Mapping major genes and quantitative trait loci controlling agronomic traits in almond

Six tree traits (self-compatibility, blooming date, blooming density, productivity, leafing date and ripening time) and five pomological traits (kernel taste, in-shell weight, shell hardness, kernel weight and double kernel) were studied in an F₁ almond progeny of 167 seedlings from the cross between the French cultivar 'R1000' and the Spanish cultivar 'Desmayo Largueta'. In addition, a set of 135 codominant microsatellites or simple-sequence repeat (SSR) markers developed from peach, cherry and almond were used for the molecular characterization of the progeny. A genetic linkage map was constructed with 56 of these SSRs. Cosegregation analysis allowed the identification of the map positions of two major genes to be confirmed for kernel taste ( Sk ) in linkage group five (G5) and for self-incompatibility ( S ) in G6. QTLs mapped include two for leafing date ( Lf-Q1 and Lf-Q2 ) in G1 and G4, one for shell hardness ( D-Q ) in G2, one each for double kernel ( Dk-Q ) and productivity ( P-Q ) in G4, one for blooming date ( Lb-Q ) in G4, two for kernel weight ( Kw-Q1 and Kw-Q2 ) in G1 and G4, and two for in-shell weight ( Shw-Q1 and Shw-Q2 ) in G1 and G2. Four SSR loci (BPPCT011, UDP96-013, UDP96-003 and PceGA025) were linked to the important agronomic traits of leafing date, shell hardness, blooming date and kernel taste. Finally, the development of efficient marker-assisted selection strategies applied to almond and other Prunus breeding programmes was also discussed.     

Molecular mapping of quantitative trait loci for field resistance to Fusarium head blight in a European winter wheat population

Fusarium head blight (FHB), one of the most destructive diseases of wheat in many parts of the world, can reduce the grain quality due to mycotoxin contamination up to rejection for usage as food or feed. Objective of this study was to map quantitative trait loci (QTL) associated with FHB resistance in the winter wheat population ‘G16‐92’ (resistant)/‘Hussar’. In all, 136 recombinant inbred lines were evaluated in field trials in 2001 and 2002 after spray inoculation with a Fusarium culmorum suspension. The area under disease progress curve was calculated based on the visually scored FHB symptoms. For means across all environments two FHB resistance QTL located on chromosomes 1A, and 2BL were identified. The individual QTL explained 9.7% and 14.1% of the phenotypic variance and together 26.7% of the genetic variance. The resistance QTL on 1A coincided with a QTL for plant height in contrast to the resistance QTL on 2BL that appeared to be independently inherited from morphological characteristics like plant height and ear compactness. Therefore, especially the QTL on 2BL could be of great interest for breeding towards FHB resistance.     

Identifying quantitative trait loci for the general combining ability of yield-relevant traits in maize

Maize is the most important staple crop worldwide. Many of its agronomic traits present with a high level of heterosis. Combining ability was proposed to exploit the rule of heterosis, and general combining ability (GCA) is a crucial measure of parental performance. In this study, a recombinant inbred line population was used to construct testcross populations by crossing with four testers based on North Carolina design II. Six yield-relevant traits were investigated as phenotypic data. GCA effects were estimated for three scenarios based on the heterotic group and the number of tester lines. These estimates were then used to identify quantitative trait loci (QTL) and dissect genetic basis of GCA. A higher heritability of GCA was obtained for each trait. Thus, testing in early generation of breeding may effectively select candidate lines with relatively superior GCA performance. The GCA QTL detected in each scenario was slightly different according to the linkage mapping. Most of the GCA-relevant loci were simultaneously detected in all three datasets. Therefore, the genetic basis of GCA was nearly constant although discrepant inbred lines were appointed as testers. In addition, favorable alleles corresponding to GCA could be pyramided via marker-assisted selection and made available for maize hybrid breeding.     

Fine mapping of quantitative trait loci using linkage disequilibrium in inbred plant populations

Linkage disequilibrium (LD)-based methods capitalize on the number of generations that occurred since the appearance of a mutation at a QTL and can produce extremely accurate estimates of the QTL position. Here, we describe a regression methodology to estimate the effect of marker haplotypes on a quantitative trait for the case of inbred plant populations. The method builds upon probabilities of being 'Identical by Descent' that are obtained via a gene-dropping simulation, where inbreeding is assumed to be due to a single seed descent process. The method was empirically tested via Monte Carlo simulation and results showed that the power to detect the true QTL position depended on the age of the QTL mutation, effective population size and marker distances. Also, increased marker polymorphism dramatically improved power and the method seemed fairly robust to differences in genetic and population assumptions. This revised version was published online in July 2006 with corrections to the Cover Date.     

Molecular mapping of major genes and quantitative trait loci determining flowering time in response to photoperiod in barley

Two major genes (eam8 and eam10) and two quantitative trait loci (QTL) determining flowering time in barley were associated with restriction fragment length polymorphism markers. The loci eam8 and eam10 were found to map in regions of chromosomes 1HL and 3HL, respectively, already estimated from previous classical linkage analyses. While investigating doubled haploid lines of a spring habit barley mapping population, two QTL for flowering time were detected on chromosomes 1HL and 7HS, respectively, when the material was grown under long photoperiod conditions. When growing the same lines under short photoperiod, no QTL were discernible. Allelic and homoeologous relationships with flowering time loci described earlier in barley and other Triticeae species are discussed.     

Genetic mapping of quantitative trait loci for fiber quality and yield trait by RIL approach in Upland cotton

The improvement of cotton fiber quality has become more important because of changes in spinning technology. Stable quantitative trait loci (QTLs) for fiber quality will enable molecular marker-assisted selection to improve fiber quality of future cotton cultivars. A simple sequence repeat (SSR) genetic linkage map consisting of 156 loci covering 1,024.4 cM was constructed using a series of recombinant inbred lines (RIL) developed from an F₂ population of an Upland cotton (Gossypium hirsutum L.) cross 7235 × TM-1. Phenotypic data were collected at Nanjing and Guanyun County in 2002 and 2003 for 5 fiber quality and 6 yield traits. We found 25 major QTLs (LOD ≥ 3.0) and 28 putative QTLs (2.0 < LOD < 3.0) for fiber quality and yield components in two or four environments independently. Among the 25 QTLs with LOD ≥ 3, we found 4 QTLs with large effects on fiber quality and 7 QTLs with large effects on yield components. The most important chromosome D8 in the present study was densely populated with markers and QTLs, in which 36 SSR loci within a chromosomal region of 72.7 cM and 9 QTLs for 8 traits were detected.     

Genetic mapping of quantitative trait loci in rye (Secale cereale L.)

Using the marker information of 275 F₂ plants quantitative traits determining morphological and yield characters were studied analyzing F₃progenies grown in four different experiments at three sites. The map constructed contains 113 markers including the major dwarfing gene Ddw1 with an average distance of about 10 cM between adjacent markers. Of the 21 QTLs detected ten were found to map on chromosome 5RL in the region of Ddw1. Beside the expected effects on plant height and peduncle length that are most probably due to the presence of the major dwarfing gene, additional effects on yield characters and flowering time were discovered in that region which may be caused by pleiotropic effects of Ddw1. An additional supposed gene cluster consisting of four QTLs controlling flowering time and yield components was discovered in the centromere region of chromosome 2R. Further loci are distributed on chromosomes 1R (1), 4R (1) 6R (3) and 7R (1). The map positions of the quantitative trait loci detected in rye are discussed in relation to major genes or QTLs determining agronomically important traits in other cereals. This revised version was published online in July 2006 with corrections to the Cover Date.     

Validation of two major quantitative trait loci for fusarium head blight resistance in Chinese wheat line W14

Identity of quantitative trait loci (QTL) governing resistance to fusarium head blight (FHB) initial infection (type I), spread (type II), kernel infection, and deoxynivalenol (DON) accumulation was characterized in Chinese wheat line W14. Ninety‐six double‐haploid lines derived from a cross of W14 × ’Pion2684’ were evaluated for FHB resistance in two greenhouse and one field experiment. Two known major QTL were validated on chromosomes 3BS and 5AS in W14 using the composite interval mapping method. The 3BS QTL had a larger effect on resistance than the 5AS QTL in the greenhouse experiments, whereas, the 5AS QTL had a larger effect in the field experiment. These two QTL together explained 33%, 35%, and 31% of the total phenotypic variation for disease spread, kernel infection, and DON concentration in the greenhouse experiments, respectively. In the field experiment, the two QTL explained 34% and 26% of the total phenotypic variation for FHB incidence and severity, respectively. W14 has both QTL, which confer reduced initial infection, disease spread, kernel infection, and DON accumulation. Therefore, marker‐assisted selection (MAS) for both QTL should be implemented in incorporating W14 resistance into adapted backgrounds. Flanking markers Xbarc133 and Xgwm493 on 3BS and Xbarc117 and Xbarc56 on 5AS are suggested for MAS.     

Molecular mapping of quantitative trait loci for grain moisture at harvest in maize

In maize, high grain moisture (GM) at harvest causes problems in harvesting, threshing, artificial drying, storage, transportation and processing. Understanding the genetic basis of GM will be useful for breeding low‐GM varieties. A quantitative genetics approach was used to identify quantitative trait loci (QTL) related to GM at harvest in field‐grown maize. The GM of a double haploid population consisting of 240 lines derived from Xianyu335 was evaluated in three planting seasons and a high‐density genetic linkage map covering 1546.4 cM was constructed. The broad‐sense heritability of GM at harvest was 71.0%. Using composite interval mapping, six QTL for GM at harvest were identified on five chromosomes (Chr). Two QTL located on Chr1, qgm1‐1 and qgm1‐2, explained 5.0% and 10.8% of the phenotypic variation in GM at harvest, respectively. The QTL qgm2, qgm3, qgm4 and qgm5 accounted for 3.3%, 8.3%, 5.4% and 11.0% of the mean phenotypic variation, respectively. Because of their consistent detection over multiple planting seasons, the detected QTL appear to be robust and reliable for the breeding of low‐GM varieties.     

Quantitative trait loci for agronomic and seed quality traits in an F2 and F4:6 soybean population

Molecular breeding is becoming more practical as better technology emerges. The use of molecular markers in plant breeding for indirect selection of important traits can favorably impact breeding efficiency. The purpose of this research is to identify quantitative trait loci (QTL) on molecular linkage groups (MLG) which are associated with seed protein concentration, seed oil concentration, seed size, plant height, lodging, and maturity, in a population from a cross between the soybean cultivars ‘Essex’ and ‘Williams.’ DNA was extracted from F₂ generation soybean leaves and amplified via polymerase chain reaction (PCR) using simple sequence repeat (SSR) markers. Markers that were polymorphic between the parents were analyzed against phenotypic trait data from the F₂ and F_4:6 generation. For the F₂ population, significant additive QTL were Satt540 (MLG M, maturity, r² = 0.11; height, r² = 0.04, seed size, r²= 0.06], Satt373 (MLG L, seed size, r² = 0.04; height, r² = 0.14), Satt50 (MLG A1, maturity r² = 0.07), Satt14 (MLG D2, oil, r² = 0.05), and Satt251 (protein r² = 0.03, oil, r² =0.04). Significant dominant QTL for the F₂ population were Satt540 (MLG M,height, r² = 0.04; seed size, r² = 0.06) and Satt14 (MLG D2, oil, r² = 0.05). In the F_4:6 generation significant additive QTL were Satt239 (MLGI, height, r² = 0.02 at Knoxville, TN and r² = 0.03 at Springfield, TN), Satt14 (MLG D2, seed size, r² = 0.14 at Knoxville, TN), Satt373 (MLG L, protein, r² = 0.04 at Knoxville, TN) and Satt251 (MLG B1, lodging r² = 0.04 at Springfield, TN). Averaged over both environments in the F_4:6 generation, significant additive QTL were identified as Satt251 (MLG B1, protein, r² = 0.03), and Satt239 (MLG I, height, r² = 0.03). The results found in this study indicate that selections based solely on these QTL would produce limited gains (based on low r² values). Few QTL were detected to be stable across environments. Further research to identify stable QTL over environments is needed to make marker-assisted approaches more widely adopted by soybean breeders. This revised version was published online in July 2006 with corrections to the Cover Date.     

An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: The basic concepts

Recognizing the enormous potential of DNA markers in plant breeding, many agricultural research centers and plant breeding institutes have adopted the capacity for marker development and marker-assisted selection (MAS). However, due to rapid developments in marker technology, statistical methodology for identifying quantitative trait loci (QTLs) and the jargon used by molecular biologists, the utility of DNA markers in plant breeding may not be clearly understood by non-molecular biologists. This review provides an introduction to DNA markers and the concept of polymorphism, linkage analysis and map construction, the principles of QTL analysis and how markers may be applied in breeding programs using MAS. This review has been specifically written for readers who have only a basic knowledge of molecular biology and/or plant genetics. Its format is therefore ideal for conventional plant breeders, physiologists, pathologists, other plant scientists and students.     

Co-localization of quantitative trait loci for foliar disease resistance in sorghum

Quantitative trait loci (QTL) analysis of resistance to three foliar diseases, viz. target leaf spot, zonate leaf spot and drechstera leaf blight was undertaken in sorghum using 168 F₇ recombinant inbred lines derived from a cross between '296B' (resistant) and 'IS18551' (susceptible) parents. The genomic region flanked by plant colour locus ( Plcor ) and simple sequence repeat marker Xtxp95 on chromosome SBI-06 harboured disease-response QTL for all the three diseases caused by different fungal pathogens. It is hypothesized that this region on sorghum chromosome SBI-06 could harbour a cluster of disease-response loci to different pathogens as observed in the syntenic regions on rice chromosome 4 and maize chromosome 2. The information gained in this study can be used in deploying marker-assisted selection for foliar resistance and map-based isolation of important disease resistance genes in sorghum.     

Genetic mapping of quantitative trait loci (QTL) for resistance to septoria tritici blotch in a winter wheat cultivar Liwilla

Septoria tritici blotch (STB), caused by Mycosphaerella graminicola (anamorph Septoria tritici, syn. Zymoseptoria tritici), is present in most wheat-growing areas worldwide. Resistance breeding appears to be the most sensible approach to disease control. An attempt was made to identify loci associated with resistance to STB in a resistant winter wheat cultivar Liwilla. In the study we used a set of 74 doubled-haploid lines generated from anthers of F₁ hybrids between the resistant cultivar Liwilla and susceptible cultivar Begra. Four monopycnidiospore isolates of M. graminicola with diverse pathogenicity were used in tests on seedlings under controlled growth conditions and on adult plants under polytunnel conditions over a six year period. In both environments, the percentage leaf area covered by necrosis and covered by pycnidia were measured; time to heading and plant height were also recorded for the polytunnel experiments. Seven isolate-specific quantitative trait loci (QTLs) were associated with STB resistance: QStb.ihar-3A.2, QStb.ihar-6A, QStb.ihar-7A.2, QStb.ihar-1B, QStb.ihar-2B.2, QStb.ihar-3B, and QStb.ihar-5D. QTL on chromosome 5D and 7A represent novel STB resistance loci. The phenotypic variance explained by individual QTLs ranged from 9.5 % to 50.3 %. Three QTLs detected on chromosomes 3A, 7A and 1B showed major effects and were detected consistently in different environments. The locations of QStb.ihar-3A.2 and QStb.ihar-1B coincide with the resistance genes Stb6 and Stb11, respectively. Locus QStb.ihar-3B and a QTL for time to heading mapped to the same location, but are most likely not associated. Most of the mapped QTLs explain the resistance associated with both low necrosis and low pycnidia coverage.     

Analysing genetic control of cooked grain traits and gelatinization temperature in a double haploid population of rice by quantitative trait loci mapping

Cooking quality in rice grains is a complex trait which requires improvement. Earlier reports show varying genetic influence on these traits, except for a common agreement on waxy (Wx) and alkali degeneration (Alk) loci on chromosome 6. The present study involved 86 doubled haploid lines derived from an indica × japonica cross involving IR64 and Azucena. Grain parameters viz., raw grain length (RGL), raw grain breadth (RGB), cooked grain length (CGL), cooked grain breadth (CGB), gelatinization temperature (GT), grain shape (RGS), length elongation ratio (LER) and breadth expansion ratio (BER) were subjected to mixed model mapping of quantitative trait loci (QTL). Segregation data of 175 markers covering a distance of 2395.5 cM spanning the entire genome were used. Fifteen main effect QTLs were detected spread over the genome, except on chromosomes 4, 8 and 11. Thirty epistatic interactions significantly influencing the traits were detected. Twelve of the main effect QTLs were involved in epistatic interactions. One main effect QTL associated with LER was detected near Alk locus. QTLs located for grain length on chromosomes 9 and 10 are reported for the first time. Detection of many epistatic loci and involvement of main effect QTLs in interactions demand for judicious selection of QTLs in marker-assisted selection programmes.     

Genetic variation in barley of crossability with wheat and its quantitative trait loci analysis

To study genetic variation in crossability, 80 barley accessions of diverse geographic origin consisting of 50 wild barleys (H. vulgare ssp. spontaneum or ssp. agriocrithon) and 30 cultivated barleys (H. vulgare ssp. vulgare) were crossed as the male parent with a highly crossable wheat variety, Shinchunaga. Crossabilities, expressed as the percentage of pollinated florets giving embryo-containing caryopses, ranged from 0% to 68.6%. Barley accessions from East Asia had generally a low crossability, while barley accessions from other regions exhibited a wider range of crossability including highly crossable genotypes. No significant difference in mean crossability was found between wild and cultivated barleys. To estimate the number and location of barley genes controlling the crossability, doubled haploid lines derived from the cross between the barley varieties Steptoe and Morex were crossed as the male parent with wheat. Quantitative trait loci (QTL) analysis using molecular markers identified four QTL. These were mapped to the centromeric regions of chromosomes 2H, 3H and 5H and the short arm of chromosome 7H. The QTL on chromosomes 3H and 5H had larger effects than those on chromosomes 2H and 7H. The four QTL collectively explained 35.4% of the total variance under a multiple QTL model. Relationships of the QTL identified in the present study with previously reported crossability genes of barley and wheat are discussed. This revised version was published online in August 2006 with corrections to the Cover Date.     

Molecular mapping of quantitative trait loci for plant growth, yield and yield related traits across three diverse locations in a doubled haploid rice population

A doubled haploid (DH) population of 125lines derived from IR64 × Azucena, an indica – japonica cross were grown in three different locations in India during the wet season of 1995. The parents of mapping population had diverse phenotypic values for the eleven traits observed. The DH lines exhibited considerable amount of variation for all the traits. Transgressive segregants were observed. Interval analysis with threshold LOD > 3.00 detected a total of thirty four quantitative trait loci (QTL) for eleven traits across three locations. The maximum number of twenty QTL were detected at Punjab location of North India. A total of seven QTL were identified for panicle length followed by six QTL for plant height. Eight QTL were identified on three chromosomes which were common across locations. A maximum of seven QTL were identified for panicle length with the peak LOD score of 6.01 and variance of 26.80%. The major QTL for plant height was located on Chromosome 1 with peak LOD score of 16.06 flanked by RZ730-RZ801 markers. Plant height had the maximum number of common QTL across environment at the same marker interval. One QTL was identified for grain yield per plant and four QTL for thousand grain weight. Clustering of QTL for different traits at the same marker intervals was observed for plant height, panicle exsertion, panicle number, panicle length and biomass production. This suggests that pleiotropism and or tight linkage of different traits could be the plausible reason for the congruence of several QTL. Common QTL identified across locations and environment provide an excellent opportunity for selecting stable chromosomal regions contributing to yield and yield components to develop QTL introgressed lines that can be deployed in rice breeding program. This revised version was published online in July 2006 with corrections to the Cover Date.     

Identification of quantitative trait loci for seed traits and floral morphology in a field-grown Lolium perenne × Lolium multiflorum mapping population

Lolium perenne L. (perennial ryegrass), and Lolium multiflorum Lam. (annual or Italian ryegrass), differ in several traits related to seed yield. Generally, L. multiflorum spikes are larger than L. perenne spikes, and have more spikelets, more florets per spikelet, larger seeds and awns. The greater number of spikelets and florets and larger seeds are associated with higher seed yield in L. multiflorum . Ryegrass ( Lolium sp.) cultivars are produced by seed multiplication and understanding the genetics of seed production traits would aid in plant improvement. A total of 30 QTL for seed production related traits were identified in this study. The QTLs were primarily located on linkage groups 2 and 4 which appear to be the most important for distinguishing L.   multiflorum and L. perenne . These QTL will be used to develop molecular markers for marker-assisted breeding and screening of L. perenne seed lots to detect seed contamination with L. multiflorum .     

Present and future of quantitative trait locus analysis in plant breeding

The joint analysis of genotype marker segregation and phenotypic values of individuals or lines enables the detection and location of loci affecting quantitative traits (QTL). The availability of DNA markers and powerful biometric methods has led to considerable progress in QTL mapping in plants. The most obvious applications of QTL analysis seem to be marker‐assisted selection (MAS) in breeding and pre‐breeding and QTL cloning. However, other areas are envisaged where QTL analysis can contribute decisively. These are: the understanding of complex traits such as plant‐pathogen interaction; plant genomics, connecting proteins and regulatory elements of known functions to QTL by candidate gene analysis; and germplasm enhancement through a characterization that allows its efficient utilization. The success in all these applications depends primarily on the reliability and accuracy of the QTL analysis itself. Therefore, the discussion of its limitations will constitute an important part of this review.