scholarly journals Transcriptome Profiling across Five Tissues of Giant Panda

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Feng Li ◽  
Chengdong Wang ◽  
Zhongxian Xu ◽  
Mingzhou Li ◽  
Linhua Deng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Giant Panda ◽  
Expression Patterns ◽  
Genetic Research ◽  
Gene Expression Pattern ◽  
Transcriptome Profiling ◽  
Ailuropoda Melanoleuca ◽  
Ppi Network ◽  
Illumina Hiseq ◽  
Lung And Kidney

Gene differential expression studies can serve to explore and understand the laws and characteristics of animal life activities, and the difference in gene expression between different animal tissues has been well demonstrated and studied. However, for the world-famous rare and protected species giant panda (Ailuropoda melanoleuca), only the transcriptome of the blood and spleen has been reported separately. Here, in order to explore the transcriptome differences between the different tissues of the giant panda, transcriptome profiles of the heart, liver, spleen, lung, and kidney from five captive giant pandas were constructed with Illumina HiSeq 2500 platform. The comparative analysis of the intertissue gene expression patterns was carried out based on the generated RNA sequencing datasets. Analyses of Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein-protein interaction (PPI) network were performed according to the identified differentially expressed genes (DEGs). We generated 194.52 GB clean base data from twenty-five sequencing libraries and identified 18,701 genes, including 3492 novel genes. With corrected p value <0.05 and |log2FoldChange| >2, we finally obtained 921, 553, 574, 457, and 638 tissue-specific DEGs in the heart, liver, spleen, lung, and kidney, respectively. In addition, we identified TTN, CAV3, LDB3, TRDN, and ACTN2 in the heart; FGA, AHSG, and SERPINC1 in the liver; CD19, CD79B, and IL21R in the spleen; NKX2-4 and SFTPB in the lung; GC and HRG in the kidney as hub genes in the PPI network. The results of the analyses showed a similar gene expression pattern between the spleen and lung. This study provided for the first time the heart, liver, lung, and kidney’s transcriptome resources of the giant panda, and it provided a valuable resource for further genetic research or other potential research.

Distinct gene expression patterns in chronic lymphocytic leukemia defined by usage of specific VH genes

Blood ◽  
2006 ◽  
Vol 107 (5) ◽  
pp. 2090-2093 ◽  
Author(s):  
Dirk Kienle ◽  
Axel Benner ◽  
Alexander Kröber ◽  
Dirk Winkler ◽  
Daniel Mertens ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chronic Lymphocytic Leukemia ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Cell Receptor ◽  
Lymphocytic Leukemia ◽  
Expression Of Genes ◽  
Vh Genes ◽  
Signaling Activation

The mutation status and usage of specific VH genes such as V3-21 and V1-69 are potentially independent pathogenic and prognostic factors in chronic lymphocytic leukemia (CLL). To investigate the role of antigenic stimulation, we analyzed the expression of genes involved in B-cell receptor (BCR) signaling/activation, cell cycle, and apoptosis control in CLL using these specific VH genes compared to VH mutated (VH-MUT) and VH unmutated (VH-UM) CLL not using these VH genes. V3-21 cases showed characteristic expression differences compared to VH-MUT (up: ZAP70 [or ZAP-70]; down: CCND2, P27) and VH-UM (down: PI3K, CCND2, P27, CDK4, BAX) involving several BCR-related genes. Similarly, there was a marked difference between VH unmutated cases using the V1-69 gene and VH-UM (up: FOS; down: BLNK, SYK, CDK4, TP53). Therefore, usage of specific VH genes appears to have a strong influence on the gene expression pattern pointing to antigen recognition and ongoing BCR stimulation as a pathogenic factor in these CLL subgroups.

scholarly journals Verticillium wilt resistant and susceptible olive cultivars express a very different basal set of genes in roots

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jorge A. Ramírez-Tejero ◽  
Jaime Jiménez-Ruiz ◽  
Alicia Serrano ◽  
Angjelina Belaj ◽  
Lorenzo León ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Pattern ◽  
Growth And Development ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Expression Level ◽  
Resistant Cultivars ◽  
Pathogen Invasion ◽  
Wide Range ◽  
Olive Cultivars

Abstract Background Olive orchards are threatened by a wide range of pathogens. Of these, Verticillium dahliae has been in the spotlight for its high incidence, the difficulty to control it and the few cultivars that has increased tolerance to the pathogen. Disease resistance not only depends on detection of pathogen invasion and induction of responses by the plant, but also on barriers to avoid the invasion and active resistance mechanisms constitutively expressed in the absence of the pathogen. In a previous work we found that two healthy non-infected plants from cultivars that differ in V. dahliae resistance such as ‘Frantoio’ (resistant) and ‘Picual’ (susceptible) had a different root morphology and gene expression pattern. In this work, we have addressed the issue of basal differences in the roots between Resistant and Susceptible cultivars. Results The gene expression pattern of roots from 29 olive cultivars with different degree of resistance/susceptibility to V. dahliae was analyzed by RNA-Seq. However, only the Highly Resistant and Extremely Susceptible cultivars showed significant differences in gene expression among various groups of cultivars. A set of 421 genes showing an inverse differential expression level between the Highly Resistant to Extremely Susceptible cultivars was found and analyzed. The main differences involved higher expression of a series of transcription factors and genes involved in processes of molecules importation to nucleus, plant defense genes and lower expression of root growth and development genes in Highly Resistant cultivars, while a reverse pattern in Moderately Susceptible and more pronounced in Extremely Susceptible cultivars were observed. Conclusion According to the different gene expression patterns, it seems that the roots of the Extremely Susceptible cultivars focus more on growth and development, while some other functions, such as defense against pathogens, have a higher expression level in roots of Highly Resistant cultivars. Therefore, it seems that there are constitutive differences in the roots between Resistant and Susceptible cultivars, and that susceptible roots seem to provide a more suitable environment for the pathogen than the resistant ones.

scholarly journals Unique Gene Expression Patterns in Human T-cell Lines Generated from Multiple Sclerosis Patients by Stimulation with a Synthetic MOG Peptide

2005 ◽  
Vol 12 (3) ◽  
pp. 203-209 ◽  
Author(s):  
Mathilda Mandel ◽  
Michael Gurevich ◽  
Gad Lavie ◽  
Irun R. Cohen ◽  
Anat Achiron
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
T Cell ◽  
Cell Lines ◽  
Healthy Subjects ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Gene Expression Patterns ◽  
T Cell Lines ◽  
Myelin Antigens

Multiple sclerosis (MS) is an autoimmune disease where T-cells activated against myelin antigens are involved in myelin destruction. Yet, healthy subjects also harbor T-cells responsive to myelin antigens, suggesting that MS patient-derived autoimmune T-cells might bear functional differences from T-cells derived from healthy individuals. We addressed this issue by analyzing gene expression patterns of myelin oligodendrocytic glycoprotein (MOG) responsive T-cell lines generated from MS patients and healthy subjects. We identified 150 transcripts that were differentially expressed between MS patients and healthy controls. The most informative 43 genes exhibited >1.5-fold change in expression level. Eighteen genes were up-regulated including BCL2, lifeguard, IGFBP3 and VEGF. Twenty five genes were down-regulated, including apoptotic activators like TNF and heat shock protein genes. This gene expression pattern was unique to MOG specific T-cell lines and was not expressed in T-cell lines reactive to tetanus toxin (TTX). Our results indicate that activation in MS that promotes T-cell survival and expansion, has its own state and that the unique gene expression pattern that characterize autoreactive T-cells in MS represent a constellation of factors in which the chronicity, timing and accumulation of damage make the difference between health and disease.

scholarly journals Combined Metabolome and Transcriptome Profiling Reveal Optimal Harvest Strategy Model Based on Different Production Purposes in Olive

Foods ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 360
Author(s):  
Guodong Rao ◽  
Jianguo Zhang ◽  
Xiaoxia Liu ◽  
Xue Li ◽  
Chenhe Wang
Keyword(s):  
Gene Expression ◽  
Olive Oil ◽  
Expression Patterns ◽  
Transcriptome Profiling ◽  
Minor Components ◽  
Harvest Time ◽  
Rna Seq ◽  
Optimal Harvest ◽  
Harvest Strategy ◽  
Different Color

Olive oil has been favored as high-quality edible oil because it contains balanced fatty acids (FAs) and high levels of minor components. The contents of FAs and minor components are variable in olive fruits of different color at harvest time, which render it difficult to determine the optimal harvest strategy for olive oil producing. Here, we combined metabolome, Pacbio Iso-seq, and Illumina RNA-seq transcriptome to investigate the association between metabolites and gene expression of olive fruits at harvest time. A total of 34 FAs, 12 minor components, and 181 other metabolites (including organic acids, polyols, amino acids, and sugars) were identified in this study. Moreover, we proposed optimal olive harvesting strategy models based on different production purposes. In addition, we used the combined Pacbio Iso-seq and Illumina RNA-seq gene expression data to identify genes related to the biosynthetic pathways of hydroxytyrosol and oleuropein. These data lay the foundation for future investigations of olive fruit metabolism and gene expression patterns, and provide a method to obtain olive harvesting strategies for different production purposes.

Biological Image Analysis via Matrix Approximation

2011 ◽  
pp. 166-170
Author(s):  
Jieping Ye ◽  
Ravi Janardan ◽  
Sudhir Kumar
Keyword(s):  
Gene Expression ◽  
Expression Pattern ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Controlled Vocabulary ◽  
Gene Expression Patterns ◽  
Image Content ◽  
Gene Expressions ◽  
Microarray Gene Expression ◽  
Individual Gene

Understanding the roles of genes and their interactions is one of the central challenges in genome research. One popular approach is based on the analysis of microarray gene expression data (Golub et al., 1999; White, et al., 1999; Oshlack et al., 2007). By their very nature, these data often do not capture spatial patterns of individual gene expressions, which is accomplished by direct visualization of the presence or absence of gene products (mRNA or protein) (e.g., Tomancak et al., 2002; Christiansen et al., 2006). For instance, the gene expression pattern images of a Drosophila melanogaster embryo capture the spatial and temporal distribution of gene expression patterns at a given developmental stage (Bownes, 1975; Tsai et al., 1998; Myasnikova et al., 2002; Harmon et al., 2007). The identification of genes showing spatial overlaps in their expression patterns is fundamentally important to formulating and testing gene interaction hypotheses (Kumar et al., 2002; Tomancak et al., 2002; Gurunathan et al., 2004; Peng & Myers, 2004; Pan et al., 2006). Recent high-throughput experiments of Drosophila have produced over fifty thousand images (http://www. fruitfly.org/cgi-bin/ex/insitu.pl). It is thus desirable to design efficient computational approaches that can automatically retrieve images with overlapping expression patterns. There are two primary ways of accomplishing this task. In one approach, gene expression patterns are described using a controlled vocabulary, and images containing overlapping patterns are found based on the similarity of textual annotations. In the second approach, the most similar expression patterns are identified by a direct comparison of image content, emulating the visual inspection carried out by biologists [(Kumar et al., 2002); see also www.flyexpress.net]. The direct comparison of image content is expected to be complementary to, and more powerful than, the controlled vocabulary approach, because it is unlikely that all attributes of an expression pattern can be completely captured via textual descriptions. Hence, to facilitate the efficient and widespread use of such datasets, there is a significant need for sophisticated, high-performance, informatics-based solutions for the analysis of large collections of biological images.

scholarly journals Regional heterogeneity in rat Peyer’s patches through whole transcriptome analysis

2020 ◽  
pp. 153537022097301
Author(s):  
Charles L Phillips ◽  
Bradley A Welch ◽  
Michael R Garrett ◽  
Bernadette E Grayson
Keyword(s):  
Gene Expression ◽  
Small Intestine ◽  
Transcriptome Analysis ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Peyer's Patches ◽  
Peyer’S Patches ◽  
Junction Protein ◽  
Whole Transcriptome Analysis ◽  
Whole Transcriptome

Peyer’s patches are gut-associated lymphoid tissue located throughout the intestinal wall. Peyer’s patches consist of highly organized ovoid-shaped follicles, classified as non-encapsulated lymphatic tissues, populated with B cells, T cells, macrophages, and dendritic cells and function as an organism’s intestinal surveillance. Limited work compares the gene profiles of Peyer’s patches derived from different intestinal regions. In the current study, we first performed whole transcriptome analysis using RNAseq to compare duodenal and ileal Peyer’s patches obtained from the small intestine of Long Evans rats. Of the 12,300 genes that were highly expressed, 18.5% were significantly different between the duodenum and ileum. Using samples obtained from additional subjects ( n = 10), we validated the novel gene expression patterns in Peyer’s patches obtained from the three regions of the small intestine. Rats had a significantly reduced number of Peyer’s patches in the duodenum in comparison to either the jejunum or ileum. Regional differences in structural, metabolic, and immune-related genes were validated. Genes such as alcohol dehydrogenase 1, gap junction protein beta 2, and serine peptidase inhibitor clade b, member 1a were significantly reduced in the ileum in comparison to other regions. On the other hand, genes such as complement C3d receptor type, lymphocyte cytosolic protein 1, and lysozyme C2 precursor were significantly lower in the duodenum. In summary, the gene expression pattern of Peyer’s patches is influenced by intestinal location and may contribute to its role in that segment.

scholarly journals Transcriptome analysis reveals immune-related gene expression changes with age in giant panda (Ailuropoda melanoleuca) blood

Aging ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 249-262 ◽  
Author(s):  
Lianming Du ◽  
Qin Liu ◽  
Fujun Shen ◽  
Zhenxin Fan ◽  
Rong Hou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcriptome Analysis ◽  
Giant Panda ◽  
Ailuropoda Melanoleuca ◽  
Related Gene ◽  
Immune Related Gene

scholarly journals Identification of Differential Gene Expression Pattern in Lens Epithelial Cells Derived from Cataractous and Noncataractous Lenses of Shumiya Cataract Rat

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Hidetoshi Ishida ◽  
Teppei Shibata ◽  
Yuka Nakamura ◽  
Yasuhito Ishigaki ◽  
Dhirendra P. Singh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Epithelial Cells ◽  
Expression Patterns ◽  
Synergetic Effect ◽  
Gene Expression Pattern ◽  
Lens Opacity ◽  
Lens Epithelial Cells ◽  
Lens Fiber ◽  
Molecular Events ◽  
Old Rats

The Shumiya cataract rat (SCR) is a model for hereditary cataract. Two-thirds of these rats develop lens opacity within 10-11 weeks. Onset of cataract is attributed to the synergetic effect of lanosterol synthase (Lss) and farnesyl-diphosphate farnesyltransferase 1 (Fdft1) mutant alleles that lead to cholesterol deficiency in the lenses, which in turn adversely affects lens biology including the growth and differentiation of lens epithelial cells (LECs). Nevertheless, the molecular events and changes in gene expression associated with the onset of lens opacity in SCR are poorly understood. In the present study, a microarray-based approach was employed to analyze comparative gene expression changes in LECs isolated from the precataractous and cataractous stages of lenses of 5-week-old SCRs. The changes in gene expression observed in microarray results in the LECs were further validated using real-time reverse transcribed quantitative PCR (RT-qPCR) in 5-, 8-, and 10-week-old SCRs. A mild posterior and cortical opacity was observed in 5-week-old rats. Expressions of approximately 100 genes, including the major intrinsic protein of the lens fiber (Mip and Aquaporin 0), deoxyribonuclease II beta (Dnase2B), heat shock protein B1 (HspB1), and crystallin γ (γCry) B, C, and F, were found to be significantly downregulated (0.07-0.5-fold) in rat LECs derived from cataract lenses compared to that in noncataractous lenses (control). Thus, our study was aimed at identifying the gene expression patterns during cataract formation in SCRs, which may be responsible for cataractogenesis in SCR. We proposed that cataracts in SCR are associated with reduced expression of these lens genes that have been reported to be related with lens fiber differentiation. Our findings may have wider implications in understanding the effect of cholesterol deficiency and the role of cholesterol-lowering therapeutics on cataractogenesis.

scholarly journals RNAseq Studies Reveal Distinct Transcriptional Response to Vitamin a (VA) Deficiency in Small Intestine (SI) versus Colon, Discovering Novel VA-regulated Genes (P15-002-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Zhi Chai ◽  
Yafei Lyu ◽  
Qiuyan Chen ◽  
Cheng-Hsin Wei ◽  
Lindsay Snyder ◽  
...  
Keyword(s):  
Gene Expression ◽  
Small Intestine ◽  
Vitamin A ◽  
Target Genes ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Differentially Expressed Gene ◽  
Gene Expression Profiles ◽  
Illumina Hiseq ◽  
The Impact

Abstract Objectives To characterize and compare the impact of vitamin A (VA) deficiency on gene expression patterns in the small intestine (SI) and the colon, and to discover novel target genes in VA-related biological pathways. Methods vitamin A deficient (VAD) mice were generated by feeding VAD diet to pregnant C57/BL6 dams and their post-weaning offspring. Total mRNA extracted from SI and colon were sequenced using Illumina HiSeq 2500 platform. Differentially Expressed Gene (DEG), Gene Ontology (GO) enrichment, and Weighted Gene Co-expression Network Analysis (WGCNA) were performed to characterize expression patterns and co-expression patterns. Results The comparison between vitamin A sufficient (VAS) and VAD groups detected 49 and 94 DEGs in SI and colon, respectively. According to GO information, DEGs in the SI demonstrated significant enrichment in categories relevant to retinoid metabolic process, molecule binding, and immune function. Immunity related pathways, such as “humoral immune response” and “complement activation,” were positively associated with VA in SI. On the contrary, in colon, “cell division” was the only enriched category and was negatively associated with VA. WGCNA identified modules significantly correlated with VA status in SI and in colon. One of those modules contained five known retinoic acid targets. Therefore we have prioritized the other module members (e.g., Mbl2, Mmp9, Mmp13, Cxcl14 and Pkd1l2) to be investigated as candidate genes regulated by VA. Comparison of co-expression modules between SI and colon indicated distinct VA effects on these two organs. Conclusions The results show that VA deficiency alters the gene expression profiles in SI and colon quite differently. Some immune-related genes (Mbl2, Mmp9, Mmp13, Cxcl14 and Pkd1l2) may be novel targets under the control of VA in SI. Funding Sources NIH training grant and NIH research grant. Supporting Tables, Images and/or Graphs

FOXA1 in breast cancer

2009 ◽  
Vol 11 ◽  
Author(s):  
Harikrishna Nakshatri ◽  
Sunil Badve
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Transcription Factor ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Gene Expression Signature ◽  
Specific Gene ◽  
Breast Cancers ◽  
Transcription Factor Network ◽  
Histopathological Classification

Breast cancer is a heterogeneous disease and classification is important for clinical management. At least five subtypes can be identified based on unique gene expression patterns; this subtype classification is distinct from the histopathological classification. The transcription factor network(s) required for the specific gene expression signature in each of these subtypes is currently being elucidated. The transcription factor network composed of the oestrogen (estrogen) receptor α (ERα), FOXA1 and GATA3 may control the gene expression pattern in luminal subtype A breast cancers. Breast cancers that are dependent on this network correspond to well-differentiated and hormone-therapy-responsive tumours with good prognosis. In this review, we discuss the interplay between these transcription factors with a particular emphasis on FOXA1 structure and function, and its ability to control ERα function. Additionally, we discuss modulators of FOXA1 function, ERα–FOXA1–GATA3 downstream targets, and potential therapeutic agents that may increase differentiation through FOXA1.

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