Molecular genetic mapping of peach

Summary A project to develop a linkage map of the peach (Prunus persica) genome is underway using an F2 population segregating for several morphological characters and pest resistance e.g., nectarine (g), weeping shape (pl) and aphid resistance (Rml). The RAPID technique was used to analyse 270 plants. Linkage analysis of the F2 population was performed using the MAPMAKER software. Eight linkage groups were established and RAPID markers flanking thepl gene were found.     

Wide mapping of a T-DNA insertion site in oilseed rape using bulk segregant analysis and comparative mapping

Doubled haploid oilseed rape lines segregating for a transgene inducing herbicide resistance (bar gene) were investigated for the wide mapping of the T-DNA insertion site. Bulk segregant analysis using presence/absence and intensity polymorphisms between the bulks, as well as comparative mapping with a linkage group deriving from another cross, led to the identification of 11 random amplified polymorphic DNA (RAPD) markers tightly or loosely linked to the bar gene. Ten RAPD loci out of 11 were located on the same side of the bar locus, strongly suggesting that the T-DNA integrated in a telomeric or subtelomeric position. The eleventh RAPD marker exhibited a strong segregation distortion, which could be the result of a heteroduplex formation. Comparison of the linkage groups obtained from the two crosses showed different recombination rates between markers, possibly reflecting differences in parental genetic backgrounds. Consequences and potential applications in transgene dispersal safety assessment studies are discussed.     

Identifying and mapping genes of economic significance

An understanding of the genetic basis of characters of commercial importance is critical if a breeder is attempting to move such characters into breeding material. A number of particularly interesting characters or genes have been identified in cool season food legumes, and in pea many of these have been tagged by molecular markers such as allozyme or DNA polymorphisms. This process of mapping and tagging genes has been greatly accelerated by recent developments in molecular biology. It appears that markers will soon be available for many genes in lentil, faba bean, and chickpea and that genetic knowledge developed in one crop will have significant applications in the other cool season food legumes.     

Quantitative trait loci mapping of forage agronomic traits in six mapping populations derived from European elite maize germplasm

Four agronomic traits were analysed including dry matter concentration (DMC) and dry matter yield (DMY) for stover, plant height (PHT) and days from planting to silking (DPS). We mapped quantitative trait loci (QTL) in three populations with doubled haploid lines (DHL), one RIL population and two testcross (TC) populations derived from crosses between two of the four populations mentioned above to elite tester lines, based on field phenotyping at multiple locations and years for each; 146–168 SSRs were used for genotyping of the four mapping populations. Significant high phenotypic and genotypic correlations were found for all traits at two locations, while DMC was negatively correlated with the other traits. A total of 42, 41, 54, and 45 QTL were identified for DMC, DMY, PHT, and DPS, respectively, with 9, 7, 12, and 7 major QTL for each trait. Most detected QTL displayed significant interactions with environment. Major QTL detected in more than two populations will contribute to marker‐assisted breeding and also to fine mapping candidate genes associated with maize agronomic traits.     

Quantitative trait loci mapping of forage stover quality traits in six mapping populations derived from European elite maize germplasm

Four forage maize stover quality traits were analysed including in vitro digestibility of organic matter (IVDOM), neutral detergent fibre (NDF), water‐soluble carbohydrates (WSC) and digestibility of NDF (DNDF). We mapped quantitative trait loci (QTL) in three DH (doubled haploid) populations (totally 250–720 DH lines): one RIL population (358 lines) and two testcross (TC) populations, based on field phenotyping at multiple locations and years for each. High phenotypic and genotypic correlations were found for all traits and significant (p < .01) at two locations, and NDF was negatively correlated with the other traits. QTL analyses were conducted by composite interval mapping. A total of 33, 23, 32 and 25 QTL were identified for IVDOM, NDF, WSC and DNDF, respectively, with three, four, five and two major QTL for each. Few consistent QTL for IVDOM, WSC and DNDF were detected in more than two populations. This study contributed to the identification of key QTL associated with forage maize digestibility traits and is beneficial for marker‐assisted breeding and fine mapping of candidate genes associated with forage maize quality.     

The application of geostatistics in erosion hazard mapping

Geostatistical interpolation or kriging of soil and vegetation variables has become an important alternative to other mapping techniques. Although a reconnaissance sampling is necessary and basic requirements of geostatistics have to be met, kriging has the advantage of giving estimates with a minimized error. In erosion hazard assessment this technique may therefore be applied instead of the conventional choropleth mapping, in order to improve the reliability of the input data for an erosion model. In a study, which was performed in the Ardèche district (Southern France) at a detailed scale (1:5000), the two methods are compared directly. It demonstrates a straightforward way to decide which method will give the best overall results at different sampling densities for erodibility controlling variables and the USLE K-factor. To this end a land unit map and several kriging maps of the investigated area (±2,5 km²) have been prepared. Quotients of kriging estimation variances and within-unit variances of the land unit map were calculated as a relative measure of error reduction. It was found that the kriging estimation variance is 66% (on average) of the within-unit variance for the USLE K-factor at a 150 meter sampling distance. This percentage can be further reduced to about 25% at a 50 meter sampling distance. It is concluded that kriging is an efficient option for mapping erodibility at this scale.     

Association mapping in a simulated barley population

The analysis of association mapping populations is frequently complicated by substructure within the population. If this is unaccounted for, it generally results in many false positive marker-trait associations. In this study, we simulate a large barley population, modelling inbreeding and selection, and compare five models for analysing marker-trait associations. One of these includes no population substructure, one includes information about geographical origin and type of barley to represent structure within the population and three use different approaches that have been proposed for estimating marker-based kinship. Kinship methods reduced the number of false positives substantially compared to the other models but none of these approaches had a clear advantage over the others. One solution is to fit more than one model and to consider as candidate associations those markers that are significant by all models. None of the approaches were very successful at detecting true associations at the lowest level of heritability considered (25%), suggesting it is important to consider power in association mapping studies to avoid missing some true associations and overestimating others.     

The New Zealand apple genome mapping project

Summary This project was initiated three years ago to support the New Zealand apple breeding programme at HortResearch and is funded by both the New Zealand Foundation for Research, Science and Technology and the New Zealand Apple and Pear Marketing Board. Our initial goal is to construct a linkage map comprising RFLP, RAPD and isoenzyme markers as well as characters of importance to our breeders and this will enable the breeders to use marker assisted selection to identify the most promising seedlings within progeny populations at an early age. Characters of interest in the shorter term include resistances to scab, powdery mildew, woolly apple aphid and silver leaf, and in the longer term more complex traits such as early and late fruit maturity, fruit quality characters, low temperature tolerance and rootstock influences such as dwarfing and precocity are under consideration. We are currently developing long-term plans for isolation of apple genes in association with other molecular biologists in Hort Research. We have used a cDNA library from apple flesh as a prolific source of RFLP probes and detect their hybridization to Southern blots using a chemiluminescent method. We have screened our mapping line of seedlings for more than 160 markers so far (1/3 RFLP, 2/3 RAPD). Detection of in situ hybridization of key RFLP probes to metaphase chromosome preparations for the purpose of associating marker linkage groups with physical chromosomes is by a digoxygenin or biotin linked immunoassay. The project has collaborative links to apple genome mapping projects in America and Europe.     

QTL mapping for the cooking time of common beans

The decrease in the per capita consumption of beans has been partially attributed to their lengthy cooking time and the aggregated capital costs of their preparation. The aim of this study was to map microsatellite (SSR) markers linked to quantitative trait loci (QTLs) that govern the cooking time of common beans. An F₂ generation consisting of 140 families was generated from a cross between lines CNFM7875 and Laranja. The cooking time of the F_2:4 and F_2:5 generations was then evaluated, and the latter generation was tested in two environments. The analysis of variance found a significant effect for the interactions between the families (P < 0.01) in both the F_2:4 and F_2:5 generations, as well as for the group analyses performed in the two environments. The experimental coefficient of variation varied from 9.42 to 17.94%. The Pearson’s correlation test indicated no significant association between water absorption and cooking time. The heritability coefficients had values of 0.532 and 0.739 for the F_2:5 families evaluated at the two different locations, and the group analysis of the F_2:5 generation indicated that there was a significant genotype × environment interaction. Of the 105 polymorphic SSRs evaluated, 91 mapped to 12 linkage groups with an estimated map size of 1,303.7 cM. Six significant QTLs were detected in both environments, and the percentage of the phenotypic variation that was explained by these loci ranged from 11.54 to 21.63%. As the genetic control was oligogenic, the identification of QTLs should serve as an optimal starting point for the implementation of a selection program.     

Rapid genotyping with DNA micro-arrays for high-density linkage mapping and QTL mapping in common buckwheat (Fagopyrum esculentum Moench)

For genetic studies and genomics-assisted breeding, particularly of minor crops, a genotyping system that does not require a priori genomic information is preferable. Here, we demonstrated the potential of a novel array-based genotyping system for the rapid construction of high-density linkage map and quantitative trait loci (QTL) mapping. By using the system, we successfully constructed an accurate, high-density linkage map for common buckwheat (Fagopyrum esculentum Moench); the map was composed of 756 loci and included 8,884 markers. The number of linkage groups converged to eight, which is the basic number of chromosomes in common buckwheat. The sizes of the linkage groups of the P1 and P2 maps were 773.8 and 800.4 cM, respectively. The average interval between adjacent loci was 2.13 cM. The linkage map constructed here will be useful for the analysis of other common buckwheat populations. We also performed QTL mapping for main stem length and detected four QTL. It took 37 days to process 178 samples from DNA extraction to genotyping, indicating the system enables genotyping of genome-wide markers for a few hundred buckwheat plants before the plants mature. The novel system will be useful for genomics-assisted breeding in minor crops without a priori genomic information.     

QTL analysis and mapping of pre-harvest sprouting resistance in Sorghum

One of the most important agronomic problems in the production of sorghum [Sorghum bicolor (L.) Moench] in humid climates is pre-harvest sprouting (PHS). A molecular linkage map was developed using 112molecular markers in an F₂ mapping population derived from a cross between IS 9530 (high resistance to PHS) and Redland B2 (susceptible to PHS). Two year phenotypic data was obtained. By means of interval mapping analysis, two significant QTL were detected in two different linkage groups with LOD scores of 8.77and 4.39. Each of these two QTL individually explained approximately 53% of the phenotypic variance, but together, in a two-QTL model, they explained 83% of the phenotypic variance with a LOD score of 12.37.These results were corroborated by a one-way ANOVA in which the four flanking markers of the most likely QTL positions displayed highly significant values in theF-test, and significant variation in trait expression was associated with marker genotypic classes. The four markers with highest effect in the one-way ANOVA were also detected in the second year replication of the F₂ population, and significant genotype × environment interactions was observed. The putative relationship between PHS resistance in sorghum and the maize Vp1 gene is also discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

Efficiency of low heritability QTL mapping under high SNP density

The efficiency of quantitative trait locus (QTL) mapping methods needs to be investigated assuming high single nucleotide polymorphism (SNP) density and low heritability QTLs. This study assessed the efficiency of the least squares, maximum likelihood, and Bayesian approaches for QTL mapping assuming high SNP density and low heritability QTLs. We simulated 50 samples of 400 F₂ individuals, which were genotyped for 1000 SNPs (average density of one SNP/centiMorgan) and phenotyped for three traits controlled by 12 QTLs and 88 minor genes. The genes were randomly distributed in the regions covered by the SNPs along ten chromosomes. The QTL heritabilities ranged from approximately 1–2% and the sample sizes were 200 and 400. The power of QTL detection ranged from 30 to 60%, the false discovery rate (FDR) ranged from only 0.5–1.2%, and the bias in the QTL position ranged from 4 to 6 cM. The QTL mapping efficiency was not influenced by the degree of dominance. The statistical approaches were comparable regarding the FDR. Regression-based and simple interval mapping methods showed equivalent power of QTL detection and mapping precision. Compared to interval mapping, the inclusive composite interval mapping provided slightly greater QTL detection power and mapping precision only for the intermediate and high heritability QTLs. By maximizing the prior number of QTLs, the Bayesian analysis provided the greatest power of QTL detection. No method proved to be superior.     

Molecular and physical mapping of genes affecting awning in wheat

Quantitative trait loci (QTL) for three traits related to awning (awn length at the base, the middle and the top of the ear) in wheat were mapped in a doubled‐haploid line (DH) population derived from the cross between the cultivars ‘Courtot’ (awned) and ‘Chinese Spring’ (awnless) and grown in Clermont‐Ferrand, France, under natural field conditions. A molecular marker linkage map of this cross that was previously constructed based on 187 DH lines and 550 markers was used for the QTL mapping. The genome was well covered (more than 95%) and a set of anchor loci regularly spaced (one marker every 20.8 cM) was chosen for marker regression analysis. For each trait, only two consistent QTL were identified with individual effects ranging from 8.5 to 45.9% of the total phenotypic variation. These two QTL cosegregated with the genes Hd on chromosome 4A and B2 on chromosome 6B, which are known to inhibit awning. The results were confirmed using ‘Chinese Spring’ deletion lines of these two chromosomes, which have awned spikes, while ‘Chinese Spring’ is usually awnless. No quantitative trait locus was detected on chromosome 5A where the B1 awn‐inhibitor gene is located, suggesting that both ‘Courtot’ and ‘Chinese Spring’ have the same allelic constitution at this locus. The occurrence of awned speltoid spikes on the deletion lines of this chromosome suggests that ‘Chinese Spring’ and ‘Courtot’ have the dominant B1 allele, indicating that B1 alone has insufficient effect to induce complete awn inhibition.     

QTL mapping of bio-energy related traits in Sorghum

Plant height (PHT), stem and leaf fresh weight (SLFW), juice weight (JW) and sugar content of stem (Brix) are important traits for biofuel production in sweet Sorghum. QTL analysis of PHT, SLFW, JW and Brix was conducted with composite interval mapping using F₂ and F_2:3 populations derived from the cross between grain Sorghum (Shihong137) × sweet Sorghum (L-Tian). Three QTLs controlling PHT were mapped on SBI-01, SBI-07 and SBI-09 under four different environments. These QTLs could explain 10.16 to 45.29% of the phenotypic variance. Two major effect QTLs on SBI-07 and SBI-09 were consistently detected under four environments. Eight QTLs controlling SLFW were mapped across three environments and accounted for 5.49–25.36% of the phenotypic variance. One major QTL on SBI-09 located between marker Sb5-206 and SbAGE03 was observed under three environments. Four QTLs controlling Brix were identified under two environments and accounted for 11.03–17.65% of the phenotypic variance. Six QTLs controlling JW were detected under two environments, and explained 6.63–23.56% of the phenotypic variance. QTLs for JW on SBI-07 and SBI-09 were consistent in two environments showing higher environmental stability. In addition, two chromosome regions on SBI-07 and SBI-09 were identified in our study having major effect on PHT, SFLW and JW. The results would be useful for the genetic improvement of sweet Sorghum to be used for biofuel production.     

RFLP mapping of QTLs for photoperiod response in tropical sorghum

Genetic control of flowering time in sorghum was investigated using a recombinant inbred lines population derived from a cross between IS 2807, a slightly photoperiod sensitive tropical caudatum landrace, and IS 7680,a highly photoperiod sensitive tropical guinea landrace. Progenies were sown with their parents at six different dates between 1995 and 1997 in Burkina Faso. Direct field measures and synthetic measures derived from the implementation of a model were used to characterize the photoperiod response. Emphasis was put to identify the most relevant traits to account for Basic Vegetative Phase (BVP) and photoperiod sensitivity sensus stricto. One QTL was detected on Linkage Group (LG) F for the traits related to BVP. Two QTLs were detected on LGs C and H for the traits related to the photoperiod sensitivity sensus stricto. This gives credit to at least partially independent genetic determinisms for those two components of photoperiod response. Evidences for possible orthology of the QTLs detected here with other QTLs and major genes involved in flowering time of sorghum and rice are discussed. This revised version was published online in July 2006 with corrections to the Cover Date.