Quantitative Trait Locus Mapping and Candidate Gene Analysis for Plant Architecture Traits Using Whole Genome Re-Sequencing in Rice

Plant breeders have focused on improving plant architecture as an effective means to increase crop yield. Here, we identify the main-effect quantitative trait loci (QTLs) for plant shape-related traits in rice (Oryza sativa) and find candidate genes by applying whole genome re-sequencing of two parental cultivars using next-generation sequencing. To identify QTLs influencing plant shape, we analyzed six traits: plant height, tiller number, panicle diameter, panicle length, flag leaf length, and flag leaf width. We performed QTL analysis with 178 F₇ recombinant in-bred lines (RILs) from a cross of japonica rice line ‘SNUSG1’ and indica rice line ‘Milyang23’. Using 131 molecular markers, including 28 insertion/deletion markers, we identified 11 main- and 16 minor-effect QTLs for the six traits with a threshold LOD value > 2.8. Our sequence analysis identified fifty-four candidate genes for the main-effect QTLs. By further comparison of coding sequences and meta-expression profiles between japonica and indica rice varieties, we finally chose 15 strong candidate genes for the 11 main-effect QTLs. Our study shows that the whole-genome sequence data substantially enhanced the efficiency of polymorphic marker development for QTL fine-mapping and the identification of possible candidate genes. This yields useful genetic resources for breeding high-yielding rice cultivars with improved plant architecture.     

遗传基因组学(Genetical genomics)的研究进展

遗传基因组学(geneticalgenomics)是将微阵列技术和数量性状座位(QTL)分析结合起来,全基因组水平上定位基因表达的QTL(eQTL).它为研究复杂性状的分子机理和调控网络提供全新的手段.遗传基因组这个概念和研究策略在2001年由Janson和Nap首先提出,到目前为止,遗传基因组学已应用于酵母、老鼠、人以及玉米等植物.研究结果表明:基因表达水平的差异是可遗传的复杂性状;eQTL可以分为顺式作用eQTL和反式作用eQTL,顺式作用eQTL就是某个基因的eQTL定位到该基因所在的基因组区域,表明可能是该基因本身的差别引起mRNA水平的差别,反式作用就是eQTL定位到其他基因组区域,表明其他基因的差别控制该基因mRNA水平的差异.将eQTL结果、基因功能注解以及多种统计分析方法相结合,不仅能更准确地鉴别控制复杂性状及其相关基因表达的候选基因,而且能构建相应的基因调控网络.     

Organ specificity and transcriptional control of metabolic routes revealed by expression QTL profiling of source-sink tissues in a segregating potato population

Background  

With the completion of genome sequences belonging to some of the major crop plants, new challenges arise to utilize this data for crop improvement and increased food security. The field of genetical genomics has the potential to identify genes displaying heritable differential expression associated to important phenotypic traits. Here we describe the identification of expression QTLs (eQTLs) in two different potato tissues of a segregating potato population and query the potato genome sequence to differentiate between cis- and trans-acting eQTLs in relation to gene subfunctionalization.     

A Linear Mixed Model Spline Framework for Analysing Time Course ‘Omics’ Data

Time course ‘omics’ experiments are becoming increasingly important to study system-wide dynamic regulation. Despite their high information content, analysis remains challenging. ‘Omics’ technologies capture quantitative measurements on tens of thousands of molecules. Therefore, in a time course ‘omics’ experiment molecules are measured for multiple subjects over multiple time points. This results in a large, high-dimensional dataset, which requires computationally efficient approaches for statistical analysis. Moreover, methods need to be able to handle missing values and various levels of noise. We present a novel, robust and powerful framework to analyze time course ‘omics’ data that consists of three stages: quality assessment and filtering, profile modelling, and analysis. The first step consists of removing molecules for which expression or abundance is highly variable over time. The second step models each molecular expression profile in a linear mixed model framework which takes into account subject-specific variability. The best model is selected through a serial model selection approach and results in dimension reduction of the time course data. The final step includes two types of analysis of the modelled trajectories, namely, clustering analysis to identify groups of correlated profiles over time, and differential expression analysis to identify profiles which differ over time and/or between treatment groups. Through simulation studies we demonstrate the high sensitivity and specificity of our approach for differential expression analysis. We then illustrate how our framework can bring novel insights on two time course ‘omics’ studies in breast cancer and kidney rejection. The methods are publicly available, implemented in the R CRAN package lmms.     

High-throughput root phenotyping screens identify genetic loci associated with root architectural traits in Brassica napus under contrasting phosphate availabilities

Background and Aims

Phosphate (Pi) deficiency in soils is a major limiting factor for crop growth worldwide. Plant growth under low Pi conditions correlates with root architectural traits and it may therefore be possible to select these traits for crop improvement. The aim of this study was to characterize root architectural traits, and to test quantitative trait loci (QTL) associated with these traits, under low Pi (LP) and high Pi (HP) availability in Brassica napus.

Methods

Root architectural traits were characterized in seedlings of a double haploid (DH) mapping population (n = 190) of B. napus [‘Tapidor’ × ‘Ningyou 7’ (TNDH)] using high-throughput phenotyping methods. Primary root length (PRL), lateral root length (LRL), lateral root number (LRN), lateral root density (LRD) and biomass traits were measured 12 d post-germination in agar at LP and HP.

Key Results

In general, root and biomass traits were highly correlated under LP and HP conditions. ‘Ningyou 7’ had greater LRL, LRN and LRD than ‘Tapidor’, at both LP and HP availability, but smaller PRL. A cluster of highly significant QTL for LRN, LRD and biomass traits at LP availability were identified on chromosome A03; QTL for PRL were identified on chromosomes A07 and C06.

Conclusions

High-throughput phenotyping of Brassica can be used to identify root architectural traits which correlate with shoot biomass. It is feasible that these traits could be used in crop improvement strategies. The identification of QTL linked to root traits under LP and HP conditions provides further insights on the genetic basis of plant tolerance to P deficiency, and these QTL warrant further dissection.     

Key questions in the genetics and genomics of eco-evolutionary dynamics

Increasing acceptance that evolution can be ‘rapid'' (or ‘contemporary'') has generated growing interest in the consequences for ecology. The genetics and genomics of these ‘eco-evolutionary dynamics'' will be—to a large extent—the genetics and genomics of organismal phenotypes. In the hope of stimulating research in this area, I review empirical data from natural populations and draw the following conclusions. (1) Considerable additive genetic variance is present for most traits in most populations. (2) Trait correlations do not consistently oppose selection. (3) Adaptive differences between populations often involve dominance and epistasis. (4) Most adaptation is the result of genes of small-to-modest effect, although (5) some genes certainly have larger effects than the others. (6) Adaptation by independent lineages to similar environments is mostly driven by different alleles/genes. (7) Adaptation to new environments is mostly driven by standing genetic variation, although new mutations can be important in some instances. (8) Adaptation is driven by both structural and regulatory genetic variation, with recent studies emphasizing the latter. (9) The ecological effects of organisms, considered as extended phenotypes, are often heritable. Overall, the study of eco-evolutionary dynamics will benefit from perspectives and approaches that emphasize standing genetic variation in many genes of small-to-modest effect acting across multiple traits and that analyze overall adaptation or ‘fitness''. In addition, increasing attention should be paid to dominance, epistasis and regulatory variation.     

Weevil x Insecticide: Does ‘Personality’ Matter?

An insect’s behavior is the expression of its integrated physiology in response to external and internal stimuli, turning insect behavior into a potential determinant of insecticide exposure. Behavioral traits may therefore influence insecticide efficacy against insects, compromising the validity of standard bioassays of insecticide activity, which are fundamentally based on lethality alone. By extension, insect ‘personality’ (i.e., an individual’s integrated set of behavioral tendencies that is inferred from multiple empirical measures) may also be an important determinant of insecticide exposure and activity. This has yet to be considered because the behavioral studies involving insects and insecticides focus on populations rather than on individuals. Even among studies of animal ‘personality’, the relative contributions of individual and population variation are usually neglected. Here, we assessed behavioral traits (within the categories: activity, boldness/shyness, and exploration/avoidance) of individuals from 15 populations of the maize weevil (Sitophilus zeamais), an important stored-grain pest with serious problems of insecticide resistance, and correlated the behavioral responses with the activity of the insecticide deltamethrin. This analysis was performed at both the population and individual levels. There was significant variation in weevil ‘personality’ among individuals and populations, but variation among individuals within populations accounted for most of the observed variation (92.57%). This result emphasizes the importance of individual variation in behavioral and ‘personality’ studies. When the behavioral traits assessed were correlated with median lethal time (LT₅₀) at the population level and with the survival time under insecticide exposure, activity traits, particularly the distance walked, significantly increased survival time. Therefore, behavioral traits are important components of insecticide efficacy, and individual variation should be considered in such studies. This is so because population differences provided only crude approximation of the individual personality in a restrained experimental setting likely to restrict individual behavior favoring the transposition of the individual variation to the population.     

Mapping determinants of gene expression plasticity by genetical genomics in C. elegans

Recent genetical genomics studies have provided intimate views on gene regulatory networks. Gene expression variations between genetically different individuals have been mapped to the causal regulatory regions, termed expression quantitative trait loci. Whether the environment-induced plastic response of gene expression also shows heritable difference has not yet been studied. Here we show that differential expression induced by temperatures of 16 °C and 24 °C has a strong genetic component in Caenorhabditis elegans recombinant inbred strains derived from a cross between strains CB4856 (Hawaii) and N2 (Bristol). No less than 59% of 308 trans-acting genes showed a significant eQTL-by-environment interaction, here termed plasticity quantitative trait loci. In contrast, only 8% of an estimated 188 cis-acting genes showed such interaction. This indicates that heritable differences in plastic responses of gene expression are largely regulated in trans. This regulation is spread over many different regulators. However, for one group of trans-genes we found prominent evidence for a common master regulator: a transband of 66 coregulated genes appeared at 24 °C. Our results suggest widespread genetic variation of differential expression responses to environmental impacts and demonstrate the potential of genetical genomics for mapping the molecular determinants of phenotypic plasticity.     

Expression Quantitative Trait Loci Are Highly Sensitive to Cellular Differentiation State

Genetical genomics is a strategy for mapping gene expression variation to expression quantitative trait loci (eQTLs). We performed a genetical genomics experiment in four functionally distinct but developmentally closely related hematopoietic cell populations isolated from the BXD panel of recombinant inbred mouse strains. This analysis allowed us to analyze eQTL robustness/sensitivity across different cellular differentiation states. Although we identified a large number (365) of “static” eQTLs that were consistently active in all four cell types, we found a much larger number (1,283) of “dynamic” eQTLs showing cell-type–dependence. Of these, 140, 45, 531, and 295 were preferentially active in stem, progenitor, erythroid, and myeloid cells, respectively. A detailed investigation of those dynamic eQTLs showed that in many cases the eQTL specificity was associated with expression changes in the target gene. We found no evidence for target genes that were regulated by distinct eQTLs in different cell types, suggesting that large-scale changes within functional regulatory networks are uncommon. Our results demonstrate that heritable differences in gene expression are highly sensitive to the developmental stage of the cell population under study. Therefore, future genetical genomics studies should aim at studying multiple well-defined and highly purified cell types in order to construct as comprehensive a picture of the changing functional regulatory relationships as possible.     

Identification of QTLs Associated with Oil Content in a High-Oil Brassica napus Cultivar and Construction of a High-Density Consensus Map for QTLs Comparison in B. napus

Increasing seed oil content is one of the most important goals in breeding of rapeseed (B. napus L.). To dissect the genetic basis of oil content in B. napus, a large and new double haploid (DH) population containing 348 lines was obtained from a cross between ‘KenC-8’ and ‘N53-2’, two varieties with >10% difference in seed oil content, and this population was named the KN DH population. A genetic linkage map consisting of 403 markers was constructed, which covered a total length of 1783.9 cM with an average marker interval of 4.4 cM. The KN DH population was phenotyped in eight natural environments and subjected to quantitative trait loci (QTL) analysis for oil content. A total of 63 identified QTLs explaining 2.64–17.88% of the phenotypic variation were identified, and these QTLs were further integrated into 24 consensus QTLs located on 11 chromosomes using meta-analysis. A high-density consensus map with 1335 marker loci was constructed by combining the KN DH map with seven other published maps based on the common markers. Of the 24 consensus QTLs in the KN DH population, 14 were new QTLs including five new QTLs in A genome and nine in C genome. The analysis revealed that a larger population with significant differences in oil content gave a higher power detecting new QTLs for oil content, and the construction of the consensus map provided a new clue for comparing the QTLs detected in different populations. These findings enriched our knowledge of QTLs for oil content and should be a potential in marker-assisted breeding of B. napus.     

A Chromosome Segment Substitution Library of Weedy Rice for Genetic Dissection of Complex Agronomic and Domestication Traits

Chromosome segment substitution lines (CSSLs) are a powerful alternative for locating quantitative trait loci (QTL), analyzing gene interactions, and providing starting materials for map-based cloning projects. We report the development and characterization of a CSSL library of a U.S. weedy rice accession ‘PSRR-1’ with genome-wide coverage in an adapted rice cultivar ‘Bengal’ background. The majority of the CSSLs carried a single defined weedy rice segment with an average introgression segment of 2.8 % of the donor genome. QTL mapping results for several agronomic and domestication traits from the CSSL population were compared with those obtained from two recombinant inbred line (RIL) populations involving the same weedy rice accession. There was congruence of major effect QTLs between both types of populations, but new and additional QTLs were detected in the CSSL population. Although, three major effect QTLs for plant height were detected on chromosomes 1, 4, and 8 in the CSSL population, the latter two escaped detection in both RIL populations. Since this was observed for many traits, epistasis may play a major role for the phenotypic variation observed in weedy rice. High levels of shattering and seed dormancy in weedy rice might result from an accumulation of many small effect QTLs. Several CSSLs with desirable agronomic traits (e.g. longer panicles, longer grains, and higher seed weight) identified in this study could be useful for rice breeding. Since weedy rice is a reservoir of genes for many weedy and agronomic attributes, the CSSL library will serve as a valuable resource to discover latent genetic diversity for improving crop productivity and understanding the plant domestication process through cloning and characterization of the underlying genes.     

Pleiotropy of FRIGIDA enhances the potential for multivariate adaptation

An evolutionary response to selection requires genetic variation; however, even if it exists, then the genetic details of the variation can constrain adaptation. In the simplest case, unlinked loci and uncorrelated phenotypes respond directly to multivariate selection and permit unrestricted paths to adaptive peaks. By contrast, ‘antagonistic’ pleiotropic loci may constrain adaptation by affecting variation of many traits and limiting the direction of trait correlations to vectors that are not favoured by selection. However, certain pleiotropic configurations may improve the conditions for adaptive evolution. Here, we present evidence that the Arabidopsis thaliana gene FRI (FRIGIDA) exhibits ‘adaptive’ pleiotropy, producing trait correlations along an axis that results in two adaptive strategies. Derived, low expression FRI alleles confer a ‘drought escape’ strategy owing to fast growth, low water use efficiency and early flowering. By contrast, a dehydration avoidance strategy is conferred by the ancestral phenotype of late flowering, slow growth and efficient water use during photosynthesis. The dehydration avoidant phenotype was recovered when genotypes with null FRI alleles were transformed with functional alleles. Our findings indicate that the well-documented effects of FRI on phenology result from differences in physiology, not only a simple developmental switch.     

The influence of genetics on future crop production strategies: from traits to genes, and genes to traits

This paper discusses how a genetical approach to plant physiology can contribute to research underpinning the production of new crop varieties. It highlights the interactions between genetics and plant breeding and how the current advances in genetics and the new science of genomics can contribute to our understanding of the genetical control of key agronomic traits ‐ the process of ‘translating’ traits to identified and mapped genes. Advances in genomics, such as the sequencing of whole genomes and expressed sequence tags, are producing information on genes and gene structures, but without knowing their function. A great deal more biology will be necessary to translate gene structure to function ‐ the process of translating genes to traits. Combining these ‘forward’ and ‘reverse’ genetic approaches will allow us to get comprehensive knowledge of the biology of agronomic traits at the physiological, biochemical and molecular levels, so that the ‘circuitry’ of our crop plants can be elucidated. This will enable plant breeders to manipulate crop phenotype using marker‐assisted breeding or genetic engineering approaches with a precision not previously possible.     

Genetic and genomic analysis of a fat mass trait with complex inheritance reveals marked sex specificity

The integration of expression profiling with linkage analysis has increasingly been used to identify genes underlying complex phenotypes. The effects of gender on the regulation of many physiological traits are well documented; however, “genetical genomic” analyses have not yet addressed the degree to which their conclusions are affected by sex. We constructed and densely genotyped a large F2 intercross derived from the inbred mouse strains C57BL/6J and C3H/HeJ on an apolipoprotein E null (ApoE^−/−) background. This BXH.ApoE^−/− population recapitulates several “metabolic syndrome” phenotypes. The cross consists of 334 animals of both sexes, allowing us to specifically test for the dependence of linkage on sex. We detected several thousand liver gene expression quantitative trait loci, a significant proportion of which are sex-biased. We used these analyses to dissect the genetics of gonadal fat mass, a complex trait with sex-specific regulation. We present evidence for a remarkably high degree of sex-dependence on both the cis and trans regulation of gene expression. We demonstrate how these analyses can be applied to the study of the genetics underlying gonadal fat mass, a complex trait showing significantly female-biased heritability. These data have implications on the potential effects of sex on the genetic regulation of other complex traits.