Gene Expression In Human Tissues Research Articles

Analysis of age-dependent gene-expression in human tissues for studying diabetes comorbidities

The study of the relationship between type 2 diabetes mellitus (T2DM) disease and other pathologies (comorbidities), together with patient age variation, poses a challenge for medical research. There is evidence that patients affected by T2DM are more likely to develop comorbidities as they grow older. Variation of gene expression can be correlated to changes in T2DM comorbidities insurgence and progression. Understanding gene expression changes requires the analysis of large heterogeneous data at different scales as well as the integration of different data sources into network medicine models. Hence, we designed a framework to shed light on uncertainties related to age effects and comorbidity by integrating existing data sources with novel algorithms. The framework is based on integrating and analysing existing data sources under the hypothesis that changes in the basal expression of genes may be responsible for the higher prevalence of comorbidities in older patients. Using the proposed framework, we selected genes related to comorbidities from existing databases, and then analysed their expression with age at the tissues level. We found a set of genes that changes significantly in certain specific tissues over time. We also reconstructed the associated protein interaction networks and the related pathways for each tissue. Using this mechanistic framework, we detected interesting pathways related to T2DM whose genes change their expression with age. We also found many pathways related to insulin regulation and brain activities, which can be used to develop specific therapies. To the best of our knowledge, this is the first study that analyses such genes at the tissue level together with age variations.

PSMD3 gene mutations cause pathological myopia

PurposeGenetic factors play a prominent role in the pathogenesis of pathological myopia (PM). However, the exact genetic mechanism of PM remains unclear. This study aimed to determine the candidate mutation...

CRISPR/Cas9-mediated mutations in both a cAMP response element and an ETS-binding site suppress FLT1 gene expression

The Fms-like tyrosine kinase-1 (FLT1) gene is expressed in various types of cells, including vascular endothelial cells and placental trophoblasts, and regulates angiogenesis, inflammation, and pregnancy. However, the basal transcriptional machinery of FLT1 is still not well understood. In this study, we first examined FLT1 promoter activity in three different types of cells, that is, trophoblast-derived cells, vascular endothelial-related cells, and HEK293 cells, using plasmid-based luciferase reporter assays, and showed that a cAMP-response element (CRE) and an ETS-binding site (EBS) are important for FLT1 expression in all cell types. To further examine the importance of these sites at the chromosomal level using HEK293 cells, we introduced CRISPR/Cas9-mediated mutations in these sites on the genomic DNA. HEK293 cells carrying these mutations clearly showed a significant decrease in endogenous FLT1 gene expression. These results suggest that CRE and EBS transcription regulatory elements are crucial for FLT1 gene expression in human tissues.

Distinct sets of olfactory receptors highly expressed in different human tissues evaluated by meta-transcriptome analysis: Association of OR10A6 in skin with keratinization.

Olfactory receptors (ORs) are expressed in many tissues and have multiple functions. However, most studies have focused on individual ORs. Here, we aimed to conduct a comprehensive meta-transcriptome analysis of OR gene expression in human tissues by using open-source tools to search a large, publicly available genotype-tissue expression (GTEx) data set. Analysis of RNA-seq data from GTEx revealed that OR expression patterns were tissue-dependent, and we identified distinct sets of ORs that were highly expressed in 12 tissues, involving 97 ORs in total. Among them, OR5P2, OR5P3 and OR10A6 were associated with skin. We further examined the roles of these ORs in skin by performing weighted gene correlation network analysis (WGCNA) and c3net analysis. WGCNA suggested that the three ORs are involved in epidermal differentiation and water-impermeable barrier homeostasis, and OR10A6 showed the largest gene sub-network in the c3net network. Immunocytochemical examination of human skin keratinocytes revealed a sparse expression pattern of OR10A6, suggesting that it is not uniformly distributed among all keratinocytes. An OR10A6 agonist, 3-phenylpropyl propionate (3PPP), transiently increased intracellular Ca2+ concentration and increased cornified envelope (CE) production in cultured keratinocytes. Knock-down of OR10A6 diminished the effect of 3PPP. Overall, integration of meta-transcriptome analysis and functional analysis uncovered distinct expression patterns of ORs in various human tissues, providing basic data for future studies of the biological functions of highly expressed ORs in individual tissues. Our results further suggest that expression of OR10A6 in skin is related to epidermal differentiation, and OR10A6 may be a potential target for modulation of keratinization.

SARS-CoV-2 infection impairs the insulin/IGF signaling pathway in the lung, liver, adipose tissue, and pancreatic cells via IRF1

BackgroundCOVID-19 can cause multiple organ damages as well as metabolic abnormalities such as hyperglycemia, insulin resistance, and new onset of diabetes. The insulin/IGF signaling pathway plays an important role in regulating energy metabolism and cell survival, but little is known about the impact of SARS-CoV-2 infection. The aim of this work was to investigate whether SARS-CoV-2 infection impairs the insulin/IGF signaling pathway in the host cell/tissue, and if so, the potential mechanism and association with COVID-19 pathology. MethodsTo determine the impact of SARS-CoV-2 on insulin/IGF signaling pathway, we utilized transcriptome datasets of SARS-CoV-2 infected cells and tissues from public repositories for a wide range of high-throughput gene expression data: autopsy lungs from COVID-19 patients compared to the control from non-COVID-19 patients; lungs from a human ACE2 transgenic mouse infected with SARS-CoV-2 compared to the control infected with mock; human pluripotent stem cell (hPSC)-derived liver organoids infected with SARS-CoV-2; adipose tissues from a mouse model of COVID-19 overexpressing human ACE2 via adeno-associated virus serotype 9 (AAV9) compared to the control GFP after SARS-CoV-2 infection; iPS-derived human pancreatic cells infected with SARS-CoV-2 compared to the mock control. Gain and loss of IRF1 function models were established in HEK293T and/or Calu3 cells to evaluate the impact on insulin signaling. To understand the mechanistic regulation and relevance with COVID-19 risk factors, such as older age, male sex, obesity, and diabetes, several transcriptomes of human respiratory, metabolic, and endocrine cells and tissue were analyzed. To estimate the association with COVID-19 severity, whole blood transcriptomes of critical patients with COVID-19 compared to those of hospitalized noncritical patients with COVID-19. ResultsWe found that SARS-CoV-2 infection impaired insulin/IGF signaling pathway genes, such as IRS, PI3K, AKT, mTOR, and MAPK, in the host lung, liver, adipose tissue, and pancreatic cells. The impairments were attributed to interferon regulatory factor 1 (IRF1), and its gene expression was highly relevant to risk factors for severe COVID-19; increased with aging in the lung, specifically in men; augmented by obese and diabetic conditions in liver, adipose tissue, and pancreatic islets. IRF1 activation was significantly associated with the impaired insulin signaling in human cells. IRF1 intron variant rs17622656-A, which was previously reported to be associated with COVID-19 prevalence, increased the IRF1 gene expression in human tissue and was frequently found in American and European population. Critical patients with COVID-19 exhibited higher IRF1 and lower insulin/IGF signaling pathway genes in the whole blood compared to hospitalized noncritical patients. Hormonal interventions, such as dihydrotestosterone and dexamethasone, ameliorated the pathological traits in SARS-CoV-2 infectable cells and tissues. ConclusionsThe present study provides the first scientific evidence that SARS-CoV-2 infection impairs the insulin/IGF signaling pathway in respiratory, metabolic, and endocrine cells and tissues. This feature likely contributes to COVID-19 severity with cell/tissue damage and metabolic abnormalities, which may be exacerbated in older, male, obese, or diabetic patients.

Discoveries in Pancreatic Physiology and Disease Biology Using Single-Cell RNA Sequencing

Transcriptome analysis is used to study gene expression in human tissues. It can promote the discovery of new therapeutic targets for related diseases by characterizing the endocrine function of pancreatic physiology and pathology, as well as the gene expression of pancreatic tumors. Compared to whole-tissue RNA sequencing, single-cell RNA sequencing (scRNA-seq) can detect transcriptional activity within a single cell. The scRNA-seq had an invaluable contribution to discovering previously unknown cell subtypes in normal and diseased pancreases, studying the functional role of rare islet cells, and studying various types of cells in diabetes as well as cancer. Here, we review the recent in vitro and in vivo advances in understanding the pancreatic physiology and pathology associated with single-cell sequencing technology, which may provide new insights into treatment strategy optimization for diabetes and pancreatic cancer.

Gene Expression of Angiotensin-Converting Enzyme 2 Receptor in Skin and the Implications for COVID-19.

Binding to the angiotensin-converting enzyme 2 (ACE2) receptor is a critical step for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to enter target cells. This enzyme is expressed in many human tissues including the lungs, but no research has demonstrated that SARS-CoV-2 can infect human skin or subcutaneous fat tissue, despite the increasing number of reported skin manifestations. The aim of this study was to investigate ACE2 gene expression in skin using a public database. A search of transcriptomic data sets from a public gene expression database to investigate ACE2 gene expression in human tissues. Human skin keratinocytes and basal cells express more ACE2 than lung epithelial cells. In contrast, both fibroblasts and melanocytes from human skin express less ACE2 than human lung epithelial cells. The high expression of ACE2 in keratinocytes and basal cells of human skin indicates that they may be directly susceptible to SARS-CoV-2 infection via the ACE2 receptor, especially in conditions of skin barrier dysfunction, and are therefore a potential target for the coronavirus.

Association of high level gene expression of ACE2 in adipose tissue with mortality of COVID-19 infection in obese patients

IntroductionObese patients have an increased risk of COVID-19 critical illness leading to ICU admission or death compared to normal weight individuals. SARS-CoV-2 binding to angiotensin-converting enzyme 2 (ACE2) receptor is a critical step mediate virus entry into target cells. Articles have alluded that the level of ACE2 gene expression in adipose tissue is higher than lung tissue, but a PubMed search found no results in articles to demonstrate this. The aim of this study was to investigate ACE2 gene expression in adipose tissue and lung tissue using a public database. Material and methodsA search of a public gene expression database to investigate ACE2 gene expression in human tissues. ResultsACE2 gene expression was present in both visceral and subcutaneous adipose tissues. The gene expression profile demonstrated that ACE2 gene expression was higher in human visceral and subcutaneous adipose tissues than human lung tissue. ConclusionThis study demonstrates that ACE2 gene expression is higher in visceral and subcutaneous adipose tissue than that in lung tissue, a major target tissue affected by SARS-CoV-2 infection. This suggests a mechanism by which excess adiposity may drive greater infection severity in patients with COVID-19.

Maternal stress in relation to sex-specific expression of placental genes involved in nutrient transport, oxygen tension, immune response, and the glucocorticoid barrier

IntroductionMurine models provide evidence that maternal stress during pregnancy can influence placenta morphology and function, including altered expression of genes involved in the maintenance and progression of pregnancy and fetal development. Corresponding research evaluating the impact of maternal stress on placental gene expression in humans is limited. We examined maternal stress in relation to placental expression of 17 candidate genes in a community-based sample. MethodsParticipants included 60 mother-newborn pairs enrolled in the PRogramming of Intergenerational Stress Mechanisms pregnancy cohort based at the Mount Sinai Hospital in New York City. Placentas were collected immediately following delivery and gene expression was measured using a qPCR-based platform. Maternal experiences of traumatic and non-traumatic stress were measured using the Life Stressor Checklist-Revised (LSC-R) administered during a mid-pregnancy interview. We used multivariable linear regression to examine associations between LSC-R scores and expression of each gene in separate models in the sample overall and stratified by fetal sex. ResultsHigher maternal stress was associated with significantly increased placental expression of the nutrient sensor gene OGT, the glucose transporter gene GLUT1, and the hypoxia sensor gene HIF3A. In models stratified by fetal sex, significant associations remained only among males. DiscussionThis study represents one of the most comprehensive examinations of maternal lifetime traumatic and non-traumatic stress in relation to placental gene expression in human tissue. Our findings support that maternal stress may alter sex-specific placental expression of genes involved in critical developmental processes.

Tissue- and Species-Specific Patterns of RNA metabolism in Post-Mortem Mammalian Retina and Retinal Pigment Epithelium

Accurate analysis of gene expression in human tissues using RNA sequencing is dependent on the quality of source material. One major source of variation in mRNA quality is post-mortem time. While it is known that individual transcripts show differential post-mortem stability, few studies have directly and comprehensively analyzed mRNA stability following death, and in particular the extent to which tissue- and species-specific factors influence post-mortem mRNA stability are poorly understood. This knowledge is particularly important for ocular tissues studies, where tissues obtained post-mortem are frequently used for research or therapeutic applications. To directly investigate this question, we profiled mRNA levels in both neuroretina and retinal pigment epithelium (RPE) from mouse and baboon over a series of post-mortem intervals. We found substantial changes in gene expression as early as 15 minutes in the mouse and as early as three hours in the baboon eye tissues. Importantly, our findings demonstrate both tissue- and species- specific patterns of RNA metabolism, by identifying a set of genes that are either rapidly degraded or very stable in both species and/or tissues. Taken together, the data from this study lay the foundation for understanding RNA regulation post-mortem and provide novel insights into RNA metabolism in the tissues of the mammalian eye.

The Translational Landscape of the Human Heart

Gene expression in human tissue has primarily been studied on the transcriptional level, largely neglecting translational regulation. Here, we analyze the translatomes of 80 human hearts to identify new translation events and quantify the effect of translational regulation. We show extensive translational control of cardiac gene expression, which is orchestrated in a process-specific manner. Translation downstream of predicted disease-causing protein-truncating variants appears to be frequent, suggesting inefficient translation termination. We identify hundreds of previously undetected microproteins, expressed from lncRNAs and circRNAs, for which we validate the protein products invivo. The translation of microproteins is not restricted to the heart and prominent in the translatomes of human kidney and liver. We associate these microproteins with diverse cellular processes and compartments and find thatmany locate to the mitochondria. Importantly, dozens of microproteins are translated from lncRNAs with well-characterized noncoding functions, indicating previously unrecognized biology.

Crohn's disease IRGM risk alleles are associated with altered gene expression in human tissues.

Crohn's disease (CD) is a chronic inflammatory gastrointestinal disorder. Genetic association studies have implicated dysregulated autophagy in CD. Among risk loci identified are a promoter single nucleotide polymorphism (SNP)( rs13361189 ) and two intragenic SNPs ( rs9637876 , rs10065172 ) in immunity-related GTPase family M ( IRGM) a gene that encodes a protein of the autophagy initiation complex. All three SNPs have been proposed to modify IRGM expression, but reports have been divergent and largely derived from cell lines. Here, analyzing RNA-Sequencing data of human tissues from the Genotype-Tissue Expression Project, we found that rs13361189 minor allele carriers had reduced IRGM expression in whole blood and terminal ileum, and upregulation in ileum of ZNF300P1, a locus adjacent to IRGM on chromosome 5q33.1 that encodes a long noncoding RNA. Whole blood and ileum from minor allele carriers had altered expression of multiple additional genes that have previously been linked to colitis and/or autophagy. Notable among these was an increase in ileum of LTF (lactoferrin), an established fecal inflammatory biomarker of CD, and in whole blood of TNF, a key cytokine in CD pathogenesis. Last, we confirmed that risk alleles at all three loci associated with increased risk for CD but not ulcerative colitis in a case-control study. Taken together, our findings suggest that genetically encoded IRGM deficiency may predispose to CD through dysregulation of inflammatory gene networks. Gene expression profiling of disease target tissues in genetically susceptible populations is a promising strategy for revealing new leads for the study of molecular pathogenesis and, potentially, for precision medicine. NEW & NOTEWORTHY Single nucleotide polymorphisms in immunity-related GTPase family M ( IRGM), a gene that encodes an autophagy initiation protein, have been linked epidemiologically to increased risk for Crohn's disease (CD). Here, we show for the first time that subjects with risk alleles at two such loci, rs13361189 and rs10065172 , have reduced IRGM expression in whole blood and terminal ileum, as well as dysregulated expression of a wide array of additional genes that regulate inflammation and autophagy.

The thanatotranscriptome: Gene expression of male reproductive organs after death

The prostate gland is one of the last internal organs to deteriorate during human decomposition; however, this phenomenon is still mysterious. Gene expression in antemortem cases has been widely studied and a majority of the analyses concentrate on discovering basic physiological processes. The question of “What happens to gene expression after a human dies?” is a novel and emerging topic. Thanatotranscriptome (thanatos-, Greek for death) involves research on mRNA transcript abundances and gene expression in human tissues after death. Our previous studies have shown that RNA is a suitable and stable molecule in postmortem liver samples up to two days. Consequently, we hypothesized that there are also measurable and significant differences in mRNA transcript abundances in prostate tissues from human remains. In the current study, the goal was to identify apoptotic molecular markers (i.e., pro- and/or anti-apoptosis genes) that provide accurate gene expression profiles regarding the time of death.Tissue samples were removed by a medical examiner from the prostate of five cadavers during autopsy. After RNA extraction, cDNA was synthesized and the concentration was determined. The cDNA was reacted in apoptosis-related gene expression profiling by human PCR Array. The PCR Array results showed that at 38 h after death, a majority of the genes for apoptosis induction and positive regulation (i.e., caspases) were over-expressed more than at five days. The expression of anti-apoptotic genes such as BAG1, BCL2, and negative regulator of apoptosis, XIAP, was significantly elevated in a time-dependent manner. However, pro-apoptotic gene expression such as TP53 and TNFSF10 was not significantly upregulated.Therefore, postmortem prostate cells counteract programmed cell death with its anti-apoptotic machinery; yet as time progresses, pro-apoptotic mechanisms dominate. In conclusion, our study implies that over-expression of genes in male reproductive organs still occurs during decomposition, which may play substantial roles in forensic research and clinical application. These findings demonstrate that there is still active postmortem gene expression; however, our future research question will be, “When does gene expression terminate after death?”

Regulatory and evolutionary signatures of sex-biased genes on both the X chromosome and the autosomes

BackgroundSex is an important but understudied factor in the genetics of human diseases. Analyses using a combination of gene expression data, ENCODE data, and evolutionary data of sex-biased gene expression in human tissues can give insight into the regulatory and evolutionary forces acting on sex-biased genes.MethodsIn this study, we analyzed the differentially expressed genes between males and females. On the X chromosome, we used a novel method and investigated the status of genes that escape X-chromosome inactivation (escape genes), taking into account the clonality of lymphoblastoid cell lines (LCLs). To investigate the regulation of sex-biased differentially expressed genes (sDEG), we conducted pathway and transcription factor enrichment analyses on the sDEGs, as well as analyses on the genomic distribution of sDEGs. Evolutionary analyses were also conducted on both sDEGs and escape genes.ResultsGenome-wide, we characterized differential gene expression between sexes in 462 RNA-seq samples and identified 587 sex-biased genes, or 3.2% of the genes surveyed. On the X chromosome, sDEGs were distributed in evolutionary strata in a similar pattern as escape genes. We found a trend of negative correlation between the gene expression breadth and nonsynonymous over synonymous mutation (dN/dS) ratios, showing a possible pleiotropic constraint on evolution of genes. Genome-wide, nine transcription factors were found enriched in binding to the regions surrounding the transcription start sites of female-biased genes. Many pathways and protein domains were enriched in sex-biased genes, some of which hint at sex-biased physiological processes.ConclusionsThese findings lend insight into the regulatory and evolutionary forces shaping sex-biased gene expression and their involvement in the physiological and pathological processes in human health and diseases.

Public data mining plus domestic experimental study defined involvement of the old-yet-uncharacterized gene matrix-remodeling associated 7 (MXRA7) in physiopathology of the eye

Matrix-remodeling associated 7 (MXRA7) gene was first reported in 2002 and named so for its co-expression with several genes known to relate with matrix-remodeling. However, not any studies had been intentionally performed to characterize this gene. We started defining the functions of MXRA7 by integrating bioinformatics analysis and experimental study. Data mining of MXRA7 expression in BioGPS, Gene Expression Omnibus and EurExpress platforms highlighted high level expression of Mxra7 in murine ocular tissues. Real-time PCR was employed to measure Mxra7 mRNA in tissues of adult C57BL/6 mice and demonstrated that Mxra7 was preferentially expressed at higher level in retina, corneas and lens than in other tissues. Then the inflammatory corneal neovascularization (CorNV) model and fungal corneal infections were induced in Balb/c mice, and mRNA levels of Mxra7 as well as several matrix-remodeling related genes (Mmp3, Mmp13, Ecm1, Timp1) were monitored with RT-PCR. The results demonstrated a time-dependent Mxra7 under-expression pattern (U-shape curve along timeline), while all other matrix-remodeling related genes manifested an opposite changes pattern (dome-shape curve). When limited data from BioGPS concerning human MXRA7 gene expression in human tissues were looked at, it was found that ocular tissue was also the one expressing highest level of MXRA7. To conclude, integrative assay of MXRA7 gene expression in public databank as well as domestic animal models revealed a selective high expression MXRA7 in murine and human ocular tissues, and its change patterns in two corneal disease models implied that MXRA7 might play a role in pathological processes or diseases involving injury, neovascularization and would healing.

Prediction of gene expression with cis-SNPs using mixed models and regularization methods

BackgroundIt has been shown that gene expression in human tissues is heritable, thus predicting gene expression using only SNPs becomes possible. The prediction of gene expression can offer important implications on the genetic architecture of individual functional associated SNPs and further interpretations of the molecular basis underlying human diseases.MethodsWe compared three types of methods for predicting gene expression using only cis-SNPs, including the polygenic model, i.e. linear mixed model (LMM), two sparse models, i.e. Lasso and elastic net (ENET), and the hybrid of LMM and sparse model, i.e. Bayesian sparse linear mixed model (BSLMM). The three kinds of prediction methods have very different assumptions of underlying genetic architectures. These methods were evaluated using simulations under various scenarios, and were applied to the Geuvadis gene expression data.ResultsThe simulations showed that these four prediction methods (i.e. Lasso, ENET, LMM and BSLMM) behaved best when their respective modeling assumptions were satisfied, but BSLMM had a robust performance across a range of scenarios. According to R2 of these models in the Geuvadis data, the four methods performed quite similarly. We did not observe any clustering or enrichment of predictive genes (defined as genes with R2 ≥ 0.05) across the chromosomes, and also did not see there was any clear relationship between the proportion of the predictive genes and the proportion of genes in each chromosome. However, an interesting finding in the Geuvadis data was that highly predictive genes (e.g. R2 ≥ 0.30) may have sparse genetic architectures since Lasso, ENET and BSLMM outperformed LMM for these genes; and this observation was validated in another gene expression data. We further showed that the predictive genes were enriched in approximately independent LD blocks.ConclusionsGene expression can be predicted with only cis-SNPs using well-developed prediction models and these predictive genes were enriched in some approximately independent LD blocks. The prediction of gene expression can shed some light on the functional interpretation for identified SNPs in GWASs.

QRank: a novel quantile regression tool for eQTL discovery.

Over the past decade, there has been a remarkable improvement in our understanding of the role of genetic variation in complex human diseases, especially via genome-wide association studies. However, the underlying molecular mechanisms are still poorly characterized, impending the development of therapeutic interventions. Identifying genetic variants that influence the expression level of a gene, i.e. expression quantitative trait loci (eQTLs), can help us understand how genetic variants influence traits at the molecular level. While most eQTL studies focus on identifying mean effects on gene expression using linear regression, evidence suggests that genetic variation can impact the entire distribution of the expression level. Motivated by the potential higher order associations, several studies investigated variance eQTLs. In this paper, we develop a Quantile Rank-score based test (QRank), which provides an easy way to identify eQTLs that are associated with the conditional quantile functions of gene expression. We have applied the proposed QRank to the Genotype-Tissue Expression project, an international tissue bank for studying the relationship between genetic variation and gene expression in human tissues, and found that the proposed QRank complements the existing methods, and identifies new eQTLs with heterogeneous effects across different quantile levels. Notably, we show that the eQTLs identified by QRank but missed by linear regression are associated with greater enrichment in genome-wide significant SNPs from the GWAS catalog, and are also more likely to be tissue specific than eQTLs identified by linear regression. An R package is available on R CRAN at https://cran.r-project.org/web/packages/QRank . xs2148@cumc.columbia.edu. Supplementary data are available at Bioinformatics online.

Large Scale Gene Expression Meta-Analysis Reveals Tissue-Specific, Sex-Biased Gene Expression in Humans.

The severity and prevalence of many diseases are known to differ between the sexes. Organ specific sex-biased gene expression may underpin these and other sexually dimorphic traits. To further our understanding of sex differences in transcriptional regulation, we performed meta-analyses of sex biased gene expression in multiple human tissues. We analyzed 22 publicly available human gene expression microarray data sets including over 2500 samples from 15 different tissues and 9 different organs. Briefly, by using an inverse-variance method we determined the effect size difference of gene expression between males and females. We found the greatest sex differences in gene expression in the brain, specifically in the anterior cingulate cortex, (1818 genes), followed by the heart (375 genes), kidney (224 genes), colon (218 genes), and thyroid (163 genes). More interestingly, we found different parts of the brain with varying numbers and identity of sex-biased genes, indicating that specific cortical regions may influence sexually dimorphic traits. The majority of sex-biased genes in other tissues such as the bladder, liver, lungs, and pancreas were on the sex chromosomes or involved in sex hormone production. On average in each tissue, 32% of autosomal genes that were expressed in a sex-biased fashion contained androgen or estrogen hormone response elements. Interestingly, across all tissues, we found approximately two-thirds of autosomal genes that were sex-biased were not under direct influence of sex hormones. To our knowledge this is the largest analysis of sex-biased gene expression in human tissues to date. We identified many sex-biased genes that were not under the direct influence of sex chromosome genes or sex hormones. These may provide targets for future development of sex-specific treatments for diseases.

Imputing Gene Expression in Uncollected Tissues Within and Beyond GTEx

Gene expression and its regulation can vary substantially across tissue types. In order to generate knowledge about gene expression in human tissues, the Genotype-Tissue Expression (GTEx) program has collected transcriptome data in a wide variety of tissue types from post-mortem donors. However, many tissue types are difficult to access and are not collected in every GTEx individual. Furthermore, in non-GTEx studies, the accessibility of certain tissue types greatly limits the feasibility and scale of studies of multi-tissue expression. In this work, we developed multi-tissue imputation methods to impute gene expression in uncollected or inaccessible tissues. Via simulation studies, we showed that the proposed methods outperform existing imputation methods in multi-tissue expression imputation and that incorporating imputed expression data can improve power to detect phenotype-expression correlations. By analyzing data from nine selected tissue types in the GTEx pilot project, we demonstrated that harnessing expression quantitative trait loci (eQTLs) and tissue-tissue expression-level correlations can aid imputation of transcriptome data from uncollected GTEx tissues. More importantly, we showed that by using GTEx data as a reference, one can impute expression levels in inaccessible tissues in non-GTEx expression studies.

Modulation of Aromatase by Phytoestrogens.

The aromatase enzyme catalyzes the conversion of androgens to estrogens in many human tissues. Estrogens are known to stimulate cellular proliferation associated with certain cancers and protect against adverse symptoms during the peri- and postmenopausal intervals. Phytoestrogens are a group of plant derived naturally occurring compounds that have chemical structures similar to estrogen. Since phytoestrogens are known to be constituents of animal/human food sources, these compounds have received increased research attention. Phytoestrogens may contribute to decreased cancer risk by the inhibition of aromatase enzyme activity and CYP19 gene expression in human tissues. This review covers (a) the aromatase enzyme (historical descriptions on function, activity, and gene characteristics), (b) phytoestrogens in their classifications and applications to human health, and (c) a chronological coverage of aromatase activity modulated by phytoestrogens from the early 1980s to 2015. In general, phytoestrogens act as aromatase inhibitors by (a) decreasing aromatase gene expression, (b) inhibiting the aromatase enzyme itself, or (c) in some cases acting at both levels of regulation. The findings presented herein are consistent with estrogen's impact on health and phytoestrogen's potential as anticancer treatments, but well-controlled, large-scale studies are warranted to determine the effectiveness of phytoestrogens on breast cancer and age-related diseases.