Suchergebnisse

Although grain yield is the most important trait for growers, milling and baking industries demand high-quality and scab-free grains for various end products. To accelerate breeding of wheat (Triticum aestivum L.) cultivars with high grain quality, genetic dissection of quality traits is necessary. Genome-wide association studies (GWAS) were conducted to identify genomic regions responsible for milling and baking quality traits in soft red winter wheat (SRWW). Seven quality traits were evaluated in two locations and 2 yr for 270 elite SRWW lines. These traits include flour yield, softness equivalent, flour protein, and four solvent (lactose, sodium carbonate, sucrose, and water) retention capacity measurements. In this study, 27,449 single nucleotide polymorphism (SNP) markers were developed by using both genotyping-by-sequencing and 90K SNP array technologies. A linear mixed model in GWAS, accounting for population structure and kinship, was fitted to identify 18 [-log(P) >= 4.0] genomic regions on 12 different chromosomes associated with the quality traits. Only one of these associations seems to be a previously identified quantitative trait locus, whereas others are novel associations. The most significant associations for quality traits were identified on chromosomes 1B, 2A, 2B, 4B, 5A, 7A, and 7D. Candidate gene searches, facilitated by the wheat genome assembly, led us to the identification of putative genes related to SRWW quality traits including fasciclin-like arabinogalactan. The results of this study can be used in developing high-quality SRWW varieties for the eastern region of the United States. ; USDA Agriculture and Food Research Initiative Competitive Grants [2011-68002-30029, 2017-67007-25939]; Virginia Tech; The Ohio State UniversityOhio State University; USDAARS Soft Wheat Quality Laboratory; Hatch Grant [IND010810] ; This project was supported by the USDA Agriculture and Food Research Initiative Competitive Grants 2011-68002-30029 (Triticeae Coordinated Agricultural Project [TCAP]) and 2017-67007-25939 (Wheat Coordinated Agricultural Project [WheatCAP]). We are grateful for financial support provided by Virginia Tech, The Ohio State University, and the USDAARS Soft Wheat Quality Laboratory. The authors would like to thank the International Wheat Genome Sequencing Consortium (IWGSC, www.wheatgenome.org) for prepublication access to IWGSC RefSeq v1.0 and annotation v1.0. The corresponding author is also thankful for the financial support from Hatch Grant no. IND010810. ; Public domain authored by a U.S. government employee

Genomic selection (GS) uses training population (TP) data to estimate the value of lines in a selection population. In breeding, the TP and selection population are often grown in different environments, which can cause low prediction accuracy when the correlation of genetic effects between the environments is low. Subsets of TP data may be more predictive than using all TP data. Our objectives were (i) to evaluate the effect of using subsets of TP data on GS accuracy between environments, and (ii) to assess the accuracy of models incorporating marker x environment interaction (MEI). Two wheat (Triticum aestivum L.) populations were phenotyped for 11 traits in independent environments and genotyped with single-nucleotide polymorphism markers. Within each population trait combination, environments were clustered. Data from one duster were used as the TP to predict the value of the same lines in the other cluster(s) of environments. Models were built using all TP data or subsets of markers selected for their effect and stability. The GS accuracy using all TP data was >0.25 for 9 of 11 traits. The between-environment accuracy was generally greatest using a subset of stable and significant markers; accuracy increased up to 48% relative to using all TP data. We also assessed accuracy using each population as the TP and the other as the selection population. Using subsets of TP data or the MEI models did not improve accuracy between populations. Using optimized subsets of markers within a population can improve GS accuracy by reducing noise in the prediction data set. ; Triticeae Coordinated Agricultural Project of the USDA National Institute of Food and Agriculture [2011-68002-30029] ; We sincerely thank the members at Dr. C. Sneller's laboratory for their help with field data collection in Ohio. Funding support was from Triticeae Coordinated Agricultural Project (2011-68002-30029) of the USDA National Institute of Food and Agriculture. ; Public domain authored by a U.S. government employee

Disease resistance is critical in soft red winter wheat (Triticum aestivum L.) cultivars. Leaf rust caused by Puccinia triticina Eriks and stripe rust caused by Puccinia striiformis Westend. f. sp. tritici Eriks. are destructive pathogens of wheat. Phenotypic data were collected at diverse locations for resistance to leaf rust (North Carolina, Texas, and Virginia) and stripe rust (Arkansas, North Carolina, Georgia, Texas, and Virginia) in a Pioneer '25R47' /'Jamestown' (P47/JT) population composed of 186 FDX5:9 recombinant inbred lines (RILs). The P47/JT RILs were geno-typed with a public 90K iSelect single-nucleotide polymorphism array. Analysis of the P47/ JT population identified two quantitative trait loci (QTL) for leaf rust resistance on chromosome 5B and two QTL for stripe rust resistance on chromosomes 3B and 6A. These QTL were associated with both infection type and disease severity. Phenotypic variation (%) explained by the putative leaf rust resistance QTL of Jamestown on 5B was as high as 22.1%. Variation explained by the putative stripe rust resistance QTL of Jamestown on 3B and 6A was as high as 11.1 and 14.3%, respectively. Introgression and pyramiding of these QTL with other genes conferring resistance to leaf and stripe rusts via marker-assisted selection will facilitate development of soft red winter wheat cultivars having more durable resistance. ; Virginia Small Grains Board; Virginia Agricultural Council; USDAUnited States Department of Agriculture (USDA) [58-6645-4-032] ; This study was supported with funding provided by the Virginia Small Grains Board and the Virginia Agricultural Council. This material is based on work supported by the USDA, under Agreement no. 58-6645-4-032. Any opinions, findings, conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the view of the USDA. The authors would like to thank the International Wheat Genome Sequencing Consortium for providing prepublication access to the IWGSC RefSeq v1.0. ; Public domain authored by a U.S. government employee

Maintaining winter wheat (Triticum aestivum L.) productivity with more efficient nitrogen (N) management will enable growers to increase profitability and reduce the negative environmental impacts associated with nitrogen loss. Wheat breeders would therefore benefit greatly from the identification and application of genetic markers associated with nitrogen use efficiency (NUE). To investigate the genetics underlying N response, two bi-parental mapping populations were developed and grown in four site-seasons under low and high N rates. The populations were derived from a cross between previously identified high NUE parents (VA05W-151 and VA09W-52) and a shared common low NUE parent, 'Yorktown.' The Yorktown x VA05W-151 population was comprised of 136 recombinant inbred lines while the Yorktown x VA09W-52 population was comprised of 138 doubled haploids. Phenotypic data was collected on parental lines and their progeny for 11 N-related traits and genotypes were sequenced using a genotyping-by-sequencing platform to detect more than 3,100 high quality single nucleotide polymorphisms in each population. A total of 130 quantitative trait loci (QTL) were detected on 20 chromosomes, six of which were associated with NUE and N-related traits in multiple testing environments. Two of the six QTL for NUE were associated with known photoperiod (Ppd-D1 on chromosome 2D) and disease resistance (FHB-4A) genes, two were reported in previous investigations, and one QTL, QNue.151-1D, was novel. The NUE QTL on 1D, 6A, 7A, and 7D had LOD scores ranging from 2.63 to 8.33 and explained up to 18.1% of the phenotypic variation. The QTL identified in this study have potential for marker-assisted breeding for NUE traits in soft red winter wheat. ; Virginia Small Grains Board ; Funding for this project was provided by the Virginia Small Grains Board (http://www.virginiagrains.com/leadership/va-small-grainsboard/) -KB and CG The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.; Funding for this project was provided by the Virginia Small Grains Board. The authors would like to thank Anthony Christopher, Jon Light, Michelle Lee, Elizabeth Hokanson, Harry Behl and William Myers for assistance collecting field data and Steve Nagle for providing technical assistance in the analysis of tissue N concentration. ; Public domain authored by a U.S. government employee

'Hilliard' (Reg. no. CV-1163, PI 676271), a soft red winter (SRW) wheat (Triticum aestivum L.) developed and tested as VA11W-108 by the Virginia Agricultural Experiment Station, was released in March 2015. Hilliard was derived from the cross '25R47'/'Jamestown'. Hilliard is widely adapted, from Texas to Ontario, Canada, and provides producers with a mid-season, medium height, awned, semi-dwarf (Rht2) cul tivar that has very high yield potential, good straw strength, and intermediate grain volume weight and quality. It expresses moderate to high levels of resistance to most diseases prevalent in the eastern United States and Ontario. In the 2016-2018 USDA-ARS Uniform SRW Wheat nurseries, Hilliard ranked first in grain yield in the southern nursery across all 3 yr (5,147-5,758 kg ha(-1)). In the uniform eastern nursery, it ranked first for grain yield in 2016 (6,159 kg ha(-1)) and 2017 (5,633 kg ha(-1)) and second in 2018 (5,515 kg ha(-1)). Grain volume weights of Hilliard were similar to overall trial averages in the uniform southern (73.4-75.2 kg hl(-1)) and eastern (70-75.8 kg hl(-1)) nurseries. Hilliard has soft grain texture with flour softness equivalent values varying from 58.1 to 61.7 g 100 g(-1). Straight grade flour yields on a Quadrumat Senior mill varied from 66.8 to 68.4 g kg(-1). Flour protein concentration varied from 7.0 to 9.1 g 100 g(-1) and gluten strength from 108 to 128 g 100 g(-1), as measured by lactic acid solvent retention capacity. Cookie spread diameter varied from 18.3 to 18.6 cm. ; U.S. Wheat and Barley Scab InitiativeUnited States Department of Agriculture (USDA) [59-0206-9-084]; Hatch Program of the National Institute of Food and Agriculture (NIFA) [59-0790-4-102]; USDA-ARS Specific Cooperative AgreementUnited States Department of Agriculture (USDA)USDA Agricultural Research Service [58-6645-00-108]; NIFATriticeae Coordinated Agricultural Project [2011-68002-30029] ; U.S. Wheat and Barley Scab Initiative, Grant/Award Number: 59-0206-9-084; Hatch Program of the National Institute of Food and Agriculture (NIFA), Grant/Award Number: 59-0790-4-102; USDA-ARS Specific Cooperative Agreement, Grant/Award Number: 58-6645-00-108; NIFATriticeae Coordinated Agricultural Project, Grant/Award Number: 2011-68002-30029 ; Public domain authored by a U.S. government employee