Mapping and analysis of quantitative trait loci in experimental populations

Whole genome scanning and association mapping identified a significant association between growth and a SNP in the IFABP-a gene of the Asian seabass

BACKGROUND

Aquaculture is the quickest growing sector in agriculture. However, QTL for important traits have been only identified in a few aquaculture species. We conducted QTL mapping for growth traits in an Asian seabass F(2) family with 359 individuals using 123 microsatellites and 22 SNPs, and performed association mapping in four populations with 881 individuals.

RESULTS

Twelve and nine significant QTL, as well as 14 and 10 suggestive QTL were detected for growth traits at six and nine months post hatch, respectively. These QTL explained 0.9-12.0% of the phenotypic variance. For body weight, two QTL intervals at two stages were overlapped while the others were mapped onto different positions. The IFABP-a gene located in a significant QTL interval for growth on LG5 was cloned and characterized. A SNP in exon 3 of the gene was significantly associated with growth traits in different populations.

CONCLUSIONS

The results of QTL mapping for growth traits suggest that growth at different stages was controlled by some common QTL and some different QTL. Positional candidate genes and association mapping suggest that the IFABP-a is a strong candidate gene for growth. Our data supply a basis for fine mapping QTL, marker-assisted selection and further detailed analysis of the functions of the IFABP-a gene in fish growth.

A candidate gene based approach validates Md-PG1 as the main responsible for a QTL impacting fruit texture in apple (Malus x domestica Borkh)

BACKGROUND

Apple is a widely cultivated fruit crop for its quality properties and extended storability. Among the several quality factors, texture is the most important and appreciated, and within the apple variety panorama the cortex texture shows a broad range of variability. Anatomically these variations depend on degradation events occurring in both fruit primary cell wall and middle lamella. This physiological process is regulated by an enzymatic network generally encoded by large gene families, among which polygalacturonase is devoted to the depolymerization of pectin. In apple, Md-PG1, a key gene belonging to the polygalacturonase gene family, was mapped on chromosome 10 and co-localized within the statistical interval of a major hot spot QTL associated to several fruit texture sub-phenotypes.

RESULTS

In this work, a QTL corresponding to the position of Md-PG1 was validated and new functional alleles associated to the fruit texture properties in 77 apple cultivars were discovered. 38 SNPs genotyped by gene full length resequencing and 2 SSR markers ad hoc targeted in the gene metacontig were employed. Out of this SNP set, eleven were used to define three significant haplotypes statistically associated to several texture components. The impact of Md-PG1 in the fruit cell wall disassembly was further confirmed by the cortex structure electron microscope scanning in two apple varieties characterized by opposite texture performance, such as 'Golden Delicious' and 'Granny Smith'.

CONCLUSIONS

The results here presented step forward into the genetic dissection of fruit texture in apple. This new set of haplotypes, and microsatellite alleles, can represent a valuable toolbox for a more efficient parental selection as well as the identification of new apple accessions distinguished by superior fruit quality features.

Individualized risk for statin-induced myopathy: current knowledge, emerging challenges and potential solutions

Skeletal muscle toxicity is the primary adverse effect of statins. In this review, we summarize current knowledge regarding the genetic and nongenetic determinants of risk for statin induced myopathy. Many genetic factors were initially identified through candidate gene association studies limited to pharmacokinetic (PK) targets. Through genome-wide association studies, it has become clear that SLCO1B1 is among the strongest PK predictors of myopathy risk. Genome-wide association studies have also expanded our understanding of pharmacodynamic candidate genes, including RYR2. It is anticipated that deep resequencing efforts will define new loci with rare variants that also contribute, and sophisticated computational approaches will be needed to characterize gene-gene and gene-environment interactions. Beyond environment, race is a critical covariate, and its influence is only partly explained by geographic differences in the frequency of known pharmacodynamic and PK variants. As such, admixture analyses will be essential for a full understanding of statin-induced myopathy.

Dissecting tocopherols content in maize (Zea mays L.), using two segregating populations and high-density single nucleotide polymorphism markers

BACKGROUND

Tocopherols, which are vitamin E compounds, play an important role in maintaining human health. Compared with other staple foods, maize grains contain high level of tocopherols.

RESULTS

Two F(2) populations (K22/CI7 and K22/Dan340, referred to as POP-1 and POP-2, respectively), which share a common parent (K22), were developed and genotyped using a GoldenGate assay containing 1,536 single nucleotide polymorphism (SNP) markers. An integrated genetic linkage map was constructed using 619 SNP markers, spanning a total of 1649.03 cM of the maize genome with an average interval of 2.67 cM. Seventeen quantitative trait loci (QTLs) for all the traits were detected in the first map and 13 in the second. In these two maps, QTLs for different traits were localized to the same genomic regions and some were co-located with candidate genes in the tocopherol biosynthesis pathway. Single QTL was responsible for 3.03% to 52.75% of the phenotypic variation and the QTLs in sum explained 23.4% to 66.52% of the total phenotypic variation. A major QTL (qc5-1/qd5-1) affecting α-tocopherol (αT) was identified on chromosome 5 between the PZA03161.1 and PZA02068.1 in the POP-2. The QTL region was narrowed down from 18.7 Mb to 5.4 Mb by estimating the recombination using high-density markers of the QTL region. This allowed the identification of the candidate gene VTE4 which encodes γ-tocopherol methyltransferase, an enzyme that transforms γ-tocopherol (γT)to αT.

CONCLUSIONS

These results demonstrate that a few QTLs with major effects and several QTLs with medium to minor effects might contribute to the natural variation of tocopherols in maize grain. The high-density markers will help to fine map and identify the QTLs with major effects even in the preliminary segregating populations. Furthermore, this study provides a simple guide line for the breeders to improve traits that minimize the risk of malnutrition, especially in developing countries.

[Animal gene pyramiding in cross populations]

Gene pyramiding aims at producing individuals with one superior economic trait according to the optimal breeding scheme involving selection of favorable target alleles or linked markers after crossing basal populations and pyramiding them into a single individual. In consideration of animal traditional cross program along with the features of animal segregating population, four types of cross programs and two types of selection strategies for gene pyramiding are performed from practice perspective of view, two population cross for pyramiding two genes (denoted II), three populations cascading cross for pyramiding three genes (denoted III), four population symmetrical (denoted IV-S) and cascading cross for pyramiding four genes (denoted IV-C), and various schemes (denoted cross program-A-E) were designed for each cross program with different levels of initial favorable allele frequencies, basal population sizes, and trait heritabilities. The process of gene pyramiding for various schemes were simulated and compared based on the population hamming distance, average superior genotype frequencies, and average phenotypic values. By simulation, the results showed that larger base population size and higher initial favorite allele frequency resulted in higher efficiency of gene pyramiding. The order of parent crossing was shown to be the most important factor in cascading cross, but had no significant influence on the symmetric cross. The results also showed that genotypic selection strategy was superior to phenotypic selection in accelerating gene pyramiding. The method and corresponding software would be used to compare different cross schemes and selection strategies. Moreover, our study would help to build the optimal gene pyramiding simulation platform.

Gene-gene interaction and functional impact of polymorphisms on innate immune genes in controlling Plasmodium falciparum blood infection level

Genetic variations in toll-like receptors and cytokine genes of the innate immune pathways have been implicated in controlling parasite growth and the pathogenesis of Plasmodium falciparum mediated malaria. We previously published genetic association of TLR4 non-synonymous and TNF-α promoter polymorphisms with P.falciparum blood infection level and here we extend the study considerably by (i) investigating genetic dependence of parasite-load on interleukin-12B polymorphisms, (ii) reconstructing gene-gene interactions among candidate TLRs and cytokine loci, (iii) exploring genetic and functional impact of epistatic models and (iv) providing mechanistic insights into functionality of disease-associated regulatory polymorphisms. Our data revealed that carriage of AA (P = 0.0001) and AC (P = 0.01) genotypes of IL12B 3′UTR polymorphism was associated with a significant increase of mean log-parasitemia relative to rare homozygous genotype CC. Presence of IL12B+1188 polymorphism in five of six multifactor models reinforced its strong genetic impact on malaria phenotype. Elevation of genetic risk in two-component models compared to the corresponding single locus and reduction of IL12B (2.2 fold) and lymphotoxin-α (1.7 fold) expressions in patients'peripheral-blood-mononuclear-cells under TLR4Thr399Ile risk genotype background substantiated the role of Multifactor Dimensionality Reduction derived models. Marked reduction of promoter activity of TNF-α risk haplotype (C-C-G-G) compared to wild-type haplotype (T-C-G-G) with (84%) and without (78%) LPS stimulation and the loss of binding of transcription factors detected in-silico supported a causal role of TNF-1031. Significantly lower expression of IL12B+1188 AA (5 fold) and AC (9 fold) genotypes compared to CC and under-representation (P = 0.0048) of allele A in transcripts of patients' PBMCs suggested an Allele-Expression-Imbalance. Allele (A+1188C) dependent differential stability (2 fold) of IL12B-transcripts upon actinomycin-D treatment and observed structural modulation (P = 0.013) of RNA-ensemble were the plausible explanations for AEI. In conclusion, our data provides functional support to the hypothesis that de-regulated receptor-cytokine axis of innate immune pathway influences blood infection level in P. falciparum malaria.

Molecular mapping of QTLs for plant type and earliness traits in pigeonpea (Cajanus cajan L. Millsp.)

Background

Pigeonpea is an important grain legume of the semi-arid tropics and sub-tropical regions where it plays a crucial role in the food and nutritional security of the people. The average productivity of pigeonpea has remained very low and stagnant for over five decades due to lack of genomic information and intensive breeding efforts. Previous SSR-based linkage maps of pigeonpea used inter-specific crosses due to low inter-varietal polymorphism. Here our aim was to construct a high density intra-specific linkage map using genic-SNP markers for mapping of major quantitative trait loci (QTLs) for key agronomic traits, including plant height, number of primary and secondary branches, number of pods, days to flowering and days to maturity in pigeonpea.

Results

A population of 186 F_2:3 lines derived from an intra-specific cross between inbred lines ‘Pusa Dwarf’ and ‘HDM04-1’ was used to construct a dense molecular linkage map of 296 genic SNP and SSR markers covering a total adjusted map length of 1520.22 cM for the 11 chromosomes of the pigeonpea genome. This is the first dense intra-specific linkage map of pigeonpea with the highest genome length coverage. Phenotypic data from the F_2:3 families were used to identify thirteen QTLs for the six agronomic traits. The proportion of phenotypic variance explained by the individual QTLs ranged from 3.18% to 51.4%. Ten of these QTLs were clustered in just two genomic regions, indicating pleiotropic effects or close genetic linkage. In addition to the main effects, significant epistatic interaction effects were detected between the QTLs for number of pods per plant.

Conclusions

A large amount of information on transcript sequences, SSR markers and draft genome sequence is now available for pigeonpea. However, there is need to develop high density linkage maps and identify genes/QTLs for important agronomic traits for practical breeding applications. This is the first report on identification of QTLs for plant type and maturity traits in pigeonpea. The QTLs identified in this study provide a strong foundation for further validation and fine mapping for utilization in the pigeonpea improvement.

Rosette iron deficiency transcript and microRNA profiling reveals links between copper and iron homeostasis in Arabidopsis thaliana

Iron (Fe) is an essential plant micronutrient, and its deficiency limits plant growth and development on alkaline soils. Under Fe deficiency, plant responses include up-regulation of genes involved in Fe uptake from the soil. However, little is known about shoot responses to Fe deficiency. Using microarrays to probe gene expression in Kas-1 and Tsu-1 ecotypes of Arabidopsis thaliana, and comparison with existing Col-0 data, revealed conserved rosette gene expression responses to Fe deficiency. Fe-regulated genes included known metal homeostasis-related genes, and a number of genes of unknown function. Several genes responded to Fe deficiency in both roots and rosettes. Fe deficiency led to up-regulation of Cu,Zn superoxide dismutase (SOD) genes CSD1 and CSD2, and down-regulation of FeSOD genes FSD1 and FSD2. Eight microRNAs were found to respond to Fe deficiency. Three of these (miR397a, miR398a, and miR398b/c) are known to regulate transcripts of Cu-containing proteins, and were down-regulated by Fe deficiency, suggesting that they could be involved in plant adaptation to Fe limitation. Indeed, Fe deficiency led to accumulation of Cu in rosettes, prior to any detectable decrease in Fe concentration. ccs1 mutants that lack functional Cu,ZnSOD proteins were prone to greater oxidative stress under Fe deficiency, indicating that increased Cu concentration under Fe limitation has an important role in oxidative stress prevention. The present results show that Cu accumulation, microRNA regulation, and associated differential expression of Fe and CuSOD genes are coordinated responses to Fe limitation.

A multiparent advanced generation inter-cross population for genetic analysis in wheat

We present the first results from a novel multiparent advanced generation inter-cross (MAGIC) population derived from four elite wheat cultivars. The large size of this MAGIC population (1579 progeny), its diverse genetic composition and high levels of recombination all contribute to its value as a genetic resource. Applications of this resource include interrogation of the wheat genome and the analysis of gene-trait association in agronomically important wheat phenotypes. Here, we report the utilization of a MAGIC population for the first time for linkage map construction. We have constructed a linkage map with 1162 DArT, single nucleotide polymorphism and simple sequence repeat markers distributed across all 21 chromosomes. We benchmark this map against a high-density DArT consensus map created by integrating more than 100 biparental populations. The linkage map forms the basis for further exploration of the genetic architecture within the population, including characterization of linkage disequilibrium, founder contribution and inclusion of an alien introgression into the genetic map. Finally, we demonstrate the application of the resource for quantitative trait loci mapping using the complex traits plant height and hectolitre weight as a proof of principle.

Genetic architecture of migration-related traits in rainbow and steelhead trout, Oncorhynchus mykiss

Although migration plays a critical role in the evolution and diversification of species, relatively little is known of the genetic architecture underlying this life history in any species. Rainbow and steelhead trout (Oncorhynchus mykiss) naturally segregate for both resident and migratory life-history types, respectively, as do other members of the salmonid family of fishes. Using an experimental cross derived from wild resident rainbow and wild migratory steelhead trout from Southeast Alaska and high throughput restriction-site associated DNA (RAD) tag sequencing, we perform a quantitative trait locus (QTL) analysis to identify the number, position, and relative contribution of genetic effects on a suite of 27 physiological and morphological traits associated with the migratory life history in this species. In total, 37 QTL are localized to 19 unique QTL positions, explaining 4-13.63% of the variation for 19 of the 27 migration-related traits measured. Two chromosomal positions, one on chromosome Omy12 and the other on Omy14 each harbor 7 QTL for migration-related traits, suggesting that these regions could harbor master genetic controls for the migratory life-history tactic in this species. Another QTL region on Omy5 has been implicated in several studies of adaptive life histories within this species and could represent another important locus underlying the migratory life history. We also evaluate whether loci identified in this out-crossed QTL study colocalize to genomic positions previously identified for associations with migration-related traits in a doubled haploid mapping family.

Model selection for quantitative trait loci mapping in a full-sib family

Statistical methods for mapping quantitative trait loci (QTLs) in full-sib forest trees, in which the number of alleles and linkage phase can vary from locus to locus, are still not well established. Previous studies assumed that the QTL segregation pattern was fixed throughout the genome in a full-sib family, despite the fact that this pattern can vary among regions of the genome. In this paper, we propose a method for selecting the appropriate model for QTL mapping based on the segregation of different types of markers and QTLs in a full-sib family. The QTL segregation patterns were classified into three types: test cross (1:1 segregation), F₂ cross (1:2:1 segregation) and full cross (1:1:1:1 segregation). Akaike’s information criterion (AIC), the Bayesian information criterion (BIC) and the Laplace-empirical criterion (LEC) were used to select the most likely QTL segregation pattern. Simulations were used to evaluate the power of these criteria and the precision of parameter estimates. A Windows-based software was developed to run the selected QTL mapping method. A real example is presented to illustrate QTL mapping in forest trees based on an integrated linkage map with various segregation markers. The implications of this method for accurate QTL mapping in outbred species are discussed.

Bimodal expression level polymorphisms in Arabidopsis thaliana

Differences in gene expression are termed expression level polymorphisms (ELPs). Here, we propose a new ELP class, bimodal ELPs (bELPs), as a criterion to screen for genes that are responsible for natural phenotypic variation and/or that are targeted by balancing selection. bELP genes are characterized by two expression level modes. Genomic scans based on nucleotide sequences are not ideal for identifying genes targeted for selection. A critical concern is that several genes can be present in the selection-targeted regions identified by such scans. This situation indicates the importance of integrating genomic sequence data and other information, such as gene expression data. Comparative transcriptomics is useful for determining evolutionarily and ecologically important polymorphisms. In a genome-wide expression screen of 34 accessions, we identified 344 Arabidopsis thaliana genes exhibiting bELPs. Population genetic analysis revealed that bELP genes had high nucleotide diversities and long linkage disequilibriums. The highest nucleotide diversity (11-fold greater than the genomic mean) was found in the At1g23780 gene, which encodes a putative F-box protein. We observed a clear association between the expression mode and sequence type of the At1g23780 gene. Our results suggest that bELPs will be useful for the screening and functional analysis of genes responsible for phenotypic polymorphisms. Such a "multi-omics" approach has the potential to facilitate the scanning of genes relevant to balanced polymorphisms not only in A. thaliana, but also in other model and non-model organisms.

Optimal Design for Marker-assisted Gene Pyramiding in Cross Population

Marker-assisted gene pyramiding aims to produce individuals with superior economic traits according to the optimal breeding scheme which involves selecting a series of favorite target alleles after cross of base populations and pyramiding them into a single genotype. Inspired by the science of evolutionary computation, we used the metaphor of hill-climbing to model the dynamic behavior of gene pyramiding. In consideration of the traditional cross program of animals along with the features of animal segregating populations, four types of cross programs and two types of selection strategies for gene pyramiding are performed from a practical perspective. Two population cross for pyramiding two genes (denoted II), three population cascading cross for pyramiding three genes(denoted III), four population symmetry (denoted IIII-S) and cascading cross for pyramiding four genes (denoted IIII-C), and various schemes (denoted cross program-A–E) are designed for each cross program given different levels of initial favorite allele frequencies, base population sizes and trait heritabilities. The process of gene pyramiding breeding for various schemes are simulated and compared based on the population hamming distance, average superior genotype frequencies and average phenotypic values. By simulation, the results show that the larger base population size and the higher the initial favorite allele frequency the higher the efficiency of gene pyramiding. Parents cross order is shown to be the most important factor in a cascading cross, but has no significant influence on the symmetric cross. The results also show that genotypic selection strategy is superior to phenotypic selection in accelerating gene pyramiding. Moreover, the method and corresponding software was used to compare different cross schemes and selection strategies.

Wheat kernel dimensions: how do they contribute to kernel weight at an individual QTL level?

Kernel dimensions (KD) contribute greatly to thousand-kernel weight (TKW) in wheat. In the present study, quantitative trait loci (QTL) for TKW, kernel length (KL), kernel width (KW) and kernel diameter ratio (KDR) were detected by both conditional and unconditional QTL mapping methods. Two related F(8:9) recombinant inbred line (RIL) populations, comprising 485 and 229 lines, respectively, were used in this study, and the trait phenotypes were evaluated in four environments. Unconditional QTL mapping analysis detected 77 additive QTL for four traits in two populations. Of these, 24 QTL were verified in at least three trials, and five of them were major QTL, thus being of great value for marker assisted selection in breeding programmes. Conditional QTL mapping analysis, compared with unconditional QTL mapping analysis, resulted in reduction in the number of QTL for TKW due to the elimination of TKW variations caused by its conditional traits; based on which we first dissected genetic control system involved in the synthetic process between TKW and KD at an individual QTL level. Results indicated that, at the QTL level, KW had the strongest influence on TKW, followed by KL, and KDR had the lowest level contribution to TKW. In addition, the present study proved that it is not all-inclusive to determine genetic relationships of a pairwise QTL for two related/causal traits based on whether they were co-located. Thus, conditional QTL mapping method should be used to evaluate possible genetic relationships of two related/causal traits.

High segregation distortion in maize B73 x teosinte crosses

Two genetic linkage maps of cultivated maize inbred lines and teosinte species were constructed. One population comprised 81 F(2) individuals derived from a cross between maize inbred line B73 and Zea mays ssp parviglumis, while the second consisted of 63 backcross individuals from a cross of maize inbred line B73 with Z. mays ssp diploperennis. In the B73 x Z. mays ssp parviglumis F(2) population, 172 simple sequence repeat (SSR) markers were mapped to 10 chromosomes, which covered 2210.8 cM. In the B73 x Z. mays ssp diploperennis backcross population, 258 SSR markers were mapped to 10 chromosomes, covering 1357.7 cM. Comparison of the two maps revealed that the total map length of Z. mays ssp diploperennis covers 1357.7 cM, which is about 61.4% of that of Z. mays ssp parviglumis (2210.8 cM). Extensive segregation distortion regions were found on chromosomes 1, 2, 3, 5, 6, 7, and 10 in the B73 x Z. mays ssp parviglumis F(2) population and on chromosomes 1-5 and 8-10 in the B73 x Z. mays ssp parviglumis backcross population. Segregation distortion analysis confirmed that the segregation distortion ratio in the interspecific population B73 x Z. mays ssp diploperennis was higher than in B73 x Z. mays ssp parviglumis. We found that the recombination distances are highly variable in these genetic crosses between cultivated and wild species of maize.

Protease inhibitor (PI) mediated defense in leaves and flowers of pigeonpea (protease inhibitor mediated defense in pigeonpea)

More than 200 insect pests are found growing on pigeonpea. Insects lay eggs, attack and feed on leaves, flowers and developing pods. Plants have developed elaborate defenses against these insect pests. The present work evaluates protease inhibitor (PI) based defense of pigeonpea in leaves and flowers. PIs in the extracts of these tender tissues were detected by using gel X-ray film contact print method. Up to three PIs (PI-3, PI-4 and PI-5) were detected in these tissues as against nine (PI-1-PI-9) in mature seeds. PI-3 is the major component of these tissues. Mechanical wounding, insect chewing, fungal pathogenesis and application of salicylic acid induced PIs in pigeonpea in these tissues. Induction was found to be local as well as systemic but local response was stronger than systemic response. During both local and systemic induction, PI-3 appeared first. In spite of the presence and induction of PIs in these tender tissues and seeds farmers continue to suffer yield loses. This is due to the weak expression of PIs. However the ability of the plant to respond to external stimuli by producing defense proteins does not seem to be compromised. This study therefore indicates that PIs are components of both constitutive and inducible defense and provide a ground for designing stronger inducible defense (PIs or other insect toxin based) in pigeonpea.

QTL mapping for seedling traits in wheat grown under varying concentrations of N, P and K nutrients

Nutrient use efficiency (NuUE), comprising nutrient uptake and utilization efficiency, is regarded as one of the most important factors for wheat yield. In the present study, six morphological, nine nutrient content and nine nutrient utilization efficiency traits were investigated at the seedling stage using a set of recombinant inbred lines (RILs), under hydroponic culture of 12 treatments including single nutrient levels and two- and three-nutrient combinations treatments of N, P and K. For the 12 designed treatments, a total of 380 quantitative trait loci (QTLs) on 20 chromosomes for the 24 traits were detected. Of these, 87, 149 and 144 QTLs for morphological, nutrient content and nutrient utilization efficiency traits were found, respectively. Using the data of the average value (AV) across 12 treatments, 70 QTLs were detected for 23 traits. Most QTLs were located in new marker regions. Twenty-six important QTL clusters were mapped on 13 chromosomes, 1A, 1B, 1D, 2B, 3A, 3B, 4A, 4B, 5D, 6A, 6B, 7A and 7B. Of these, ten clusters involved 147 QTLs (38.7%) for investigated traits, indicating that these 10 loci were more important for the NuUE of N, P and K. We found evidence for cooperative uptake and utilization (CUU) of N, P and K in the early growth period at both the phenotype and QTL level. The correlation coefficients (r) between nutrient content and nutrient utilization efficiency traits for N, P and K were almost all significantly positive correlations. A total of 32 cooperative CUU loci (L1-L32) were found, which included 190 out of the 293 QTLs (64.8%) for the nutrient uptake and utilization efficiency traits, indicating that the CUU-QTLs were common for N, P and K. The CUU-QTLs in L3, L7, L16 and L28 were relatively stable. The CUU-QTLs may explain the CUU phenotype at the QTL level.

Genetic insight into yield-associated traits of wheat grown in multiple rain-fed environments

Background

Grain yield is a key economic driver of successful wheat production. Due to its complex nature, little is known regarding its genetic control. The goal of this study was to identify important quantitative trait loci (QTL) directly and indirectly affecting grain yield using doubled haploid lines derived from a cross between Hanxuan 10 and Lumai 14.

Methodology/Principal Findings

Ten yield-associated traits, including yield per plant (YP), number of spikes per plant (NSP), number of grains per spike (NGS), one-thousand grain weight (TGW), total number of spikelets per spike (TNSS), number of sterile spikelets per spike (NSSS), proportion of fertile spikelets per spike (PFSS), spike length (SL), density of spikelets per spike (DSS) and plant height (PH), were assessed across 14 (for YP) to 23 (for TGW) year × location × water regime environments in China. Then, the genetic effects were partitioned into additive main effects (a), epistatic main effects (aa) and their environment interaction effects (ae and aae) by using composite interval mapping in a mixed linear model.

Conclusions/Significance

Twelve (YP) to 33 (PH) QTLs were identified on all 21 chromosomes except 6D. QTLs were more frequently observed on chromosomes 1B, 2B, 2D, 5A and 6B, and were concentrated in a few regions on individual chromosomes, exemplified by three striking yield-related QTL clusters on chromosomes 2B, 1B and 4B that explained the correlations between YP and other traits. The additive main-effect QTLs contributed more phenotypic variation than the epistasis and environmental interaction. Consistent with agronomic analyses, a group of progeny derived by selecting TGW and NGS, with higher grain yield, had an increased frequency of QTL for high YP, NGS, TGW, TNSS, PFSS, SL, PH and fewer NSSS, when compared to low yielding progeny. This indicated that it is feasible by marker-assisted selection to facilitate wheat production.

QTL detection power of multi-parental RIL populations in Arabidopsis thaliana

A major goal of today's biology is to understand the genetic basis of quantitative traits. This can be achieved by statistical methods that evaluate the association between molecular marker variation and phenotypic variation in different types of mapping populations. The objective of this work was to evaluate the statistical power of quantitative trait loci (QTL) detection of various multi-parental mating designs, as well as to assess the reasons for the observed differences. Our study was based on an empirical data of 20 Arabidopsis thaliana accessions, which have been selected to capture the maximum genetic diversity. The examined mating designs differed strongly with respect to the statistical power to detect QTL. We observed the highest power to detect QTL for the diallel cross with random mating design. The results of our study suggested that performing sibling mating within subpopulations of joint-linkage mapping populations has the potential to considerably increase the power for QTL detection. Our results, however, revealed that using designs in which more than two parental alleles segregate in each subpopulation increases the power even more.

Flowering time in maize: linkage and epistasis at a major effect locus

In a previous study, we identified a candidate fragment length polymorphism associated with flowering time variation after seven generations of selection for flowering time, starting from the maize inbred line F252. Here, we characterized the candidate region and identified underlying polymorphisms. Then, we combined QTL mapping, association mapping, and developmental characterization to dissect the genetic mechanisms responsible for the phenotypic variation. The candidate region contained the Eukaryotic Initiation Factor (eIF-4A) and revealed a high level of sequence and structural variation beyond the 3'-UTR of eIF-4A, including several insertions of truncated transposable elements. Using a biallelic single-nucleotide polymorphism (SNP) (C/T) in the candidate region, we confirmed its association with flowering time variation in a panel of 317 maize inbred lines. However, while the T allele was correlated with late flowering time within the F252 genetic background, it was correlated with early flowering time in the association panel with pervasive interactions between allelic variation and the genetic background, pointing to underlying epistasis. We also detected pleiotropic effects of the candidate polymorphism on various traits including flowering time, plant height, and leaf number. Finally, we were able to break down the correlation between flowering time and leaf number in the progeny of a heterozygote (C/T) within the F252 background consistent with causal loci in linkage disequilibrium. We therefore propose that both a cluster of tightly linked genes and epistasis contribute to the phenotypic variation for flowering time.

Genetic mapping of quantitative phenotypic traits in Saccharomyces cerevisiae

Saccharomyces cerevisiae has become a favorite production organism in industrial biotechnology presenting new challenges to yeast engineers in terms of introducing advantageous traits such as stress tolerances. Exploring subspecies diversity of S. cerevisiae has identified strains that bear industrially relevant phenotypic traits. Provided that the genetic basis of such phenotypic traits can be identified inverse engineering allows the targeted modification of production strains. Most phenotypic traits of interest in S. cerevisiae strains are quantitative, meaning that they are controlled by multiple genetic loci referred to as quantitative trait loci (QTL). A straightforward approach to identify the genetic basis of quantitative traits is QTL mapping which aims at the allocation of the genetic determinants to regions in the genome. The application of high-density oligonucleotide arrays and whole-genome re-sequencing to detect genetic variations between strains has facilitated the detection of large numbers of molecular markers thus allowing high-resolution QTL mapping over the entire genome. This review focuses on the basic principle and state of the art of QTL mapping in S. cerevisiae. Furthermore we discuss several approaches developed during the last decade that allow down-scaling of the regions identified by QTL mapping to the gene level. We also emphasize the particular challenges of QTL mapping in nonlaboratory strains of S. cerevisiae.

Marker-assisted selection in plant breeding for salinity tolerance

Marker-assisted selection (MAS) is the process of using morphological, biochemical, or DNA markers as indirect selection criteria for selecting agriculturally important traits in crop breeding. This process is used to improve the effectiveness or efficiency of selection for the traits of interest in breeding programs. The significance of MAS as a tool for crop improvement has been extensively investigated in different crop -species and for different traits. The use of MAS for manipulating simple/qualitative traits is straightforward and has been well reported. However, MAS for the improvement of complex/polygenic traits, including plant tolerance/resistance to abiotic stresses, is more complicated, although its usefulness has been recognized. With the recent advances in marker technology, including high-throughput genotyping of plants, together with the development of nested association mapping populations, it is expected that the utility of MAS for breeding for stress tolerance traits will increase. In this chapter, we describe the basic procedure for using MAS in crop breeding for salt tolerance.

Flowering time variation in oilseed rape (Brassica napus L.) is associated with allelic variation in the FRIGIDA homologue BnaA.FRI.a

Oilseed rape (Brassica napus L.) is a major oil crop which is grown worldwide. Adaptation to different environments and regional climatic conditions involves variation in the regulation of flowering time. Winter types have a strong vernalization requirement whereas semi-winter and spring types have a low vernalization requirement or flower without exposure to cold, respectively. In Arabidopsis thaliana, FRIGIDA (FRI) is a key regulator which inhibits floral transition through activation of FLOWERING LOCUS C (FLC), a central repressor of flowering which controls vernalization requirement and response. Here, four FRI homologues in B. napus were identified by BAC library screening and PCR-based cloning. While all homologues are expressed, two genes were found to be differentially expressed in aerial plant organs. One of these, BnaA.FRI.a, was mapped to a region on chromosome A03 which co-localizes with a major flowering time quantitative trait locus in multiple environments in a doubled-haploid mapping population. Association analysis of BnaA.FRI.a revealed that six SNPs, including at least one at a putative functional site, and one haplotype block, respectively, are associated with flowering time variation in 248 accessions, with flowering times differing by 13-19 d between extreme haplotypes. The results from both linkage analysis and association mapping indicate that BnaA.FRI.a is a major determinant of flowering time in oilseed rape, and suggest further that this gene also contributes to the differentiation between growth types. The putative functional polymorphisms identified here may facilitate adaptation of this crop to specific environments through marker-assisted breeding.

Exploiting natural variation to identify insect-resistance genes

Herbivorous insects are widespread and often serious constraints to crop production. The use of insect-resistant crops is a very effective way to control insect pests in agriculture, and the development of such crops can be greatly enhanced by knowledge on plant resistance mechanisms and the genes involved. Plants have evolved diverse ways to cope with insect attack that has resulted in natural variation for resistance towards herbivorous insects. Studying the molecular genetics and transcriptional background of this variation has facilitated the identification of resistance genes and processes that lead to resistance against insects. With the development of new technologies, molecular studies are not restricted to model plants anymore. This review addresses the need to exploit natural variation in resistance towards insects to increase our knowledge on resistance mechanisms and the genes involved. We will discuss how this knowledge can be exploited in breeding programmes to provide sustainable crop protection against insect pests. Additionally, we discuss the current status of genetic research on insect-resistance genes. We conclude that insect-resistance mechanisms are still unclear at the molecular level and that exploiting natural variation with novel technologies will contribute greatly to the development of insect-resistant crop varieties.

Genomic analysis of QTLs and genes altering natural variation in stochastic noise

Quantitative genetic analysis has long been used to study how natural variation of genotype can influence an organism's phenotype. While most studies have focused on genetic determinants of phenotypic average, it is rapidly becoming understood that stochastic noise is genetically determined. However, it is not known how many traits display genetic control of stochastic noise nor how broadly these stochastic loci are distributed within the genome. Understanding these questions is critical to our understanding of quantitative traits and how they relate to the underlying causal loci, especially since stochastic noise may be directly influenced by underlying changes in the wiring of regulatory networks. We identified QTLs controlling natural variation in stochastic noise of glucosinolates, plant defense metabolites, as well as QTLs for stochastic noise of related transcripts. These loci included stochastic noise QTLs unique for either transcript or metabolite variation. Validation of these loci showed that genetic polymorphism within the regulatory network alters stochastic noise independent of effects on corresponding average levels. We examined this phenomenon more globally, using transcriptomic datasets, and found that the Arabidopsis transcriptome exhibits significant, heritable differences in stochastic noise. Further analysis allowed us to identify QTLs that control genomic stochastic noise. Some genomic QTL were in common with those altering average transcript abundance, while others were unique to stochastic noise. Using a single isogenic population, we confirmed that natural variation at ELF3 alters stochastic noise in the circadian clock and metabolism. Since polymorphisms controlling stochastic noise in genomic phenotypes exist within wild germplasm for naturally selected phenotypes, this suggests that analysis of Arabidopsis evolution should account for genetic control of stochastic variance and average phenotypes. It remains to be determined if natural genetic variation controlling stochasticity is equally distributed across the genomes of other multi-cellular eukaryotes.

Comprehensive genetic dissection of wood properties in a widely-grown tropical tree: Eucalyptus

Background

Eucalyptus is an important genus in industrial plantations throughout the world and is grown for use as timber, pulp, paper and charcoal. Several breeding programmes have been launched worldwide to concomitantly improve growth performance and wood properties (WPs). In this study, an interspecific cross between Eucalyptus urophylla and E. grandis was used to identify major genomic regions (Quantitative Trait Loci, QTL) controlling the variability of WPs.

Results

Linkage maps were generated for both parent species. A total of 117 QTLs were detected for a series of wood and end-use related traits, including chemical, technological, physical, mechanical and anatomical properties. The QTLs were mainly clustered into five linkage groups. In terms of distribution of QTL effects, our result agrees with the typical L-shape reported in most QTL studies, i.e. most WP QTLs had limited effects and only a few (13) had major effects (phenotypic variance explained > 15%). The co-locations of QTLs for different WPs as well as QTLs and candidate genes are discussed in terms of phenotypic correlations between traits, and of the function of the candidate genes. The major wood property QTL harbours a gene encoding a Cinnamoyl CoA reductase (CCR), a structural enzyme of the monolignol-specific biosynthesis pathway.

Conclusions

Given the number of traits analysed, this study provides a comprehensive understanding of the genetic architecture of wood properties in this Eucalyptus full-sib pedigree. At the dawn of Eucalyptus genome sequence, it will provide a framework to identify the nature of genes underlying these important quantitative traits.

Expression level of a gibberellin 20-oxidase gene is associated with multiple agronomic and quality traits in barley

The use of dwarfing genes has resulted in the most significant improvements in yield and adaptation in cereal crops. The allelic dwarfing gene sdw1/denso has been used throughout the world to develop commercial barley varieties. The sdw1 gene has never been used successfully for malting barley, but only for a large number of feed varieties. One of the gibberellin 20-oxidase genes (Hv20ox₂) was identified as the candidate gene for sdw1/denso. Semi-quantitative real-time RT-PCR revealed that Hv20ox₂ was expressed at different levels in various organs of barley. Transcriptional levels were reduced in leaf blade, sheath, stem and rachis tissue in the barley variety Baudin with the denso gene. Subsequently, the relative expression levels of Hv20ox₂ were determined by quantitative real-time RT-PCR in a doubled haploid population and mapped as a quantitative trait. A single expression quantitative trait locus (eQTL) was identified and mapped to its structural gene region on chromosome 3H. The eQTL was co-located with QTLs for yield, height, development score, hectolitre weight and grain plumpness. The expression level of Hv20ox₂ was reduced fourfold in the denso mutant, but around 60-fold in the sdw1 mutant, compared to the control variety. The reduced expression level of Hv20ox₂ enhanced grain yield by increasing the number of effective tillers, but had negative effects on grain and malting quality. The sdw1 gene can be used only in feed barley due to its severe reduction of Hv20ox₂ expression. The gene expression marker for Hv20ox₂ can be used to distinguish different alleles of sdw1/denso.

Conditional QTL mapping for plant height with respect to the length of the spike and internode in two mapping populations of wheat

Plant height (PH) in wheat is a complex trait; its components include spike length (SL) and internode lengths. To precisely analyze the factors affecting PH, two F(8:9) recombinant inbred line (RIL) populations comprising 485 and 229 lines were generated. Crosses were performed between Weimai 8 and Jimai 20 (WJ) and between Weimai 8 and Yannong 19 (WY). Possible genetic relationships between PH and PH components (PHC) were evaluated at the quantitative trait locus (QTL) level. PH and PHC (including SL and internode lengths from the first to the fourth counted from the top, abbreviated as FIITL, SITL, TITL, and FOITL, respectively) were measured in four environments. Individual and the pooled values from four trials were used in the present analysis. A QTL for PH was mapped using data on PH and on PH conditioned by PHC using IciMapping V2.2. All 21 chromosomes in wheat were shown to harbor factors affecting PH in two populations, by both conditional and unconditional QTL mapping methods. At least 11 pairwise congruent QTL were identified in the two populations. In total, ten unconditional QTL and five conditional QTL that could be detected in the conditional analysis only have been verified in no less than three trials in WJ and WY. In addition, three QTL on the short arms of chromosomes 4B, 4D, and 7B were mapped to positions similar to those of the semi-dwarfing genes Rht-B1, Rht-D1 and Rht13, respectively. Conditional QTL mapping analysis in WJ and WY proved that, at the QTL level, SL contributed the least to PH, followed by FIITL; TITL had the strongest influence on PH, followed by SITL and FOITL. The results above indicated that the conditional QTL mapping method can be used to evaluate possible genetic relationships between PH and PHC, and it can efficiently and precisely reveal counteracting QTL, which will enhance the understanding of the genetic basis of PH in wheat. The combination of two related populations with a large/moderate population size made the results authentic and accurate.

Systems genetics analysis of mouse chondrocyte differentiation

One of the goals of systems genetics is the reconstruction of gene networks that underlie key processes in development and disease. To identify cartilage gene networks that play an important role in bone development, we used a systems genetics approach that integrated microarray gene expression profiles from cartilage and bone phenotypic data from two sets of recombinant inbred strains. Microarray profiles generated from isolated chondrocytes were used to generate weighted gene coexpression networks. This analysis resulted in the identification of subnetworks (modules) of coexpressed genes that then were examined for relationships with bone geometry and density. One module exhibited significant correlation with femur length (r = 0.416), anteroposterior diameter (r = 0.418), mediolateral diameter (r = 0.576), and bone mineral density (r = 0.475). Highly connected genes (n = 28) from this and other modules were tested in vitro using prechondrocyte ATDC5 cells and RNA interference. Five of the 28 genes were found to play a role in chondrocyte differentiation. Two of these, Hspd1 and Cdkn1a, were known previously to function in chondrocyte development, whereas the other three, Bhlhb9, Cugbp1, and Spcs3, are novel genes. Our integrative analysis provided a systems-level view of cartilage development and identified genes that may be involved in bone development.

Moving micronutrients from the soil to the seeds: genes and physiological processes from a biofortification perspective

The micronutrients iron (Fe), zinc (Zn), and copper (Cu) are essential for plants and the humans and animals that consume plants. Increasing the micronutrient density of staple crops, or biofortification, will greatly improve human nutrition on a global scale. This review discusses the processes and genes needed to translocate micronutrients through the plant to the developing seeds, and potential strategies for developing biofortified crops.

Association genetics of complex traits in plants

Association mapping is rapidly becoming the main method for dissecting the genetic architecture of complex traits in plants. Currently most association mapping studies in plants are preformed using sets of genes selected to be putative candidates for the trait of interest, but rapid developments in genomics will allow for genome-wide mapping in virtually any plant species in the near future. As the costs for genotyping are decreasing, the focus has shifted towards phenotyping. In plants, clonal replication and/or inbred lines allows for replicated phenotyping under many different environmental conditions. Reduced sequencing costs will increase the number of studies that use RNA sequencing data to perform expression quantitative trait locus (eQTL) mapping, which will increase our knowledge of how gene expression variation contributes to phenotypic variation. Current population sizes used in association mapping studies are modest in size and need to be greatly increased if mutations explaining less than a few per cent of the phenotypic variation are to be detected. Association mapping has started to yield insights into the genetic architecture of complex traits in plants, and future studies with greater genome coverage will help to elucidate how plants have managed to adapt to a wide variety of environmental conditions.

The genetic basis of divergent pigment patterns in juvenile threespine sticklebacks

Animal pigment patterns are important for a range of functions, including camouflage and communication. Repeating pigment patterns, such as stripes, bars and spots have been of particular interest to developmental and theoretical biologists, but the genetic basis of natural variation in such patterns is largely unexplored. In this study, we identify a difference in a periodic pigment pattern among juvenile threespine sticklebacks (Gasterosteus aculeatus) from different environments. Freshwater sticklebacks exhibit prominent vertical bars that visually break up the body shape, but sticklebacks from marine populations do not. We hypothesize that these distinct pigment patterns are tuned to provide crypsis in different habitats. This phenotypic difference is widespread and appears in most of the freshwater populations that we sampled. We used quantitative trait locus (QTL) mapping in freshwater-marine F2 hybrids to elucidate the genetic architecture underlying divergence in this pigmentation pattern. We identified two QTL that were significantly associated with variation in barring. Interestingly, these QTL were associated with two distinct aspects of the pigment pattern: melanophore number and overall pigment level. We compared the QTL locations with positions of known pigment candidate genes in the stickleback genome. We also identified two major QTL for juvenile body size, providing new insights into the genetic basis of juvenile growth rates in natural populations. In summary, although there is a growing literature describing simple genetic bases for adaptive coloration differences, this study emphasizes that pigment patterns can also possess a more complex genetic architecture.

Using stochastic causal trees to augment Bayesian networks for modeling eQTL datasets

Background

The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phenotypes. The immense potential offered by these data derives from the fact that genotypic variation is the sole source of perturbation and can therefore be used to reconcile changes in gene expression programs with the parental genotypes. To date, several methodologies have been developed for modeling eQTL data. These methods generally leverage genotypic data to resolve causal relationships among gene pairs implicated as associates in the expression data. In particular, leading studies have augmented Bayesian networks with genotypic data, providing a powerful framework for learning and modeling causal relationships. While these initial efforts have provided promising results, one major drawback associated with these methods is that they are generally limited to resolving causal orderings for transcripts most proximal to the genomic loci. In this manuscript, we present a probabilistic method capable of learning the causal relationships between transcripts at all levels in the network. We use the information provided by our method as a prior for Bayesian network structure learning, resulting in enhanced performance for gene network reconstruction.

Results

Using established protocols to synthesize eQTL networks and corresponding data, we show that our method achieves improved performance over existing leading methods. For the goal of gene network reconstruction, our method achieves improvements in recall ranging from 20% to 90% across a broad range of precision levels and for datasets of varying sample sizes. Additionally, we show that the learned networks can be utilized for expression quantitative trait loci mapping, resulting in upwards of 10-fold increases in recall over traditional univariate mapping.

Conclusions

Using the information from our method as a prior for Bayesian network structure learning yields large improvements in accuracy for the tasks of gene network reconstruction and expression quantitative trait loci mapping. In particular, our method is effective for establishing causal relationships between transcripts located both proximally and distally from genomic loci.

Quantitative genetic analysis suggests causal association between cuticular hydrocarbon composition and desiccation survival in Drosophila melanogaster

Survival to low relative humidity is a complex adaptation, and many repeated instances of evolution to desiccation have been observed among Drosophila populations and species. One general mechanism for desiccation resistance is Cuticular Hydrocarbon (CHC) melting point. We performed the first Quantitative Trait Locus (QTL) map of population level genetic variation in desiccation resistance in D. melanogaster. Using a panel of Recombinant Inbred Lines (RILs) derived from a single natural population, we mapped QTL in both sexes throughout the genome. We found that in both sexes, CHCs correlated strongly with desiccation resistance. At most desiccation resistance loci there was a significant association between CHCs and desiccation resistance of the sort predicted from clinal patterns of CHC variation and biochemical properties of lipids. This association was much stronger in females than males, perhaps because of greater overall abundance of CHCs in females, or due to correlations between CHCs used for waterproofing and sexual signalling in males. CHC evolution may be a common mechanism for desiccation resistance in D. melanogaster. It will be interesting to compare patterns of CHC variation and desiccation resistance in species which adapt to desiccation, and rainforest restricted species which cannot.

Effects of missing marker and segregation distortion on QTL mapping in F2 populations

Missing marker and segregation distortion are commonly encountered in actual quantitative trait locus (QTL) mapping populations. Our objective in this study was to investigate the impact of the two factors on QTL mapping through computer simulations. Results indicate that detection power decreases with increasing levels of missing markers, and the false discovery rate increases. Missing markers have greater effects on smaller effect QTL and smaller size populations. The effect of missing markers can be quantified by a population with a reduced size similar to the marker missing rate. As for segregation distortion, if the distorted marker is not closely linked with any QTL, it will not have significant impact on QTL mapping; otherwise, the impact of the distortion will depend on the degree of dominance of QTL, frequencies of the three marker types, the linkage distance between the distorted marker and QTL, and the mapping population size. Sometimes, the distortion can result in a higher genetic variance than that of non-distortion, and therefore benefits the detection of linked QTL. A formula of the ratio of genetic variance explained by QTL under distortion and non-distortion was given in this study, so as to easily determine whether the segregation distortion marker (SDM) increases or decreases the QTL detection power. The effect of SDM decreases rapidly as its linkage relationship with QTL becomes looser. In general, distorted markers will not have a great effect on the position and effect estimations of QTL, and their effects can be ignored in large-size mapping populations.

Epistasis: obstacle or advantage for mapping complex traits?

Identification of genetic loci in complex traits has focused largely on one-dimensional genome scans to search for associations between single markers and the phenotype. There is mounting evidence that locus interactions, or epistasis, are a crucial component of the genetic architecture of biologically relevant traits. However, epistasis is often viewed as a nuisance factor that reduces power for locus detection. Counter to expectations, recent work shows that fitting full models, instead of testing marker main effect and interaction components separately, in exhaustive multi-locus genome scans can have higher power to detect loci when epistasis is present than single-locus scans, and improvement that comes despite a much larger multiple testing alpha-adjustment in such searches. We demonstrate, both theoretically and via simulation, that the expected power to detect loci when fitting full models is often larger when these loci act epistatically than when they act additively. Additionally, we show that the power for single locus detection may be improved in cases of epistasis compared to the additive model. Our exploration of a two step model selection procedure shows that identifying the true model is difficult. However, this difficulty is certainly not exacerbated by the presence of epistasis, on the contrary, in some cases the presence of epistasis can aid in model selection. The impact of allele frequencies on both power and model selection is dramatic.

Relation among plant growth, carbohydrates and flowering time in the Arabidopsis Landsberg erecta x Kondara recombinant inbred line population

Arabidopsis thaliana natural variation was used to study plant performance viewed as the accumulation of photo-assimilates, their allocation and storage, in relation to other growth-related features and flowering-related traits. Quantitative trait locus (QTL) analysis using recombinant inbred lines derived from the cross between Landsberg erecta (originating from Poland) and Kondara (originating from Tajikistan) grown on hydroponics, revealed QTLs for the different aspects of plant growth-related traits, sugar and starch contents and flowering-related traits. Co-locations of QTLs for these different aspects were detected at different regions, mainly at the ER locus; the top of chromosomes 3, 4 and 5; and the bottom of chromosome 5. Increased plant growth was associated with early flowering and leaf transitory starch, and correlated negatively with the levels of soluble sugar at early phases of development. From the significant correlations and the co-locations of the QTLs for these aspects, we conclude that there is a complex relationship between plant growth-related traits, carbohydrate content and flowering-related traits.

Molecular basis of trait correlations

Trait correlations are common phenomena in biology. Plant breeders need to consider trait correlations to either improve correlated traits simultaneously or to reduce undesirable side effects when improving only one of the correlated traits. Pleiotropy or close linkage are the two major reasons for genetic trait correlations and are often confounded at the level of quantitative trait loci or genes. With the progress of genetic and genomic approaches, discrimination of intragenic linkage from true pleiotropy is increasingly possible. This will substantially impact breeding strategies and will be helpful to understand the nature of trait correlations.

COE: a general approach for efficient genome-wide two-locus epistasis test in disease association study

The availability of high-density single nucleotide polymorphisms (SNPs) data has made genome-wide association study computationally challenging. Two-locus epistasis (gene-gene interaction) detection has attracted great research interest as a promising method for genetic analysis of complex diseases. In this article, we propose a general approach, COE, for efficient large scale gene-gene interaction analysis, which supports a wide range of tests. In particular, we show that many commonly used statistics are convex functions. From the observed values of the events in two-locus association test, we can develop an upper bound of the test value. Such an upper bound only depends on single-locus test and the genotype of the SNP-pair. We thus group and index SNP-pairs by their genotypes. This indexing structure can benefit the computation of all convex statistics. Utilizing the upper bound and the indexing structure, we can prune most of the SNP-pairs without compromising the optimality of the result. Our approach is especially efficient for large permutation test. Extensive experiments demonstrate that our approach provides orders of magnitude performance improvement over the brute force approach.

Genes underlying quantitative variation in ecologically important traits: PIF4 (phytochrome interacting factor 4) is associated with variation in internode length, flowering time, and fruit set in Arabidopsis thaliana

Association studies utilize the action of recombination over numerous generations to identify loci that underlie quantitative traits. We use a candidate-gene association approach, segregation analyses and analyses of local linkage disequilibrium (LD) to evaluate the potentially causal effects of molecular variation at PIF4 (PHYTOCROME INTERACTING FACTOR 4) on ecologically important traits in Arabidopsis thaliana. A preliminary analysis of sequence diversity in 14 natural genotypes revealed one intermediate-frequency replacement polymorphism at PIF4. A sample of 161 natural accessions was genotyped at PIF4 and screened for average length of early internodes, inflorescence length, days to flowering and flowering interval (days between bolting and flowering) under high- and low-density environments to test for genotype-phenotype associations. PIF4 was associated with early internode lengths, while the PIF4x treatment interaction was associated with flowering interval in the panel of 161 accessions. Further, in a set of recombinant inbred lines that segregate for the PIF4 polymorphism, nucleotide substitutions at PIF4 co-segregated with early internode lengths, days to flowering and fruit set, suggesting that cryptic population structure in the association-mapping panel and attendant LD with a physically distant locus do not account for the observed association. Finally, in a panel of pseudochromosomes from 20 re-sequenced genotypes, LD appeared to decay rapidly in the immediate vicinity of PIF4, suggesting that flanking loci contribute little to the observed association. In sum, the results suggest that PIF4 causally affects early internode lengths on the primary inflorescence, potentially via effects on reproductive timing and that these traits in turn affect fitness.

Intricate environment-modulated genetic networks control isoflavone accumulation in soybean seeds

BACKGROUND

Soybean (Glycine max [L] Merr.) seed isoflavones have long been considered a desirable trait to target in selection programs for their contribution to human health and plant defense systems. However, attempts to modify seed isoflavone contents have not always produced the expected results because their genetic basis is polygenic and complex. Undoubtedly, the extreme variability that seed isoflavones display over environments has obscured our understanding of the genetics involved.

RESULTS

In this study, a mapping population of RILs with three replicates was analyzed in four different environments (two locations over two years). We found a total of thirty-five main-effect genomic regions and many epistatic interactions controlling genistein, daidzein, glycitein and total isoflavone accumulation in seeds. The use of distinct environments permitted detection of a great number of environment-modulated and minor-effect QTL. Our findings suggest that isoflavone seed concentration is controlled by a complex network of multiple minor-effect loci interconnected by a dense epistatic map of interactions. The magnitude and significance of the effects of many of the nodes and connections in the network varied depending on the environmental conditions. In an attempt to unravel the genetic architecture underlying the traits studied, we searched on a genome-wide scale for genomic regions homologous to the most important identified isoflavone biosynthetic genes. We identified putative candidate genes for several of the main-effect and epistatic QTL and for QTL reported by other groups.

CONCLUSIONS

To better understand the underlying genetics of isoflavone accumulation, we performed a large scale analysis to identify genomic regions associated with isoflavone concentrations. We not only identified a number of such regions, but also found that they can interact with one another and with the environment to form a complex adaptable network controlling seed isoflavone levels. We also found putative candidate genes in several regions and overall we advanced the knowledge of the genetics underlying isoflavone synthesis.

The support of meat value chains by genetic technologies

Ongoing meat and food industry consolidation has resulted in the creation of larger and more complex, vertically integrated and/or coordinated food production systems. These systems have also been focused on development of differentiated 'Value Chains' as a departure from the traditional commodity oriented 'Supply Chains'. The main goal of value chains is to achieve sustainable competitiveness through focusing resources on efficiently producing goods that offer superior consumer-recognized value. A closely-aligned value chain often contains vertically and horizontally linked players such as genetics and genetic improvement program(s), farmer(s), processor(s), distributor(s), and retailer(s). In this paper we postulate that the underlying foundation of the success of meat value chain accomplishments has been through substantial development of animal genetic technologies enabling sustainable production of animal protein-based consumer products of desirable quantity and quality. It is plausible to assume that further advancement in genomic selection and eventually proteomics will enable implementation of more complex genetic improvement programs leading to further development of differentiated meat value chains focused on ever changing consumer needs.

Functional genomics and genetical genomics approaches towards elucidating networks of genes affecting meat performance in pigs

The benefit of functional genomics is to identify key pathways and functional networks of genes and candidate genes underlying the genetic control of phenotypes. Genetical genomics, i.e. the integration of genetic analysis and expression phenotypes, has the potential to uncover regulatory networks controlling the coordinated expression of genes and to map variation on the level of DNA affecting the mRNA expression. Here we illustrate our own attempts to apply functional genomics and genetical genomics approaches in order to identify functional networks of genes relevant to traits related to meat performance. Expression data of 74 M longissimus dorsi samples obtained using Affymetrix GeneChips were correlated with drip loss and principal components (PCs) with high loadings of meat quality traits. Functional annotation analyses revealed that differences in water holding capacity, early pH decline and ultimate pH were related to the ubiquitin-proteasome system, mitochondrial metabolic pathways and muscle structural aspects. In particular, 1279 genes were correlated with drip loss (P <or= 0.001; q <or= 0.004). Negatively correlated transcripts were enriched in functional categories like extracellular matrix receptor interaction and Ca-signalling. Transcripts with a positive correlation represented oxidative phosphorylation, mitochondrial pathways and transporter activity. A linkage analysis revealed 897 expression QTL (eQTL) with 104 eQTL mapping in QTL regions for water holding capacity including 8 cis eQTL. The reduction of the multi-dimensional data sets of meat performance traits into lower dimensions of PC and the genetical genomics approach of eQTL analysis proved to be appropriate means to detect relevant biological pathways and to experimentally prioritize candidate genes.

An empirical method for establishing positional confidence intervals tailored for composite interval mapping of QTL

BACKGROUND

Improved genetic resolution and availability of sequenced genomes have made positional cloning of moderate-effect QTL realistic in several systems, emphasizing the need for precise and accurate derivation of positional confidence intervals (CIs) for QTL. Support interval (SI) methods based on the shape of the QTL likelihood curve have proven adequate for standard interval mapping, but have not been shown to be appropriate for use with composite interval mapping (CIM), which is one of the most commonly used QTL mapping methods.

RESULTS

Based on a non-parametric confidence interval (NPCI) method designed for use with the Haley-Knott regression method for mapping QTL, a CIM-specific method (CIM-NPCI) was developed to appropriately account for the selection of background markers during analysis of bootstrap-resampled data sets. Coverage probabilities and interval widths resulting from use of the NPCI, SI, and CIM-NPCI methods were compared in a series of simulations analyzed via CIM, wherein four genetic effects were simulated in chromosomal regions with distinct marker densities while heritability was fixed at 0.6 for a population of 200 isolines. CIM-NPCIs consistently capture the simulated QTL across these conditions while slightly narrower SIs and NPCIs fail at unacceptably high rates, especially in genomic regions where marker density is high, which is increasingly common for real studies. The effects of a known CIM bias toward locating QTL peaks at markers were also investigated for each marker density case. Evaluation of sub-simulations that varied according to the positions of simulated effects relative to the nearest markers showed that the CIM-NPCI method overcomes this bias, offering an explanation for the improved coverage probabilities when marker densities are high.

CONCLUSIONS

Extensive simulation studies herein demonstrate that the QTL confidence interval methods typically used to positionally evaluate CIM results can be dramatically improved by accounting for the procedural complexity of CIM via an empirical approach, CIM-NPCI. Confidence intervals are a critical measure of QTL utility, but have received inadequate treatment due to a perception that QTL mapping is not sufficiently precise for procedural improvements to matter. Technological advances will continue to challenge this assumption, creating even more need for the current improvement to be refined.