Populations of doubled haploids for genetic mapping in hexaploid winter triticale

To create a framework for genetic dissection of hexaploid triticale, six populations of doubled haploid (DH) lines were developed from pairwise hybrids of high-yielding winter triticale cultivars. The six populations comprise between 97 and 231 genotyped DH lines each, totaling 957 DH lines. A consensus genetic map spans 4593.9 cM is composed of 1576 unique DArT markers. The maps reveal several structural rearrangements in triticale genomes. In preliminary tests of the populations and maps, markers specific to wheat segments of the engineered rye chromosome 1R (RM1B) were identified. Example QTL mapping of days to heading in cv. Krakowiak revealed loci on chromosomes 2BL and 2R responsible for extended vernalization requirement, and candidate genes were identified. The material is available to all parties interested in triticale genetics.     

Genetic mapping of a major gene in triticale conferring resistance to bacterial leaf streak

Key message

A major gene conferring resistance to bacterial leaf streak was mapped to chromosome 5R in triticale.

Abstract

Bacterial leaf streak (BLS), caused by Xanthomonas translucens pv. undulosa (Xtu), is an important disease of wheat and triticale around the world. Although resistance to BLS is limited in wheat, several triticale accessions have high levels of resistance. To characterize the genetic basis of this resistance, we developed triticale mapping populations using a resistant accession (Siskiyou) and two susceptible accessions (UC38 and Villax St. Jose). Bulked segregant analysis in an F₂ population derived from the cross of Siskiyou × UC38 led to the identification of a simple sequence repeat (SSR) marker (XSCM138) on chromosome 5R that co-segregated with the resistance gene. The cross of Siskiyou × Villax St. Jose was advanced into an F_2:5 recombinant inbred line population and evaluated for BLS reaction. Genetic linkage maps on this population were assembled with markers generated using genotyping-by-sequencing as well as several SSR markers previously identified on 5R. Quantitative trait locus (QTL) mapping revealed a single major QTL on chromosome 5R, underlined by the same SSR marker as in the Siskiyou × UC38 population. The F₁ hybrids of the two crosses were highly resistant to BLS, indicating that resistance is largely dominant. This work will facilitate introgression of this rye-derived BLS resistance gene into the wheat genome by molecular marker-mediated chromosome engineering.

     

Bridging the genotyping gap: using genotyping by sequencing (GBS) to add high-density SNP markers and new value to traditional bi-parental mapping and breeding populations

Genotyping by sequencing (GBS) is the latest application of next-generation sequencing protocols for the purposes of discovering and genotyping SNPs in a variety of crop species and populations. Unlike other high-density genotyping technologies which have mainly been applied to general interest “reference” genomes, the low cost of GBS makes it an attractive means of saturating mapping and breeding populations with a high density of SNP markers. One barrier to the widespread use of GBS has been the difficulty of the bioinformatics analysis as the approach is accompanied by a high number of erroneous SNP calls which are not easily diagnosed or corrected. In this study, we use a 384-plex GBS protocol to add 30,984 markers to an indica (IR64) × japonica (Azucena) mapping population consisting of 176 recombinant inbred lines of rice (Oryza sativa) and we release our imputation and error correction pipeline to address initial GBS data sparsity and error, and streamline the process of adding SNPs to RIL populations. Using the final imputed and corrected dataset of 30,984 markers, we were able to map recombination hot and cold spots and regions of segregation distortion across the genome with a high degree of accuracy, thus identifying regions of the genome containing putative sterility loci. We mapped QTL for leaf width and aluminum tolerance, and were able to identify additional QTL for both phenotypes when using the full set of 30,984 SNPs that were not identified using a subset of only 1,464 SNPs, including a previously unreported QTL for aluminum tolerance located directly within a recombination hotspot on chromosome 1. These results suggest that adding a high density of SNP markers to a mapping or breeding population through GBS has a great value for numerous applications in rice breeding and genetics research.     

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.     

Identification of a major QTL allele from wild soybean (Glycine soja Sieb. & Zucc.) for increasing alkaline salt tolerance in soybean

Salt-affected soils are generally classified into two main categories, sodic (alkaline) and saline. Our previous studies showed that the wild soybean accession JWS156-1 (Glycine soja) from the Kinki area of Japan was tolerant to NaCl salt, and the quantitative trait locus (QTL) for NaCl salt tolerance was located on soybean linkage group N (chromosome 3). Further investigation revealed that the wild soybean accession JWS156-1 also had a higher tolerance to alkaline salt stress. In the present study, an F₆ recombinant inbred line mapping population (n = 112) and an F₂ population (n = 149) derived from crosses between a cultivated soybean cultivar Jackson and JWS156-1 were used to identify QTL for alkaline salt tolerance in soybean. Evaluation of soybean alkaline salt tolerance was carried out based on salt tolerance rating (STR) and leaf chlorophyll content (SPAD value) after treatment with 180 mM NaHCO₃ for about 3 weeks under greenhouse conditions. In both populations, a significant QTL for alkaline salt tolerance was detected on the molecular linkage group D2 (chromosome 17), which accounted for 50.2 and 13.0% of the total variation for STR in the F₆ and the F₂ populations, respectively. The wild soybean contributed to the tolerance allele in the progenies. Our results suggest that QTL for alkaline salt tolerance is different from the QTL for NaCl salt tolerance found previously in this wild soybean genotype. The DNA markers closely associated with the QTLs might be useful for marker-assisted selection to pyramid tolerance genes in soybean for both alkaline and saline stresses.     

Fine mapping of a preharvest sprouting QTL interval on chromosome 2B in white wheat

Key message

Fine mapping by recombinant backcross populations revealed that a preharvest sprouting QTL on 2B contained two QTLs linked in coupling with different effects on the phenotype.

Abstract

Wheat preharvest sprouting (PHS) occurs when grain germinates on the plant before harvest, resulting in reduced grain quality. Previous mapping of quantitative trait locus (QTL) revealed a major PHS QTL, QPhs.cnl-2B.1, located on chromosome 2B significant in 16 environments that explained from 5 to 31 % of the phenotypic variation. The objective of this project was to fine map the QPhs.cnl-2B.1 interval. Fine mapping was carried out in recombinant backcross populations (BC₁F₄ and BC₁F₅) that were developed by backcrossing selected doubled haploids to a recurrent parent and self-pollinating the BC₁F₄ and BC₁F₅ generations. In each generation, three markers in the QPhs.cnl-2B.1 interval were used to screen for recombinants. Fine mapping revealed that the QPhs.cnl-2B.1 interval contained two PHS QTLs linked in coupling. The distal PHS QTL, located between Wmc453c and Barc55, contributed 8 % of the phenotypic variation and also co-located with a major seed dormancy QTL determined by germination index. The proximal PHS QTL, between Wmc474 and CNL415-rCDPK, contributed 16 % of the variation. Several candidate genes including Mg-chelatase H subunit family protein, GTP-binding protein and calmodulin/Ca²⁺-dependent protein kinase were linked to the PHS QTL. Although many recombinant lines were identified, the lack of polymorphism for markers in the QTL interval prevented the localization of the recombination breakpoints and identification of the gene underlying the phenotype.     

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.     

Genomewide markers as cofactors for precision mapping of quantitative trait loci

In composite interval mapping of quantitative trait loci (QTL), subsets of background markers are used to account for the effects of QTL outside the marker interval being tested. Here, I propose a QTL mapping approach (called G model) that utilizes genomewide markers as cofactors. The G model involves backward elimination on a given chromosome after correcting for genomewide marker effects, calculated under a random effects model, at all the other chromosomes. I simulated a trait controlled by 15 or 30 QTL, mapping populations of N = 96, 192, and 384 recombinant inbreds, and N _M = 192 and 384 evenly spaced markers. In the C model, which utilized subsets of background markers, the number of QTL detected and the number of false positives depended on the number of cofactors used, with five cofactors being too few with N = 384 and 20–40 cofactors being too many with N = 96. A window size of 0 cM for excluding cofactors maintained the number of true QTL detected while decreasing the number of false positives. The number of true QTL detected was generally higher with the G model than with the C model, and the G model led to good control of the type I error rate in simulations where the null hypothesis of no marker–QTL linkage was true. Overall, the results indicated that the G model is useful in QTL mapping because it is less subjective and has equal, if not better, performance when compared with the traditional approach of using subsets of markers to account for background QTL.     

Comparative mapping of Raphanus sativus genome using Brassica markers and quantitative trait loci analysis for the Fusarium wilt resistance trait

Fusarium wilt (FW), caused by the soil-borne fungal pathogen Fusarium oxysporum is a serious disease in cruciferous plants, including the radish (Raphanus sativus). To identify quantitative trait loci (QTL) or gene(s) conferring resistance to FW, we constructed a genetic map of R. sativus using an F₂ mapping population derived by crossing the inbred lines ‘835’ (susceptible) and ‘B2’ (resistant). A total of 220 markers distributed in 9 linkage groups (LGs) were mapped in the Raphanus genome, covering a distance of 1,041.5 cM with an average distance between adjacent markers of 4.7 cM. Comparative analysis of the R. sativus genome with that of Arabidopsis thaliana and Brassica rapa revealed 21 and 22 conserved syntenic regions, respectively. QTL mapping detected a total of 8 loci conferring FW resistance that were distributed on 4 LGs, namely, 2, 3, 6, and 7 of the Raphanus genome. Of the detected QTL, 3 QTLs (2 on LG 3 and 1 on LG 7) were constitutively detected throughout the 2-year experiment. QTL analysis of LG 3, flanked by ACMP0609 and cnu_mBRPGM0085, showed a comparatively higher logarithm of the odds (LOD) value and percentage of phenotypic variation. Synteny analysis using the linked markers to this QTL showed homology to A. thaliana chromosome 3, which contains disease-resistance gene clusters, suggesting conservation of resistance genes between them.     

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.     

Identifying a Major QTL Associated with Salinity Tolerance in Nile Tilapia Using QTL-Seq

Selection of new lines with high salinity tolerance allows for economically feasible production of tilapias in brackish water areas. Mapping QTLs and identifying the markers linked to salinity-tolerant traits are the first steps in the improvement of the tolerance in tilapia through marker-assisted selection techniques. By using QTL-seq strategy and linkage-based analysis, two significant QTL intervals (chrLG4 and chrLG18) on salinity-tolerant traits were firstly identified in the Nile tilapia. Fine mapping with microsatellite and SNP markers suggested a major QTL region that located at 23.0 Mb of chrLG18 and explained 79% of phenotypic variation with a LOD value of 95. Expression analysis indicated that at least 10 genes (e.g., LACTB2, KINH, NCOA2, DIP2C, LARP4B, PEX5R, and KCNJ9) near or within the QTL interval were significantly differentially expressed in intestines, brains, or gills under 10, 15, or 20 ppt challenges. Our findings suggest that QTL-seq can be effectively utilized in QTL mapping of salinity-tolerant traits in fish. The identified major QTL is a promising locus to improve our knowledge on the genetic mechanism of salinity tolerance in tilapia.     

Validation and high-resolution mapping of a major quantitative trait locus for alkaline salt tolerance in soybean using residual heterozygous line

Alkaline soil restricts soybean plant growth and yield. In our previous study, a major alkaline salt tolerance quantitative trait locus (QTL) was identified in soybean on chromosome 17. In this study, the residual heterozygous line (RHL46), which was selected from a population of F6 recombinant inbred lines (RILs) derived from a cross between an alkaline salt-sensitive soybean cultivar Jackson and a tolerant wild soybean accession JWS156-1, was used for validation and high-resolution mapping of the QTL. In a large segregating population (n = 1,109), which was produced by self-pollinating heterozygotes of RHL46, segregation of alkaline salt tolerance showed a continuous distribution, and the tolerant plants were predominant. Linkage mapping analysis revealed a major QTL with a large dominant effect for alkaline salt tolerance, and the highest LOD score was detected between the single sequence repeat (SSR) markers GM17-12.2 and Satt447. Furthermore, 10 fixed recombinant lines carrying chromosome fragments of different lengths in the QTL region were selected from the RHL46 progeny. Phenotype evaluation and SSR marker analysis of the recombinant lines narrowed down the QTL to a 3.33-cM interval region between the markers GM17-11.6 and Satt447 with a physical map length of approximately 771 kb. High-resolution mapping of the alkaline salt tolerance QTL will be useful not only for marker-assisted selection in soybean breeding programs but also for map-based cloning of the alkaline salt tolerance gene in order to understand alkaline salt tolerance in soybean and other plant species.     

Mapping of durable stripe rust resistance in a durum wheat cultivar Wollaroi

Wollaroi, an Australian durum wheat cultivar, produced a low stripe rust response and the alternative parent Bansi was highly susceptible. The Wollaroi/Bansi recombinant inbred line (RIL) population was phenotyped across three consecutive crop seasons. A genetic map of the Wollaroi/Bansi RIL population comprising 799 markers (diversity arrays technology and simple sequence repeat markers) was used to determine the genomic location of stripe rust resistance genes carried by the cultivar Wollaroi. Composite interval mapping detected three consistent quantitative trait loci (QTL) in chromosomes 2A, 3B and 5B. These QTL were named QYr.sun-2A, QYr.sun-3B and QYr.sun-5B. Another QTL, QYr.sun-1B, was detected only in the 2009 crop season. QTL in chromosomes 1B, 2A, 3B and 5B explained on average 6, 9.3, 26.7 and 8.7 %, respectively, of the variation in stripe rust response. All QTL were contributed by Wollaroi. RILs carrying these QTL singly produced intermediate stripe rust severities ranging from 46.2 to 55.7 %, whereas RILs with all four QTL produced the lowest disease severity (34.3 %). The consistently low stripe rust response of Wollaroi for 20 years demonstrated the durability of the resistance loci involved. The QTL combination detected in this study is being transferred to common wheat.     

Quantitative trait loci controlling aluminum tolerance in soybean: candidate gene and single nucleotide polymorphism marker discovery

Aluminum (Al) toxicity is an important abiotic stress that affects soybean production in acidic soils throughout the world. Development of Al-tolerant cultivars is an efficient and environmentally friendly solution to the problem. A previous report identified quantitative trait loci (QTL) for Al tolerance inherited from PI 416937, using restriction fragment length polymorphism markers, in a population of Young × PI 416937. The population was genotyped with 162 simple sequence repeats to enhance the power of QTL detection and enable the selection of candidate genes for functional marker development. Two QTL that explained 54 % of the phenotypic variation in root extension under Al stress conditions (HIAL) were refined on chromosomes (chr) Gm08 and Gm16. Three QTL located on chr Gm08, Gm16 and Gm19 explained 59 % of the phenotypic variation in root extension as a percent of control (PC). Two major QTL, designated qAL_HIAL_08 and qAL_PC_08, controlling HIAL and PC, respectively, were mapped to the same genomic region on chr Gm08 and inherited their favorable allele from PI 416937. These QTL explained 45 and 41 % of phenotypic variation in HIAL and PC, respectively. Six homologues for citrate synthase (CS) genes were found in the soybean genome sequence at chr Gm02, Gm08, Gm14, Gm15, and Gm18. Sixteen single nucleotide polymorphisms (SNPs) were identified in the CS homologue on chr Gm08. A SimpleProbe assay of Glyma08g42400-SNP was developed for the major QTL on chr Gm08. The SNPs identified from this region could be used for marker-assisted selection of Al tolerance.     

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 and yield components of spring wheat under contrasting moisture regimes

Key message

A stable QTL that may be used in marker-assisted selection in wheat breeding programs was detected for yield, yield components and drought tolerance-related traits in spring wheat association mapping panel.

Abstract

Genome-wide association mapping has become a widespread method of quantitative trait locus (QTL) identification for many crop plants including wheat (Triticum aestivum L.). Its benefit over traditional bi-parental mapping approaches depends on the extent of linkage disequilibrium in the mapping population. The objectives of this study were to determine linkage disequilibrium decay rate and population structure in a spring wheat association mapping panel (n = 285–294) and to identify markers associated with yield and yield components, morphological, phenological, and drought tolerance-related traits. The study was conducted under fully irrigated and rain-fed conditions at Greeley, CO, USA and Melkassa, Ethiopia in 2010 and 2011 (five total environments). Genotypic data were generated using diversity array technology markers. Linkage disequilibrium decay rate extended over a longer genetic distance for the D genome (6.8 cM) than for the A and B genomes (1.7 and 2.0 cM, respectively). Seven subpopulations were identified with population structure analysis. A stable QTL was detected for grain yield on chromosome 2DS both under irrigated and rain-fed conditions. A multi-trait region significant for yield and yield components was found on chromosome 5B. Grain yield QTL on chromosome 1BS co-localized with harvest index QTL. Vegetation indices shared QTL with harvest index on chromosome 1AL and 5A. After validation in relevant genetic backgrounds and environments, QTL detected in this study for yield, yield components and drought tolerance-related traits may be used in marker-assisted selection in wheat breeding programs.     

QTLs and epistasis for aluminum tolerance in rice (Oryza sativa L.) at different seedling stages

To investigate the genetic background for aluminum (Al) tolerance in rice, a recombinant inbred (RI) population, derived from a cross between an Al-sensitive lowland indica rice variety IR1552 and an Al-tolerant upland japonica rice variety Azucena, was used in culture solution. A molecular linkage map, together with 104 amplified fragment length polymorphism (AFLP) markers and 103 restriction fragment length polymorphism (RFLP) markers, was constructed to map quantitative trait loci (QTLs) and epistatic loci for Al tolerance based on the segregation for relative root length (RRL) in the population. RRL was measured after stress for 2 and 4 weeks at a concentration of 1mM of Al³⁺ and a control with a pH 4.0, respectively. Two QTLs were detected at both the 2nd and the 4th weeks on chromosomes 1 and 12 from unconditional mapping, while the QTL on chromosome 1 was only detected at the 2nd stress week from conditional mapping. The effect of the QTL on chromosome 12 was increased with an increase of the stress period from 2 to 4 weeks. The QTL on chromosome 1 was expressed only at the earlier stress, but its contribution to tolerance was prolonged during growth. At least one different QTL was detected at the different stress periods. Mean comparisons between marker genotypic classes indicated that the positive alleles at the QTLs were from the Al-tolerant upland rice Azucena. An important heterozygous non-allelic interaction on Al tolerance was found. The results indicated that tolerance in the younger seedlings was predominantly controlled by an additive effect, while an epistatic effect was more important to the tolerance in older seedlings; additionally the detected QTLs may be multiple allelic loci for Al tolerance and phosphorus-uptake efficiency, or for Al and Fe²⁺ tolerance. Received: 29 July 1999 / Accepted: 13 October 1999     

Quantitative trait loci mapping of adult-plant resistance to powdery mildew in triticale

Powdery mildew (PM) is a common disease caused by Blumeria graminis, which affects cereals and has recently adapted to triticale. Adult-plant resistance (APR) genes provide durable protection of crops from the disease. Quantitative trait loci corresponding to the APR effects were mapped in an F₂ population of “Lamberto” (susceptible) × “Moderto” (resistant). A genetic map of winter triticale was constructed based on the segregation of 863 DArT, 38 microsatellite and 10 resistance gene analogue markers. Composite interval mapping (CIM) was applied to identify three QTLs for maximum disease severity (MDS) and two for the area under disease progress curve (AUDPC) conferring resistance to the powdery mildew on chromosomes: 6A, 7A, 1B and 4R. The 39% variation in AUDPC was explained by the main QTL localised on chromosome 4R. Genes coding TRIUR3 proteins, serine/threonine protein kinase and cell wall associated kinases were localised in silico within the QTL and alternative DNA markers were proposed for flexible use in laboratories of diversified throughput.     

Identification and validation of QTL and their associated genes for pre-emergent metribuzin tolerance in hexaploid wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Background

Herbicide tolerance is an important trait that allows effective weed management in wheat crops. Genetic knowledge of metribuzin tolerance in wheat is needed to develop new cultivars for the industry. Here, we evaluated metribuzin tolerance in a recombinant inbred line (RIL) mapping population derived from Synthetic W7984 and Opata 85 over two consecutive years to identify quantitative trait loci (QTL) contributing to the trait. Herbicide tolerance was measured by two chlorophyll traits, SPAD chlorophyll content index (CCI) and visual senescence score (SNS). The markers associated with major QTL from Synthetic W7984, positively contributing to reduced phytotoxic effects under herbicide treatment were validated in two F_3/4 recombinant inbred populations developed from crosses of Synthetic W7984?×?Westonia and Synthetic W7984?×?Lang.

Results

Composite interval mapping (CIM) identified four QTL, two on chromosome 4A and one each on chromosomes 2D and 1A. The chromosomal position of the two QTL mapped on 4A within 10 cM intervals was refined and validated by multiple interval mapping (MIM). The major QTL affecting both measures of tolerance jointly explained 42 and 45% of the phenotypic variation by percentage CCI reduction and SNS, respectively. The identified QTL have a pure additive effect. The metribuzin tolerant allele of markers, Xgwm33 and Xbarc343, conferred lower phytotoxicity and explained the maximum phenotypic variation of 28.8 and 24.5%, respectively. The approximate physical localization of the QTL revealed the presence of five candidate genes (ribulose-bisphosphate carboxylase, oxidoreductase (rbcS), glycosyltransferase, serine/threonine-specific protein kinase and phosphotransferase) with a direct role in photosynthesis and/or metabolic detoxification pathways.

Conclusion

Metribuzin causes photo-inhibition by interrupting electron flow in PSII. Consequently, chlorophyll traits enabled the measure of high proportion of genetic variability in the mapping population. The validated molecular markers associated with metribuzin tolerance mediating QTL may be used in marker-assisted breeding to select metribuzin tolerant lines. Alternatively, validated favourable alleles could be introgressed into elite wheat cultivars to enhance metribuzin tolerance and improve grain yield in dryland farming for sustainable wheat production.