scholarly journals A Bivariate Mapping Model Identifies Major Covariation QTLs for Biomass Allocation Between Leaf and Stem Growth of Catalpa bungei

2021 ◽  
Vol 12 ◽  
Author(s):  
Miaomiao Zhang ◽  
Nan Lu ◽  
Tianqing Zhu ◽  
Guijuan Yang ◽  
Guanzheng Qu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Biomass Allocation ◽  
Expression Profiling ◽  
Genetic Architecture ◽  
Critical Role ◽  
Stem Growth ◽  
Width Ratio ◽  
Specific Gene ◽  
Mapping Model ◽  
Length Width

Biomass allocation plays a critical role in plant morphological formation and phenotypic plasticity, which greatly impact plant adaptability and competitiveness. While empirical studies on plant biomass allocation have focused on molecular biology and ecology approaches, detailed insight into the genetic basis of biomass allocation between leaf and stem growth is still lacking. Herein, we constructed a bivariate mapping model to identify covariation QTLs governing carbon (C) allocation between the leaves and stem as well as the covariation of traits within and between organs in a full-sib mapping population of C. bungei. A total of 123 covQTLs were detected for 23 trait pairs, including six leaf traits (leaf length, width, area, perimeter, length/width ratio and petiole length) and five stem traits (height, diameter at breast height, wood density, stemwood volume and stemwood biomass). The candidate genes were further identified in tissue-specific gene expression data, which provided insights into the genetic architecture underlying C allocation for traits or organs. The key QTLs related to growth and biomass allocation, which included UVH1, CLPT2, GAD/SPL, COG1 and MTERF4, were characterised and verified via gene function annotation and expression profiling. The integration of a bivariate Quantitative trait locus mapping model and gene expression profiling will enable the elucidation of genetic architecture underlying biomass allocation and covariation growth, in turn providing a theoretical basis for forest molecular marker-assisted breeding with specific C allocation strategies for adaptation to heterogeneous environments.

scholarly journals Gene Expression Profiling on Global cDNA Arrays Gives Hints Concerning Potential Signal Transduction Pathways Involved in Cardiac Fibrosis of Renal Failure

2003 ◽  
Vol 4 (6) ◽  
pp. 571-583 ◽  
Author(s):  
Kerstin Amann ◽  
Heidrun Ridinger ◽  
Christiane Rutenberg ◽  
Eberhard Ritz ◽  
Gerhard Mall ◽  
...  
Keyword(s):  
Gene Expression ◽  
Renal Failure ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Cardiac Remodelling ◽  
Cardiomyocyte Hypertrophy ◽  
Specific Gene ◽  
Interstitial Tissue ◽  
Sham Operation ◽  
Cdna Arrays

Cardiac remodelling with interstitial fibrosis in renal failure, which so far is only poorly understood on the molecular level, was investigated in the rat model by a global gene expression profiling analysis. Sprague–Dawley rats were subjected to subtotal nephrectomy (SNX) or sham operation (sham) and followed for 2 and 12 weeks, respectively. Heart-specific gene expression profiling, with RZPD Rat Unigene-1 cDNA arrays containing about 27 000 gene and EST sequences revealed substantial changes in gene expression in SNX compared to sham animals. Motor protein genes, growth and differentiation markers, and extracellular matrix genes were upregulated in SNX rats. Obviously, not only genes involved in cardiomyocyte hypertrophy, but also genes involved in the expansion of non-vascular interstitial tissue are activated very early in animals with renal failure. Together with earlier findings in the SNX model, the present data suggest the hypothesis that the local renin–angiotensin system (RAS) may be activated by at least two pathways: (a) via second messengers and Gproteins (short-term signalling); and (b) via motor proteins, actins and integrins (longterm signalling). The study documents that complex hybridization analysis yields reproducible and promising results of patterns of gene activation pointing to signalling pathways involved in cardiac remodelling in renal failure. The complete array data are available via http://www.rzpd.de/cgi-bin/services/exp/viewExpressionData.pl.cgi

scholarly journals Identification and Expression Profiling of Protein Phosphatases (PP2C) Gene Family in Gossypium hirsutum L.

2019 ◽  
Vol 20 (6) ◽  
pp. 1395 ◽  
Author(s):  
Hamna Shazadee ◽  
Nadeem Khan ◽  
Jingjing Wang ◽  
Chencan Wang ◽  
Jianguo Zeng ◽  
...  
Keyword(s):  
Gossypium Hirsutum ◽  
Gene Family ◽  
Expression Profiling ◽  
Critical Role ◽  
Fiber Development ◽  
Chromosomal Mapping ◽  
Composition Analysis ◽  
Specific Gene ◽  
Specific Response ◽  
Pp2c Gene

The protein phosphatase (PP2C) gene family, known to participate in cellular processes, is one of the momentous and conserved plant-specific gene families that regulate signal transduction in eukaryotic organisms. Recently, PP2Cs were identified in Arabidopsis and various other crop species, but analysis of PP2C in cotton is yet to be reported. In the current research, we found 87 (Gossypium arboreum), 147 (Gossypium barbadense), 181 (Gossypium hirsutum), and 99 (Gossypium raimondii) PP2C-encoding genes in total from the cotton genome. Herein, we provide a comprehensive analysis of the PP2C gene family in cotton, such as gene structure organization, gene duplications, expression profiling, chromosomal mapping, protein motif organization, and phylogenetic relationships of each species. Phylogenetic analysis further categorized PP2C genes into 12 subgroups based on conserved domain composition analysis. Moreover, we observed a strong signature of purifying selection among duplicated pairs (i.e., segmental and dispersed) of Gossypium hirsutum. We also observed the tissue-specific response of GhPP2C genes in organ and fiber development by comparing the RNA-sequence (RNA-seq) data reported on different organs. The qRT-PCR validation of 30 GhPP2C genes suggested their critical role in cotton by exposure to heat, cold, drought, and salt stress treatments. Hence, our findings provide an overview of the PP2C gene family in cotton based on various bioinformatic tools that demonstrated their critical role in organ and fiber development, and abiotic stress tolerance, thereby contributing to the genetic improvement of cotton for the resistant cultivar.

scholarly journals Genome-Wide Gene Expression Profiling Revealed a Critical Role for GATA3 in the Maintenance of the Th2 Cell Identity

PLoS ONE ◽  
2013 ◽  
Vol 8 (6) ◽  
pp. e66468 ◽  
Author(s):  
Tetsuya Sasaki ◽  
Atsushi Onodera ◽  
Hiroyuki Hosokawa ◽  
Yukiko Watanabe ◽  
Shu Horiuchi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Critical Role ◽  
Cell Identity ◽  
Th2 Cell ◽  
Genome Wide ◽  
Genome Wide Gene Expression

Chromatin-Modifying Enzymes in T Cell Development

2020 ◽  
Vol 38 (1) ◽  
pp. 397-419
Author(s):  
Michael J. Shapiro ◽  
Virginia Smith Shapiro
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
Biological Effects ◽  
Critical Role ◽  
T Cell Development ◽  
Regulation Of Gene Expression ◽  
Chromatin Accessibility ◽  
Cell Development ◽  
Specific Gene ◽  
Dynamic Regulation

T cell development involves stepwise progression through defined stages that give rise to multiple T cell subtypes, and this is accompanied by the establishment of stage-specific gene expression. Changes in chromatin accessibility and chromatin modifications accompany changes in gene expression during T cell development. Chromatin-modifying enzymes that add or reverse covalent modifications to DNA and histones have a critical role in the dynamic regulation of gene expression throughout T cell development. As each chromatin-modifying enzyme has multiple family members that are typically all coexpressed during T cell development, their function is sometimes revealed only when two related enzymes are concurrently deleted. This work has also revealed that the biological effects of these enzymes often involve regulation of a limited set of targets. The growing diversity in the types and sites of modification, as well as the potential for a single enzyme to catalyze multiple modifications, is also highlighted.

Prediction of Response to Treatment with Lenalidomide in Patients with Non-Del 5q Myelodysplastic Syndrome by Gene Expression Profiling Remains Difficult.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 2781-2781
Author(s):  
Wolf-Karsten Hofmann ◽  
Florian Nolte ◽  
Ouidad Benlasfer ◽  
Eckhard Thiel ◽  
Gerhard Ehninger ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bone Marrow ◽  
Myelodysplastic Syndrome ◽  
Clinical Response ◽  
Expression Profiling ◽  
Research Funding ◽  
Bone Marrow Cells ◽  
Response To Treatment ◽  
Specific Gene ◽  
Prediction Of Response

Abstract Abstract 2781 Poster Board II-757 Lenalidomide belongs to a proprietary class of immunmodulatory drugs showing therapeutic activity in patients with myelodysplastic syndrome (MDS), in particular in those having the 5q-abnormality, but also in patients not showing this cytogenetical aberration. In 2008, Ebert et al. (PLos Med. 2, e35) could demonstrate that there is a specific gene expression profile in bone marrow cells collected from MDS-patients either with 5q- syndrome as well as MDS-patients having no 5q-abnormality which is strongly correlated with the clinical response to treatment with lenalidomide. Whereas this finding is not of clinical importance in patients with MDS del 5q (overall response 75 %) it may play a pivotal role for prediction of clinical response to lenalidomide in non-del 5q MDS-patients. Therefore, we have studied gene expression profile (HG-U133plus2.0, Affymetrix, Santa Clara, CA) of routinely isolated low-density mononuclear bone marrow cells from 8 patients with IPSS low/int-1 risk MDS having no deletion on chromosome 5 but were subsequently treated with lenalidomide 5 mg/day. All of the patients were transfusion dependent for red blood cells. The median duration of treatment with lenalidomide was 22 weeks. RNA was extracted by Trizol and quality controlled by using a Bioanalyzer 2100 system (Agilent, Waldborn, Germany) to exclude RNA degradation. Microarray hybridization was performed according to the standard Affymetrix protocol. Data were analyzed by Microarray Analysis Suites 5.0 (MAS 5.0; Affymetrix) and GeneSpring (Agilent Technologies, Santa Clara, CA). For clustering analysis we utilized the gene list of 68 discriminating genes as published by Ebert et al. the molecular analysis did clearly separate two groups of patients having specific gene expression profiles according to the responder/non-responder group as published previously. Furthermore, single sample prediction could discriminate three out of 8 patients to be possible responders to lenalidomide but this was not correlated to the clinical course of those patients while on treatment with lenalidomide. However, none of the MDS-patients receiving lenalidomide did show significant clinical response as defined by reduction of transfusion requirement by 50 % or transfusion independence. In conclusion, prediction of response to lenalidomide in non-del 5q patients by gene expression profiling so far remains critical. Prospective analysis of molecular changes including DNA analysis in larger clinical trials using lenalidomide in non-del 5q MDS-patients are required to establish reliable predictive markers in MDS. Disclosures: Hofmann: Celgene: Research Funding. Platzbecker:Celgene: Research Funding.

scholarly journals Gene expression profiling of the Notch-AhR-IL22 axis at homeostasis and in response to tissue injury

2017 ◽  
Vol 37 (6) ◽  
Author(s):  
Marc Weidenbusch ◽  
Severin Rodler ◽  
Shangqing Song ◽  
Simone Romoli ◽  
Julian A. Marschner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Tissue Injury ◽  
Expression Profiles ◽  
Notch Pathway ◽  
Gene Expression Profiles ◽  
Sterile Inflammation ◽  
Specific Gene ◽  
Specific Gene Expression

Notch and interleukin-22 (IL-22) signaling are known to regulate tissue homeostasis and respond to injury in humans and mice, and the induction of endogenous aryl hydrocarbon receptor (Ahr) ligands through Notch links the two pathways in a hierarchical fashion. However in adults, the species-, organ- and injury-specific gene expression of the Notch-AhR-IL22 axis components is unknown. We therefore performed gene expression profiling of DLL1, DLL3, DLL4, DLK1, DLK2, JAG1, JAG2, Notch1, Notch2, Notch3, Notch4, ADAM17/TNF-α ADAM metalloprotease converting enzyme (TACE), PSEN1, basigin (BSG)/CD147, RBP-J, HES1, HES5, HEY1, HEYL, AHR, ARNT, ARNT2, CYP1A1, CYP24A1, IL-22, IL22RA1, IL22RA2, IL10RB, and STAT3 under homeostatic conditions in ten mature murine and human organs. Additionally, the expression of these genes was assessed in murine models of acute sterile inflammation and progressive fibrosis. We show that there are organ-specific gene expression profiles of the Notch-AhR-IL22 axis in humans and mice. Although there is an overall interspecies congruency, specific differences between human and murine expression signatures do exist. In murine tissues with AHR/ARNT expression CYP1A1 and IL-22 were correlated with HES5 and HEYL expression, while in human tissues no such correlation was found. Notch and AhR signaling are involved in renal inflammation and fibrosis with specific gene expression changes in each model. Despite the presence of all Notch pathway molecules in the kidney and a model-specific induction of Notch ligands, IL-22 was only up-regulated in acute inflammation, but rapidly down-regulated during regeneration. This implies that for targeting injury responses, e.g. via IL-22, species-specific differences, injury type and time points have to be considered.

scholarly journals Mouse strain specific gene expression differences for illumina microarray expression profiling in embryos

2012 ◽  
Vol 5 (1) ◽  
pp. 232 ◽  
Author(s):  
Petra Kraus ◽  
Xing Xing ◽  
Siew Lim ◽  
Max E Fun ◽  
V Sivakamasundari ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mouse Strain ◽  
Expression Profiling ◽  
Specific Gene ◽  
Specific Gene Expression ◽  
Microarray Expression Profiling ◽  
Microarray Expression

Identification of Tumor-Specific Molecular Signatures in Intracranial Ependymoma and Association With Clinical Characteristics

2006 ◽  
Vol 24 (33) ◽  
pp. 5223-5233 ◽  
Author(s):  
Piergiorgio Modena ◽  
Elena Lualdi ◽  
Federica Facchinetti ◽  
Joris Veltman ◽  
James F. Reid ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiling ◽  
Hedgehog Signaling ◽  
Clinical Characteristics ◽  
Disease Onset ◽  
Gene Expression Signature ◽  
Comparative Genomic ◽  
Specific Gene ◽  
Molecular Signatures ◽  
Intracranial Ependymoma

Purpose To delineate clinically relevant molecular signatures of intracranial ependymoma. Materials and Methods We analyzed 24 primary intracranial ependymomas. For genomic profiling, microarray-based comparative genomic hybridization (CGH) was used and results were validated by fluorescent in situ hybridization and loss of heterozygosity mapping. We performed gene expression profiling using microarrays, real-time quantitative reverse transcriptase polymerase chain reaction, and methylation analysis of selected genes. We applied class comparison analyses to compare both genomic and expression profiling data with clinical characteristics. Results A variable number of genomic imbalances were detected by array CGH, revealing multiple regions of recurrent gain (including 2q23, 7p21, 12p, 13q21.1, and 20p12) and loss (including 5q31, 6q26, 7q36, 15q21.1, 16q24, 17p13.3, 19p13.2, and 22q13.3). An ependymoma-specific gene expression signature was characterized by the concurrent abnormal expression of developmental and differentiation pathways, including NOTCH and sonic hedgehog signaling. We identified specific differentially imbalanced genomic clones and gene expression signatures significantly associated with tumor location, patient age at disease onset, and retrospective risk for relapse. Integrated genomic and expression profiling allowed us to identify genes of which the expression is deregulated in intracranial ependymoma, such as overexpression of the putative proto-oncogene YAP1 (located at 11q22) and downregulation of the SULT4A1 gene (at 22q13.3). Conclusion The present exploratory molecular profiling study allowed us to refine previously reported intervals of genomic imbalance, to identify novel restricted regions of gain and loss, and to identify molecular signatures correlating with various clinical variables. Validation of these results on independent data sets represents the next step before translation into the clinical setting.

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