Genetic loci modulating fitness and life span in Caenorhabditis elegans: categorical trait interval mapping in CL2a x Bergerac-BO recombinant-inbred worms

Quantitative trait loci (QTL) can implicate an unbiased sampling of genes underlying a complex, polygenic phenotype. QTL affecting longevity in Caenorhabditis elegans were mapped using a CL2a x Bergerac-BO recombinant-inbred population. Genotypes were compared at 30 transposon-specific markers for two paired sample sets totaling 171 young controls and 172 longevity-selected worms (the last-surviving 1%) from a synchronously aged population. A third sample set, totaling 161 worms from an independent culture, was analyzed for confirmation of loci. At least six highly significant QTL affecting life span were detected both by single-marker (chi(2)) analysis and by two interval-mapping procedures--one intended for nonparametric traits and another developed specifically for mapping of categorical traits. These life-span QTL were located on chromosomes I (near the hP4 locus), III (near stP127), IV (near stP44), V (a cluster of three peaks, near stP192, stP23, and stP6), and X (two distinct peaks, near stP129 and stP2). Epistatic effects on longevity were also analyzed by Fisher's exact test, which indicated a significant life-span interaction between markers on chromosomes V (stP128) and III (stP127). Several further interactions were significant in the initial unselected population; two of these, between distal loci on chromosome V, were completely eliminated in the long-lived subset. Allelic longevity effects for two QTL, on chromosomes IV and V, were confirmed in backcrossed congenic lines and were highly significant in two very different environments-growth on solid agar medium and in liquid suspension culture.     

Genetic mapping of quantitative trait loci governing longevity of Caenorhabditis elegans in recombinant-inbred progeny of a Bergerac-BO x RC301 interstrain cross

Recombinant-inbred populations, generated from a cross between Caenorhabditis elegans strains Bergerac-BO and RC301, were used to identify quantitative trait loci (QTL) affecting nematode longevity. Genotypes of young controls and longevity-selected worms (the last-surviving 1% from a synchronously aged population) were assessed at dimorphic transposon-specific markers by multiplex polymerase chain reaction. The power of genetic mapping was enhanced, in a novel experimental design, through map expansion by accrual of recombinations over several generations, internally controlled longevity selection from a genetically heterogeneous, homozygous population, and selective genotyping of extremely long-lived worms. Analysis of individual markers indicated seven life-span QTL, situated near markers on chromosomes I (tcbn2), III (stP127), IV (stP13), V (stP6, stP23, and stP128), and X (stP41). These loci were corroborated, and mapped with increased precision, by nonparametric interval mapping-which supported all loci implicated by single-marker analysis. In addition, a life-span QTL on chromosome II (stP100-stP196), was significant only by interval mapping. Congenic lines were constructed for the longevity QTL on chromosomes III and X, by backcrossing the Bergerac-BO QTL allele into an RC301 background with selection for flanking markers. Survival data for these lines demonstrated consistent and significant effects of each QTL on life span.     

Genetic variation underlying pod size and color traits of common bean depends on quantitative trait loci with epistatic effects

Common bean is an important vegetable legume in many regions of the world. Size and color of fresh pods are the key factors for deciding the commercial acceptance of bean as a fresh vegetable. The genetic basis of important horticultural traits of common bean is still poorly understood, which hinders DNA marker-assisted breeding in this crop. Here we report the identification of single-locus and epistatic quantitative trait loci (QTLs), as well as their environment interaction effects for six pod traits, namely width, thickness, length, size index, beak length and color, using an Andean intra-gene pool recombinant inbred line population from a cross between a cultivated common bean and an exotic nuña bean. The QTL analyses performed detected a total of 23 QTLs (single-locus QTLs and epistatic QTLs): five with only individual additive effects and six with only epistatic effects, while the remaining twelve showed both effects. These QTLs were distributed across linkage groups (LGs) 1, 2, 4, 6, 7, 8, 9, 10 and 11; particularly noteworthy are the QTLs for pod size co-located on LGs 1 and 4, indicative of tight linkage or genes with pleiotropic effects governing these traits. Overall, the results obtained showed that additive and epistatic effects are the major genetic basis of pod size and color traits. The mapping of QTLs including epistatic loci for the six pod traits evaluated provides support for implementing marker-assisted selection toward genetic improvement of common bean.     

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。     

Validation of quantitative trait loci for Ascochyta blight resistance in pea (Pisum sativum L.), using populations from two crosses

Resistance to Ascochyta blight of pea was genetically characterized by mapping quantitative trait loci (QTLs) using two crosses, 3147-A26 (A26, partially resistant) × cultivar Rovar (susceptible) and 3148-A88 (A88, partially resistant) × Rovar, with the aim of developing an increased understanding of the genetics of resistance and of identifying linked molecular markers that may be used to develop resistant germplasm. Molecular linkage maps for both crosses were aligned so that the results of QTL mapping could be compared. Ascochyta blight disease severity in response to natural epidemics was measured in field trials conducted in Western Australia and New Zealand. Eleven putative QTLs for Ascochyta blight resistance were identified from the A26 × Rovar population and 14 putative QTLs from the A88 × Rovar population. Six QTLs were associated with the same genomic regions in both populations. These QTLs reside on linkage groups II, III, IV, V, and VII (two QTLs). The severity of Ascochyta blight disease symptoms on pea increases during field epidemics as plants mature; therefore, QTLs for plant reproductive maturity were mapped. Six QTLs were detected for plant maturity in the A26 × Rovar population, while five plant maturity QTLs were mapped in the A88 × Rovar population. QTLs for plant maturity coincide with Ascochyta blight resistance QTLs in four genomic regions, on linkage groups II (two regions), III, and V. The plant maturity and Ascochyta blight resistance QTLs on III were linked in repulsion phase. Therefore, the coincidence of these QTLs may be explained by linkage of distinct loci for the two traits. The QTLs on linkage groups II and V were linked in coupling phase; therefore, linked QTLs for resistance and maturity may be present in these regions, or the Ascochyta blight resistance QTLs detected in these regions are the result of pleiotropic effects of plant-maturity genetic loci.     

Gene actions of QTLs affecting several agronomic traits resolved in a recombinant inbred rice population and two backcross populations

To understand the types of gene action controlling seven quantitative traits in rice, we carried out quantitative trait locus (QTL) mapping in order to distinguish between the main-effect QTLs (M-QTLs) and digenic epistatic QTLs (E-QTLs) responsible for the trait performance of 254 recombinant inbred lines (RILs) from rice varieties Lemont/Teqing and two backcross hybrid (BCF₁) populations derived from these RILs. We identified 44 M-QTL and 95 E-QTL pairs in the RI and BCF₁ populations as having significant effects on the mean values and mid-parental heterosis of heading date, plant height, flag leaf length, flag leaf width, panicle length, spikelet number and spikelet fertility. The E-QTLs detected collectively explained a larger portion of the total phenotypic variation than the M-QTLs in both the RI and BCF₁ populations. In both BCF₁ populations, over-dominant (or under-dominant) loci were more important than additive and complete or partially dominant loci for M-QTLs and E-QTL pairs, thereby supporting prior findings that overdominance resulting from epistatic loci are the primary genetic basis of inbreeding depression and heterosis in rice.     

水稻加工品质数量性状基因座 (QTLs)分子定位研究

检测了Lemont/特青RI群体212个株系的糙米率（BR）,精米率（MR）和整精米率（HR）等3项加工品质性状,利用RFLP连锁图和线性模型的复合区间作图方法（QTLMapperV1.0)进行QTL定位研究。群体呈边境分布,双向超亲现象明显,HR较BR,MR变异范围更大并偏向低值方向;分别检测到1个MR,4个HR主效QTL,其中QHr6和QHr7等2个基因座具有较大遗传效应;分别检测到12对影响BR、5对影响MR,16对影响HR的上位性基因座,上位性效应的影响大于主效QTLs,不同性状或同一性状上位性效应通过共同的区间形成复杂的互相联系。     

The relationship between loci for mating system and fitness-related traits in Mimulus (Scrophulariaceae): a test for deleterious pleiotropy of QTLs with large effects.

Loci with large phenotypic effects are generally not thought to be important in the evolution of quantitative traits because of their deleterious pleiotropic effects, yet empirical studies of such pleiotropic effects are lacking. Here I use molecular markers to test the extent of deleterious pleiotropy of quantitative trait loci (QTLs) that have large effects on mating system differences between the wild plants Mimulus guttatus and M. platycalyx (Scrophulariaceae). Six fitness-related traits, namely germination rate (GR), number of nodes (NN), number of flowers (NF), plant height (HT), above-ground biomass (WT), and flowering time (FT) were examined in a growth chamber for a backcross population between M. guttatus and M. platycalyx (with M. platycalyx as recurrent parent). Interval mapping based upon a linkage map consisting of isozyme and random amplified polymorphic DNA (RAPD) markers detected no QTL for fitness-related traits near the mating system QTLs. Single-marker analysis based upon 13 markers flanking the mating system QTLs detected three significant marker-fitness trait associations, and these associations indicate beneficial effects of mating system loci. This suggests that QTLs with large effects on mating system traits do not have significant deleterious pleiotropic effects, and that they could be important factors in adaptive evolution of Mimulus.     

Identification of main effects, epistatic effects and their environmental interactions of QTLs for yield traits in rice

Quantitative trait loci (QTLs) controlling yield and yield components were identified by using a doubled haploid (DH) population of 120 lines from a sub-specific cross between ‘Samgang’ (Indica) and ‘Nagdong’ (Japonica). Main effects, epistatic effects, their environment interactions of QTLs were analyzed via mixed linear model approach across different environments. A total of 17 putative QTLs were identified on 8 chromosomes and five QTLs were detected over two years. 7 QTLs of main effects and 23 epistatic interactions were observed for five traits. Epistatic interactions played an important role in controlling the expression of yield related traits. The epistatic effects explained higher percentages of phenotype variation for panicles per plant, seed set percentage and yield. Significant QTL×environment (QE) interactions effects were identified for all traits, including 5 main effect QTLs. However, the present study failed to identify the significant interactions between epistatic loci containing main effect QTLs and the environment. The information provided in the present study could be used in the marker-assisted selection to enhance selection efficiency and to improve yield in rice.     

An application of Bayesian QTL mapping to early development in double haploid lines of rainbow trout including environmental effects

A Bayesian model and variable dimensional parameter estimation based on Markov chain Monte Carlo was applied to map quantitative trait loci (QTLs) in a doubled haploid mapping population of rainbow trout. To increase power, the analysis was performed using the multiple-QTL model, which simultaneously accounted for all the environmental and genetic main effects that influence the expression of early development life history traits. By doing so we obtained the posterior estimated effects for the environmental factors as well as the number, positions, and the effects for the QTLs. The analyses revealed QTLs for time at hatching, embryonic length and weight at swim-up stage. The posterior expectation of the number of QTLs in different linkage groups shows that at least four QTLs are needed to explain the observed differences in early development between the clonal lines. The Bayesian method effectively combined all the information available to accurately position these QTLs in the rainbow trout genome.     

Mapping quantitative trait loci with epistatic effects

Epistatic variance can be an important source of variation for complex traits. However, detecting epistatic effects is difficult primarily due to insufficient sample sizes and lack of robust statistical methods. In this paper, we develop a Bayesian method to map multiple quantitative trait loci (QTLs) with epistatic effects. The method can map QTLs in complicated mating designs derived from the cross of two inbred lines. In addition to mapping QTLs for quantitative traits, the proposed method can even map genes underlying binary traits such as disease susceptibility using the threshold model. The parameters of interest are various QTL effects, including additive, dominance and epistatic effects of QTLs, the locations of identified QTLs and even the number of QTLs. When the number of QTLs is treated as an unknown parameter, the dimension of the model becomes a variable. This requires the reversible jump Markov chain Monte Carlo algorithm. The utility of the proposed method is demonstrated through analysis of simulation data.     

QTL mapping for yield and yield contributing traits in two mapping populations of bread wheat

In bread wheat, single-locus and two-locus QTL analyses were conducted for seven yield and yield contributing traits using two different mapping populations (P I and P II). Single-locus QTL analyses involved composite interval mapping (CIM) for individual traits and multiple-trait composite interval mapping (MCIM) for correlated yield traits to detect the pleiotropic QTLs. Two-locus analyses were conducted to detect main effect QTLs (M-QTLs), epistatic QTLs (E-QTLs) and QTL × environment interactions (QE and QQE). Only a solitary QTL for spikelets per spike was common between the above two populations. HomoeoQTLs were also detected, suggesting the presence of triplicate QTLs in bread wheat. Relatively fewer QTLs were detected in P I than in P II. This may be partly due to low density of marker loci on P I framework map (173) than in P II (521) and partly due to more divergent parents used for developing P II. Six QTLs were important which were pleiotropic/coincident involving more than one trait and were also consistent over environments. These QTLs could be utilized efficiently for marker assisted selection (MAS).     

玉米开花期相关性状的QTL分析

利用玉米强优势组合(Mo17×黄早四)自交衍生的191个F_2单株构建了由SSR和AFLP标记组成的分子连锁图谱,用F2进一步自交产生的184个F_(2:3)家系调查散粉期、吐丝期和开花-吐丝间隔期(ASI)的表型值,采用基于混合线性模型的复合区间作图法和相应的作图软件QTLmapper/V2.0,在两个生长环境下定位了与散粉期、吐丝期和ASI相关的QTL数目分别为13、7和5个,检测到3对控制散粉期、17对控制吐丝期和5对控制ASI的上位性效应位点;同时发现了与环境存在显著互作的3个散粉期、3个吐丝期和2个ASI单位点标记区域以及1对散粉期、3对吐丝期和2对ASI上位性效应区域.对玉米散粉期、吐丝期和ASI遗传基础中遗传因素相对作用大小分析表明,加性效应、部分显性效应和上位性效应是玉米开花期相关性状的重要遗传基础.     

Genetic analysis of single-locus and epistatic QTLs for seed traits in an adapted × nuña RIL population of common bean (Phaseolus vulgaris L.)

Key message

The QTLs analyses here reported demonstrate the significant role of both individual additive and epistatic effects in the genetic control of seed quality traits in the Andean common bean.

Abstract

Common bean shows considerable variability in seed size and coat color, which are important agronomic traits determining farmer and consumer acceptability. Therefore, strategies must be devised to improve the genetic base of cultivated germplasm with new alleles that would contribute positively to breeding programs. For that purpose, a population of 185 recombinant inbred lines derived from an Andean intra-gene pool cross, involving an adapted common bean (PMB0225 parent) and an exotic nuña bean (PHA1037 parent), was evaluated under six different—short and long-day—environmental conditions for seed dimension, weight, color, and brightness traits, as well as the number of seed per pod. A multi-environment Quantitative Trait Loci (QTL) analysis was carried out and 59 QTLs were mapped on all linkage groups, 18 of which had only individual additive effects, while 27 showed only epistatic effects and 14 had both individual additive and epistatic effects. Multivariate models that included significant QTL explained from 8 to 68  % and 2 to 15 % of the additive and epistatic effects, respectively. Most of these QTLs were consistent over environment, though interactions between QTLs and environments were also detected. Despite this, QTLs with differential effect on long-day and short-day environments were not found. QTLs identified were positioned in cluster, suggesting that either pleiotropic QTLs control several traits or tightly linked QTLs for different traits map together in the same genomic regions. Overall, our results show that digenic epistatic interactions clearly play an important role in the genetic control of seed quality traits in the Andean common bean.     

Genetic variation in pleiotropy: differential epistasis as a source of variation in the allometric relationship between long bone lengths and body weight

Pleiotropy is an aspect of genetic architecture underlying the phenotypic covariance structure. The presence of genetic variation in pleiotropy is necessary for natural selection to shape patterns of covariation between traits. We examined the contribution of differential epistasis to variation in the intertrait relationship and the nature of this variation. Genetic variation in pleiotropy was revealed by mapping quantitative trait loci (QTLs) affecting the allometry of mouse limb and tail length relative to body weight in the mouse-inbred strain LG/J by SM/J intercross. These relationship QTLs (rQTLs) modify relationships between the traits affected by a common pleiotropic locus. We detected 11 rQTLs, mostly affecting allometry of multiple bones. We further identified epistatic interactions responsible for the observed allometric variation. Forty loci that interact epistatically with the detected rQTLs were identified. We demonstrate how these epistatic interactions differentially affect the body size variance and the covariance of traits with body size. We conclude that epistasis, by differentially affecting both the canalization and mean values of the traits of a pleiotropic domain, causes variation in the covariance structure. Variation in pleiotropy maintains evolvability of the genetic architecture, in particular the evolvability of its modular organization.     

水稻株高上位性效应和ＱＥ互作效应的ＱＴＬ遗传研究

利用基因混合模型的ＱＴＬ定位方法研究了由籼稻品种ＩＲ６４和粳稻品种Ａzucena杂交衍生的ＤＨ群体在４个环境中的ＱＴＬ上位性效应和环境互作效应,结果表明,上位性是数量性状的重要遗传基础,并揭示了上位性的几个重要特点,所有的ＱＴＬ都参与了上位性效应的形成,６４％的ＱＴＬ还具有本身的加性效应,因此传统方法对ＱＴＬ加性效应的估算会由于上位性的影响而有偏,其他３６％的ＱＴＬ没有本身的加性效应,却参与了４８％的上位性互作用,这些位点可能通过诱发和修饰其他位点而起作用,上位性的特点还包括,经常发现了一个ＱＴＬ与多个ＱＴＬ发生互作;大效应的ＱＴＬ也参与上位性互作;上位性互作受环境影响,ＱＴＬ与环境的互效应比ＱＴＬ的主效应更多地被检测到,表明数量性状基因的表达易受环境影响。     

The extent and genetic basis of phenotypic divergence in life history traits in Mimulus guttatus

Differential natural selection acting on populations in contrasting environments often results in adaptive divergence in multivariate phenotypes. Multivariate trait divergence across populations could be caused by selection on pleiotropic alleles or through many independent loci with trait‐specific effects. Here, we assess patterns of association between a suite of traits contributing to life history divergence in the common monkey flower, Mimulus guttatus, and examine the genetic architecture underlying these correlations. A common garden survey of 74 populations representing annual and perennial strategies from across the native range revealed strong correlations between vegetative and reproductive traits. To determine whether these multitrait patterns arise from pleiotropic or independent loci, we mapped QTLs using an approach combining high‐throughput sequencing with bulk segregant analysis on a cross between populations with divergent life histories. We find extensive pleiotropy for QTLs related to flowering time and stolon production, a key feature of the perennial strategy. Candidate genes related to axillary meristem development colocalize with the QTLs in a manner consistent with either pleiotropic or independent QTL effects. Further, these results are analogous to previous work showing pleiotropy‐mediated genetic correlations within a single population of M. guttatus experiencing heterogeneous selection. Our findings of strong multivariate trait associations and pleiotropic QTLs suggest that patterns of genetic variation may determine the trajectory of adaptive divergence.     

Genetic analysis of hemopoietic cell cycling in mice suggests its involvement in organismal life span.

Normal somatic cells undergo replicative senescence in vitro but the significance of this process in organismic aging remains controversial. We have shown previously that hemopoietic stem cells of common inbred strains of mice vary widely in cycling activity and that this parameter is inversely correlated with strain-dependent mean life span. To assess whether cell cycling and life span are causally related, we searched for quantitative trait loci (QTLs) that contributed to variation of these traits in BXH and BXD recombinant inbred mice. Two QTLs, mapping to exactly the same intervals on chromosomes 7 and 11, were identified that were associated with variation of both cell cycling and life span. The locus on chromosome 11 mapped to the cytokine cluster, a segment that shows synteny with human chromosome 5q, in which deletions are strongly associated with myelodysplastic syndrome. These data indicate that steady-state cell turn-over, here measured in hemopoietic progenitor cells, may have a significant effect on the mean life span of mammals.     

Dynamic QTL and epistasis analysis on seedling root traits in upland cotton

Roots are involved in acquisition of water and nutrients, as well as in providing structural support to plant. The root system provides a dynamic model for developmental analysis. Here, we investigated quantitative trait loci (QTL), dynamic conditional QTL and epistatic interactions for seedling root traits using an upland cotton F₂ population and a constructed genetic map. Totally, 37 QTLs for root traits, 35 dynamic conditional QTLs based on the net increased amount of root traits (root tips, forks, length, surface area and volume) (i) after transplanting 10 days compared to 5 days, and (ii) after transplanting 15 days to 10 days were detected. Obvious dynamic characteristic of QTL and dynamic conditional QTL existed at different developmental stages of root because QTL and dynamic conditional QTL had not been detected simultaneously. We further confirmed that additive and dominance effects of QTL qRSA-chr1-1 in interval time 5 to 10 DAT (days after transplant) offset the effects in 10 to 15 DAT. Lots of two-locus interactions for root traits were identified unconditionally or dynamically, and a few epistatic interactions were only detected simultaneously in interval time of 5–10 DAT and 10–15 DAT, suggesting different interactive genetic mechanisms on root development at different stages. Dynamic conditional QTL and epistasis effects provide new attempts to understand the dynamics of roots and provide clues for root architecture selection in upland cotton.     

QTL mapping of root traits in a doubled haploid population from a cross between upland and lowland japonica rice in three environments

To genetically dissect drought resistance associated with japonica upland rice, we evaluated a doubled haploid (DH) population from a cross between two japonica cultivars for seven root traits under three different growing conditions (upland, lowland and upland in PVC pipe). The traits included basal root thickness (BRT), total root number (RN), maximum root length (MRL), root fresh weight (RFW), root dry weight (RDW), ratio of root fresh weight to shoot fresh weight (RFW/SFW) and ratio of root dry weight to shoot dry weight (RDW/SDW). The BRT was significantly correlated with the index of drought resistance, which was defined as the ratio of yield under the stress of the upland condition to that under the normal lowland condition. A complete genetic linkage map with 165 molecular markers covering 1,535 cM was constructed. Seven additive quantitative trait loci (QTLs) and 15 pairs of epistatic loci for BRT and RN were identified under upland and lowland conditions, and 12 additive QTLs and 17 pairs of epistatic QTLs for BRT, RN, MRL, RFW, RFW/SFW and RDW/SDW were identified under the PVC pipe condition. Four additive QTLs and one pair of epistatic QTLs controlling IDR were also found. These QTLs individually explained up to 25.6% of the phenotypic variance. QTL × environment (Q × E) interactions were detected for all root traits, and the contributions of these interactions ranged from 1.1% to 19.9%. Five co-localized QTLs controlling RFW and RDW, RFW/SFW, RDW/SDW and IDR, BRT and RN, RN, MRL and IDR were found. Four types of QTLs governing BRT and RN were classified by their detection in the upland and lowland conditions. Some common QTLs for root traits across different backgrounds were also revealed. These co-localized QTLs and common QTLs will facilitate marker-assisted selection for root traits in rice breeding programs.