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Results for “expression quantitative trait loci”

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PubMed2006

Modelling epistatic effects of embryo and endosperm QTL on seed quality traits.

Coordinated expression of embryo and endosperm tissues is required for proper seed development. The coordination among these two tissues is controlled by the interaction between multiple genes expressed in the embryo and endosperm genomes. In this article, we present a statistical model for testing whether quantitative trait loci (QTL) active in different genomes, diploid embryo and triploid endosperm, epistatically affect a trait expressed on the endosperm tissue. The maximum likelihood approach, implemented with the EM algorithm, was derived to provide the maximum likelihood estimates of the locations of embryo- and endosperm-specific QTL and their main effects and epistatic effects. This model was used in a real example for rice in which two QTL, one from the embryo genome and the other from the endosperm genome, exert a significant interaction effect on gel consistency on the endosperm. Our model has successfully detected Waxy, a candidate gene in the embryo genome known to regulate one of the major steps of amylose biosynthesis in the endosperm. This model will have great implications for agricultural and evolutionary genetic research.

Algorithms↗

PubMed2026

Deciphering novel targets in salivary gland pleomorphic adenoma by integrating plasma proteomics and parotid transcriptomics analyses.

BACKGROUND/PURPOSE: Pleomorphic adenoma (PA) is the most common salivary gland benign tumor, with its molecular drivers elusive due to a lack of experimental models. This study aimed to decipher novel targets in PA by systematically integrating plasma protein quantitative trait loci (pQTL)-based Mendelian randomization (MR) with multi-omics profiling of parotid gland tissues. MATERIALS AND METHODS: We performed two-sample MR using 5450 plasma pQTLs and genome-wide association study summary for benign or broader salivary gland diseases from FinnGen consortium. Bulk RNA-sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) comparing PA to normal tissue were used for transcriptomic validation. Immunohistochemistry (IHC) was applied for protein-level validation in human PA, adenoid cystic carcinoma (ACC), and murine inflammatory lesions. RESULTS: MR identified 12 plasma proteins associated with benign salivary gland tumor risk. Transmembrane serine protease 6 (TMPRSS6) was the only protein significantly risk-increasing for both benign and broader salivary gland diseases. Strikingly, mitogen-activated protein kinase kinase 4 (MAP2K4) showed opposite MR effects between benign and all-lesion outcomes. Bulk RNA-seq showed limited concordance with MR findings, while scRNA-seq revealed a unique plastic epithelium and partially validated candidates at cellular resolution. Critically, IHC confirmed MAP2K4 protein overexpression specifically in human PA, but not in ACC or inflammatory lesions, while TMPRSS6 was downregulated in established pathologies despite its genetic risk association. CONCLUSION: By integrating plasma proteome-based causal inference with parotid tissue multi-omics, this study unveils MAP2K4 as a potential PA-specific driver. This integrative framework provides novel, context-specific targets for further functional investigation in salivary gland tumorigenesis.

Gene expression profiling↗

PubMed2005

Genetic regulation of gene expression during shoot development in Arabidopsis.

The genetic control of gene expression during shoot development in Arabidopsis thaliana was analyzed by combining quantitative trait loci (QTL) and microarray analysis. Using oligonucleotide array data from 30 recombinant inbred lines derived from a cross of Columbia and Landsberg erecta ecotypes, the Arabidopsis genome was scanned for marker-by-gene linkages or so-called expression QTL (eQTL). Single-feature polymorphisms (SFPs) associated with sequence disparities between ecotypes were purged from the data. SFPs may alter the hybridization efficiency between cDNAs from one ecotype with probes of another ecotype. In genome scans, five eQTL hot spots were found with significant marker-by-gene linkages. Two of the hot spots coincided with classical QTL conditioning shoot regeneration, suggesting that some of the heritable gene expression changes observed in this study are related to differences in shoot regeneration efficiency between ecotypes. Some of the most significant eQTL, particularly those at the shoot regeneration QTL sites, tended to show cis-chromosomal linkages in that the target genes were located at or near markers to which their expression was linked. However, many linkages of lesser significance showed expected "trans-effects," whereby a marker affects the expression of a target gene located elsewhere on the genome. Some of these eQTL were significantly linked to numerous genes throughout the genome, suggesting the occurrence of large groups of coregulated genes controlled by single markers.

Arabidopsis↗

PubMed2003

A strategy for the integration of QTL, gene expression, and sequence analyses.

Although hundreds if not thousands of quantitative trait loci (QTL) have been described for a wide variety of complex traits, only a very small number of these QTLs have been reduced to quantitative trait genes (QTGs) and quantitative trait nucleotides (QTNs). A strategy, Multiple Cross Mapping (MCM), is described for detecting QTGs and QTNs that is based on leveraging the information contained within the haplotype structure of the mouse genome. As described in the current report, the strategy utilizes the six F(2) intercrosses that can be formed from the C57BL/6J (B6), DBA/2J (D2), BALB/cJ (C), and LP/J (LP) inbred mouse strains. Focusing on the phenotype of basal locomotor activity, it was found that in all three B6 intercrosses, a QTL was detected on distal Chromosome (Chr) 1; no QTL was detected in the other three intercrosses, and thus, it was assumed that at the QTL, the C, D2, and LP strains had functionally identical alleles. These intercross data were used to form a simple algorithm for interrogating microsatellite, single nucleotide polymorphism (SNP), brain gene expression, and sequence databases. The results obtained point to Kcnj9 (which has a markedly lower expression in the B6 strain) as being the likely QTG. Further, it is suggested that the lower expression in the B6 strain results from a polymorphism in the 5'-UTR that disrupts the binding of at least three transcription factors. Overall, the method described should be widely applicable to the analysis of QTLs.

Algorithms↗

PubMed2005

Physical mapping of genes in the porcine ovarian transcriptome.

Reproductive efficiency and associated traits are of major economic importance to the swine industry and have been more difficult to improve genetically than other production traits. Integration of phenotypical data with gene mapping and expression studies provides a powerful approach for dissection of the genetic basis regulating complex traits. We developed a total of 101 polymerase chain reaction-based markers, representing 91 unique genes, for expressed sequence tags previously reported to be putatively differentially expressed in the porcine ovarian transcriptome of a swine line selected on an index of high ovulation rate and embryonic survival. These were subsequently used in physical mapping experiments with a porcine radiation hybrid and somatic cell hybrid panels. Our results increased the information content of the porcine physical map useful for comparative mapping by c. 10%. Moreover, the mapped genes are likely to be biologically relevant to the molecular mechanisms that control ovulation rate in the pig. A total of 12 differentially expressed genes were mapped to regions previously reported to contain quantitative trait loci affecting swine ovulation rate.

Animals↗

PubMed1998

Quantitative trait loci implicated in corpus callosum midsagittal area in mice.

The midsagittal area of the corpus callosum expressed as the percentage of the hemispheric surface is smaller in the NZB/BlNJ than in the C57BL/6By inbred strain of mice. We performed a QTL mapping analysis using 284 F2s. Two loci linked to this measure were found: the CCrSQTL1 and CCrSQTL2 at 87 and 67 centiMorgans from the centromere on chromosomes 1 and 4 respectively. The two loci interacted significantly. The total source of genetic variation contributed to 25% of the observed variance.

Animals↗

PubMed1998

Environment-influenced expression of polygene mutations isolated from a natural population of Drosophila melanogaster.

Quantitative trait loci (QTLs) affecting sternopleural bristle number in Drosophila melanogaster have been mapped using phenotypic markers and progeny testing. The loci were found on four of the third chromosomes isolated from a natural population. All four loci showed large effects at the standard 25 degrees C culture temperature, but they responded in different ways when developmental temperature was lowered or raised. These data support the hypothesis that genotype x environment interactions have important influences on polygene expression, and some loci might be silent, or phenotypically neutral, under some conditions but play a large phenotypic role under others. Thus, a full cataloging of the loci contributing to mutational variance for QTLs cannot be done at just a single, controlled environmental condition.

Animals↗

PubMed2026

Integrated multi-omics identification of m6A-SNP-related diagnostic biomarkers in amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) lacks reliable and minimally invasive biomarkers for early diagnosis. m6A-associated single-nucleotide polymorphisms (m6A-SNPs) may influence RNA methylation and gene expression, offering opportunities to identify clinically relevant diagnostic markers. METHODS: We integrated eQTLGen cis-eQTL data, RMVar m6A-SNP annotations, and ALS transcriptomic datasets to identify m6A-SNP-related genes. Random Forest and LASSO regression were combined to screen robust diagnostic markers. A nomogram was constructed and validated using independent cohorts. Immune infiltration, predicted m6A modification sites, and potential RBP-SNP interactions were assessed. Peripheral blood samples from ALS patients were used for exploratory validation of gene expression and global m6A levels. RESULTS: We identified 109 ALS-associated m6A-SNP-related genes with cis-eQTL signals and narrowed these to seven candidate diagnostic markers (TMED5, OXR1, BRI3, FEM1C, SUZ12, EIF2AK4, and TJAP1). The seven-gene model outperformed the individual markers in the training cohort and retained moderate discrimination in the independent validation cohort. ALS samples showed differences in inferred immune-cell composition, including monocytes, neutrophils, and T-cell subsets. The selected SNP loci were located near predicted m6A sites and annotated RBP-binding regions. Exploratory clinical validation showed significant upregulation of FEM1C and SUZ12 at both mRNA and protein levels, accompanied by reduced global m6A modification. CONCLUSIONS: Through multi-omics integration and exploratory clinical validation, this study identifies m6A-SNP-related candidate markers associated with ALS. The findings support further evaluation of m6A-related signatures for ALS discrimination and molecular characterization, while larger independent cohorts and additional calibration are required before clinical application.

Humans↗

PubMed2005

Mapping of 443 porcine EST improves the comparative maps for SSC1 and SSC7 with the human genome.

Numerous mapping studies of complex traits in the pig have resulted in quantitative trait loci (QTL) intervals of 10-20 cM. To improve the chances to identify the genes located in such intervals, increased expressed sequence tags (EST)-based marker density, coupled with comparative mapping with species whose genomes have been sequenced such as human and mouse, is the most efficient tool. In this study, we mapped 443 porcine EST with a radiation hybrid (RH) panel (384 had LOD > 6.0) and a somatic cell hybrid panel. Requiring no discrepancy between two-point and multipoint RH data allowed robust assignment of 309 EST, of which most were located on porcine chromosomes (SSC) 1, 4, 7, 8 and X. Moreover, we built framework maps for two chromosomes, SSC1 and SSC7, with mapped QTL in regions with known rearrangement between pig and human genomes. Using the Blast tool, we found orthologies between 407 of the 443 pig cDNA sequences and human genes, or to existing pig genes. Our porcine/human comparative mapping results reveal possible new homologies for SSC1, SSC3, SSC5, SSC6, SSC12 and SSC14 and add markers in synteny breakpoints for chromosome 7.

Animals↗

PubMed2025

Network-based drug repurposing for psychiatric disorders using single-cell genomics.

Neuropsychiatric disorders lack effective treatments due to a limited understanding of the underlying cellular and molecular mechanisms. To address this, we integrated population-scale single-cell genomics data and analyzed 23 cell-type-level gene regulatory networks across schizophrenia, bipolar disorder, and autism. Our analysis revealed potential druggable transcription factors co-regulating known risk genes that converge into cell-type-specific co-regulated modules. We applied graph neural networks on those modules to prioritize novel risk genes and leveraged them in a network-based drug repurposing framework to identify 220 drug molecules with the potential for targeting specific cell types. We found evidence for 37 of these drugs in reversing disorder-associated transcriptional phenotypes. Additionally, we discovered 335 drug-cell quantitative trait loci (eQTLs), revealing genetic variation's influence on drug target expression at the cell-type level. Our results provide a single-cell network medicine resource that provides potential mechanistic insights for advancing treatment options for neuropsychiatric disorders.

Drug Repositioning↗

PubMed2003

A targeted approach to the identification of candidate genes determining susceptibility to Plasmodium gallinaceum in Aedes aegypti.

The malaria parasite, Plasmodium, has evolved an intricate life cycle that includes stages specific to a mosquito vector and to the vertebrate host. The mosquito midgut represents the first barrier Plasmodium parasites encounter following their ingestion with a blood meal from an infected vertebrate. Elucidation of the molecular interaction between the parasite and the mosquito could help identify novel approaches to preventing parasite development and subsequent transmission to vertebrates. We have used an integrated Bulked Segregant Analysis-Differential Display (BSA-DD) approach to target genes expressed that are in the midgut and located within two genome regions involved in determining susceptibility to P. gallinaceum in the mosquito Aedes aegypti. A total of twenty-two genes were identified and characterized, including five genes with no homologues in public sequence databases. Eight of these genes were mapped genetically to intervals on chromosome 2 that contain two quantitative trait loci (QTLs) that determine susceptibility to infection by P. gallinaceum. Expression analysis revealed several expression patterns, and ten genes were specifically or preferentially expressed in the midgut of adult females. Real-time PCR quantification of expression with respect to the time of blood meal ingestion and infection status in mosquito strains permissive and refractory for malaria revealed a differential expression pattern for seven genes. These represent candidate genes that may influence the ability of the mosquito vector to support the development of Plasmodium parasites. Here we describe their isolation and discuss their putative roles in parasite-mosquito interactions and their use as potential targets in strategies designed to block transmission of malaria.

Aedes↗

PubMed2005

Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice.

Activation of the mesolimbic dopamine reward pathway by acute ethanol produces reinforcement and changes in gene expression that appear to be crucial to the molecular basis for adaptive behaviors and addiction. The inbred mouse strains DBA/2J and C57BL/6J exhibit contrasting acute behavioral responses to ethanol. We used oligonucleotide microarrays and bioinformatics methods to characterize patterns of gene expression in three brain regions of the mesolimbic reward pathway of these strains. Expression profiling included examination of both differences in gene expression 4 h after saline injection or acute ethanol (2 g/kg). Using a rigorous stepwise method for microarray analysis, we identified 788 genes differentially expressed in control DBA/2J versus C57BL/6J mice and 307 ethanol-regulated genes in the nucleus accumbens, prefrontal cortex, and ventral tegmental area. There were strikingly divergent patterns of ethanol-responsive gene expression in the two strains. Ethanol-responsive genes also showed clustering at discrete chromosomal regions, suggesting local chromatin effects in regulation. Ethanol-regulated genes were generally related to neuroplasticity, but regulation of discrete functional groups and pathways was brain region specific: glucocorticoid signaling, neurogenesis, and myelination in the prefrontal cortex; neuropeptide signaling and developmental genes, including factor Bdnf, in the nucleus accumbens; and retinoic acid signaling in the ventral tegmental area. Bioinformatics analysis identified several potential candidate genes for quantitative trait loci linked to ethanol behaviors, further supporting a role for expression profiling in identifying genes for complex traits. Brain region-specific changes in signaling and neuronal plasticity may be critical components in development of lasting ethanol behavioral phenotypes such as dependence, sensitization, and craving.

Animals↗

PubMed2006

Integration--a key to success in the genetic dissection of complex diseases?

Complex diseases are polygenic and multifactorial. The outcome of two decades of search for the culprit genes in complex diseases involving the cardiovascular system has been less than satisfactory. Genomic studies using linkage analysis have led so far to the detection of a large number of quantitative trait loci that embed a large number of candidate genes. Transcriptomic studies using differential gene expression profiling and DNA microarrays have also generated hundreds of potential candidate genes. None of these genetic strategies has enabled researchers to reduce the number of genes to a manageable number or to identify the specific culprit genes. We recently proposed that the search for genes involved in complex diseases such as hypertension might benefit from an integration of genomics and transcriptomics as a logical alternative strategy to using either approach alone. We applied this integrated genomic-transcriptomic approach to identify the genes that are involved in the pathogenesis of hypertension in the Sabra rat model of salt susceptibility. We successfully identified seven novel candidate genes for hypertension, an outcome that could not have been achieved by genomics or transcriptomics alone.

Animals↗

PubMed2005

Genetic regulation of bone mass: from bone density to bone strength.

Osteoporosis is a common disease characterized in adults by diminished bone density. Bone is an organ that evolves and grows throughout life, and establishing optimal bone density in childhood and adolescence serves to buffer bone loss later in life. Bone density, a measurable entity, is the clinical substitute for bone strength, or the ability to defend against fracture. Chronic diseases may adversely affect optimal peak bone density. Bone density is under genetic control, as revealed by three lines of investigations. These include (1) the finding of quantitative trait loci for bone density, (2) the finding that specific mutations in genes that are important in the development of osteoblast or osteoclast lineages alter bone density, and (3) the linkeage of known polymorphisms for genes involved in mineral homeostasis to bone density and/or fracture. Future therapeutics for improving peak bone density or delaying bone loss later in life may take advantage of the genetic nature of bone density development.

Bone Density↗

PubMed2026

Identification and fine mapping of a locus controlling multi-main-stem trait in Brassica napus.

BACKGROUND: The main stem is a crucial component determining individual plant yield in rapeseed (Brassica napus). However, the genetic and developmental basis underlying the multi-main-stem trait remains largely unclear. RESULTS: In this study, we identified a multi-main-stem mutant, mms1, which exhibited a significantly increased silique number per plant and abnormal shoot apical meristem (SAM) development. Genetic analysis demonstrated that the multi-main-stem trait was controlled by a recessive gene. Using bulked segregant analysis combined with a Brassica napus 50 K SNP array and map-based cloning, the locus was mapped to a 340-kb interval on chromosome A09 of the ZS11 reference genome and was designated BnaA09.MMS1. Candidate gene analysis revealed that BnaA09G0254500ZS, which harbors sequence variations in both the promoter and coding regions and shows significantly increased expression in the mutant, was the most likely candidate gene. In addition, phytohormone analysis revealed reduced auxin accumulation in mutant SAMs, together with transcriptomic changes in genes associated with the CLAVATA3 (CLV3)-WUSCHEL (WUS) feedback loop. CONCLUSIONS: These findings provide an important foundation for elucidating the genetic basis of the multi-main-stem trait and offer a valuable genetic resource for rapeseed improvement.

Brassica napus↗

PubMed2004

Quantifying the relationship between gene expressions and trait values in general pedigrees.

Treating mRNA transcript abundances as quantitative traits and examining their relationships with clinical traits have been pursued by using an analytical approach of quantitative genetics. Recently, Kraft et al. presented a family expression association test (FEXAT) for correlation between gene expressions and trait values with a family-based (sibships) design. This statistic did not account for biological relationships of related subjects, which may inflate type I error rate and/or decrease power of statistical tests. In this article, we propose two new test statistics based on a variance-components approach for analyses of microarray data obtained from general pedigrees. Our methods accommodate covariance between relatives for unmeasured genetic effects and directly model covariates of clinical importance. The efficacy and validity of our methods are investigated by using simulated data under different sample sizes, family sizes, and family structures. The proposed LR method has correct type I error rate with moderate to large sample sizes regardless of family structure and family sizes. It has higher power with complex pedigrees and similar power to the FEXAT with sibships. The other proposed FEXAT(R) method is favorable with large family sizes, regardless of sample sizes and family structure. Our methods, robust to population stratification, are complementary to the FEXAT in expression-trait association studies.

Animals↗

PubMed2004

Microarrays and beyond: what potential do current and future genomics tools have for breeders?

One of the most exciting tools from genomics is the ability to obtain a whole-genome snapshot of gene expression. This is typically called a microarray analysis, because probes for the genes of interest, which can run into the thousands, are spotted in a very small array on a glass slide or some other substrate. The resulting array is often called a gene chip, or simply a chip, in the case of short oligo arrays, or slides in the case of cDNA or long oligo arrays. Microarrays offer the awesome potential of simultaneously examining the level of expression, where expression is intended to measure the standing amount of mRNA, for all of the genes in a genome. Given this potential, it is not surprising that microarrays have attracted a great deal of attention from animal geneticists and breeders. The purpose of this review is to provide a brief, yet critical, overview of some of the potential uses of such whole-genome expression studies in applied animal breeding and to speculate about what additional forthcoming tools might be of use.

Animals↗

PubMed2005

Searching QTL by gene expression: analysis of diabesity.

BACKGROUND: Recent developments in sequence databases provide the opportunity to relate the expression pattern of genes to their genomic position, thus creating a transcriptome map. Quantitative trait loci (QTL) are phenotypically-defined chromosomal regions that contribute to allelically variant biological traits, and by overlaying QTL on the transcriptome, the search for candidate genes becomes extremely focused. RESULTS: We used our novel data mining tool, ExQuest, to select genes within known diabesity QTL showing enriched expression in primary diabesity affected tissues. We then quantified transcripts in adipose, pancreas, and liver tissue from Tally Ho mice, a multigenic model for Type II diabetes (T2D), and from diabesity-resistant C57BL/6J controls. Analysis of the resulting quantitative PCR data using the Global Pattern Recognition analytical algorithm identified a number of genes whose expression is altered, and thus are novel candidates for diabesity QTL and/or pathways associated with diabesity. CONCLUSION: Transcription-based data mining of genes in QTL-limited intervals followed by efficient quantitative PCR methods is an effective strategy for identifying genes that may contribute to complex pathophysiological processes.

Algorithms↗