eQTL Hotspot Research Articles

Molecular mechanisms underpinning quantitative resistance to Phytophthora sojae in Glycine max using a systems genomics approach.

Expression of quantitative disease resistance in many host-pathogen systems is controlled by genes at multiple loci, each contributing a small effect to the overall response. We used a systems genomics approach to study the molecular underpinnings of quantitative disease resistance in the soybean-Phytophthora sojae pathosystem, incorporating expression quantitative trait loci (eQTL) mapping and gene co-expression network analysis to identify the genes putatively regulating transcriptional changes in response to inoculation. These findings were compared to previously mapped phenotypic (phQTL) to identify the molecular mechanisms contributing to the expression of this resistance. A subset of 93 recombinant inbred lines (RILs) from a Conrad × Sloan population were inoculated with P. sojae isolate 1.S.1.1 using the tray-test method; RNA was extracted, sequenced, and the normalized read counts were genetically mapped from tissue collected at the inoculation site 24h after inoculation from both mock and inoculated samples. In total, more than 100,000 eQTLs were mapped. There was a switch from predominantly cis-eQTLs in the mock treatment to an almost entirely nonoverlapping set of predominantly trans-eQTLs in the inoculated treatment, where greater than 100-fold more eQTLs were mapped relative to mock, indicating vast transcriptional reprogramming due to P. sojae infection occurred. The eQTLs were organized into 36 hotspots, with the four largest hotspots from the inoculated treatment corresponding to more than 70% of the eQTLs, each enriched for genes within plant-pathogen interaction pathways. Genetic regulation of trans-eQTLs in response to the pathogen was predicted to occur through transcription factors and signaling molecules involved in plant-pathogen interactions, plant hormone signal transduction, and MAPK pathways. Network analysis identified three co-expression modules that were correlated with susceptibility to P. sojae and associated with three eQTL hotspots. Among the eQTLs co-localized with phQTLs, two cis-eQTLs with putative functions in the regulation of root architecture or jasmonic acid, as well as the putative master regulators of an eQTL hotspot nearby a phQTL, represent candidates potentially underpinning the molecular control of these phQTLs for resistance.

A nuclear receptor HR96-related gene underlies large trans-driven differences in detoxification gene expression in a generalist herbivore

The role, magnitude, and molecular nature of trans-driven expression variation underlying the upregulation of detoxification genes in pesticide resistant arthropod populations has remained enigmatic. In this study, we performed expression quantitative trait locus (eQTL) mapping (n = 458) between a pesticide resistant and a susceptible strain of the generalist herbivore and crop pest Tetranychus urticae. We found that a single trans eQTL hotspot controlled large differences in the expression of a subset of genes in different detoxification gene families, as well as other genes associated with host plant use. As established by additional genetic approaches including RNAi gene knockdown, a duplicated gene with a nuclear hormone receptor HR96-related ligand-binding domain was identified as causal for the expression differences between strains. The presence of a large family of HR96-related genes in T. urticae may enable modular control of detoxification and host plant use genes, facilitating this species’ known and rapid evolution to diverse pesticides and host plants.

Expression quantitative trait loci mapping identified PtrXB38 as a key hub gene in adventitious root development in Populus.

Plant establishment requires the formation and development of an extensive root system with architecture modulated by complex genetic networks. Here, we report the identification of the PtrXB38 gene as an expression quantitative trait loci (eQTL) hotspot, mapped using 390 leaf and 444 xylem Populus trichocarpa transcriptomes. Among predicted targets of this trans-eQTL were genes involved in plant hormone responses and root development. Overexpression of PtrXB38 in Populus led to significant increases in callusing and formation of both stem-born roots and base-born adventitious roots. Omics studies revealed that genes and proteins controlling auxin transport and signaling were involved in PtrXB38-mediated adventitious root formation. Protein-protein interaction assays indicated that PtrXB38 interacts with components of endosomal sorting complexes required for transport machinery, implying that PtrXB38-regulated root development may be mediated by regulating endocytosis pathway. Taken together, this work identified a crucial root development regulator and sheds light on the discovery of other plant developmental regulators through combining eQTL mapping and omics approaches.

Comprehensive transcriptional variability analysis reveals gene networks regulating seed oil content of Brassica napus

BackgroundRegulation of gene expression plays an essential role in controlling the phenotypes of plants. Brassica napus (B. napus) is an important source for the vegetable oil in the world, and the seed oil content is an important trait of B. napus.ResultsWe perform a comprehensive analysis of the transcriptional variability in the seeds of B. napus at two developmental stages, 20 and 40 days after flowering (DAF). We detect 53,759 and 53,550 independent expression quantitative trait loci (eQTLs) for 79,605 and 76,713 expressed genes at 20 and 40 DAF, respectively. Among them, the local eQTLs are mapped to the adjacent genes more frequently. The adjacent gene pairs are regulated by local eQTLs with the same open chromatin state and show a stronger mode of expression piggybacking. Inter-subgenomic analysis indicates that there is a feedback regulation for the homoeologous gene pairs to maintain partial expression dosage. We also identify 141 eQTL hotspots and find that hotspot87-88 co-localizes with a QTL for the seed oil content. To further resolve the regulatory network of this eQTL hotspot, we construct the XGBoost model using 856 RNA-seq datasets and the Basenji model using 59 ATAC-seq datasets. Using these two models, we predict the mechanisms affecting the seed oil content regulated by hotspot87-88 and experimentally validate that the transcription factors, NAC13 and SCL31, positively regulate the seed oil content.ConclusionsWe comprehensively characterize the gene regulatory features in the seeds of B. napus and reveal the gene networks regulating the seed oil content of B. napus.

The role of transposon inverted repeats in balancing drought tolerance and yield-related traits in maize.

The genomic basis underlying the selection for environmental adaptation and yield-related traits in maize remains poorly understood. Here we carried out genome-wide profiling of the small RNA (sRNA) transcriptome (sRNAome) and transcriptome landscapes of a global maize diversity panel under dry and wet conditions and uncover dozens of environment-specific regulatory hotspots. Transgenic and molecular studies of Drought-Related Environment-specific Super eQTL Hotspot on chromosome 8 (DRESH8) and ZmMYBR38, a target of DRESH8-derived small interfering RNAs, revealed a transposable element-mediated inverted repeats (TE-IR)-derived sRNA- and gene-regulatory network that balances plant drought tolerance with yield-related traits. A genome-wide scan revealed that TE-IRs associate with drought response and yield-related traits that were positively selected and expanded during maize domestication. These results indicate that TE-IR-mediated posttranscriptional regulation is a key molecular mechanism underlying the tradeoff between crop environmental adaptation and yield-related traits, providing potential genomic targets for the breeding of crops with greater stress tolerance but uncompromised yield.

EQTLs play critical roles in regulating gene expression and identifying key regulators in rice.

The regulation of gene expression plays an essential role in both the phenotype and adaptation of plants. Transcriptome sequencing enables simultaneous identification of exonic variants and quantification of gene expression. Here, we sequenced the leaf transcriptomes of 287 rice accessions from around the world and obtained a total of 177 853 high-quality single nucleotide polymorphisms after filtering. Genome-wide association study identified 44 354 expression quantitative trait loci (eQTLs), which regulate the expression of 13 201 genes, as well as 17 local eQTL hotspots and 96 distant eQTL hotspots. Furthermore, a transcriptome-wide association study screened 21 candidate genes for starch content in the flag leaves at the heading stage. HS002 was identified as a significant distant eQTL hotspot with five downstream genes enriched for diterpene antitoxin synthesis. Co-expression analysis, eQTL analysis, and linkage mapping together demonstrated that bHLH026 acts as a key regulator to activate the expression of downstream genes. The transgenic assay revealed that bHLH026 is an important regulator of diterpenoid antitoxin synthesis and enhances the disease resistance of rice. These findings improve our knowledge of the regulatory mechanisms of gene expression variation and complex regulatory networks of the rice genome and will facilitate genetic improvement of cultivated rice varieties.

Network Analysis Prioritizes DEWAX and ICE1 as the Candidate Genes for Major eQTL Hotspots in Seed Germination of Arabidopsis thaliana

Seed germination is characterized by a constant change of gene expression across different time points. These changes are related to specific processes, which eventually determine the onset of seed germination. To get a better understanding on the regulation of gene expression during seed germination, we performed a quantitative trait locus mapping of gene expression (eQTL) at four important seed germination stages (primary dormant, after-ripened, six-hour after imbibition, and radicle protrusion stage) using Arabidopsis thaliana Bay x Sha recombinant inbred lines (RILs). The mapping displayed the distinctness of the eQTL landscape for each stage. We found several eQTL hotspots across stages associated with the regulation of expression of a large number of genes. Interestingly, an eQTL hotspot on chromosome five collocates with hotspots for phenotypic and metabolic QTL in the same population. Finally, we constructed a gene co-expression network to prioritize the regulatory genes for two major eQTL hotspots. The network analysis prioritizes transcription factors DEWAX and ICE1 as the most likely regulatory genes for the hotspot. Together, we have revealed that the genetic regulation of gene expression is dynamic along the course of seed germination.

Fully automated web-based tool for identifying regulatory hotspots

BackgroundRegulatory hotspots are genetic variations that may regulate the expression levels of many genes. It has been of great interest to find those hotspots utilizing expression quantitative trait locus (eQTL) analysis. However, it has been reported that many of the findings are spurious hotspots induced by various unknown confounding factors. Recently, methods utilizing complicated statistical models have been developed that successfully identify genuine hotspots. Next-generation Intersample Correlation Emended (NICE) is one of the methods that show high sensitivity and low false-discovery rate in finding regulatory hotspots. Even though the methods successfully find genuine hotspots, they have not been widely used due to their non-user-friendly interfaces and complex running processes. Furthermore, most of the methods are impractical due to their prohibitively high computational complexity.ResultsTo overcome the limitations of existing methods, we developed a fully automated web-based tool, referred to as NICER (NICE Renew), which is based on NICE program. First, we dramatically reduced running and installing burden of NICE. Second, we significantly reduced running time by incorporating multi-processing. Third, besides our web-based NICER, users can use NICER on Google Compute Engine and can readily install and run the NICER web service on their local computers. Finally, we provide different input formats and visualizations tools to show results. Utilizing a yeast dataset, we show that NICER can be successfully used in an eQTL analysis to identify many genuine regulatory hotspots, for which more than half of the hotspots were previously reported elsewhere.ConclusionsEven though many hotspot analysis tools have been proposed, they have not been widely used for many practical reasons. NICER is a fully-automated web-based solution for eQTL mapping and regulatory hotspots analysis. NICER provides a user-friendly interface and has made hotspot analysis more viable by reducing the running time significantly. We believe that NICER will become the method of choice for increasing power of eQTL hotspot analysis.

Mapping the Effects of Genetic Variation on Chromatin State and Gene Expression Reveals Loci That Control Ground State Pluripotency.

Mouse embryonic stem cells (mESCs) cultured in the presence of LIF occupy a ground state with highly active pluripotency-associated transcriptional and epigenetic circuitry. However, ground state pluripotency in some inbred strain backgrounds is unstable in the absence of ERK1/2 and GSK3 inhibition. Using an unbiased genetic approach, we dissect the basis of this divergent response to extracellular cues by profiling gene expression and chromatin accessibility in 170 genetically heterogeneous mESCs. We map thousands of loci affecting chromatin accessibility and/or transcript abundance, including 10 QTL hotspots where genetic variation at a single locus coordinates the regulation of genes throughout the genome. For one hotspot, we identify a single enhancer variant ∼10 kb upstream of Lifr associated with chromatin accessibility and mediating a cascade of molecular events affecting pluripotency. We validate causation through reciprocal allele swaps, demonstrating the functional consequences of noncoding variation in gene regulatory networks that stabilize pluripotent states invitro.

Combined GWAS and eQTL analysis uncovers a genetic regulatory network orchestrating the initiation of secondary cell wall development in cotton.

The cotton fibre serves as a valuable experimental system to study cell wall synthesis in plants, but our understanding of the genetic regulation of this process during fibre development remains limited. We performed a genome-wide association study (GWAS) and identified 28 genetic loci associated with fibre quality in allotetraploid cotton. To investigate the regulatory roles of these loci, we sequenced fibre transcriptomes of 251 cotton accessions and identified 15330 expression quantitative trait loci (eQTL). Analysis of local eQTL and GWAS data prioritised 13 likely causal genes for differential fibre quality in a transcriptome-wide association study (TWAS). Characterisation of distal eQTL revealed unequal genetic regulation patterns between two subgenomes, highlighted by an eQTL hotspot (Hot216) that established a genome-wide genetic network regulating the expression of 962 genes. The primary regulatory role of Hot216, and specifically the gene encoding a KIP-related protein, was found to be the transcriptional regulation of genes responsible for cell wall synthesis, which contributes to fibre length by modulating the developmental transition from rapid cell elongation to secondary cell wall synthesis. This study uncovered the genetic regulation of fibre-cell development and revealed the molecular basis of the temporal modulation of secondary cell wall synthesis during plant cell elongation.

Genome-wide expression quantitative trait locus analysis in a recombinant inbred line population for trait dissection in peanut.

SummaryThe transcriptome connects genome to the gene function and ultimate phenome in biology. So far, transcriptomic approach was not used in peanut for performing trait mapping in bi‐parental populations. In this research, we sequenced the whole transcriptome in immature seeds in a peanut recombinant inbred line (RIL) population and explored thoroughly the landscape of transcriptomic variations and its genetic basis. The comprehensive analysis identified total 49 691 genes in RIL population, of which 92 genes followed a paramutation‐like expression pattern. Expression quantitative trait locus (eQTL) analysis identified 1207 local eQTLs and 15 837 distant eQTLs contributing to the whole‐genome transcriptomic variation in peanut. There were 94 eQTL hot spot regions detected across the genome with the dominance of distant eQTL. By integrating transcriptomic profile and annotation analyses, we unveiled a putative candidate gene and developed a linked marker InDel02 underlying a major QTL responsible for purple testa colour in peanut. Our result provided a first understanding of genetic basis of whole‐genome transcriptomic variation in peanut and illustrates the potential of the transcriptome‐aid approach in dissecting important traits in non‐model plants.

Systems biology with high-throughput sequencing reveals genetic mechanisms underlying the metabolic syndrome in the Lyon hypertensive rat.

The metabolic syndrome (MetS) is a collection of co-occurring complex disorders including obesity, hypertension, dyslipidemia, and insulin resistance. The Lyon hypertensive and Lyon normotensive rats are models of MetS sensitivity and resistance, respectively. To identify genetic determinants and mechanisms underlying MetS, an F2 intercross between Lyon hypertensive and Lyon normotensive was comprehensively studied. Multidimensional data were obtained including genotypes of 1536 single-nucleotide polymorphisms, 23 physiological traits, and >150 billion nucleotides of RNA-seq reads from the livers of F2 intercross offspring and parental rats. Phenotypic and expression quantitative trait loci (eQTL) were mapped. Application of systems biology methods identified 17 candidate MetS genes. Several putative causal cis-eQTL were identified corresponding with phenotypic QTL loci. We found an eQTL hotspot on rat chromosome 17 that is causally associated with multiple MetS-related traits and found RGD1562963, a gene regulated in cis by this eQTL hotspot, as the most likely eQTL driver gene directly affected by genetic variation between Lyon hypertensive and Lyon normotensive rats. Our study sheds light on the intricate pathogenesis of MetS and demonstrates that systems biology with high-throughput sequencing is a powerful method to study the pathogenesis of complex genetic diseases.

Abstract 18436: Systems Biology Identifies a Gene Driving Expression of Metabolic Syndrome in Lyon Rats

The metabolic syndrome (MetS) is a collection of co-occurring complex disorders including obesity, hypertension, dyslipidemia, and insulin resistance. The Lyon Hypertensive (LH) and Lyon Normotensive (LN) rats are models of MetS sensitivity and resistance, respectively. To identify genetic loci influencing phenotypes underlying MetS, an F2 intercross between LH and LN was studied to identify physiological quantitative trait loci (pQTL) contributing to plasma lipid and leptin levels, blood pressure, and body weight/adiposity. We performed mRNA-seq in F2 rats to identify the loci regulating gene expression, or expression (e)QTL, followed by gene expression network analyses. Systems biology methods were applied to identify candidate MetS genes, including genes previously shown to be MetS-related. We found an eQTL hotspot on RNO17, which was also located within pQTLs for MetS-related traits. The genes regulated by this eQTL hotspot were mainly in two co-expression network modules (a mitochondria related module and a gene regulation related module) and causally affect many MetS-related traits. Multiple evidences strongly and consistently support RGD1562963, a gene regulated in cis by this eQTL hotspot as the eQTL driver gene directly affected by genetic variation between LH and LN rats. Our study sheds light on the intricate pathogenesis of MetS and that systems biology with high-throughput sequencing is a powerful method to study the etiology of complex multifactorial diseases.

Abstract 233: Isoproterenol-induced Cardiac Hypertrophy And Failure In Mice: Gene Network Modeling

Heart failure is highly heterogeneous and as a result, relatively few insights into the pathways and drivers of heart failure have been identified using system-wide methods such as genome-wide association studies (GWAS). We have developed a resource, the Hybrid Mouse Diversity Panel (HMDP) for high resolution GWAS and systems genetics in mice. Eight week old female mice from 93 unique inbred strains of the HMDP were given 20 μg/g/day of isoproterenol through an abdominally implanted Alzet micropump. Three weeks post-implantation, all mice were sacrificed, along with age-matched controls. The mice exhibited widely varying degrees of hypertrophy and heart functioning. A portion of the left ventricle was processed and arrayed on an Illumina Mouse Ref 8.0 platform. We used Maximal Information Component Analysis, a novel method of network construction which allows for non-linear relationships between genes as well as non-binary partitioning of genes into sub-networks to subdivide the expression data into a series of modules. In order to identify modules which may contribute to Isoproterenol-induced hypertrophy and failure, we examined the correlation of each module to clinically relevant cardiac traits traits such as organ weights and echocardiographic parameters. We identified several modules with strong correlations to multiple heart failure-related clinical traits, including one module of 41 genes which contained several genes of interest, including Lgals3, a diagnostic marker for heart failure. Utilizing eQTL hotspot analysis, we have identified a locus which is involved in the regulation of this module. A gene within this locus, Magi2, regulates the turnover of the β-adrenergic receptor and represents a likely candidate for the response to isoproterenol.

New aQTL SNPs for the CYP2D6 Identified by a Novel Mediation Analysis of Genome-Wide SNP Arrays, Gene Expression Arrays, and CYP2D6 Activity

Background. The genome-wide association studies (GWAS) have been successful during the last few years. A key challenge is that the interpretation of the results is not straightforward, especially for transacting SNPs. Integration of transcriptome data into GWAS may provide clues elucidating the mechanisms by which a genetic variant leads to a disease. Methods. Here, we developed a novel mediation analysis approach to identify new expression quantitative trait loci (eQTL) driving CYP2D6 activity by combining genotype, gene expression, and enzyme activity data. Results. 389,573 and 1,214,416 SNP-transcript-CYP2D6 activity trios are found strongly associated (P < 10−5, FDR = 16.6% and 11.7%) for two different genotype platforms, namely, Affymetrix and Illumina, respectively. The majority of eQTLs are trans-SNPs. A single polymorphism leads to widespread downstream changes in the expression of distant genes by affecting major regulators or transcription factors (TFs), which would be visible as an eQTL hotspot and can lead to large and consistent biological effects. Overlapped eQTL hotspots with the mediators lead to the discovery of 64 TFs. Conclusions. Our mediation analysis is a powerful approach in identifying the trans-QTL-phenotype associations. It improves our understanding of the functional genetic variations for the liver metabolism mechanisms.

Unraveling Inflammatory Responses using Systems Genetics and Gene-Environment Interactions in Macrophages

Many common diseases have an important inflammatory component mediated in part by macrophages. Here we used a systems genetics strategy to examine the role of common genetic variation in macrophage responses to inflammatory stimuli. We examined genome-wide transcript levels in macrophages from 92 strains of the Hybrid Mouse Diversity Panel. We exposed macrophages to control media, bacterial lipopolysaccharide (LPS), or oxidized phospholipids. We performed association mapping under each condition and identified several thousand expression quantitative trait loci (eQTL), gene-by-environment interactions, and eQTL "hot spots" that specifically control LPS responses. We used siRNA knockdown of candidate genes to validate an eQTL hot spot in chromosome 8 and identified the gene 2310061C15Rik as a regulator of inflammatory responses in macrophages. We have created a public database where the data presented here can be used as a resource for understanding many common inflammatory traits that are modeled in the mouse and for the dissection of regulatory relationships between genes.

Deciphering the molecular basis of wine yeast fermentation traits using a combined genetic and genomic approach.

The genetic basis of the phenotypic diversity of yeast is still poorly understood. Wine yeast strains have specific abilities to grow and ferment under stressful conditions compared with other strains, but the genetic basis underlying these traits is unknown. Understanding how sequence variation influences such phenotypes is a major challenge to address adaptation mechanisms of wine yeast. We aimed to identify the genetic basis of fermentation traits and gain insight into their relationships with variations in gene expression among yeast strains. We combined fermentation trait QTL mapping and expression profiling of fermenting cells in a segregating population from a cross between a wine yeast derivative and a laboratory strain. We report the identification of QTL for various fermentation traits (fermentation rates, nitrogen utilization, metabolites production) as well as expression QTL (eQTL). We found that many transcripts mapped to several eQTL hotspots and that two of them overlapped with QTL for fermentation traits. A QTL controlling the maximal fermentation rate and nitrogen utilization overlapping with an eQTL hotspot was dissected. We functionally demonstrated that an allele of the ABZ1 gene, localized in the hotspot and involved in p-aminobenzoate biosynthesis, controls the fermentation rate through modulation of nitrogen utilization. Our data suggest that the laboratory strain harbors a defective ABZ1 allele, which triggers strong metabolic and physiological alterations responsible for the generation of the eQTL hotspot. They also suggest that a number of gene expression differences result from some alleles that trigger major physiological disturbances.

Differential gene expression in nearly isogenic lines with QTL for partial resistance to Puccinia hordei in barley

BackgroundThe barley-Puccinia hordei (barley leaf rust) pathosystem is a model for investigating partial disease resistance in crop plants and genetic mapping of phenotypic resistance has identified several quantitative trait loci (QTL) for partial resistance. Reciprocal QTL-specific near-isogenic lines (QTL-NILs) have been developed that combine two QTL, Rphq2 and Rphq3, the largest effects detected in a recombinant-inbred-line (RIL) population derived from a cross between the super-susceptible line L94 and partially-resistant line Vada. The molecular mechanism underpinning partial resistance in these QTL-NILs is unknown.ResultsAn Agilent custom microarray consisting of 15,000 probes derived from barley consensus EST sequences was used to investigate genome-wide and QTL-specific differential expression of genes 18 hours post-inoculation (hpi) with Puccinia hordei. A total of 1,410 genes were identified as being significantly differentially expressed across the genome, of which 55 were accounted for by the genetic differences defined by QTL-NILs at Rphq2 and Rphq3. These genes were predominantly located at the QTL regions and are, therefore, positional candidates. One gene, encoding the transcriptional repressor Ethylene-Responsive Element Binding Factor 4 (HvERF4) was located outside the QTL at 71 cM on chromosome 1H, within a previously detected eQTL hotspot for defence response. The results indicate that Rphq2 or Rphq3 contains a trans-eQTL that modulates expression of HvERF4. We speculate that HvERF4 functions as an intermediate that conveys the response signal from a gene(s) contained within Rphq2 or Rphq3 to a host of down-stream defense responsive genes. Our results also reveal that barley lines with extreme or intermediate partial resistance phenotypes exhibit a profound similarity in their spectrum of Ph-responsive genes and that hormone-related signalling pathways are actively involved in response to Puccinia hordei.ConclusionsDifferential gene expression between QTL-NILs identifies genes predominantly located within the target region(s) providing both transcriptional and positional candidate genes for the QTL. Genetically mapping the differentially expressed genes relative to the QTL has the potential to discover trans-eQTL mediated regulatory relays initiated from genes within the QTL regions.

Integrative Analysis of Low- and High-Resolution eQTL

The study of expression quantitative trait loci (eQTL) is a powerful way of detecting transcriptional regulators at a genomic scale and for elucidating how natural genetic variation impacts gene expression. Power and genetic resolution are heavily affected by the study population: whereas recombinant inbred (RI) strains yield greater statistical power with low genetic resolution, using diverse inbred or outbred strains improves genetic resolution at the cost of lower power. In order to overcome the limitations of both individual approaches, we combine data from RI strains with genetically more diverse strains and analyze hippocampus eQTL data obtained from mouse RI strains (BXD) and from a panel of diverse inbred strains (Mouse Diversity Panel, MDP). We perform a systematic analysis of the consistency of eQTL independently obtained from these two populations and demonstrate that a significant fraction of eQTL can be replicated. Based on existing knowledge from pathway databases we assess different approaches for using the high-resolution MDP data for fine mapping BXD eQTL. Finally, we apply this framework to an eQTL hotspot on chromosome 1 (Qrr1), which has been implicated in a range of neurological traits. Here we present the first systematic examination of the consistency between eQTL obtained independently from the BXD and MDP populations. Our analysis of fine-mapping approaches is based on ‘real life’ data as opposed to simulated data and it allows us to propose a strategy for using MDP data to fine map BXD eQTL. Application of this framework to Qrr1 reveals that this eQTL hotspot is not caused by just one (or few) ‘master regulators’, but actually by a set of polymorphic genes specific to the central nervous system.

Replication and narrowing of gene expression quantitative trait loci using inbred mice

Gene expression quantitative trait locus (eQTL) mapping has become a powerful tool in systems biology. While many authors have made important discoveries using this approach, one persistent challenge in eQTL studies is the selection of loci and genes that should receive further biological investigation. In this study we compared eQTL generated from gene expression profiling in the livers of two panels of mouse strains: 41 BXD recombinant inbred and 36 Mouse Diversity Panel (MDP) strains. Cis-eQTL, loci in which the transcript and its maximum QTL are colocated, have been shown to be more reproducible than trans-eQTL, which are not colocated with the transcript. We observed that between 9.9 and 12.1% of cis-eQTL and between 2.0 and 12.6% of trans-eQTL replicated between the two panels depending on the degree of statistical stringency. Notably, a significant eQTL hotspot on distal chromosome 12 observed in the BXD panel was reproduced in the MDP. Furthermore, the shorter linkage disequilibrium in the MDP strains allowed us to considerably narrow the locus and limit the number of candidate genes to a cluster of Serpin genes, which code for extracellular proteases. We conclude that this strategy has some utility in increasing confidence and resolution in eQTL mapping studies; however, due to the high false-positive rate in the MDP, eQTL mapping in inbred strains is best carried out in combination with an eQTL linkage study.