Genetic and molecular dissection of quantitative traits in rice

Recent progress in the generation of a molecular genetic map and markers for rice has made possible a new phase of mapping individual genes associated with complex traits. This type of analysis is often referred to as quantitative trait locus (QTL) analysis. Increasing numbers of QTL analyses are providing enormous amounts of information about QTLs, such as the numbers of loci involved, their chromosomal locations and gene effects. Clarification of genetic bases of complex traits has a big impact not only on fundamental research on rice plant development, but it also has practical benefits for rice breeding. In this review, we summarize recent progress of QTL analysis of several complex traits in rice. A strategy for positional cloning of genes at QTLs is also discussed.     

Construction of Chromosome Segment Substitution Lines in Peanut (Arachis hypogaea L.) Using a Wild Synthetic and QTL Mapping for Plant Morphology

Chromosome segment substitution lines (CSSLs) are powerful QTL mapping populations that have been used to elucidate the molecular basis of interesting traits of wild species. Cultivated peanut is an allotetraploid with limited genetic diversity. Capturing the genetic diversity from peanut wild relatives is an important objective in many peanut breeding programs. In this study, we used a marker-assisted backcrossing strategy to produce a population of 122 CSSLs from the cross between the wild synthetic allotetraploid (A. ipaënsis×A. duranensis)^4x and the cultivated Fleur11 variety. The 122 CSSLs offered a broad coverage of the peanut genome, with target wild chromosome segments averaging 39.2 cM in length. As a demonstration of the utility of these lines, four traits were evaluated in a subset of 80 CSSLs. A total of 28 lines showed significant differences from Fleur11. The line×trait significant associations were assigned to 42 QTLs: 14 for plant growth habit, 15 for height of the main stem, 12 for plant spread and one for flower color. Among the 42 QTLs, 37 were assigned to genomic regions and three QTL positions were considered putative. One important finding arising from this QTL analysis is that peanut growth habit is a complex trait that is governed by several QTLs with different effects. The CSSL population developed in this study has proved efficient for deciphering the molecular basis of trait variations and will be useful to the peanut scientific community for future QTL mapping studies.     

Explaining the heritability of an ecologically significant trait in terms of individual quantitative trait loci

Most natural populations display substantial genetic variation in behaviour, morphology, physiology, life history and the susceptibility to disease. A major challenge is to determine the contributions of individual loci to variation in complex traits. Quantitative trait locus (QTL) mapping has identified genomic regions affecting ecologically significant traits of many species. In nearly all cases, however, the importance of these QTLs to population variation remains unclear. In this paper, we apply a novel experimental method to parse the genetic variance of floral traits of the annual plant Mimulus guttatus into contributions of individual QTLs. We first use QTL-mapping to identify nine loci and then conduct a population-based breeding experiment to estimate V(Q), the genetic variance attributable to each QTL. We find that three QTLs with moderate effects explain up to one-third of the genetic variance in the natural population. Variation at these loci is probably maintained by some form of balancing selection. Notably, the largest effect QTLs were relatively minor in their contribution to heritability.     

Bulk segregant analysis with molecular markers and its use for improving drought resistance in maize

The usual method to locate and compare loci regulating quantitative traits (QTLs) requires a segregating population of plants with each one genotyped with molecular markers. However, plants from such segregating populations can also be grouped according to phenotypic expression of a trait and tested for differences in allele frequency between the population bulks: bulk segregant analysis (BSA). The same probes used for making a genetic map (e.g. isozyme, RFLP, RAPD, etc) can be used for BSA. A molecular marker showing polymorphism between the parents of the population and which is closely-linked to a major QTL regulating a particular trait will mainly co-segregate with that QTL, i.e. segregate according to the phenotype if the QTL has a large effect. Thus, if plants are grouped according to expression of the trait and extreme groups tested with that polymorphic marker, the frequency of the two marker alleles present within each of the two bulks should deviate significantly from the ratio of 1 : 1 expected for most populations. As chromosomal locations of many molecular markers have now been determined in many species, the map location of closely-linked QTLs can therefore be deduced without having to genotype every individual in segregating populations. This has been used successfully with composite populations of maize to locate QTLs associated with yield under severe drought. An inbred line derived from one of the populations selected for higher drought yield has been crossed with a drought-susceptible inbred line to produce a mapping population for QTL analysis of physiological and developmental traits likely to regulate yield under drought. Future work to identify traits having QTLs with flanking markers showing significant allele frequency differences in the GSA studies will indicate those traits likely to be important in determining yield under drought.Key words: Bulk segregant analysis (BSA), drought resistance, genetic maps, maize, molecular markers, Zea mays (L.).      

QTL analysis of intraspecific differences between two Silene vulgaris ecotypes

BACKGROUND AND AIMS: Serpentine soils provide a highly selective substrate for plant colonization and growth and represent an ideal system for studying the evolution of plant-ecotypes. In the present study the aim was to identify the genetic architecture of morphological traits distinguishing serpentine and non-serpentine ecotypes of Silene vulgaris. METHODS: Using an F(2) mapping population derived from an intraspecific cross between a serpentine and a non-serpentine ecotype of S. vulgaris, the genetic architecture of 12 morphological traits was explored using a quantitative trait locus (QTL) analysis. KEY RESULTS: The QTL analysis identified a total of 49 QTLs, of which 24 were classified as major QTLs. The mean number of QTLs per trait category was found to correspond well with numbers reported in the literature for similar crosses. Clustering of QTLs for different traits was found on several linkage groups. CONCLUSIONS: Morphological traits that differentiate the two ecotypes are strongly correlated, presumably as a consequence of the joint effects of extensive linkage of QTLs for different traits and directional selection. The signature of consistent directional selection was found for leaf and shoot trait divergence. Intraspecific ecotype differences in S. vulgaris were found to be distributed across the entire genome. The study shows that QTL analyses on non-model organisms can provide novel insights into the genetic basis of plant diversification.     

Identification of quantitative trait loci for agronomically important traits and their association with genic-microsatellite markers in sorghum

The identification of quantitative trait loci (QTLs) affecting agronomically important traits enable to understand their underlying genetic mechanisms and genetic basis of their complex interactions. The aim of the present study was to detect QTLs for 12 agronomic traits related to staygreen, plant early development, grain yield and its components, and some growth characters by analyzing replicated phenotypic datasets from three crop seasons, using the population of 168 F₇ RILs of the cross 296B × IS18551. In addition, we report mapping of a subset of genic-microsatellite markers. A linkage map was constructed with 152 marker loci comprising 149 microsatellites (100 genomic- and 49 genic-microsatellites) and three morphological markers. QTL analysis was performed by using MQM approach. Forty-nine QTLs were detected, across environments or in individual environments, with 1–9 QTLs for each trait. Individual QTL accounted for 5.2–50.4% of phenotypic variance. Several genomic regions affected multiple traits, suggesting the phenomenon of pleiotropy or tight linkage. Stable QTLs were identified for studied traits across different environments, and genetic backgrounds by comparing the QTLs in the study with previously reported QTLs in sorghum. Of the 49 mapped genic-markers, 18 were detected associating either closely or exactly as the QTL positions of agronomic traits. EST marker Dsenhsbm19, coding for a key regulator (EIL-1) of ethylene biosynthesis, was identified co-located with the QTLs for plant early development and staygreen trait, a probable candidate gene for these traits. Similarly, such exact co-locations between EST markers and QTLs were observed in four other instances. Collectively, the QTLs/markers identified in the study are likely candidates for improving the sorghum performance through MAS and map-based gene isolations.     

Yield-enhancing quantitative trait loci (QTLs) from wild species

Wild species of crop plants are increasingly being used to improve various agronomic traits including yield in cultivars. Dense molecular maps have enabled mapping of quantitative trait loci (QTLs) for complex traits such as yield. QTLs for increased yield have been identified from wild relatives of several crop plants. Advanced backcross QTL analysis has been used to identify naturally occurring favorable QTL alleles for yield and minimize the effect of unwanted alleles from wild species. Yield QTLs from wild species are distributed on almost all chromosomes but more often in some regions. Many QTLs for yield and related traits derived from different wild accessions or species map to identical chromosomal regions. QTLs for highly correlated yield associated traits are also often co-located implying linkage or pleiotropic effects. Many QTLs have been detected in more than one environment and in more than one genetic background. The overall direction of effect of some QTLs however, may vary with genetic context. Thus, there is evidence of stable and consistent major effect yield-enhancing QTLs derived from wild species in several crops. Such QTLs are good targets for use in marker assisted selection though their context-dependency is a major constraint. Literature on yield QTLs mapped from wild species is summarized with special reference to rice and tomato.     

QTL mapping for sexually dimorphic fitness-related traits in wild bighorn sheep

Dissecting the genetic architecture of fitness-related traits in wild populations is key to understanding evolution and the mechanisms maintaining adaptive genetic variation. We took advantage of a recently developed genetic linkage map and phenotypic information from wild pedigreed individuals from Ram Mountain, Alberta, Canada, to study the genetic architecture of ecologically important traits (horn volume, length, base circumference and body mass) in bighorn sheep. In addition to estimating sex-specific and cross-sex quantitative genetic parameters, we tested for the presence of quantitative trait loci (QTLs), colocalization of QTLs between bighorn sheep and domestic sheep, and sex × QTL interactions. All traits showed significant additive genetic variance and genetic correlations tended to be positive. Linkage analysis based on 241 microsatellite loci typed in 310 pedigreed animals resulted in no significant and five suggestive QTLs (four for horn dimension on chromosomes 1, 18 and 23, and one for body mass on chromosome 26) using genome-wide significance thresholds (Logarithm of odds (LOD) >3.31 and >1.88, respectively). We also confirmed the presence of a horn dimension QTL in bighorn sheep at the only position known to contain a similar QTL in domestic sheep (on chromosome 10 near the horns locus; nominal P<0.01) and highlighted a number of regions potentially containing weight-related QTLs in both species. As expected for sexually dimorphic traits involved in male-male combat, loci with sex-specific effects were detected. This study lays the foundation for future work on adaptive genetic variation and the evolutionary dynamics of sexually dimorphic traits in bighorn sheep.     

A genetic analysis of seed and berry weight in grapevine.

Fruit size and seedlessness are highly relevant traits in many fruit crop species, and both are primary targets of breeding programs for table grapes. In this work we performed a quantitative genetic analysis of size and seedlessness in an F1 segregating population derived from the cross between a classical seeded (Vitis vinifera L. 'Dominga') and a newly bred seedless ('Autumn Seedless') cultivar. Fruit size was scored as berry weight (BW), and for seedlessness we considered both seed fresh weight (SFW) and the number of seeds and seed traces (SN) per berry. Quantitative trait loci (QTL) analysis of BW detected 3 QTLs affecting this trait and accounting for up to 67% of the total phenotypic variance. QTL analysis for seedlessness detected 3 QTLs affecting SN (explaining up to 35% of total variance) and 6 affecting SFW (explaining up to 90% of total variance). Among them, a major effect QTL explained almost half of the phenotypic variation for SFW. Comparative analysis of QTLs for these traits reduced the number of grapevine genomic regions involved, one of them being a major effect QTL for seedlessness. Association analyses showed that microsatellite locus VMC7F2, closely linked to this QTL, is a useful marker for selection of seedlessnes.     

Regression-based multi-trait QTL mapping using a structural equation model

Quantitative trait loci (QTL) mapping often results in data on a number of traits that have well-established causal relationships. Many multi-trait QTL mapping methods that account for the correlation among multiple traits have been developed to improve the statistical power and the precision of QTL parameter estimation. However, none of these methods are capable of incorporating the causal structure among the traits. Consequently, genetic functions of the QTL may not be fully understood. Structural equation modeling (SEM) allows researchers to explicitly characterize the causal structure among the variables and to decompose effects into direct, indirect, and total effects. In this paper, we developed a multi-trait SEM method of QTL mapping that takes into account the causal relationships among traits related to grain yield. Performance of the proposed method is evaluated by simulation study and applied to data from a wheat experiment. Compared with single trait analysis and the multi-trait least-squares analysis, our multi-trait SEM improves statistical power of QTL detection and provides important insight into how QTLs regulate traits by investigating the direct, indirect, and total QTL effects. The approach also helps build biological models that more realistically reflect the complex relationships among QTL and traits and is more precise and efficient in QTL mapping than single trait analysis.     

利用双单倍体群体剖析水稻产量及其相关性状的遗传基础

主效QTL、上位性效应和它们与环境的互作(QE)都是数量性状的重要遗传因素。利用籼粳交珍汕97／武育粳2号F1植株上的花药进行组织培养得到的190个双单倍体群体和179个微卫星标记,通过两年两重复田间试验,采用混合线性模型方法分析了9个控制水稻产量及其相关性状的遗传效应,得到57个主效QTL,41对上位性互作,8对QTL与环境的互作和7对上位性效应与环境的互作。单个主效QTL解释这些性状1．3％～25．8％的表型方差。各性状QTL的累积表型贡献率达11．5％～66．8％。大多数性状之间具有显著的表型相关性,相关性较高的性状之间常具有较多共同或紧密连锁的QTL。结果表明,基因的多效性或紧密连锁可能是性状相关的重要遗传基础。     

Bayesian analysis for genetic architecture of dynamic traits

The dissection of the genetic architecture of quantitative traits, including the number and locations of quantitative trait loci (QTL) and their main and epistatic effects, has been an important topic in current QTL mapping. We extend the Bayesian model selection framework for mapping multiple epistatic QTL affecting continuous traits to dynamic traits in experimental crosses. The extension inherits the efficiency of Bayesian model selection and the flexibility of the Legendre polynomial model fitting to the change in genetic and environmental effects with time. We illustrate the proposed method by simultaneously detecting the main and epistatic QTLs for the growth of leaf age in a doubled-haploid population of rice. The behavior and performance of the method are also shown by computer simulation experiments. The results show that our method can more quickly identify interacting QTLs for dynamic traits in the models with many numbers of genetic effects, enhancing our understanding of genetic architecture for dynamic traits. Our proposed method can be treated as a general form of mapping QTL for continuous quantitative traits, being easier to extend to multiple traits and to a single trait with repeat records.     

Heritability, correlations and in silico mapping of locomotor behavior and neurochemistry in inbred strains of mice

The midbrain dopamine system mediates normal and pathologic behaviors related to motor activity, attention, motivation/reward and cognition. These are complex, quantitative traits whose variation among individuals is modulated by genetic, epigenetic and environmental factors. Conventional genetic methods have identified several genes important to this system, but the majority of factors contributing to the variation remain unknown. To understand these genetic and environmental factors, we initiated a study measuring 21 behavioral and neurochemical traits in 15 common inbred mouse strains. We report trait data, heritabilities and genetic and non-genetic correlations between pheno-types. In general, the behavioral traits were more heritable than neurochemical traits, and both genetic and non-genetic correlations within these trait sets were high. Surprisingly, there were few significant correlations between the behavioral and the individual neurochemical traits. However, striatal serotonin and one measure of dopamine turnover (DOPAC/DA) were highly correlated with most behavioral measures. The variable accounting for the most variation in behavior was mouse strain and not a specific neurochemical measure, suggesting that additional genetic factors remain to be determined to account for these behavioral differences. We also report the prospective use of the in silico method of quantitative trait loci (QTL) analysis and demonstrate difficulties in the use of this method, which failed to detect significant QTLs for the majority of these traits. These data serve as a framework for further studies of correlations between different midbrain dopamine traits and as a guide for experimental cross designs to identify QTLs and genes that contribute to these traits.     

Identification of quantitative trait loci for wood quality and growth across eight full-sib coastal Douglas-fir families

Typical linkage and quantitative trait locus (QTL) analyses in forest trees have been conducted in single pedigrees with sex-averaged linkage maps. The results of a QTL analysis for wood quality and growth traits of coastal Douglas-fir using eight full-sib families, each consisting of 40 progeny, replicated on four sites are presented. The resulting map of segregating genetic markers consisted of 120 amplified fragment length polymorphism (AFLP) loci distributed across 19 linkage groups. The wood quality traits represent the widest suite of traits yet examined for QTL analysis in a tree species in a single study. Wood fiber traits showed the lowest number of QTLs (3) with relatively small effect (ca. 4%); wood density traits also showed just three QTLs but with slightly larger effect; wood chemistry traits showed more QTLs (7), while ring density traits showed many QTLs with large numbers of QTLs (78) and interesting patterns of temporal variation. Growth traits gave just five QTLs but of major effect (10–16%). Trees, with their long generation times, provide a rich resource for studies of temporal variation of QTL expression.     

Dissecting the Genetic Basis of Extremely Large Grain Shape in Rice Cultivar ＇JZ1560＇

Rice grain shape,grain length(GL),width(GW),thickness(GT)and length-to-width ratio(LWR),are usually controlled by multiple quantitative trait locus(QTL).To elucidate the genetic basis of extremely large grain shape,QTL analysis was performed using an F2 population derived from a cross between a japonica cultivar ’JZ1560’(extremely large grain)and a contrasting indica cultivar ’FAZ1’(small grain).A total number of 24 QTLs were detected on seven different chromosomes.QTLs for GL,GW,GT and LWR explained 11.6%,95.62%,91.5%and 89.9%of total phenotypic variation,respectively.Many QTLs pleiotropically controlled different grain traits,contributing complex traits correlation.GW2 and qSW5/GW5,which have been cloned previously to control GW,showed similar chromosomal locations with qGW2-I/qGT2-I/qLWR2-2 and qGW5-2/qLWR5-l and should be the right candidate genes.Plants pyramiding GW2 and qSW5/GW5 showed a significant increase in GW compared with those carrying one of the two major QTLs.Furthermore,no significant QTL interaction was observed between GW2 and qSW5/GW5.These results suggested that GW2 and qSW5/GW5 might work in independent pathways to regulate grain traits.’JZ1560’ alleles underlying all QTLs contributed an increase in GW and GT and the accumulation of additive effects generates the extremely large grain shape in ’JZ1560’.     

水稻产量相关QTL研究现状

产量是最为复杂的数量性状,对它的遗传机理了解甚微。近15年来,许多学者利用随机分离群体定位了许多影响水稻产量及其组分的QTL,即以QTL定位的方法对产量潜力进行遗传剖析。试验证明上位性效应对产量及其组分性状遗传变异起着重要作用,但目前大多数QTL研究仍侧重于发掘和克隆单个主效QTL,然而对单一基因／QTL的深入了解还不足以诠释复杂性状遗传基础的全貌,还没有为育种家提供足够的可应用于分子标记辅助育种的遗传信息并用于提高水稻产量。笔者认为今后的数量性状研究尚需加强复杂性状QTL遗传网络的发掘,在改良水稻品种性状的同时发展并完善QTL研究。     

A unified DNA sequence and non‐DNA sequence mapping model of complex traits

Increasing evidence shows that quantitative inheritance is based on both DNA sequence and non‐DNA sequence variants. However, how to simultaneously detect these variants from a mapping study has been unexplored, hampering our effort to illustrate the detailed genetic architecture of complex traits. We address this issue by developing a unified model of quantitative trait locus (QTL) mapping based on an open‐pollinated design composed of randomly sampling maternal plants from a natural population and their half‐sib seeds. This design forms a two‐level hierarchical platform for a joint linkage‐linkage disequilibrium analysis of population structure. The EM algorithm was implemented to estimate and test DNA sequence‐based effects and non‐DNA sequence‐based effects of QTLs. We applied this model to analyze genetic mapping data from the OP design of a gymnosperm coniferous species, Torreya grandis, identifying 25 significant DNA sequence and non‐DNA sequence QTLs for seedling height and diameter growth in different years. Results from computer simulation show that the unified model has good statistical properties and is powerful for QTL detection. Our model enables the tests of how a complex trait is affected differently by DNA‐based effects and non‐DNA sequence‐based transgenerational effects, thus allowing a more comprehensive picture of genetic architecture to be charted and quantified.     

QTL mapping of combining ability and heterosis of agronomic traits in rice backcross recombinant inbred lines and hybrid crosses

Background

Combining ability effects are very effective genetic parameters in deciding the next phase of breeding programs. Although some breeding strategies on the basis of evaluating combining ability have been utilized extensively in hybrid breeding, little is known about the genetic basis of combining ability. Combining ability is a complex trait that is controlled by polygenes. With the advent and development of molecular markers, it is feasible to evaluate the genetic bases of combining ability and heterosis of elite rice hybrids through QTL analysis.

Methodology/Principal Findings

In the present study, we first developed a QTL-mapping method for dissecting combining ability and heterosis of agronomic traits. With three testcross populations and a BCRIL population in rice, biometric and QTL analyses were conducted for ten agronomic traits. The significance of general combining ability and special combining ability for most of the traits indicated the importance of both additive and non-additive effects on expression levels. A large number of additive effect QTLs associated with performance per se of BCRIL and general combining ability, and dominant effect QTLs associated with special combining ability and heterosis were identified for the ten traits.

Conclusions/Significance

The combining ability of agronomic traits could be analyzed by the QTL mapping method. The characteristics revealed by the QTLs for combining ability of agronomic traits were similar with those by multitudinous QTLs for agronomic traits with performance per se of BCRIL. Several QTLs (1–6 in this study) were identified for each trait for combining ability. It demonstrated that some of the QTLs were pleiotropic or linked tightly with each other. The identification of QTLs responsible for combining ability and heterosis in the present study provides valuable information for dissecting genetic basis of combining ability.     

A New Method to Infer Causal Phenotype Networks Using QTL and Phenotypic Information

In the context of genetics and breeding research on multiple phenotypic traits, reconstructing the directional or causal structure between phenotypic traits is a prerequisite for quantifying the effects of genetic interventions on the traits. Current approaches mainly exploit the genetic effects at quantitative trait loci (QTLs) to learn about causal relationships among phenotypic traits. A requirement for using these approaches is that at least one unique QTL has been identified for each trait studied. However, in practice, especially for molecular phenotypes such as metabolites, this prerequisite is often not met due to limited sample sizes, high noise levels and small QTL effects. Here, we present a novel heuristic search algorithm called the QTL+phenotype supervised orientation (QPSO) algorithm to infer causal directions for edges in undirected phenotype networks. The two main advantages of this algorithm are: first, it does not require QTLs for each and every trait; second, it takes into account associated phenotypic interactions in addition to detected QTLs when orienting undirected edges between traits. We evaluate and compare the performance of QPSO with another state-of-the-art approach, the QTL-directed dependency graph (QDG) algorithm. Simulation results show that our method has broader applicability and leads to more accurate overall orientations. We also illustrate our method with a real-life example involving 24 metabolites and a few major QTLs measured on an association panel of 93 tomato cultivars. Matlab source code implementing the proposed algorithm is freely available upon request.     

Pleiotropic effects on mandibular morphology II: differential epistasis and genetic variation in morphological integration

The evolution of morphological modularity through the sequestration of pleiotropy to sets of functionally and developmentally related traits requires genetic variation in the relationships between traits. Genetic variation in relationships between traits can result from differential epistasis, where epistatic relationships for pairs of loci are different for different traits. This study maps relationship quantitative trait loci (QTLs), specifically QTLs that affect the relationship between individual mandibular traits and mandible length, across the genome in an F2 intercross of the LG/J and SM/J inbred mouse strains (N = 1045). We discovered 23 relationship QTLs scattered throughout the genome. All mandibular traits were involved in one or more relationship QTL. When multiple traits were affected at a relationship QTL, the traits tended to come from a developmentally restricted region of the mandible, either the muscular processes or the alveolus. About one-third of the relationship QTLs correspond to previously located trait QTLs affecting the same traits. These results comprise examples of genetic variation necessary for an evolutionary response to selection on the range of pleiotropic effects.