Optimum allocation of resources for QTL detection using a nested association mapping strategy in maize

In quantitative trait locus (QTL) mapping studies, it is mandatory that the available financial resources are spent in such a way that the power for detection of QTL is maximized. The objective of this study was to optimize for three different fixed budgets the power of QTL detection 1 − β* in recombinant inbred line (RIL) populations derived from a nested design by varying (1) the genetic complexity of the trait, (2) the costs for developing, genotyping, and phenotyping RILs, (3) the total number of RILs, and (4) the number of environments and replications per environment used for phenotyping. Our computer simulations were based on empirical data of 653 single nucleotide polymorphism markers of 26 diverse maize inbred lines which were selected on the basis of 100 simple sequence repeat markers out of a worldwide sample of 260 maize inbreds to capture the maximum genetic diversity. For the standard scenario of costs, the optimum number of test environments (Eopt) ranged across the examined total budgets from 7 to 19 in the scenarios with 25 QTL. In comparison, the Eopt values observed for the scenarios with 50 and 100 QTL were slightly higher. Our finding of differences in 1 − β* estimates between experiments with optimally and sub-optimally allocated resources illustrated the potential to improve the power for QTL detection without increasing the total resources necessary for a QTL mapping experiment. Furthermore, the results of our study indicated that also in studies using the latest genomics tools to dissect quantitative traits, it is required to evaluate the individuals of the mapping population in a high number of environments with a high number of replications per environment

Identification of Rice Transcription Factors Associated with Drought Tolerance Using the Ecotilling Method

The drought tolerance (DT) of plants is a complex quantitative trait. Under natural and artificial selection, drought tolerance represents the crop survival ability and production capacity under drought conditions (Luo, 2010). To understand the regulation mechanism of varied drought tolerance among rice genotypes, 95 diverse rice landraces or varieties were evaluated within a field screen facility based on the ‘line–source soil moisture gradient’, and their resistance varied from extremely resistant to sensitive. The method of Ecotype Targeting Induced Local Lesions in Genomes (Ecotilling) was used to analyze the diversity in the promoters of 24 transcription factor families. The bands separated by electrophoresis using Ecotilling were converted into molecular markers. STRUCTURE analysis revealed a value of K = 2, namely, the population with two subgroups (i.e., indica and japonica), which coincided very well with the UPGMA clusters (NTSYS-pc software) using distance-based analysis and InDel markers. Then the association analysis between the promoter diversity of these transcription factors and the DT index/level of each variety was performed. The results showed that three genes were associated with the DT index and that five genes were associated with the DT level. The sequences of these associated genes are complex and variable, especially at approximately 1000 bp upstream of the transcription initiation sites. The study illuminated that association analysis aimed at Ecotilling diversity of natural groups could facilitate the isolation of rice genes related to complex quantitative traits

Genetic Analysis of Central Carbon Metabolism Unveils an Amino Acid Substitution That Alters Maize NAD-Dependent Isocitrate Dehydrogenase Activity

Background: Central carbon metabolism (CCM) is a fundamental component of life. The participating genes and enzymes are thought to be structurally and functionally conserved across and within species. Association mapping utilizes a rich history of mutation and recombination to achieve high resolution mapping. Therefore, applying association mapping in maize (Zea mays ssp. mays), the most diverse model crop species, to study the genetics of CCM is a particularly attractive system. Methodology/Principal Findings: We used a maize diversity panel to test the CCM functional conservation. We found heritable variation in enzyme activity for every enzyme tested. One of these enzymes was the NAD-dependent isocitrate dehydrogenase (IDH, E.C. 1.1.1.41), in which we identified a novel amino-acid substitution in a phylogenetically conserved site. Using candidate gene association mapping, we identified that this non-synonymous polymorphism was associated with IDH activity variation. The proposed mechanism for the IDH activity variation includes additional components regulating protein level. With the comparison of sequences from maize and teosinte (Zea mays ssp. Parviglumis), the maize wild ancestor, we found that some CCM genes had also been targeted for selection during maize domestication. Conclusions/Significance: Our results demonstrate the efficacy of association mapping for dissecting natural variation in primary metabolic pathways. The considerable genetic diversity observed in maize CCM genes underlies heritable phenotypic variation in enzyme activities and can be useful to identify putative functional sites

Association and Linkage Analysis of Aluminum Tolerance Genes in Maize

Aluminum (Al) toxicity is a major worldwide constraint to crop productivity on acidic soils. Al becomes soluble at low pH, inhibiting root growth and severely reducing yields. Maize is an important staple food and commodity crop in acidic soil regions, especially in South America and Africa where these soils are very common. Al exclusion and intracellular tolerance have been suggested as two important mechanisms for Al tolerance in maize, but little is known about the underlying genetics. linkage populations with approximately 200 individuals each were used to study genetic variation in this complex trait. Al tolerance was measured as net root growth in nutrient solution under Al stress, which exhibited a wide range of variation between lines. Comparative and physiological genomics-based approaches were used to select 21 candidate genes for evaluation by association analysis.). These four candidate genes are high priority subjects for follow-up biochemical and physiological studies on the mechanisms of Al tolerance in maize. Immediately, elite haplotype-specific molecular markers can be developed for these four genes and used for efficient marker-assisted selection of superior alleles in Al tolerance maize breeding programs

An 11-bp Insertion in Zea mays fatb Reduces the Palmitic Acid Content of Fatty Acids in Maize Grain

The ratio of saturated to unsaturated fatty acids in maize kernels strongly impacts human and livestock health, but is a complex trait that is difficult to select based on phenotype. Map-based cloning of quantitative trait loci (QTL) is a powerful but time-consuming method for the dissection of complex traits. Here, we combine linkage and association analyses to fine map QTL-Pal9, a QTL influencing levels of palmitic acid, an important class of saturated fatty acid. QTL-Pal9 was mapped to a 90-kb region, in which we identified a candidate gene, Zea mays fatb (Zmfatb), which encodes acyl-ACP thioesterase. An 11-bp insertion in the last exon of Zmfatb decreases palmitic acid content and concentration, leading to an optimization of the ratio of saturated to unsaturated fatty acids while having no effect on total oil content. We used three-dimensional structure analysis to explain the functional mechanism of the ZmFATB protein and confirmed the proposed model in vitro and in vivo. We measured the genetic effect of the functional site in 15 different genetic backgrounds and found a maximum change of 4.57 mg/g palmitic acid content, which accounts for ∼20–60% of the variation in the ratio of saturated to unsaturated fatty acids. A PCR-based marker for QTL-Pal9 was developed for marker-assisted selection of nutritionally healthier maize lines. The method presented here provides a new, efficient way to clone QTL, and the cloned palmitic acid QTL sheds lights on the genetic mechanism of oil biosynthesis and targeted maize molecular breeding

Deletion of the Huntingtin Polyglutamine Stretch Enhances Neuronal Autophagy and Longevity in Mice

Expansion of a stretch of polyglutamine in huntingtin (htt), the protein product of the IT15 gene, causes Huntington's disease (HD). Previous investigations into the role of the polyglutamine stretch (polyQ) in htt function have suggested that its length may modulate a normal htt function involved in regulating energy homeostasis. Here we show that expression of full-length htt lacking its polyglutamine stretch (ΔQ-htt) in a knockin mouse model for HD (Hdh140Q/ΔQ), reduces significantly neuropil mutant htt aggregates, ameliorates motor/behavioral deficits, and extends lifespan in comparison to the HD model mice (Hdh140Q/+). The rescue of HD model phenotypes is accompanied by the normalization of lipofuscin levels in the brain and an increase in the steady-state levels of the mammalian autophagy marker microtubule-associate protein 1 light chain 3-II (LC3-II). We also find that ΔQ-htt expression in vitro increases autophagosome synthesis and stimulates the Atg5-dependent clearance of truncated N-terminal htt aggregates. ΔQ-htt's effect on autophagy most likely represents a gain-of-function, as overexpression of full-length wild-type htt in vitro does not increase autophagosome synthesis. Moreover, HdhΔQ/ΔQ mice live significantly longer than wild-type mice, suggesting that autophagy upregulation may be beneficial both in diseases caused by toxic intracellular aggregate-prone proteins and also as a lifespan extender in normal mammals

Differential Selection on Carotenoid Biosynthesis Genes as a Function of Gene Position in the Metabolic Pathway: A Study on the Carrot and Dicots

Background: Selection of genes involved in metabolic pathways could target them differently depending on the position of genes in the pathway and on their role in controlling metabolic fluxes. This hypothesis was tested in the carotenoid biosynthesis pathway using population genetics and phylogenetics. Methodology/Principal Findings: Evolutionary rates of seven genes distributed along the carotenoid biosynthesis pathway

The Complex Genetic Architecture of the Metabolome

Discovering links between the genotype of an organism and its metabolite levels can increase our understanding of metabolism, its controls, and the indirect effects of metabolism on other quantitative traits. Recent technological advances in both DNA sequencing and metabolite profiling allow the use of broad-spectrum, untargeted metabolite profiling to generate phenotypic data for genome-wide association studies that investigate quantitative genetic control of metabolism within species. We conducted a genome-wide association study of natural variation in plant metabolism using the results of untargeted metabolite analyses performed on a collection of wild Arabidopsis thaliana accessions. Testing 327 metabolites against >200,000 single nucleotide polymorphisms identified numerous genotype–metabolite associations distributed non-randomly within the genome. These clusters of genotype–metabolite associations (hotspots) included regions of the A. thaliana genome previously identified as subject to recent strong positive selection (selective sweeps) and regions showing trans-linkage to these putative sweeps, suggesting that these selective forces have impacted genome-wide control of A. thaliana metabolism. Comparing the metabolic variation detected within this collection of wild accessions to a laboratory-derived population of recombinant inbred lines (derived from two of the accessions used in this study) showed that the higher level of genetic variation present within the wild accessions did not correspond to higher variance in metabolic phenotypes, suggesting that evolutionary constraints limit metabolic variation. While a major goal of genome-wide association studies is to develop catalogues of intraspecific variation, the results of multiple independent experiments performed for this study showed that the genotype–metabolite associations identified are sensitive to environmental fluctuations. Thus, studies of intraspecific variation conducted via genome-wide association will require analyses of genotype by environment interaction. Interestingly, the network structure of metabolite linkages was also sensitive to environmental differences, suggesting that key aspects of network architecture are malleable

Behavioral genomics of honeybee foraging and nest defense

The honeybee has been the most important insect species for study of social behavior. The recently released draft genomic sequence for the bee will accelerate honeybee behavioral genetics. Although we lack sufficient tools to manipulate this genome easily, quantitative trait loci (QTLs) that influence natural variation in behavior have been identified and tested for their effects on correlated behavioral traits. We review what is known about the genetics and physiology of two behavioral traits in honeybees, foraging specialization (pollen versus nectar), and defensive behavior, and present evidence that map-based cloning of genes is more feasible in the bee than in other metazoans. We also present bioinformatic analyses of candidate genes within QTL confidence intervals (CIs). The high recombination rate of the bee made it possible to narrow the search to regions containing only 17–61 predicted peptides for each QTL, although CIs covered large genetic distances. Knowledge of correlated behavioral traits, comparative bioinformatics, and expression assays facilitated evaluation of candidate genes. An overrepresentation of genes involved in ovarian development and insulin-like signaling components within pollen foraging QTL regions suggests that an ancestral reproductive gene network was co-opted during the evolution of foraging specialization. The major QTL influencing defensive/aggressive behavior contains orthologs of genes involved in central nervous system activity and neurogenesis. Candidates at the other two defensive-behavior QTLs include modulators of sensory signaling (Am5HT(7) serotonin receptor, AmArr4 arrestin, and GABA-B-R1 receptor). These studies are the first step in linking natural variation in honeybee social behavior to the identification of underlying genes