Focus on chickpea root rot

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Chickpea breeders are calling on new tools to build resistance to costly chickpea root-rot disease

Photo of chickpea disease Phytophthora root rot
Yorker variety affected by chickpea disease Phytophthora root rot (right) compared with a disease-free plant. PHOTO Sean Bithell, NSW DPI

Resistance to the major chickpea disease Phytophthora root rot (PRR) has been brought into focus at the genomic level, with the trait found to associate with discrete regions of the chickpea genome.

The identification of these quantitative trait loci (QTL) is an important step in the efficient breeding of chickpea varieties resistant to the costly disease, made possible by GRDC investment. It also marks a major project achievement, which has in turn led to a new, more efficient breeding approach for PRR resistance – genomic selection.

Of the top five chickpea diseases, PRR is the most severe, with an annual estimated cost of $8.2 million to the Australian chickpea industry.

Through a five-year GRDC investment, the NSW Department of Primary Industries (DPI) and the University of Adelaide (UA) have been working to identify disease resistance QTL.

Chickpea breeder Dr Kristy Hobson from NSW DPI says research by UA PhD student Amritha Amalraj suggested the source of resistance from cultivated chickpea (from the variety Yorker) and wild chickpeas may differ.

UA work also identified many QTL that have relatively small effect sizes.

The effect size – which ranges from 3.4 to 25.9 per cent – describes the extent of genetic variation explained by the QTL, suggesting the genetic control for PRR is complex.

For example, an effect size of 100 per cent would mean the QTL explains all the genetic variation observed. In contrast, with small effects, confidence that the presence of the QTL predicts the resistant phenotype is lower.

UA’s Dr Yongle (Leo) Li says marker-assisted selection uses only a few DNA markers with large effect to facilitate selection and is thus generally not suitable for selecting traits that are genetically complex (controlled by numerous genes).

“Additionally, it is very difficult to successfully ‘pyramid’ such a large number of QTL together into an adapted background using a marker-assisted backcrossing strategy.”

In contrast, genomic selection is a suitable method for incorporating a quantitative resistance trait within the breeding program.

Genomic selection uses the collective effects of all DNA markers simultaneously from across the whole genome in conjunction with phenotypic data to predict the breeding value of an untested line.

Dr Hobson explains that this tool will inform parent selection rather than marker identification. Dr Li will generate genomic estimated breeding values (GEBV) for lines, based on the phenotypic and genotypic data previously generated in the QTL mapping research, using only the genomic information.

With the cost of marker/sequencing technologies continuing to decline and the challenges associated with reliable phenotyping for PRR resistance, the implementation of genomic selection is attractive for the national chickpea-breeding program, she says.

Although a new approach in Australian chickpea breeding, it has been successfully implemented by large breeding companies and international non-profits, such as the International Maize and Wheat Improvement Center.

The use of a genomic selection approach for PRR in this GRDC-invested project will see the work extended for a year with additional investment. The project is already achieving promising results.

As a preliminary analysis, the research team has tested the prediction accuracy of the first validation set. This was done using three recombinant inbred line populations as the so-called ‘training population’.

The result was high prediction accuracy, which was otherwise not achievable with the traditional marker-assisted selection approach. Dr Li found using markers across the whole genome and applying a new model called functional BLUP, which has been formulated using genomic and phenotypic data, the GEBV of the lines had a correlation with ‘true’ phenotypes of up to 70 per cent accuracy.

These results are promising as they provide the opportunity for gains in efficiency by reducing the costs of disease screening, shorter breeding cycles and ultimately delivering to growers varieties with improved level of PRR resistance.

More information

Dr Kristy Hobson
02 6763 1174
0400 955 476
kristy.hobson@dpi.nsw.gov.au

Dr Yongle Li
08 8313 6725
yongle.li@adelaide.edu.au