Model analysis of flowering phenology in recombinant inbred lines of barley

A generic model for flowering phenology as a function of daily temperature and photoperiod was applied to predict differences of flowering times among 96 individuals (including the two parents) of a recombinant inbred line population in barley (Hordeum vulgare L.). Because of the large number of individuals to study, there is a need for simple ways to derive model parameters for each genotype. Therefore the number of genotype-specific parameters was reduced to four, namely f(o) (the minimum number of days to flowering at the optimum temperature and photoperiod), (1) and (2) (the development stages for the start and the end of the photoperiod-sensitive phase, respectively), and delta (the photoperiod sensitivity). Values of these parameters were estimated using a newly described methodological framework based on data from a photoperiod-controlled experiment where plants were mutually transferred between long-day and short-day environments at regular intervals. This modelling approach was tested in eight independent field environments of different sowing dates in two growing seasons. The four-parameter model predicted 37-67% of observed phenotypic variation in an environment, 76% of variation in across-environment mean days to flowering among the genotypes, and 96% of variation in across-genotype mean among the eight environments. When all the observations of the 96 genotypes across the eight environments were pooled, the model explained 81% of the total variation. Sensitivity analysis showed that all four model parameters were important for predicting differences in flowering time among the genotypes; but their relative importance differed and the ranking was in the order of f(o), delta, theta1, and theta2. This study highlighted the potential of using ecophysiological models to assist the genetic analysis of quantitative crop traits whose phenotype is often environment-dependent.     

Combining quantitative trait Loci analysis and an ecophysiological model to analyze the genetic variability of the responses of maize leaf growth to temperature and water deficit

Ecophysiological models predict quantitative traits of one genotype in any environment, whereas quantitative trait locus (QTL) models predict the contribution of alleles to quantitative traits under a limited number of environments. We have combined both approaches by dissecting into effects of QTLs the parameters of a model of maize (Zea mays) leaf elongation rate (LER; H. Ben Haj Salah, F. Tardieu [1997] Plant Physiol 114: 893-900). Response curves of LER to meristem temperature, water vapor pressure difference, and soil water status were established in 100 recombinant inbred lines (RILs) of maize in six experiments carried out in the field or in the greenhouse. All responses were linear and common to different experiments, consistent with the model. A QTL analysis was carried out on the slopes of these responses by composite interval mapping confirmed by bootstrap analysis. Most QTLs were specific of one response only. QTLs of abscisic acid concentration in the xylem sap colocalized with QTLs of response to soil water deficit and conferred a low response. Each parameter of the ecophysiological model was computed as the sum of QTL effects, allowing calculation of parameters for 11 new RILs and two parental lines. LERs were simulated and compared with measurements in a growth chamber experiment. The combined model accounted for 74% of the variability of LER, suggesting that it has a general value for any RIL under any environment.     

Selection on QTL and complex traits in complex environments

Understanding genetic variation for complex traits in heterogeneous environments is a fundamental problem in biology. In this issue of Molecular Ecology, Fournier‐Level et al. ( 2013 ) analyse quantitative trait loci (QTL) influencing ecologically important phenotypes in mapping populations of Arabidopsis thaliana grown in four habitats across its native European range. They used causal modelling to quantify the selective consequences of life history and morphological traits and QTL on components of fitness. They found phenology QTL colocalizing with known flowering time genes as well as novel loci. Most QTL influenced fitness via life history and size traits, rather than QTL having direct effects on fitness. Comparison of phenotypes among environments found no evidence for genetic trade‐offs for phenology or growth traits, but genetic trade‐offs for fitness resulted because flowering time had opposite fitness effects in different environments. These changes in QTL effects and selective consequences may maintain genetic variation among populations.     

Crop model based QTL analysis across environments and QTL based estimation of time to floral induction and flowering in <Emphasis Type="Italic">Brassica oleracea</Emphasis>

Studying quantitative traits is complicated due to genotype by environment interactions. One strategy to overcome these difficulties is to combine quantitative trait loci (QTL) and ecophysiological models, e.g. by identifying QTLs for the response curves of adaptive traits to influential environmental factors. A B. oleracea DH-population segregating for time to flowering was cultivated at different temperature regimes. Composite interval mapping was carried out on the three parameters of a model describing time to flowering as a function of temperature, i.e. on the intercept and slope of the response of time to floral induction to temperature and on the duration from transition to flowering. The additive effects of QTLs detected for the parameters have been used to estimate time to floral induction and flowering in the B. oleracea DH-population. The combined QTL and crop model explained 66% of the phenotypic variation for time to floral induction and 56% of the phenotypic variation for time to flowering. Estimation of time to floral induction and flowering based on environment specific QTLs explained 61 and 41% of the phenotypic variation. Results suggest that flowering time can be predicted effectively by coupling QTL and crop models and that using crop modelling tools for QTL analysis increases the power of QTL detection.     

Identification of quantitative trait loci influencing aerial morphogenesis in the model legume <Emphasis Type="Italic">Medicago truncatula</Emphasis>

In many legume crops, especially in forage legumes, aerial morphogenesis defined as growth and development of plant organs, is an essential trait as it determines plant and seed biomass as well as forage quality (protein concentration, dry matter digestibility). Medicago truncatula is a model species for legume crops. A set of 29 accessions of M. truncatula was evaluated for aerial morphogenetic traits. A recombinant inbred lines (RILs) mapping population was used for analysing quantitative variation in aerial morphogenetic traits and QTL detection. Genes described to be involved in aerial morphogenetic traits in other species were mapped to analyse co-location between QTLs and genes. A large variation was found for flowering date, morphology and dynamics of branch elongation among the 29 accessions and within the RILs population. Flowering date was negatively correlated to main stem and branch length. QTLs were detected for all traits, and each QTL explained from 5.2 to 59.2% of the phenotypic variation. A QTL explaining a large part of genetic variation for flowering date and branch growth was found on chromosome 7. The other chromosomes were also involved in the variation detected in several traits. Mapping of candidate genes indicates a co-location between a homologue of Constans gene or a flowering locus T (FT) gene and the QTL of flowering date on chromosome 7. Other candidate genes for several QTLs are described. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Detection of QTLs for flowering date in three mapping populations of the model legume species Medicago truncatula

Adaptation to the environment and reproduction are dependent on the date of flowering in the season. The objectives of this paper were to evaluate the effect of photoperiod on flowering date of the model species for legume crops, Medicago truncatula and to describe genetic architecture of this trait in multiple mapping populations. The effect of photoperiod (12 and 18 h) was analysed on eight lines. Quantitative variation in three recombinant inbred lines (RILs) populations involving four parental lines was evaluated, and QTL detection was carried out. Flowering occurred earlier in long than in short photoperiods. Modelling the rate of progression to flowering with temperature and photoperiod gave high R(2), with line-specific parameters that indicated differential responses of the lines to both photoperiod and temperature. QTL detection showed a QTL on chromosome 7 that was common to all populations and seasons. Taking advantage of the multiple mapping populations, it was condensed into a single QTL with a support interval of only 0.9 cM. In a bioanalysis, six candidate genes were identified in this interval. This design also indicated other genomic regions that were involved in flowering date variation more specifically in one population or one season. The analysis on three different mapping populations detected more QTLs than on a single population, revealed more alleles and gave a more precise position of the QTLs that were common to several populations and/or seasons. Identification of candidate genes was a result of integration of QTL analysis and genomics in M. truncatula.     

Flowering time QTL in natural populations of Arabidopsis thaliana and implications for their adaptive value

The genetic basis of phenotypic traits is of great interest to evolutionary biologists, but their contribution to adaptation in nature is often unknown. To determine the genetic architecture of flowering time in ecologically relevant conditions, we used a recombinant inbred line population created from two locally adapted populations of Arabidopsis thaliana from Sweden and Italy. Using these RILs, we identified flowering time QTL in growth chambers that mimicked the natural temperature and photoperiod variation across the growing season in each native environment. We also compared the genomic locations of flowering time QTL to those of fitness (total fruit number) QTL from a previous three‐year field study. Ten total flowering time QTL were found, and in all cases, the Italy genotype caused early flowering regardless of the conditions. Two QTL were consistent across chamber environments, and these had the largest effects on flowering time. Five of the fitness QTL colocalized with flowering time QTL found in the Italy conditions, and in each case, the local genotype was favoured. In contrast, just two flowering time QTL found in the Sweden conditions colocalized with fitness QTL and in only one case was the local genotype favoured. This implies that flowering time may be more important for adaptation in Italy than Sweden. Two candidate genes (FLC and VIN3) underlying the major flowering time QTL found in the current study are implicated in local adaptation.     

Mapping QTLs for Plant Phenology and Production Traits Using Indica Rice (Oryza sativa L.) Lines Adapted to Rainfed Environment

Drought is a major abiotic stress limiting rice production and yield stability in rainfed ecosystems. Identifying quantitative trait loci (QTL) for rice yield and yield components under water limited environments will help to develop drought resilient cultivars using marker assisted breeding (MAB) strategy. A total of 232 recombinant inbred lines of IR62266/Norungan were used to map QTLs for plant phenology and production traits under rainfed condition in target population of environments. A total of 79 QTLs for plant phenology and production traits with phenotypic variation ranging from 4.4 to 72.8% were detected under non-stress and drought stress conditions across two locations. Consistent QTLs for phenology and production traits were detected across experiments and water regimes. The QTL region, RM204-RM197-RM217 on chromosome 6 was linked to days to 50% flowering and grain yield per plant under both rainfed and irrigated conditions. The same genomic region, RM585-RM204-RM197 was also linked to harvest index under rainfed condition with positive alleles from Norungan, a local landrace. QTLs for plant production and drought resistance traits co-located near RM585-RM204-RM197-RM217 region on chromosome 6 in several rice genotypes. Thus with further fine mapping, this region may be useful as a candidate QTL for MAB, map-based cloning of genes and functional genomics studies for rainfed rice improvement.     

Genetic and physical mapping of flowering time loci in canola (Brassica napus L.)

We identified quantitative trait loci (QTL) underlying variation for flowering time in a doubled haploid (DH) population of vernalisation—responsive canola (Brassica napus L.) cultivars Skipton and Ag-Spectrum and aligned them with physical map positions of predicted flowering genes from the Brassica rapa genome. Significant genetic variation in flowering time and response to vernalisation were observed among the DH lines from Skipton/Ag-Spectrum. A molecular linkage map was generated comprising 674 simple sequence repeat, sequence-related amplified polymorphism, sequence characterised amplified region, Diversity Array Technology, and candidate gene based markers loci. QTL analysis indicated that flowering time is a complex trait and is controlled by at least 20 loci, localised on ten different chromosomes. These loci each accounted for between 2.4 and 28.6 % of the total genotypic variation for first flowering and response to vernalisation. However, identification of consistent QTL was found to be dependant upon growing environments. We compared the locations of QTL with the physical positions of predicted flowering time genes located on the sequenced genome of B. rapa. Some QTL associated with flowering time on A02, A03, A07, and C06 may represent homologues of known flowering time genes in Arabidopsis; VERNALISATION INSENSITIVE 3, APETALA1, CAULIFLOWER, FLOWERING LOCUS C, FLOWERING LOCUS T, CURLY LEAF, SHORT VEGETATIVE PHASE, GA3 OXIDASE, and LEAFY. Identification of the chromosomal location and effect of the genes influencing flowering time may hasten the development of canola varieties having an optimal time for flowering in target environments such as for low rainfall areas, via marker-assisted selection.     

Adaptive divergence in flowering time among natural populations of Arabidopsis thaliana: Estimates of selection and QTL mapping

To identify the ecological and genetic mechanisms of local adaptation requires estimating selection on traits, identifying their genetic basis, and evaluating whether divergence in adaptive traits is due to conditional neutrality or genetic trade‐offs. To this end, we conducted field experiments for three years using recombinant inbred lines (RILs) derived from two ecotypes of Arabidopsis thaliana (Italy, Sweden), and at each parental site examined selection on flowering time and mapped quantitative trait loci (QTL). There was strong selection for early flowering in Italy, but weak selection in Sweden. Eleven distinct flowering time QTL were detected, and for each the Italian genotype caused earlier flowering. Twenty‐seven candidate genes were identified, two of which (FLC and VIN3) appear under major flowering time QTL in Italy. Seven of eight QTL in Italy with narrow credible intervals colocalized with previously reported fitness QTL, in comparison to three of four in Sweden. The results demonstrate that the magnitude of selection on flowering time differs strikingly between our study populations, that the genetic basis of flowering time variation is multigenic with some QTL of large effect, and suggest that divergence in flowering time between ecotypes is due mainly to conditional neutrality.     

Novel loci control variation in reproductive timing in Arabidopsis thaliana in natural environments

Molecular biologists are rapidly characterizing the genetic basis of flowering in model species such as Arabidopsis thaliana. However, it is not clear how the developmental pathways identified in controlled environments contribute to variation in reproductive timing in natural ecological settings. Here we report the first study of quantitative trait loci (QTL) for date of bolting (the transition from vegetative to reproductive growth) in A. thaliana in natural seasonal field environments and compare the results with those obtained under typical growth-chamber conditions. Two QTL specific to long days in the chamber were expressed only in spring-germinating cohorts in the field, and two loci specific to short days in the chamber were expressed only in fall-germinating cohorts, suggesting differential involvement of the photoperiod pathway in different seasonal environments. However, several other photoperiod-specific QTL with large effects in controlled conditions were undetectable in natural environments, indicating that expression of allelic variation at these loci was overridden by environmental factors specific to the field. Moreover, a substantial number of QTL with major effects on bolting date in one or more field environments were undetectable under controlled environment conditions. These novel loci suggest the involvement of additional genes in the transition to flowering under ecologically relevant conditions.     

Assortative mating by flowering time and its effect on correlated traits in variable environments

Reproductive timing is a key life‐history trait that impacts the pool of available mates, the environment experienced during flowering, and the expression of other traits through genetic covariation. Selection on phenology, and its consequences on other life‐history traits, has considerable implications in the context of ongoing climate change and shifting growing seasons. To test this, we grew field‐collected seed from the wildflower Mimulus guttatus in a greenhouse to assess the standing genetic variation for flowering time and covariation with other traits. We then created full‐sib families through phenological assortative mating and grew offspring in three photoperiod treatments representing seasonal variation in daylength. We find substantial quantitative genetic variation for the onset of flowering time, which covaried with vegetative traits. The assortatively‐mated offspring varied in their critical photoperiod by over two hours, so that families differed in their probability of flowering across treatments Allocation to flowering and vegetative growth changed across the daylength treatments, with consistent direction and magnitude of covariation among flowering time and other traits. Our results suggest that future studies of flowering time evolution should consider the joint evolution of correlated traits and shifting seasonal selection to understand how environmental variation influences life histories.     

Multi-environment QTL analyses for drought-related traits in a recombinant inbred population of chickpea (Cicer arientinum L.)

A recombinant inbred line (RIL) population, comprising 181 lines derived from ILC588 × ILC3279, was evaluated in 10 environments across three locations with different moisture gradients. A drought resistance score (DRS) and three phenology traits—plant height (PLHT), days to flowering (DFLR), and days to maturity (MAT)—were recorded along with seven yield-related traits—grain yield (GY), biological yield (BY), harvest index (HI), the number of pods/3 plants (Pod), percentage of empty pods (%Epod), 100 seed weight (100 sw), and seed number/3 plants (SN). Two RILs (152, 162) showed the best GYs and DRSs under stressed and non-stressed environments. The quantitative trait loci (QTLs) analyses detected 93 significant QTLs (LOD ≥ 2.0) across the genome × environment interactions. The highest phenotypic variation (>24 %) was explained by the QTL_DFLR in Terbol-11. Four common possible pleiotropic QTLs on LG3 and LG4 were identified as associated with DFLR, DRS, GY, MAT, HI, SN, and Pod. No significant epistatic interactions were found between these QTLs and the other markers. However, the QTL for DRS was detected as a conserved QTL in three late planting environments. The markers H6C-07 (on LG3) and H5G01 (on LG4) were associated with QTLs for many traits in all environments studied except two. The allele ‘A’ of marker H6C07 (from the tolerant parent ILC588) explained 80 % of the yield increase under late planting and 29.8 % of that under dry environments. Concentrating on LG3 and LG4 in molecular breeding programs for drought could speed up improvement for these traits.     

应用中国和欧洲油菜建立的双二倍体群体对3个重要农艺性状的QTL定位以及与环境的互作分析

以中国的高油分自交系“高油”和欧洲高含油量品种“Sollux”的F1产生的282个株系组成的双二倍体(DH)群体为材料,在125个SSR标记座位构建的连锁图谱基础上,根据在中国和欧洲四个不同环境下的表型鉴定结果,采用混合线性模型基础上的QTL分析软件,对油菜3个重要农艺性状:株高,开花期和成熟期进行了数量性状基因座位(QTL)的联合定位分析,估测了这些QTL的加性、上位性以及与环境的互作效应。结果表明各性状均受多个加性、加加上位以及与环境互作的QTL控制。株高受多个QTL影响(12个位点具有加性或兼有环境互作效应,5个位点具有互作效应),以加性效应为主,加性效应总和可解释定位群体表型变异的75%左右,并多兼有上位性效应。12个主效QTL中,9个是“高油”等位基因相对“Sollux”有降低株高的作用,大多数加性×环境互作QTL的有效等位基因具有环境选择特异性。7个ae基因座位中,5个“高油”等位基因在杭州种植环境下,除一例外所有在德国环境下的互作基因座中,“Sollux”等位基因起着增加株高的作用,加加上位性主效总和为加性主效总和的三分之一。7个控制花期和8个控制成熟期的主效QTL中,分别有6个和5个是来自“高油”的等位基因相对“Sollux”具有提前开花和成熟的效应,这些QTL的效应总和占到性状表型变异的60%左右。5个位于第2和第12连锁群中的2个大效应QTL可能和已多次报导的VFN1和VFN3基因相近或相同。开花期和成熟期两性状均检测到显著的ae互作效应,双亲等位基因的效应在各环境下呈离散分布。位于14和19连锁群上的两个主效株高QTL同时也是控制开花期和油分含量的基因位点,因而利用这两个位点进行标记辅助筛选时要考虑到对油分含量的影响。控制成熟期的8个主效QTL中有3个同时也是控制开花期的基因座位,证实了开花期和成熟期高度正相关的遗传基础,两个生育性状均表现有较弱的QTL间加加上位互作,但以主效QTL的作用为主。     

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.     

Life-history QTLS and natural selection on flowering time in Boechera stricta, a perennial relative of Arabidopsis

Plants must precisely time flowering to capitalize on favorable conditions. Although we know a great deal about the genetic basis of flowering phenology in model species under controlled conditions, the genetic architecture of this ecologically important trait is poorly understood in nonmodel organisms. Here, we evaluated the transition from vegetative growth to flowering in Boechera stricta, a perennial relative of Arabidopsis thaliana. We examined flowering time QTLs using 7920 recombinant inbred individuals, across seven laboratory and field environments differing in vernalization, temperature, and photoperiod. Genetic and environmental factors strongly influenced the transition to reproduction. We found directional selection for earlier flowering in the field. In the growth chamber experiment, longer winters accelerated flowering, whereas elevated ambient temperatures delayed flowering. Our analyses identified one large effect QTL (nFT), which influenced flowering time in the laboratory and the probability of flowering in the field. In Montana, homozygotes for the native allele at nFT showed a selective advantage of 6.6%. Nevertheless, we found relatively low correlations between flowering times in the field and the growth chambers. Additionally, we detected flowering-related QTLs in the field that were absent across the full range of laboratory conditions, thus emphasizing the need to conduct experiments in natural environments.     

Genetic mapping of QTLs for sugar-related traits in a RIL population of Sorghum bicolor L. Moench

The productivity of sorghum is mainly determined by quantitative traits such as grain yield and stem sugar-related characteristics. Substantial crop improvement has been achieved by breeding in the last decades. Today, genetic mapping and characterization of quantitative trait loci (QTLs) is considered a valuable tool for trait enhancement. We have investigated QTL associated with the sugar components (Brix, glucose, sucrose, and total sugar content) and sugar-related agronomic traits (flowering date, plant height, stem diameter, tiller number per plant, fresh panicle weight, and estimated juice weight) in four different environments (two locations) using a population of 188 recombinant inbred lines (RILs) from a cross between grain (M71) and sweet sorghum (SS79). A genetic map with 157 AFLP, SSR, and EST-SSR markers was constructed, and several QTLs were detected using composite interval mapping (CIM). Further, additive × additive interaction and QTL × environmental interaction were estimated. CIM identified more than five additive QTLs in most traits explaining a range of 6.0–26.1% of the phenotypic variation. A total of 24 digenic epistatic locus pairs were identified in seven traits, supporting the hypothesis that QTL analysis without considering epistasis can result in biased estimates. QTLs showing multiple effects were identified, where the major QTL on SBI-06 was significantly associated with most of the traits, i.e., flowering date, plant height, Brix, sucrose, and sugar content. Four out of ten traits studied showed a significant QTL × environmental interaction. Our results are an important step toward marker-assisted selection for sugar-related traits and biofuel yield in sorghum.     

Mapping quantitative trait loci associated with southern leaf blight resistance in maize (Zea mays L.)

Southern leaf blight (SLB) caused by the fungus Cochliobolus heterostrophus (Drechs.) Drechs. is a major foliar disease of maize worldwide. Our objectives were to identify quantitative trait loci (QTL) for resistance to SLB and flowering traits in recombinant inbred line (RIL) population derived from the cross of inbred lines LM5 (resistant) and CM140 (susceptible). A set of 207 RILs were phenotyped for resistance to SLB at three time intervals for two consecutive years. Four putative QTL for SLB resistance were detected on chromosomes 3, 8 and 9 that accounted for 54% of the total phenotypic variation. Days to silking and anthesis–silking interval (ASI) QTL were located on chromosomes 6, 7 and 9. A comparison of the obtained results with the published SLB resistance QTL studies suggested that the detected bins 9.03/02 and 8.03/8.02 are the hot spots for SLB resistance whereas novel QTL were identified in bins 3.08 and 8.01/8.04. The linked markers are being utilized for marker‐assisted mobilization of QTL conferring resistance to SLB in elite maize backgrounds. Fine mapping of identified QTL will facilitate identification of candidate genes underlying SLB resistance.     

Paths to selection on life history loci in different natural environments across the native range of Arabidopsis thaliana

Selection on quantitative trait loci (QTL) may vary among natural environments due to differences in the genetic architecture of traits, environment‐specific allelic effects or changes in the direction and magnitude of selection on specific traits. To dissect the environmental differences in selection on life history QTL across climatic regions, we grew a panel of interconnected recombinant inbred lines (RILs) of Arabidopsis thaliana in four field sites across its native European range. For each environment, we mapped QTL for growth, reproductive timing and development. Several QTL were pleiotropic across environments, three colocalizing with known functional polymorphisms in flowering time genes (CRY2, FRI and MAF2‐5), but major QTL differed across field sites, showing conditional neutrality. We used structural equation models to trace selection paths from QTL to lifetime fitness in each environment. Only three QTL directly affected fruit number, measuring fitness. Most QTL had an indirect effect on fitness through their effect on bolting time or leaf length. Influence of life history traits on fitness differed dramatically across sites, resulting in different patterns of selection on reproductive timing and underlying QTL. In two oceanic field sites with high prereproductive mortality, QTL alleles contributing to early reproduction resulted in greater fruit production, conferring selective advantage, whereas alleles contributing to later reproduction resulted in larger size and higher fitness in a continental site. This demonstrates how environmental variation leads to change in both QTL effect sizes and direction of selection on traits, justifying the persistence of allelic polymorphism at life history QTL across the species range.     

Identification of quantitative trait loci across recombinant inbred lines and testcross populations for traits of agronomic importance in rice

This study was conducted to determine whether quantitative trait loci (QTL) controlling traits of agronomic importance detected in recombinant inbred lines (RILs) are also expressed in testcross (TC) hybrids of rice. A genetic map was constructed using an RIL population derived from a cross between B5 and Minghui 63, a parent of the most widely grown hybrid rice cultivar in China. Four TC hybrid populations were produced by crossing the RILs with three maintaining lines for the widely used cytoplasmic male-sterile (CMS) lines and the genic male-sterile line Peiai64s. The mean values of the RILs for the seven traits investigated were significantly correlated to those of the F1 hybrids in the four TC populations. Twenty-seven main-effect QTL were identified in the RILs. Of these, the QTL that had the strongest effect on each of the seven traits in the RILs was detected in two or more of the TC populations, and six other QTL were detected in one TC population. Epistatic analysis revealed that the effect of epistatic QTL was relatively weak and cross combination specific. Searching publicly available QTL data in rice revealed the positional convergence of the QTL with the strongest effect in a wide range of populations and under different environments. Since the main-effect QTL is expressed across different testers, and in different genetic backgrounds and environments, it is a valuable target for gene manipulation and for further application in rice breeding. When a restorer line that expresses main-effect QTL is bred, it could be used in a number of cross combinations.