scholarly journals Weighted Gene Correlation Network Meta-Analysis Reveals Functional Candidate Genes Associated with High- and Sub-Fertile Reproductive Performance in Beef Cattle

Genes ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 543 ◽  
Author(s):  
Pablo A. S. Fonseca ◽  
Aroa Suárez-Vega ◽  
Angela Cánovas
Keyword(s):  
Candidate Genes ◽  
Meta Analysis ◽  
Economic Benefits ◽  
Correlation Network ◽  
Economic Losses ◽  
Hormone Regulation ◽  
Sequencing Data ◽  
Hub Genes ◽  
Gene Correlation ◽  
Upstream Regulators

Improved reproductive efficiency could lead to economic benefits for the beef industry, once the intensive selection pressure has led to a decreased fertility. However, several factors limit our understanding of fertility traits, including genetic differences between populations and statistical limitations. In the present study, the RNA-sequencing data from uterine samples of high-fertile (HF) and sub-fertile (SF) animals was integrated using co-expression network meta-analysis, weighted gene correlation network analysis, identification of upstream regulators, variant calling, and network topology approaches. Using this pipeline, top hub-genes harboring fixed variants (HF × SF) were identified in differentially co-expressed gene modules (DcoExp). The functional prioritization analysis identified the genes with highest potential to be key-regulators of the DcoExp modules between HF and SF animals. Consequently, 32 functional candidate genes (10 upstream regulators and 22 top hub-genes of DcoExp modules) were identified. These genes were associated with the regulation of relevant biological processes for fertility, such as embryonic development, germ cell proliferation, and ovarian hormone regulation. Additionally, 100 candidate variants (single nucleotide polymorphisms (SNPs) and insertions and deletions (INDELs)) were identified within those genes. In the long-term, the results obtained here may help to reduce the frequency of subfertility in beef herds, reducing the associated economic losses caused by this condition.

scholarly journals Integrative Identification of Hub Genes Associated With Immune Cells in Atrial Fibrillation Using Weighted Gene Correlation Network Analysis

2021 ◽  
Vol 7 ◽  
Author(s):  
Tao Yan ◽  
Shijie Zhu ◽  
Miao Zhu ◽  
Chunsheng Wang ◽  
Changfa Guo
Keyword(s):  
Atrial Fibrillation ◽  
Network Analysis ◽  
Molecular Mechanism ◽  
Immune Cells ◽  
Bioinformatics Analysis ◽  
Functional Enrichment ◽  
Correlation Network ◽  
Hub Genes ◽  
Qrt Pcr ◽  
Gene Correlation

Background: Atrial fibrillation (AF) is the most common tachyarrhythmia in the clinic, leading to high morbidity and mortality. Although many studies on AF have been conducted, the molecular mechanism of AF has not been fully elucidated. This study was designed to explore the molecular mechanism of AF using integrative bioinformatics analysis and provide new insights into the pathophysiology of AF.Methods: The GSE115574 dataset was downloaded, and Cibersort was applied to estimate the relative expression of 22 kinds of immune cells. Differentially expressed genes (DEGs) were identified through the limma package in R language. Weighted gene correlation network analysis (WGCNA) was performed to cluster DEGs into different modules and explore relationships between modules and immune cell types. Functional enrichment analysis was performed on DEGs in the significant module, and hub genes were identified based on the protein-protein interaction (PPI) network. Hub genes were then verified using quantitative real-time polymerase chain reaction (qRT-PCR).Results: A total of 2,350 DEGs were identified and clustered into eleven modules using WGCNA. The magenta module with 246 genes was identified as the key module associated with M1 macrophages with the highest correlation coefficient. Three hub genes (CTSS, CSF2RB, and NCF2) were identified. The results verified using three other datasets and qRT-PCR demonstrated that the expression levels of these three genes in patients with AF were significantly higher than those in patients with SR, which were consistent with the bioinformatic analysis.Conclusion: Three novel genes identified using comprehensive bioinformatics analysis may play crucial roles in the pathophysiological mechanism in AF, which provide potential therapeutic targets and new insights into the treatment and early detection of AF.

scholarly journals Weighted Gene Correlation Network Analysis (WGCNA) Detected Loss of MAGI2 Promotes Chronic Kidney Disease (CKD) by Podocyte Damage

2018 ◽  
Vol 51 (1) ◽  
pp. 244-261 ◽  
Author(s):  
Zhi Zuo ◽  
Jian-Xiao Shen ◽  
Yan Pan ◽  
Juan Pu ◽  
Yong-Gang Li ◽  
...  
Keyword(s):  
Chronic Kidney Disease ◽  
Network Analysis ◽  
Kidney Disease ◽  
Kidney Diseases ◽  
Correlation Network ◽  
Hub Genes ◽  
Podocyte Injury ◽  
Protein Levels ◽  
Podocyte Damage ◽  
Gene Correlation

Background/Aims: Podocyte damage is associated with proteinuria, glomerulosclerosis and decline of renal function. This study aimed to screen critical genes associated with podocyte injury in chronic kidney disease (CKD) by weighted gene correlation network analysis (WGCNA), and explore related functions. Methods: GSE66107, GSE93798, GSE30528, GSE32591 gene expression data including podocyte injury models or glomeruli in CKD patients were downloaded from the GEO database. R was used for data analysis. Differentially expressed genes (DEGs) (FDR< 0.05 or |Fold Change|≥1.5) in GSE993395 were assessed by WGCNA. According to Gene Ontology (GO) and known podocyte standard genes (PSGs), podocyte injury-associated modules were defined, with hub genes selected based on average intramodular connectivity. The Cytoscape software was used for network visualization. Nephroseq was used to assess the clinical significance of hub genes. Small interfering RNA (siRNA) was used to evaluate the roles of hub genes in podocyte injury Results: Totally 7957 DEGs were screened, with 15 (co.DEGs) altered in all 4 datasets; 4031 DEGs were used for WGCNA, encompassing 12 modules. Green modules (most PSGs and co.DEGs) were significantly enriched in glomerular development, and considered podocyte injury-associated modules. Furthermore, MAGI2 (a hub gene) was also a co.DEG and PSG. Glomerular MAGI2 levels were reduced in various kidney diseases, and positively and negatively associated with glomerular filtration rate and urinary protein levels in CKD patients. Moreover, MAIG2 knockdown reduced NPHS2, CD2AP and SYNPO levels, and induced podocyte rearrangement and apoptosis. Conclusion: MAGI2 identified by WGCNA regulates cytoskeletal rearrangement in podocytes, with its loss predisposing to proteinuria and CKD.

scholarly journals Gene co-expression analyses of health(span) across multiple species

2021 ◽  
Author(s):  
Steffen Möller ◽  
Nadine Saul ◽  
Israel W. Barrantes ◽  
András Gézsi ◽  
Michael Walter ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Enrichment Analysis ◽  
Gene Clusters ◽  
Hub Genes ◽  
Health Span ◽  
Network Analyses ◽  
Health Related ◽  
Gene Correlation ◽  
The Cross ◽  
Multiple Species

Health(span)-related gene clusters/modules were recently identified based on knowledge about the cross-species genetic basis of health, to interpret transcriptomic datasets describing health-related interventions. However, the cross-species comparison of health-related observations reveals a lot of heterogeneity, not least due to widely varying health(span) definitions and study designs, posing a challenge for the exploration of conserved healthspan modules and, specifically, their transfer across species. To improve the identification and exploration of conserved/transferable healthspan modules, here we apply an established workflow based on gene co-expression network analyses employing GEO/ArrayExpress data for human and animal models, and perform a comprehensive meta-analysis of the resulting modules related to health(span), yielding a small set of health(span) candidate genes, backed by the literature. For each experiment, WGCNA (weighted gene correlation network analysis) was thus used to infer modules of genes which correlate in their expression with a "health phenotype score" and to determine the most-connected (hub) genes for each such module, and their interactions. After mapping these hub genes to their human orthologs, 12 health(span) genes were identified in at least two species (ACTN3, ANK1, MRPL18, MYL1, PAXIP1, PPP1CA, SCN3B, SDCBP, SKIV2L, TUBG1, TYROBP, WIPF1), for which enrichment analysis by g:profiler finds an association with actin filament-based movement and associated organelles as well as muscular structures. We conclude that a meta-study of hub genes from co-expression network analyses for the complex phenotype health(span), across multiple species, can yield molecular-mechanistic insights and can direct experimentalists to further investigate the contribution of individual genes and their interactions to health(span).

scholarly journals Comprehensive Analysis of Differentially Expressed miRNAs and mRNAs Reveals That miR-181a-5p Plays a Key Role in Diabetic Dermal Fibroblasts

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Peng Liu ◽  
Yi Zhu ◽  
Qin Li ◽  
Biao Cheng
Keyword(s):  
Wound Healing ◽  
Dermal Fibroblast ◽  
Healing Process ◽  
Dermal Fibroblasts ◽  
Differentially Expressed ◽  
Correlation Network ◽  
Wound Healing Process ◽  
Hub Genes ◽  
Functional Changes ◽  
Gene Correlation

A diabetic nonhealing wound causes heavy economic burden and compromised quality of life in patients. The human dermal fibroblast (HDF), which is an important kind of effector cell in the wound healing process, represents different biological behaviors in the normal and diabetic skins. Given this, we attempt to explore functional changes in diabetic skin-derived HDFs and try to find out the “hub” genes that modulate diabetic HDFs and may be the potential therapeutic targets of diabetic wound healing. We searched the GEO database for related miRNA (GSE68185, GSE84971) and mRNA (GSE49566, GSE78891) profiles. After eliminating batch effects and identifying differentially expressed genes (DEGs), we applied enrichment analyses and found that 3 miRNAs and 30 mRNAs were differentially expressed in diabetic HDFs. Enrichment analyses showed that these genes are closely related to wound healing, for example, extracellular matrix (ECM) organization, angiogenesis, cell proliferation, and migration. Subsequently, we constructed the gene correlation network of DEGs to identify hub genes by merging the protein-protein interaction network, weighted gene coexpression network, and predicted miRNA-mRNA regulatory network. Based on the gene correlation network, we identified the top 3 hub genes: miR-181a-5p, POSTN, and CDH11. Among these, POSTN is a predicted target of miR-181a-5p and is supposed to work together with CDH11 as a functional group. Finally, we verified the expression pattern of the hub genes by in vitro quantification experiments in glucose-cultured HDFs. Our study suggested that miR-181a-5p possibly plays a key role in modulation of HDF behaviors during the diabetic state. However, the effects and mechanisms of miR-181a-5p in high glucose-cultured HDFs remain to be explored in the future.

Cereal pre-harvest sprouting: a global agricultural disaster regulated by complex genetic and biochemical mechanisms

2021 ◽  
Author(s):  
Li Tai ◽  
Hong-Jin Wang ◽  
Xiao-Jing Xu ◽  
Wei-Hang Sun ◽  
Lan Ju ◽  
...  
Keyword(s):  
Crop Production ◽  
Regulatory Networks ◽  
Crop Yields ◽  
Germination Rate ◽  
Meta Analysis ◽  
Biological Significance ◽  
Economic Benefits ◽  
Economic Losses ◽  
High Germination ◽  
Custom Made

Abstract With the growth of the global population and uncontrollable natural disasters, crop yields must be steadily increased to enhance human adaptability to risks. Pre-harvest sprouting (PHS) is a global disaster for agricultural production, which is mainly used to describe the phenomenon in which grains germinate on the mother plant directly before harvest. After domestication, the dormancy level of cultivated crops was generally lower than that of wild ancestors. Although the shortened dormancy period likely improved the industrial performance of cereals such as wheat, barley, rice, and maize, the excessively high germination rate has caused frequent PHS in areas with higher rainfall, causing great economic losses. Here, we systematically reviewed the causes and harms of PHS, the major indicators and methods for PHS assessment, emphasising the biological significance of PHS in crop production. Wheat quantitative trait loci (QTLs) functioning in PHS controls were also comprehensively summarised for a meta-analysis. Finally, we used Arabidopsis as a model plant to develop more complete PHS regulatory networks for wheat. The integration of this information is conducive to cultivating custom-made cultivated lines suitable for different demands and different regions and is of great significance for improving crop yield and economic benefits.

Fertiliser evenness - losses and costs: A study on the economic benefits of uniform applications of fertiliser

1999 ◽  
pp. 215-220 ◽  
Author(s):  
R. Horrell ◽  
A.K. Metherell ◽  
S. Ford ◽  
C. Doscher
Keyword(s):  
Crop Yields ◽  
Cumulative Effect ◽  
Economic Loss ◽  
Economic Benefits ◽  
Significant Loss ◽  
Economic Losses ◽  
Financial Return ◽  
Spread Pattern ◽  
Fertiliser Application ◽  
Seed Crops

Over two million tonnes of fertiliser are applied to New Zealand pastures and crops annually and there is an increasing desire by farmers to ensure that the best possible economic return is gained from this investment. Spreading distribution measurements undertaken by Lincoln Ventures Ltd (LVL) have identified large variations in the evenness of fertiliser application by spreading machines which could lead to a failure to achieve optimum potential in some crop yields and to significant associated economic losses. To quantify these losses, a study was undertaken to calculate the effect of uneven fertiliser application on crop yield. From LVL's spreader database, spread patterns from many machines were categorised by spread pattern type and by coefficient of variation (CV). These patterns were then used to calculate yield losses when they were combined with the response data from five representative cropping and pastoral situations. Nitrogen fertiliser on ryegrass seed crops shows significant production losses at a spread pattern CV between 30% and 40%. For P and S on pasture, the cumulative effect of uneven spreading accrues, until there is significant economic loss occurring by year 3 for both the Waikato dairy and Southland sheep and beef systems at CV values between 30% and 40%. For nitrogen on pasture, significant loss in a dairy system occurs at a CV of approximately 40% whereas for a sheep and beef system it is at a CV of 50%, where the financial return from nitrogen application has been calculated at the average gross revenue of the farming system. The conclusion of this study is that the current Spreadmark standards are a satisfactory basis for defining the evenness requirements of fertiliser applications in most circumstances. On the basis of Spreadmark testing to date, more than 50% of the national commercial spreading fleet fails to meet the standard for nitrogenous fertilisers and 40% fails to meet the standard for phosphatic fertilisers.Keywords: aerial spreading, crop response, economic loss, fertiliser, ground spreading, striping, uneven application, uneven spreading, yield loss

scholarly journals A meta-analysis of genome-wide association studies for average daily gain and lean meat percentage in two Duroc pig populations

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shenping Zhou ◽  
Rongrong Ding ◽  
Fanming Meng ◽  
Xingwang Wang ◽  
Zhanwei Zhuang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Growth And Development ◽  
Genetic Architecture ◽  
Association Studies ◽  
Meta Analysis ◽  
Average Daily Gain ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Daily Gain

Abstract Background Average daily gain (ADG) and lean meat percentage (LMP) are the main production performance indicators of pigs. Nevertheless, the genetic architecture of ADG and LMP is still elusive. Here, we conducted genome-wide association studies (GWAS) and meta-analysis for ADG and LMP in 3770 American and 2090 Canadian Duroc pigs. Results In the American Duroc pigs, one novel pleiotropic quantitative trait locus (QTL) on Sus scrofa chromosome 1 (SSC1) was identified to be associated with ADG and LMP, which spans 2.53 Mb (from 159.66 to 162.19 Mb). In the Canadian Duroc pigs, two novel QTLs on SSC1 were detected for LMP, which were situated in 3.86 Mb (from 157.99 to 161.85 Mb) and 555 kb (from 37.63 to 38.19 Mb) regions. The meta-analysis identified ten and 20 additional SNPs for ADG and LMP, respectively. Finally, four genes (PHLPP1, STC1, DYRK1B, and PIK3C2A) were detected to be associated with ADG and/or LMP. Further bioinformatics analysis showed that the candidate genes for ADG are mainly involved in bone growth and development, whereas the candidate genes for LMP mainly participated in adipose tissue and muscle tissue growth and development. Conclusions We performed GWAS and meta-analysis for ADG and LMP based on a large sample size consisting of two Duroc pig populations. One pleiotropic QTL that shared a 2.19 Mb haplotype block from 159.66 to 161.85 Mb on SSC1 was found to affect ADG and LMP in the two Duroc pig populations. Furthermore, the combination of single-population and meta-analysis of GWAS improved the efficiency of detecting additional SNPs for the analyzed traits. Our results provide new insights into the genetic architecture of ADG and LMP traits in pigs. Moreover, some significant SNPs associated with ADG and/or LMP in this study may be useful for marker-assisted selection in pig breeding.

scholarly journals Hyaluronan-mediated motility receptor expression functions as a prognostic biomarker in uterine carcinosarcoma based on bioinformatics analysis

2021 ◽  
Vol 49 (6) ◽  
pp. 030006052110210
Author(s):  
Hui Sun ◽  
Li Ma ◽  
Jie Chen
Keyword(s):  
Interaction Network ◽  
Maximal Clique ◽  
Receptor Expression ◽  
The Cancer Genome Atlas ◽  
Uterine Carcinosarcoma ◽  
Sequencing Data ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Normal Tissues ◽  
Potential Biomarker

Objective Uterine carcinosarcoma (UCS) is a rare, aggressive tumour with a high metastasis rate and poor prognosis. This study aimed to explore potential key genes associated with the prognosis of UCS. Methods Transcriptional expression data were downloaded from the Gene Expression Profiling Interactive Analysis database and differentially expressed genes (DEGs) were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses using Metascape. A protein–protein interaction network was constructed using the STRING website and Cytoscape software, and the top 30 genes obtained through the Maximal Clique Centrality algorithm were selected as hub genes. These hub genes were validated by clinicopathological and sequencing data for 56 patients with UCS from The Cancer Genome Atlas database. Results A total of 1894 DEGs were identified, and the top 30 genes were considered as hub genes. Hyaluronan-mediated motility receptor (HMMR) expression was significantly higher in UCS tissues compared with normal tissues, and elevated expression of HMMR was identified as an independent prognostic factor for shorter survival in patients with UCS. Conclusions These results suggest that HMMR may be a potential biomarker for predicting the prognosis of patients with UCS.

scholarly journals Identification of SNPs Associated with Somatic Cell Score in Candidate Genes in Italian Holstein Friesian Bulls

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 366
Author(s):  
Riccardo Moretti ◽  
Dominga Soglia ◽  
Stefania Chessa ◽  
Stefano Sartore ◽  
Raffaella Finocchiaro ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Genetic Resistance ◽  
Genetic Selection ◽  
Significant Snps ◽  
Economic Losses ◽  
Genotype Distribution ◽  
Inflammatory Reactions ◽  
Next Generation Sequencing Technology ◽  
Holstein Friesian ◽  
Holstein Bulls

Mastitis is an infectious disease affecting the mammary gland, leading to inflammatory reactions and to heavy economic losses due to milk production decrease. One possible way to tackle the antimicrobial resistance issue stemming from antimicrobial therapy is to select animals with a genetic resistance to this disease. Therefore, aim of this study was to analyze the genetic variability of the SNPs found in candidate genes related to mastitis resistance in Holstein Friesian bulls. Target regions were amplified, sequenced by Next-Generation Sequencing technology on the Illumina® MiSeq, and then analyzed to find correlation with mastitis related phenotypes in 95 Italian Holstein bulls chosen with the aid of a selective genotyping approach. On a total of 557 detected mutations, 61 showed different genotype distribution in the tails of the deregressed EBVs for SCS and 15 were identified as significantly associated with the phenotype using two different approaches. The significant SNPs were identified in intergenic or intronic regions of six genes, known to be key components in the immune system (namely CXCR1, DCK, NOD2, MBL2, MBL1 and M-SAA3.2). These SNPs could be considered as candidates for a future genetic selection for mastitis resistance, although further studies are required to assess their presence in other dairy cattle breeds and their possible negative correlation with other traits.

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