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PubMed2026

Integrative TWAS and multi-omics analyses prioritize HSPE1 as a candidate risk gene for bipolar disorder with immune cell-specific regulatory evidence.

BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder associated with substantial disability. Although genome-wide association studies have identified multiple BD-associated loci, the underlying genes and mechanisms remain incompletely understood. METHODS: We integrated a European-ancestry BD genome-wide association dataset with cross-tissue and tissue-specific transcriptome-wide association studies (TWAS) and complementary gene-based analysis. Candidate genes were further evaluated using differential expression analysis, consensus clustering, immune infiltration analysis, machine learning, summary-data-based Mendelian randomization, Mendelian randomization using single-cell expression quantitative trait locus data, single-nucleus transcriptomics, phenome-wide association analysis, and virtual screening. RESULTS: The integrative analyses prioritized 37 candidate genes. Peripheral-blood differential-expression analysis identified 14 genes that remained significant after FDR correction, and their expression profiles separated BD samples into two expression-defined clusters. Machine-learning analysis selected UNC50, LMAN2L, LYG2, HSPE1, and KANSL3 for an exploratory classification nomogram. SMR associated genetically predicted higher HSPE1 expression with increased BD risk in two blood eQTL datasets. Cell-type-specific analyses indicated HSPE1-related associations in T-cell and natural killer cell subsets, while single-nucleus analysis descriptively showed higher HSPE1 expression in medial thalamic T cells from BD samples. PheWAS identified no genome-wide significant associations for HSPE1, whereas virtual screening identified candidate compounds with favorable predicted docking scores against the HSPE1 structure. CONCLUSION: This integrative multi-omics study identified HSPE1 as a candidate BD risk gene with immune-cell-related regulatory evidence, providing insight into BD pathogenesis and supporting functional validation.

Humans↗

PubMed2001

Confirmation and fine mapping of chromosomal regions influencing peak bone mass in mice.

Bone mineral density (BMD) is determined by both environmental influences and polygenic inheritance. The extreme difficulty of dissecting out environmental factors from genetic ones in humans has motivated the investigation of animal models. Previously, we used quantitative trait locus (QTL) analysis to examine peak BMD in 24 recombinant inbred (RI) mouse strains, derived from a cross between C57BL/6 (B6) and DBA/2 (D2) progenitors (RI-BXD). The distribution of BMD values among these strains indicated strong genetic influences and a number of chromosomal sites linked to BMD were identified provisionally. Using three additional independent mapping populations derived from the same progenitors, we have confirmed loci on chromosomes 1, 2, and 4, and 11 that contain genes that influence peak BMD. Using a novel fine-mapping approach (RI segregation testing [RIST]), we have substantially narrowed two of the BMD-related chromosomal regions and in the process eliminated a number of candidate genes. The homologous regions in the human genome for each of these murine QTLs have been identified in recent human genetic studies. In light of this, we believe that findings in mice should aid in the identification of specific candidate genes for study in humans.

Animals↗

PubMed2001

Testing life-history pleiotropy in Caenorhabditis elegans.

Much life-history theory assumes that alleles segregating in natural populations pleiotropically affect life-history traits. This assumption, while plausible, has rarely been tested directly. Here we investigate the genetic relationship between two traits often suggested to be connected by pleiotropy: maternal body size and fertility. We carry out a quantitative trait locus (QTL) analysis on two isolates of the free-living nematode Caenorhabditis elegans, and identify two body size and three fertility QTLs. We find that one of the fertility QTLs colocalizes with the two body size QTLs on Chromosome IV. Further analysis, however, shows that these QTLs are genetically separable. Thus, none of the five body size or fertility QTLs identified here shows detectable pleiotropy for the assayed traits. The evolutionary origin of these QTLs, possible candidate loci, and the significance for life-history evolution are discussed.

Animals↗

PubMed2006

A variable cluster of ethylene response factor-like genes regulates metabolic and developmental acclimation responses to submergence in rice.

Submergence-1 (Sub1), a major quantitative trait locus affecting tolerance to complete submergence in lowland rice (Oryza sativa), contains two or three ethylene response factor (ERF)-like genes whose transcripts are regulated by submergence. In the submergence-intolerant japonica cultivar M202, this locus encodes two ERF genes, Sub1B and Sub1C. In the tolerant near-isogenic line containing the Sub1 locus from the indica FR13A, M202(Sub1), the locus additionally encodes the ERF gene Sub1A. During submergence, the tolerant M202(Sub1) displayed restrained leaf and internode elongation, chlorophyll degradation, and carbohydrate consumption, whereas the enzymatic activities of pyruvate decarboxylase and alcohol dehydrogenase were increased significantly compared with the intolerant M202. Transcript levels of genes associated with carbohydrate consumption, ethanolic fermentation, and cell expansion were distinctly regulated in the two lines. Sub1A and Sub1C transcript levels were shown to be upregulated by submergence and ethylene, with the Sub1C allele in M202 also upregulated by treatment with gibberellic acid (GA). These findings demonstrate that the Sub1 region haplotype determines ethylene- and GA-mediated metabolic and developmental responses to submergence through differential expression of Sub1A and Sub1C. Submergence tolerance in lowland rice is conferred by a specific allele variant of Sub1A that dampens ethylene production and GA responsiveness, causing quiescence in growth that correlates with the capacity for regrowth upon desubmergence.

Acclimatization↗

PubMed1998

Identification of a genetic region in mice that specifies sensitivity to propofol.

BACKGROUND: Long-sleep (LS) and short-sleep (SS) mice, initially selected for differential sensitivity to ethanol, also exhibit differential sensitivity to propofol. By interbreeding LS and SS mice to obtain progeny whose chromosomes are a patchwork of the LS and SS chromosomes, the authors determined whether differential propofol sensitivity cosegregates with any particular chromosomal region(s). Such cosegregation is the essence of genetic linkage mapping and a first step toward isolating a gene that can modulate propofol sensitivity in mammals. A gene underlying a quantitative trait such as anesthetic sensitivity is commonly called a quantitative trait locus (QTL). METHODS: The propofol dose was 20 mg/kg injected retroorbitally. Sensitivity was measured as the duration of the loss of righting reflex (LORR). The LORR and propofol brain levels at awakening were determined for 24 LSXSS recombinant-inbred (RI) strains, derived by intercrossing LS and SS for two generations followed by >20 generations of inbreeding. A genetic linkage between LORR and an albino mutation on chromosome 7 was investigated further using 164 second-generation progeny (F2s) from intercrossing inbred LS and inbred SS mice, similar to the LSXSS RIs except F2s are not inbred. The linkage between propofol sensitivity and the albino locus also was investigated using additional genetic markers on chromosome 7. Statistical significance was assessed by interval mapping using a regression method for RIs and Mapmaker/QTL (Whitehead Institute, Cambridge, MA) for F2s. RESULTS: Genetic mapping in the LSXSS RIs revealed a QTL tightly linked to the Tyr (albino) locus that accounts for nearly all of the genetic difference in propofol sensitivity between LS and SS mice. Analysis of propofol brain levels at awakening indicated that this QTL results from differential neurosensitivity. Mapping in F2s confirmed the genetic linkage to Tyr. Mice (ISS c/c x C57BL/6 c2j/C) that differed only by an albino mutation at Tyr were not differentially sensitive to propofol. CONCLUSIONS: A single QTL, called Lorp1, underlies most of the genetic difference in propofol neurosensitivity between LS and SS mice. Although this QTL is tightly linked to Tyr, propofol sensitivity is not modulated by albinism. For mapping this QTL, the LSXSS RIs proved to be an especially powerful resource, localizing the candidate-gene region to a 99% confidence interval of only 2.5 centimorgans.

Anesthetics, Intravenous↗

PubMed1999

Fine mapping and characterization of linked quantitative trait loci involved in the transition of the maize apical meristem from vegetative to generative structures.

Quantitative trait locus (QTL) mapping has detected two linked QTL in the 8L chromosome arm segment introgressed from Gaspé Flint (a Northern Flint open-pollinated population) into the background of N28 (a Corn Belt Dent inbred line). Homozygous recombinant lines, with a variable length of the introgressed segment, confirmed the presence of the two previously identified, linked QTL. In the N28 background, Gaspé Flint QTL alleles at both loci induce a reduction in node number, height, and days to anthesis (pollen shed). Given the determinate growth pattern of maize, the phenotypic effects indicate that the two QTL are involved in the transition of the apical meristem from vegetative to generative structures. Relative to the effects of the two QTL in the background of N28, we distinguish two general developmental factors affecting the timing of pollen shed. The primary factor is the timing of the transition of the apical meristem. The second, derivative factor is the global extent of internode elongation. Having separated the two linked QTL, we have laid the foundation for the positional cloning of the QTL with a larger effect.

Analysis of Variance↗

PubMed2003

Titin is a candidate gene for stroke volume response to endurance training: the HERITAGE Family Study.

A genome-wide linkage scan for endurance training-induced changes in submaximal exercise stroke volume (DeltaSV50) in the HERITAGE Family Study revealed two chromosomal regions (2q31-q32 and 10p11.2) with at least suggestive evidence of linkage among white families. Here we report a further characterization of the quantitative trait locus (QTL) in chromosome 2q31 and provide evidence that titin (TTN) is likely a candidate gene involved. The original linkage was detected with two markers (D2S335 and D2S1391), and the QTL covered approximately 25 million base pairs (Mb). We added 12 microsatellite markers resulting in an average marker density of one marker per 2.3 Mb. The evidence of linkage increased from P = 0.006 to P = 0.0002 and 0.00002 in the multi- and single-point analyses, respectively. The strongest evidence of linkage was seen with two markers in and near the TTN gene. Transmission/disequilibrium test (TDT) with the same marker set provided evidence for association with one of the TTN markers (D2S385; P = 0.004). TTN is a major contributor to the elasticity of cardiomyocytes and a key regulator of the Frank-Starling mechanism. Since TTN is the largest gene in the human genome, the challenge is to identify the DNA sequence variants contributing to the interindividual differences in cardiac adaptation to endurance training.

Chromosome Mapping↗

PubMed2006

Replication of small effect quantitative trait loci for behavioral traits facilitated by estimation of effect size from independent cohorts.

Quantitative trait locus (QTL) mapping is often done in a single segregating population, such as a backcross or an intercross. Both QTL location and effect size are then estimated from the same dataset. This approach results in an over-estimate of effect size for two reasons: (1) LOD scores, which are maximized over numerous point-wise tests, are correlated with estimated effect size and (2) small effect QTLs are often undetected in underpowered experiments, yielding inflated effect sizes for detected QTLs (the Beavis effect). When it is impractical to maintain or generate large population sizes, an alternative is to use two populations, one for initial detection and localization and a second for a locus-matched estimate of effect size, not conditioned on significance. Recombinant inbred (RI) panels are eminently suitable for this approach, as each strain genotype can be sampled repeatedly. We present mapping results from the LXS RI panel for two behavioral phenotypes relating to ethanol response: low-dose ethanol activation and loss of righting following high-dose injection. Both the phenotypes were measured in two or three independent cohorts, which were then used to re-estimate effect size. Many small-effect QTLs replicated using this approach, but in all cases, effect size, in the replicate cohorts, was reduced from the initial estimate, often substantially. Such a reduction will have important consequences for power analyses in which sample sizes are determined for subsequent confirmation studies.

Alcoholism↗

PubMed2005

Inferring gene transcriptional modulatory relations: a genetical genomics approach.

Bayesian network modeling is a promising approach to define and evaluate gene expression circuits in diverse tissues and cell types under different experimental conditions. The power and practicality of this approach can be improved by restricting the number of potential interactions among genes and by defining causal relations before evaluating posterior probabilities for billions of networks. A newly developed genetical genomics method that combines transcriptome profiling with complex trait analysis now provides strong constraints on network architecture. This method detects those chromosomal intervals responsible for differences in mRNA expression using quantitative trait locus (QTL) mapping. We have developed an efficient Bayesian approach that exploits the genetical genomics method to focus computational effort on the most plausible gene modulatory networks. We exploit a dense marker map for a genetic reference population (GRP) that consists of 32 BXD strains of mice made by intercrossing two progenitor strains--C57BL/6J and DBA/2J. These progenitors differ at approximately 1.3 million known single nucleotide polymorphisms (SNPs), all of which can be exploited to estimate the probability that a gene contains functional polymorphisms that segregate within the GRP. We constructed 66 candidate networks that include all the candidate modulator genes located in the 209 statistically significant trans-acting QTL regions. SNPs that distinguish between the two progenitor strains were used to further winnow the list of candidate modulators. Bayesian network was then used to identify the genetic modulatory relations that best explain the microarray data.

Algorithms↗

PubMed2000

Quantitative trait loci on chromosomes 3 and 17 influence phenotypes of the metabolic syndrome.

Recent research has emphasized the importance of the metabolic cluster, which includes glucose intolerance, dyslipidemia, and high blood pressure, as a strong predictor of the obesity-related morbidities and premature mortality. Fundamental to this association, commonly referred to as the metabolic syndrome, is the close interaction between abdominal fat patterning, total body adiposity, and insulin resistance. As the initial step in identifying major genetic loci influencing these phenotypes, we performed a genomewide scan by using a 10-centiMorgan map in 2,209 individuals distributed over 507 nuclear Caucasian families. Pedigree-based analysis using a variance components linkage model demonstrated a quantitative trait locus (QTL) on chromosome 3 (3q27) strongly linked to six traits representing these fundamental phenotypes [logarithm of odds (lod) scores ranged from 2.4 to 3.5]. This QTL exhibited possible epistatic interaction with a second QTL on chromosome 17 (17p12) strongly linked to plasma leptin levels (lod = 5.0). Situated at these epistatic QTLs are candidate genes likely to influence two biologic precursor pathways of the metabolic syndrome.

Blood Glucose↗

PubMed2003

Fine mapping of complex trait genes combining pedigree and linkage disequilibrium information: a Bayesian unified framework.

We present a Bayesian method that combines linkage and linkage disequilibrium (LDL) information for quantitative trait locus (QTL) mapping. This method uses jointly all marker information (haplotypes) and all available pedigree information; i.e., it is not restricted to any specific experimental design and it is not required that phases are known. Infinitesimal genetic effects or environmental noise ("fixed") effects can equally be fitted. A diallelic QTL is assumed and both additive and dominant effects can be estimated. We have implemented a combined Gibbs/Metropolis-Hastings sampling to obtain the marginal posterior distributions of the parameters of interest. We have also implemented a Bayesian variant of usual disequilibrium measures like D' and r(2) between QTL and markers. We illustrate the method with simulated data in "simple" (two-generation full-sib families) and "complex" (four-generation) pedigrees. We compared the estimates with and without using linkage disequilibrium information. In general, using LDL resulted in estimates of QTL position that were much better than linkage-only estimates when there was complete disequilibrium between the mutant QTL allele and the marker. This advantage, however, decreased when the association was only partial. In all cases, additive and dominant effects were estimated accurately either with or without disequilibrium information.

Bayes Theorem↗

PubMed2002

Genetic analysis of scab resistance QTL in wheat with microsatellite and AFLP markers.

Three chromosomal regions associated with scab resistance were detected in a common cultivar, Ning7840, by microsatellite and AFLP analysis. Six microsatellites on chromosome 3BS, Xgwm389, Xgwm533, Xbarc147, Xgwm493, Xbarc102, and Xbarc131, were integrated into an amplified fragment length polymorphism (AFLP) linkage group containing a major quantitative trait locus (QTL) for scab resistance in a mapping population of 133 recombinant inbred lines (RILs) derived from 'Ning7840' x 'Clark'. Based on single-factor analysis of variance of scab infection data from four experiments, Xgwm533 and Xbarc147 were the two microsatellite markers most tightly associated with the major scab resistance QTL. Interval analysis based on the integrated map of AFLP and microsatellite markers showed that the major QTL was located in a chromosome region about 8 cM in length around Xgwm533 and Xbarc147. Based on mapping of six microsatellite markers on eight 3BS deletion lines, the major QTL was located distal to breakage point 3BS-8. In total, 18 microsatellites were physically located on different subarm regions on 3BS. Two microsatellites, Xgwm120 and Xgwm614, were significantly associated with QTL for scab resistance on chromosome 2BL and 2AS, respectively. The resistance alleles on 3BS, 2BL, and 2AS were all derived from 'Ning7840'. Significant interaction between the major QTL on 3BS and the QTL on 2BL was detected based on microsatellite markers linked to them. Using these microsatellite markers would facilitate marker-assisted selection to improve scab resistance in wheat.

Chromosome Mapping↗

PubMed2006

AB-QTL analysis in spring barley: II. Detection of favourable exotic alleles for agronomic traits introgressed from wild barley (H. vulgare ssp. spontaneum).

The objective of the present study was to identify favourable exotic Quantitative Trait Locus (QTL) alleles for the improvement of agronomic traits in the BC2DH population S42 derived from a cross between the spring barley cultivar Scarlett and the wild barley accession ISR42-8 (Hordeum vulgare ssp. spontaneum). QTLs were detected as a marker main effect and/or a marker x environment interaction effect (M x E) in a three-factorial ANOVA. Using field data of up to eight environments and genotype data of 98 SSR loci, we detected 86 QTLs for nine agronomic traits. At 60 QTLs the marker main effect, at five QTLs the M x E interaction effect, and at 21 QTLs both the effects were significant. The majority of the M x E interaction effects were due to changes in magnitude and are, therefore, still valuable for marker assisted selection across environments. The exotic alleles improved performance in 31 (36.0%) of 86 QTLs detected for agronomic traits. The exotic alleles had favourable effects on all analysed quantitative traits. These favourable exotic alleles were detected, in particular on the short arm of chromosome 2H and the long arm of chromosome 4H. The exotic allele on 4HL, for example, improved yield by 7.1%. Furthermore, the presence of the exotic allele on 2HS increased the yield component traits ears per m2 and thousand grain weight by 16.4% and 3.2%, respectively. The present study, hence, demonstrated that wild barley does harbour valuable alleles, which can enrich the genetic basis of cultivated barley and improve quantitative agronomic traits.

Alleles↗

PubMed2004

Haplotype analysis in multiple crosses to identify a QTL gene.

Identifying quantitative trait locus (QTL) genes is a challenging task. Herein, we report using a two-step process to identify Apoa2 as the gene underlying Hdlq5, a QTL for plasma high-density lipoprotein cholesterol (HDL) levels on mouse chromosome 1. First, we performed a sequence analysis of the Apoa2 coding region in 46 genetically diverse mouse strains and found five different APOA2 protein variants, which we named APOA2a to APOA2e. Second, we conducted a haplotype analysis of the strains in 21 crosses that have so far detected HDL QTLs; we found that Hdlq5 was detected only in the nine crosses where one parent had the APOA2b protein variant characterized by an Ala61-to-Val61 substitution. We then found that strains with the APOA2b variant had significantly higher (P < or = 0.002) plasma HDL levels than those with either the APOA2a or the APOA2c variant. These findings support Apoa2 as the underlying Hdlq5 gene and suggest the Apoa2 polymorphisms responsible for the Hdlq5 phenotype. Therefore, haplotype analysis in multiple crosses can be used to support a candidate QTL gene.

Amino Acid Sequence↗

PubMed2004

Dissection of multigenic obesity traits in congenic mouse strains.

Previous quantitative trait locus mapping (QTL) identified multigenic obesity (MOB) loci on mouse Chromosome (Chr) 2 that influence the interrelated phenotypes of obesity, insulin resistance, and dyslipidemia. To better localize and characterize the MOB locus, three congenic mouse strains were created. Overlapping genomic intervals from the lean CAST/Ei (CAST) strain were introgressed onto an obesity-susceptible C57BL/6 (BL6) background to create proximal (15 Mb-73 Mb), middle (63 Mb-165 Mb), and distal (83 Mb-182 Mb) congenic strains. The congenic strains showed differences in obesity, insulin, and lipid traits consistent with the original QTL analysis for the locus. Importantly, characterization of the MOB congenics localized the effects of genes that underlie obesity-related traits to an introgressed interval (73-83 Mb) unique to the middle MOB congenic. Conversely, significant differences between the lipid and insulin profiles of the middle and distal MOB congenics implicated the presence of at least two genes that underlie these traits. When fed an atherogenic diet, several traits associated with metabolic syndrome were observed in the distal MOB congenic, while alterations in plasma lipoproteins were observed in the middle MOB congenic strain.

Animals↗

PubMed2005

Identifying novel genes for atherosclerosis through mouse-human comparative genetics.

Susceptibility to atherosclerosis is determined by both environmental and genetic factors. Its genetic determinants have been studied by use of quantitative-trait-locus (QTL) analysis. So far, 21 atherosclerosis QTLs have been identified in the mouse: 7 in a high-fat-diet model only, 9 in a sensitized model (apolipoprotein E- or LDL [low-density lipoprotein] receptor-deficient mice) only, and 5 in both models, suggesting that different gene sets operate in each model and that a subset operates in both. Among the 27 human atherosclerosis QTLs reported, 17 (63%) are located in regions homologous (concordant) to mouse QTLs, suggesting that these mouse and human atherosclerosis QTLs have the same underlying genes. Therefore, genes regulating human atherosclerosis will be found most efficiently by first finding their orthologs in concordant mouse QTLs. Novel mouse QTL genes will be found most efficiently by using a combination of the following strategies: identifying QTLs in new crosses performed with previously unused parental strains; inducing mutations in large-scale, high-throughput mutagenesis screens; and using new genomic and bioinformatics tools. Once QTL genes are identified in mice, they can be tested in human association studies for their relevance in human atherosclerotic disease.

Animals↗

PubMed2002

Non-ahr gene susceptibility Loci for porphyria and liver injury induced by the interaction of 'dioxin' with iron overload in mice.

Among the actions of 2,3,7,8-tetrachlorodibenzo-p-dioxin (dioxin) in mice is the induction of hepatic porphyria. This is similar to the most common disease of this type in humans, sporadic porphyria cutanea tarda (PCT). Evidence is consistent with the actions of dioxin being mediated through binding to the aryl hydrocarbon receptor (AHR) with different Ahr alleles in mouse strains apparently accounting for differential downstream gene expression and susceptibility. However, studies of dioxin-induced porphyria and liver injury indicate that the mechanisms must involve interactions with other genes, perhaps associated with iron metabolism. We performed a quantitative trait locus (QTL) analysis of an F(2) cross between susceptible C57BL/6J (Ahr(b1) allele) and the highly resistant DBA/2 (Ahr(d) allele) strains after treatment with dioxin and iron. For porphyria we found QTLs on chromosomes 11 and 14 in addition to the Ahr gene (chromosome 12). Studies with C57BL/6.D2 Ahr(d) mice confirmed that the Ahr(d) allele alone did not completely negate the response. SWR mice are syngenic for the Ahr(d) allele with the DBA/2 strain but are susceptible to porphyria after elevation of hepatic iron. Analysis of SWRxD2 F(2) mice treated with iron and dioxin showed a QTL on chromosome 11, as well as finding other loci on chromosomes 1 (and possibly 9), for both porphyria and liver injury. These findings show for the first time the location of genes, other than Ahr, that modulate the mechanism of hepatic porphyria and injury caused by dioxin in mice. Orthologous loci may contribute to the pathogenesis of human sporadic PCT.

Animals↗

PubMed2001

Replacement of (alpha)1-Na-K-ATPase of Dahl rats by Milan rats lowers blood pressure but does not affect its activity.

Both linkage and use of congenic strains have shown that a chromosome region near the gene for the Na-K-ATPase alpha(1)-subunit (Atp1a1) contained a quantitative trait locus (QTL) for blood pressure (BP). Currently, two congenic strains, designated S.M5 and S.M6, were made by replacing a segment of the Dahl salt-sensitive SS/Jr (S) rat by the homologous region of the Milan normotensive rat (MNS). In S.M5, the gene for Atp1a1 is from the MNS strain; whereas in S.M6, Atp1a1 is from the S strain. The baseline activity of the alpha(1)-Na-K-ATPase and its stoichiometry were evaluated by an assay of ouabain-sensitive inwardly and outwardly directed (86)Rb and (22)Na fluxes in erythrocytes. The two congenic strains showed a similar BP, but both had a BP lower than that of S rats (P < 0.0001). Neither the alpha(1)-Na-K-ATPase activity nor its stoichiometry was affected by the substitution of the Atp1a1 alleles of S by those of MNS. Thus the BP-lowering effects observed in S.M5 and S.M6 could not be attributed to the alpha(1)-Na-K-ATPase activity or its stoichiometry. Atp1a1 is not supported as a candidate to be a BP QTL.

Alleles↗