Genome-wide association mapping of quantitative resistance to sudden death syndrome in soybean

Background

Sudden death syndrome (SDS) is a serious threat to soybean production that can be managed with host plant resistance. To dissect the genetic architecture of quantitative resistance to the disease in soybean, two independent association panels of elite soybean cultivars, consisting of 392 and 300 unique accessions, respectively, were evaluated for SDS resistance in multiple environments and years. The two association panels were genotyped with 52,041 and 5,361 single nucleotide polymorphisms (SNPs), respectively. Genome-wide association mapping was carried out using a mixed linear model that accounted for population structure and cryptic relatedness.

Result

A total of 20 loci underlying SDS resistance were identified in the two independent studies, including 7 loci localized in previously mapped QTL intervals and 13 novel loci. One strong peak of association on chromosome 18, associated with all disease assessment criteria across the two panels, spanned a physical region of 1.2 Mb around a previously cloned SDS resistance gene (GmRLK18-1) in locus Rfs2. An additional variant independently associated with SDS resistance was also found in this genomic region. Other peaks were within, or close to, sequences annotated as homologous to genes previously shown to be involved in plant disease resistance. The identified loci explained an average of 54.5% of the phenotypic variance measured by different disease assessment criteria.

Conclusions

This study identified multiple novel loci and refined the map locations of known loci related to SDS resistance. These insights into the genetic basis of SDS resistance can now be used to further enhance durable resistance to SDS in soybean. Additionally, the associations identified here provide a basis for further efforts to pinpoint causal variants and to clarify how the implicated genes affect SDS resistance in soybean.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-809) contains supplementary material, which is available to authorized users.     

QTL mapping of fire blight resistance in apple

Fire blight caused by the bacterium Erwinia amylovora is a severe threat to apple and pear orchards worldwide. Apple varieties exhibit a wide range of relative susceptibility/tolerance to fire blight. Although, no monogenic resistance against fire blight has been identified yet, recent evidence indicates the existence of quantitative resistance. Potential sources of fire blight resistance include several wild Malus species and some apple cultivars. F1 progenies of ‘Fiesta’בDiscovery’ were inoculated with the Swiss strain Ea 610 and studied under controlled conditions to identify quantitative trait loci (QTLs) for fire blight resistance. Disease was evaluated at four time points after inoculation. Shoot lesion length and the area under disease progress curve (AUDPC) values were used for QTL analysis. One significant (LOD score of 7.5–8.1, p<0.001) QTL was identified on the linkage group 7 of ‘Fiesta’ (F7). The F7 QTL explained about 37.5–38.6% of the phenotypic variation.     

Interval mapping of genes for quantitative resistance of maize to Setosphaeria turcica,cause of northern leaf blight,in a tropical environment

Quantitative trait loci (QTL) involved in the resistance of maize to Setosphaeria turcica, the causal agent of northern leaf blight, were located by interval mapping analysis of 121 F_2:3 lines derived from a cross between Mo17 (moderately resistant) and B52 (susceptible). A linkage map spanning 112 RFLP loci with 15 cM mean interval length was constructed, based on marker data recorded in a previous study. Field tests with artificial inoculation were conducted at three sites in tropical mid- to high-altitude regions of Kenya, East Africa. Host-plant response was measured in terms of incubation period, disease severity (five scoring dates), and the area under the disease progress curve (AUDPC). Heritability of all traits was high (around 0.75). QTL associated with the incubation period were located on chromosomes 2S and 8L. For disease severity and AUDPC, significant QTL were detected in the putative centromeric region of chromosome 1 and on 2S, 3L, 5S, 6L, 7L, 8L and 9S. On 2S the same marker interval which carried a gene enhancing latent period was also associated with reduced disease severity of juvenile plants. QTL on chromosomes 3L, 5S, 7L and 8L were significant across environments but all other QTL were affected by a large genotype x environment interaction. Partially dominant gene action for resistance as well as for susceptibility was prevailing. Single QTL explained 10 to 38% of the phenotypic variation of the traits. All but the QTL on chromosomes 1, 6 and 9 were contributed by the resistant parent Mo17. On chromosome 8L a QTL mapped to the same region as the major race-specific gene Ht2, supporting the hypothesis that some qualitative and quantitative resistance genes may be allelic.Abbreviations AUDPC area under the disease progress curve - CIMMYT International Maize and Wheat Improvement Center - KARI Kenya Agricultural Research Institute - NCLB northern corn leaf blight - QTL quantitative trait locus/loci     

Identification of quantitative trait loci controlling resistance to gray leaf spot disease in maize

Breeding maize for gray leaf spot (GLS) resistance has been hindered by the quantitative nature of the inheritance of GLS resistance and by the limitations of selection under less than optimumal disease pressure. In order to identify the quantitative trait loci (QTLs) controlling GLS resistance, a cross was made between B73 (susceptible) and Va14 (resistant) to generate a large F₂ population. Six GLS disease assessments were made throughout the disease season for over 1000 F₂ plants in 1989, and for 600 F₂-derived F₃ lines replicated in two blocks in 1990. RFLP analysis for78 marker loci representing all ten maize chromosomes was conducted in 239 F₂ individuals including those with the extreme GLS disease phenotypes. The GLS disease scores of the three field evaluations, each averaged over six ratings, were separately used for the interval mapping in order to determine the consistency of the QTL effects. The heavy GLS disease pressure, meticulous disease ratings, and large population size of this study afforded us the sensitivity for detecting QTL effects. QTLs located on three chromosomes (1, 4, and 8) had large effects on GLS resistance, each explaining 35.0–56.0%, 8.8–14.3%, and 7.7–11.0% of the variance, respectively. These three QTL effects were remarkably consistent across three disease evaluations over 2 years and two generations. Smaller QTL effects were also found on chromosomes 2 and 5, but the chromosome-5 effect might be a false positive because it was not repeatable even in the same location. The chromosome-1 QTLs had the largest effect or highest R² reported for any quantitative trait to-date. Except for the chromosome-4 gene, which was from the susceptible parent B73, the resistance alleles at all QTL were derived from Va14. The resistance QTLs on chromosomes 1 and 2 appear to have additive effects, but those on chromosomes 4 and 8 are dominant and recessive, respectively. Significant interaction between the QTLs on chromosomes 1 and 4 was detected in all three evaluations. Cumulatively, the four QTLs identified in this study explained 44, 60, and 68% of the variance in F₂, and in F₃ replications 1 and 2, respectively.     

Modelling the genetic architecture of flowering time control in barley through nested association mapping

Background

Barley, globally the fourth most important cereal, provides food and beverages for humans and feed for animal husbandry. Maximizing grain yield under varying climate conditions largely depends on the optimal timing of flowering. Therefore, regulation of flowering time is of extraordinary importance to meet future food and feed demands. We developed the first barley nested association mapping (NAM) population, HEB-25, by crossing 25 wild barleys with one elite barley cultivar, and used it to dissect the genetic architecture of flowering time.

Results

Upon cultivation of 1,420 lines in multi-field trials and applying a genome-wide association study, eight major quantitative trait loci (QTL) were identified as main determinants to control flowering time in barley. These QTL accounted for 64% of the cross-validated proportion of explained genotypic variance (p_G). The strongest single QTL effect corresponded to the known photoperiod response gene Ppd-H1. After sequencing the causative part of Ppd-H1, we differentiated twelve haplotypes in HEB-25, whereof the strongest exotic haplotype accelerated flowering time by 11 days compared to the elite barley haplotype. Applying a whole genome prediction model including main effects and epistatic interactions allowed predicting flowering time with an unmatched accuracy of 77% of cross-validated p_G.

Conclusions

The elaborated causal models represent a fundamental step to explain flowering time in barley. In addition, our study confirms that the exotic biodiversity present in HEB-25 is a valuable toolbox to dissect the genetic architecture of important agronomic traits and to replenish the elite barley breeding pool with favorable, trait-improving exotic alleles.

     

Genetic mapping of maize streak virus resistance from the Mascarene source. I. Resistance in line D211 and stability against different virus clones

Maize streak virus (MSV) disease may cause significant grain yield reductions in maize in Africa. Réunion island maize germplasm is a proven source of strong resistance. Its genetic control was investigated using 123 RFLP markers in an F₂ population of D211 (resistant) × B73 (susceptible). This population of 165 F_2:3 families was carefully evaluated in Harare (Zimbabwe) and in Réunion. Artificial infestation was done with viruliferous leafhoppers. Each plant was rated weekly six times after infestation on a 1–9 scale previously adjusted by image analysis. QTL analyses were conducted for each scoring date, and for the areas under the disease, incidence and severity progress curves. The composite interval mapping method used allowed the estimation of the additive and dominance effects and QTL × environment interactions. Heritabilities ranged from 73% to 98%, increasing with time after infestation. Resistance to streak virus in D211 was provided by one region on chromosome 1, with a major effect, and four other regions on chromosomes 2, 3 (two regions) and 10, with moderate or minor effects. Overall, they explained 48–62% of the phenotypic variation for the different variables. On chromosome 3, one of the two regions seemed to be more involved in early resistance, whereas the second was detected at the latest scoring date. Other QTLs were found to be stable over time and across environments. Mild QTL × environment interactions were detected. Global gene action appeared to be partially dominant, in favor of resistance, except at the earliest scoring dates, where it was additive. From this population, 32 families were chosen, representing the whole range of susceptibility to MSV. They were tested in Réunion against three MSV clones, along with a co-inoculation of two of them. Virulence differences between clones were significant. There were genotype × clone interactions, and these were more marked for disease incidence than for severity. Although these interactions were not significant for the mean disease scores, it is suggested that breeders should select for completely resistant genotypes. Received: 15 June 1998 / Accepted: 30 January 1999     

Quantitative trait loci for lodging resistance,plant height and partial resistance to mycosphaerella blight in field pea (Pisum sativum L.)

With the development of genetic maps and the identification of the most-likely positions of quantitative trait loci (QTLs) on these maps, molecular markers for lodging resistance can be identified. Consequently, marker-assisted selection (MAS) has the potential to improve the efficiency of selection for lodging resistance in a breeding program. This study was conducted to identify genetic loci associated with lodging resistance, plant height and reaction to mycosphaerella blight in pea. A population consisting of 88 recombinant inbred lines (RILs) was developed from a cross between Carneval and MP1401. The RILs were evaluated in 11 environments across the provinces of Manitoba, Saskatchewan and Alberta, Canada in 1998, 1999 and 2000. One hundred and ninety two amplified fragment length polymorphism (AFLP) markers, 13 random amplified polymorphic DNA (RAPD) markers and one sequence tagged site (STS) marker were assigned to ten linkage groups (LGs) that covered 1,274 centi Morgans (cM) of the pea genome. Six of these LGs were aligned with the previous pea map. Two QTLs were identified for lodging resistance that collectively explained 58% of the total phenotypic variation in the mean environment. Three QTLs were identified each for plant height and resistance to mycosphaerella blight, which accounted for 65% and 36% of the total phenotypic variation, respectively, in the mean environment. These QTLs were relatively consistent across environments. The AFLP marker that was associated with the major locus for lodging resistance was converted into the sequence-characterized amplified-region (SCAR) marker. The presence or absence of the SCAR marker corresponded well with the lodging reaction of 50 commercial pea varieties.Communicated by H. F. Linskens     

Genetic loci associated with field resistance to late blight in offspring of Solanum phureja and S.tuberosum grown under short-day conditions

Field resistance to late blight – a fungal disease caused by Phytophthora infestans – has been genetically characterized by analyzing trait-marker association in a Solanum phureja (phu)×dihaploid Solanum tuberosum (dih-tbr) population. Trait data were developed at three locations over a 3-year period under natural infection pressure. RAPD (random amplified polymorphic DNA) and AFLP (amplified fragment length polymorphism)markers were used to develop anonymous genetic linkage groups subsequently anchored to potato chromosomes using mapped RFLP (restriction fragment length polymorphism), SSR (single sequence repeats) and AFLP markers. RFLP and SSR markers achieved the most-accurate anchoring. Two genetic maps were obtained, with 987.4 cM for phu and 773.7 cM for dih-tbr. Trait-marker association was revealed by single-marker and interval mapping analyses. Two important QTLs (quantitative trait loci) were detected on chromosomes VII and XII as a contribution from both parents, totalling up to 16% and 43%, respectively, of the phenotypic variation (PH). One additional QTL was detected on chromosome XI (up to 11% of the PH) as a contribution from the phu parent, and three others were detected on chromosome III (up to 13% of the PH), chromosome V (up to 11% of the PH) and chromosome VIII (up to 11% of the PH) as a contribution from the dih-tbr parent. Our results reveal new genetic loci of the potato genome that contribute to resistance to late blight. We postulate that some of these loci could be related to plant growth under short-day conditions. Received: 5 July 2000 / Accepted: 17 November 2000     

Genetic mapping of maize stripe disease resistance from the Mascarene source

Maize stripe virus (MStV) is a potentially threatening virus disease of maize in the tropics. We mapped quantitative trait loci (QTLs) controlling resistance to MStV in a maize population of 157 F(2:3) families derived from the cross between two maize lines, Rev81 (tropical resistant) and B73 (temperate susceptible). Resistance was evaluated under artificial inoculations in replicated screenhouse trials across different seasons in Réunion Island, France. Composite interval mapping was employed for QTL detection with a linkage map of 143 microsatellite markers. Heritability estimates across seasons were 0.96 and 0.90 for incidence and severity, respectively, demonstrating a high genotypic variability and a good control of the environment. Three regions on chromosomes 2L, 3 and 5, with major effects, and another region on chromosome 2S, with minor effects, provided resistance to MStV in Rev81. In individual seasons, the chr2L QTL explained 60-65% of the phenotypic variation for disease incidence and 21-42% for severity. The chr3 QTL, mainly associated with incidence and located near centromere, explained 42-57% of the phenotypic variation, whereas the chr5 QTL, mainly associated with severity, explained 26-53%. Overall, these QTLs explained 68-73% of the phenotypic variance for incidence and 50-59% for severity. The major QTLs on chr2 and 3 showed additive gene action and were found to be stable over time and across seasons. They also were found to be included in genomic regions with important clusters of resistance genes to diseases and pests. The major QTL on chr5 appeared to be partially dominant in favour of resistance. It was stable over time but showed highly significant QTL x season interactions. Possible implications of these QTLs in different mechanisms of resistance against the virus or the insect vector are discussed. The prospects for transferring these QTLs in susceptible maize cultivars and combining them with other resistances to virus diseases by conventional or marker-assisted breeding are promising.     

Recovering Power in Association Mapping Panels with Variable Levels of Linkage Disequilibrium

Association mapping has permitted the discovery of major QTL in many species. It can be applied to existing populations and, as a consequence, it is generally necessary to take into account structure and relatedness among individuals in the statistical model to control false positives. We analytically studied power in association studies by computing noncentrality parameter of the tests and its relationship with parameters characterizing diversity (genetic differentiation between groups and allele frequencies) and kinship between individuals. Investigation of three different maize diversity panels genotyped with the 50k SNPs array highlighted contrasted average power among panels and revealed gaps of power of classical mixed models in regions with high linkage disequilibrium (LD). These gaps could be related to the fact that markers are used for both testing association and estimating relatedness. We thus considered two alternative approaches to estimating the kinship matrix to recover power in regions of high LD. In the first one, we estimated the kinship with all the markers that are not located on the same chromosome than the tested SNP. In the second one, correlation between markers was taken into account to weight the contribution of each marker to the kinship. Simulations revealed that these two approaches were efficient to control false positives and were more powerful than classical models.     

Chromosomal mapping of host resistance loci to Trichinella spiralis nematode infection in rats

The differences in host response among strains of rats to intestinal nematode parasite Trichinella spiralis infection could provide a powerful benefit for further elucidation of molecular interactions between the host and the parasite. Using several strains of rats, we previously observed that DA strain is a strong responder and F344 strain is a weak responder with respect to expulsion of the adult worm. To identify the host resistance loci, quantitative trait loci (QTLs) analysis in F2 population from crosses between DA and F344 strains was performed. One significant QTL (designated as Tspe) was mapped to the middle region of chromosome 9. In addition, the effect of DA allele at Tspe locus could act recessively and lead to the rejection of more adult worms from the gut. The results from the present study provide more insights on host–parasite interactions, which may be useful in facilitating the development of novel approaches for treatment and control of intestinal parasites in human and domestic livestock.     

Epistatic interaction is an important genetic basis of grain yield and its components in maize

A population of 294 recombinant inbred lines (RIL) derived from Yuyu22, an elite maize hybrid extending broadly in China, has been constructed to investigate the genetic basis of grain yield, and associated yield components in maize. The main-effect quantitative trait loci (QTL), digenic epistatic interactions, and their interactions with the environment for grain yield and its three components were identified by using the mixed linear model approach. Thirty-two main-effect QTL and forty-four pairs of digenic epistatic interactions were detected for the four measured traits in four environments. Our results suggest that both additive effects and epistasis (additive × additive) effects are important genetic bases of grain yield and its components in the RIL population. Only 30.4% of main-effect QTL for ear length were involved in epistatic interactions. This implies that many loci in epistatic interactions may not have significant effects for traits alone but may affect trait expression by epistatic interaction with the other loci.     

Genetics of seedling and adult plant resistance to net blotch (Pyrenophora teres f. teres) and spot blotch (Cochliobolus sativus) in barley

Net blotch (caused by Pyrenophora teres f. teres) and spot blotch (Cochliobolus sativus) are important foliar diseases of barley in the midwestern region of the USA. To determine the number and chromosomal location of Mendelian and quantitative trait loci (QTL) controlling resistance to these diseases, a doubled haploid population (Steptoe/Morex) was evaluated to the pathogens at the seedling stage in the greenhouse and at the adult plant stage in the field. Alleles at two or three unlinked loci were found to confer resistance to the net blotch pathogen at the seedling stage depending on how progeny exhibiting an intermediate infection response were classified. This result was corroborated in the quantitative analysis of the raw infection response data as 2 major QTL were identified on chromosomes 4 and 6M. A third QTL was also identified on chromosome 6P. Seven QTL were identified for net blotch resistance at the adult plant stage and mapped to chromosomes 1P, 2P, 3P, 3M, 4, 6P, and 7P. The 7 QTL collectively accounted for 67.6% of the phenotypic variance under a multiple QTL model. Resistance to the spot blotch pathogen was conferred by a single gene at the seedling stage. This gene was mapped to the distal region of chromosome 1P on the basis of both qualitative and quantitative data analyses. Two QTL were identified for spot blotch resistance at the adult plant stage: the largest QTL effect mapped to chromosome 5P and the other mapped to chromosome 1P near the seedling resistance locus. Together, the 2 QTL explained 70.1% of the phenotypic variance under a multiple QTL model. On the basis of the chromosomal locations of resistance alleles detected in this study, it should be feasible to combine high levels of resistance to both P. teres f. teres and C. sativus in barley cultivars.     

Lineage-specific mapping of quantitative trait loci

We present an approach for quantitative trait locus (QTL) mapping, termed as ‘lineage-specific QTL mapping'', for inferring allelic changes of QTL evolution along with branches in a phylogeny. We describe and analyze the simplest case: by adding a third taxon into the normal procedure of QTL mapping between pairs of taxa, such inferences can be made along lineages to a presumed common ancestor. Although comparisons of QTL maps among species can identify homology of QTLs by apparent co-location, lineage-specific mapping of QTL can classify homology into (1) orthology (shared origin of QTL) versus (2) paralogy (independent origin of QTL within resolution of map distance). In this light, we present a graphical method that identifies six modes of QTL evolution in a three taxon comparison. We then apply our model to map lineage-specific QTLs for inbreeding among three taxa of yellow monkey-flower: Mimulus guttatus and two inbreeders M. platycalyx and M. micranthus, but critically assuming outcrossing was the ancestral state. The two most common modes of homology across traits were orthologous (shared ancestry of mutation for QTL alleles). The outbreeder M. guttatus had the fewest lineage-specific QTL, in accordance with the presumed ancestry of outbreeding. Extensions of lineage-specific QTL mapping to other types of data and crosses, and to inference of ancestral QTL state, are discussed.     

Genome-wide association mapping identifies the genetic basis of discrete and quantitative variation in sexual weaponry in a wild sheep population

Understanding the genetic architecture of phenotypic variation in natural populations is a fundamental goal of evolutionary genetics. Wild Soay sheep (Ovis aries) have an inherited polymorphism for horn morphology in both sexes, controlled by a single autosomal locus, Horns. The majority of males have large normal horns, but a small number have vestigial, deformed horns, known as scurs; females have either normal horns, scurs or no horns (polled). Given that scurred males and polled females have reduced fitness within each sex, it is counterintuitive that the polymorphism persists within the population. Therefore, identifying the genetic basis of horn type will provide a vital foundation for understanding why the different morphs are maintained in the face of natural selection. We conducted a genome-wide association study using ～36000 single nucleotide polymorphisms (SNPs) and determined the main candidate for Horns as RXFP2, an autosomal gene with a known involvement in determining primary sex characters in humans and mice. Evidence from additional SNPs in and around RXFP2 supports a new model of horn-type inheritance in Soay sheep, and for the first time, sheep with the same horn phenotype but different underlying genotypes can be identified. In addition, RXFP2 was shown to be an additive quantitative trait locus (QTL) for horn size in normal-horned males, accounting for up to 76% of additive genetic variation in this trait. This finding contrasts markedly from genome-wide association studies of quantitative traits in humans and some model species, where it is often observed that mapped loci only explain a modest proportion of the overall genetic variation.     

Breeding for resistance to downy mildews and stalk rots in maize

Summary The present review includes information on distribution, symptoms, inoculation techniques, disease rating, sources of resistance, genetics of resistance, breeding approaches for resistance, and the present status of resistance breeding with respect to Sclerophthora and Peronosclerospora downy mildews and Erwinia, Cephalosporium and Fusarium stalk rots. Some suggestions highlighting research gaps pertinent to future breeding strategies are mentioned.Publication No. 2993, Experiment Station, GB Pant University of Agriculture and Technology, Pantnagar, India     

Quantitative trait loci for plant height in four maize populations and their associations with qualitative genetic loci

Summary We report that plant height quantitative trait loci (QTLs) identified in a given small population are not consistent with QTLs identified in other small populations, and that most QTLs are in close proximity to mapped qualitative genetic loci. These observations provide evidence to support the hypothesis that qualitative genetic loci are the same loci that affect quantitative traits, and affirm that these modest experiments probably identify real QTLs.