A stochastic expectation and maximization algorithm for detecting quantitative trait-associated genes

MOTIVATION: Most biological traits may be correlated with the underlying gene expression patterns that are partially determined by DNA sequence variation. The correlations between gene expressions and quantitative traits are essential for understanding the functions of genes and dissecting gene regulatory networks. RESULTS: In the present study, we adopted a novel statistical method, called the stochastic expectation and maximization (SEM) algorithm, to analyze the associations between gene expression levels and quantitative trait values and identify genetic loci controlling the gene expression variations. In the first step, gene expression levels measured from microarray experiments were assigned to two different clusters based on the strengths of their association with the phenotypes of a quantitative trait under investigation. In the second step, genes associated with the trait were mapped to genetic loci of the genome. Because gene expressions are quantitative, the genetic loci controlling the expression traits are called expression quantitative trait loci. We applied the same SEM algorithm to a real dataset collected from a barley genetic experiment with both quantitative traits and gene expression traits. For the first time, we identified genes associated with eight agronomy traits of barley. These genes were then mapped to seven chromosomes of the barley genome. The SEM algorithm and the result of the barley data analysis are useful to scientists in the areas of bioinformatics and plant breeding. Availability and implementation: The R program for the SEM algorithm can be downloaded from our website: http://www.statgen.ucr.edu.     

To clone or not to clone plant QTLs: present and future challenges

Recent technical advancements and refinement of analytical methods have enabled the loci (quantitative trait loci, QTLs) responsible for the genetic control of quantitative traits to be dissected molecularly. To date, most plant QTLs have been cloned using a positional cloning approach following identification in experimental crosses. In some cases, an association between sequence variation at a candidate gene and a phenotype has been established by analysing existing genetic accessions. These strategies can be refined using appropriate genetic materials and the latest developments in genomics platforms. We foresee that although QTL analysis and cloning addressing naturally occurring genetic variation should shed light on mechanisms of plant adaptation, a greater emphasis on approaches relying on mutagenesis and candidate gene validation is likely to accelerate the pace of discovering the genes underlying QTLs.     

QTL analysis and comparative genomics of herbage quality traits in perennial ryegrass (Lolium perenne L.)

Genetic control of herbage quality variation was assessed through the use of the molecular marker-based reference genetic map of perennial ryegrass (Lolium perenne L.). The restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP) and genomic DNA-derived simple sequence repeat-based (SSR) framework marker set was enhanced, with RFLP loci corresponding to genes for key enzymes involved in lignin biosynthesis and fructan metabolism. Quality traits such as crude protein (CP) content, estimated in vivo dry matter digestibility (IVVDMD), neutral detergent fibre content (NDF), estimated metabolisable energy (EstME) and water soluble carbohydrate (WSC) content were measured by near infrared reflectance spectroscopy (NIRS) analysis of herbage harvests. Quantitative trait locus (QTL) analysis was performed using single-marker regression, simple interval mapping and composite interval mapping approaches, detecting a total of 42 QTLs from six different sampling experiments varying by developmental stage (anthesis or vegetative growth), location or year. Coincident QTLs were detected on linkage groups (LGs) 3, 5 and 7. The region on LG3 was associated with variation for all measured traits across various experimental datasets. The region on LG7 was associated with variation for all traits except CP, and is located in the vicinity of the lignin biosynthesis gene loci xlpomt1 (caffeic acid-O-methyltransferase), xlpccr1 (cinnamoyl CoA-reductase) and xlpssrcad 2.1 (cinnamyl alcohol dehydrogenase). Comparative genomics analysis of these gene classes with wheat (Triticum aestivum L.) provides evidence for conservation of gene order over evolutionary time and the basis for cross-specific genetic information transfer. The identification of co-location between QTLs and functionally associated genetic markers is critical for the implementation of marker-assisted selection programs and for linkage disequilibrium studies, which will enable future improvement strategies for perennial ryegrass.     

Genomic approaches to analyzing natural variation in Arabidopsis thaliana

The genomics tools available for studying Arabidopsis thaliana are a great resource for researchers trying to characterize and understand the genetic basis of natural variation. Abundant polymorphic markers aid quantitative trait locus (QTL) mapping, the fully sequenced genome provides rapid identification of candidate loci, and extensive knockout collections allow those candidate loci to be tested. Combining QTL mapping of classic phenotypic traits with biochemical or expression analysis is providing mechanistic insight into the traits of interest. Conversely, natural variation studies are now being done on genomic traits such as methylation or chiasma frequency.     

Beyond Arabidopsis. Translational biology meets evolutionary developmental biology

Developmental processes shape plant morphologies, which constitute important adaptive traits selected for during evolution. Identifying the genes that act in developmental pathways and determining how they are modified during evolution is the focus of the field of evolutionary developmental biology, or evo-devo. Knowledge of genetic pathways in the plant model Arabidopsis serves as the starting point for investigating how the toolkit of developmental pathways has been used and reused to form different plant body plans. One productive approach is to identify genes in other species that are orthologous to genes known to control developmental pathways in Arabidopsis and then determine what changes have occurred in the protein coding sequence or in the gene's expression to produce an altered morphology. A second approach relies on natural variation among wild populations or crop plants. Natural variation can be exploited to identify quantitative trait loci that underlie important developmental traits and, thus, define those genes that are responsible for adaptive changes. The possibility of applying comparative genomics approaches to Arabidopsis and related species promises profound new insights into the interplay of evolution and development.     

Sequence diversity and haplotype associations with phenotypic responses to crowding: GIGANTEA affects fruit set in Arabidopsis thaliana

Identifying the molecular genetic basis of intraspecific variation in quantitative traits promises to provide novel insight into their evolutionary history as well as genetic mechanisms of adaptation. In an attempt to identify genes responsible for natural variation in competitive responses in Arabidopsis thaliana, we examined DNA sequence diversity at seven loci previously identified as members of the phytochrome B signalling network. For one gene, GIGANTEA (GI), we detected significant haplotype structure. To test for GI haplogroup-phenotype associations, we genotyped 161 A. thaliana accessions at GI and censused the same accessions for total fruit set and the expression of three phenotypic traits (days to flowering, petiole length, and inflorescence height) in a greenhouse experiment where plants were grown in crowded and uncrowded environments. We detected a significant association between GI and total fruit set that resulted in a 14% difference in average fruit set among GI haplogroups. Given that fruit set is an important component of fitness in this species and given the magnitude of the effect, the question arises as to how variation at this locus is maintained. Our observation of frequent and significant epistasis between GI and background single nucleotide polymorphisms (SNP), where the fitness ranking of the GI allele either reverses or does not differ depending on the allele at the interacting SNP, suggests that epistatic selection may actively maintain or at least slow the loss of variation at GI. This result is particularly noteworthy in the light of the ongoing debate regarding the genetic underpinnings of phenotypic evolution and recent observations that epistasis for phenotypic traits and components of fitness is common in A. thaliana.     

植物逆境胁迫抗性的功能基因组研究策略

植物对逆境胁迫抗性的功能基因组研究主要是寻找胁迫抗性位点在相关物种基因组中的保守位置,发现胁迫反应中的高度保守序列,确定植物胁迫反应的调控机理,进而得到植物对逆境胁迫抗性的关键代谢途径和其中的关键调控因子,为进一步选择用于改良植物对逆境胁迫抗性的关键基因奠定基础。本文从主要模式植物(苔藓类植物、复苏植物、盐土植物和甜土植物)、主要技术策略(基因的差异表达分析、基因表达序列标签、cDNA芯片技术。基因表达序列分析和基因敲除和突变体筛选分析)和生物信息学方法(数据分析的生物信息学方法设计到序列比较、比较基因组学、电子克隆)等三个方面对国内外植物逆境胁迫抗性的功能基因组研究策略作了全面综述。     

Genetical genomics identifies the genetic architecture for growth and weevil resistance in spruce

In plants, relationships between resistance to herbivorous insect pests and growth are typically controlled by complex interactions between genetically correlated traits. These relationships often result in tradeoffs in phenotypic expression. In this study we used genetical genomics to elucidate genetic relationships between tree growth and resistance to white pine terminal weevil (Pissodes strobi Peck.) in a pedigree population of interior spruce (Picea glauca, P. engelmannii and their hybrids) that was growing at Vernon, B.C. and segregating for weevil resistance. Genetical genomics uses genetic perturbations caused by allelic segregation in pedigrees to co-locate quantitative trait loci (QTLs) for gene expression and quantitative traits. Bark tissue of apical leaders from 188 trees was assayed for gene expression using a 21.8K spruce EST-spotted microarray; the same individuals were genotyped for 384 SNP markers for the genetic map. Many of the expression QTLs (eQTL) co-localized with resistance trait QTLs. For a composite resistance phenotype of six attack and oviposition traits, 149 positional candidate genes were identified. Resistance and growth QTLs also overlapped with eQTL hotspots along the genome suggesting that: 1) genetic pleiotropy of resistance and growth traits in interior spruce was substantial, and 2) master regulatory genes were important for weevil resistance in spruce. These results will enable future work on functional genetic studies of insect resistance in spruce, and provide valuable information about candidate genes for genetic improvement of spruce.     

Natural genetic variation in Arabidopsis: tools, traits and prospects for evolutionary ecology

BACKGROUND: The model plant Arabidopsis thaliana (Arabidopsis) shows a wide range of genetic and trait variation among wild accessions. Because of its unparalleled biological and genomic resources, the potential of Arabidopsis for molecular genetic analysis of this natural variation has increased dramatically in recent years. SCOPE: Advanced genomics has accelerated molecular phylogenetic analysis and gene identification by quantitative trait loci (QTL) mapping and/or association mapping in Arabidopsis. In particular, QTL mapping utilizing natural accessions is now becoming a major strategy of gene isolation, offering an alternative to artificial mutant lines. Furthermore, the genomic information is used by researchers to uncover the signature of natural selection acting on the genes that contribute to phenotypic variation. The evolutionary significance of such genes has been evaluated in traits such as disease resistance and flowering time. However, although molecular hallmarks of selection have been found for the genes in question, a corresponding ecological scenario of adaptive evolution has been difficult to prove. Ecological strategies, including reciprocal transplant experiments and competition experiments, and utilizing near-isogenic lines of alleles of interest will be a powerful tool to measure the relative fitness of phenotypic and/or allelic variants. CONCLUSIONS: As the plant model organism, Arabidopsis provides a wealth of molecular background information for evolutionary genetics. Because genetic diversity between and within Arabidopsis populations is much higher than anticipated, combining this background information with ecological approaches might well establish Arabidopsis as a model organism for plant evolutionary ecology.     

玉米抗甘蔗花叶病毒基因的比较定位

收集了玉米抗甘蔗花叶病毒基因/QTL定位信息, 借助玉米遗传图谱IBM2 2005 Neighbors进行了整合。在国内外研究中, 累计报道81个抗病毒基因位点, 分布在玉米7条染色体上, 比较定位发现这些位点集中分布于第3和6染色体。采用元分析技术, 确定3个“一致性”抗病毒QTL, 其中1个位于第3染色体, 在遗传图谱IBM2 2005 Neighbors上覆盖的范围为6.44 cM; 2个位于第6染色体, 覆盖范围分别为6.16 cM和27.48 cM。借助比较基因组学策略, 在第3染色体“一致性”QTL区间内筛选出4个抗病位置候选基因。该研究结果为确定和克隆抗病主效基因提供了基础。     

Advances in cereal genomics and applications in crop breeding

Recent advances in cereal genomics have made it possible to analyse the architecture of cereal genomes and their expressed components, leading to an increase in our knowledge of the genes that are linked to key agronomically important traits. These studies have used molecular genetic mapping of quantitative trait loci (QTL) of several complex traits that are important in breeding. The identification and molecular cloning of genes underlying QTLs offers the possibility to examine the naturally occurring allelic variation for respective complex traits. Novel alleles, identified by functional genomics or haplotype analysis, can enrich the genetic basis of cultivated crops to improve productivity. Advances made in cereal genomics research in recent years thus offer the opportunities to enhance the prediction of phenotypes from genotypes for cereal breeding.     

Understanding quantitative genetic variation

Until recently, it was impracticable to identify the genes that are responsible for variation in continuous traits, or to directly observe the effects of their different alleles. Now, the abundance of genetic markers has made it possible to identify quantitative trait loci (QTL)--the regions of a chromosome or, ideally, individual sequence variants that are responsible for trait variation. What kind of QTL do we expect to find and what can our observations of QTL tell us about how organisms evolve? The key to understanding the evolutionary significance of QTL is to understand the nature of inherited variation, not in the immediate mechanistic sense of how genes influence phenotype, but, rather, to know what evolutionary forces maintain genetic variability.     

Determining causality and consequence of expression quantitative trait loci

Expression quantitative trait loci (eQTLs) are currently the most abundant and systematically-surveyed class of functional consequence for genetic variation. Recent genetic studies of gene expression have identified thousands of eQTLs in diverse tissue types for the majority of human genes. Application of this large eQTL catalog provides an important resource for understanding the molecular basis of common genetic diseases. However, only now has both the availability of individuals with full genomes and corresponding advances in functional genomics provided the opportunity to dissect eQTLs to identify causal regulatory variants. Resolving the properties of such causal regulatory variants is improving understanding of the molecular mechanisms that influence traits and guiding the development of new genome-scale approaches to variant interpretation. In this review, we provide an overview of current computational and experimental methods for identifying causal regulatory variants and predicting their phenotypic consequences.     

QTL mapping and the genetic basis of adaptation: recent developments

Quantitative trait loci (QTL) mapping has been used in a number of evolutionary studies to study the genetic basis of adaptation by mapping individual QTL that explain the differences between differentiated populations and also estimating their effects and interaction in the mapping population. This analysis can provide clues about the evolutionary history of populations and causes of the population differentiation. QTL mapping analysis methods and associated computer programs provide us tools for such an inference on the genetic basis and architecture of quantitative trait variation in a mapping population. Current methods have the capability to separate and localize multiple QTL and estimate their effects and interaction on a quantitative trait. More recent methods have been targeted to provide a comprehensive inference on the overall genetic architecture of multiple traits in a number of environments. This development is important for evolutionary studies on the genetic basis of multiple trait variation, genotype by environment interaction, host–parasite interaction, and also microarray gene expression QTL analysis.     

Identification of a QTL in Mus musculus for Alcohol Preference,Withdrawal, and Ap3m2 Expression Using Integrative Functional Genomics and Precision Genetics

Extensive genetic and genomic studies of the relationship between alcohol drinking preference and withdrawal severity have been performed using animal models. Data from multiple such publications and public data resources have been incorporated in the GeneWeaver database with >60,000 gene sets including 285 alcohol withdrawal and preference-related gene sets. Among these are evidence for positional candidates regulating these behaviors in overlapping quantitative trait loci (QTL) mapped in distinct mouse populations. Combinatorial integration of functional genomics experimental results revealed a single QTL positional candidate gene in one of the loci common to both preference and withdrawal. Functional validation studies in Ap3m2 knockout mice confirmed these relationships. Genetic validation involves confirming the existence of segregating polymorphisms that could account for the phenotypic effect. By exploiting recent advances in mouse genotyping, sequence, epigenetics, and phylogeny resources, we confirmed that Ap3m2 resides in an appropriately segregating genomic region. We have demonstrated genetic and alcohol-induced regulation of Ap3m2 expression. Although sequence analysis revealed no polymorphisms in the Ap3m2-coding region that could account for all phenotypic differences, there are several upstream SNPs that could. We have identified one of these to be an H3K4me3 site that exhibits strain differences in methylation. Thus, by making cross-species functional genomics readily computable we identified a common QTL candidate for two related bio-behavioral processes via functional evidence and demonstrate sufficiency of the genetic locus as a source of variation underlying two traits.     

The capture of heritable variation for genetic quality through social competition

In theory, females of many species choose mates based on traits that are indicators of male genetic quality. A fundamental question in evolutionary biology is why genetic variation for such indicator traits persists despite strong persistent selection imposed by female preference, which is known as the lek paradox. One potential solution to the lek paradox suggests that the traits that are targets of mate choice should evolve condition-dependent expression and that condition should have a large genetic variance. Condition is expected to exhibit high genetic variance because it is affected by a large number of physiological processes and hence, condition-dependent traits should 'capture' variation contributed by a large number of loci. We suggest that a potentially important cause of variation in condition is competition for limited resources. Here, we discuss a pair of models to analyze the evolutionary genetics of traits affected by success in social competition for resources. We show that competition can contribute to genetic variation of 'competition-dependent' traits that have fundamentally different evolutionary properties than other sources of variation. Competition dependence can make traits honest indicators of genetic quality by revealing the relative competitive ability of males, can provide a component of heritable variation that does not contribute to trait evolution, and can help maintain heritable variation under directional selection. Here we provide a general introduction to the concept of competition dependence and briefly introduce two models to demonstrate the potential evolutionary consequences of competition-dependent trait expression.