Searching across-cohort relatives in 54,092 GWAS samples via encrypted genotype regression.

Explicitly sharing individual level data in genomics studies has many merits comparing to sharing summary statistics, including more strict QCs, common statistical analyses, relative identification and improved statistical power in GWAS, but it is hampered by privacy or ethical constraints. In this study, we developed encG-reg, a regression approach that can detect relatives of various degrees based on encrypted genomic data, which is immune of ethical constraints. The encryption properties of encG-reg are based on the random matrix theory by masking the original genotypic matrix without sacrificing precision of individual-level genotype data. We established a connection between the dimension of a random matrix, which masked genotype matrices, and the required precision of a study for encrypted genotype data. encG-reg has false positive and false negative rates equivalent to sharing original individual level data, and is computationally efficient when searching relatives. We split the UK Biobank into their respective centers, and then encrypted the genotype data. We observed that the relatives estimated using encG-reg was equivalently accurate with the estimation by KING, which is a widely used software but requires original genotype data. In a more complex application, we launched a finely devised multi-center collaboration across 5 research institutes in China, covering 9 cohorts of 54,092 GWAS samples. encG-reg again identified true relatives existing across the cohorts with even different ethnic backgrounds and genotypic qualities. Our study clearly demonstrates that encrypted genomic data can be used for data sharing without loss of information or data sharing barrier.

Single-cell RNA-seq data analysis reveals functionally relevant biomarkers of early brain development and their regulatory footprints in human embryonic stem cells (hESCs).

The complicated process of neuronal development is initiated early in life, with the genetic mechanisms governing this process yet to be fully elucidated. Single-cell RNA sequencing (scRNA-seq) is a potent instrument for pinpointing biomarkers that exhibit differential expression across various cell types and developmental stages. By employing scRNA-seq on human embryonic stem cells, we aim to identify differentially expressed genes (DEGs) crucial for early-stage neuronal development. Our focus extends beyond simply identifying DEGs. We strive to investigate the functional roles of these genes through enrichment analysis and construct gene regulatory networks to understand their interactions. Ultimately, this comprehensive approach aspires to illuminate the molecular mechanisms and transcriptional dynamics governing early human brain development. By uncovering potential links between these DEGs and intelligence, mental disorders, and neurodevelopmental disorders, we hope to shed light on human neurological health and disease. In this study, we have used scRNA-seq to identify DEGs involved in early-stage neuronal development in hESCs. The scRNA-seq data, collected on days 26 (D26) and 54 (D54), of the in vitro differentiation of hESCs to neurons were analyzed. Our analysis identified 539 DEGs between D26 and D54. Functional enrichment of those DEG biomarkers indicated that the up-regulated DEGs participated in neurogenesis, while the down-regulated DEGs were linked to synapse regulation. The Reactome pathway analysis revealed that down-regulated DEGs were involved in the interactions between proteins located in synapse pathways. We also discovered interactions between DEGs and miRNA, transcriptional factors (TFs) and DEGs, and between TF and miRNA. Our study identified 20 significant transcription factors, shedding light on early brain development genetics. The identified DEGs and gene regulatory networks are valuable resources for future research into human brain development and neurodevelopmental disorders.

Comparative and functional analysis unveils the contribution of photoperiod to DNA methylation, sRNA accumulation, and gene expression variations in short-day and long-day grasses.

Photoperiod employs complicated networks to regulate various developmental processes in plants, including flowering transition. However, the specific mechanisms by which photoperiod affects epigenetic modifications and gene expression variations in plants remain elusive. In this study, we conducted a comprehensive analysis of DNA methylation, small RNA (sRNA) accumulation, and gene expressions under different daylengths in facultative long-day (LD) grass Brachypodium distachyon and short-day (SD) grass rice. Our results showed that while overall DNA methylation levels were minimally affected by different photoperiods, CHH methylation levels were repressed under their favorable light conditions, particularly in rice. We identified numerous differentially methylated regions (DMRs) that were influenced by photoperiod in both plant species. Apart from differential sRNA clusters, we observed alterations in the expression of key components of the RNA-directed DNA methylation pathway, DNA methyltransferases, and demethylases, which may contribute to the identified photoperiod-influenced CHH DMRs. Furthermore, we identified many differentially expressed genes in response to different daylengths, some of which were associated with the DMRs. Notably, we discovered a photoperiod-responsive gene MYB11 in the transcriptome of B. distachyon, and further demonstrated its role as a flowering inhibitor by repressing FT1 transcription. Together, our comparative and functional analysis sheds light on the effects of daylength on DNA methylation, sRNA accumulation, and gene expression variations in LD and SD plants, thereby facilitating better designing breeding programs aimed at developing high-yield crops that can adapt to local growing seasons.

Identification of reliable QTLs and designed QTL breeding for grain shape and milling quality in the reciprocal introgression lines in rice.

Milling quality (MQ) and grain shape (GS) of rice (Oryza sativa L.) are correlated traits, both determine farmers' final profit. More than one population under multiple environments may provide valuable information for breeding selection on these MQ-GS correlations. However, suitable analytical methods for reciprocal introgression lines with linkage map for this kind of correlation remains unclear. In this study, our major tasks were (1) to provide a set of reciprocal introgression lines (composed of two BC2RIL populations) suitable for mapping by linkage mapping using markers/bins with physical positions; (2) to test the mapping effects of different methods by using MQ-GS correlation dissection as sample case; (3) to perform genetic and breeding simulation on pyramiding favorite alleles of QTLs for representative MQ-GS traits. Finally, with four analysis methods and data collected under five environments, we identified about 28.4 loci on average for MQ-GS traits. Notably, 52.3% of these loci were commonly detected by different methods and eight loci were novel. There were also nine regions harboring loci for different MQ-GS traits which may be underlying the MQ-GS correlations. Background independent (BI) loci were also found for each MQ and GS trait. All these information may provide useful resources for rice molecular breeding.

WMDS.net: a network control framework for identifying key players in transcriptome programs.

MOTIVATION: Mammalian cells can be transcriptionally reprogramed to other cellular phenotypes. Controllability of such complex transitions in transcriptional networks underlying cellular phenotypes is an inherent biological characteristic. This network controllability can be interpreted by operating a few key regulators to guide the transcriptional program from one state to another. Finding the key regulators in the transcriptional program can provide key insights into the network state transition underlying cellular phenotypes. RESULTS: To address this challenge, here, we proposed to identify the key regulators in the transcriptional co-expression network as a minimum dominating set (MDS) of driver nodes that can fully control the network state transition. Based on the theory of structural controllability, we developed a weighted MDS network model (WMDS.net) to find the driver nodes of differential gene co-expression networks. The weight of WMDS.net integrates the degree of nodes in the network and the significance of gene co-expression difference between two physiological states into the measurement of node controllability of the transcriptional network. To confirm its validity, we applied WMDS.net to the discovery of cancer driver genes in RNA-seq datasets from The Cancer Genome Atlas. WMDS.net is powerful among various cancer datasets and outperformed the other top-tier tools with a better balance between precision and recall. AVAILABILITY AND IMPLEMENTATION: https://github.com/chaofen123/WMDS.net. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The menin-MLL1 interaction is a molecular dependency in NUP98-rearranged AML.

Translocations involving the NUP98 gene produce NUP98-fusion proteins and are associated with a poor prognosis in acute myeloid leukemia (AML). MLL1 is a molecular dependency in NUP98-fusion leukemia, and therefore we investigated the efficacy of therapeutic blockade of the menin-MLL1 interaction in NUP98-fusion leukemia models. Using mouse leukemia cell lines driven by NUP98-HOXA9 and NUP98-JARID1A fusion oncoproteins, we demonstrate that NUP98-fusion-driven leukemia is sensitive to the menin-MLL1 inhibitor VTP50469, with an IC50 similar to what we have previously reported for MLL-rearranged and NPM1c leukemia cells. Menin-MLL1 inhibition upregulates markers of differentiation such as CD11b and downregulates expression of proleukemogenic transcription factors such as Meis1 in NUP98-fusion-transformed leukemia cells. We demonstrate that MLL1 and the NUP98 fusion protein itself are evicted from chromatin at a critical set of genes that are essential for the maintenance of the malignant phenotype. In addition to these in vitro studies, we established patient-derived xenograft (PDX) models of NUP98-fusion-driven AML to test the in vivo efficacy of menin-MLL1 inhibition. Treatment with VTP50469 significantly prolongs survival of mice engrafted with NUP98-NSD1 and NUP98-JARID1A leukemias. Gene expression analysis revealed that menin-MLL1 inhibition simultaneously suppresses a proleukemogenic gene expression program, including downregulation of the HOXa cluster, and upregulates tissue-specific markers of differentiation. These preclinical results suggest that menin-MLL1 inhibition may represent a rational, targeted therapy for patients with NUP98-rearranged leukemias.

The role of macrophage polarization and related key molecules in pulmonary inflammation and fibrosis induced by coal dust dynamic inhalation exposure in Sprague-Dawley rats.

Coal dust is the main occupational hazard factor during coal mining operations. This study aimed to investigate the role of macrophage polarization and its molecular regulatory network in lung inflammation and fibrosis in Sprague-Dawley rats caused by coal dust exposure. Based on the key exposure parameters (exposure route, dose and duration) of the real working environment of coal miners, the dynamic inhalation exposure method was employed, and a control group and three coal dust groups (4, 10 and 25 mg/m3) were set up. Lung function was measured after 30, 60 and 90 days of coal dust exposure. Meanwhile, the serum, lung tissue and bronchoalveolar lavage fluid were collected after anesthesia for downstream experiments (histopathological analysis, RT-qPCR, ELISA, etc.). The results showed that coal dust exposure caused stunted growth, increased lung organ coefficient and decreased lung function in rats. The expression level of the M1 macrophage marker iNOS was significantly upregulated in the early stage of exposure and was accompanied by higher expression of the inflammatory cytokines TNF-α, IL-1ß, IL-6 and the chemokines IL-8, CCL2 and CCL5, with the most significant trend of CCL5 mRNA in lung tissues. Expression of the M2 macrophage marker Arg1 was significantly upregulated in the mid to late stages of coal dust exposure and was accompanied by higher expression of the anti-inflammatory cytokines IL-10 and TGF-ß. In conclusion, macrophage polarization and its molecular regulatory network (especially CCL5) play an important role in lung inflammation and fibrosis in SD rats exposed to coal dust by dynamic inhalation.

Hsa-miR-379 down-regulates Rac1/MLK3/JNK/AP-1/Collagen I cascade reaction by targeting connective tissue growth factor in human alveolar basal epithelial A549 cells.

OBJECTIVE: This study was aimed to screen and identify miRNAs that could regulate human CTGF gene and downstream cascade reaction Rac1/MLK3/JNK/AP-1/Collagen I by bioinformatics and experimental means. METHODS: TargetScan and Tarbase were used to predict miRNAs that may have regulatory effects on human CTGF gene. The dual-luciferase reporter gene assay was employed to verify the results obtained in bioinformatics. Human alveolar basal epithelial A549 cells were exposed to silica (SiO2) culture medium for 24 h to establish an in vitro model of pulmonary fibrosis, and bleomycin (BLM) of 100 ng/mL was used as a positive control. The miRNA and mRNA expression levels were determined by RT-qPCR, and the protein levels were measured by western blot in hsa-miR-379-3p overexpression group or not. RESULTS: A total of 9 differentially expressed miRNAs that might regulate the human CTGF gene were predicted. Hsa-miR-379-3p and hsa-miR-411-3p were selected for the subsequent experiments. The results of the dual-luciferase reporter assay showed that hsa-miR-379-3p could bind to CTGF, but hsa-miR-411-3p could not. Compared with the control group, SiO2 exposure (25 and 50 µg/mL) could significantly reduce the expression level of hsa-miR-379-3p in A549 cells. SiO2 exposure (50 µg/mL) could significantly increase the mRNA expression levels of CTGF, Collagen I, Rac1, MLK3, JNK, AP1, and VIM in A549 cells, while CDH1 level was significantly decreased. Compared with SiO2 + NC group, the mRNA expression levels of CTGF, Collagen I, Rac1, MLK3, JNK, AP1, and VIM were significantly decreased, and CDH1 level was significantly higher when hsa-miR-379-3p was overexpressed. At the same time, overexpression of hsa-miR-379-3p improved the protein levels of CTGF, Collagen I, c-Jun and phospho-c-Jun, JNK1 and phospho-JNK1 significantly compared with SiO2 + NC group. CONCLUSION: Hsa-miR-379-3p was demonstrated for the first time that could directly target and down-regulate human CTGF gene, and further affect the expression levels of key genes and proteins in Rac1/MLK3/JNK/AP-1/Collagen I cascade reaction.

Ferroptosis-associated lncRNA prognostic signature predicts prognosis and immune response in laryngeal squamous carcinoma.

In order to construct a prognostic model of ferroptosis-related lncRNA associated with laryngeal carcinoma and to investigate its prognostic value, RNA sequencing, genomic mutation, and clinical data of laryngeal squamous carcinoma patients were collected from the TCGA database. Patients were randomly divided into train and test groups. Cox regression analysis and lasso regression analysis were performed on the data of patients in the training group, and their independent prognostic effect was validated in the test group and the whole cohort. Data from 123 laryngeal squamous carcinoma patients in the TCGA database were collected. According to previous literature, 484 ferroptosis-related genes were collected, and 912 ferroptosis-related lncRNAs were obtained by co-expression. Cox models suggested six lncRNAs involved in ferroptosis (AC083862.2, CYTOR, AC114296.1, LINC02768, GATA2-AS1, CTB-178M22.2). Patients were divided into high-risk and low-risk groups based on median risk scores. Kapkan-Meier survival curve results showed a statistical difference in survival between the high- and low-risk groups. Receiver operating characteristic curves and principal component analysis demonstrated the high accuracy of the model. Univariate and multifactorial Cox regression analyses and column plots demonstrated risk scores as independent prognostic factors. The distribution of prognostic marker risk scores was correlated with clinical staging. Immune infiltration studies suggested the model was associated with immune checkpoints and multiple immune functions. GATA2-AS1 was able to promote cell proliferation, cell migration, and cell invasion. This study identified six lncRNAs associated with ferroptosis in laryngeal squamous carcinoma as prognostic predictors, which may be promising biomarkers involved in the treatment of laryngeal squamous carcinoma.

Development of a double shmiR lentivirus effectively targeting both BCL11A and ZNF410 for enhanced induction of fetal hemoglobin to treat ß-hemoglobinopathies.

A promising treatment for ß-hemoglobinopathies is the de-repression of γ-globin expression leading to increased fetal hemoglobin (HbF) by targeting BCL11A. Here, we aim to improve a lentivirus vector (LV) containing a single BCL11A shmiR (SS) to further increase γ-globin induction. We engineered a novel LV to express two shmiRs simultaneously targeting BCL11A and the γ-globin repressor ZNF410. Erythroid cells derived from human HSCs transduced with the double shmiR (DS) showed up to a 70% reduction of both BCL11A and ZNF410 proteins. There was a consistent and significant additional 10% increase in HbF compared to targeting BCL11A alone in erythroid cells. Erythrocytes differentiated from SCD HSCs transduced with the DS demonstrated significantly reduced in vitro sickling phenotype compared to the SS. Erythrocytes differentiated from transduced HSCs from ß-thalassemia major patients demonstrated improved globin chain balance by increased γ-globin with reduced microcytosis. Reconstitution of DS-transduced cells from Berkeley SCD mice was associated with a statistically larger reduction in peripheral blood hemolysis markers compared with the SS vector. Overall, these results indicate that the DS LV targeting BCL11A and ZNF410 can enhance HbF induction for treating ß-hemoglobinopathies and could be used as a model to simultaneously and efficiently target multiple gene products.

Unique regulatory roles of ncRNAs changed by PM2.5 in human diseases.

PM2.5 is a type of particulate matter with an aerodynamic diameter smaller than 2.5 µm, and exposure to PM2.5 can adversely damage human health. PM2.5 may impair health through oxidative stress, inflammatory reactions, immune function alterations and chromosome or DNA damage. Through increasing in-depth studies, researchers have found that noncoding RNAs (ncRNAs), particularly microRNAs (miRNAs), circular RNAs (circRNAs) as well as long noncoding RNAs (lncRNAs), might play significant roles in PM2.5-related human diseases via some of the abovementioned mechanisms. Therefore, in this review, we mainly discuss the regulatory function of ncRNAs altered by PM2.5 in human diseases and summarize the potential molecular mechanisms. The findings reveal that these ncRNAs might induce or promote diseases via inflammation, the oxidative stress response, cell autophagy, apoptosis, cell junction damage, altered cell proliferation, malignant cell transformation, disruption of synaptic function and abnormalities in the differentiation and status of immune cells. Moreover, according to a bioinformatics analysis, the altered expression of potential genes caused by these ncRNAs might be related to the development of some human diseases. Furthermore, some ncRNAs, including lncRNAs, miRNAs and circRNAs, or processes in which they are involved may be used as biomarkers for relevant diseases and potential targets to prevent these diseases. Additionally, we performed a meta-analysis to identify more promising diagnostic ncRNAs as biomarkers for related diseases.

Combined application of multiple biomarkers for early auxiliary diagnosis of silicosis.

Silicosis is an important industrial health problem for those workers exposed to silica. The present study aimed to investigate the sensitivity and specificity of combined detection of biomarkers in early auxiliary diagnosis of silicosis, the risk factors of silicosis were also studied. The study sample comprised 65 workers who had clinical silicosis and 70 matched control subjects who were exposed to silica but did not have clinical silicosis. The levels of superoxide dismutase, malondialdehyde, interleukin 6 (IL-6), tumor necrosis factor-alpha, and cholinesterases in the serum of 135 subjects were measured. After completing the biochemical assays, a logistic regression model based on the above biochemical determination results was established, and the receiver operating characteristic curve was used for judging the discrimination ability of different statistical indexes. The expression levels of MDA, IL-6, and TNF-alpha in serum samples of patients with stage I silicosis and MDA and IL-6 in serum samples of patients with stage II silicosis were all significantly higher. Results from logistic regression analysis showed that ChEs were protective factors for silicosis, while age, chronic respiratory symptoms, IL-6, and MDA were risk factors. The areas under the ROC curve (AUC) were 0.86 (IL-6), 0.81 (MDA), and 0.65 (TNF-alpha or ChEs). AUC-ROC = 0.90 (95%CI:0.84-0.95). The diagnostic efficiency of IL-6 combined with MDA and TNF-alpha was better than that of any single biomarker.

Multi-omics analysis reveals expression complexity and functional diversity of mouse kinome.

Protein kinases are a crucial component of signaling pathways involved in a wide range of cellular responses, including growth, proliferation, differentiation, and migration. Systematic investigation of protein kinases is critical to better understand phosphorylation-mediated signaling pathways and may provide insights into the development of potential therapeutic drug targets. Here we perform a systems-level analysis of the mouse kinome by analyzing multi-omics data. We used bulk and single-cell transcriptomic data from the C57BL/6J mouse strain to define tissue- and cell-type-specific expression of protein kinases, followed by investigating variations in sequence and expression between C57BL/6J and DBA/2J strains. We then profiled a deep brain phosphoproteome from C57BL/6J and DBA/2J strains as well as their reciprocal hybrids to infer the activity of the mouse kinome. Finally, we performed phenome-wide association analysis using the BXD recombinant inbred (RI) mice (a cross between C57BL/6J and DBA/2J strains) to identify any associations between variants in protein kinases and phenotypes. Collectively, our study provides a comprehensive analysis of the mouse kinome by investigating genetic sequence variation, tissue-specific expression patterns, and associations with downstream phenotypes.

Innovative approach to identify multigenomic and environmental interactions associated with birth defects in family-based hybrid designs.

Genes, including those with transgenerational effects, work in concert with behavioral, environmental, and social factors via complex biological networks to determine human health. Understanding complex relationships between causal factors underlying human health is an essential step towards deciphering biological mechanisms. We propose a new analytical framework to investigate the interactions between maternal and offspring genetic variants or their surrogate single nucleotide polymorphisms (SNPs) and environmental factors using family-based hybrid study design. The proposed approach can analyze diverse genetic and environmental factors and accommodate samples from a variety of family units, including case/control-parental triads, and case/control-parental dyads, while minimizing potential bias introduced by population admixture. Comprehensive simulations demonstrated that our innovative approach outperformed the log-linear approach, the best available method for case-control family data. The proposed approach had greater statistical power and was capable to unbiasedly estimate the maternal and child genetic effects and the effects of environmental factors, while controlling the Type I error rate against population stratification. Using our newly developed approach, we analyzed the associations between maternal and fetal SNPs and obstructive and conotruncal heart defects, with adjustment for demographic and lifestyle factors and dietary supplements. Fourteen and 11 fetal SNPs were associated with obstructive and conotruncal heart defects, respectively. Twenty-seven and 17 maternal SNPs were associated with obstructive and conotruncal heart defects, respectively. In addition, maternal body mass index was a significant risk factor for obstructive defects. The proposed approach is a powerful tool for interrogating the etiological mechanism underlying complex traits.

Genome-wide association studies revealed complex genetic architecture and breeding perspective of maize ear traits.

BACKGROUND: Maize (Zea Mays) is one of the world's most important crops. Hybrid maize lines resulted a major improvement in corn production in the previous and current centuries. Understanding the genetic mechanisms of the corn production associated traits greatly facilitate the development of superior hybrid varieties. RESULT: In this study, four ear traits associated with corn production of Nested Association Mapping (NAM) population were analyzed using a full genetic model, and further, optimal genotype combinations and total genetic effects of current best lines, superior lines, and superior hybrids were predicted for each of the traits at four different locations. The analysis identified 21-34 highly significant SNPs (-log10P > 5), with an estimated total heritability of 37.31-62.34%, while large contributions to variations was due to dominance, dominance-related epistasis, and environmental interaction effects ([Formula: see text] 14.06% ~ 49.28%), indicating these factors contributed significantly to phenotypic variations of the ear traits. Environment-specific genetic effects were also discovered to be crucial for maize ear traits. There were four SNPs found for three ear traits: two for ear length and weight, and two for ear row number and length. Using the Enumeration method and the stepwise tuning technique, optimum multi-locus genotype combinations for superior lines were identified based on the information obtained from GWAS. CONCLUSIONS: Predictions of genetic breeding values showed that different genotype combinations in different geographical regions may be better, and hybrid-line variety breeding with homozygote and heterozygote genotype combinations may have a greater potential to improve ear traits.

The association between undiagnosed diabetes and cognitive function: findings from the China health and retirement longitudinal study.

BACKGROUND: The cognitive function of people with diabetes has gained an increasing interest in recent years, and this study focuses on exploring the relationship between undiagnosed diabetes and cognitive function among the middle-aged and elderly people in China. METHODS: The data came from the China Health and Retirement Longitudinal Study (CHARLS) which was conducted between July and October 2015. 9855 subjects were enrolled in the study. Executive function and episodic memory were used to assess cognitive function. The subjects were divided into three groups: no diabetes, diagnosed diabetes, and undiagnosed diabetes, and weighted multiple linear regression models were established to evaluate the association of undiagnosed diabetes with cognitive function. RESULTS: After controlling for covariates, undiagnosed diabetes was statistically associated with executive function (ß = -0.215, P < 0.01). In the age group of ≥65 years, undiagnosed diabetes was statistically associated with executive function (ß = -0.358, P < 0.01) and episodic memory (ß = -0.356, P < 0.01). When adjusting for confounders, no statistically significant associations were found between diagnosed diabetes and cognitive function except in 45-54 age group (ß = 0.374, P < 0.05). CONCLUSIONS: The cross-sectional study suggested that undiagnosed diabetes was linked to poor cognitive function, especially in the elderly population. Timely diagnosis and active treatment of diabetes are important to reduce the occurrence of cognitive impairment. Further prospective cohort studies are required to articulate the association between undiagnosed diabetes and cognitive function.

Bisphenol B disrupts testis differentiation partly via the estrogen receptor-mediated pathway and subsequently causes testicular dysgenesis in Xenopus laevis.

There is growing concern about adverse effects of bisphenol A alternatives including bisphenol B (BPB) due to their estrogenic activity. However, limited data are available concerning the influences of BPB on male reproductive development in vertebrates, especially in amphibians, which are believed to be susceptible to estrogenic chemicals. The present study investigated the effects of 10, 100 and 1000 nM BPB (2.42, 24.2 and 242 µg/L) on testis development in Xenopus laevis, a model amphibian species for studying gonadal feminization. We found that exposure to BPB from stages 45/46 to 52 resulted in down-regulation of testis-biased gene expression and up-regulation of ovary-biased gene and vitellogenin (vtgb1) expression in gonad-mesonephros complexes (GMCs) of tadpoles at stage 52, coupled with suppressed cell proliferation in testes and reduced gonadal metameres, resembling the effects of 17ß-estradiol. Moreover, an estrogen receptor (ER) antagonist ICI 182780 antagonized BPB-caused up-regulation of ovary-biased gene and vtgb1 expression to some degree, indicating that the effects of BPB on X. laevis testis differentiation could be partly mediated by ER. All observations demonstrate that early exposure to BPB inhibited testis differentiation and exerted certain feminizing effects during gonadal differentiation. When exposure was extended to post-metamorphosis, testes exhibited histological and morphological abnormalities including segmented, discontinuous and fragmented shapes, besides altered sex-dimorphic gene expression. Notably, most of BPB-caused alterations were not concentration-dependent, but the lowest concentration indeed exerted significant effects. Overall, our study for the first time reveals that low concentrations of BPB can disrupt testis differentiation partly due to its estrogenic activity and subsequently cause testicular dysgenesis after metamorphosis, highlighting its reproductive risk to amphibians and other vertebrates including humans. Our finding also implies that estrogenic chemicals-caused testis differentiation inhibition at tadpole stages could predict later testicular dysgenesis after metamorphosis, meaning a possibility of early detection of abnormal testis development caused by estrogenic chemicals.

Genetic architecture of protein expression and its regulation in the mouse brain.

BACKGROUND: Natural variation in protein expression is common in all organisms and contributes to phenotypic differences among individuals. While variation in gene expression at the transcript level has been extensively investigated, the genetic mechanisms underlying variation in protein expression have lagged considerably behind. Here we investigate genetic architecture of protein expression by profiling a deep mouse brain proteome of two inbred strains, C57BL/6 J (B6) and DBA/2 J (D2), and their reciprocal F1 hybrids using two-dimensional liquid chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) technology. RESULTS: By comparing protein expression levels in the four mouse strains, we observed 329 statistically significant differentially expressed proteins between the two parental strains and characterized the genetic basis of protein expression. We further applied a proteogenomic approach to detect variant peptides and define protein allele-specific expression (pASE), identifying 33 variant peptides with cis-effects and 17 variant peptides showing trans-effects. Comparison of regulation at transcript and protein levels show a significant divergence. CONCLUSIONS: The results provide a comprehensive analysis of genetic architecture of protein expression and the contribution of cis- and trans-acting regulatory differences to protein expression.

Functional mapping of tillering QTLs using the Wang-Lan-Ding model and a SSSL population.

Understanding dynamic changes in the genetic architecture of quantitative traits is crucial in developmental genetics. Functional mapping is an appropriate method that passes a mathematical equation to describe a biological developmental process with the genetic mapping framework. Appropriate genetic model and applicable mapping population are indispensable condition for functional mapping of important agronomic traits in plants. Based on the Wang-Lan-Ding model, we ever applied a DH population to carry out functional mapping QTLs underlying growth trajectory on tiller number. However, inconsistent genetic background among the DH lines might disturb the mapping results. With the advent of innovative research materials, single segment substitution lines, allows us to do more precise genetic analyses. Thus functional mapping was again conducted on tiller number using the Wang-Lan-Ding model and a single segment substitution line population with the genetic background of Huajingxian 74 so as to explore QTL dynamic mechanism to regulate developmental traits. We detected that all five single segment substitution lines harbored tillering QTLs with additives and/or dominances to influence the four functional parameters, the optimum tillering time (t0), the maximum tiller number (K), the tillering increased rate (r) and the tillering decreased rate (c), which were estimated from the Wang-Lan-Ding model and with some biological meaning. They mainly brought the inflexion point (t0) delay, the peak increase (K) and the degradation (c) acceleration, while the growth (r) slow down. Moreover, epistatic interactions among these QTLs were confirmed to be prevalent. A total of 39 significant epistatic effects were detected to associate with the four parameters, occupying 34.8% of 112 pairs of epistatic interactions investigated. Contrary to the QTL effects, these epistatic effects largely decreased t0, K and c, while increased r. Our results indicated that the five QTL effects and their epistatic effects significantly changed the shape and trajectory of tiller number via influence of the four functional parameters. Rational use of these QTLs is expected to improve tillering number of rice by molecular design breeding.

Identification of key miRNAs and mRNAs related to coronary artery disease by meta-analysis.

BACKGROUND: To illustrate the mechanism of miRNA and mRNA in coronary artery diseasen (CAD), differentially expressed microRNAs (DEmiRNAs) and genes (DEGs) were analyzed. METHODS: The mRNA transcription profiles of GSE20680 (including 87 blood samples of CAD and 52 blood samples of control), GSE20681 (including 99 blood samples of CAD and 99 blood samples of control) and GSE12288 (including 110 blood samples of CAD and 112 blood samples of control) and the miRNA transcription profiles of GSE59421 (including 33 blood samples of CAD and 37 blood samples of control), GSE49823 (including 12 blood samples of CAD and 12 blood samples of control) and GSE28858 (including 13 blood samples of CAD and 13 blood samples of control) were downloaded from Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/ ). Then, the homogenous expressed mRNAs and miRNAs across the three mRNA transcription profiles and three miRNA transcription profiles were screened using the Fishers exact test in MetaDE. ES package. The weighted gene co-expression network analysis (WGCNA) was used to analyze gene modules. Additionally, the integrated miRNAs-targets regulatory network using the DEmiRNA and their targets was constructed using Cytoscape. RESULTS: A total of 1201 homogenously statistically significant DEGs were identified including 879 up-regulated and 322 down-regulated DEGs, while a total of 47 homogenously statistically significant DEmiRNAs including 37 up-regulated and 10 down-regulated DEmiRNAs in CAD compared with the controls across the three mRNA transcription profiles and the three miRNA transcription profiles. A total of 5067 genes were clustered into 9 modules in the training dataset, among which, 8 modules were validated. In the miRNAs-targets network, there existed 267 interaction relationships among 5 miRNAs (hsa-miR-361-5p, hsa-miR-139-5p, hsa-miR-146b-5p, hsa-miR-502-5p and hsa-miR-501-5p) and 213 targets. CAV1 could be the target of hsa-miR-361-5 while HSF2 was the target of both hsa-miR-361-5p and hsa-miR-146b-5p. CAV1 was significantly enriched in the GO term of regulation of cell proliferation. CONCLUSION: hsa-miR-361-5p, has-miR-146b-5p, CAV1 and HSF2 could play an important role in CAD.