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Wheat (Triticum aestivum L.) production is necessary for global food and nutrition security. Reducing plant height is an effective strategy to increase lodging resistance, harvest index, and eventually wheat yield. Rht8 is a gibberellic acid–sensitive reduced height (Rht) gene and has been cloned. Rht8 encodes a ribonuclease H‐like (RNHL) superfamily protein that reduces plant height without reduction in coleoptile length. High‐throughput diagnostic markers are not available for precise selection of RNHL in wheat breeding. In this study, we found that different cultivars may carry 1–3 copies of RNHLs on chromosome 2D, and only 2D carries the semi‐dwarf allele of RNHL although the wild‐type RNHL allele is detected in several other chromosomes. We developed two kompetitive allele specific PCR (KASP) markers, Rht8‐KASP‐V2 and Rht8‐KASP‐V3, based on the causal variation in RNHL. The two markers co‐segregated with plant height in a recombinant inbred population and were validated in a panel of hard winter wheat breeding lines from the 2022 Regional Germplasm Observation Nursery and Regional Performance Nursery. Rht8 has not been extensively deployed in US hard winter wheat and development of the diagnostic KASP markers will facilitate Rht8 transfer to US wheat cultivars. Core Ideas: Each cultivar carries 1–3 copies of ribonuclease H‐like domains (RNHLs) on 2D and mutations in all those copies determine Rht8 phenotype.Two kompetitive allele‐specific PCR (KASP) markers were developed for the recently cloned Rht8 gene.The two markers were diagnostic for Rht8 in a wheat diversity panel.Low Rht8 frequency in US wheat suggests high potential of using Rht8 in the United States to improve US wheat production. [ABSTRACT FROM AUTHOR]

Wheat resistance to Fusarium head blight (FHB) has often been associated with some undesirable agronomic traits. To study the relationship between wheat FHB resistance and agronomic traits, we constructed a linkage map of single nucleotide polymorphisms (SNPs) using an F6:8 population from G97252W × G97380A. The two hard winter wheat parents showed contrasts in FHB resistance, plant height (HT), heading date (HD), spike length (SL), spike compactness (SC), kernel number per spike (KNS), spikelet number per spike (SNS), thousand-grain weight (TGW) and grain size (length and width). Quantitative trait locus (QTL) mapping identified one major QTL (QFhb.hwwg-2DS) on chromosome arm 2DS for the percentage of symptomatic spikelets (PSS) in the spike, deoxynivalenol (DON) content and Fusarium damaged kernel (FDK). This QTL explained up to 71.8% of the phenotypic variation for the three FHB-related traits and overlapped with the major QTL for HT, HD, SL, KNS, SNS, TGW, and grain size. QTL on chromosome arms 2AL, 2DS, 3AL and 4BS were significant for the spike and grain traits measured. G97252W contributed FHB resistance and high SNS alleles at QFhb.hwwg-2DS, high KNS alleles at the QTL on 2AL and 2DS, and high TGW and grain size alleles at QTL on 3AL; whereas G97380A contributed high TGW and grain size alleles at the QTL on 2AL and 2DS, respectively, and the high KNS allele at the 4BS QTL. Combining QFhb.hwwg-2DS with positive alleles for spike and grain traits from other chromosomes may simultaneously improve FHB resistance and grain yield in new cultivars. [ABSTRACT FROM AUTHOR]

Wheat (Triticum aestivum L.) wild relatives are rich genetic resources for genetic improvement of wheat. The short arm of rye (Secale cereale L.) chromosome 1 (1RS) contains many beneficial genes for resistance to drought, insects, and diseases, therefore the 1RS wheat translocations have been widely used in wheat breeding programs worldwide. To facilitate marker‐assisted identification of 1RS in wheat breeding, we designed a set of Kompetitive allele‐specific polymerase chain reaction (KASP) markers to detect the translocations of 1RS with long arm from wheat chromosome 1A (1RS.1AL) and 1RS with long arm from wheat chromosome 1B (1RS.1BL) based on the sequence flanking single nucleotide polymorphisms (SNPs) generated by genotyping‐by‐sequencing (GBS) between wheat and rye panels. We identified a set of three SNP markers for diagnosis and differentiation of the two 1RS translocations in wheat. Among the three KASP markers, 1AS‐05056 is 1RS specific, and clearly separated the genotypes with 1RS (1RS.1AL and 1RS.1BL) from those without the two 1RS translocations; whereas 1AS‐29875 clearly identified the 1RS.1AL translocation and 1BS‐16654 separated 1RS.1BL from 1RS.1AL. The three new KASP markers together accurately identified the presence of 1RS translocation on either 1A or 1B chromosome in a panel of 95 representative U.S. winter wheat accessions, which were further validated in two additional U.S. hard winter wheat panels. Therefore, they can be used for routine screening of 1RS.1BL and 1RS.1AL translocation lines in wheat breeding programs. Core Ideas: 1RS, 1AS, and 1BS specific SNPs were identified by analyzing GBS‐SNPs from both wheat and rye panels.Three chromosome‐arm‐specific KASPs clearly detected the 1RS.1AL and 1RS.1BL translocations in wheat.Three KASP markers were diagnostic for 1RS.1AL and 1RS.1BL in two U.S. hard winter wheat panels. [ABSTRACT FROM AUTHOR]

In the Southern Great Plains, wheat cultivars have been selected for a combination of outstanding yield and drought tolerance as a long-term breeding goal. To understand the underlying genetic mechanisms, this study aimed to dissect the quantitative trait loci (QTL) associated with yield components and kernel traits in two wheat cultivars `TAM 112' and `Duster' under both irrigated and dryland environments. A set of 182 recombined inbred lines (RIL) derived from the cross of TAM 112/Duster were planted in 13 diverse environments for evaluation of 18 yield and kernel related traits. High-density genetic linkage map was constructed using 5,081 single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing (GBS). QTL mapping analysis detected 134 QTL regions on all 21 wheat chromosomes, including 30 pleiotropic QTL regions and 21 consistent QTL regions, with 10 QTL regions in common. Three major pleiotropic QTL on the short arms of chromosomes 2B (57.5 - 61.6 Mbps), 2D (37.1 - 38.7 Mbps), and 7D (66.0 - 69.2 Mbps) colocalized with genes Ppd-B1, Ppd-D1, and FT-D1, respectively. And four consistent QTL associated with kernel length (KLEN), thousand kernel weight (TKW), plot grain yield (YLD), and kernel spike-1 (KPS) (Qklen.tamu.1A.325, Qtkw.tamu.2B.137, Qyld.tamu.2D.3, and Qkps.tamu.6A.113) explained more than 5% of the phenotypic variation. QTL Qklen.tamu.1A.325 is a novel QTL with consistent effects under all tested environments. Marker haplotype analysis indicated the QTL combinations significantly increased yield and kernel traits. QTL and the linked markers identified in this study will facilitate future marker-assisted selection (MAS) for pyramiding the favorable alleles and QTL mapbased cloning. [ABSTRACT FROM AUTHOR]

Fusarium head blight (FHB), caused by the fungus Fusarium graminearum Schwabe is an important disease of wheat that causes severe yield losses along with serious quality concerns. Incorporating the host resistance from either wild relatives, landraces, or exotic materials remains challenging and has shown limited success. Therefore, a better understanding of the genetic basis of native FHB resistance in hard winter wheat (HWW) and combining it with major quantitative trait loci (QTLs) can facilitate the development of FHB-resistant cultivars. In this study, we evaluated a set of 257 breeding lines from the South Dakota State University (SDSU) breeding program to uncover the genetic basis of native FHB resistance in the US hard winter wheat. We conducted a multi-locus genomewide association study (ML-GWAS) with 9,321 high-quality single-nucleotide polymorphisms (SNPs). A total of six distinct marker-trait associations (MTAs) were identified for the FHB disease index (DIS) on five different chromosomes including 2A, 2B, 3B, 4B, and 7A. Further, eight MTAs were identified for Fusarium-damaged kernels (FDK) on six chromosomes including 3B, 5A, 6B, 6D, 7A, and 7B. Out of the 14 significant MTAs, 10 were found in the proximity of previously reported regions for FHB resistance in different wheat classes and were validated in HWW, while four MTAs represent likely novel loci for FHB resistance. Accumulation of favorable alleles of reported MTAs resulted in significantly lower mean DIS and FDK score, demonstrating the additive effect of FHB resistance alleles. Candidate gene analysis for two important MTAs identified several genes with putative proteins of interest; however, further investigation of these regions is needed to identify genes conferring FHB resistance. The current study sheds light on the genetic basis of native FHB resistance in the US HWW germplasm and the resistant lines and MTAs identified in this study will be useful resources for FHB resistance breeding via marker-assisted selection. [ABSTRACT FROM AUTHOR]

Powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), is a disease of global importance, and new powdery mildew resistance genes that can be directly used in cultivar development are urgently needed. A recombinant inbred line population from 'CI 17884' × 'Bainong 418' was genotyped using single nucleotide polymorphism markers generated from genotyping-by-sequencing, and evaluated for responses to Great Plains Bgt isolates OKS(14)-B-3-1 and NEI-1-3. Genetic mapping identified a powdery mildew resistance gene, designated PmBN418, on a 1BL.1RS translocation segment in Bainong 418. Given that PmBN418 conferred resistance to Bgt isolates virulent to Pm8 that resides on the chromosome arm 1RS translocated from rye (Secale cereale L.) cv. 'Petkus', PmBN418 is either a new gene or a new allele of Pm8. Phenotypic and genomic data analyses indicated segregation distortion of the powdery mildew resistance gene due to reduced transmission of the wheat (Triticum aestivum L.)-rye 1BL.1RS translocation segment from Bainong 418, while the wheat-Triticum speltoides translocation segment 7S#1 in CI 17884 was preferentially transmitted. Bainong 418, a high-yielding cultivar with good resistance to several U.S. Bgt isolates, is a useful resistance source for wheat breeding, and the availability of the Kompetitive Allele Specific PCR (KASP) marker KASP-1RS-1 makes marker-assisted introgression of PmBN418 into locally adapted cultivars feasible. [ABSTRACT FROM AUTHOR]

Integrating high-throughput phenotyping (HTP) based traits into phenomic and genomic selection (GS) can accelerate the breeding of high-yielding and climate-resilient wheat cultivars. In this study, we explored the applicability of Unmanned Aerial Vehicles (UAV)-assisted HTP combined with deep learning (DL) for the phenomic or multi-trait (MT) genomic prediction of grain yield (GY), test weight (TW), and grain protein content (GPC) in winter wheat. Significant correlations were observed between agronomic traits and HTP-based traits across different growth stages of winter wheat. Using a deep neural network (DNN) model, HTP-based phenomic predictions showed robust prediction accuracies for GY, TW, and GPC for a single location with R 2 of 0.71, 0.62, and 0.49, respectively. Further prediction accuracies increased (R 2 of 0.76, 0.64, and 0.75) for GY, TW, and GPC, respectively when advanced breeding lines from multi-locations were used in the DNN model. Prediction accuracies for GY varied across growth stages, with the highest accuracy at the Feekes 11 (Milky ripe) stage. Furthermore, forward prediction of GY in preliminary breeding lines using DNN trained on multi-location data from advanced breeding lines improved the prediction accuracy by 32% compared to single-location data. Next, we evaluated the potential of incorporating HTP-based traits in multi-trait genomic selection (MT-GS) models in the prediction of GY, TW, and GPC. MT-GS, models including UAV data-based anthocyanin reflectance index (ARI), green chlorophyll index (GCI), and ratio vegetation index 2 (RVI_2) as covariates demonstrated higher predictive ability (0.40, 0.40, and 0.37, respectively) as compared to single-trait model (0.23) for GY. Overall, this study demonstrates the potential of integrating HTP traits into DL-based phenomic or MT-GS models for enhancing breeding efficiency., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Kaushal, Gill, Billah, Khan, Halder, Bernardo, Amand, Bai, Glover, Maimaitijiang and Sehgal.)

Leaf rust, caused by Puccinia triticina Eriks., is one of the most widespread diseases of wheat and breeding for resistance is one of the most effective methods of control. Lr16 is a wheat leaf rust resistance gene (R-gene) that provides resistance at both the seedling and adult stages. Simple-sequence repeat (SSR) markers have been used to map Lr16 to the distal end of chromosome 2B. The objectives of this study were to use RNA sequencing (RNA-seq) and in silico subtraction to identify new R-gene analogs (RGAs) and use them as Lr16 markers. RNA was isolated from the susceptible wheat cultivar Thatcher (Tc) and the resistant Tc isolines TcLr10, TcLr16, TcLr21, and sequenced using Illumina technology. Using in silico subtraction, sequences from the resistant Tc isolines were aligned to a Tc reference expressed sequence tag (EST) set. Sequences not aligning to the Tc reference were assembled into contigs and analyzed using BLASTx to determine putative gene functions. Primer pairs were designed for 181 RGA sequences, of which, 137 amplified in at least one of the parents. A mapping population was developed with 165 F 2 lines from a cross between the rust-susceptible cultivar Chinese Spring (CS) and TcLr16. Two RGA markers XTaLr16_RGA266585 and XTaLr16_RGA22128 were identified that mapped proximally 1.2 and 23.8 cM from Lr16, respectively. Three SSR markers Xwmc764, Xwmc661, and Xbarc35 mapped between these two RGA markers at distances of 5.0, 10.9, and 16.1 cM from Lr16, respectively. In silico subtraction is an effective technique for isolating RGAs linked to R-genes of interest., (© 2015 The Authors.)