Stable quantitative trait loci (QTL) are important for deployment in marker assisted selection in wheat (Triticum aestivum L.) and other crops. We reported QTL discovery in wheat using a population ...of 217 recombinant inbred lines and multiple statistical approach including multi-environment, multi-trait and epistatic interactions analysis. We detected nine consistent QTL linked to different traits on chromosomes 1A, 2A, 2B, 5A, 5B, 6A, 6B and 7A. Grain yield QTL were detected on chromosomes 2B.1 and 5B across three or four models of GenStat, MapQTL, and QTLNetwork while the QTL on chromosomes 5A.1, 6A.2, and 7A.1 were only significant with yield from one or two models. The phenotypic variation explained (PVE) by the QTL on 2B.1 ranged from 3.3-25.1% based on single and multi-environment models in GenStat and was pleiotropic or co-located with maturity (days to heading) and yield related traits (test weight, thousand kernel weight, harvest index). The QTL on 5B at 211 cM had PVE range of 1.8-9.3% and had no significant pleiotropic effects. Other consistent QTL detected in this study were linked to yield related traits and agronomic traits. The QTL on 1A was consistent for the number of spikes m-2 across environments and all the four analysis models with a PVE range of 5.8-8.6%. QTL for kernels spike-1 were found in chromosomes 1A, 2A.1, 2B.1, 6A.2, and 7A.1 with PVE ranged from 5.6-12.8% while QTL for thousand kernel weight were located on chromosomes 1A, 2B.1, 5A.1, 6A.2, 6B.1 and 7A.1 with PVEranged from 2.7-19.5%. Among the consistent QTL, five QTL had significant epistatic interactions (additive × additive) at least for one trait and none revealed significant additive × additive × environment interactions. Comparative analysis revealed that the region within the confidence interval of the QTL on 5B from 211.4-244.2 cM is also linked to genes for aspartate-semialdehyde dehydrogenase, splicing regulatory glutamine/lysine-rich protein 1 isoform X1, and UDP-glucose 6-dehydrogenase 1-like isoform X1. The stable QTL could be important for further validation, high throughput SNP development, and marker-assisted selection (MAS) in wheat.
Wheat is a cool seasoned crop requiring low temperature during grain filling duration and therefore increased temperature causes significant yield reduction. A set of 125 spring wheat genotypes from ...International Maize and Wheat Improvement Centre (CIMMYT-Mexico) was evaluated for phenological and yield related traits at three locations in Pakistan under normal sowing time and late sowing time for expose to prolonged high temperature. With the help of genome-wide association study using genotyping-by-sequencing, marker trait associations (MTAs) were observed separately for the traits under normal and late sown conditions.
Significant reduction ranging from 9 to 74% was observed in all traits under high temperature. Especially 30, 25, 41 and 66% reduction was observed for days to heading (DH), plant height (PH), spikes per plant (SPP) and yield respectively. We identified 55,954 single nucleotide polymorphisms (SNPs) using genotyping by sequencing of these 125 hexaploid spring wheat genotypes and conducted genome-wide association studies (GWAS) for days to heading (DH), grain filled duration (GFD), plant height (PH), spikes per plant (SPP), grain number per spike (GNS), thousand kernel weight (TKW) and grain yield per plot (GY). Genomic regions identified through GWAS explained up to 13% of the phenotypic variance, on average. A total of 139 marker-trait associations (MTAs) across three wheat genomes (56 on genome A, 55 on B and 28 on D) were identified for all the seven traits studied. For days to heading, 20; grain filled duration, 21; plant height, 23; spikes per plant, 13; grain numbers per spike, 8; thousand kernel weight, 21 and for grain yield, 33 MTAs were detected under normal and late sown conditions.
This study identifies the essential resource of genetics research and underpins the chromosomal regions of seven agronomic traits under normal and high temperature. Significant relationship was observed between the number of favored alleles and trait observations. Fourteen protein coding genes with their respective annotations have been searched with the sequence of seven MTAs which were identified in this study. These findings will be helpful in the development of a breeder friendly platform for the selection of high yielding wheat lines at high temperature areas.
Two drought-tolerant wheat cultivars, 'TAM 111' and 'TAM 112', have been widely grown in the Southern Great Plains of the U.S. and used as parents in many wheat breeding programs worldwide. This ...study aimed to reveal genetic control of yield and yield components in the two cultivars under both dryland and irrigated conditions. A mapping population containing 124 F5:7 recombinant inbred lines (RILs) was developed from the cross of TAM 112/TAM 111. A set of 5,948 SNPs from the wheat 90K iSelect array and double digest restriction-site associated DNA sequencing was used to construct high-density genetic maps. Data for yield and yield components were obtained from 11 environments. QTL analyses were performed based on 11 individual environments, across all environments, within and across mega-environments. Thirty-six unique consistent QTL regions were distributed on 13 chromosomes including 1A, 1B, 1D, 2A, 2D, 3D, 4B, 4D, 6A, 6B, 6D, 7B, and 7D. Ten unique QTL with pleiotropic effects were identified on four chromosomes and eight were in common with the consistent QTL. These QTL increased dry biomass grain yield by 16.3 g m-2, plot yield by 28.1 g m-2, kernels spike-1 by 0.7, spikes m-2 by 14.8, thousand kernel weight by 0.9 g with favorable alleles from either parent. TAM 112 alleles mainly increased spikes m-2 and thousand kernel weight while TMA 111 alleles increased kernels spike-1, harvest index and grain yield. The saturated genetic map and markers linked to significant QTL from this study will be very useful in developing high throughput genotyping markers for tracking the desirable haplotypes of these important yield-related traits in popular parental cultivars.
Scour is the most significant threat to waterways because it leads to the failure of bridge piers and other structural components. When a collar is put in place around the pier to lessen the direct ...effect of the downflow on the streambed, the maximum scour depth and velocity rate are reduced. Due to simplicity of a collar implementation around existing bridge piers and the protection of the body of bridge piers. The current paper aimed to test a collar as a flow-altering countermeasure by examining the effect of collars width and elevation on scour reduction around a rectangular pier. The results showed that the collar at higher level of piers have reduced the maximum scour depth by up to 45%, increased the scour hole's volume and planning area is upstream of the pier. Additionally, in order to calculate the maximum scour depth upstream of piers, an empirical formula was created.
Wheat cultivars 'TAM 111' and 'TAM 112' have been dominantly grown in the Southern U.S. Great Plains for many years due to their high yield and drought tolerance. To identify the molecular basis and ...genetic control of drought tolerance in these two landmark cultivars, RNA-seq analysis was conducted to compare gene expression difference in flag leaves under fully irrigated (wet) and water deficient (dry) conditions. A total of 2254 genes showed significantly altered expression patterns under dry and wet conditions in the two cultivars. TAM 111 had 593 and 1532 dry-wet differentially expressed genes (DEGs), and TAM 112 had 777 and 1670 at heading and grain-filling stages, respectively. The two cultivars have 1214 (53.9%) dry-wet DEGs in common, which agreed with their excellent adaption to drought, but 438 and 602 dry-wet DEGs were respectively shown only in TAM 111 and TAM 112 suggested that each has a specific mechanism to cope with drought. Annotations of all 2254 genes showed 1855 have functions related to biosynthesis, stress responses, defense responses, transcription factors and cellular components related to ion or protein transportation and signal transduction. Comparing hierarchical structure of biological processes, molecule functions and cellular components revealed the significant regulation differences between TAM 111 and TAM 112, particularly for genes of phosphorylation and adenyl ribonucleotide binding, and proteins located in nucleus and plasma membrane. TAM 112 showed more active than TAM 111 in response to drought and carried more specific genes with most of them were up-regulated in responses to stresses of water deprivation, heat and oxidative, ABA-induced signal pathway and transcription regulation. In addition, 258 genes encoding predicted uncharacterized proteins and 141 unannotated genes with no similar sequences identified in the databases may represent novel genes related to drought response in TAM 111 or TAM 112. This research thus revealed different drought-tolerance mechanisms in TAM 111 and TAM 112 and identified useful drought tolerance genes for wheat adaption. Data of gene sequence and expression regulation from this study also provided useful information of annotating novel genes associated with drought tolerance in the wheat genome.
Salinity is a leading threat to crop growth throughout the world. Salt stress induces altered physiological processes and several inhibitory effects on the growth of cereals, including wheat ...(Triticum aestivum L.). In this study, we determined the effects of salinity on five spring and five winter wheat genotypes seedlings. We evaluated the salt stress on root and shoot growth attributes, i.e., root length (RL), shoot length (SL), the relative growth rate of root length (RGR-RL), and shoot length (RGR-SL). The ionic content of the leaves was also measured. Physiological traits were also assessed, including stomatal conductance (gs), chlorophyll content index (CCI), and light-adapted leaf chlorophyll fluorescence, i.e., the quantum yield of photosystem II (Fv′/Fm′) and instantaneous chlorophyll fluorescence (Ft). Physiological and growth performance under salt stress (0, 100, and 200 mol/L) were explored at the seedling stage. The analysis showed that spring wheat accumulated low Na+ and high K+ in leaf blades compared with winter wheat. Among the genotypes, Sakha 8, S-24, W4909, and W4910 performed better and had improved physiological attributes (gs, Fv′/Fm′, and Ft) and seedling growth traits (RL, SL, RGR-SL, and RGR-RL), which were strongly linked with proper Na+ and K+ discrimination in leaves and the CCI in leaves. The identified genotypes could represent valuable resources for genetic improvement programs to provide a greater understanding of plant tolerance to salt stress.
Key message
Greenbug and Hessian fly are important pests that decrease wheat production worldwide. We developed and validated breeder-friendly KASP markers for marker-assisted breeding to increase ...selection efficiency.
Greenbug (
Schizaphis graminum
Rondani) and Hessian fly
Mayetiola destructor
(Say) are two major destructive insect pests of wheat (
Triticum aestivum
L.) throughout wheat production regions in the USA and worldwide. Greenbug and Hessian fly infestation can significantly reduce grain yield and quality. Breeding for resistance to these two pests using marker-assisted selection (MAS) is the most economical strategy to minimize losses. In this study, doubled haploid lines from the Synthetic W7984 × Opata M85 wheat reference population were used to construct linkage maps for the greenbug resistance gene
Gb7
and the Hessian fly resistance gene
H32
with genotyping-by-sequencing (GBS) and 90K array-based single nucleotide polymorphism (SNP) marker data. Flanking markers were closely linked to
Gb7
and
H32
and were located on chromosome 7DL and 3DL, respectively.
Gb7
-linked markers (synopGBS773 and synopGBS1141) and
H32
-linked markers (synopGBS901 and IWB65911) were converted into Kompetitive Allele Specific PCR (KASP) assays for MAS in wheat breeding. In addition, comparative mapping identified syntenic regions in
Brachypodium distachyon
, rice (
Oryza sativa
), and sorghum (
Sorghum bicolor
) for
Gb7
and
H32
that can be used for fine mapping and map-based cloning of the genes. The KASP markers developed in this study are the first set of SNPs tightly linked to
Gb7
and
H32
and will be very useful for MAS in wheat breeding programs and future genetic studies of greenbug and Hessian fly resistance.
•Unmanned Aerial Vehicle (UAV) was able to assess foliage disease severity in wheat.•Image processing and plot level data extraction framework was developed.•UAV can be used as a high-throughput ...phenotyping system.
One of the major goals in all wheat (Triticum aestivum L.) breeding programs is to develop disease-resistant varieties. Unmanned Aerial Vehicles (UAVs) equipped with remote sensors can provide spectral measurements that can be used to assess foliage disease severity. Measurement of disease severity trait during the genotype selection process has always been challenging as it takes a substantial amount of time, cost, and labor to phenotype many breeding lines. This study investigates the potential use of low-cost UAV, equipped with digital cameras as a field phenotyping tool for foliage disease severity in awheat breeding program. A field experiment was conducted in 2017 and 2018 at Castroville, Texas. The experiment site has favorable weather conditions for developing wheat leaf rust (Puccinia triticina f. sp.tritici). Red, Green, and Blue band (RGB) images were acquired by flying rotary-wing UAV. Images were then processed to develop orthomosaics and three vegetation indices were calculated. The obtained image dataset was further processed to generate plot-level data. Visual notes on field response and leaf rust severity were taken to calculate the coefficient of infection (CI). A significant variation in vegetation indices was found among the wheat genotypes in both years. Normalized Difference Index (NDI), Green Index (GI), and Green Leaf Index (GLI) were linearly related to CI with R2 values ranging from 0.72 to 0.79 (p < 0.05) in 2017 and 0.63 to 0.68 (p < 0.05) in 2018. Ground-based Normalized Difference Vegetation Indices (NDVI) also showed a significant relationship with CI in both years (R2 = 0.86, p < 0.05 in 2017 and R2 = 0.83, p < 0.05 in 2018). The results showed that UAVs imaging and automated data extraction can facilitate the acquisition of high throughput phenotyping data for disease severity ratings.
Hybrid wheat (Triticum aestivum L.) offers promises to break the yield stagnation in global wheat productivity as a result of heterosis. But, for this promise to be realized, the level of heterosis ...must be adequate. To test this, elite winter wheat lines from the breeding programs of the University of Nebraska–Lincoln (UNL) and Texas A&M University (TAMU) were crossed in a 25‐by‐25 full‐diallel design using a chemical hybridizing agent (CHA) to produce experimental hybrids. These hybrids were planted in a modified augmented design with commercial checks and parents at McGregor, TX, in 2016 (n = 612) and Greenville and Bushland, TX, in 2017 (n = 470) to evaluate for yield heterosis and combining ability. A subset of hybrids (n = 333) were repeated between years. The effect of field heterogeneity in grain yield was corrected by spatial modelling in ASReml‐R. Commercial heterosis ranged from −78.3 to 20.4% in 2016 and −32.9 to 6.2% in 2017. High‐parent heterosis (HPH) ranged from −70.4 to 54.3% in 2016 and −26.9 to 29.2% in 2017. General combining ability (GCA) variance was significantly higher than zero, whereas specific combining ability (SCA) variance was not. Significant maternal effect was identified in some crosses tested by computing reciprocal effects between crosses and estimating variances. This indicates that most of the heterosis is due to additive rather than dominance effect. These results suggest exploitation of GCA for higher yield while underscoring the need for development of heterotic pools to maximize SCA and dominance effects.
Hessian fly (Mayetiola destructor) is a worldwide pest of wheat (Triticum spp.) causing significant yield losses. Utilizing resistant varieties of wheat is the most effective method of control, ...particularly in mild climates. The effectiveness of resistance genes is lost over time due to genetic diversity within fly populations, and most cultivars have only one resistance gene making them vulnerable to this loss of resistance. Thirty‐seven resistance genes have been mapped along with four Hessian fly response genes and 11 novel quantitative trait loci (QTL). The majority of these exhibit antibiotic resistance, but new research suggests two or more novel QTL are associated with a valuable tolerant response. Studies suggest that fitness costs associated with resistance can be overcome after the initial infestation, but this may not hold true with repeated fly attacks and should be considered when pyramiding genes. Several of these genes do show temperature sensitivity, which should also be considered during breeding. Resistance mechanisms include increased levels of salicylic acid, upregulation of oxo‐phytodienoic acid reductase genes and genes responsible for lipid and protein mobilization, and increased synthesis of polyphenols, among others. These mechanisms are part of an effector‐triggered response. Resistant genes and QTL with KASP markers for use in creating gene pyramids include QHf.hwwg‐6BS, Qhara.icd‐6B, h4, H7, H32, H33, H34, H35, and H36. GWAS has been used to screen large numbers of elite breeding lines for resistance to Hessian fly. Marker trait associations discovered through GWAS can potentially be used in creating gene pyramids with multiple pest and pathogen resistance genes.
Core Ideas
Relatively untapped sources of Hessian fly resistance in wheat include parasitoids, tolerance, and antixenosis.
Resistance mechanisms are based on effector‐triggered immunity and appear to be gene specific in some cases.
Resistance and response genes have been mapped to the A, B, and D genome with a distinct cluster on 1A.
Validated kompetitive allele‐specific PCR (KASP) markers for use in marker‐assisted selection (MAS) are available for QHf.hwwg‐6BS, Qhara.icd‐6B, H32, H34, H35, and H36.
A better understanding of fitness costs, temperature sensitivity, and gene pyramid use for pest resistance is needed.
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