have been doing is a bit repetitive.

On Monday the 13, we harvested the inoculated clusters of V. rupestris B38 x ‘Horizon’ to do incidence ratings. For the incidence ratings, instead of rating on a subjective 0-4 scale, we take a tally of the number of clean/infected/mummified (extremely advanced black rot) berries so that we have an objective, quantitative measurement of disease intensity.  We can therefore do the QTL analysis in two different ways (using either the 0-4 scale or the incidence ratings) to see the differences and similarities that arise between them.

Countin berries
Counting berries

In these two weeks, we rated for disease in ‘Horizon’ x ‘Illinois 547-1’, until Monday the 20th, when we harvested these clusters as well.

On Wednesday the 22, we did our first QTL analysis, on the disease severity ratings from rupestris. We do the analysis using R-QTL, a package in R, which is a code-based open-source statistical software.

The goal of a QTL analysis is to discover regions of the genome that control a trait of interest, in our case black rot resistance/susceptibility. It does this by cross-referencing the segregation of disease intensity (the phenotypic differences) with polymorphisms in the DNA (the genotypic differences). This identifies regions of the genome, Quantitative Trait Loci (QTLs) that are associated with the trait.

Conducting QTL analysis in R
Conducting QTL analysis in R

In our analysis, we discovered two significant QTLs. From these, scientists develop molecular markers, which are short repetitive sequences (SSRs, or microsatellites) located nearby in the genome. An individual’s possession of the SSR, and therefore of the trait, is commonly assessed by PCR (which generates many copies of the SSR as well as of the genome) followed by electrophoresis (which separates the DNA fragments created by the PCR by length). The presence of  DNA fragments the length of the SSR (as diagnosed through the electrophoresis) identifies the individual as having the molecular marker.

Of course, from the SSRs and onward exceeds the scope of my project. My task was to identify the QTLs involved in black rot resistance/susceptibility through phenotyping in the vineyard. The genotyping was done before I arrived, and the development of the microsatellites will be done after I’ve left. Now its left to Beth and future grad students and summer scholars to carry the torch.

Go team Black Rot!