Low validation rate of quantitative trait loci for Gibberella ear rot resistance in European maize

Key message

Six quantitative trait loci (QTL) for Gibberella ear rot resistance in maize were tested in two different genetic backgrounds; three QTL displayed an effect in few near isogenic line pairs.

Abstract

Few quantitative trait loci (QTL) mapping studies for Gibberella ear rot (GER) have been conducted, but no QTL have been verified so far. QTL validation is prudent before their implementation into marker-assisted selection (MAS) programs. Our objectives were to (1) validate six QTL for GER resistance, (2) evaluate the QTL across two genetic backgrounds, (3) investigate the genetic background outside the targeted introgressions. Pairs of near isogenic lines (NILs) segregating for a single QTL (Qger1, Qger2, Qger10, Qger13, Qger16, or Qger21) were developed by recurrent backcross until generation BC₃S₂. Donor parents (DP) carrying QTL were backcrossed to a susceptible (UH009) and a moderately resistant (UH007) recurrent parent. MAS was performed using five SNP markers covering a region of 40 cM around each QTL. All NILs were genotyped with the MaizeSNP50 assay and phenotyped for GER severity and deoxynivalenol and zearalenone content. Traits were significantly (P < 0.001) intercorrelated. Out of 34 NIL pairs with the UH009 genetic background, three pairs showed significant differences in at least one trait for three QTL (Qger1, Qger2, Qger13). Out of 25 NIL pairs with the UH007 genetic background, five pairs showed significant differences in at least one trait for two QTL (Qger2, Qger21). However, Qger16, Qger10 and Qger13 were most likely false positives. The genetic background possibly affected NIL pairs comparisons due to linkage drag and/or epistasis with residual loci from the DP in non-target regions. In conclusion, validation rates were disappointingly low, which further indicates that GER resistance is controlled by many low-effect QTL.

     

Quantitative trait loci associated with agronomic traits and stripe rust in winter wheat mapping population using single nucleotide polymorphic markers

Heavy rain during the wheat seedling stage, drought in the flowering stage, and high temperatures with high humidity prior to harvest all contribute to substantial reductions in overall wheat yields in the Chinese province of Sichuan. In this study, we explored the effects of Rht-B1 and Yr18 in Chuannong16 (CN16) and a population derived from breeding line 30481. The population of 188 recombinant inbred lines was genotyped using an iSelect 90,000 single nucleotide polymorphism array and two functional markers for Rht-B1 and Yr18, and was phenotyped over 2 years in replicated trials. Grain yield was highly correlated with leaf color, plant height, and thousand kernel weights, and was negatively correlated with sedimentation. Plant height was positively correlated with grain yield and leaf color and negatively correlated with the number of tillers, thousand kernel weight, and sedimentation volume. In addition, sedimentation was negatively correlated with all five of the other traits (plant height, leaf color, tillers per square meter, grain yield, and thousand kernel weight) using both genetic and phenotypic correlation. The semi-dwarf allele Rht-B1b reduced plant height, grain yield, and thousand kernel weight. Yr18 did not affect stripe rust or other agronomic traits in the population examined. A total of 15 quantitative trait locii (QTLs) were identified for seven traits over 2 years, except for grain yield. One pleiotropic QTL on chromosome 4B was significantly associated with leaf color, thousand kernel weight, and plant height, but it was in different scaffolds with Rht-B1 on the physical map. We found a co-segregation SNP marker with Yr18 in our population; they were not in the same region on the physical map. This may be due to the relatively small population size and limited recombinant events in the population.     

Detection and verification of quantitative trait loci for resistance to Fusarium ear rot in maize

Fusarium ear rot caused by Fusarium verticillioides is a prevalent disease in maize which can severely reduce grain yields and quality. Identification of stable quantitative trait loci (QTL) for resistance to Fusarium ear rot is a basic prerequisite for understanding the genetic mechanism of resistance and for the use of marker-assisted selection. In this study, two hundred and ten F _2:3 families were developed from a cross between resistant inbred line BT-1 and susceptible inbred line Xi502, and were genotyped with 178 simple sequence repeat markers. The resistance of each line was evaluated in two environments by artificial inoculation using the nail-punch method. The resistance QTL were detected using the composite interval mapping method. Three QTL were detected on chromosomes 4, 5 and 10. Of them, the QTL on chromosome 4 (bin 4.05/06) had the largest resistance to Fusarium ear rot, and could explain 17.95?% of the phenotypic variation. For further verification of the QTL effect, we developed near-isogenic lines (NILs) carrying the QTL region on chromosome 4 using parental line Xi502 as the recurrent parent. In the NIL background, this QTL can increase the resistance by 33.7?C35.2?% if the resistance region is homozygous, and by 17.8?C26.5?% if the resistance region contains the heterozygous allele. The stable and significant resistance effect of the QTL on chromosome 4 lays the foundation for further marker-assisted selection and map-based cloning in maize.     

Quantitative trait loci for biofortification traits in maize grain

Detecting genes that influence biofortification traits in cereal grain could help increase the concentrations of bioavailable mineral elements in crops to solve the global mineral malnutrition problem. The aims of this study were to detect the quantitative trait loci (QTLs) for phosphorus (P), iron (Fe), zinc (Zn), and magnesium (Mg) concentrations in maize grain in a mapping population, as well as QTLs for bioavailable Fe, Zn, and Mg, by precalculating their respective ratios with P. Elemental analysis of grain samples was done by coupled plasma-optical emission spectrometry in 294 F(4) lines of a biparental population taken from field trials of over 3 years. The population was mapped using sets of 121 polymorphic markers. QTL analysis revealed 32 significant QTLs detected for 7 traits, of which some were colocalized. The Additive-dominant model revealed highly significant additive effects, suggesting that biofortification traits in maize are generally controlled by numerous small-effect QTLs. Three QTLs for Fe/P, Zn/P, and Mg/P were colocalized on chromosome 3, coinciding with simple sequence repeats marker bnlg1456, which resides in close proximity to previously identified phytase genes (ZM phys1 and phys2). Thus, we recommend the ratios as bioavailability traits in biofortification research.     

Quantitative trait loci mapping of yield and related traits using a high-density genetic map of maize

Improving grain yield is the ultimate goal of the maize-breeding programs. In this study, analyses of conditional and unconditional quantitative trait locus (QTL) and epistatic interactions were used to elucidate the genetic architecture of yield and its related traits. A total of 15 traits of a recombinant inbred line population, including yield per plant (YPP), seven ear-related traits, and seven kernel-related traits, were measured in six different environments. Based on the genetic linkage map constructed using 2091 bins as markers, 56 main-effect QTLs for these traits were identified. These QTLs were distributed across eight genomic regions (bin 1.06, bin 4.02/4.05/4.08, bin 5.04, bin 7.04, bin 8.08, and bin 9.04), within the marker intervals of 85.45–6260.66 kb, and the phenotypic variance explained ranging from 5.69 to 11.56 %. One gene (GRMZM2G168229) encoding SBP-box domain protein was located in the small interval of qKRN4-3 and may be involved in patterning of kernel row number. Seventeen conditional QTLs identified for YPP were conditioned on its related traits and explained 6.18–23.15 % of the phenotypic variance. Conditional mapping analysis revealed that qYPP4-1, qYPP6-1, and qYPP8-1 are partially influenced by YPP-related traits at the individual QTL level. Digenic epistatic analysis identified 12 digenic interactions involving 22 loci across the whole genome. In addition, conditional digenic epistatic analysis identified 14 digenic interactions involving 21 loci. This study provides valuable information for understanding the genetic relationship between YPP and related traits and constitutes the first step toward the cloning of the relevant genes.     

Quantitative trait loci controlling agronomic and biochemical traits in Cannabis sativa

Understanding the genetic basis of complex traits is a fundamental goal of evolutionary genetics. Yet, the genetics controlling complex traits in many important species such as hemp (Cannabis sativa) remain poorly investigated. Because hemp’s change in legal status with the 2014 and 2018 U.S. Federal Farm Bills, interest in the genetics controlling its numerous agriculturally important traits has steadily increased. To better understand the genetics of agriculturally important traits in hemp, we developed an F₂ population by crossing two phenotypically distinct hemp cultivars (Carmagnola and USO31). Using whole-genome sequencing, we mapped quantitative trait loci (QTL) associated with variation in numerous agronomic and biochemical traits. A total of 69 loci associated with agronomic (34) and biochemical (35) trait variation were identified. We found that most QTL co-localized, suggesting that the phenotypic distinctions between Carmagnola and USO31 are largely controlled by a small number of loci. We identified TINY and olivetol synthase as candidate genes underlying co-localized QTL clusters for agronomic and biochemical traits, respectively. We functionally validated the olivetol synthase candidate by expressing the alleles in yeast. Gas chromatography-mass spectrometry assays of extracts from these yeast colonies suggest that the USO31 olivetol synthase is functionally less active and potentially explains why USO31 produces lower cannabinoids compared to Carmagnola. Overall, our results help modernize the genomic understanding of complex traits in hemp.     

Quantitative trait loci for agronomic traits in an elite barley population for Mediterranean conditions

Advances in plant breeding through marker-assisted selection (MAS) are only possible when genes or quantitative trait loci (QTLs) can contribute to the improvement of elite germplasm. A population of recombinant inbred lines (RILs) was developed for one of the best crosses of the Spanish National Barley Breeding Program, between two six-row winter barley cultivars Orria and Plaisant. The objective of this study was to identify favourable QTLs for agronomic traits in this population, which may help to optimise breeding strategies for these and other elite materials for the Mediterranean region. A genetic linkage map was developed for 217 RILs, using 382 single nucleotide polymorphism markers, selected from the barley oligonucleotide pool assay BOPA1 and two genes. A subset of 112 RILs was evaluated for several agronomic traits over a period of 2 years at three locations, Lleida and Zaragoza (Spain) and Fiorenzuola d’Arda (Italy), for a total of five field trials. An important segregation distortion occurred during population development in the region surrounding the VrnH1 locus. A QTL for grain yield and length of growth cycle was also found at this locus, apparently linked to a differential response of the VrnH1 alleles to temperature. A total of 33 QTLs was detected, most of them for important breeding targets such as plant height and thousand-grain weight. QTL × environment interactions were prevalent for most of the QTLs detected, although most interactions were of a quantitative nature. Therefore, QTLs suitable for MAS for most traits were identified.     

Quantitative trait loci for partial resistance to Aphanomyces root rot in pea

Aphanomyces root rot, caused by Aphanomyces euteiches Drechs, is the most-important disease of pea ( Pisum sativum L.) worldwide. No efficient chemicals are available to control the pathogen. To facilitate breeding for Aphanomyces root rot resistance and to better understand the inheritance of partial resistance, our goal was to identify QTLs associated with field partial resistance. A population of 127 RILs from the cross Puget (susceptible) x 90-2079 (partially resistant) was used. The lines were assessed for resistance to A. euteiches under field conditions at two locations in the United States (Pullman, Wash. and LeSueur, Minn.) in 1996 and 1998 for three criteria based on symptom intensity and disease effects on the whole plant. The RILs were genotyped using automated AFLPs, RAPDs, SSRs, ISSRs, STSs, isozymes and morphological markers. The resulting genetic map consisted of 324 linked markers distributed over 13 linkage groups covering 1,094 cM (Kosambi). Twenty seven markers were anchored to other published pea genetic maps. A total of seven genomic regions were associated with Aphanomyces root rot resistance. The first one, located on LG IVb and named Aph1, was considered as "major" since it was highly consistent over the years, locations and resistance criteria studied, and it explained up to 47% of the variation in the 1998 Minnesota trial. Two other year-specific QTLs, namely Aph2 and Aph3, were revealed from different scoring criteria on LG V and Ia, respectively. Aph2 and Aph3 mapped near the r (wrinkled/round seeds) and af (normal/afila leaves) genes, and accounted for up to 32% and 11% of the variation, respectively. Four other "minor" QTLs, identified on LG Ib, VII and B, were specific to one environment and one resistance criterion. The resistance alleles of Aph3 and the two "minor" QTLs on LG Ib were derived from the susceptible parent. Flanking markers for the major Aphanomyces resistance QTL, Aph1, have been identified for use in marker-assisted selection to improve breeding efficiency.     

Mapping quantitative trait loci (QTLs) for resistance to Gibberella zeae infection in maize

The basic prerequisite for an efficient breeding program to improve levels of resistance to pathogens in plants is the identification of genes controlling the resistance character. If the response to pathogens is under the control of a multilocus system, the utilization of molecular markers becomes essential. Stalk and ear rot caused by Gibberella zeae is a widespread disease of corn: resistance to G. zeae is quantitatively inherited. Our experimental approach to understanding the genetic basis of resistance to Gibberella is to estimate the genetic linkage between available molecular markers and the character, measured as the amount of diseased tissue 40 days after inoculation of a suspension of Fusarium graminearum, the conidial form of G. zeae, into the first stalk internode. Sensitive and resistant parental inbreds were crossed to obtain F₁ and F₂ populations: the analysis of the segregation of 95 RFLP (restriction fragment length polymorphism) clones and 10 RAPD (random amplified polymorphic DNA) markers was performed on a population of 150 F₂ individuals. Analysis of resistance was performed on the F₃ families obtained by selfing the F₂ plants. Quantitative trait loci (QTL) detection was based either on analysis of regression coefficients between family mean value and allele values in the F₂ population, or by means of interval mapping, using MAPMAKER-QTL. A linkage map of maize was obtained, in which four to five genomic regions are shown to carry factors involved in the resistance to G. zeae.     

QTL mapping of resistance to Fusarium ear rot using a RIL population in maize

Fusarium ear rot is a prevalent disease in maize, reducing grain yields and quality. Resistance breeding is an efficient way to minimize losses caused by the disease. In this study, 187 lines from a RIL population along with the resistant (87-1) and susceptible (Zong 3) parents were planted in Zhengzhou and Beijing with three replications in years 2004 and 2006. Each line was artificially inoculated using the nail-punch method. Significant genotypic variation in response to Fusarium ear rot was detected in both years. Based on a genetic map containing 246 polymorphic SSR markers with average genetic distances of 9.1 cM, the ear-rot resistance QTL were firstly analyzed by composite interval mapping (CIM). Three QTL were detected in both Zhengzhou and Beijing in 2004; and three and four QTL, respectively, were identified in 2006. The resistant parent contributed all resistance QTL. By using composite interval mapping and a mixed model (MCIM), significant epistatic effects on Fusarium ear rot as well as interactions between mapped loci and environments were observed across environments. Two QTL on chromosome 3 (3.04 bin) were consistently identified across all environments by the two methods. The major resistant QTL with the largest effect was flanked by markers umc1025 and umc1742 on chromosome 3 (3.04 bin), explaining 13–22% of the phenotypic variation. The SSR markers closely flanking the major resistance QTL will facilitate marker-assisted selection (MAS) of resistance to Fusarium ear rot in maize breeding programs.     

Molecular mapping of quantitative trait loci for three kernel-related traits in maize using a double haploid population

Kernel size and kernel weight are important factors possibly involved in the determination of grain yield in maize, so identifying the genetic basis of kernel-related traits provides insights into the breeding of high-yield maize varieties. Kernel length (KL), kernel width (KW) and hundred kernel weight (HKW) were evaluated in three various planting conditions for the 240 field-grown double haploid (DH) lines derived from the single-cross hybrid Xianyu335. Variations in KL, KW and HKW were observed among DH lines, and all three traits showed a broad sense heritability of 76%. A total of 964 single nucleotide polymorphisms (SNPs) from the MaizeSNP3072 chip was utilised to create a high-density genetic map of 1546.4 cM and to identify quantitative trait loci (QTLs). Using composite interval mapping, a total of five, seven and five QTLs have been mapped for KL, KW and HKW, respectively. qkl1-2 and qkl4-1 explained 17.8% and 14.2% of the phenotypic variation in KL, respectively, and the other three QTLs contributed 3.2–4.0%. The phenotypic variation explained (PVE) of seven QTLs responsible for KW ranged from 3.3 to 9.5%. Three QTLs for HKW, qhkw1, qhkw5 and qhkw10 each explained more than 10% of the phenotypic variation, and qhkw4 and qhkw9 accounted for 3.0% and 6.0%, respectively. Due to their detection in multiple planting environments, the loci mapped here appear to be potential targets for the improvement of maize grain yield.     

Quantitative trait loci associated with seed and seedling traits in Lactuca

Seed and seedling traits related to germination and stand establishment are important in the production of cultivated lettuce (Lactuca sativa L.). Six seed and seedling traits segregating in a L. sativa cv. Salinas x L. serriola recombinant inbred line population consisting of 103 F8 families revealed a total of 17 significant quantitative trait loci (QTL) resulting from three seed production environments. Significant QTL were identified for germination in darkness, germination at 25 and 35°C, median maximum temperature of germination, hypocotyl length at 72 h post-imbibition, and plant (seedling) quality. Some QTL for germination and early seedling growth characteristics were co-located, suggestive of pleiotropic loci regulating these traits. A single QTL (Htg6.1) described 25 and 23% of the total phenotypic variation for high temperature germination in California- and Netherlands-grown populations, respectively, and was significant between 33 and 37°C. Additionally, Htg6.1 showed significant epistatic interactions with other Htg QTL and a consistent effect across all the three seed production environments. L. serriola alleles increased germination at these QTL. The estimate of narrow-sense heritability (h²) of Htg6.1 was 0.84, indicating potential for L. serriola as a source of germination thermotolerance for lettuce introgression programs.     

Quantitative trait loci for baseline erythroid traits

A substantial genetic contribution underlies variation in baseline peripheral blood counts. We performed quantitative trait locus/loci (QTL) analyses to identify chromosome (Chr) regions harboring genes influencing the baseline erythroid parameters in F₂ intercrosses between NZW/LacJ, SM/J, and C57BLKS/J inbred mice. We identified multiple significant QTL for red blood cell (RBC) count, hemoglobin (Hgb) and hematocrit (Hct) levels, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean cell hemoglobin concentration (CHCM). We identified four RBC count QTL: Rbcq1 (Chr 1, peak LOD score at 62 cM,), Rbcq2 (Chr 4, 60 cM), Rbcq3 (Chr 11, 34 cM), and Rbcq4 (Chr 10, 60 cM). Three MCV QTL were identified: Mcvq1 (Chr 7, 30 cM), Mvcq2 (Chr 11, 6 cM), and Mcvq3 (Chr 10, 60 cM). Single significant loci for Hgb (Hgbq1, Chr 16, 32 cM), Hct (Hctq1, Chr 3, 42 cM), and MCH (Mchq1, Chr 10, 60 cM) were identified. The data support the existence of a common RBC/MCH/MCV locus on Chr 10. Two QTL for CHCM (Chcmq1, Chr 2, 48 cM; Chcmq2, Chr 9, 44 cM) and an interaction between Chcmq2 with a locus on Chr 19 were identified. These analyses emphasize the genetic complexity underlying the regulation of erythroid peripheral blood traits in normal populations and suggest that genes not previously recognized as significantly impacting normal erythropoiesis exist.     

Bayesian quantitative trait loci mapping for multiple traits

Most quantitative trait loci (QTL) mapping experiments typically collect phenotypic data on multiple correlated complex traits. However, there is a lack of a comprehensive genomewide mapping strategy for correlated traits in the literature. We develop Bayesian multiple-QTL mapping methods for correlated continuous traits using two multivariate models: one that assumes the same genetic model for all traits, the traditional multivariate model, and the other known as the seemingly unrelated regression (SUR) model that allows different genetic models for different traits. We develop computationally efficient Markov chain Monte Carlo (MCMC) algorithms for performing joint analysis. We conduct extensive simulation studies to assess the performance of the proposed methods and to compare with the conventional single-trait model. Our methods have been implemented in the freely available package R/qtlbim (http://www.qtlbim.org), which greatly facilitates the general usage of the Bayesian methodology for unraveling the genetic architecture of complex traits.     

A major QTL for resistance to Gibberella stalk rot in maize

Fusarium graminearum Schwabe, the conidial form of Gibberella zeae, is the causal fungal pathogen responsible for Gibberella stalk rot of maize. Using a BC₁F₁ backcross mapping population derived from a cross between ‘1145’ (donor parent, completely resistant) and ‘Y331’ (recurrent parent, highly susceptible), two quantitative trait loci (QTLs), qRfg1 and qRfg2, conferring resistance to Gibberella stalk rot have been detected. The major QTL qRfg1 was further confirmed in the double haploid, F₂, BC₂F₁, and BC₃F₁ populations. Within a qRfg1 confidence interval, single/low-copy bacterial artificial chromosome sequences, anchored expressed sequence tags, and insertion/deletion polymorphisms, were exploited to develop 59 markers to saturate the qRfg1 region. A step by step narrowing-down strategy was adopted to pursue fine mapping of the qRfg1 locus. Recombinants within the qRfg1 region, screened from each backcross generation, were backcrossed to ‘Y331’ to produce the next backcross progenies. These progenies were individually genotyped and evaluated for resistance to Gibberella stalk rot. Significant (or no significant) difference in resistance reactions between homozygous and heterozygous genotypes in backcross progeny suggested presence (or absence) of qRfg1 in ‘1145’ donor fragments. The phenotypes were compared to sizes of donor fragments among recombinants to delimit the qRfg1 region. Sequential fine mapping of BC₄F₁ to BC₆F₁ generations enabled us to progressively refine the qRfg1 locus to a ~500-kb interval flanked by the markers SSR334 and SSR58. Meanwhile, resistance of qRfg1 to Gibberella stalk rot was also investigated in BC₃F₁ to BC₆F₁ generations. Once introgressed into the ‘Y331’ genome, the qRfg1 locus could steadily enhance the frequency of resistant plants by 32–43%. Hence, the qRfg1 locus was capable of improving maize resistance to Gibberella stalk rot.     

Quantitative trait loci mapping and the genetic basis of heterosis in maize and rice

Despite its importance to agriculture, the genetic basis of heterosis is still not well understood. The main competing hypotheses include dominance, overdominance, and epistasis. NC design III is an experimental design that has been used for estimating the average degree of dominance of quantitative trait loci (QTL) and also for studying heterosis. In this study, we first develop a multiple-interval mapping (MIM) model for design III that provides a platform to estimate the number, genomic positions, augmented additive and dominance effects, and epistatic interactions of QTL. The model can be used for parents with any generation of selfing. We apply the method to two data sets, one for maize and one for rice. Our results show that heterosis in maize is mainly due to dominant gene action, although overdominance of individual QTL could not completely be ruled out due to the mapping resolution and limitations of NC design III. For rice, the estimated QTL dominant effects could not explain the observed heterosis. There is evidence that additive × additive epistatic effects of QTL could be the main cause for the heterosis in rice. The difference in the genetic basis of heterosis seems to be related to open or self pollination of the two species. The MIM model for NC design III is implemented in Windows QTL Cartographer, a freely distributed software.     

Multiple-interval mapping for quantitative trait loci controlling endosperm traits

Endosperm traits are trisomic inheritant and are of great economic importance because they are usually directly related to grain quality. Mapping for quantitative trait loci (QTL) underlying endosperm traits can provide an efficient way to genetically improve grain quality. As the traditional QTL mapping methods (diploid methods) are usually designed for traits under diploid control, they are not the ideal approaches to map endosperm traits because they ignore the triploid nature of endosperm. In this article, a statistical method considering the triploid nature of endosperm (triploid method) is developed on the basis of multiple-interval mapping (MIM) to map for the underlying QTL. The proposed triploid MIM method is derived to broadly use the marker information either from only the maternal plants or from both the maternal plants and their embryos in the backcross and F2 populations for mapping endosperm traits. Due to the use of multiple intervals simultaneously to take multiple QTL into account, the triploid MIM method can provide better detection power and estimation precision, and as shown in this article it is capable of analyzing and searching for epistatic QTL directly as compared to the traditional diploid methods and current triploid methods using only one (or two) interval(s). Several important issues in endosperm trait mapping, such as the relation and differences between the diploid and triploid methods, variance components of genetic variation, and the problems if effects are present and ignored, are also addressed. Simulations are performed to further explore these issues, to investigate the relative efficiency of different experimental designs, and to evaluate the performance of the proposed and current methods in mapping endosperm traits. The MIM-based triploid method can provide a powerful tool to estimate the genetic architecture of endosperm traits and to assist the marker-assisted selection for the improvement of grain quality in crop science. The triploid MIM FORTRAN program for mapping endosperm traits is available on the worldwide web (http://www.stat.sinica.edu.tw/chkao/).     

Quantitative trait loci mapping for canine hip dysplasia and its related traits in UK Labrador Retrievers

Background

Canine hip dysplasia (CHD) is characterised by a malformation of the hip joint, leading to osteoarthritis and lameness. Current breeding schemes against CHD have resulted in measurable but moderate responses. The application of marker-assisted selection, incorporating specific markers associated with the disease, or genomic selection, incorporating genome-wide markers, has the potential to dramatically improve results of breeding schemes. Our aims were to identify regions associated with hip dysplasia or its related traits using genome and chromosome-wide analysis, study the linkage disequilibrium (LD) in these regions and provide plausible gene candidates. This study is focused on the UK Labrador Retriever population, which has a high prevalence of the disease and participates in a recording program led by the British Veterinary Association (BVA) and The Kennel Club (KC).

Results

Two genome-wide and several chromosome-wide QTLs affecting CHD and its related traits were identified, indicating regions related to hip dysplasia.

Conclusion

Consistent with previous studies, the genetic architecture of CHD appears to be based on many genes with small or moderate effect, suggesting that genomic selection rather than marker-assisted selection may be an appropriate strategy for reducing this disease.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-833) contains supplementary material, which is available to authorized users.     

Quantitative trait loci for aluminum resistance in wheat

Quantitative trait loci (QTL) for wheat resistance to aluminum (Al) toxicity were analyzed using simple sequence repeats (SSRs) in a population of 192 F₆ recombinant inbred lines (RILs) derived from a cross between an Al-resistant cultivar, Atlas 66 and an Al-sensitive cultivar, Chisholm. Wheat reaction to Al was measured by relative root growth and root response to hematoxylin stain in nutrient-solution culture. After screening 1,028 SSR markers for polymorphisms between the parents and bulks, we identified two QTLs for Al resistance in Atlas 66. One major QTL was mapped on chromosome 4D that co-segregated with the Al-activated malate transporter gene (ALMT1). Another minor QTL was located on chromosome 3BL. Together, these two QTLs accounted for about 57% of the phenotypic variation in hematoxylin staining score and 50% of the variation in net root growth (NRG). Expression of the minor QTL on 3BL was suppressed by the major QTL on 4DL. The two QTLs for Al resistance in Atlas 66 were also verified in an additional RIL population derived from Atlas 66/Century. Several SSR markers closely linked to the QTLs were identified and have potential to be used for marker-assisted selection (MAS) to improve Al-resistance of wheat cultivars in breeding programs.     

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.