Genetic control of grain yield and grain physical characteristics in a bread wheat population grown under a range of environmental conditions

Key message

Genetic analysis of the yield and physical quality of wheat revealed complex genetic control, including strong effects of photoperiod-sensitivity loci.

Abstract

Environmental conditions such as moisture deficit and high temperatures during the growing period affect the grain yield and grain characteristics of bread wheat (Triticum aestivum L.). The aim of this study was to map quantitative trait loci (QTL) for grain yield and grain quality traits using a Drysdale/Gladius bread wheat mapping population grown under a range of environmental conditions in Australia and Mexico. In general, yield and grain quality were reduced in environments exposed to drought and/or heat stress. Despite large effects of known photoperiod-sensitivity loci (Ppd-B1 and Ppd-D1) on crop development, grain yield and grain quality traits, it was possible to detect QTL elsewhere in the genome. Some of these QTL were detected consistently across environments. A locus on chromosome 6A (TaGW2) that is known to be associated with grain development was associated with grain width, thickness and roundness. The grain hardness (Ha) locus on chromosome 5D was associated with particle size index and flour extraction and a region on chromosome 3B was associated with grain width, thickness, thousand grain weight and yield. The genetic control of grain length appeared to be largely independent of the genetic control of the other grain dimensions. As expected, effects on grain yield were detected at loci that also affected yield components. Some QTL displayed QTL-by-environment interactions, with some having effects only in environments subject to water limitation and/or heat stress.     

QTL mapping for yield and photosynthetic related traits under different water regimes in wheat

The improvement for drought tolerance requires understanding of the genetic control of wheat (Triticum aestivum L.) reaction to drought. In this study, a set of 131 recombinant inbred lines of wheat were investigated under well-watered (WW) and drought stress (DS) environments across 2 years to map quantitative trait loci (QTLs) for yield and physiological traits. A total of 225 QTLs were detected, including 32 non-environment-specific loci that were significant in both DS and WW, one drought-specific locus and two watering-specific loci. Three consistently-expressed QTLs (QTkw-3A.2, QTss-1A, and QScn-7A.1) were identified in at least three environments and the QTkw-1D.1 was significant in DS across the 2 years. By unconditional and conditional QTL analysis, spike number per plant and kernel number per spike were more important than thousand-kernel weight for grain yield (GY) at the given genetic background. Meta-analysis identified 67 meta-QTLs that contained QTLs for at least two traits. High frequency co-location of QTLs was found among either the spike-related traits or the six physiological traits. Four photosynthesis traits (CHL, LWUE, P _N, and C _i) were co-located with GY and/or yield components on various MQTLs. The results provided QTLs that warrant further study for drought tolerance breeding and are helpful for understanding the genetic basis of drought tolerance and the genetic contribution of yield components to GY at individual QTL level in wheat.     

Construction of an integrative linkage map and QTL mapping of grain yield-related traits using three related wheat RIL populations

Key message

A novel high-density consensus wheat genetic map was obtained based on three related RIL populations, and the important chromosomal regions affecting yield and related traits were specified.

Abstract

A prerequisite for mapping quantitative trait locus (QTL) is to build a genetic linkage map. In this study, three recombinant inbred line populations (represented by WL, WY, and WJ) sharing one common parental line were used for map construction and subsequently for QTL detection of yield-related traits. PCR-based and diversity arrays technology markers were screened in the three populations. The integrated genetic map contains 1,127 marker loci, which span 2,976.75 cM for the whole genome, 985.93 cM for the A genome, 922.16 cM for the B genome, and 1,068.65 cM for the D genome. Phenotypic values were evaluated in four environments for populations WY and WJ, but three environments for population WL. Individual and combined phenotypic values across environments were used for QTL detection. A total of 165 putative additive QTL were identified, 22 of which showed significant additive-by-environment interaction effects. A total of 65 QTL (51.5 %) were stable across environments, and 23 of these (35.4 %) were common stable QTL that were identified in at least two populations. Notably, QTkw-5B.1, QTkw-6A.2, and QTkw-7B.1 were common major stable QTL in at least two populations, exhibiting 11.28–16.06, 5.64–18.69, and 6.76–21.16 % of the phenotypic variance, respectively. Genetic relationships between kernel dimensions and kernel weight and between yield components and yield were evaluated. Moreover, QTL or regions that commonly interact across genetic backgrounds were discussed by comparing the results of the present study with those of previous similar studies. The present study provides useful information for marker-assisted selection in breeding wheat varieties with high yield.     

Genetic dissection of drought tolerance in chickpea (Cicer arietinum L.)

Key message

Analysis of phenotypic data for 20 drought tolerance traits in 1–7 seasons at 1–5 locations together with genetic mapping data for two mapping populations provided 9 QTL clusters of which one present on CaLG04 has a high potential to enhance drought tolerance in chickpea improvement.

Abstract

Chickpea (Cicer arietinum L.) is the second most important grain legume cultivated by resource poor farmers in the arid and semi-arid regions of the world. Drought is one of the major constraints leading up to 50 % production losses in chickpea. In order to dissect the complex nature of drought tolerance and to use genomics tools for enhancing yield of chickpea under drought conditions, two mapping populations—ICCRIL03 (ICC 4958 × ICC 1882) and ICCRIL04 (ICC 283 × ICC 8261) segregating for drought tolerance-related root traits were phenotyped for a total of 20 drought component traits in 1–7 seasons at 1–5 locations in India. Individual genetic maps comprising 241 loci and 168 loci for ICCRIL03 and ICCRIL04, respectively, and a consensus genetic map comprising 352 loci were constructed (http://cmap.icrisat.ac.in/cmap/sm/cp/varshney/). Analysis of extensive genotypic and precise phenotypic data revealed 45 robust main-effect QTLs (M-QTLs) explaining up to 58.20 % phenotypic variation and 973 epistatic QTLs (E-QTLs) explaining up to 92.19 % phenotypic variation for several target traits. Nine QTL clusters containing QTLs for several drought tolerance traits have been identified that can be targeted for molecular breeding. Among these clusters, one cluster harboring 48 % robust M-QTLs for 12 traits and explaining about 58.20 % phenotypic variation present on CaLG04 has been referred as “QTL-hotspot”. This genomic region contains seven SSR markers (ICCM0249, NCPGR127, TAA170, NCPGR21, TR11, GA24 and STMS11). Introgression of this region into elite cultivars is expected to enhance drought tolerance in chickpea.     

Genome-wide association mapping of yield components and drought tolerance-related traits in cotton

Drought causes serious yield losses in cotton production throughout the world. Association mapping allows identification and localization of the genes controlling drought-related traits which will be helpful in cotton breeding. In the present study, genetic diversity analysis and association mapping of yield and drought traits were performed on a panel of 99 upland cotton genotypes using 177 SSR (simple sequence repeat) markers. Yield parameters and drought tolerance-related traits were evaluated for two seasons under two watering regimes: water-stressed and well-watered. The traits included seed cotton yield (SCY), lint yield (LY), lint percentage (LP), water-use efficiency (WUE), yield potential (YP), yield reduction (YR), yield index (YI), drought sensitivity index (DSI), stress tolerance index (STI), harmonic mean (HM), and geometric mean productivity (GMP). The genotypes with the least change in seed cotton yield under drought stress were Zeta 2, Delcerro, Nazilli 87, and DAK 66/3 which were also the most water-use efficient cultivars. The average genetic diversity of the panel was 0.38. The linkage disequilibrium decayed relatively rapidly at 20–30 cM (r²?≥?0.5). We identified 30 different SSR markers associated with the traits. Fifteen and 23 SSR markers were linked to the traits under well-watered and water-stress conditions, respectively. To our knowledge, most of these quantitative yield and drought tolerance-associated loci were newly identified. The genetic diversity and association mapping results should facilitate the development of drought-tolerant cotton lines with high yield in molecular breeding programs.     

Multiple-line cross QTL mapping for biomass yield and plant height in triticale (× Triticosecale Wittmack)

Key message

QTL mapping in multiple families identifies trait-specific and pleiotropic QTL for biomass yield and plant height in triticale.

Abstract

Triticale shows a broad genetic variation for biomass yield which is of interest for a range of purposes, including bioenergy. Plant height is a major contributor to biomass yield and in this study, we investigated the genetic architecture underlying biomass yield and plant height by multiple-line cross QTL mapping. We employed 647 doubled haploid lines from four mapping populations that have been evaluated in four environments and genotyped with 1710 DArT markers. Twelve QTL were identified for plant height and nine for biomass yield which cross-validated explained 59.6 and 38.2 % of the genotypic variance, respectively. A major QTL for both traits was identified on chromosome 5R which likely corresponds to the dominant dwarfing gene Ddw1. In addition, we detected epistatic QTL for plant height and biomass yield which, however, contributed only little to the genetic architecture of the traits. In conclusion, our results demonstrate the potential of genomic approaches for a knowledge-based improvement of biomass yield in triticale.     

Population structure and association mapping of yield contributing agronomic traits in foxtail millet

Key message

Association analyses accounting for population structure and relative kinship identified eight SSR markers ( p < 0.01) showing significant association ( R ²  = 18 %) with nine agronomic traits in foxtail millet.

Abstract

Association mapping is an efficient tool for identifying genes regulating complex traits. Although association mapping using genomic simple sequence repeat (SSR) markers has been successfully demonstrated in many agronomically important crops, very few reports are available on marker-trait association analysis in foxtail millet. In the present study, 184 foxtail millet accessions from diverse geographical locations were genotyped using 50 SSR markers representing the nine chromosomes of foxtail millet. The genetic diversity within these accessions was examined using a genetic distance-based and a general model-based clustering method. The model-based analysis using 50 SSR markers identified an underlying population structure comprising five sub-populations which corresponded well with distance-based groupings. The phenotyping of plants was carried out in the field for three consecutive years for 20 yield contributing agronomic traits. The linkage disequilibrium analysis considering population structure and relative kinship identified eight SSR markers (p < 0.01) on different chromosomes showing significant association (R ² = 18 %) with nine agronomic traits. Four of these markers were associated with multiple traits. The integration of genetic and physical map information of eight SSR markers with their functional annotation revealed strong association of two markers encoding for phospholipid acyltransferase and ubiquitin carboxyl-terminal hydrolase located on the same chromosome (5) with flag leaf width and grain yield, respectively. Our findings on association mapping is the first report on Indian foxtail millet germplasm and this could be effectively applied in foxtail millet breeding to further uncover marker-trait associations with a large number of markers.     

QTL for resistance to root lesion nematode (Pratylenchus thornei) from a synthetic hexaploid wheat source

Key message

A whole genome average interval mapping approach identified eight QTL associated with P. thornei resistance in a DH population from a cross between the synthetic-derived wheat Sokoll and cultivar Krichauff.

Abstract

Pratylenchus thornei are migratory nematodes that feed and reproduce within the wheat root cortex, causing cell death (lesions) resulting in severe yield reductions globally. Genotypic selection using molecular markers closely linked to Pratylenchus resistance genes will accelerate the development of new resistant cultivars by reducing the need for laborious and expensive resistance phenotyping. A doubled haploid wheat population (150 lines) from a cross between the synthetic-derived cultivar Sokoll (P. thornei resistant) and cultivar Krichauff (P. thornei moderately susceptible) was used to identify quantitative trait loci (QTL) associated with P. thornei resistance. The resistance identified in the glasshouse was validated in a field trial. A genetic map was constructed using Diversity Array Technology and the QTL regions identified were further targeted with simple sequence repeat (SSR) and single-nucleotide polymorphism (SNP) markers. Six significant and two suggestive P. thornei resistance QTL were detected using a whole genome average interval mapping approach. Three QTL were identified on chromosome 2B, two on chromosome 6D, and a single QTL on each of chromosomes 2A, 2D and 5D. The QTL on chromosomes 2BS and 6DS mapped to locations previously identified to be associated with Pratylenchus resistance. Together, the QTL on 2B (QRlnt.sk-2B.1–2B.3) and 6D (QRlnt.sk-6D.1 and 6D.2) explained 30 and 48 % of the genotypic variation, respectively. Flanking PCR-based markers based on SSRs and SNPs were developed for the major QTL on 2B and 6D and provide a cost-effective high-throughput tool for marker-assisted breeding of wheat with improved P. thornei resistance.     

Variation at the vernalisation genes Vrn-H1 and Vrn-H2 determines growth and yield stability in barley (Hordeum vulgare) grown under dryland conditions in Syria

Key message

Spring growth in barley controlled by natural variation at Vrn-H1 and Vrn-H2 improved yield stability in marginal Syrian environments.

Abstract

The objective of the present study was to identify QTL influencing agronomic performance in rain-fed Mediterranean environments in a recombinant inbred line (RIL) population, ARKE derived from the Syrian barley landrace, Arta and the Australian feed cultivar, Keel. The population was field tested for agronomic performance at two locations in Syria for 4 years with two sowing dates, in autumn and winter. Genotypic variability in yield of the RIL population was mainly affected by year-to-year variation presumably caused by inter-annual differences in rainfall distribution. The spring growth habit and early flowering inherited from the Australian cultivar Keel increased plant height and biomass and improved yield stability in Syrian environments. QTL for yield and biomass coincided with the map location of flowering time genes, in particular the vernalisation genes Vrn-H1 and Vrn-H2. In marginal environments with terminal drought, the Vrn-H1 allele inherited from Keel improved final biomass and yield. Under changing climate conditions, such as shorter winters, reduced rainfall, and early summer drought, spring barley might thus outperform the traditional vernalisation-sensitive Syrian landraces. We present the ARKE population as a valuable genetic resource to further elucidate the genetics of drought adaptation of barley in the field.     

Molecular Dissection of a Genomic Region Governing Root Traits Associated with Drought Tolerance Employing a Combinatorial Approach of QTL Mapping and RNA-seq in Rice

Drought is considered as one of the major obstacles for progressive yield enhancement and stability in rice, especially in rain-fed conditions. Being a complex trait, drought is regulated by numerous quantitative trait loci (QTL), of which, however, very few underlying genes have been cloned. In the present investigation, we made an attempt to uncover the candidate gene(s) behind a major QTL, rdw8.1 governing drought tolerance traits viz., root dry weight and root length. The targeted QTL has been delimited to 366.75 kb from 10.17 Mb by QTL mapping in BC₁F₂ population. Further, the targeted region was delineated employing next-generation sequencing based RNA-seq. Based on the QTL mapping and RNA-seq approaches, the plausible candidate gene underlying the QTL region was identified as a wound inducible protein (LOC_Os08g08090). This gene can be of potential value to enhance the drought tolerance of the elite rice varieties through molecular breeding.     

Mapping resistance to the bird cherry-oat aphid and the greenbug in wheat using sequence-based genotyping

Key message

Identification of novel resistance QTL against wheat aphids. First QTL-resistance report for R. padi in wheat and chromosome 2DL for S. graminum . These sources have potential use in wheat breeding.

Abstract

The aphids Rhopalosiphum padi and Schizaphis graminum are important pests of common wheat (Triticum aestivum L.). Characterization of the genetic bases of resistance sources is crucial to facilitate the development of resistant wheat cultivars to these insects. We examined 140 recombinant inbred lines (RILs) from the cross of Seri M82 wheat (susceptible) with the synthetic hexaploid wheat CWI76364 (resistant). RILs were phenotyped for R. padi antibiosis and tolerance traits. Phenotyping of S. graminum resistance was based on leaf chlorosis in a greenhouse screening and the number of S. graminum/tiller in the field. RILs were also scored for pubescence. Using a sequence-based genotyping method, we located genomic regions associated with these resistance traits. A quantitative trait locus (QTL) for R. padi antibiosis (QRp.slu.4BL) that explained 10.2 % of phenotypic variation was found in chromosome 4BL and located 14.6 cM apart from the pubescence locus. We found no association between plant pubescence and the resistance traits. We found two QTLs for R. padi tolerance (QRp.slu.5AL and QRp.slu.5BL) in chromosomes 5AL and 5BL, with an epistatic interaction between a locus in chromosome 3AL (EnQRp.slu.5AL) and QRp.slu.5AL. These genomic regions explained about 35 % of the phenotypic variation. We re-mapped a previously reported gene for S. graminum resistance (putatively Gba) in 7DL and found a novel QTL associated with the number of aphids/tiller (QGb.slu-2DL) in chromosome 2DL. This is the first report on the genetic mapping of R. padi resistance in wheat and the first report where chromosome 2DL is shown to be associated with S. graminum resistance.     

Genetic analysis and major QTL detection for maize kernel size and weight in multi-environments

Key Message

Twelve major QTL in five optimal clusters and several epistatic QTL are identified for maize kernel size and weight, some with pleiotropic will be promising for fine-mapping and yield improvement.

Abstract

Kernel size and weight are important target traits in maize (Zea mays L.) breeding programs. Here, we report a set of quantitative trait loci (QTL) scattered through the genome and significantly controlled the performance of four kernel traits including length, width, thickness and weight. From the cross V671 (large kernel) × Mc (small kernel), 270 derived F_2:3 families were used to identify QTL of maize kernel-size traits and kernel weight in five environments, using composite interval mapping (CIM) for single-environment analysis along with mixed linear model-based CIM for joint analysis. These two mapping strategies identified 55 and 28 QTL, respectively. Among them, 6 of 23 coincident were detected as interacting with environment. Single-environment analysis showed that 8 genetic regions on chromosomes 1, 2, 4, 5 and 9 clustered more than 60 % of the identified QTL. Twelve stable major QTLs accounting for over 10 % of phenotypic variation were included in five optimal clusters on the genetic region of bins 1.02–1.03, 1.04–1.06, 2.05–2.07, 4.07–4.08 and 9.03–9.04; the addition and partial dominance effects of significant QTL play an important role in controlling the development of maize kernel. These putative QTL may have great promising for further fine-mapping with more markers, and genetic improvement of maize kernel size and weight through marker-assisted breeding.     

Genome-wide linkage mapping of yield-related traits in three Chinese bread wheat populations using high-density SNP markers

Key message

We identified 21 new and stable QTL, and 11 QTL clusters for yield-related traits in three bread wheat populations using the wheat 90 K SNP assay.

Abstract

Identification of quantitative trait loci (QTL) for yield-related traits and closely linked molecular markers is important in order to identify gene/QTL for marker-assisted selection (MAS) in wheat breeding. The objectives of the present study were to identify QTL for yield-related traits and dissect the relationships among different traits in three wheat recombinant inbred line (RIL) populations derived from crosses Doumai?×?Shi 4185 (D?×?S), Gaocheng 8901?×?Zhoumai 16 (G?×?Z) and Linmai 2?×?Zhong 892 (L?×?Z). Using the available high-density linkage maps previously constructed with the wheat 90 K iSelect single nucleotide polymorphism (SNP) array, 65, 46 and 53 QTL for 12 traits were identified in the three RIL populations, respectively. Among them, 34, 23 and 27 were likely to be new QTL. Eighteen common QTL were detected across two or three populations. Eleven QTL clusters harboring multiple QTL were detected in different populations, and the interval 15.5–32.3 cM around the Rht-B1 locus on chromosome 4BS harboring 20 QTL is an important region determining grain yield (GY). Thousand-kernel weight (TKW) is significantly affected by kernel width and plant height (PH), whereas flag leaf width can be used to select lines with large kernel number per spike. Eleven candidate genes were identified, including eight cloned genes for kernel, heading date (HD) and PH-related traits as well as predicted genes for TKW, spike length and HD. The closest SNP markers of stable QTL or QTL clusters can be used for MAS in wheat breeding using kompetitive allele-specific PCR or semi-thermal asymmetric reverse PCR assays for improvement of GY.

     

Relationships between grain protein content and grain yield components through quantitative trait locus analyses in a recombinant inbred line population derived from two elite durum wheat cultivars

Grain protein content (GPC) in durum wheat (Triticum turgidum var. durum) is negatively correlated with grain yield. To evaluate possible genetic interrelationships between GPC and grain yield per spike, thousand-kernel weight and kernel number per spike, quantitative trait loci (QTL) for GPC were mapped using GPC-adjusted data in a covariance analysis on yield components. Phenotypic data were evaluated in a segregating population of 120 recombinant inbred lines derived from crossing the elite cultivars Svevo and Ciccio. The material was tested at five environments in southern Italy. QTL were determined by composite interval mapping based on the Svevo?×?Ciccio linkage map described in Gadaleta et al. (2009) and integrated with DArT markers. The close relationship between GPC and yield components was reflected in the negative correlation between the traits and in the reduction of variance when GPC values were adjusted to yield components. Ten independent genomic regions involved in the expression of GPC were detected, six of which were associated with QTL for one or more grain yield components. QTL alleles with increased GPC effects were associated with QTL alleles with decreased effects on one or more yield component traits, or vice versa (i.e. the allelic effects were in opposite direction). Four QTL for GPC showed always significant effects, and these QTL should represent genes that influence GPC independently from variation in the yield components. Such genes are of special interest in wheat breeding since they would allow an increase in GPC without a concomitant decrease in grain yield.     

Genome-wide association analysis identified SNPs closely linked to a gene resistant to Soil-borne wheat mosaic virus

Key message

Using association and linkage mapping, two SNP markers closely linked to the SBWMV resistance gene on chromosome 5D were identified and can be used to select the gene in breeding.

Abstract

Soil-borne wheat mosaic virus (SBWMV) disease is a serious viral disease of winter wheat growing areas worldwide. SBWMV infection can significantly reduce grain yield up to 80 %. Developing resistant wheat cultivars is the only feasible strategy to reduce the losses. In this study, wheat Infinium iSelect Beadchips with 9 K wheat SNPs were used to genotype an association mapping population of 205 wheat accessions. Six new SNPs from two genes were identified to be significantly associated with the gene for SBWMV resistance on chromosome 5D. The SNPs and Xgwm469, an SSR marker that has been reported to be associated with the gene, were mapped close to the gene using F₆-derived recombinant inbred lines from the cross between a resistant parent ‘Heyne’ and a susceptible parent ‘Trego’. Two representative SNPs, wsnp_CAP11_c209_198467 and wsnp_JD_c4438_5568170, from the two linked genes in wheat were converted into KBioscience Competitive Allele-Specific Polymerase assays and can be easily used in marker-assisted selection to improve wheat resistance to SBWMV in breeding.     

Comparative QTL analysis of early short-time drought tolerance in Polish fodder and malting spring barleys

Key message

An effective approach for the further evolution of QTL markers, may be to create mapping populations for locally adapted gene pools, and to phenotype the studied trait under local conditions.

Abstract

Mapping populations of Polish fodder and malting spring barleys (Hordeum vulgare L.) were used to analyze traits describing short-time drought response at the seedlings stage. High-throughput genotyping (Diversity Array Technology (DArT) markers) and phenotyping techniques were used. The results showed high genetic diversity of the studied populations which allowed the creation of high-density linkage maps. There was also high diversity in the physiological responses of the barleys. Quantitative trait locus (QTL) analysis revealed 18 QTLs for nine physiological traits on all chromosomes except 1H in malting barley and 15 QTLs for five physiological traits on chromosomes 2H, 4H, 5H and 6H in fodder barley. Chromosomes 4H and 5H contained QTLs which explained most of the observed phenotypic variations in both populations. There was a major QTL for net photosynthetic rate in the malting barley located on chromosome 5H and two major QTLs for overall photochemical performance (PI) located on 5H and 7H. One major QTL related to photochemical quenching of chlorophyll fluorescence was located on chromosome 4H in fodder barley. Three QTL regions were common to both mapping populations but the corresponding regions explained different drought-induced traits. One region was for QTLs related to PSII photosynthetic activity stress index in malting barley, and the corresponding region in fodder barley was related to the water content stress index. These results are in accordance with previous studies which showed that different traits were responsible for drought tolerance variations in fodder and malting barleys.     

Mapping QTLs for physiological and biochemical traits related to grain yield under control and terminal heat stress conditions in bread wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

In order to detect genomic regions with different effects for some of the physiological and biochemical traits of wheat, four experiments were conducted at Research Farm of Agricultural and Natural Resources Research Center of Zabol in 2015–2016 and 2016–2017 growing seasons. The experiments were carried out using four alpha lattice designs with two replications under non-stress and terminal heat stress conditions. Plant materials used in this study included 167 recombinant inbred lines and their parents (‘SeriM82’ and ‘Babax’). Six traits including grain yield (GY), proline content (PRO), water soluble carbohydrates (WSC), maximum efficiency of photosystem II (Fv/Fm), cytoplasmic membrane stability (CMS) and chlorophyll content (CHL) were evaluated. Genetic linkage map consisted of 211 AFLP marker, 120 SSR marker and 144 DArT markers with 1864 cm length and 4.4 cm mean distance. QTL analysis was carried out using a mixed-model-based composite interval mapping (MCIM) method. By the combined analysis of normal phenotypic values, 27 additive QTLs and five pairs of epistatic effects were identified for studied traits, among which two additive and one epistatic QTL showed significant QTL?×?environment interactions. By the combined analysis of stress phenotypic values, a total of 26 QTLs with additive effects and 5 epistatic QTLs were detected, among which one additive and one epistatic QTL showed QTL?×?environment interactions. Six QTLs with major effects (QGY-2B, QGY-2D, QPro-5B, QWSC-4A, QFv/Fm-6A and QCMS-4B), which were common between two conditions could be useful for marker-assisted selection (MAS) in order to develop heat tolerant and high-performance wheat varieties.     

Identification and validation of QTL for grain yield and plant water status under contrasting water treatments in fall-sown spring wheats

Key message

Chromosome regions affecting grain yield, grain yield components and plant water status were identified and validated in fall-sown spring wheats grown under full and limited irrigation.

Abstract

Increases in wheat production are required to feed a growing human population. To understand the genetic basis of grain yield in fall-sown spring wheats, we performed a genome-wide association study (GWAS) including 262 photoperiod-insensitive spring wheat accessions grown under full and limited irrigation treatments. Analysis of molecular variance showed that 4.1% of the total variation in the panel was partitioned among accessions originally developed under fall-sowing or spring-sowing conditions, 11.7% among breeding programs within sowing times and 84.2% among accessions within breeding programs. We first identified QTL for grain yield, yield components and plant water status that were significant in at least three environments in the GWAS, and then selected those that were also significant in at least two environments in a panel of eight biparental mapping populations. We identified and validated 14 QTL for grain yield, 15 for number of spikelets per spike, one for kernel number per spike, 11 for kernel weight and 9 for water status, which were not associated with differences in plant height or heading date. We detected significant correlations among traits and colocated QTL that were consistent with those correlations. Among those, grain yield and plant water status were negatively correlated in all environments, and six QTL for these traits were colocated or tightly linked (<?1 cM). QTL identified and validated in this study provide useful information for the improvement of fall-sown spring wheats under full and limited irrigation.

     

Effect of a rye dwarfing gene on plant height,heading stage,and Fusarium head blight in triticale (×Triticosecale Wittmack)

Key message

The rye-derived dwarfing gene Ddw1 on chromosome 5R acts in triticale in considerably reducing plant height, increasing FHB severity and delaying heading stage.

Abstract

Triticale, an amphiploid hybrid between durum wheat and rye, is an European cereal mainly grown in Germany, France, Poland, and Belarus for feeding purposes. Dwarfing genes might further improve the genetic potential of triticale concerning lodging resistance and yield. However, they might have pleiotropic effects on other, agronomically important traits including Fusarium head blight. Therefore, we analyzed a population of 199 doubled haploid (DH) lines of the cross HeTi117-06 × Pigmej for plant height, heading stage, and FHB severity across 2 locations and 2 years. The most prominent QTL was detected on chromosome 5R explaining 48, 77, and 71 % of genotypic variation for FHB severity, plant height, and heading stage, respectively. The frequency of recovery in cross validation was ≥90 % for all three traits. Because the markers that detect dwarfing gene Ddw1 in rye are also in our population the most closely linked markers, we assume that this major QTL resembles Ddw1. For FHB severity two, for plant height three, and for heading stage five additional QTL were detected. Caused by the considerable genetic variation for heading stage and FHB severity within the progeny with the dwarfing allele, short-strawed, early heading and FHB-resistant lines can be developed when population size is large enough.     

Single nucleotide polymorphism tightly linked to a major QTL on chromosome 7A for both kernel length and kernel weight in wheat

Thousand-kernel weight (TKW) is one of the major components of grain yield in wheat (Triticum aestivum). Identifying major quantitative trait loci (QTLs) for TKW and developing effective markers are prerequisite for success in marker-assisted selection (MAS) to improve wheat yield through breeding. This study mapped a major QTL, designated as TaTKW-7AL, for increasing TKW on the long arm of chromosome 7A of ‘Clark’ to a 1.3-cM interval between single nucleotide polymorphism (SNP) markers IWB13913 and IWA5913. This QTL explained 19.7 % of the phenotypic variation for TKW. A QTL for increasing kernel length (KL), one of the major components of TKW, was mapped in the same interval as TaTKW-7AL, suggesting that increased TKW by the QTL in ‘Clark’ is most likely due to the increased KL. Association analysis on a diversity panel of 200 US winter wheat accessions also identified a haplotype of three SNP markers (IWB13913, IWB6693 and IWA5913) that were tightly associated with the both KL and TKW. The analysis of allele frequencies of the haplotype in the diversity panel suggested that the favorable allele of TaTKW-7AL has not been strongly selected for in practice and has potential to be used to improve grain yield in US hard winter wheat breeding. Two user-friendly flanking KASPar markers, IWB13913 and IWA5913, were developed for MAS of TaTKW-7AL.