scholarly journals Homoeologue expression insights into the basis of growth heterosis at the intersection of ploidy and hybridity in Cyprinidae (Carassius auratus red var. × Cyprinus carpio)

2015 ◽  
Author(s):  
Li Ren ◽  
Wuhui Li ◽  
Chenchen Tang ◽  
Jun Xiao ◽  
Xiaojun Tan ◽  
...  
Keyword(s):  
Cyprinus Carpio ◽  
Carassius Auratus ◽  
Driving Forces ◽  
Expression Patterns ◽  
Global Gene Expression ◽  
Regulation Mechanism ◽  
Rna Seq ◽  
Allopolyploid Speciation ◽  
Expression Bias ◽  
Changing Patterns

Hybridization and polyploidization are considered important driving forces that form new epigenetic regulations. To study the changing patterns of expression accompanying hybridization and polyploidization, we used RNA-seq and qPCR to investigate global expression and homoeologue expression in diploid and allotetraploid hybrids of Carassius auratus red var. (♀) (R) and Cyprinus carpio (♂) (C). By comparing the relative expression levels between the hybrids and their parents, we defined the expression level dominance (ELD) and homoeologue expression bias (HEB) in liver tissue. The results showed that polyploidization contributed to the conversion of homoeologue ELD. In addition, hybridization had more effect on the change in HEB than polyploidization, while polyploidization has been considered to have more effect on the change of global gene expression than hybridization. Meanwhile, similar expression patterns were found in growth-related genes. The results suggested that hybridization and polyploidization result in differential degrees of maternal HEB in the three tissues tested. The results of this study will increase our understanding of the underlying regulation mechanism of rapid growth in diploid hybrids and allotetraploids. The differential degrees of global expression and homoeologue expression contribute to growth heterosis in newly formed hybrids and allotetraploids, ensuring the on-going success of allopolyploid speciation.

scholarly journals Time Series RNA-seq in Pigeonpea Revealed the Core Genes in Metabolic Pathways under Aluminum Stress

Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 380 ◽  
Author(s):  
Zhaoxu Gao ◽  
Biying Dong ◽  
Hongyan Cao ◽  
Hang He ◽  
Qing Yang ◽  
...  
Keyword(s):  
Time Series ◽  
Metabolic Pathways ◽  
Expression Patterns ◽  
Plant Stress ◽  
Regulation Mechanism ◽  
Rna Seq ◽  
Aluminum Stress ◽  
Biological Regulation ◽  
Al Stress ◽  
The Impact

Pigeonpea is an important economic crop in the world and is mainly distributed in tropical and subtropical regions. In order to further expand the scope of planting, one of the problems that must be solved is the impact of soil acidity on plants in these areas. Based on our previous work, we constructed a time series RNA sequencing (RNA-seq) analysis under aluminum (Al) stress in pigeonpea. Through a comparison analysis, 11,425 genes were found to be differentially expressed among all the time points. After clustering these genes by their expression patterns, 12 clusters were generated. Many important functional pathways were identified by gene ontology (GO) analysis, such as biological regulation, localization, response to stimulus, metabolic process, detoxification, and so on. Further analysis showed that metabolic pathways played an important role in the response of Al stress. Thirteen out of the 23 selected genes related to flavonoids and phenols were downregulated in response to Al stress. In addition, we verified these key genes of flavonoid- and phenol-related metabolism pathways by qRT-PCR. Collectively, our findings not only revealed the regulation mechanism of pigeonpea under Al stress but also provided methodological support for further exploration of plant stress regulation mechanisms.

scholarly journals Subgenome Bias and Temporal Postponement of Gene Expression Contributes to the Distinctions of Fiber Quality in Gossypium Species

2021 ◽  
Vol 12 ◽  
Author(s):  
Huan Mei ◽  
Bowen Qi ◽  
Zegang Han ◽  
Ting Zhao ◽  
Menglan Guo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Fiber Quality ◽  
Expression Patterns ◽  
Rna Seq ◽  
Hub Genes ◽  
Hub Gene ◽  
Expression Of Genes ◽  
Multiple Dimensions ◽  
Cotton Species ◽  
Expression Bias

As two cultivated widely allotetraploid cotton species, although Gossypium hirsutum and Gossypium barbadense evolved from the same ancestor, they differ in fiber quality; the molecular mechanism of that difference should be deeply studied. Here, we performed RNA-seq of fiber samples from four G. hirsutum and three G. barbadense cultivars to compare their gene expression patterns on multiple dimensions. We found that 15.90–37.96% of differentially expressed genes showed biased expression toward the A or D subgenome. In particular, interspecific biased expression was exhibited by a total of 330 and 486 gene pairs at 10 days post-anthesis (DPA) and 20 DPA, respectively. Moreover, 6791 genes demonstrated temporal differences in expression, including 346 genes predominantly expressed at 10 DPA in G. hirsutum (TM-1) but postponed to 20 DPA in G. barbadense (Hai7124), and 367 genes predominantly expressed at 20 DPA in TM-1 but postponed to 25 DPA in Hai7124. These postponed genes mainly participated in carbohydrate metabolism, lipid metabolism, plant hormone signal transduction, and starch and sucrose metabolism. In addition, most of the co-expression network and hub genes involved in fiber development showed asymmetric expression between TM-1 and Hai7124, like three hub genes detected at 10 DPA in TM-1 but not until 25 DPA in Hai7124. Our study provides new insights into interspecific expression bias and postponed expression of genes associated with fiber quality, which are mainly tied to asymmetric hub gene network. This work will facilitate further research aimed at understanding the mechanisms underlying cotton fiber improvement.

scholarly journals Zebrafish pituitary gene expression before and after sexual maturation

2014 ◽  
Vol 221 (3) ◽  
pp. 429-440 ◽  
Author(s):  
Wenxia He ◽  
Xiangyan Dai ◽  
Xiaowen Chen ◽  
Jiangyan He ◽  
Zhan Yin
Keyword(s):  
Gene Expression ◽  
Sexual Maturation ◽  
Sexual Maturity ◽  
Expression Patterns ◽  
Endocrine System ◽  
Global Gene Expression ◽  
Gene Expression Patterns ◽  
Pituitary Hormone ◽  
Rna Seq ◽  
Before And After

Sexual maturation and somatic growth cessation are associated with adolescent development, which is precisely controlled by interconnected neuroendocrine regulatory pathways in the endogenous endocrine system. The pituitary gland is one of the key regulators of the endocrine system. By analyzing the RNA sequencing (RNA-seq) transcriptome before and after sexual maturation, in this study, we characterized the global gene expression patterns in zebrafish pituitaries at 45 and 90 days post-fertilization (dpf). A total of 15 043 annotated genes were expressed in the pituitary tissue, 3072 of which were differentially expressed with a greater than or equal to twofold change between pituitaries at 45 and 90 dpf. In the pituitary transcriptome, the most abundant transcript was gh. The expression levels of gh remained high even after sexual maturation at 90 dpf. Among the eight major pituitary hormone genes, lhb was the only gene that exhibited a significant change in its expression levels between 45 and 90 dpf. Significant changes in the pituitary transcripts included genes involved in the regulation of immune responses, bone metabolism, and hormone secretion processes during the juvenile–sexual maturity transition. Real-time quantitative PCR analysis was carried out to verify the RNA-seq transcriptome results and demonstrated that the expression patterns of the eight major pituitary hormone genes did not exhibit a significant gender difference at 90 dpf. For the first time, we report the quantitative global gene expression patterns at the juvenile and sexual maturity stages. These expression patterns may account for the dynamic neuroendocrine regulation observed in body metabolism.

scholarly journals Integrated SMRT Technology with UMI RNA-Seq Reveals the Hub Genes in Stamen Petalody in Camellia oleifera

Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 749
Author(s):  
Huie Li ◽  
Yang Hu ◽  
Chao Gao ◽  
Qiqiang Guo ◽  
Quanen Deng ◽  
...  
Keyword(s):  
Single Molecule ◽  
Expression Patterns ◽  
Regulation Mechanism ◽  
Camellia Oleifera ◽  
Rna Seq ◽  
Hub Genes ◽  
Similar Expression Pattern ◽  
Transcription Factor Genes ◽  
Key Factor ◽  
Solid Foundation

Male sterility caused by stamen petalody is a key factor for a low fruit set rate and a low yield of Camellia oleifera but can serve as a useful genetic tool because it eliminates the need for artificial emasculation. However, its molecular regulation mechanism still remains unclear. In this study, transcriptome was sequenced and analyzed on two types of bud materials, stamen petalody mutants and normal materials, at six stages of stamen development based on integrated single-molecule real-time (SMRT) technology with unique molecular identifiers (UMI) and RNA-seq technology to identify the hub genes responsible for stamen petalody in C. oleifera. The results show that a large number of alternative splicing events were identified in the transcriptome. A co-expression network analysis of MADSs and all the differentially expressed genes between the mutant stamens and the normal materials showed that four MADS transcription factor genes, CoSEP3.1, CoAGL6, CoSEP3.2, and CoAP3, were predicted to be the hub genes responsible for stamen petalody. Among these four, the expression patterns of CoAGL6 and CoSEP3.2 were consistently high in the mutant samples, but relatively low in the normal samples at six stages, while the patterns of CoSEP3.1 and CoAP3 were initially low in mutants and then were upregulated during development but remained relatively high in the normal materials. Furthermore, the genes with high connectivity to the hub genes showed significantly different expression patterns between the mutant stamens and the normal materials at different stages. qRT-PCR results showed a similar expression pattern of the hub genes in the RNA-seq. These results lay a solid foundation for the directive breeding of C. oleifera varieties and provide references for the genetic breeding of ornamental Camellia varieties.

scholarly journals Co-Expression Network-based Analysis associated with potato initial resistance

2018 ◽  
Author(s):  
Lang Yan ◽  
Xianjun Lai ◽  
Yan Wu ◽  
Xuemei Tan ◽  
Yizheng Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Gene Expression Patterns ◽  
Evolutionary Divergence ◽  
Regulation Mechanism ◽  
Rna Seq ◽  
Functional Studies ◽  
Study Gene Expression ◽  
Gene Modules ◽  
Dramatic Shift

RNA sequencing (RNA-seq) providing genome-wide expression datasets has been successfully used to study gene expression patterns and regulation mechanism among multiple samples. Gene co-expression networks (GCNs) studies within or across species showed that coordinated genes in expression patterns are often functionally related. For potatoes, a large amount of publicly available transcriptome datasets have been generated but an optimal GCN detecting expression patterns in different genotypes, tissues and environmental conditions, is lacking. We constructed a potato GCN using 16 published RNA-Seq datasets covering 11 cultivars from native habitat worldwide. The correlations of gene expression were assessed pair-wisely and biologically meaningful gene modules which are highly connected in GCN were identified. One of the primitively native-farmer-selected cultivars in the Andes, ssp.Andigena, had relative far distance in gene expression patterns with other modern varieties. GCN in further enriched 134 highly and specifically co-expressed genes in ssp.Andigena associated with potato disease and stress resistance, which underlying the dramatic shift in evolutionary pressures during potato artificial domestication. In total, the network was consisted of into 14 gene models that involves in a variety of plant processes, which sheds light on how gene modules organized intra- and inter-varieties in the context of evolutionary divergence and provides a basis of information resource for potato gene functional studies.

scholarly journals Integration of transcriptomic data identifies key hallmark genes in hypertrophic cardiomyopathy

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jing Xu ◽  
Xiangdong Liu ◽  
Qiming Dai
Keyword(s):  
Machine Learning ◽  
Hypertrophic Cardiomyopathy ◽  
Heart Diseases ◽  
Expression Patterns ◽  
Support Vector ◽  
Rna Seq ◽  
Ppi Network ◽  
Learning Methods ◽  
Transcriptomic Data ◽  
Machine Learning Methods

Abstract Background Hypertrophic cardiomyopathy (HCM) represents one of the most common inherited heart diseases. To identify key molecules involved in the development of HCM, gene expression patterns of the heart tissue samples in HCM patients from multiple microarray and RNA-seq platforms were investigated. Methods The significant genes were obtained through the intersection of two gene sets, corresponding to the identified differentially expressed genes (DEGs) within the microarray data and within the RNA-Seq data. Those genes were further ranked using minimum-Redundancy Maximum-Relevance feature selection algorithm. Moreover, the genes were assessed by three different machine learning methods for classification, including support vector machines, random forest and k-Nearest Neighbor. Results Outstanding results were achieved by taking exclusively the top eight genes of the ranking into consideration. Since the eight genes were identified as candidate HCM hallmark genes, the interactions between them and known HCM disease genes were explored through the protein–protein interaction (PPI) network. Most candidate HCM hallmark genes were found to have direct or indirect interactions with known HCM diseases genes in the PPI network, particularly the hub genes JAK2 and GADD45A. Conclusions This study highlights the transcriptomic data integration, in combination with machine learning methods, in providing insight into the key hallmark genes in the genetic etiology of HCM.

scholarly journals Clustering Single-Cell RNA-Seq Data with Regularized Gaussian Graphical Model

Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 311
Author(s):  
Zhenqiu Liu
Keyword(s):  
Single Cell ◽  
Free Parameter ◽  
Graphical Model ◽  
Expression Patterns ◽  
Information Criterion ◽  
Log P ◽  
Rna Seq ◽  
Clustering Methods ◽  
Wide Range ◽  
Free Parameters

Single-cell RNA-seq (scRNA-seq) is a powerful tool to measure the expression patterns of individual cells and discover heterogeneity and functional diversity among cell populations. Due to variability, it is challenging to analyze such data efficiently. Many clustering methods have been developed using at least one free parameter. Different choices for free parameters may lead to substantially different visualizations and clusters. Tuning free parameters is also time consuming. Thus there is need for a simple, robust, and efficient clustering method. In this paper, we propose a new regularized Gaussian graphical clustering (RGGC) method for scRNA-seq data. RGGC is based on high-order (partial) correlations and subspace learning, and is robust over a wide-range of a regularized parameter λ. Therefore, we can simply set λ=2 or λ=log(p) for AIC (Akaike information criterion) or BIC (Bayesian information criterion) without cross-validation. Cell subpopulations are discovered by the Louvain community detection algorithm that determines the number of clusters automatically. There is no free parameter to be tuned with RGGC. When evaluated with simulated and benchmark scRNA-seq data sets against widely used methods, RGGC is computationally efficient and one of the top performers. It can detect inter-sample cell heterogeneity, when applied to glioblastoma scRNA-seq data.

scholarly journals MicroRNA-27b-3p Targets the Myostatin Gene to Regulate Myoblast Proliferation and Is Involved in Myoblast Differentiation

Cells ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 423
Author(s):  
Genxi Zhang ◽  
Mingliang He ◽  
Pengfei Wu ◽  
Xinchao Zhang ◽  
Kaizhi Zhou ◽  
...  
Keyword(s):  
Muscle Growth ◽  
Luciferase Reporter ◽  
Myoblast Differentiation ◽  
Regulation Mechanism ◽  
Rna Seq ◽  
Myostatin Gene ◽  
Primary Myoblasts ◽  
Chicken Muscle ◽  
Proliferation And Differentiation ◽  
Myoblast Proliferation

microRNAs play an important role in the growth and development of chicken embryos, including the regulation of skeletal muscle genesis, myoblast proliferation, differentiation, and apoptosis. Our previous RNA-seq studies showed that microRNA-27b-3p (miR-27b-3p) might play an important role in regulating the proliferation and differentiation of chicken primary myoblasts (CPMs). However, the mechanism of miR-27b-3p regulating the proliferation and differentiation of CPMs is still unclear. In this study, the results showed that miR-27b-3p significantly promoted the proliferation of CPMs and inhibited the differentiation of CPMs. Then, myostatin (MSTN) was confirmed to be the target gene of miR-27b-3p by double luciferase reporter assay, RT-qPCR, and Western blot. By overexpressing and interfering with MSTN expression in CPMs, the results showed that overexpression of MSTN significantly inhibited the proliferation and differentiation of CPMs. In contrast, interference of MSTN expression had the opposite effect. This study showed that miR-27b-3p could promote the proliferation of CPMs by targeting MSTN. Interestingly, both miR-27b-3p and MSTN can inhibit the differentiation of CPMs. These results provide a theoretical basis for further understanding the function of miR-27b-3p in chicken and revealing its regulation mechanism on chicken muscle growth.

scholarly journals Gene Expression Profile and Co-Expression Network of Pearl Gentian Grouper under Cold Stress by Integrating Illumina and PacBio Sequences

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1745
Author(s):  
Ben-Ben Miao ◽  
Su-Fang Niu ◽  
Ren-Xie Wu ◽  
Zhen-Bang Liang ◽  
Bao-Gui Tang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cold Stress ◽  
Differential Expression Analysis ◽  
Endocrine System ◽  
Control Group ◽  
Regulation Mechanism ◽  
Rna Seq ◽  
Cold Tolerant ◽  
Stress Signals ◽  
Membrane Changes

Pearl gentian grouper (Epinephelus fuscoguttatus ♀ × Epinephelus lanceolatus ♂) is a fish of high commercial value in the aquaculture industry in Asia. However, this hybrid fish is not cold-tolerant, and its molecular regulation mechanism underlying cold stress remains largely elusive. This study thus investigated the liver transcriptomic responses of pearl gentian grouper by comparing the gene expression of cold stress groups (20, 15, 12, and 12 °C for 6 h) with that of control group (25 °C) using PacBio SMRT-Seq and Illumina RNA-Seq technologies. In SMRT-Seq analysis, a total of 11,033 full-length transcripts were generated and used as reference sequences for further RNA-Seq analysis. In RNA-Seq analysis, 3271 differentially expressed genes (DEGs), two low-temperature specific modules (tan and blue modules), and two significantly expressed gene sets (profiles 0 and 19) were screened by differential expression analysis, weighted gene co-expression networks analysis (WGCNA), and short time-series expression miner (STEM), respectively. The intersection of the above analyses further revealed some key genes, such as PCK, ALDOB, FBP, G6pC, CPT1A, PPARα, SOCS3, PPP1CC, CYP2J, HMGCR, CDKN1B, and GADD45Bc. These genes were significantly enriched in carbohydrate metabolism, lipid metabolism, signal transduction, and endocrine system pathways. All these pathways were linked to biological functions relevant to cold adaptation, such as energy metabolism, stress-induced cell membrane changes, and transduction of stress signals. Taken together, our study explores an overall and complex regulation network of the functional genes in the liver of pearl gentian grouper, which could benefit the species in preventing damage caused by cold stress.

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