Mind boggling potato breeding

Tom Wagner explains how he does what he does, kinda, sorta.

Anyway, I had some extra pollen of Nordic October (one of my best reds) and went to a potato seedling growing in a raised bed. I emasculated several buds of the yet un-named seedling and proceeded to tell my neighbor of the pedigree. I said that the original line was CT8406-33, a chacoense/tuuberosum hybrid with slightly blue rings in a purple skinned white flesh potato that was but one of some seedling tubers lines bred for high glycoalkoloids in the foliage to repel Colorado Potato Beetles. This line was either selfed or OP’ed and the result was Red Cat, a red skinned, red fleshed line that had lots of berries. I crossed Red Cat to a male parent called Lenape, a white skinned, white flesh line with high glycoalcoloids. The cross led to the Negro y Azul, a very black/blue skin and fleshed line that saw it’s origin on some certified organic ground off I-5 near Buttonwillow, California. Negro y Azul was crossed to Kern Toro, one of my best reds at that time, a combination of NorDonna and Fontenot. The cross of Negro y Azul and Kern Toro led to Azul Toro, an excellent early blue flesh variety. I crossed the female Azul Toro with pollen from Blue Blood Russet, a cross of Blue Cat and an unknown russet seedling. The resulting cross was named Paint Jar, an inky black/blue with occasional white patches in the flesh. I crossed the Paint Jar with pollen from Dark Red Norland and this created Paint Nor. Paint Nor was crossed with pollen from October Blue, a cross of Nordic October, a red similar to Kern Toro with the exception of additional germplasm from Red October that had ND2912-2R in it….to Azul Toro, previously mentioned. The two seedlings in the raised bed has one I named last week as Mule Skinner Blues. The other had to be named and I thought of Mostly Purple and I serendipitously named it MOSTLY PURPLE as I crossed it with pollen from Nordic October…knowing fully that I had permission to do so.

Senate discusses wild rice

Good news for wild rice breeders, from Washington, DC of all places.

Funding for wild rice and forestry research cleared a Senate committee hurdle last week, said U.S. Sen. Amy Klobuchar, DFL-Minn.

The Senate Appropriations Committee last week approved $5.5 million in agriculture and economic development initiations that include new product research for wood and wild rice research.

A $300,000 appropriation would develop new and hardier strains of wild rice, Klobuchar said. It would fund research to tackle some of the most critical problems for wild rice producers, including shattering resistance, disease resistance, germplasm retention and seed storage.

Wild rice is the only cereal grain native to North America. Minnesota is the nation’s second-largest producer of wild rice, with production concentration near the Red Lake Band of Chippewa Indians, the Democratic senator said.

I’d really like to have heard the august US Senators debate the ins and outs of that 300 large. Maybe one of them explained what “germplasm retention” is.

Why do we still not have an early warning system for genetic erosion?

I’ve blogged about ProMED before a couple of times. It’s advertised as a “global electronic reporting system for outbreaks of emerging infectious diseases & toxins.” But it is actually a bit more than that, as a recent piece on cassava brown streak disease revealed. There have recently been some stories in the Ugandan popular press about this disease. And one of the early ones made it to ProMED. That’s useful enough, but it also elicited a reply from Prof. Mark Laing of the School of Biochemistry, Genetics, Microbiology and Plant Pathology, University of KwaZulu-Natal in Pietermaritzburg, South Africa. He noted that “that there is hope on the horizon versus both cassava mosaic disease (CMD) and cassava brown streak virus (CBSV)” and quoted a couple of breeding programmes that are having some success. That’s really how you want an early warning system to work. It should not only give warning of the problem, but also get people to discuss possible solutions. It doesn’t seem all that complicated to set up. Is it too much to hope for that there’ll be something along these lines for genetic erosion before I crawl away to my well-earned retirement?

Livestock genetics symposium online

DAD-Net informs us that the presentations given at the symposium on Statistical Genetics of Livestock for the Post-Genomic Era, held at the University of Wisconsin-Madison, USA, on May 4-6, 2009, are now available online in the form of both PDFs and videos. Quite a resource.

Making that haystack smaller

Germplasm collections can be very large, and that can put off potential users. What breeder really wants to screen thousands of accessions, when only a dozen might end up being useful? It’s not surprising, therefore, that people have looked for short-cuts. One approach is to make a “core collection.” You use the available data on the collection to select a sub-set which you hope will contain most of the original genetic diversity in a fraction (20%, say) of the total number of accessions. And then you evaluate that subset, rather than the whole collection, and use the results to delve back into the remaining 80% of the material, with hopefully a better chance of finding what you’re looking for.

That’s been done for lots of large collections now, with a certain amount of success in increasing their use — and usefulness. But breeders are not really satisfied. They want to shorten the odds even more. And the application of Geographic Information Systems (GIS) technology in something called the Focused Identification of Germplasm Strategy (FIGS) provides a potentially effective way of doing just that.

Jeremy described recently over at Bioversity how FIGS was used to increase the chances of finding a needle in a haystack by “start[ing] with a smaller haystack.” The haystack was 16,000 wheat accessions. The needle was resistance to powdery mildew.

It works like this: take 400 genebank samples known to have some resistance to powdery mildew and use the geographical location where they evolved and were collected to determine the environmental profile that can be associated with resistance. Then apply that profile to a further 16,089 samples with location data, using the profile as a template to identify those that were found in places that share the conditions associated with resistance. The result is a group of 1320 wheat varieties, mostly from Turkey, Iran and Afghanistan. This much more manageable subset was screened by growing them with diverse strains of powdery mildew. About 16% of the samples (211 of 1320) showed some resistance.

These varieties then moved to the next phase, molecular screening for the presence of different alleles of the Pm3 gene. More than half (111 of the 211) had Pm3 resistance, some in previously unknown forms. In the end the group isolated and identified 7 new functional alleles of the Pm3 gene. It took scientists 100 years to find the first 7 Pm3 alleles. FIGS doubled the number in a fraction of the time.

Very good. But is it always going to work? Another recent paper — in fact, a series of papers — counsels caution.

Continue reading “Making that haystack smaller”