The incidence of sexually dimorphic gene expression varies greatly between tissues in the rat

The role of Eif2s3y in mouse spermatogenesis

Eukaryotic translation initiation factor 2 subunit 3 and structural gene Y-linked (Eif2s3y) gene, the gene encoding eIF2γ protein, is located on the mouse Y chromosome short arm. The Eif2s3y gene is globally expressed in all tissues and plays an important role in regulating global and gene-specific mRNA translation initiation. During the process of protein translation initiation, Eif2s3x(its homolog) and Eif2s3y encoded eIF2γ perform similar functions. However, it has been noticed that Eif2s3y plays a crucial role in spermatogenesis, including spermatogonia mitosis, meiosis, and spermiogenesis of spermatids, which may account for infertility. In the period of spermatogenesis, the role of Eif2s3x and Eif2s3y are not equivalent. Importance of Eif2s3y has been observed in ESC and implicated in several aspects, including the pluripotency state and the proliferation rate. Here, we discuss the functional significance of Eif2s3y in mouse spermatogenesis and self-renewal of ESCs.

Cardiac cellularity is dependent upon biological sex and is regulated by gonadal hormones

AIMS

Sex differences have been consistently identified in cardiac physiology and incidence of cardiac disease. However, the underlying biological causes for the differences remain unclear. We sought to characterize the cardiac non-myocyte cellular landscape in female and male hearts to determine whether cellular proportion of the heart is sex-dependent and whether endocrine factors modulate the cardiac cell proportions.

METHODS AND RESULTS

Utilizing high-dimensional flow cytometry and immunofluorescence imaging, we found significant sex-specific differences in cellular composition of the heart in adult and juvenile mice, that develops postnatally. Removal of systemic gonadal hormones by gonadectomy results in rapid sex-specific changes in cardiac non-myocyte cellular proportions including alteration in resident mesenchymal cell and leucocyte populations, indicating gonadal hormones and their downstream targets regulate cardiac cellular composition. The ectopic reintroduction of oestrogen and testosterone to female and male mice, respectively, reverses many of these gonadectomy-induced compositional changes.

CONCLUSION

This work shows that the constituent cell types of the mouse heart are hormone-dependent and that the cardiac cellular landscapes are distinct in females and males, remain plastic, and can be rapidly modulated by endocrine factors. These observations have implications for strategies aiming to therapeutically alter cardiac cellular heterogeneity and underscore the importance of considering biological sex for studies examining cardiac physiology and stress responses.

Considering Sex as a Biological Variable in Basic and Clinical Studies: An Endocrine Society Scientific Statement

In May 2014, the National Institutes of Health (NIH) stated its intent to "require applicants to consider sex as a biological variable (SABV) in the design and analysis of NIH-funded research involving animals and cells." Since then, proposed research plans that include animals routinely state that both sexes/genders will be used; however, in many instances, researchers and reviewers are at a loss about the issue of sex differences. Moreover, the terms sex and gender are used interchangeably by many researchers, further complicating the issue. In addition, the sex or gender of the researcher might influence study outcomes, especially those concerning behavioral studies, in both animals and humans. The act of observation may change the outcome (the "observer effect") and any experimental manipulation, no matter how well-controlled, is subject to it. This is nowhere more applicable than in physiology and behavior. The sex of established cultured cell lines is another issue, in addition to aneuploidy; chromosomal numbers can change as cells are passaged. Additionally, culture medium contains steroids, growth hormone, and insulin that might influence expression of various genes. These issues often are not taken into account, determined, or even considered. Issues pertaining to the "sex" of cultured cells are beyond the scope of this Statement. However, we will discuss the factors that influence sex and gender in both basic research (that using animal models) and clinical research (that involving human subjects), as well as in some areas of science where sex differences are routinely studied. Sex differences in baseline physiology and associated mechanisms form the foundation for understanding sex differences in diseases pathology, treatments, and outcomes. The purpose of this Statement is to highlight lessons learned, caveats, and what to consider when evaluating data pertaining to sex differences, using 3 areas of research as examples; it is not intended to serve as a guideline for research design.

A comprehensive rat transcriptome built from large scale RNA-seq-based annotation

The rat is an important model organism in biomedical research for studying human disease mechanisms and treatments, but its annotated transcriptome is far from complete. We constructed a Rat Transcriptome Re-annotation named RTR using RNA-seq data from 320 samples in 11 different organs generated by the SEQC consortium. Totally, there are 52 807 genes and 114 152 transcripts in RTR. Transcribed regions and exons in RTR account for ∼42% and ∼6.5% of the genome, respectively. Of all 73 074 newly annotated transcripts in RTR, 34 213 were annotated as high confident coding transcripts and 24 728 as high confident long noncoding transcripts. Different tissues rather than different stages have a significant influence on the expression patterns of transcripts. We also found that 11 715 genes and 15 852 transcripts were expressed in all 11 tissues and that 849 house-keeping genes expressed different isoforms among tissues. This comprehensive transcriptome is freely available at http://www.unimd.org/rtr/. Our new rat transcriptome provides essential reference for genetics and gene expression studies in rat disease and toxicity models.

Tissue-specific sex differences in human gene expression

Despite extensive sex differences in human complex traits and disease, the male and female genomes differ only in the sex chromosomes. This implies that most sex-differentiated traits are the result of differences in the expression of genes that are common to both sexes. While sex differences in gene expression have been observed in a range of different tissues, the biological mechanisms for tissue-specific sex differences (TSSDs) in gene expression are not well understood. A total of 30 640 autosomal and 1021 X-linked transcripts were tested for heterogeneity in sex difference effect sizes in n = 617 individuals across 40 tissue types in Genotype-Tissue Expression (GTEx). This identified 65 autosomal and 66 X-linked TSSD transcripts (corresponding to unique genes) at a stringent significance threshold. Results for X-linked TSSD transcripts showed mainly concordant direction of sex differences across tissues and replicate previous findings. Autosomal TSSD transcripts had mainly discordant direction of sex differences across tissues. The top cis-expression quantitative trait loci (eQTLs) across tissues for autosomal TSSD transcripts are located a similar distance away from the nearest androgen and estrogen binding motifs and the nearest enhancer, as compared to cis-eQTLs for transcripts with stable sex differences in gene expression across tissue types. Enhancer regions that overlap top cis-eQTLs for TSSD transcripts, however, were found to be more dispersed across tissues. These observations suggest that androgen and estrogen regulatory elements in a cis region may play a common role in sex differences in gene expression, but TSSD in gene expression may additionally be due to causal variants located in tissue-specific enhancer regions.

Sex specific associations in genome wide association analysis of renal cell carcinoma

Renal cell carcinoma (RCC) has an undisputed genetic component and a stable 2:1 male to female sex ratio in its incidence across populations, suggesting possible sexual dimorphism in its genetic susceptibility. We conducted the first sex-specific genome-wide association analysis of RCC for men (3227 cases, 4916 controls) and women (1992 cases, 3095 controls) of European ancestry from two RCC genome-wide scans and replicated the top findings using an additional series of men (2261 cases, 5852 controls) and women (1399 cases, 1575 controls) from two independent cohorts of European origin. Our study confirmed sex-specific associations for two known RCC risk loci at 14q24.2 (DPF3) and 2p21(EPAS1). We also identified two additional suggestive male-specific loci at 6q24.3 (SAMD5, male odds ratio (ORmale) = 0.83 [95% CI = 0.78-0.89], Pmale = 1.71 × 10-8 compared with female odds ratio (ORfemale) = 0.98 [95% CI = 0.90-1.07], Pfemale = 0.68) and 12q23.3 (intergenic, ORmale = 0.75 [95% CI = 0.68-0.83], Pmale = 1.59 × 10-8 compared with ORfemale = 0.93 [95% CI = 0.82-1.06], Pfemale = 0.21) that attained genome-wide significance in the joint meta-analysis. Herein, we provide evidence of sex-specific associations in RCC genetic susceptibility and advocate the necessity of larger genetic and genomic studies to unravel the endogenous causes of sex bias in sexually dimorphic traits and diseases like RCC.

Machine learning applied to transcriptomic data to identify genes associated with feed efficiency in pigs

BACKGROUND

To date, the molecular mechanisms that underlie residual feed intake (RFI) in pigs are unknown. Results from different genome-wide association studies and gene expression analyses are not always consistent. The aim of this research was to use machine learning to identify genes associated with feed efficiency (FE) using transcriptomic (RNA-Seq) data from pigs that are phenotypically extreme for RFI.

METHODS

RFI was computed by considering within-sex regression on mean metabolic body weight, average daily gain, and average backfat gain. RNA-Seq analyses were performed on liver and duodenum tissue from 32 high and 33 low RFI pigs collected at 153 d of age. Machine-learning algorithms were used to predict RFI class based on gene expression levels in liver and duodenum after adjusting for batch effects. Genes were ranked according to their contribution to the classification using the permutation accuracy importance score in an unbiased random forest (RF) algorithm based on conditional inference. Support vector machine, RF, elastic net (ENET) and nearest shrunken centroid algorithms were tested using different subsets of the top rank genes. Nested resampling for hyperparameter tuning was implemented with tenfold cross-validation in the outer and inner loops.

RESULTS

The best classification was obtained with ENET using the expression of 200 genes in liver [area under the receiver operating characteristic curve (AUROC): 0.85; accuracy: 0.78] and 100 genes in duodenum (AUROC: 0.76; accuracy: 0.69). Canonical pathways and candidate genes that were previously reported as associated with FE in several species were identified. The most remarkable pathways and genes identified were NRF2-mediated oxidative stress response and aldosterone signalling in epithelial cells, the DNAJC6, DNAJC1, MAPK8, PRKD3 genes in duodenum, and melatonin degradation II, PPARα/RXRα activation, and GPCR-mediated nutrient sensing in enteroendocrine cells and SMOX, IL4I1, PRKAR2B, CLOCK and CCK genes in liver.

CONCLUSIONS

ML algorithms and RNA-Seq expression data were found to provide good performance for classifying pigs into high or low RFI groups. Classification was better with gene expression data from liver than from duodenum. Genes associated with FE in liver and duodenum tissue that can be used as predictive biomarkers for this trait were identified.

Evidence of sex-bias in gene expression in the brain transcriptome of two populations of rainbow trout (Oncorhynchus mykiss) with divergent life histories

Sex-bias in gene expression is a mechanism that can generate phenotypic variance between the sexes, however, relatively little is known about how patterns of sex-bias vary during development, and how variable sex-bias is between different populations. To that end, we measured sex-bias in gene expression in the brain transcriptome of rainbow trout (Oncorhynchus mykiss) during the first two years of development. Our sampling included from the fry stage through to when O. mykiss either migrate to the ocean or remain resident and undergo sexual maturation. Samples came from two F1 lines: One from migratory steelhead trout and one from resident rainbow trout. All samples were reared in a common garden environment and RNA sequencing (RNA-seq) was used to estimate patterns of gene expression. A total of 1,716 (4.6% of total) genes showed evidence of sex-bias in gene expression in at least one time point. The majority (96.7%) of sex-biased genes were differentially expressed during the second year of development, indicating that patterns of sex-bias in expression are tied to key developmental events, such as migration and sexual maturation. Mapping of differentially expressed genes to the O. mykiss genome revealed that the X chromosome is enriched for female upregulated genes, and this may indicate a lack of dosage compensation in rainbow trout. There were many more sex-biased genes in the migratory line than the resident line suggesting differences in patterns of gene expression in the brain between populations subjected to different forces of selection. Overall, our results suggest that there is considerable variation in the extent and identity of genes exhibiting sex-bias during the first two years of life. These differentially expressed genes may be connected to developmental differences between the sexes, and/or between adopting a resident or migratory life history.

Sex-specific differences in hypertension and associated cardiovascular disease

Although intrinsic mechanisms that regulate arterial blood pressure (BP) are similar in men and women, marked variations exist at the molecular, cellular and tissue levels. These physiological disparities between the sexes likely contribute to differences in disease onset, susceptibility, prevalence and treatment responses. Key systems that are important in the development of hypertension and cardiovascular disease (CVD), including the sympathetic nervous system, the renin-angiotensin-aldosterone system and the immune system, are differentially activated in males and females. Biological age also contributes to sexual dimorphism, as premenopausal women experience a higher degree of cardioprotection than men of similar age. Furthermore, sex hormones such as oestrogen and testosterone as well as sex chromosome complement likely contribute to sex differences in BP and CVD. At the cellular level, differences in cell senescence pathways may contribute to increased longevity in women and may also limit organ damage caused by hypertension. In addition, many lifestyle and environmental factors - such as smoking, alcohol consumption and diet - may influence BP and CVD in a sex-specific manner. Evidence suggests that cardioprotection in women is lost under conditions of obesity and type 2 diabetes mellitus. Treatment strategies for hypertension and CVD that are tailored according to sex could lead to improved outcomes for affected patients.

Autosomal genetic control of human gene expression does not differ across the sexes

BACKGROUND

Despite their nearly identical genomes, males and females differ in risk, incidence, prevalence, severity and age-at-onset of many diseases. Sexual dimorphism is also seen in human autosomal gene expression, and has largely been explored by examining the contribution of genotype-by-sex interactions to variation in gene expression.

RESULTS

In this study, we use data from a mixture of pedigree and unrelated individuals with verified European ancestry to investigate the sex-specific genetic architecture of gene expression measured in whole blood across n=1048 males and n=1005 females by treating gene expression intensities in the sexes as two distinct traits and estimating the genetic correlation (r _G) between them. These correlations measure the similarity of the combined additive genetic effects of all single-nucleotide polymorphisms across the autosomal chromosomes, and thus the level of common genetic control of gene expression across the sexes. Genetic correlations are estimated across the sexes for the expression levels of 12,528 autosomal gene expression probes using bivariate GREML, and tested for differences in autosomal genetic control of gene expression across the sexes. Overall, no deviation of the distribution of test statistics is observed from that expected under the null hypothesis of a common autosomal genetic architecture for gene expression across the sexes.

CONCLUSIONS

These results suggest that males and females share the same common genetic control of gene expression.