scholarly journals Bone Signaling in Middle Ear Development: A Genome-Wide Differential Expression Analysis

2014 ◽  
Vol 297 (12) ◽  
pp. 2349-2355 ◽  
Author(s):  
Michelle Christine Nielsen ◽  
Tomas Martin Bertelsen ◽  
Morten Friis ◽  
Ole Winther ◽  
Lennart Friis-Hansen ◽  
...  
Keyword(s):  
Differential Expression ◽  
Expression Analysis ◽  
Middle Ear ◽  
Differential Expression Analysis ◽  
Ear Development ◽  
Genome Wide ◽  
A Genome ◽  
Middle Ear Development

scholarly journals Genome-Wide Association Study and Transcriptome Differential Expression Analysis of the Feather Rate in Shouguang Chickens

2020 ◽  
Vol 11 ◽  
Author(s):  
Xiayi Liu ◽  
Zhou Wu ◽  
Junying Li ◽  
Haigang Bao ◽  
Changxin Wu
Keyword(s):  
Differential Expression ◽  
Candidate Genes ◽  
Rna Sequencing ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Serine Phosphorylation ◽  
Differentially Expressed ◽  
Genome Wide Association ◽  
Sequencing Analysis ◽  
Genome Wide

The feather rate phenotype in chicks, including early-feathering and late-feathering phenotypes, are widely used as a sexing system in the poultry industry. The objective of this study was to obtain candidate genes associated with the feather rate in Shouguang chickens. In the present study, we collected 56 blood samples and 12 hair follicle samples of flight feathers from female Shouguang chickens. Then we identified the chromosome region associated with the feather rate by genome-wide association analysis (GWAS). We also performed RNA sequencing and analyzed differentially expressed genes between the early-feathering and late-feathering phenotypes using HISAT2, StringTie, and DESeq2. We identified a genomic region of 10.0–13.0 Mb of chromosome Z, which is statistically associated with the feather rate of Shouguang chickens at one-day old. After RNA sequencing analysis, 342 differentially expressed known genes between the early-feathering (EF) and late-feathering (LF) phenotypes were screened out, which were involved in epithelial cell differentiation, intermediate filament organization, protein serine kinase activity, peptidyl-serine phosphorylation, retinoic acid binding, and so on. The sperm flagellar 2 gene (SPEF2) and prolactin receptor (PRLR) gene were the only two overlapping genes between the results of GWAS and differential expression analysis, which implies that SPEF2 and PRLR are possible candidate genes for the formation of the chicken feathering phenotype in the present study. Our findings help to elucidate the molecular mechanism of the feather rate in chicks.

scholarly journals Genome-Wide Identification of Circular RNAs Potentially Involved in the Biosynthesis of Secondary Metabolites in Salvia miltiorrhiza

2021 ◽  
Vol 12 ◽  
Author(s):  
Mei Jiang ◽  
Haimei Chen ◽  
Qing Du ◽  
Liqiang Wang ◽  
Xinyue Liu ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Expression Analysis ◽  
Expression Profiles ◽  
Salvia Miltiorrhiza ◽  
Differential Expression Analysis ◽  
Functional Enrichment ◽  
Circular Rnas ◽  
Primary Metabolism ◽  
Genome Wide ◽  
A Genome

Circular RNAs (circRNAs) play various roles in cellular functions. However, no studies have been reported on the potential involvement of circRNAs in the biosynthesis of secondary metabolites in plants. Here, we performed a genome-wide discovery of circRNAs from root, stem and leaf samples of Salvia miltiorrhiza using RNA-Seq. We predicted a total of 2,476 circRNAs with at least two junction reads using circRNA_finder and CIRI, of which 2,096, 151 and 229 were exonic, intronic and intergenic circRNAs, respectively. Sequence similarity analysis showed that 294 out of 2,476 circRNAs were conserved amongst multiple plants. Of the 55 predicted circRNAs, 31 (56%) were validated successfully by PCR and Sanger sequencing using convergent and divergent primer pairs. Alternative circularisation analysis showed that most parental genes produced two circRNAs. Functional enrichment analyses of the parental genes showed that the primary metabolism pathways were significantly enriched, particularly the carbon metabolism. Differential expression analysis showed that the expression profiles of circRNAs were tissue-specific. Co-expression analysis showed 275 circRNAs, and their parental genes had significantly positive correlations. However, 14 had significantly negative correlations. Weighted gene co-expression network analysis showed that nine circRNAs were co-expressed with four modules of protein-coding genes. Next, we found 416 exonic circRNAs with miRNA-binding sites, suggesting possible interactions between circRNAs and miRNAs. Lastly, we found six validated circRNAs, namely, SMscf2473-46693-46978, SMscf3091-29256-29724, SMscf16-111773-112193, SMscf432-13232-13866, SMscf7007-10563-10888 and SMscf1730-1749-2013, which were originated from the genes involved in the biosynthesis of secondary metabolites. Their parental genes were acetyl-CoA C-acetyltransferase 1 (SmAACT1), 1-deoxy-d-xylulose-5-phosphate synthase 2 (SmDXS2), 4-hydroxy-3-methylbut-2-enyl diphosphate reductase 1 (SmHDR1), kaurene synthase-like 2 (SmKSL2), DWF4 and CYP88A3, respectively. In particular, the correlation coefficient of SMscf2473-46693-46978 and SmDXS2 gene was 0.86 (p = 0.003), indicating a potential interaction between this pair of circRNA and its parent gene. Our results provided the first comprehensive catalogue of circRNAs in S. miltiorrhiza and identified one circRNA that might play important roles in the biosynthesis of secondary metabolites.

scholarly journals Identification of rhizome-specific genes by genome-wide differential expression Analysis in Oryza longistaminata

2011 ◽  
Vol 11 (1) ◽  
pp. 18 ◽  
Author(s):  
Fengyi Hu ◽  
Di Wang ◽  
Xiuqin Zhao ◽  
Ting Zhang ◽  
Haixi Sun ◽  
...  
Keyword(s):  
Differential Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Genome Wide ◽  
Oryza Longistaminata

scholarly journals Genome-wide identification of cyclin-dependent kinase (CDK) genes affecting adipocyte differentiation in cattle

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Cuili Pan ◽  
Zhaoxiong Lei ◽  
Shuzhe Wang ◽  
Xingping Wang ◽  
Dawei Wei ◽  
...  
Keyword(s):  
Gene Family ◽  
Expression Analysis ◽  
Adipocyte Differentiation ◽  
Bos Taurus ◽  
Adipogenic Differentiation ◽  
Critical Role ◽  
Bos Indicus ◽  
Specific Expression ◽  
Genome Wide ◽  
A Genome

Abstract Background Cyclin-dependent kinases (CDKs) are protein kinases regulating important cellular processes such as cell cycle and transcription. Many CDK genes also play a critical role during adipogenic differentiation, but the role of CDK gene family in regulating bovine adipocyte differentiation has not been studied. Therefore, the present study aims to characterize the CDK gene family in bovine and study their expression pattern during adipocyte differentiation. Results We performed a genome-wide analysis and identified a number of CDK genes in several bovine species. The CDK genes were classified into 8 subfamilies through phylogenetic analysis. We found that 25 bovine CDK genes were distributed in 16 different chromosomes. Collinearity analysis revealed that the CDK gene family in Bos taurus is homologous with Bos indicus, Hybrid-Bos taurus, Hybrid Bos indicus, Bos grunniens and Bubalus bubalis. Several CDK genes had higher expression levels in preadipocytes than in differentiated adipocytes, as shown by RNA-seq analysis and qPCR, suggesting a role in the growth of emerging lipid droplets. Conclusion In this research, 185 CDK genes were identified and grouped into eight distinct clades in Bovidae, showing extensively homology. Global expression analysis of different bovine tissues and specific expression analysis during adipocytes differentiation revealed CDK4, CDK7, CDK8, CDK9 and CDK14 may be involved in bovine adipocyte differentiation. The results provide a basis for further study to determine the roles of CDK gene family in regulating adipocyte differentiation, which is beneficial for beef quality improvement.

scholarly journals Best practices on the differential expression analysis of multi-species RNA-seq

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Matthew Chung ◽  
Vincent M. Bruno ◽  
David A. Rasko ◽  
Christina A. Cuomo ◽  
José F. Muñoz ◽  
...  
Keyword(s):  
Best Practices ◽  
Differential Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Single Species ◽  
Rna Seq ◽  
Species Analysis ◽  
Differential Gene ◽  
Multiple Species ◽  
Downstream Analysis

AbstractAdvances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression.

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