Interplay Between Polymorphic Short Tandem Repeats and Gene Expression Variation in Caenorhabditis elegans.

Short tandem repeats (STRs) have orders of magnitude higher mutation rates than single nucleotide variants (SNVs) and have been proposed to accelerate evolution in many organisms. However, only few studies have addressed the impact of STR variation on phenotypic variation at both the organismal and molecular levels. Potential driving forces underlying the high mutation rates of STRs also remain largely unknown. Here, we leverage the recently generated expression and STR variation data among wild Caenorhabditis elegans strains to conduct a genome-wide analysis of how STRs affect gene expression variation. We identify thousands of expression STRs (eSTRs) showing regulatory effects and demonstrate that they explain missing heritability beyond SNV-based expression quantitative trait loci. We illustrate specific regulatory mechanisms such as how eSTRs affect splicing sites and alternative splicing efficiency. We also show that differential expression of antioxidant genes and oxidative stresses might affect STR mutations systematically using both wild strains and mutation accumulation lines. Overall, we reveal the interplay between STRs and gene expression variation by providing novel insights into regulatory mechanisms of STRs and highlighting that oxidative stress could lead to higher STR mutation rates.

Mapping splice QTLs reveals distinct transcriptional and post-transcriptional regulatory variation of gene expression and identifies putative alternative splicing variation mediating complex trait variation in pigs.

BACKGROUND: Alternative splicing is an important step in gene expression, generating multiple isoforms for the same genes and greatly expanding the diversity of proteomes. Genetic variation in alternative splicing contributes to phenotypic diversity in natural populations. However, the genetic basis of variation in alternative splicing in livestock including pigs remains poorly understood. RESULTS: In this study, using a Duroc x Pietrain F2 pig population, we performed genome-wide analysis of alternative splicing estimated from stranded RNA-Seq data in skeletal muscle. We characterized the genetic architecture of alternative splicing and compared its basic features with those of overall gene expression. We detected a large number of novel alternative splicing events that were not previously annotated. We found heritability of quantitative alternative splicing scores (percent spliced in or PSI) to be lower than that of overall gene expression. In addition, heritabilities showed little correlation between alternative splicing and overall gene expression. We mapped expression QTLs (eQTLs) and splice QTLs (sQTLs) and found them to be largely non-overlapping. Finally, we integrated sQTL mapping with phenotype QTL (pQTL mapping to identify potential mediator of pQTL effect by alternative splicing. CONCLUSIONS: Our results suggest that regulatory variation exists at multiple levels and that their genetic controls are distinct, offering opportunities for genetic improvement.

Alterations in Growth Habit to Channel End-of-Season Perennial Reserves towards Increased Yield and Reduced Regrowth after Defoliation in Upland Cotton (Gossypium hirsutum L.).

Cotton (Gossypium spp.) is the primary source of natural textile fiber in the U.S. and a major crop in the Southeastern U.S. Despite constant efforts to increase the cotton fiber yield, the yield gain has stagnated. Therefore, we undertook a novel approach to improve the cotton fiber yield by altering its growth habit from perennial to annual. In this effort, we identified genotypes with high-expression alleles of five floral induction and meristem identity genes (FT, SOC1, FUL, LFY, and AP1) from an Upland cotton mini-core collection and crossed them in various combinations to develop cotton lines with annual growth habit, optimal flowering time, and enhanced productivity. To facilitate the characterization of genotypes with the desired combinations of stacked alleles, we identified molecular markers associated with the gene expression traits via genome-wide association analysis using a 63 K SNP Array. Over 14,500 SNPs showed polymorphism and were used for association analysis. A total of 396 markers showed associations with expression traits. Of these 396 markers, 159 were mapped to genes, 50 to untranslated regions, and 187 to random genomic regions. Biased genomic distribution of associated markers was observed where more trait-associated markers mapped to the cotton D sub-genome. Many quantitative trait loci coincided at specific genomic regions. This observation has implications as these traits could be bred together. The analysis also allowed the identification of candidate regulators of the expression patterns of these floral induction and meristem identity genes whose functions will be validated.

Repeat variants for the SbMATE transporter protect sorghum roots from aluminum toxicity by transcriptional interplay in cis and trans.

Acidic soils, where aluminum (Al) toxicity is a major agricultural constraint, are globally widespread and are prevalent in developing countries. In sorghum, the root citrate transporter SbMATE confers Al tolerance by protecting root apices from toxic Al3+, but can exhibit reduced expression when introgressed into different lines. We show that allele-specific SbMATE transactivation occurs and is caused by factors located away from SbMATE Using expression-QTL mapping and expression genome-wide association mapping, we establish that SbMATE transcription is controlled in a bipartite fashion, primarily in cis but also in trans Multiallelic promoter transactivation and ChIP analyses demonstrated that intermolecular effects on SbMATE expression arise from a WRKY and a zinc finger-DHHC transcription factor (TF) that bind to and trans-activate the SbMATE promoter. A haplotype analysis in sorghum RILs indicates that the TFs influence SbMATE expression and Al tolerance. Variation in SbMATE expression likely results from changes in tandemly repeated cis sequences flanking a transposable element (a miniature inverted repeat transposable element) insertion in the SbMATE promoter, which are recognized by the Al3+-responsive TFs. According to our model, repeat expansion in Al-tolerant genotypes increases TF recruitment and, hence, SbMATE expression, which is, in turn, lower in Al-sensitive genetic backgrounds as a result of lower TF expression and fewer binding sites. We thus show that even dominant cis regulation of an agronomically important gene can be subjected to precise intermolecular fine-tuning. These concerted cis/trans interactions, which allow the plant to sense and respond to environmental cues, such as Al3+ toxicity, can now be used to increase yields and food security on acidic soils.

Genome-wide expression quantitative trait locus studies facilitate isolation of causal genes controlling panicle structure.

The morphology of rice (Oryza sativa L.) panicles is an important determinant of grain yield, and elucidation of the genetic control of panicle structure is very important for fulfilling the demand for high yield in breeding programs. In a quantitative trait locus (QTL) study using 82 backcross inbred lines (BILs) derived from Koshihikari and Habataki, 68 QTLs for 25 panicle morphological traits were identified. Gene expression profiling from inflorescence meristems of BILs was obtained. A combination of phenotypic QTL (pQTL) and expression QTL (eQTL) analysis revealed co-localization between pQTLs and eQTLs, consistent with significant correlations between phenotypic traits and gene expression levels. By combining pQTL and eQTL data, two genes were identified as controlling panicle structure: OsMADS18 modulates the average length of the primary rachis and OsFTL1 has pleiotropic effects on the total number of secondary rachides, number of grains per panicle, plant height and the length of flag leaves. Phenotypes were confirmed in RNA interference knocked-down plants and overexpressor lines. The combination of pQTL and eQTL analysis could facilitate identification of genes involved in rice panicle formation.

Ensemble genomic analysis in human lung tissue identifies novel genes for chronic obstructive pulmonary disease.

BACKGROUND: Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) significantly associated with chronic obstructive pulmonary disease (COPD). However, many genetic variants show suggestive evidence for association but do not meet the strict threshold for genome-wide significance. Integrative analysis of multiple omics datasets has the potential to identify novel genes involved in disease pathogenesis by leveraging these variants in a functional, regulatory context. RESULTS: We performed expression quantitative trait locus (eQTL) analysis using genome-wide SNP genotyping and gene expression profiling of lung tissue samples from 86 COPD cases and 31 controls, testing for SNPs associated with gene expression levels. These results were integrated with a prior COPD GWAS using an ensemble statistical and network methods approach to identify relevant genes and observe them in the context of overall genetic control of gene expression to highlight co-regulated genes and disease pathways. We identified 250,312 unique SNPs and 4997 genes in the cis(local)-eQTL analysis (5% false discovery rate). The top gene from the integrative analysis was MAPT, a gene recently identified in an independent GWAS of lung function. The genes HNRNPAB and PCBP2 with RNA binding activity and the gene ACVR1B were identified in network communities with validated disease relevance. CONCLUSIONS: The integration of lung tissue gene expression with genome-wide SNP genotyping and subsequent intersection with prior GWAS and omics studies highlighted candidate genes within COPD loci and in communities harboring known COPD genes. This integration also identified novel disease genes in sub-threshold regions that would otherwise have been missed through GWAS.

Identification and mapping of expressed genes associated with the 2DL QTL for fusarium head blight resistance in the wheat line Wuhan 1.

BACKGROUND: Fusarium head blight (FHB) is a problem of great concern in small grain cereals, especially wheat. A quantitative trait locus (QTL) for FHB resistance (FHB_SFI) located on the long arm of chromosome 2D in the spring wheat genotype Wuhan 1 is a resistance locus which has potential to improve the FHB resistance of bread wheat since it confers effective resistance to wheat breeding lines. Recently, differentially expressed genes (DEG) have been identified by comparing near isogenic lines (NIL) carrying the susceptible and resistant alleles for the 2DL QTL, using RNA-Seq. In the present study, we aimed to identify candidate genes located within the genetic interval for the 2DL QTL for FHB resistance, as assessed by single floret inoculation (FHB_SFI), and possibly contributing to it. RESULTS: Combining previous and additional bioinformatics analyses, 26 DEG that were located on chromosome arm 2DL were selected for further characterization of their expression profile by RT-qPCR. Seven of those DEG showed a consistent differential expression profile between either three pairs of near isogenic lines or other genotypes carrying the R and S alleles for the 2DL QTL for FHB resistance. UN25696, which was identified in previous expression work using microarray was also confirmed to have a differential expression pattern. Those eight candidate genes were further characterized in 85 lines of a double haploid mapping population derived from the cross Wuhan 1/Nyubai, the population where the 2DL QTL was originally identified. The expression QTL for gene Traes_2DL_179570792 overlapped completely with the mapping interval for the 2DL QTL for FHB_SFI while the expression QTL for UN25696 mapped near the QTL, but did not overlap with it. None of the other genes had a significant eQTL on chromosome 2DL. Higher expression of Traes_2DL_179570792 and UN25696 was associated with the resistant allele at that locus. CONCLUSIONS: Of the 26 DEG from the 2DL chromosome further characterized in this study, only two had an expression QTL located in or near the interval for the 2DL QTL. Traes_2DL_179570792 is the first expression marker identified as associated with the 2DL QTL.

A splicing mutation in PHKG1 decreased its expression in skeletal muscle and caused PSE meat in Duroc × Luchuan crossbred pigs.

In recent years, Luchuan pigs in southern China have been used to produce high-quality meat by crossbreeding them with Duroc boars; however, PSE (pale, soft and exudative) meat was frequently reported in the crossbred pigs, and the underlying reason remains unknown. We excluded the possibility of the well-known causative mutations in RYR1 and PRKAG3 but identified the existence of an unfavorable allele of a splicing mutation (g.8283C>A) in PHKG1 in two Duroc boars and three Duroc × Luchuan crossbred pigs with PSE meat. An association analysis with 425 Duroc × Luchuan crossbred pigs revealed that the polymorphism of the splicing site of PHKG1 has significant association with the ultimate meat pH value (P = 0.035) and color score (P = 0.004). In addition, a strong cis-eQTL (expression QTL) signal for the expression of PHKG1 was identified in 189 Duroc × Luchuan crossbred pigs, and the splicing mutation was proven to be significantly associated with the expression of PHKG1 (P = 4.01e-11). Furthermore, RNA-sequencing data analysis confirmed that 131 CC homozygotes had only one transcript (T1), with FPKM (fragments per kilobase of transcript per million) of 35.40 ± 7.28, and 58 CA heterozygotes had two types of transcripts (T1 and T2), with FPKM of 19.63 ± 5.11 and 9.20 ± 2.39 respectively. Based on the association and eQTL analysis results, we concluded that PSE meat in Duroc × Luchuan crossbred pigs is caused by the splicing mutation in PHKG1. Our findings further support the effect of the causative mutation in PHKG1 on meat quality. The GEO accession number for the data is GSE124315.

Genome variants associated with RNA splicing variations in bovine are extensively shared between tissues.

BACKGROUND: Mammalian phenotypes are shaped by numerous genome variants, many of which may regulate gene transcription or RNA splicing. To identify variants with regulatory functions in cattle, an important economic and model species, we used sequence variants to map a type of expression quantitative trait loci (expression QTLs) that are associated with variations in the RNA splicing, i.e., sQTLs. To further the understanding of regulatory variants, sQTLs were compare with other two types of expression QTLs, 1) variants associated with variations in gene expression, i.e., geQTLs and 2) variants associated with variations in exon expression, i.e., eeQTLs, in different tissues. RESULTS: Using whole genome and RNA sequence data from four tissues of over 200 cattle, sQTLs identified using exon inclusion ratios were verified by matching their effects on adjacent intron excision ratios. sQTLs contained the highest percentage of variants that are within the intronic region of genes and contained the lowest percentage of variants that are within intergenic regions, compared to eeQTLs and geQTLs. Many geQTLs and sQTLs are also detected as eeQTLs. Many expression QTLs, including sQTLs, were significant in all four tissues and had a similar effect in each tissue. To verify such expression QTL sharing between tissues, variants surrounding (±1 Mb) the exon or gene were used to build local genomic relationship matrices (LGRM) and estimated genetic correlations between tissues. For many exons, the splicing and expression level was determined by the same cis additive genetic variance in different tissues. Thus, an effective but simple-to-implement meta-analysis combining information from three tissues is introduced to increase power to detect and validate sQTLs. sQTLs and eeQTLs together were more enriched for variants associated with cattle complex traits, compared to geQTLs. Several putative causal mutations were identified, including an sQTL at Chr6:87392580 within the 5th exon of kappa casein (CSN3) associated with milk production traits. CONCLUSIONS: Using novel analytical approaches, we report the first identification of numerous bovine sQTLs which are extensively shared between multiple tissue types. The significant overlaps between bovine sQTLs and complex traits QTL highlight the contribution of regulatory mutations to phenotypic variations.

Problematic alcohol use associates with sodium channel and clathrin linker 1 (SCLT1) in trauma-exposed populations.

Excessive alcohol use is extremely prevalent in the United States, particularly among trauma-exposed individuals. While several studies have examined genetic influences on alcohol use and related problems, this has not been studied in the context of trauma-exposed populations. We report results from a genome-wide association study of alcohol consumption and associated problems as measured by the alcohol use disorders identification test (AUDIT) in a trauma-exposed cohort. Results indicate a genome-wide significant association between total AUDIT score and rs1433375 [N = 1036, P = 2.61 × 10-8 (dominant model), P = 7.76 × 10-8 (additive model)], an intergenic single-nucleotide polymorphism located 323 kb upstream of the sodium channel and clathrin linker 1 (SCLT1) at 4q28. rs1433375 was also significant in a meta-analysis of two similar, but independent, cohorts (N = 1394, P = 0.0004), the Marine Resiliency Study and Systems Biology PTSD Biomarkers Consortium. Functional analysis indicated that rs1433375 was associated with SCLT1 gene expression and cortical-cerebellar functional connectivity measured via resting state functional magnetic resonance imaging. Together, findings suggest a role for sodium channel regulation and cerebellar functioning in alcohol use behavior. Identifying mechanisms underlying risk for problematic alcohol use in trauma-exposed populations is critical for future treatment and prevention efforts.

High-Dimensional Gaussian Graphical Regression Models with Covariates.

Though Gaussian graphical models have been widely used in many scientific fields, relatively limited progress has been made to link graph structures to external covariates. We propose a Gaussian graphical regression model, which regresses both the mean and the precision matrix of a Gaussian graphical model on covariates. In the context of co-expression quantitative trait locus (QTL) studies, our method can determine how genetic variants and clinical conditions modulate the subject-level network structures, and recover both the population-level and subject-level gene networks. Our framework encourages sparsity of covariate effects on both the mean and the precision matrix. In particular for the precision matrix, we stipulate simultaneous sparsity, i.e., group sparsity and element-wise sparsity, on effective covariates and their effects on network edges, respectively. We establish variable selection consistency first under the case with known mean parameters and then a more challenging case with unknown means depending on external covariates, and establish in both cases the ℓ2 convergence rates and the selection consistency of the estimated precision parameters. The utility and efficacy of our proposed method is demonstrated through simulation studies and an application to a co-expression QTL study with brain cancer patients.

Integrating Phenotypic and Gene Expression Linkage Mapping to Dissect Rust Resistance in Chickling Pea.

Rusts are among the most important foliar biotrophic fungal diseases in legumes. Lathyrus cicera crop can be severely damaged by Uromyces pisi, to which partial resistance has been identified. Nevertheless, the underlying genetic basis and molecular mechanisms of this resistance are poorly understood in L. cicera. To prioritise the causative variants controlling partial resistance to rust in L. cicera, a recombinant inbred line (RIL) population, segregating for response to this pathogen, was used to combine the detection of related phenotypic- and expression-quantitative trait loci (pQTLs and eQTLs, respectively). RILs' U. pisi disease severity (DS) was recorded in three independent screenings at seedling (growth chamber) and in one season of exploratory screening at adult plant stage (semi-controlled field conditions). A continuous DS range was observed in both conditions and used for pQTL mapping. Different pQTLs were identified under the growth chamber and semi-controlled field conditions, indicating a distinct genetic basis depending on the plant developmental stage and/or the environment. Additionally, the expression of nine genes related to U. pisi resistance in L. cicera was quantified for each RIL individual and used for eQTL mapping. One cis-eQTL and one trans-eQTL were identified controlling the expression variation of one gene related to rust resistance - a member of glycosyl hydrolase family 17. Integrating phenotyping, gene expression and linkage mapping allowed prioritising four candidate genes relevant for disease-resistance precision breeding involved in adaptation to biotic stress, cellular, and organelle homeostasis, and proteins directly involved in plant defence.

The genetics of gene expression in a Caenorhabditis elegans multiparental recombinant inbred line population.

Studying genetic variation of gene expression provides a powerful way to unravel the molecular components underlying complex traits. Expression quantitative trait locus (eQTL) studies have been performed in several different model species, yet most of these linkage studies have been based on the genetic segregation of two parental alleles. Recently, we developed a multiparental segregating population of 200 recombinant inbred lines (mpRILs) derived from four wild isolates (JU1511, JU1926, JU1931, and JU1941) in the nematode Caenorhabditis elegans. We used RNA-seq to investigate how multiple alleles affect gene expression in these mpRILs. We found 1789 genes differentially expressed between the parental lines. Transgression, expression beyond any of the parental lines in the mpRILs, was found for 7896 genes. For expression QTL mapping almost 9000 SNPs were available. By combining these SNPs and the RNA-seq profiles of the mpRILs, we detected almost 6800 eQTLs. Most trans-eQTLs (63%) co-locate in six newly identified trans-bands. The trans-eQTLs found in previous two-parental allele eQTL experiments and this study showed some overlap (17.5-46.8%), highlighting on the one hand that a large group of genes is affected by polymorphic regulators across populations and conditions, on the other hand, it shows that the mpRIL population allows identification of novel gene expression regulatory loci. Taken together, the analysis of our mpRIL population provides a more refined insight into C. elegans complex trait genetics and eQTLs in general, as well as a starting point to further test and develop advanced statistical models for detection of multiallelic eQTLs and systems genetics studying the genotype-phenotype relationship.

Dissecting the Genetic Basis of Variation in Drosophila Sleep Using a Multiparental QTL Mapping Resource.

There is considerable variation in sleep duration, timing and quality in human populations, and sleep dysregulation has been implicated as a risk factor for a range of health problems. Human sleep traits are known to be regulated by genetic factors, but also by an array of environmental and social factors. These uncontrolled, non-genetic effects complicate powerful identification of the loci contributing to sleep directly in humans. The model system, Drosophila melanogaster, exhibits a behavior that shows the hallmarks of mammalian sleep, and here we use a multitiered approach, encompassing high-resolution QTL mapping, expression QTL data, and functional validation with RNAi to investigate the genetic basis of sleep under highly controlled environmental conditions. We measured a battery of sleep phenotypes in >750 genotypes derived from a multiparental mapping panel and identified several, modest-effect QTL contributing to natural variation for sleep. Merging sleep QTL data with a large head transcriptome eQTL mapping dataset from the same population allowed us to refine the list of plausible candidate causative sleep loci. This set includes genes with previously characterized effects on sleep and circadian rhythms, in addition to novel candidates. Finally, we employed adult, nervous system-specific RNAi on the Dopa decarboxylase, dyschronic, and timeless genes, finding significant effects on sleep phenotypes for all three. The genes we resolve are strong candidates to harbor causative, regulatory variation contributing to sleep.

Comparison Between Expression Microarrays and RNA-Sequencing Using UKBEC Dataset Identified a trans-eQTL Associated with MPZ Gene in Substantia Nigra.

In recent years, the advantages of RNA-sequencing (RNA-Seq) have made it the platform of choice for measuring gene expression over traditional microarrays. However, RNA-Seq comes with bioinformatical challenges and higher computational costs. Therefore, this study set out to assess whether the increased depth of transcriptomic information facilitated by RNA-Seq is worth the increased computation over microarrays, specifically at three levels: absolute expression levels, differentially expressed genes identification, and expression QTL (eQTL) mapping in regions of the human brain. Using the United Kingdom Brain Expression Consortium (UKBEC) dataset, there is high agreement of gene expression levels measured by microarrays and RNA-seq when quantifying absolute expression levels and when identifying differentially expressed genes. These findings suggest that depending on the aims of a study, the relative ease of working with microarray data may outweigh the computational time and costs of RNA-Seq pipelines. On the other, there was low agreement when mapping eQTLs. However, a number of eQTLs associated with genes that play important roles in the brain were found in both platforms. For example, a trans-eQTL was mapped that is associated with the MPZ gene in the substantia nigra. These eQTLs that we have highlighted are extremely promising candidates that merit further investigation.

Contribution of unfixed transposable element insertions to human regulatory variation.

Thousands of unfixed transposable element (TE) insertions segregate in the human population, but little is known about their impact on genome function. Recently, a few studies associated unfixed TE insertions to mRNA levels of adjacent genes, but the biological significance of these associations, their replicability across cell types and the mechanisms by which they may regulate genes remain largely unknown. Here, we performed a TE-expression QTL analysis of 444 lymphoblastoid cell lines (LCL) and 289 induced pluripotent stem cells using a newly developed set of genotypes for 2743 polymorphic TE insertions. We identified 211 and 176 TE-eQTL acting in cis in each respective cell type. Approximately 18% were shared across cell types with strongly correlated effects. Furthermore, analysis of chromatin accessibility QTL in a subset of the LCL suggests that unfixed TEs often modulate the activity of enhancers and other distal regulatory DNA elements, which tend to lose accessibility when a TE inserts within them. We also document a case of an unfixed TE likely influencing gene expression at the post-transcriptional level. Our study points to broad and diverse cis-regulatory effects of unfixed TEs in the human population and underscores their plausible contribution to phenotypic variation. This article is part of a discussion meeting issue 'Crossroads between transposons and gene regulation'.

Cell Specificity of Human Regulatory Annotations and Their Genetic Effects on Gene Expression.

Epigenomic signatures from histone marks and transcription factor (TF)-binding sites have been used to annotate putative gene regulatory regions. However, a direct comparison of these diverse annotations is missing, and it is unclear how genetic variation within these annotations affects gene expression. Here, we compare five widely used annotations of active regulatory elements that represent high densities of one or more relevant epigenomic marks-"super" and "typical" (nonsuper) enhancers, stretch enhancers, high-occupancy target (HOT) regions, and broad domains-across the four matched human cell types for which they are available. We observe that stretch and super enhancers cover cell type-specific enhancer "chromatin states," whereas HOT regions and broad domains comprise more ubiquitous promoter states. Expression quantitative trait loci (eQTL) in stretch enhancers have significantly smaller effect sizes compared to those in HOT regions. Strikingly, chromatin accessibility QTL in stretch enhancers have significantly larger effect sizes compared to those in HOT regions. These observations suggest that stretch enhancers could harbor genetically primed chromatin to enable changes in TF binding, possibly to drive cell type-specific responses to environmental stimuli. Our results suggest that current eQTL studies are relatively underpowered or could lack the appropriate environmental context to detect genetic effects in the most cell type-specific "regulatory annotations," which likely contributes to infrequent colocalization of eQTL with genome-wide association study signals.

Physical linkage and mate preference generate linkage disequilibrium for behavioral isolation in two parapatric crickets.

Behavioral isolation is a potent barrier to gene flow and a source of striking diversity in the animal kingdom. However, it remains unclear if the linkage disequilibrium (LD) between sex-specific traits required for behavioral isolation results mostly from physical linkage between signal and preference loci or from directional mate preferences. Here, we test this in the field crickets Gryllus rubens and G. texensis. These closely related species diverged with gene flow and have strongly differentiated songs and preference functions for the mate calling song rhythm. We map quantitative trait loci for signal and preference traits (pQTL) as well as for gene expression associated with these traits (eQTL). We find strong, positive genetic covariance between song traits and between song and preference. Our results show that this is in part explained by incomplete physical linkage: although both linked pQTL and eQTL couple male and female traits, major effect loci for different traits were never on the same chromosome. We suggest that the finely tuned, highly divergent preference functions are likely an additional source of LD between male and female traits in this system. Furthermore, pleiotropy of gene expression presents an underappreciated mechanism to link sexually dimorphic phenotypes.

A multilocus association analysis method integrating phenotype and expression data reveals multiple novel associations to flowering time variation in wild-collected Arabidopsis thaliana.

The adaptation to a new habitat often results in a confounding between genomewide genotype and beneficial alleles. When the confounding is strong, or the allelic effects is weak, it is a major statistical challenge to detect the adaptive polymorphisms. We describe a novel approach to dissect polygenic traits in natural populations. First, candidate adaptive loci are identified by screening for loci directly associated with the adaptive trait or the expression of genes known to affect it. Then, a multilocus genetic architecture is inferred using a backward elimination association analysis across all candidate loci with an adaptive false discovery rate-based threshold. Effects of population stratification are controlled by accounting for genomic kinship in both steps of the analysis and also by simultaneously testing all candidate loci in the multilocus model. We illustrate the method by exploring the polygenic basis of an important adaptive trait, flowering time in Arabidopsis thaliana, using public data from the 1,001 genomes project. We revealed associations between 33 (29) loci and flowering time at 10 (16)°C in this collection of natural accessions, where standard genomewide association analysis methods detected five (3) loci. The 33 (29) loci explained approximately 55.1 (48.7)% of the total phenotypic variance of the respective traits. Our work illustrates how the genetic basis of highly polygenic adaptive traits in natural populations can be explored in much greater detail using new multilocus mapping approaches taking advantage of prior biological information, genome and transcriptome data.

Quantitative Trait Transcripts Mapping Coupled with Expression Quantitative Trait Loci Mapping Reveal the Molecular Network Regulating the Apetalous Characteristic in Brassica napus L.

The apetalous trait of rapeseed (Brassica napus, AACC, 2n = 38) is important for breeding an ideal high-yield rapeseed with superior klendusity to Sclerotinia sclerotiorum. Currently, the molecular mechanism underlying the apetalous trait of rapeseed is unclear. In this study, 14 petal regulators genes were chosen as target genes (TGs), and the expression patterns of the 14 TGs in the AH population, containing 189 recombinant inbred lines derived from a cross between apetalous "APL01" and normal "Holly," were analyzed in two environments using qRT-PCR. Phenotypic data of petalous degree (PDgr) in the AH population were obtained from the two environments. Both quantitative trait transcript (QTT)-association mapping and expression QTL (eQTL) analyses of TGs expression levels were performed to reveal regulatory relationships among TGs and PDgr. QTT mapping for PDgr determined that PLURIPETALA (PLP) was the major negative QTT associated with PDgr in both environments, suggesting that PLP negatively regulates the petal development of line "APL01." The QTT mapping of PLP expression levels showed that CHROMATIN-REMODELING PROTEIN 11 (CHR11) was positively associated with PLP expression, indicating that CHR11 acts as a positive regulator of PLP expression. Similarly, QTT mapping for the remaining TGs identified 38 QTTs, associated with 13 TGs, and 31 QTTs, associated with 10 TGs, respectively, in the first and second environments. Additionally, eQTL analyses of TG expression levels showed that 12 and 11 unconditional eQTLs were detected in the first and second environment, respectively. Based on the QTTs and unconditional eQTLs detected, we presented a hypothetical molecular regulatory network in which 14 petal regulators potentially regulated the apetalous trait in "APL01" through the CHR11-PLP pathway. PLP acts directly as the terminal signal integrator negatively regulating petal development in the CHR11-PLP pathway. These findings will aid in the understanding the molecular mechanism underlying the apetalous trait of rapeseed.