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Identification and confirmation of greenbug resistance loci in an advanced mapping population of sorghum

Published online by Cambridge University Press:  10 November 2017

SOMASHEKHAR PUNNURI  and
YINGHUA HUANG
SOMASHEKHAR PUNNURI
Affiliation:
Department of Plant Biology, Ecology and Evolution, Oklahoma State University, Stillwater, OK 74078, USA
YINGHUA HUANG*
Affiliation:
Department of Plant Biology, Ecology and Evolution, Oklahoma State University, Stillwater, OK 74078, USA USDA-ARS Plant Science Research Laboratory, 1301 N. Western Road, Stillwater, OK 74075, USA
*
*To whom all correspondence should be addressed. Email: [email protected]
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Summary

Greenbug infestations to sorghum can cause severe and above economic threshold damage in the Great Plains of the United States. The current study was conducted to identify quantitative trait loci (QTLs) and potential candidate genes residing within the QTL region responsible for greenbug resistance in an advanced mapping population. Inter-crossed populations are useful in detecting QTLs tightly linked to genetic markers with high resolution. In the current study, QTLs responsible for greenbug resistance in sorghum were mapped using an inter-cross population derived from two parents, BTx623 (greenbug-susceptible line) and PI 607900 (greenbug-resistant line). Molecular markers for 115 loci were used to construct a linkage map which eventually facilitated tagging portions of the sorghum genome regions responsible for greenbug resistance. The molecular genetic map covered all the chromosomes of sorghum with a total genome length of 963·0 cM. The advanced mapping population revealed and confirmed the location of greenbug resistance loci, which explained a high phenotypic variation from 72·9 to 80·9% of greenbug resistance. The loci for greenbug resistance were mapped to the region flanked by markers Starssbnm 93 and Starssbnm 102 on chromosome 9 with an increased allelic effect from the resistant parent. The locations of these loci were compared with a previous study on QTL analysis using an F2 mapping population. The results from the present study were in agreement with the findings in the F2 QTL analysis and identified QTLs had a better confidence interval. The markers/QTLs identified from the current study can be effectively utilized in marker-assisted selection and map-based cloning experiments.

Type
Crops and Soils Research Papers
Information
The Journal of Agricultural Science , Volume 155 , Issue 10 , December 2017 , pp. 1610 - 1622
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Copyright
Copyright © Cambridge University Press 2017 

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Footnotes

†

Present address: 1005 State University Dr., Agricultural Research Station, Fort Valley State University, Fort Valley, GA 31030, USA.

References

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