|PUNNURI, SOMASHEKHAR - Oklahoma State University|
|STEETS, JANETTE - Oklahoma State University|
|WU, YANQI - Oklahoma State University|
Submitted to: Euphytica
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/3/2012
Publication Date: 5/1/2013
Citation: Punnuri, S., Huang, Y., Steets, J., Wu, Y. 2013. Developing new markers and QTL mapping for greenbug resistance in sorghum [Sorghum bicolor (L.) Moench]. Euphytica. 191(2):191-203.
Interpretive Summary: Greenbug (Schizaphis graminum Rondani) is one of the most important pests of sorghum causing substantial yield and quality losses in grain, forage and biofuel production in the United States. Thus, genetic improvement for greenbug resistance is needed for sustainable production in sorghum. In the current research, we attempted to identify to the genomic regions contributing greenbug resistance to sorghum crop. The research first involved phenotying of a mapping population (consisting of 371 individuals developed from a cross of the resistant line with a susceptible cultivar, BTx623) for greenbug resistance-related traits. At the same time, all individual plants were genotyped with 102 polymorphic SSR markers (i.e., 69 genomic and 33 EST SSRs). As a result, a linkage map spanning a total length of 729.5 cM across the genome was constructed with the SSR markers. By combinatorial analysis of the two sets of data, we have identified four major QTLs for greenbug resistance on chromosome 9 and several minor resistance loci on chromosome 3 of sorghum. In addition, 48 new SSR markers were developed during this study, which are a useful addition for sorghum genotyping and genome analysis. In summary, we report here that greenbug resistance QTLs were identified in this population and molecular markers closely linked to the resistance traits were developed in this study. The newly identified greenbug resistance loci and the related markers are useful for both identifying resistant genotypes from the sorghum germplasm pool and facilitating greenbug resistance improvement in sorghum through the marker-assisted selection method.
Technical Abstract: Greenbug is a major damaging insect to sorghum production in the United States. Among various virulent greenbug biotypes, biotype I is the most predominant and severe for sorghum. To combat with the damaging pest, greenbug resistant sources were obtained from screening sorghum germplasm collection. This experiment was conducted to identify the genomic regions contributing resistance to greenbug biotype I in a sorghum accession, PI 607900. An F2 mapping population consisting of 371 individuals developed from a cross of the resistant line with an elite cultivar, BTx623 (susceptible) were tested and scored for their response to greenbug feeding in the greenhouse. Significant differences in resistance were observed between the two parental lines and among their F2 progeny in response to greenbug feeding at 7, 10, 14, and 21 days after infestation. A linkage map spanning a total length of 729.5 cM across the genome was constructed with 102 polymorphic SSR markers (69 genomic and 33 EST SSRs). Of those microsatellite markers, 48 were newly developed during this study, which are a useful addition for sorghum genotyping and genome mapping. Single marker analysis revealed 29 markers to be significantly associated with the plant response to greenbug feeding damage. The results from interval mapping, composite interval mapping and multiple interval mapping analyses identified four major QTLs for greenbug resistance on chromosome 9. These QTLs collectively accounted for 34 to 82% of the phenotypic variance in greenbug resistance. Minor QTLs located on chromosome 3 explained 1% of the phenotypic variance in greenbug resistance. The major allele for greenbug resistance was on chromosome 9 close to receptor-like kinase Xa21-binding protein 3. These markers are useful to screen more resistant genotypes. Furthermore, the markers tagged to QTL regions can be used to enhance the sorghum breeding program for greenbug resistance through marker-assisted selection and map-based cloning.