Biology subjects

Zheng, Z.

Publications and source records attributed to Zheng, Z..

At least 217 records · Page 12Linked to original sources

bioRxiv2019

Homoploid hybridization signals due to ancestral subdivision: a case study on the D lineage in wheat

Homoploid hybrid speciation has been reported in a wide range of species since the exploitation of genome sequences in evolutionary studies. However, the interference of ancestral subdivision has not been adequately considered in many such investigations. Using the D lineage in wheat as an example, we showed clearly that ancestral subdivision has led to false detection of homoploid hybridization signals. We develop a novel statistical framework by examining the changes in shared ancestral variations and infer on the likelihood of speciation due to genuine homoploid hybridization or ancestral subdivisions. Applying this to wheat data, we found that homoploid hybridization was not involved in the origin of the D lineage contrary to the now widely held belief. This example indicates that the significance of homoploid hybrid speciation is likely exaggerated. The underlying methodology developed in this study should be valuable for clarifying whether homoploid hybridization has contributed to the speciation of many other species.

evolutionary biology↗

bioRxiv2019

Multi-walled carbon nanotubes/nano-Ag-TiO2 membrane DNA electrochemical biosensor

A highly sensitive DNA electrochemical biosensor was prepared based on multi-walled carbon nanotube/nano-Ag-TiO2 composite membrane. The Ag-TiO2 composite is mixed with a suitable amount of multi-walled carbon nanotubes (MWNT) dispersed in N,N-dimethylformamide to form a uniform and stable mixed solution, which is applied onto the surface of the bare carbon paste electrode. A MWNT/Ag-TiO2 modified carbon paste electrode was prepared. The large specific surface area and good electron transport properties of carbon nanotubes have a good synergistic effect on the good biocompatibility of Ag-TiO2 nanocomposites and excellent adsorption capacity of DNA, which significantly improves the immobilization and DNA hybridization of DNA probes. Detection sensitivity. The preparation of the sensing membrane and the immobilization and hybridization of DNA were characterized by cyclic voltammetry and electrochemical impedance spectroscopy. The exogenous glufosinate acetyltransferase gene fragment of transgenic plants was detected by electrochemical impedance spectroscopy. The linear range was 1. 0 x 10 - 11 [~]1. 0 x 10 - 6 mol / L. The detection limit was 3. 12 x 10 - 12 mol / L.

bioengineering↗

bioRxiv2019

Powerful solution for experimental cerebral malaria treatment: artesunate and tetramethylpyrazine

BackgroundCerebral malaria (CM) is a kind of serious neurological complication caused by the acute Plasmodium falciparum infection. About 300000 patients including children under 5 years old died from this disease every year. Even intravenous artesunate (Art) is employed as the most effictive drug in the treatment of CM, high incidence of death and neurological sequelae are still inevitable. Therefore, we assessed the combination of Art and tetramethylpyrazine (TMP), to treat experimental CM (ECM) in C57BL/6 mice infected with Plasmodium berghei ANKA (PbA). A non-biased whole brain quantitative proteomic analysis was also conducted to get some insight of the mechanism of the combinational treatment.\n\nResultsTreatment of (ECM)-C57BL/6 mice with the combination of Art and TMP increased the survival, improved clinical signs and prevented neurological manifestations. These effects were related to reduction of parasitised red blood cells (pRBC) adhesion, sequestration, maintaining brain microvascular integrity, increasing nerve growth factor, neurotrophin levels, and alleviating hippocampal neuronal damage and astrocyte activation. The pharmacological effects of Art-TMP combination therapy were analyzed by ECM mice brain proteomic function enrichment. Based on an isobaric tag for relative and absolute quantitation (iTRAQ) fold-change of 1.2 (P-value < 0.05), 217 down-regulated and 177 up-regulated proteins were identified, presenting a significantly altered proteome profile of the combined Art and TMP group as compared to the group treated with Art or TMP alone. These results suggested that the Art-TMP combination could be used as a powerful solution for CM and its neurologic damage.\n\nConclusionsAn effictive therapy for CM with low mortality rate and protect against ECM-induced neurocognitive impairment has been proposed through the combination of Art and TMP, which can provide an effective adjuvant treatment in the clinic. iTRAQ proteomics provide a resource for further mechanistic studies to examine the synergistic effects of Art and TMP and their potential to serve as an adjunctive treatment method and intervention targets.\n\nAuthor SummaryCerebral malaria (CM) is the most serious neurological complication caused by Plasmodium falciparum infection. Even after antimalarial treatment, severe neurological sequelae still exist. We used tetramethylpyrazine (TMP), the main ingredient of the traditional Chinese medicine Chuanxiong, and artesunate (Art) as a combination of drugs. We found that Art-TMP combination could improve the clinical symptoms of CM and protect the nervous system. At the same time, proteomics was used to analyze the protective mechanism of Art-TMP combination administration on ECM mice. This study suggests that the combination of Art and TMP may be used as an adjuvant therapy for clinical CM and iTRAQ proteomics provides resources for further study of Art-TMP combination and provides potential prognostic biomarkers for this therapeutic intervention.

pathology↗

bioRxiv2019

A resource-efficient tool for mixed model association analysis of large-scale data

The genome-wide association study (GWAS) has been widely used as an experimental design to detect associations between genetic variants and a phenotype. Two major confounding factors, population stratification and relatedness, could potentially lead to inflated GWAS test-statistics and thereby spurious associations. Mixed linear model (MLM)-based approaches can be used to account for sample structure. However, genome-wide association (GWA) analyses in biobank samples such as the UK Biobank (UKB) often exceed the capability of most existing MLM-based tools especially if the number of traits is large. Here, we developed an MLM-based tool (called fastGWA) that controls for population stratification by principal components and relatedness by a sparse genetic relationship matrix for GWA analyses of biobank-scale data. We demonstrated by extensive simulations that fastGWA is reliable, robust and highly resource-efficient. We then applied fastGWA to 2,173 traits on 456,422 array-genotyped and imputed individuals and 2,048 traits on 46,191 whole-exome-sequenced individuals in the UKB.

genetics↗

bioRxiv2019

Automated Reconstruction of a Serial-Section EM Drosophila Brain with Flood-Filling Networks and Local Realignment

Reconstruction of neural circuitry at single-synapse resolution is a key target for improving understanding of the nervous system in health and disease. Serial section transmission electron microscopy (ssTEM) is among the most prolific imaging methods employed in pursuit of such reconstructions. We demonstrate how Flood-Filling Networks (FFNs) can be used to computationally segment a forty-teravoxel whole-brain Drosophila ssTEM volume. To compensate for data irregularities and imperfect global alignment, FFNs were combined with procedures that locally re-align serial sections as well as dynamically adjust and synthesize image content. The proposed approach produced a largely merger-free segmentation of the entire ssTEM Drosophila brain, which we make freely available. As compared to manual tracing using an efficient skeletonization strategy, the segmentation enabled circuit reconstruction and analysis workflows that were an order of magnitude faster.

neuroscience↗

bioRxiv2019

Recovery of trait heritability from whole genome sequence data

Heritability, the proportion of phenotypic variance explained by genetic factors, can be estimated from pedigree data 1, but such estimates are uninformative with respect to the underlying genetic architecture. Analyses of data from genome-wide association studies (GWAS) on unrelated individuals have shown that for human traits and disease, approximately one-third to two-thirds of heritability is captured by common SNPs 2-5. It is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular if the causal variants are rare, or other reasons such as overestimation of heritability from pedigree data. Here we show that pedigree heritability for height and body mass index (BMI) appears to be largely recovered from whole-genome sequence (WGS) data on 25,465 unrelated individuals of European ancestry. We assigned 33.7 million genetic variants to groups based upon their minor allele frequencies (MAF) and linkage disequilibrium (LD) with variants nearby, and estimated and partitioned genetic variance accordingly. The estimated heritability was 0.68 (SE 0.10) for height and 0.30 (SE 0.10) for BMI, with a range of ~0.60 - 0.71 for height and ~0.25 - 0.35 for BMI, depending on quality control and analysis strategies. Low-MAF variants in low LD with neighbouring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection thereon. Cumulatively variants with 0.0001 < MAF < 0.1 explained 0.47 (SE 0.07) and 0.30 (SE 0.10) of heritability for height and BMI, respectively. Our results imply that rare variants, in particular those in regions of low LD, is a major source of the still missing heritability of complex traits and disease.

genetics↗

bioRxiv2019

Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data

Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation. Current high-throughput technologies for detecting PAIs, such as promoter capture Hi-C, are not scalable to large cohorts. Here, we present an analytical approach that uses summary-level data from cohort-based DNA methylation (DNAm) quantitative trait locus (mQTL) studies to predict PAIs. Using mQTL data from human peripheral blood (n=1,980), we predicted 34,797 PAIs which showed strong overlap with the chromatin contacts identified by previous experimental assays. The promoter-interacting DNAm sites were enriched in enhancers or near expression QTLs. Genes whose promoters were involved in PAIs were more actively expressed, and gene pairs with promoter-promoter interactions were enriched for co-expression. Integration of the predicted PAIs with GWAS data highlighted interactions among 601 DNAm sites associated with 15 complex traits. This study demonstrates the use of mQTL data to predict PAIs and provides insights into the role of PAIs in complex trait variation.

genetics↗

bioRxiv2019

An abscisic acid (ABA) homeostasis regulated by its production, catabolism and transport in peanut leaves in response to drought stress

ABA is an important messenger that acts as the signaling mediator for regulating the adaptive response of plants to drought stress. Two production pathways, de novo biosynthesis and hydrolysis of glucose-conjugated ABA by {beta}-glucosidase (BG), increase cellular ABA levels in plants. ABA catabolism via hydroxylation by 8-hydroxylase (CYP707A), or conjugation by uridine diphosphate glucosyltransferase (UGT), decreases cellular ABA levels. The transport of ABA through ATP-binding cassette (ABC)-containing transporter proteins, members of ABC transporter G family (ABCG), across plasma membrane (PM) is another important pathway to regulate cellular ABA levels. In this study, based on our previously constructed transcriptome of peanut leaves in response to drought stress, fourteen candidate genes involved in ABA production (including AhZEP, AhNCED1 and AhNCED3, AhABA2, AhAAO1 and AhAAO2, AhABA3, AhBG11 and AhBG24), catabolism (including AhCYP707A3, AhUGT71K1 and AhUGT73B4) and transport (including AhABCG22-1 and AhABCG22-2), were identified homologously and phylogenetically, and further analyzed at the transcriptional level by real-time RT-PCR, simultaneously determining ABA levels in peanut leaves in response to drought. The high sequence identity and very similar subcellular localization of the proteins deduced from 14 identified genes involved in ABA production, catabolism and transport with the reported corresponding enzymes in databases suggest their similar roles in regulating cellular ABA levels. In response to drought stress, ABA accumulation levels in peanut leaves agree very well with the up-regulated expressions of ABA-producing genes (AhZEP, AhNCED1, AhAAO2, AhABA3, AhBG11 and AhBG24) and PM-localized ABA importer genes (AhABCG22-1 and AhABCG22-2), although the expression of ABA catabolic genes (AhCYP707A3 and AhUGT71K1) was also up-regulated. It is likely that drought-responsive induction of catabolic genes helps not only to maintain ABA levels within a permissible range, but also to prepare the plant for degradation of ABA after removal of the stress. These results suggest that ABA homeostasis in peanut leaves in response to drought may be coordinated by a master regulatory circuit that involves production, catabolism, and as well as transport.

plant biology↗

bioRxiv2019

Streamlined low-input transcriptomics through EASY-RNAseq

High-throughput sequencing for transcriptome profiling is an increasingly accessible and important tool for biological research. However, accurate profiling of small cell populations remains challenging due to issues with gene detection sensitivity and experimental complexity. Here we describe a streamlined RNAseq protocol (EASY RNAseq) for sensitive transcriptome assessment starting from low amount of input materials. EASY RNAseq is technically robust enough for sequencing small pools of homogenous and heterogeneous cells, recovering higher numbers of genes and with a more even expression distribution pattern than other commonly used methods. Application of EASY RNAseq to single human embryos at the 8-cell stage was able to achieve detection of 70% protein-coding genes. This workflow may thus serve as a useful tool for sensitive interrogation of rare cell populations.

genomics↗

bioRxiv2019

A novel QTL conferring Fusarium crown rot resistance located on chromosome arm 6HL in barley

Fusarium crown rot (FCR), caused primarily by Fusarium pseudograminearum, is a devastating disease for cereal production in semi-arid regions worldwide. To identify and characterize loci conferring FCR resistance, we assessed a landrace AWCS799 which is among the top lines identified from a screening. Genetic control of its resistance was investigated by generating and analysing two populations of recombinant inbred lines. One of the populations was used for QTL detection and the other for validation. A novel QTL, located on the long arm of chromosome 6H (designated as Qcrs.caf-6H), was consistently detected in each of the four trials conducted against the mapping population. The QTL explained up to 29.1% of the phenotypic variance and its effect was confirmed in the validation population. Significant interactions between this resistance locus and either plant height or heading date were not detected, further facilitating its manipulation in breeding programs. Key MessageThis study identified and validated a novel and large-effect QTL conferring Fusarium crown rot resistance on the long arm of chromosome 6HL in barley.

plant biology↗

bioRxiv2019

Improved polygenic prediction by Bayesian multiple regression on summary statistics

The capacity to accurately predict an individuals phenotype from their DNA sequence is one of the great promises of genomics and precision medicine. Recently, Bayesian methods for generating polygenic predictors have been successfully applied in human genomics but require the individual level data, which are often limited in their access due to privacy or logistical concerns, and are computationally very intensive. This has motivated methodological frameworks that utilise publicly available genome-wide association studies (GWAS) summary data, which now for some traits include results from greater than a million individuals. In this study, we extend the established summary statistics methodological framework to include a class of point-normal mixture prior Bayesian regression models, which have been shown to generate optimal genetic predictions and can perform heritability estimation, variant mapping and estimate the distribution of the genetic effects. In a wide range of simulations and cross-validation using 10 real quantitative traits and 1.1 million variants on 350,000 individuals from the UK Biobank (UKB), we establish that our summary based method, SBayesR, performs similarly to methods that use the individual level data and outperforms other state-of-the-art summary statistics methods in terms of prediction accuracy and heritability estimation at a fraction of the computational resources. We generate polygenic predictors for body mass index and height in two independent data sets and show that by exploiting summary statistics on 1.1 million variants from the largest GWAS meta-analysis (n {approx} 700, 000) that the SBayesR prediction R2 improved on average across traits by 6.8% relative to that estimated from an individual-level data BayesR analysis of data from the UKB (n {approx} 450, 000). Compared with commonly used state-of-the-art summary-based methods, SBayesR improved the prediction R2 by 4.1% relative to LDpred and by 28.7% relative to clumping and p-value thresholding. SBayesR gave comparable prediction accuracy to the recent RSS method, which has a similar model, but at a computational time that is two orders of magnitude smaller. The methodology is implemented in a very efficient and user-friendly software tool titled GCTB.

genetics↗

bioRxiv2019

Efficient estimation and applications of cross-validated genetic predictions

Large-scale cohorts with combined genetic and phenotypic data, coupled with methodological advances, have produced increasingly accurate genetic predictors of complex human phenotypes called polygenic risk scores (PRS). In addition to the potential translational impacts of identifying at-risk individuals, PRS are being utilized for a growing list of scientific applications including causal inference, identifying pleiotropy and genetic correlation, and powerful gene-based and mixed model association tests. Existing PRS approaches rely on external large-scale genetic cohorts that have also measured the phenotype of interest. They further require matching on ancestry and genotyping platform or imputation quality. In this work we present a novel reference-free method to produce PRS that does not rely on an external cohort. We show that naive implementations of reference-free PRS either result in substantial over-fitting or prohibitive increases in computational time. We show that our algorithm avoids both of these issues, and can produce informative in-sample PRS over any existing cohort without over-fitting. We then demonstrate several novel applications of reference-free PRS including detection of pleiotropy across 246 metabolic traits and efficient mixed-model association testing.

genetics↗

bioRxiv2019

Epidemic foci of hemorrhagic fever with renal syndrome in Shandong Province, China, based on patients, rodents and molecular epidemiology characteristics, 2012-2015

BackgroundHemorrhagic fever with renal syndrome (HFRS), an infectious disease caused by hantaviruses, is endemic in China and remains a serious public health problem. Historically, Shandong Province has had the largest HFRS burden in China. However, we do not have a comprehensive and clear understanding of the current epidemic foci of HFRS in Shandong Province.\n\nMethodology/Principal FindingsThe incidence and mortality rates were calculated, and a phylogenetic analysis was performed after laboratory testing of the virus in rodents. Spatial epidemiology analysis was applied to investigate the epidemic foci, including their sources. A total of 6,206 HFRS cases and 59 related deaths were reported in Shandong Province. The virus carriage rates of the rodents Rattus norvegicus, Apodemus agrarius and Mus musculus were 10.24%, 6.31% and 0.27%, respectively. The phylogenetic analysis indicated that two novel viruses isolated from R. norvegicus in Anqiu City and Qingzhou City were dissimilar to the other isolated strains, but closely related to strains previously isolated in northeastern China. Three epidemic foci were defined, two of which were derived from the Jining and Linyi epidemic foci, respectively, while the other was the residue of the Jining epidemic focus.\n\nConclusions/SignificanceThe southeastern and central Shandong Province are current key HFRS epidemic foci dominated by A. agrarius and R. norvegicus, respectively. Our study could help local departments to strengthen prevention and control measures in key areas to reduce the hazards of HFRS.\n\nAuthor summaryHemorrhagic fever with renal syndrome (HFRS) is a global infectious disease, which is still a serious public health threat in China today. The reported HFRS cases in Shandong Province accounted for approximate one third of total cases in the whole country. HFRS is a zoonosis mainly caused by Hantaan virus (HTNV) and Seoul virus (SEOV), which natural rodent hosts are A. agrarius and R. norvegicus, respectively. To explore the current HFRS epidemic foci based on patients, rodents and molecular epidemiology characteristics in Shandong Province, we collected the records of HFRS cases from whole province and the rodents captured in 14 surveillance sites. We found that the epidemic situation of HFRS is quiet different in temporal and spatial distribution. Three epidemic foci were defined based on patients, rodents and molecular epidemiology characteristics. The situation of HFRS epidemic foci in Shandong Province was clear. Our study provides a reference for relevant departments to develop key prevention strategies.

epidemiology↗

bioRxiv2019

Multi-locus characterization and phylogenetic inference of Leishmania spp. in snakes from Northwest China

BackgroundLeishmaniasis caused by protozoan parasite Leishmania is a neglected disease which is endemic in the northwest of China. Reptiles were considered to be the potential reservoir hosts for mammalian Leishmaniasis, and Leishmania had been detected in lizards from the epidemic area in the northwest of China. To date, few studies are focused on the natural infection of snakes with Leishmania.\n\nMethodsIn this study, 15 snakes captured from 10 endemic foci in the northwest of China were detected Leishmania spp. on the base of mitochondrial cytochrome b, heat shock protein 70 gene and ribosomal internal transcribed spacer 1 regions, and identified with phylogenetic and network analyses.\n\nResultIn total, Leishmania gene was found in 7 snakes. The phylogenetic inference trees and network analysis suggests that the species identification was confirmed as Leishmania donovani, Leishmania turanica and Leishmania sp.\n\nConclusionOur work is the first time to investigate the natural Leishmania spp. infection of snakes in the northwest of China. Mammalian Leishmania was discovered in snakes and the reptilian Leishmania was closely related to the clinical strains both prompt the importance of snakes in the disease cycle. To indicate the epidemiological involvement of snakes, a wide sample size in epidemic area and the pathogenic features of reptilian Leishmania promastigotes are recommended in the future research.

evolutionary biology↗

bioRxiv2018

Genetic analyses of medication-use and implications for precision medicine

It is common that one medication is prescribed for several indications, and conversely that several medications are prescribed for the same indication, suggesting a complex biological network for disease risk and its relationship with pharmacological function. Genome-wide association studies (GWASs) of medication-use may contribute to understanding of disease etiology, generation of new leads relevant for drug discovery and quantify prospects for precision medicine. We conducted GWAS to profile self-reported medication-use from 23 categories in approximately 320,000 individuals from the UK Biobank. A total of 505 independent genetic loci that met stringent criteria for statistical significance were identified. We investigated the implications of these GWAS findings in relation to biological mechanism, drug target identification and genetic risk stratification of disease. Amongst the medication-associated genes were 16 known therapeutic-effect target genes for medications from 9 categories.

genetics↗

bioRxiv2018

Repression of Transcription Factor AP-2 Alpha by Peroxisome Proliferator Activated Receptor Gamma Reveals a Novel Transcriptional Circuit in basal-squamous Bladder Cancer

The discovery of bladder cancer transcriptional subtypes provides an opportunity to identify high risk patients, and tailor disease management. Recent studies suggest tumor heterogeneity contributes to \"plasticity\" of molecular subtype during progression and following treatment. Nonetheless, the transcriptional drivers of the aggressive basal-squamous subtype remain unidentified. As PPAR{gamma} has been repeatedly implicated in the luminal subtype of bladder cancer, we hypothesized inactivation of this transcriptional master regulator during progression results in increased expression of basal-squamous specific transcription factors (TFs) which act to drive aggressive behavior. We initiated a pharmacologic and RNA-seq-based screen to identify PPAR{gamma}-repressed, basal-squamous specific TFs. Hierarchical clustering of RNA-seq data following treatment of a panel of human bladder cancer cell lines with a PPAR{gamma} agonist identified a number of TFs regulated by PPAR{gamma} activation, several of which are implicated in urothelial and squamous differentiation. One PPAR{gamma}-repressed TF implicated in squamous differentiation identified is Transcription Factor Activating Protein 2 alpha (TFAP2A). We show TFAP2A and its paralog TFAP2C are overexpressed in basal-squamous bladder cancer and in squamous areas of cystectomy samples, and that overexpression is associated with increased lymph node metastasis and distant recurrence, respectively. Biochemical analysis confirmed the ability of PPAR{gamma} activation to repress TFAP2A, while PPAR{gamma} antagonist studies indicate the requirement of a functional receptor. In vivo tissue recombination studies show TFAP2A and TFAP2C promote tumor growth in line with the aggressive nature of basal-squamous bladder cancer. Our findings suggest PPAR{gamma} inactivation, as well as TFAP2A and TFAP2C overexpression cooperate with other TFs to promote the basal-squamous transition.

cancer biology↗

bioRxiv2018

Novel susceptibility loci and genetic regulation mechanisms for type 2 diabetes

We conducted a meta-analysis of genome-wide association studies (GWAS) with [~]16 million genotyped/imputed genetic variants in 62,892 type 2 diabetes (T2D) cases and 596,424 controls of European ancestry. We identified 139 common and 4 rare (minor allele frequency < 0.01) variants associated with T2D, 42 of which (39 common and 3 rare variants) were independent of the known variants. Integration of the gene expression data from blood (n = 14,115 and 2,765) and other T2D-relevant tissues (n = up to 385) with the GWAS results identified 33 putative functional genes for T2D, three of which were targeted by approved drugs. A further integration of DNA methylation (n = 1,980) and epigenomic annotations data highlighted three putative T2D genes (CAMK1D, TP53INP1 and ATP5G1) with plausible regulatory mechanisms whereby a genetic variant exerts an effect on T2D through epigenetic regulation of gene expression. We further found evidence that the T2D-associated loci have been under purifying selection.

genetics↗

bioRxiv2018

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Understanding the difference in genetic regulation of gene expression between brain and blood is important for discovering genes associated with brain-related traits and disorders. Here, we estimate the correlation of genetic effects at the top associated cis-expression (cis-eQTLs or cis-mQTLs) between brain and blood for genes expressed (or CpG sites methylated) in both tissues, while accounting for errors in their estimated effects (rb). Using publicly available data (n = 72 to l,366), we find that the genetic effects of cis-eQTLs (PeQTL < 5x10-8) or mQTLs (PmQTL < 1x10-10) are highly correlated between independent brain and blood samples ([Formula] with SE = 0.015 for cis-eQTL and [Formula] with SE = 0.006 for cis-mQTLs). Using meta-analyzed brain eQTL/mQTL data (n = 526 to 1,194), we identify 61 genes and 167 DNA methylation (DNAm) sites associated with 4 brain-related traits and disorders. Most of these associations are a subset of the discoveries (97 genes and 295 DNAm sites) using data from blood with larger sample sizes (n = l,980 to 14,115). We further find that cis-eQTLs with tissue-specific effects are approximately uniformly distributed across all the functional annotation categories, and that mean difference in gene expression level between brain and blood is almost independent of the difference in the corresponding cis-eQTL effect. Our results demonstrate the gain of power in gene discovery for brain-related phenotypes using blood cis-eQTL or cis-mQTL data with large sample sizes.

genetics↗