A PCR-based linkage map of Agrostis stolonifera and identification of QTL markers for dollar spot resistance

Honig, Josh A.; Kubik, Christine; Majewski, Martin; Poulsen, Christine; Weibel, Eric N.; Amundsen, Keenan; Warnke, Scott E.; Meyer, William A.; Bonos, Stacy A.

doi:10.1007/s11032-014-0029-z

Cited by 10 publications

(21 citation statements)

References 63 publications

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“…The linkage map used for this study is comprised of 200 simple sequence repeat (SSR) and expressed sequence tags-simple sequence repeat (EST-SSR) primer pairs that mapped 468 alleles in the progeny (Honig et al, 2014;Kubik et al, 2011). The linkage map used for this study is comprised of 200 simple sequence repeat (SSR) and expressed sequence tags-simple sequence repeat (EST-SSR) primer pairs that mapped 468 alleles in the progeny (Honig et al, 2014;Kubik et al, 2011).…”

Section: Quantitative Trait Loci Associated With Drought Tolerance Inmentioning

confidence: 99%

“…The population was developed by an intraspecific cross of a disease-resistant (L93-10) with a susceptible (7418-3) genotype of creeping bentgrass. The creeping bentgrass genetic linkage maps used for this project were created for each individual parent genotype and were developed by Honig et al (2014). Additional details regarding the parents can be found in Honig et al (2014).…”

Section: Linkage Map Creation and Plant Materialsmentioning

confidence: 99%

“…Additional details regarding the parents can be found in Honig et al (2014). For marker type designations and other groups, please refer to Honig et al (2014). The creeping bentgrass genetic linkage maps used for this project were created for each individual parent genotype and were developed by Honig et al (2014).…”

Section: Linkage Map Creation and Plant Materialsmentioning

confidence: 99%

“…Briefly, phenotypic and genomic data were entered into the MapQTL 5.0 software (Kyazma software; van Ooijen, 2004). Quantitative trait locus analysis was performed using the mean values for each phenotypic trait for each environment and year (Churchill and Doerge, 1994;Jansen and Stam, 1994;Jung et al, 1996;Lander and Botstein 1989;Zeng, 1994). Quantitative trait locus analysis was performed using the mean values for each phenotypic trait for each environment and year (Churchill and Doerge, 1994;Jansen and Stam, 1994;Jung et al, 1996;Lander and Botstein 1989;Zeng, 1994).…”

Section: Experimental Design and Statistical Analysismentioning

confidence: 99%

“…As described in Honig et al (2014), the creeping bentgrass linkage groups in numerical order 1 through 7 correspond to rice (Oryza sativa L.) chromosomes 5, 7, 1, 3, 8, and 9, 2, and 6, respectively. As described in Honig et al (2014), the creeping bentgrass linkage groups in numerical order 1 through 7 correspond to rice (Oryza sativa L.) chromosomes 5, 7, 1, 3, 8, and 9, 2, and 6, respectively.…”

Section: )mentioning

confidence: 99%

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Quantitative Trait Loci Associated with Drought Tolerance in Creeping Bentgrass

Merewitz

Belanger²,

Warnke³

et al. 2014

Crop Science

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Improvement in the drought tolerance of the cool‐season perennial grass species creeping bentgrass (Agrostis stolonifera L.) has significant value within the turfgrass industry. Understanding genomic regions associated with quantitative trait loci (QTL) such as drought tolerance will allow for advancement of breeding strategies to identify creeping bentgrass germplasm with improved abiotic stress tolerance. A multiyear and multienvironment study was performed to identify QTL in a mapping population of creeping bentgrass segregating for phenotypic traits associated with drought tolerance. Phenotypic data was collected during two growth chamber studies and 2 yr of a field trial. The phenotypic traits that were measured included turf quality (TQ), relative water content (RWC), canopy temperature depression (CTD), osmotic adjustment (OA), electrolyte leakage (EL), chlorophyll content (CHL), water use efficiency (WUE), and the normalized difference vegetative index (NDVI). Quantitative trait loci were identified for all traits on both parental maps except for OA and EL. Quantitative trait loci were found within all linkage groups except for group 2 in both parents. The linkage group areas that had QTL with a significant amount of overlapping for multiple traits and trials included linkage group 5.2, 7.1, and 7.2 on the drought tolerant parent ‘L‐93’ and groups 4.2 and 7.2 on the drought sensitive parent 7418–3. These and other QTL identified in this study have potential to be used in future studies that aim to more closely identify the genes associated with these QTL areas and for further investigation of their potential for use in marker‐assisted selection practices.

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