What is in this article?:
- Higher wheat yields, better breeding to follow genome mapping?
- Focus on applying technology
• The discoveries by teams of scientists in England, Germany and the United States could also provide guideposts to dealing with diseases like UG99 and mitigate alarming claims about coming climate change-caused food catastrophes.
Focus on applying technology
“To some extent I think it’s fair to say our forte is focusing on how to apply the technology to challenging problems, whether a big genome or a complex genetic problem in humans.”
Was UG99 a driver behind the research?
“No, it really wasn’t driven from a particular agricultural problem. It was driven from the standpoint that having this basic information would help breeders with any problem they approach. It will provide them with more detailed markers within the genome to help them evaluate sensitivity — or resistance in the case of rust.
(To see more about the threat of UG99 to wheat, see UG99: A future threat to U.S. wheat growers).
“So, the reasons for getting into the research were broader.
“I’m a chemistry and computational guy — not a breeder. But, in general, when people do crosses they’ll identify strains that are more or less resistant. Being able to more precisely understand the mechanisms of that in terms of what genes are involved and where they are.
“One of the things the study did is provide a good, although not perfect, view of the wheat genome. It’s certainly the best view we have so far.
“That will help identify the genes contributing to resistance. It will also provide around 100,000 markers for more precise mapping locations within the genome when crosses are made. That way breeders can tell which component genome is present in each of the crosses.”
Did the sheer size of the genome surprise you?
“We actually knew that going in.
“To be candid, I was surprised it worked as well as it did. I knew it was a tremendous challenge and we’d get a pretty good, valuable view of the total gene content. The work done by the computational people, particularly in Germany, really gave a much better view of the genome.
“Wheat is a hexaploid genome, so it came from three precursor diploid genomes about 10,000 years ago when it was domesticated. The computational team was able to do a much better job than I expected at separating the three copies of each of the genes. They compared the diploid relatives of the wheat and other species.
“I knew that would work somewhat — it was a great idea. But the success they had was marvelous.”
Wheat has five times the amount of DNA in the human genome?
“The weed we worked with in the 1990s has about 135 million bases. Rice has about 400 million bases. Humans and corn are both, roughly, around 3 billion bases.
“Wheat has about 16 billion bases. So, it’s much bigger than the human genome. The fact that it has three copies of a related 5 billion base genome that was hybridized to domestic wheat was a real technical challenge to separate those out computationally.
“The other thing that was difficult with the wheat genome is that about 80 to 90 percent is made up of repeats of a relatively small number of sequences. Those are very difficult to deal with computationally, as well.”
Did that happen because of breeding through the centuries?
“That’s an interesting question that no one really has an answer for. Theories have been floated but no one knows.”
On further agricultural research at the lab…
“We’re continuing with wheat research, having recently completed the sequencing on a couple of other related subspecies. Those include durum wheat and we’re just now working on the computational side of that.
“We want to improve the view of the wheat genome. This is a very valuable first step but it isn’t at the same level of precision as, say, the corn genome.
“We also have an ongoing (collaborative) project to study the evolution of very primitive plants. That has implications for seed development and understanding that process.”
“We put all the data from my lab in a public database. Anyone can access it freely and I’m a big proponent of that. It drives the field ahead for everyone because no one is smart enough to figure everything out.
“Our lab has millions of dollars worth of sequencing instruments. Other labs don’t have that but do have really smart people who can use data we provide to work on something we haven’t thought of.”