scholarly journals Identification and evaluation of suitable reference genes for gene expression analysis in rubber tree leaf

2019 ◽  
Author(s):  
xiangyu long ◽  
Jilai Lu ◽  
Nat N. V. Kav ◽  
Yunxia Qin ◽  
Yongjun Fang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Reference Genes ◽  
Rubber Tree ◽  
Ubiquitin Proteasome System ◽  
New Genes ◽  
Ubiquitin Proteasome ◽  
Suitable Reference ◽  
Tree Leaf

Abstract Backgroud Gene expression profiling is increasingly applied to investigate molecular mechanisms for which, normalization with suitable reference genes is critical. Previously we have reported several suitable reference genes for laticifer samples from rubber, however, little is known about reference genes in leaf. Results The main objective of this current study was to identify some reference genes with stable expression patterns in leaf at various developmental stages, as well as during abiotic (temperature extremes) and biotic stresses. Gene expression profiling experiments in rubber tree leaf identified the ubiquitin-proteasome system as having excellent potential as reference genes. Among a total of 30 tested genes investigated, 24 new (including 11 genes involved in the ubiquitin-proteasome system), 4 previously identified and 2 specific genes, were further evaluated using quantitative real-time PCR. Our results indicated that the new genes had better stability of expression when compared with others. For instance, an ubiquitin conjugating enzyme (RG0099) and three ubiquitin-protein ligases (RG0928, RG2190 and RG0118) expressed stably in all samples, and were confirmed to be suitable reference genes in rubber tree leaf in four different conditions. Finally, we suggest that using more than one reference gene may be appropriate in gene expression studies when employing different software to normalize gene expression data. Conclusion Our findings have significant implications for the reliability of data obtained from genomics studies in rubber tree and perhaps in other species.

scholarly journals Identification and evaluation of suitable reference genes for gene expression analysis in rubber tree leaf

2020 ◽  
Vol 47 (3) ◽  
pp. 1921-1933
Author(s):  
Xiangyu Long ◽  
Jilai Lu ◽  
Nat N. V. Kav ◽  
Yunxia Qin ◽  
Yongjun Fang
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Reference Genes ◽  
Gene Expression Analysis ◽  
Rubber Tree ◽  
Suitable Reference ◽  
Tree Leaf

Gene Expression Profiling Reveals Fundamental Differences between Leukemic Stem Cells (Lin-CD34+CD38−) and Mature Blasts (Lin−CD34+CD38+) of Acute Myeloid Leukaemia (AML) Patients.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 1377-1377
Author(s):  
Kazem Zibara ◽  
Daniel Pearce ◽  
David Taussig ◽  
Spyros Skoulakis ◽  
Simon Tomlinson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Populations ◽  
Leukemic Stem Cells ◽  
Significant Differential Expression ◽  
New Genes

Abstract The identification of LSC has important implications for future research as well as for the development of novel therapies. The phenotypic description of LSC now enables their purification and should facilitate the identification of genes that are preferentially expressed in these cells compared to normal HSC. However, gene-expression profiling is usually conducted on mononuclear cells of AML patients from either peripheral blood and/or bone marrow. These samples contain a mixture of blasts cells, normal hematopoietic cells and limited number of leukemic stem cells. Thus, this results in a composite profile that obscure differences between LSC and blasts cells with low proliferative potential. The aim of this study was to compare the gene expression profile of highly purified LSC versus leukemic blasts in order to identify genes that might have important roles in driving the leukemia. For this purpose, we analyzed the gene expression profiles of highly purified LSCs (Lin−CD34+CD38−) and more mature blast cells (Lin−CD34+CD38+) isolated from 7 adult AML patients. All samples were previously tested for the ability of the Lin−CD34+CD38− cells but not the Lin−CD34+CD38+ fraction to engraft using the non-obese diabetic/severe combined immuno-deficiency (NOD-SCID) repopulation assay. Affymetrix microarrays (U133A chip), containing 22,283 genes, were used for the analysis. Comparison of Lin-CD34+CD38- cell population to the Lin−CD34+CD38+ cell fraction showed 5421 genes to be expressed in both fractions. Comparative analysis of gene-expression profiles showed statistically significant differential expression of 133 genes between the 2 cell populations. Most of the genes were downregulated in the LSC-enriched fraction, compared to the more differentiated fraction. Gene ontology was used to determine the categories of the up-regulated transcripts. These transcripts, which are selectively expressed, include a number of known genes (e.g., receptors, signalling genes, proliferation and cell cycle genes and transcription factors). These genes play important roles in differentiation, self-renewal, migration and adhesion of HSCs. Among the genes showing the highest differences in expression levels were the following: ribonucleotide reductase M2 polypeptide, thymidylate synthetase, ZW10 interactor, cathepsin G, azurocidin 1, topoisomerase II, CDC20, nucleolar and spindle associated protein 1, Rac GTPase activating protein 1, leukocyte immunoglobulin-like receptor, proliferating cell nuclear antigen, myeloperoxidase, cyclin A1 (RRM2, TYMS, ZWINT, CTSG, AZU1, TOP2A, CDC20, NUSAP1, RACGAP1, LILRB2, PCNA, MPO, CCNA1). Some transcripts detected have not been implicated in HSC functions, and others have unknown function so far. This work identifies new genes that might play a role in leukemogenesis and cancer stem cells. It also leads to a better description and understanding of the molecular phenotypes of these 2 cell populations. Hence, in addition to being a more efficient way to further understand the biology of LSC, this should also provide a more efficient way of identifying new therapeutics and diagnostic targets.

scholarly journals Genome-wide identification of ubiquitin proteasome subunits as superior reference genes for transcript normalization during receptacle development in strawberry cultivars

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jianqing Chen ◽  
Jinyu Zhou ◽  
Yanhong Hong ◽  
Zekun Li ◽  
Xiangyu Cheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reference Genes ◽  
Housekeeping Genes ◽  
Ubiquitin Proteasome System ◽  
Genome Wide ◽  
A Genome ◽  
Proteasome Subunits ◽  
Ubiquitin Proteasome ◽  
Gene Transcripts ◽  
Strawberry Cultivars

Abstract Background Gene transcripts that show invariant abundance during development are ideal as reference genes (RGs) for accurate gene expression analyses, such as RNA blot analysis and reverse transcription–quantitative real time PCR (RT-qPCR) analyses. In a genome-wide analysis, we selected three “Commonly used” housekeeping genes (HKGs), fifteen “Traditional” HKGs, and nine novel genes as candidate RGs based on 80 publicly available transcriptome libraries that include data for receptacle development in eight strawberry cultivars. Results The results of the multifaceted assessment consistently revealed that expression of the novel RGs showed greater stability compared with that of the “Commonly used” and “Traditional” HKGs in transcriptome and RT-qPCR analyses. Notably, the majority of stably expressed genes were associated with the ubiquitin proteasome system. Among these, two 26 s proteasome subunits, RPT6A and RPN5A, showed superior expression stability and abundance, and are recommended as the optimal RGs combination for normalization of gene expression during strawberry receptacle development. Conclusion These findings provide additional useful and reliable RGs as resources for the accurate study of gene expression during receptacle development in strawberry cultivars.

scholarly journals Evaluation of Endogenous Reference Genes ofBactrocera (Tetradacus) minaxby Gene Expression Profiling under Various Experimental Conditions

2014 ◽  
Vol 97 (2) ◽  
pp. 597-604 ◽  
Author(s):  
Zhi-Chuang Lü ◽  
Liu-Hao Wang ◽  
Rui-Lin Dai ◽  
Gui-Fen Zhang ◽  
Jian-Ying Guo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Reference Genes ◽  
Experimental Conditions ◽  
Endogenous Reference ◽  
Endogenous Reference Genes

New genes associated with rheumatoid arthritis identified by gene expression profiling

2017 ◽  
Vol 44 (3) ◽  
pp. 107-113 ◽  
Author(s):  
H. Wang ◽  
J. Guo ◽  
J. Jiang ◽  
W. Wu ◽  
X. Chang ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
New Genes

Custom microarray for glycobiologists: considerations for glycosyltransferase gene expression profiling

2002 ◽  
Vol 69 ◽  
pp. 135-142 ◽  
Author(s):  
Elena M. Comelli ◽  
Margarida Amado ◽  
Steven R. Head ◽  
James C. Paulson
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Affymetrix Genechip ◽  
Microarray Technology ◽  
Gene Arrays ◽  
Glycosyltransferase Gene

The development of microarray technology offers the unprecedented possibility of studying the expression of thousands of genes in one experiment. Its exploitation in the glycobiology field will eventually allow the parallel investigation of the expression of many glycosyltransferases, which will ultimately lead to an understanding of the regulation of glycoconjugate synthesis. While numerous gene arrays are available on the market, e.g. the Affymetrix GeneChip® arrays, glycosyltransferases are not adequately represented, which makes comprehensive surveys of their gene expression difficult. This chapter describes the main issues related to the establishment of a custom glycogenes array.

278: Gene Expression Profiling of Prostatic Epithelial Cells in Two-Dimensional Versus Three-Dimensional Cultures

2007 ◽  
Vol 177 (4S) ◽  
pp. 93-93
Author(s):  
Toshiyuki Tsunoda ◽  
Junichi Inocuchi ◽  
Darren Tyson ◽  
Seiji Naito ◽  
David K. Ornstein
Keyword(s):  
Gene Expression ◽  
Epithelial Cells ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Three Dimensional ◽  
Two Dimensional
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