Identification of quantitative trait loci and associated candidate genes for low-temperature tolerance in cold-hardy winter wheat

Low-temperature (LT) tolerance is an important economic trait in winter wheat (Triticum aestivum L.) that determines the plants’ ability to cope with below freezing temperatures. Essential elements of the LT tolerance mechanism are associated with the winter growth habit controlled by the vernalization loci (Vrn-1) on the group 5 chromosomes. To identify genomic regions, which in addition to vrn-1 determine the level of LT tolerance in hexaploid wheat, two doubled haploid (DH) mapping populations were produced using parents with winter growth habit (vrn-A1, vrn-B1, and vrn-D1) but showing different LT tolerance levels. A total of 107 DH lines were analyzed by genetic mapping to produce a consensus map of 2,873 cM. The LT tolerance levels for the Norstar (LT₅₀=−20.7°C) × Winter Manitou (LT₅₀=−14.3°C) mapping population ranged from −12.0 to −22.0°C. Single marker analysis and interval mapping of phenotyped lines revealed a major quantitative trait locus (QTL) on chromosome 5A and a weaker QTL on chromosome 1D. The 5A QTL located 46 cM proximal to the vrn-A1 locus explained 40% of the LT tolerance variance. Two C-repeat Binding Factor (CBF) genes expressed during cold acclimation in Norstar were located at the peak of the 5A QTL.     

Detection and stability of quantitative trait loci (QTL) in Eucalyptus globulus

Eucalyptus globulus Labill. ssp. globulus is an important tree species for the pulp and paper industry, and several breeding programmes throughout the world are striving to improve key traits such as growth and wood density. This study aimed to detect quantitative trait loci (QTL) for growth, wood density, relative bark thickness and early flowering in a single full-sib E. globulus family grown across seven sites. Growth was measured a number of times over a 6-year period, enabling temporal stability of growth QTL to be studied. Ten putative QTL (LOD > 2.0) were detected in the single family, which was of moderate size. Based on permutations of the trait data, six of these QTL were significant at the experimentwise significance level of 0.1 for at least one of the four models implemented in analysis to remove site effects. For wood density, two putative QTL explained 20% of the variance for the trait, indicating that a small number of QTL might explain a reasonable proportion of the trait variance. One of these QTL was found to be independent of QTL for growth whereas the second QTL co-segregated with a QTL for relative incremental growth. The marker nearest to this QTL was associated with fast growth but low wood density. A putative growth QTL at year 6 was found to be relatively stable across ages. In addition, it was found that residuals from models based on measurements from across all families across all sites in the trial detected QTL with greater experimentwise significance.     

Maize leaf temperature responses to drought: Thermal imaging and quantitative trait loci (QTL) mapping

Leaf temperature has been shown to vary when plants are subjected to water stress conditions. Recent advances in infrared thermography have increased the probability of recording drought tolerant responses more accurately. The aims of this study were to identify the effects of drought on leaf temperature using infrared thermography. Furthermore, the genomic regions responsible for the expression of leaf temperature variation in maize seedlings (Zea mays L.) were explored. The maize inbred lines Zong3 and 87-1 were evaluated using infrared thermography and exhibited notable differences in leaf temperature response to water stress. Correlation analysis indicated that leaf temperature response to water stress played an integral role in maize biomass accumulation. Additionally, a mapping population of 187 recombinant inbred lines (RILs) derived from a cross between Zong3 and 87-1 was constructed to identify quantitative trait loci (QTL) responsible for physiological traits associated with seedling water stress. Leaf temperature differences (LTD) and the drought tolerance index (DTI) of shoot fresh weight (SFW) and shoot dry weight (SDW) were the traits evaluated for QTL analysis in maize seedlings. A total of nine QTL were detected by composite interval mapping (CIM) for the three traits (LTD, RSFW and RSDW). Two co-locations responsible for both RSFW and RSDW were detected on chromosomes 1 and 2, respectively, which showed common signs with their trait correlations. Another co-location was detected on chromosome 9 between LTD and shoot biomass, which provided genetic evidence that leaf temperature affects biomass accumulation. Additionally, the utility of a thermography system for drought tolerance breeding in maize was discussed.     

Estimation of the contribution of quantitative trait loci (QTL) to the variance of a quantitative trait by means of genetic markers

The estimation of the contribution of an individual quantitative trait locus (QTL) to the variance of a quantitative trait is considered in the framework of an analysis of variance (ANOVA). ANOVA mean squares expectations which are appropriate to the specific case of QTL mapping experiments are derived. These expectations allow the specificities associated with the limited number of genotypes at a given locus to be taken into account. Discrepancies with classical expectations are particularly important for two-class experiments (backcross, recombinant inbred lines, doubled haploid populations) and F₂ populations. The result allows us firstly to reconsider the power of experiments (i.e. the probability of detecting a QTL with a given contribution to the variance of the trait). It illustrates that the use of classical formulae for mean squares expectations leads to a strong underestimation of the power of the experiments. Secondly, from the observed mean squares it is possible to estimate directly the variance associated with a locus and the fraction of the total variance associated to this locus (r _l ² ). When compared to other methods, the values estimated using this method are unbiased. Considering unbiased estimators increases in importance when (1) the experimental size is limited; (2) the number of genotypes at the locus of interest is large; and (3) the fraction of the variation associated with this locus is small. Finally, specific mean squares expectations allows us to propose a simple analytical method by which to estimate the confidence interval of r _l ² . This point is particularly important since results indicate that 95% confidence intervals for r _l ² can be rather wide:2–23% for a 10% estimate and 8–34% for a 20% estimate if 100 individuals are considered.     

玉米杂交种掖单13号的SSR连锁图谱构建与叶夹角和叶向值的QTL定位与分析

为了增加单位面积产量, 玉米育种者已经开始了更密植更紧凑株型的选育。叶夹角和叶向值是评价玉米株型的重要指标。本研究以掖478×丹340的500个F2单株为作图群体, 构建了具有138个位点的SSR标记连锁图谱, 图谱总长度为1 394.9 cM, 平均间距10.1 cM。利用397个F2：3家系对叶夹角和叶向值进行QTL定位分析, 结果表明: 叶夹角和叶向值分别检测到6和8个QTL, 累计解释表型变异41.0%和60.8%, 单个QTL的贡献率在2.9%~13.6%之间。与叶夹角和叶向值有关的基因主要作用方式为加性和部分显性。此外两个性状共检测到9对上位性互作位点, 表明上位性互作在叶夹角和叶向值的遗传中也起较重要的作用。     

Epistatic expression of quantitative trait loci (QTL) in soybean [Glycine max (L.) Merr.] determined by QTL association with RFLP alleles

Quantitative trait values for seed oil and protein content or for maturity were measured in recombinant inbred lines (RIL) of soybean derived from a cross between two soybean cultivars: Minsoy PI 27890 and Noir 1 PI 290136. Seed oil was found to be inversely correlated to protein content. By analyzing DNA from plants with extreme phenotypes, we were able to identify quantitative trait loci (QTL) for these traits as being linked to several restriction fragment length polymorphism (RFLP) loci, including R183 for oil and protein content and R79 for maturity. Cumulative distributions of trait values were graphed for those RIL with Minsoy alleles and for those with Noir 1 alleles. As already suggested by the alleles found associated with extreme phenotypes, the distributions were consistent with an independent and additive expression of the maturity QTL linked to R79. That is, the cumulative distributions for plants with Minsoy alleles and for plants with Noir 1 alleles were similar in shape, but the entire Noir 1 curve had been shifted to later maturity dates. In contrast, the trait distributions for a locus affecting oil and protein content linked to R183 were not compatible with an additive model. These results suggest that this approach can be used for rapid identification of QTLs with epistatic expression.     

Identification of quantitative trait loci associated with bone traits and body weight in an F2 resource population of chickens*

Bone fractures at the end of lay are a significant problem in egg-laying strains of hens. The objective of the current study was to identify quantitative trait loci (QTL) associated with bone mineralization and strength in a chicken resource population. Layer (White Leghorn hens) and broiler (Cobb-Cobb roosters) lines were crossed to generate an F2 population of 508 hens over seven hatches, and 26 traits related to bone integrity, including bone mineral density (BMD) and content (BMC), were measured. Genotypes of 120 microsatellite markers on 28 autosomal groups were determined, and interval mapping was conducted to identify QTL regions. Twenty-three tests representing three chromosomal regions (chromosomes 4, 10 and 27) contained significant QTL that surpassed the 5% genome-wise threshold, and 47 tests representing 15 chromosomes identified suggestive QTL that surpassed the 5% chromosome-wise threshold. Although no significant QTL influencing BMD and BMC were detected after adjusting for variation in body weight and egg production, multiple suggestive QTL were found. These results support previous experiments demonstrating an important genetic regulation of bone strength in chickens, but suggest the regulation may be due to the effects of multiple genes that each account for relatively small amounts of variation in bone strength.     

犬髋关节发育不良数量性状位点及致病基因研究进展

犬髋关节发育不良(canine hip dysplasia,CHD)是一种以髋关节松弛为主要特征的先天遗传性疾病,受环境和基因共同作用,发病率较高,但其发病机制尚未完全明了。近年来,在CHD基因组学研究方面取得了重要进展,譬如,发现数量性状位点(quantitative trait locus,QTL)与CHD中髋关节Norberg角、背外侧半脱位评分及分离指数存在联系,FBN2、LRR1、COL6A3与FN1等基因也与CHD的发生相关。为进一步明确CHD的发病机制,本文就CHD相关的QTL及相关候选致病基因的研究进展,尤其对相关QTL在染色体中的位置与功能以及候选致病基因的功能进行综述。     

Analysis of quantitative trait loci (QTLs) and quantitative trait alleles (QTAs) for potato tuber yield and starch content

 Using RFLP markers, QTLs for tuber starch-content and tuber yield were mapped in two F₁ populations derived from crossing non-inbred di-haploid potato breeding lines. QTLs were identified and mapped, based on both single-marker tests and interval analyses. A model specifically developed for interval QTL analysis in non-inbred plant species was successfully applied for the first time to experimental data. Results of both methods of QTL analysis were similar but not identical. QTLs for tuber starch-content and tuber yield were analysed in segregating populations K31 and LH in five and two environments, respectively. Population K31 was fully genotyped whereas population LH was selectively genotyped according to high and low tuber-starch content. Eighteen putative QTLs for tuber starch-content were identified on all 12 potato linkage groups and eight putative QTLs for tuber yield were identified on eight linkage groups. Twenty of twenty six putative QTLs were reproducibly detected in at least two environments and/or mapping populations. Few major QTLs for tuber starch-content were highly stable across environments but were detected in only one of the two mapping populations analysed. Most QTLs for tuber yield were linked with QTLs for tuber starch-content suggesting that the effects on both traits are controlled by the same genetic factors. The results are discussed with respect to marker-assisted selection in potato. Received: 9 March 1998 / Accepted: 29 April 1998     

Identification of diabetes susceptibility loci in db mice by combined quantitative trait loci analysis and haplotype mapping

To identify the disease-susceptibility genes of type 2 diabetes, we performed quantitative trait loci (QTL) analysis in F(2) populations generated from a BKS.Cg-m+/+Lepr(db) and C3H/HeJ intercross, taking advantage of genetically determined obesity and diabetes traits associated with the db gene. A genome-wide scan in the F(2) populations divided by sex and db genotypes identified 14 QTLs in total and 3 major QTLs on chromosome (Chr) 3 (LOD 5.78) for fat pad weight, Chr 15 (LOD 6.64) for body weight, and Chr 16 (LOD 8.15) for blood glucose concentrations. A linear-model-based genome scan using interactive covariates allowed us to consider sex- or sex-by db-specific effects of each locus. For the most significant QTL on Chr 16, the high-resolution haplotype comparison between BKS and C3H strains reduced the critical QTL interval from 20 to 4.6 Mb by excluding shared haplotype regions and identified 11 nonsynonymous single-nucleotide polymorphisms in six candidate genes.     

Identification of quantitative trait loci (QTLs) for heading date and plant height in cultivated rice (Oryza sativa L.)

Lemont and Teqing are both semidwarf rice varieties that differ in heading date by only 6 days. However, when Lemont and Teqing are crossed there is transgressive segregation for both heading date (HD) and plant height (PH). By testing 2418 F₄ lines with 113 well-distributed RFLP markers, we identified and mapped chromosomal regions that were largely responsible for this transgressive segregation. QHd3a, a QTL from Lemont that gives 8 days earlier heading, was identified on chromosome 3 approximately 3 cM from the marker RG348. Another QTL with a large effect, QHd8a, which gives 7 days earlier heading, was identified on chromosome 8 of Teqing between RG20 and RG1034. Along with a QTL, QHd9a with a phenotypic effect of 3.5 days, these genomic regions collectively explain 76.5% of the observed phenotypic variance in heading date. Four QTLs which altered plant height from 4 to 7 cm were also mapped; these collectively explain 48.8% of the observed phenotypic variation in plant height. None of the QTLs for plant height mapped to chromosome 1, the location of the semidwarf gene sd-1. All three of the HD loci mapped to approximately the same genomic locations as PH QTLs, and in all cases, there was a reduction in height of approximately 1 cm for every day of earlier heading. The correspondence between the HD and some of the PH loci suggests that genes at these chromosome locations may have pleiotropic effects on both HD and PH. The observed heterosis in the F₁ plants for HD can be largely explained by the dominance for earliness of the identified HD loci and distribution of earlier heading alleles in the parents. However, overdominance observed at one of the PH QTL may, at least in part, be responsible for the observed heterosis in PH.     

Identification of quantitative trait loci and candidate genes for an anxiolytic‐like response to ethanol in BXD recombinant inbred strains

Genetic differences in acute behavioral responses to ethanol contribute to the susceptibility to alcohol use disorder and the reduction of anxiety is a commonly reported motive underlying ethanol consumption among alcoholics. Therefore, we studied the genetic variance in anxiolytic‐like responses to ethanol across the BXD recombinant inbred (RI) mouse panel using the light–dark transition model of anxiety. Strain‐mean genetic mapping and a mixed‐model quantitative trait loci (QTL) analysis replicated several previously published QTL for locomotor activity and identified several novel anxiety‐related loci. Significant loci included a chromosome 11 saline anxiety‐like QTL (Salanq1) and a chromosome 12 locus (Etanq1) influencing the anxiolytic‐like response to ethanol. Etanq1 was successfully validated by studies with BXD advanced intercross strains and fine‐mapped to a region comprising less than 3.5 Mb. Through integration of genome‐wide mRNA expression profiles of the mesocorticolimbic reward circuit (prefrontal cortex, nucleus accumbens and ventral midbrain) across the BXD RI panel, we identified high priority candidate genes within Etanq1, the strongest of which was Ninein (Nin), a Gsk3β‐interacting protein that is highly expressed in the brain.     

Quantitative trait loci and candidate genes associated with starch pasting viscosity characteristics in cassava (Manihot esculenta Crantz)

Starch pasting viscosity is an important quality trait in cassava (Manihot esculenta Crantz) cultivars. The aim here was to identify loci and candidate genes associated with the starch pasting viscosity. Quantitative trait loci (QTL) mapping for seven pasting viscosity parameters was carried out using 100 lines of an F₁ mapping population from a cross between two cassava cultivars Huay Bong 60 and Hanatee. Starch samples were obtained from roots of cassava grown in 2008 and 2009 at Rayong, and in 2009 at Lop Buri province, Thailand. The traits showed continuous distribution among the F₁ progeny with transgressive variation. Fifteen QTL were identified from mean trait data, with Logarithm of Odds (LOD) values from 2.77–13.01 and phenotype variations explained (PVE) from10.0–48.4%. In addition, 48 QTL were identified in separate environments. The LOD values ranged from 2.55–8.68 and explained 6.6–43.7% of phenotype variation. The loci were located on 19 linkage groups. The most important QTL for pasting temperature (PT) (qPT.1LG1) from mean trait values showed largest effect with highest LOD value (13.01) and PVE (48.4%). The QTL co‐localised with PT and pasting time (PTi) loci that were identified in separate environments. Candidate genes were identified within the QTL peak regions. However, the major genes of interest, encoding the family of glycosyl or glucosyl transferases and hydrolases, were located at the periphery of QTL peaks. The loci identified could be effectively applied in breeding programmes to improve cassava starch quality. Alleles of candidate genes should be further studied in order to better understand their effects on starch quality traits.     

Identification of quantitative trait loci (QTL) for fruit-quality traits and number of weeks of flowering in the cultivated strawberry

Fruit quality and repeat flowering are two major foci of several strawberry breeding programs. The identification of quantitative trait loci (QTL) and molecular markers linked to these traits could improve breeding efficiency. In this work, an F₁ population derived from the cross ‘Delmarvel’ × ‘Selva’ was used to develop a genetic linkage map for QTL analyses of fruit-quality traits and number of weeks of flowering. Some QTL for fruit-quality traits were identified on the same homoeologous groups found in previous studies, supporting trait association in multiple genetic backgrounds and utility in multiple breeding programs. None of the QTL for soluble solids colocated with a QTL for titratable acids, and, although the total soluble solid contents were significantly and positively correlated with titratable acids, the correlation coefficient value of 0.2452 and independence of QTL indicate that selection for high soluble solids can be practiced independently of selection for low acidity. One genomic region associated with the total number of weeks of flowering was identified quantitatively on LG IV-S-1. The most significant marker, FxaACAO2I8C-145S, explained 43.3 % of the phenotypic variation. The repeat-flowering trait, scored qualitatively, mapped to the same region as the QTL. Dominance of the repeat-flowering allele was demonstrated by the determination that the repeat-flowering parent was heterozygous. This genomic region appears to be the same region identified in multiple mapping populations and testing environments. Markers linked in multiple populations and testing environments to fruit-quality traits and repeat flowering should be tested widely for use in marker-assisted breeding.     

Identification of quantitative trait loci (QTL) for oil and protein contents and their relationships with other seed quality traits in Brassica juncea

A detailed RFLP-genomic map was used to study the genetics of oil, seed and meal protein and sum of oil and seed/meal protein contents in a recombinant doubled-haploid population developed by crossing black- and yellow-seeded Brassica juncea lines. Two yellow seed color genes (SC-B4, SC-A6) and one QTL for erucic acid content (E_1b) showed pleiotropic effect for oil, protein and sum of oil and seed/meal protein contents. Six (O-A1, O-A6, O-A9, O-B3, O-B4, O-B5) and five (SP-A1, SP-A9, SP-B4, SP-B6, SP-C) QTLs were significant for oil and seed protein contents, respectively. Tight linkage of three of these QTLs (SP-A1, SP-A9, SP-B4, O-A1, O-A9, O-B4), with opposite effects, poses challenge to the plant breeders for simultaneous improvement of negatively correlated (r = −0.7**) oil and seed protein contents. However, one QTL for oil content (O-B3) and two for seed protein content (SP-B6, SP-C) were found to be unlinked, which offer the possibility for simultaneous improvement of these two traits. QTLs significant for meal protein (MP-A1, MP-A6, MP-A9, MP-B5, MP-B6) were significant at least for oil, seed protein or sum of oil and seed/meal protein contents (T-A6, T-A7, T-B4, T-B5). Sum of oil and seed protein contents and sum of oil and meal protein contents had a perfect correlation, as well as same epistatic interactions and QTLs with similar additive effect. This indicates that protein in seed or meal has practically the same meaning for breeding purposes. Epistatic interactions were significant for the quality traits, and their linkage reflected association among the traits.     

A genome-wide survey of maize lipid-related genes: candidate genes mining,digital gene expression profiling and co-location with QTL for maize kernel oil

Lipids play an important role in plants due to their abundance and their extensive participation in many metabolic processes. Genes involved in lipid metabolism have been extensively studied in Arabidopsis and other plant species. In this study, a total of 1003 maize lipid-related genes were cloned and annotated, including 42 genes with experimental validation, 732 genes with full-length cDNA and protein sequences in public databases and 229 newly cloned genes. Ninety-seven maize lipid-related genes with tissue-preferential expression were discovered by in silico gene expression profiling based on 1984483 maize Expressed Sequence Tags collected from 182 cDNA libraries. Meanwhile, 70 QTL clusters for maize kernel oil were identified, covering 34.5% of the maize genome. Fifty-nine (84%) QTL clusters co-located with at least one lipid-related gene, and the total number of these genes amounted to 147. Interestingly, thirteen genes with kernel-preferential expression profiles fell within QTL clusters for maize kernel oil content. All the maize lipid-related genes identified here may provide good targets for maize kernel oil QTL cloning and thus help us to better understand the molecular mechanism of maize kernel oil accumulation.     

A mixed-model quantitative trait loci (QTL) analysis for multiple-environment trial data using environmental covariables for QTL-by-environment interactions, with an example in maize

Complex quantitative traits of plants as measured on collections of genotypes across multiple environments are the outcome of processes that depend in intricate ways on genotype and environment simultaneously. For a better understanding of the genetic architecture of such traits as observed across environments, genotype-by-environment interaction should be modeled with statistical models that use explicit information on genotypes and environments. The modeling approach we propose explains genotype-by-environment interaction by differential quantitative trait locus (QTL) expression in relation to environmental variables. We analyzed grain yield and grain moisture for an experimental data set composed of 976 F(5) maize testcross progenies evaluated across 12 environments in the U.S. corn belt during 1994 and 1995. The strategy we used was based on mixed models and started with a phenotypic analysis of multi-environment data, modeling genotype-by-environment interactions and associated genetic correlations between environments, while taking into account intraenvironmental error structures. The phenotypic mixed models were then extended to QTL models via the incorporation of marker information as genotypic covariables. A majority of the detected QTL showed significant QTL-by-environment interactions (QEI). The QEI were further analyzed by including environmental covariates into the mixed model. Most QEI could be understood as differential QTL expression conditional on longitude or year, both consequences of temperature differences during critical stages of the growth.     

Identification and verification of QTL associated with growth traits in two genetic backgrounds of Barramundi (Lates calcarifer)

Quantitative trait loci (QTL) affecting growth traits have previously been mapped in linkage groups (LG) 2, 3 and 23 of Barramundi ( Lates carcalifer ), but these QTL have not been verified in different genetic backgrounds and environments. Here, we report the identification and verification of QTL for growth traits on LG2, 3, 10 and 23 in F₁ families constructed using brooders from the Singapore Marine Aquaculture Center (MAC) and from wild stocks collected in Thailand (THAI). The previously detected QTL for body weight and length linked to marker Lca371 on LG2 were confirmed in both the MAC and THAI families, whereas other QTL previously mapped to LG3 and 23 were only detected in one of the two families. QTL for body weight and length were identified in the MAC family, but not in the THAI family, in a region where the insulin-like growth factor 2 ( IGF2 ) and tyrosine hydroxylase 1 ( TH1 ) genes are located on LG10. Significant epistatic interactions were identified between markers Lca287 on LG2 and IGF2 on LG10 for growth trait QTL in the MAC family, but not in the THAI family. Effects of the IGF2 , TH1 and parvalbumin 1 candidate genes were family-specific. Our results indicate that some but not all QTL are family-specific in Barramundi.