Putative quantitative trait loci associated with calcium content in soybean seed

Seed calcium content is an important quality attribute of specialty soybean [Glycine max (L.) Merr.] for soyfoods. However, analyzing seed for calcium content is time consuming and labor intensive. Knowing quantitative trait loci (QTL) for seed calcium will facilitate the development of elite cultivars with proper calcium content through marker-assisted selection (MAS). The objective of this study was to identify major QTL associated with calcium content in soybean seed. Calcium content was tested in 178 F(2:3) and 157 F(2:4) lines derived from the cross of SS-516 (low calcium) x Camp (high calcium). The F(2:3) lines were genotyped with 148 simple sequence repeat markers in a previous study on seed hardness, and the genotypic data were used in the QTL analysis of the current study. Four QTL designated as Ca1, Ca2, Ca3, and Ca4 on linkage groups (LGs) A2, I, and M were identified by both single-marker analysis and composite-interval mapping, and the QTL accounted for 10.7%, 16.3%, 14.9%, and 9.7% of calcium content variation, respectively. In addition, multiple-interval mapping analysis revealed a significant dominant-by-dominant interaction effect between Ca1 and Ca3, which accounted for 4.3% calcium content variation. These QTL will facilitate the implementation of MAS for calcium content in soybean-breeding programs.     

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 associated with chemical composition of the chicken carcass

Major objectives of the poultry industry are to increase meat production and to reduce carcass fatness, mainly abdominal fat. Information on growth performance and carcass composition are important for the selection of leaner meat chickens. To enhance our understanding of the genetic architecture underlying the chemical composition of chicken carcasses, an F₂ population developed from a broiler × layer cross was used to map quantitative trait loci (QTL) affecting protein, fat, water and ash contents in chicken carcasses. Two genetic models were applied in the QTL analysis: the line‐cross and the half‐sib models, both using the regression interval mapping method. Six significant and five suggestive QTL were mapped in the line‐cross analysis, and four significant and six suggestive QTL were mapped in the half‐sib analysis. A total of eleven QTL were mapped for fat (ether extract), five for protein, four for ash and one for water contents in the carcass using both analyses. No study to date has reported QTL for carcass chemical composition in chickens. Some QTL mapped here for carcass fat content match, as expected, QTL regions previously associated with abdominal fat in the same or in different populations, and novel QTL for protein, ash and water contents in the carcass are presented here. The results described here also reinforce the need for fine mapping and to perform multi‐trait analyses to better understand the genetic architecture of these traits.     

Quantitative trait loci underlying the development of seed composition in soybean (Glycine max L. Merr.).

One hundred and forty-three F2:7 recombinant inbred lines (RILs) developed from the cross of soybean cultivars 'Charleston' and 'Dongnong 594' were analyzed for the quantitative trait loci (QTLs) underlying protein or oil content at 6 different developmental stages by composite interval mapping with a mixed genetic model. The genotype x environment (GxE) interactions of the QTLs were also evaluated. Nineteen (2004) and 33 (2005) unconditional QTLs underlying seed protein or oil content at the different developmental stages were mapped onto 8 and 9 linkage groups, respectively. The proportion of phenotypic variation explained by these QTLs ranged from 6.26% to 30.52% and from 5.38% to 28.47%, respectively. Fourteen (2004) and 21 (2005) conditional QTLs underlying seed protein or oil content were mapped onto 5 and 8 linkage groups, respectively. The proportion of phenotypic variation explained by these QTLs ranged from 2.97% to 29.68% and from 5.42% to 31.96%, respectively. The numbers and types of QTLs and the genetic effect for the two traits were different at each developmental stage. However, several genomic regions that simultaneously control the development of both traits were detected. The genetic effect on protein content and oil content was opposite for loci in the marker interval Satt335-SSatt334, reflecting a negative correlation of protein content and oil content. A G x E interaction effect of some QTLs underlying protein or oil content at different growth periods was observed.     

Quantitative trait loci affecting seed mineral concentrations in Brassica napus grown with contrasting phosphorus supplies

MethodsA population of 124 recombinant inbred lines derived from a cross between P-inefficient ‘B104-2’ and P-efficient ‘Eyou Changjia’ was used for phenotypic investigation and QTL analysis. Two-year field trials were conducted with two P treatments. Concentrations of mineral elements (P, Ca, Mg, Fe, Zn, Cu and Mn) in seeds were determined and QTLs were identified by composite interval mapping.ConclusionsThe accumulation of mineral elements in seeds is controlled by multiple genes. Common physiological and molecular mechanisms could be involved in the accumulation of several mineral elements, and genes involved in these processes in B. napus are suggested. These results offer insights to the genetic basis of seed mineral accumulation across different P levels in B. napus.     

Quantitative trait loci associated with oligosaccharide and sucrose contents in soybean (Glycine max L.)

Oligosaccharides and sucrose are very important nutritional components in soybean seeds. However, little information is available about their inheritance. We used molecular markers to identify the genomic regions significantly associated with the quantitative trait locus (QTL) that controls oligosaccharide and sucrose contents in segregating F_2:10 Rl lines. Two related, but independent, QTLs were identified for oligosaccharides — near marker satt546 on linkage group (LG) D1b+W and satt278 on LG L. Four others, for sucrose content, were located at LG B1 (satt197), D1b+W (satt546), and L (satt523 and satt278). Finally, we found two common QTLs, on LG D1b+W and L, that are associated with both oligosaccharides and sucrose.     

Quantitative trait loci and molecular markers associated with wheat allelopathy

Wheat (Triticum aestivum L.) has been examined for allelopathic potential against annual ryegrass (Lolium rigidum). The bioassay technique, 'equal-compartment-agar-method', was employed to evaluate seedling allelopathy in a doubled-haploid (DH) population derived from cv Sunco (weakly allelopathic) and cv Tasman (strongly allelopathic). A significant difference in allelopathic activity was found among the DH lines, which inhibited the root length of ryegrass across a range from 23.7 to 88.3%. The phenotypic data showed that wheat allelopathic activity was distributed normally within this DH population and a substantial transgressive segregation for seedling allelopathic activity was also found. Analysis of restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP) and microsatellite (SSRs) markers identified two major QTLs on chromosome 2B associated with wheat allelopathy. The linkage analysis of genetic markers and the QTLs may improve genetic gains for the allelopathic activity through marker-assisted selection in wheat breeding. The development of wheat allelopathic cultivars could reduce the over-reliance of weed control on synthetic herbicides.Communicated by J. Dvorak     

Quantitative trait loci influencing honeybee alarm pheromone levels.

Quantitative trait loci (QTL) mapping procedures were used to identify loci that influence the levels of alarm pheromones found in the stinging apparatus of worker honeybees. An F1 queen was produced from a cross between a queen of European origin and a drone descended from an African subspecies. Haploid drones from the hybrid queen were individually backcrossed to European queens to produce 172 colonies. Samples of stings were taken from backcross workers of these colonies. Alarm pheromone levels were determined by gas chromatography. RAPD markers were scored from the haploid drone fathers of these colonies. The multiple-QTL model (MQM) of MapQTL was used to identify QTLs that influence the levels of four alarm pheromone components. Seven independent, potential QTLs were identified with LOD scores greater than two, and one at LOD 1.88. We identified one QTL for n-decyl acetate, three for n-octanol, four for isopentyl acetate, and one for hexyl acetate. One region of linkage group XI shows a strong influence on body size and the levels of three alarm pheromone components. This locus explained 40% of the variance for the amount of n-decyl acetate (LOD 6.57). In general, the QTLs influencing alarm pheromone levels were independent of previously identified loci that influenced the stinging behavior of these colonies. The only exception was a potential locus influencing levels of n-octanol, which was inversely correlated with stinging behavior.     

Quantitative trait loci associated with parasitic infection in Scottish blackface sheep

This study aimed to identify quantitative trait loci associated with endoparasitic infection in Scottish Blackface sheep. Data were collected from 789 animals over a 3-year period. All of the animals were continually exposed to a mixed nematode infection by grazing. Faecal samples were collected in August, September and October each year at ca. 16, 20 and 24 weeks of age; Nematodirus spp. eggs were counted separately from the other species of nematodes. Blood samples were collected in October from which immunoglobulin A (IgA) activity was measured and DNA was extracted for genotyping. In total, 139 Microsatellite markers were genotyped across eight chromosomal regions (chromosomes 1, 2, 3, 5, 14, 18, 20 and 21) in the sires and progeny were genotyped for the markers that were polymorphic in their sire. Evidence was found for quantitative trait loci (QTL) on chromosomes 2, 3, 14 and 20. QTL associated with specific IgA activity were identified in chromosomes 3 and 20, in regions close to IFNG (chromosome 3) and the MHC (chromosome 20). QTL associated with Nematodirus FEC were identified on chromosomes 2, 3 and 14. Lastly, QTL associated with non-Nematodirus Strongyle FEC were identified on chromosomes 3 and 20. This study has shown that some aspects of host resistance to gastrointestinal parasites are under strong genetic control, therefore these QTL could be utilised in a marker-assisted selection scheme to increase host resistance to gastrointestinal parasites.     

Quantitative trait loci associated with functional stay-green SNU-SG1 in rice

During monocarpic senescence in higher plants, functional stay-green delays leaf yellowing, maintaining photosynthetic competence, whereas nonfunctional stay-green retains leaf greenness without sustaining photosynthetic activity. Thus, functional stay-green is considered a beneficial trait that can increase grain yield in cereal crops. A stay-green japonica rice 'SNU-SG1' had a good seed-setting rate and grain yield, indicating the presence of a functional stay-green genotype. SNU-SG1 was crossed with two regular cultivars to determine the inheritance mode and identify major QTLs conferring stay-green in SNU-SG1. For QTL analysis, linkage maps with 100 and 116 DNA marker loci were constructed using selective genotyping with F2 and RIL (recombinant inbred line) populations, respectively. Molecular marker-based QTL analyses with both populations revealed that the functional stay-green phenotype of SNU-SG1 is regulated by several major QTLs accounting for a large portion of the genetic variation. Three main-effect QTLs located on chromosomes 7 and 9 were detected in both populations and a number of epistatic-effect QTLs were also found. The amount of variation explained by several digenic interactions was larger than that explained by main-effect QTLs. Two main-effect QTLs on chromosome 9 can be considered the target loci that most influence the functional stay-green in SNU-SG1. The functional stay-green QTLs may help develop low-input high-yielding rice cultivars by QTL-marker-assisted breeding with SNU-SG1.     

Quantitative trait loci associated with maximal exercise endurance in mice.

The role of genetics in the determination of maximal exercise endurance is unclear. Six- to nine-week-old F2 mice (n = 99; 60 female, 39 male), derived from an intercross of two inbred strains that had previously been phenotyped as having high maximal exercise endurance (Balb/cJ) and low maximal exercise endurance (DBA/2J), were treadmill tested to estimate exercise endurance. Selective genotyping of the F2 cohort (n = 12 high exercise endurance; n = 12 low exercise endurance) identified a significant quantitative trait locus (QTL) on chromosome X (53.7 cM, DXMit121) in the entire cohort and a suggestive QTL on chromosome 8 (36.1 cM, D8Mit359) in the female mice. Fine mapping with the entire F2 cohort and additional informative markers confirmed and narrowed the QTLs. The chromosome 8 QTL (EE8(F)) is homologous with two suggestive human QTLs and one significant rat QTL previously linked with exercise endurance. No effect of sex (P = 0.33) or body weight (P = 0.79) on exercise endurance was found in the F2 cohort. These data indicate that genetic factors in distinct chromosomal regions may affect maximal exercise endurance in the inbred mouse. Whereas multiple genes are located in the identified QTL that could functionally affect exercise endurance, this study serves as a foundation for further investigations delineating the identity of genetic factors influencing maximum exercise endurance.     

Quantitative trait loci associated with body weight and abdominal fat traits on chicken chromosomes 3, 5 and 7

Body weight and abdominal fat traits in meat-type chickens are complex and economically important factors. Our objective was to identify quantitative trait loci (QTL) responsible for body weight and abdominal fat traits in broiler chickens. The Northeast Agricultural University Resource Population (NEAURP) is a cross between broiler sires and Baier layer dams. We measured body weight and abdominal fat traits in the F(2) population. A total of 362 F(2) individuals derived from four F(1) families and their parents and F(0) birds were genotyped using 29 fluorescent microsatellite markers located on chromosomes 3, 5 and 7. Linkage maps for the three chromosomes were constructed and interval mapping was performed to identify putative QTLs. Nine QTL for body weight were identified at the 5% genome-wide level, while 15 QTL were identified at the 5% chromosome-wide level. Phenotypic variance explained by these QTL varied from 2.95 to 6.03%. In particular, a QTL region spanning 31 cM, associated with body weight at 1 to 12 weeks of age and carcass weight at 12 weeks of age, was first identified on chromosome 5. Three QTLs for the abdominal fat traits were identified at the 5% chromosome-wide level. These QTLs explained 3.42 to 3.59% of the phenotypic variance. This information will help direct prospective fine mapping studies and can facilitate the identification of underlying genes and causal mutations for body weight and abdominal fat traits.     

Quantitative trait loci and comparative genomics of cereal cell wall composition

Quantitative trait loci (QTLs) affecting sugar composition of the cell walls of maize (Zea mays) pericarp were mapped as an approach to the identification of genes involved in cereal wall biosynthesis. Mapping was performed using the IBM (B73 x Mo17) recombinant inbred line population. There were statistically significant differences between B73 and Mo17 in content of xylose (Xyl), arabinose (Ara), galactose (Gal), and glucose. Thirteen QTLs were found, affecting the content of Xyl (two QTLs), Ara (two QTLs), Gal (five QTLs), Glc (two QTLs), Ara + Gal (one QTL), and Xyl + Glc (one QTL). The chromosomal regions corresponding to two of these, affecting Ara + Gal and Ara on maize chromosome 3, could be aligned with a syntenic region on rice (Oryza sativa) chromosome 1, which has been completely sequenced and annotated. The contiguous P1-derived artificial chromosome rice clones covering the QTLs were predicted to encode 117 and 125 proteins, respectively. Two of these genes encode putative glycosyltransferases, displaying similarity to carbohydrate-active enzyme database family GT4 (galactosyltransferases) or to family GT64 (C-terminal domain of animal heparan synthases). The results illustrate the potential of using natural variation, emerging genomic resources, and homeology within the Poaceae to identify candidate genes involved in the essential process of cell wall biosynthesis.     

Molecular markers associated with seed weight in two soybean populations

Seed weight (SW) is a component of soybean, Glycine max (L.) Merr., seed yield, as well as an important trait for food-type soybeans. Two soybean populations, 120 F₄-derived lines of YoungxPI416937 (Pop1) and 111 F₂-derived lines of PI97100xCoker 237 (Pop2), were mapped with RFLP makers to identify quantitative trait loci (QTLs) conditioning SW across environments and populations. The genetic map of Pop1 consisted of 155 loci covering 973 cM, whereas Pop2 involved 153 loci and covered 1600 cM of map distance. For Pop1, the phenotypic data were collected from Plains, GA., Windblow, N.C., and Plymouth, N.C., in 1994. For Pop2, data were collected from Athens, GA., in 1994 and 1995, and Blackville, S.C., in 1995. Based on single-factor analysis of variance (ANOVA), seven and nine independent loci were associated with SW in Pop1 and Pop2, respectively. Together the loci explained 73% of the variability in SW in Pop1 and 74% in Pop2. Transgressive segregation occurred among the progeny in both populations. The marker loci associated with SW were highly consistent across environments and years. Two QTLs on linkage group (LG) F and K were located at similar genomic regions in both populations. The high consistency of QTLs across environments indicates that effective marker-assisted selection is feasible for soybean SW.     

A genome scan for quantitative trait loci associated with body weight at different developmental stages in chickens

A genome scan to detect quantitative trait loci (QTL) affecting body weight in chickens was conducted on 238 F(2) chickens from a reciprocal cross of Silky Fowl and White Plymouth Rock using 125 microsatellite markers covering 23 autosomes and the Z chromosome. Two types of QTL were considered: static QTL (SQ) and developmental QTL (DQ). Static QTL affected the body weight from hatch to time t, and DQ affected the body weight from time t-1 to time t. Six SQ and nine DQ were detected. Of these QTL, four reached a genome-wide significance of 5% or better, with SQ1 and DQ1 being the most significant QTL. Static QTL1 was on chromosome 1 between GCT0006 and MCW0106 and explained 4.05-9.80% of the phenotypic variation in body weights from 3 to 12 weeks of age. At 9, 10 and 11 weeks, the genome-wide significance thresholds of SQ1 were <1%. Developmental QTL1 was located on chromosome 1 between MCW0168 and GCT0006, and explained 2.75% of the phenotypic variation for body weight from week 7 to 8 with a genome-wide significance level <1%. The results suggest that body weight from hatch to time t and developmental growth from time t-1 to time t may involve two different sets of genes or gene actions.     

Quantitative trait loci for seed yield and yield-related traits, and their responses to reduced phosphorus supply in Brassica napus

Background and Aims

One of the key targets of breeding programmes in rapeseed (Brassica napus) is to develop high-yield varieties. However, the lack of available phosphorus (P) in soils seriously limits rapeseed production. The aim of this study was to dissect the genetic control of seed yield and yield-related traits in B. napus grown with contrasting P supplies.

Methods

Two-year field trials were conducted at one site with normal and low P treatments using a population of 124 recombinant inbred lines derived from a cross between ‘B104-2’ and ‘Eyou Changjia’. Seed yield, seed weight, seed number, pod number, plant height, branch number and P efficiency coefficient (PEC) were investigated. Quantitative trait locus (QTL) analysis was performed by composite interval mapping.

Key Results

The phenotypic values of most of the tested traits were reduced under the low P conditions. In total, 74 putative QTLs were identified, contributing 7·3–25·4 % of the phenotypic variation. Of these QTLs, 16 (21·6 %) were detected in two seasons and in the mean value of two seasons, and eight QTLs for two traits were conserved across P levels. Low-P-specific QTLs were clustered on chromosomes A1, A6 and A8. By comparative mapping between Arabidopsis and B. napus, 161 orthologues of 146 genes involved in Arabidopsis P homeostasis and/or yield-related trait control were associated with 45 QTLs corresponding to 23 chromosomal regions. Four gene-based markers developed from genes involved in Arabidopsis P homeostasis were mapped to QTL intervals.

Conclusions

Different genetic determinants were involved in controlling seed yield and yield-related traits in B. napus under normal and low P conditions. The QTLs detected under reduced P supply may provide useful information for improving the seed yield of B. napus in soils with low P availability in marker-assisted selection.     

Quantitative trait loci associated with fatness in a broiler–layer cross

An F₂ population established by crossing a broiler male line and a layer line was used to map quantitative trait loci (QTL) affecting abdominal fat weight, abdominal fat percentage and serum cholesterol and triglyceride concentrations. Two genetic models, the line-cross and the half-sib, were applied in the QTL analysis, both using the regression interval method. Three significant QTL and four suggestive QTL were mapped in the line-cross analysis and four significant and four suggestive QTL were mapped in the half-sib analysis. A total of five QTL were mapped for abdominal fat weight, six for abdominal fat percentage and four for triglyceride concentration in both analyses. New QTL associated with serum triglyceride concentration were mapped on GGA5, GGA23 and GG27. QTL mapped between markers LEI0029 and ADL0371 on GGA3 for abdominal fat percentage and abdominal fat weight and a suggestive QTL on GGA12 for abdominal fat percentage showed significant parent-of-origin effects. Some QTL mapped here match QTL regions mapped in previous studies using different populations, suggesting good candidate regions for fine-mapping and candidate gene searches.     

Quantitative trait loci associated with adaptation to Mediterranean dryland conditions in barley

The objective of the present study was to identify quantitative trait loci (QTL) influencing agronomic performance across rain fed Mediterranean environments in a recombinant inbred line (RIL) population derived from the barley cultivars ER/Apm and Tadmor. The population was tested in four locations (two in Syria and two in Lebanon) during four consecutive years. This allowed the analysis of marker main effects as well as of marker by location and marker by year within location interactions. The analysis demonstrated the significance of crossover interactions in environments with large differences between locations and between years within locations. Alleles from the parent with the higher yield potential, ER/Apm, were associated with improved performance at all markers exhibiting main effects for grain yield. The coincidence of main effect QTL for plant height and yield indicated that average yield was mainly determined by plant height, where Tadmor's taller plants, being susceptible to lodging, yielded less. However, a number of crossover interactions were detected, in particular for yield, where the Tadmor allele improved yield in the locations with more severe drought stress. The marker with the highest number of cross-over interactions for yield and yield component traits mapped close to the flowering gene Ppd-H2 and a candidate gene for drought tolerance HVA1 on chromosome 1H. Effects of these candidate genes and QTL may be involved in adaptation to severe drought as frequently occurring in the driest regions in the Mediterranean countries. Identification of QTL and genes affecting field performance of barley under drought stress is a first step towards the understanding of the genetics behind drought tolerance.     

Quantitative trait loci associated with drought tolerance at reproductive stage in rice

Drought is a major constraint to rice (Oryza sativa) yield and its stability in rainfed and poorly irrigated environments. Identifying genomic regions influencing the response of yield and its components to water deficits will aid in our understanding of the genetics of drought tolerance and development of more drought tolerant cultivars. Quantitative trait loci (QTL) for grain yield and its components and other agronomic traits were identified using a subset of 154 doubled haploid lines derived from a cross between two rice cultivars, CT9993-510 to 1-M and IR62266-42 to 6-2. Drought stress treatments were managed by use of a line source sprinkler irrigation system, which provided a linearly decreasing level of irrigation coinciding with the sensitive reproductive growth stages. The research was conducted at the Ubon Rice Research Center, Ubon, Thailand. A total of 77 QTL were identified for grain yield and its components under varying levels of water stress. Out of the total of 77 QTL, the number of QTL per trait were: 7-grain yield (GY); 8-biological yield (BY); 6-harvest index (HI); 5-d to flowering after initiation of irrigation gradient (DFAIG); 10-total spikelet number (TSN); 7-percent spikelet sterility (PSS); 23-panicle number (PN); and 11-plant height (PH). The phenotypic variation explained by individual QTL ranged from 7.5% to 55.7%. Under well-watered conditions, we observed a high genetic association for BY, HI, DFAIG, PSS, TSN, PH, and GY. However, only BY and HI were found to be significantly associated with GY under drought treatments. QTL flanked by markers RG104 to RM231, EMP2_2 to RM127, and G2132 to RZ598 on chromosomes 3, 4, and 8 were associated with GY, HI, DFAIG, BY, PSS, and PN under drought treatments. The aggregate effects of these QTL on chromosomes 3, 4, and 8 resulted in higher grain yield. These QTL will be useful for rainfed rice improvement, and will also contribute to our understanding of the genetic control of GY under drought conditions at the sensitive reproductive stage. Close linkage or pleiotropy may be responsible for the coincidence of QTL detected in this experiment. Digenic interactions between QTL main effects for GY, BY, HI, and PSS were observed under irrigation treatments. Most (but not all) DH lines have the same response in measure of productivity when the intensity of water deficit was increased, but no QTL by irrigation treatment interaction was detected. The identification of genomic regions associated with GY and its components under drought stress will be useful for marker-based approaches to improve GY and its stability for farmers in drought-prone rice environments.