Pre- and postnatal hepatic gene expression profiles of two pig breeds differing in body composition: insight into pathways of metabolic regulation

2007 ◽  
Vol 29 (3) ◽  
pp. 267-279 ◽  
Author(s):  
Siriluck Ponsuksili ◽  
Eduard Murani ◽  
Christina Walz ◽  
Manfred Schwerin ◽  
Klaus Wimmers
Keyword(s):  
Body Composition ◽  
Metabolic Regulation ◽  
Time Course ◽  
Developmental Stages ◽  
Expression Profiles ◽  
Cell Activity ◽  
Gene Expression Profiles ◽  
Prenatal Development ◽  
Glycogen Accumulation ◽  
Insight Into

The liver plays a central role in the regulation of the metabolic status, partitioning of nutrients, and expenditure of energy. To gain insight into hepatic metabolic pathways and key transcripts affecting traits related to body composition, liver expression profiles were compared of pigs of two breeds, the obese German Landrace (DL) and the lean Pietrain (Pi). Porcine oligonucleotide microarray were hybridized with liver cRNAs obtained at peripubertal age (180 days of age) and prenatal stages (35, 63, and 91 days postconception) that represent three developmental stages of liver, i.e., period of differentiation, period of metabolic activity, and period of glycogen accumulation. In terms of the number of genes regulated between DL and Pi, the most striking distinctions were found at peripubertal age with upregulation of key genes of lipid metabolism pathways (FASN, ACSS2, ACACA) in obese DL pigs and upregulation of genes of cell growth and/or maintenance, and protein syntheses, as well as cell proliferation pathways (PPARD, POU1F1, IGF2R), in lean Pi pigs. Moreover, time course analysis of breed-dependent expression profiles revealed breed-typical temporal regulation from prenatal stages to peripubertal age of genes assigned to biological processes involving lipid pathways and cell activity, i.e., breed differences are already initiated during early prenatal development. Information about mRNA expression levels of the two breeds differing in body composition, partitioning and utilization of nutrients and energy reveals functional candidate genes for traits related to obesity and leanness.

scholarly journals RNA-Seq analysis of genes affected by Cyclophilin A/DIAGEOTROPICA (DGT) in tomato root development

2020 ◽  
Author(s):  
Maria G. Ivanchenko ◽  
Olivia R. Ozguc ◽  
Stephanie R. Bollmann ◽  
Valerie N. Fraser ◽  
Molly Megraw
Keyword(s):  
Developmental Stages ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cyclophilin A ◽  
Developmental Pathways ◽  
Root Tip ◽  
Rna Seq ◽  
Tomato Root ◽  
Initial Comparison ◽  
Insight Into

AbstractCyclophilin A/DIAGEOTROPICA (DGT) has been linked to auxin-regulated development in tomato and appears to affect multiple developmental pathways. Loss of DGT function results in a pleiotropic phenotype that is strongest in the roots, including shortened roots with no lateral branching. Here, we present an RNA-Seq dataset comparing the gene expression profiles of wildtype (‘Ailsa Craig’) and dgt tissues from three spatially separated developmental stages of the tomato root tip, with three replicates for each tissue and genotype. We also identify differentially expressed genes, provide an initial comparison of genes affected in each genotype and tissue, and provide the pipeline used to analyze the data. Further analysis of this dataset can be used to gain insight into the effects of DGT on various root developmental pathways in tomato.

Gene expression profiles of bovine genital ridges during sex determination and early differentiation of the gonads†

2019 ◽  
Author(s):  
Benjamín Planells ◽  
Isabel Gómez-Redondo ◽  
José María Sánchez ◽  
Michael McDonald ◽  
Ángela Cánovas ◽  
...  
Keyword(s):  
Sex Determination ◽  
Nuclear Export ◽  
Time Course ◽  
Developmental Stages ◽  
Current Knowledge ◽  
Expression Profiles ◽  
Gene Activation ◽  
Gene Expression Profiles ◽  
Early Differentiation

AbstractMost current knowledge of sex determination in mammals has emerged from mouse and human studies. To investigate the molecular regulation of the sex determination process in cattle, we used an RNA sequencing strategy to analyze the transcriptome landscape of male and female bovine fetal gonads collected in vivo at key developmental stages: before, during, and after SRY gene activation on fetal days D35 (bipotential gonad formation), D39 (peak SRY expression), and D43 (early gonad differentiation). Differentially expressed genes (DEGs) were identified in male vs. female germinal ridges and among group genes showing similar expression profiles during the three periods. There were 143, 96, and 658 DEG between males and female fetuses at D35, D39, and D43, respectively. On D35, genes upregulated in females were enriched in translation, nuclear export, RNA localization, and mRNA splicing events, whereas those upregulated in males were enriched in cell proliferation regulation and male sex determination terms. In time-course experiments, 767 DEGs in males and 545 DEGs in females were identified between D35 vs. D39, and 3157 DEGs in males and 2008 in females were identified between D39 vs. D43. Results highlight unique aspects of sex determination in cattle, such as the expression of several Y chromosome genes (absent in mice and humans) before SRY expression and an abrupt increase in the nuclear expression of SOX10 (instead of SOX9 expression in the Sertoli cell cytoplasm as observed in mice) during male determination and early differentiation.

scholarly journals RNA-Seq analysis of genes affected by Cyclophilin A/DIAGEOTROPICA (DGT) in tomato root development

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 1175
Author(s):  
Maria G. Ivanchenko ◽  
Olivia R. Ozguc ◽  
Stephanie R. Bollmann ◽  
Valerie N. Fraser ◽  
Molly Megraw
Keyword(s):  
Developmental Stages ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cyclophilin A ◽  
Developmental Pathways ◽  
Root Tip ◽  
Rna Seq ◽  
Tomato Root ◽  
Initial Comparison ◽  
Insight Into

Cyclophilin A/DIAGEOTROPICA (DGT) has been linked to auxin-regulated development in tomato and appears to affect multiple developmental pathways. Loss of DGT function results in a pleiotropic phenotype that is strongest in the roots, including shortened roots with no lateral branching. Here, we present an RNA-Seq dataset comparing the gene expression profiles of wildtype (‘Ailsa Craig’) and dgt tissues from three spatially separated developmental stages of the tomato root tip, with three replicates for each tissue and genotype. We also identify differentially expressed genes, provide an initial comparison of genes affected in each genotype and tissue, and provide the pipeline used to analyze the data. Further analysis of this dataset can be used to gain insight into the effects of DGT on various root developmental pathways in tomato.

scholarly journals Genome-Wide Gene Expression Profiles Reveal Distinct Molecular Characteristics of the Goose Granulosa Cells

2021 ◽  
Vol 12 ◽  
Author(s):  
Guangliang Gao ◽  
Silu Hu ◽  
Keshan Zhang ◽  
Haiwei Wang ◽  
Youhui Xie ◽  
...  
Keyword(s):  
Granulosa Cells ◽  
Time Course ◽  
Developmental Stages ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Follicular Development ◽  
Egg Laying ◽  
Molecular Characteristics ◽  
Genome Wide ◽  
Laying Performance

Granulosa cells (GCs) are decisive players in follicular development. In this study, the follicle tissues and GCs were isolated from the goose during the peak-laying period to perform hematoxylin-eosin staining and RNA-seq, respectively. Moreover, the dynamic mRNA and lncRNA expression profiles and mRNA-lncRNA network analysis were integrated to identify the important genes and lncRNAs. The morphological analysis showed that the size of the GCs did not significantly change, but the thickness of the granulosa layer cells differed significantly across the developmental stages. Subsequently, 14,286 mRNAs, 3,956 lncRNAs, and 1,329 TUCPs (transcripts with unknown coding potential) were detected in the GCs. We identified 37 common DEGs in the pre-hierarchical and hierarchical follicle stages, respectively, which might be critical for follicle development. Moreover, 3,089 significant time-course DEGs (Differentially expressed genes) and 13 core genes in 4 clusters were screened during goose GCs development. Finally, the network lncRNA G8399 with CADH5 and KLF2, and lncRNA G8399 with LARP6 and EOMES were found to be important for follicular development in GCs. Thus, the results would provide a rich resource for elucidating the reproductive biology of geese and accelerate the improvement of the egg-laying performance of geese.

scholarly journals Bayesian approach for predicting responses to therapy from high-dimensional time-course gene expression profiles

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Arika Fukushima ◽  
Masahiro Sugimoto ◽  
Satoru Hiwa ◽  
Tomoyuki Hiroyasu
Keyword(s):  
Gene Expression ◽  
Time Course ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Response To Therapy ◽  
Hcv Infection ◽  
Entire Treatment Period ◽  
Time Points ◽  
Time Course Data ◽  
Conventional Methods

Abstract Background Historical and updated information provided by time-course data collected during an entire treatment period proves to be more useful than information provided by single-point data. Accurate predictions made using time-course data on multiple biomarkers that indicate a patient’s response to therapy contribute positively to the decision-making process associated with designing effective treatment programs for various diseases. Therefore, the development of prediction methods incorporating time-course data on multiple markers is necessary. Results We proposed new methods that may be used for prediction and gene selection via time-course gene expression profiles. Our prediction method consolidated multiple probabilities calculated using gene expression profiles collected over a series of time points to predict therapy response. Using two data sets collected from patients with hepatitis C virus (HCV) infection and multiple sclerosis (MS), we performed numerical experiments that predicted response to therapy and evaluated their accuracies. Our methods were more accurate than conventional methods and successfully selected genes, the functions of which were associated with the pathology of HCV infection and MS. Conclusions The proposed method accurately predicted response to therapy using data at multiple time points. It showed higher accuracies at early time points compared to those of conventional methods. Furthermore, this method successfully selected genes that were directly associated with diseases.

scholarly journals Genome-Wide Identification of Soybean ABC Transporters Relate to Aluminum Toxicity

2021 ◽  
Vol 22 (12) ◽  
pp. 6556
Author(s):  
Junjun Huang ◽  
Xiaoyu Li ◽  
Xin Chen ◽  
Yaru Guo ◽  
Weihong Liang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Abc Transporters ◽  
Developmental Stages ◽  
Aluminum Toxicity ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Purifying Selection ◽  
Biotic Stresses ◽  
Genome Wide ◽  
New Germplasm

ATP-binding cassette (ABC) transporter proteins are a gene super-family in plants and play vital roles in growth, development, and response to abiotic and biotic stresses. The ABC transporters have been identified in crop plants such as rice and buckwheat, but little is known about them in soybean. Soybean is an important oil crop and is one of the five major crops in the world. In this study, 255 ABC genes that putatively encode ABC transporters were identified from soybean through bioinformatics and then categorized into eight subfamilies, including 7 ABCAs, 52 ABCBs, 48 ABCCs, 5 ABCDs, 1 ABCEs, 10 ABCFs, 111 ABCGs, and 21 ABCIs. Their phylogenetic relationships, gene structure, and gene expression profiles were characterized. Segmental duplication was the main reason for the expansion of the GmABC genes. Ka/Ks analysis suggested that intense purifying selection was accompanied by the evolution of GmABC genes. The genome-wide collinearity of soybean with other species showed that GmABCs were relatively conserved and that collinear ABCs between species may have originated from the same ancestor. Gene expression analysis of GmABCs revealed the distinct expression pattern in different tissues and diverse developmental stages. The candidate genes GmABCB23, GmABCB25, GmABCB48, GmABCB52, GmABCI1, GmABCI5, and GmABCI13 were responsive to Al toxicity. This work on the GmABC gene family provides useful information for future studies on ABC transporters in soybean and potential targets for the cultivation of new germplasm resources of aluminum-tolerant soybean.

scholarly journals Prediction of Pharmacological and Xenobiotic Responses to Drugs Based on Time Course Gene Expression Profiles

PLoS ONE ◽  
2009 ◽  
Vol 4 (12) ◽  
pp. e8126 ◽  
Author(s):  
Tao Huang ◽  
WeiRen Cui ◽  
LeLe Hu ◽  
KaiYan Feng ◽  
Yi-Xue Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Time Course ◽  
Expression Profiles ◽  
Gene Expression Profiles

Classical Cancer Biology: Misconceptions and Limitations

2017 ◽  
Author(s):  
Abicumaran Uthamacumaran
Keyword(s):  
Cancer Cells ◽  
Cancer Biology ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Transformed Cells ◽  
Epigenetic Landscape ◽  
Normal Cells ◽  
Cancer Models ◽  
Stem Cell Division ◽  
Insight Into

Cancer is the co-evolution of cancer cells and their turbulent microenvironment, characterized by dynamical hyper-chaotic gene expression profiles. However, cancers should not be viewed as the result of random mutations and malfunctioning information processing systems. Rather, it is the selective advantages conferred by adaptive evolution of cellular biosystems. Although on a systemic scale, cancer is defined as a disease, on a cellular basis they outperform healthy (non-transformed cells) in terms of survival and reproductive success. Their enhanced longevity pathways, metastatic invasion, extended telomeres, dynamical morphogenesis, regenerative stem cell division and environment-specific metabolic cascades indicate they are adaptive evolutionary cell states that have surpassed the boundaries normal cells are confined to. Therefore, the paper presents a brief summary of currently existing classical cancer models in the field of mathematical biology and the misconceptions of cancer epimetabolomes to further advance cancer research beyond its current limits. Through an insight into the mathematical behaviors of cancer cells, a quantum adaptive epigenetic landscape is proposed to explain the selective evolutionary dominance of cancer cells.

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