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Finding genes faster

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Mexico
June 1, 2007

Source: CIMMYT E-News, vol 4 no. 5, May 2007

A CIMMYT research group in China has developed a better way to identify the locations of genes that contribute to quantitative traits important for breeding. It could open the way to improved crops faster for the world’s rural poor.

It’s not easy to make the connection between resource-poor farmers of the developing world and “biometricians,” as biological statisticians are known. But a new statistical methodology developed by CIMMYT and published in one of the world’s most prestigious scientific journals may help plant breeders to work more efficiently and—more importantly—to breed better crops for those farmers.

Science, art, and quantitative traits

Traditional crop breeding has been regarded almost as much as an art as a science. This is because breeders use their long, accumulated (and largely undocumented) experience to select parental plants most likely to give offspring the desired traits. But the process can be hit and miss and take many years and much expense. This is partly because breeders select simultaneously for many key traits—yield potential, disease resistance, drought tolerance, to name a few. Under those circumstance, and lacking scientific methods to choose precisely the right parental plants and progeny based on their actual genetic makeup, breeders must try to cover all bases by planting many crosses among many parents and evaluating physiological traits, either visually, through chemical analyses, or by measuring plant performance in the field.

Biotechnology has long promised to facilitate breeders’ work, specifically through methods that provide breeders with information about the crop genes associated with physiological traits of importance. That has worked fairly well to date for simple traits—say, resistance to a particular pathogen, when such resistance is governed by only one or two genes in the plant. But, as it turns out, simply-governed traits are also generally easy for breeders to select for and improve in their plots. What they really need help on are the traits that have a more complex genetic basis, such as yield potential or drought tolerance, because those traits are governed by multiple genes or because the associated genes may express themselves in many ways, depending on the environment in which the plant is grown. These are known as “quantitative traits,” and the classical Mendelian rules of inheritance, which constitute the basis of modern genetics, simply do not apply very well to them. “The fact is, after 20 years of work, breeders and molecular geneticists are still struggling with quantitative traits,” says Jonathan Crouch, Director of Genetic Resources Enhancement at CIMMYT.

Locating the genome regions that really count

Genetic researchers seek out segments of a plant’s DNA that are associated with quantitative traits; areas where there may be one important gene or a concentration of several genes that contribute to physiological traits of interest. These segments are called quantitative trait loci (QTL). Identifying QTL by a molecular signature in the DNA has been an important goal over the last two decades, to help breeders more accurately select plants likely to have the genes for desirable traits.

The most commonly used technique to identify QTL is called composite interval mapping (CIM), but it has not proven as efficient or effective a methodology as breeders had hoped. That is where CIMMYT quantitative geneticist Jiankang Wang, along with colleagues at the Chinese Academy of Agricultural Sciences (CAAS), have stepped in. In a recent paper published in the journal “Genetics”, they presented details of a way to vastly improve the CIM technique. “The newly-developed QTL mapping method and software will help breeders use genetic data from CGIAR centers and national agricultural research systems to mine novel genes, acquire more complete genetic knowledge for quantitative traits of interest, and conduct efficient genotypic selection,” says Wang. “Farmers will benefit from having higher yielding, more disease resistant, and more drought tolerant rice, maize, and wheat varieties with better grain quality.” He says the improved technique, which was tested extensively through computer simulations, outperforms CIM in accuracy and speed. This is good news to plant breeders, for whom the promise of modern genetic technologies to enhance breeding for quantitative traits has taken a long time to be fulfilled.

In fact, the CIMMYT team has written a special computer program that plant genetics specialists anywhere in the world can download and use to apply their new technique (http://www.isbreeding.net/software.html). The Crop Research Informatics Laboratory (CRIL), one of the joint programs between CIMMYT and the International Rice Research Institute (IRRI), will be one of the first facilities in the world to use the new tool. For breeders and geneticists at CIMMYT, the real impact of the effectiveness of the new techniques will come when seeds of better crops are in the hands of the farmers who need them most.

 

 

 

 

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