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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