The dehydrins gene expression differs across ecotypes in Norway spruce and relates to weather fluctuations

AbstractNorway spruce has a broad natural distribution range, which results in a substantial variety of its physiological and genetic variation. There are three distinct altitudinal ecotypes described in this tree species. The physiological optimum of each ecotype may be shifted due to ongoing climate change, especially in traits associated with water demand that might be crucial for adaptation. Dehydrins are proteins that help to mitigate the adverse effects of dehydration. Dehydrin gene expression patterns appeared to be a suitable marker for plant stress assessment. Genetically determined differences in response between individuals and populations were formerly studied, however, mainly in controlled conditions. We evaluated ecotypic variation in dehydrin gene expression in a clonal bank comprised of all three ecotypes. A genetic relationship among targeted trees was uncovered utilizing GBS (Genotyping by Sequencing) platform. We sampled 4–6 trees of each ecotype throughout 15 months period. Subsequently, we assessed the RNA expression of dehydrin genes by qRT-PCR. For this study, we deliberately selected dehydrins from different categories. Our findings detected significant differences among ecotypes in dehydrin expression. The association of recorded climatic variables and individual gene expression across the study period was evaluated and revealed, for certain genes, a correlation between dehydrin gene expression and precipitation, temperature, and day-length.

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Biological Image Analysis via Matrix Approximation

Encyclopedia of Data Warehousing and Mining, Second Edition ◽

10.4018/978-1-60566-010-3.ch027 ◽

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.

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CancerLivER: a database of liver cancer gene expression resources and biomarkers

Database ◽

10.1093/database/baaa012 ◽

2020 ◽

Vol 2020 ◽

Author(s):

Harpreet Kaur ◽

Sherry Bhalla ◽

Dilraj Kaur ◽

Gajendra PS Raghava

Keyword(s):

Gene Expression ◽

Liver Cancer ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Full Potential ◽

Individual Gene ◽

Comprehensive Information ◽

Tremendous Amount ◽

Disease Specific

Abstract Liver cancer is the fourth major lethal malignancy worldwide. To understand the development and progression of liver cancer, biomedical research generated a tremendous amount of transcriptomics and disease-specific biomarker data. However, dispersed information poses pragmatic hurdles to delineate the significant markers for the disease. Hence, a dedicated resource for liver cancer is required that integrates scattered multiple formatted datasets and information regarding disease-specific biomarkers. Liver Cancer Expression Resource (CancerLivER) is a database that maintains gene expression datasets of liver cancer along with the putative biomarkers defined for the same in the literature. It manages 115 datasets that include gene-expression profiles of 9611 samples. Each of incorporated datasets was manually curated to remove any artefact; subsequently, a standard and uniform pipeline according to the specific technique is employed for their processing. Additionally, it contains comprehensive information on 594 liver cancer biomarkers which include mainly 315 gene biomarkers or signatures and 178 protein- and 46 miRNA-based biomarkers. To explore the full potential of data on liver cancer, a web-based interactive platform was developed to perform search, browsing and analyses. Analysis tools were also integrated to explore and visualize the expression patterns of desired genes among different types of samples based on individual gene, GO ontology and pathways. Furthermore, a dataset matrix download facility was provided to facilitate the users for their extensive analysis to elucidate more robust disease-specific signatures. Eventually, CancerLivER is a comprehensive resource which is highly useful for the scientific community working in the field of liver cancer.Availability: CancerLivER can be accessed on the web at https://webs.iiitd.edu.in/raghava/cancerliver.

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RNA-seq: primary cells, cell lines and heat stress

10.1101/013979 ◽

2015 ◽

Author(s):

Carl J Schmdt ◽

Elizabeth M Pritchett ◽

Liang Sun ◽

Richard V.N. Davis ◽

Allen Hubbard ◽

...

Keyword(s):

Gene Expression ◽

Heat Stress ◽

Sequence Data ◽

Expression Patterns ◽

Effective Means ◽

Cost Effective ◽

Rna Seq ◽

Individual Gene ◽

Examine Gene Expression ◽

A Cell

Transcriptome analysis by RNA-seq has emerged as a high-throughput, cost-effective means to evaluate the expression pattern of genes in organisms. Unlike other methods, such as microarrays or quantitative PCR, RNA-seq is a target free method that permits analysis of essentially any RNA that can be amplified from a cell or tissue. At its most basic, RNA-seq can determine individual gene expression levels by counting the number of times a particular transcript was found in the sequence data. Transcript levels can be compared across multiple samples to identify differentially expressed genes and infer differences in biological states between the samples. We have used this approach to examine gene expression patterns in chicken and human cells, with particular interest in determining response to heat stress.

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Learning Processes in Hierarchical Pairs Regulate Entire Gene Expression in Cells

10.21203/rs.3.rs-1136384/v1 ◽

2021 ◽

Author(s):

Tomoyuki Yamaguchi

Keyword(s):

Gene Expression ◽

Learning Process ◽

Expression Patterns ◽

Two Factors ◽

Regulatory Cascades ◽

Target Ratio ◽

A Cell ◽

The Difference ◽

Genetically Determined ◽

Entire Gene

Abstract Expression of numerous genes is precisely controlled in a cell in various contexts. While genetic and epigenetic mechanisms contribute to this regulation, how each mechanism cooperates to ensure the proper expression patterns of whole gene remains unclear. Here, I theoretically show that the repetition of simple biological processes makes appropriate whole-gene expression only if the appropriateness of current pattern is roughly detectable. A learning pair model is developed, in which two factors autonomously approach the target ratio by repeating two stochastic processes; competitive amplification with a small addition term and decay depending on the difference between the current and target ratios. Furthermore, thousands of factors are self-regulated in a hierarchical-pair architecture, in which the activation degrees competitively amplify, while transducing the activation signal, and decay at four different probabilities. Changes in whole-gene expression during human early embryogenesis and hematopoiesis are reproduced in simulation using this epigenetic learning process in a single genetically-determined hierarchical-pair architecture of gene regulatory cascades. On the background of this learning process, I propose the law of biological inertia which means that a living cell basically maintains the expression pattern while renewing the contents.

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Transcriptomic Time Series Analysis in Wound Healing: Challenges and Perspectives on Data Interpretation

10.21203/rs.3.rs-929173/v1 ◽

2021 ◽

Author(s):

Ksenia Zlobina ◽

Eric Malekos ◽

Han Chen ◽

Marcella Gomez

Keyword(s):

Gene Expression ◽

Time Series ◽

Wound Healing ◽

Expression Patterns ◽

Data Interpretation ◽

Differentially Expressed ◽

Expression Data ◽

Sample Collection ◽

Individual Gene ◽

Experimental Approaches

Abstract Background: Wound transcriptomic analysis can be used to quantify wound healing stages and identify leverage points for wound healing intervention. However, individual gene signatures corresponding to wound healing stages vary from one experiment to another and are highly dependent on both experimental setup and bioinformatics methods. Methods: We develop a systematic approach to informatively compare time series from publicly available wound transcriptomic datasets, including mouse and human wounds, and identify consistent gene expression patterns. Results: We reveal the limitations of gene expression data collection, interpretation, and comparison. For example, the sample rate of wound transcriptomic sample collection must be higher than the rate of changes in the wound healing processes, otherwise, important changes in gene expression may be missed. This may lead to mis finding the most significant genes, as peaks of expression for highly differentially expressed genes are lost. Nevertheless, we derived a short list of genes highly differentially expressed in all datasets under consideration. After clustering and normalization, these genes clearly demonstrate similarly changing dynamics of expression between the wounds and may be used for wound healing stage detection.Conclusions: A list of genes that may be used for transcriptomics-based wound healing stage detection is provided. In addition, we suggest experimental approaches that could help researchers to extract more meaningful results.

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Meta-Analysis of RNA-Seq Studies Reveals Genes With Dominant Functions During Flower Bud Endo- To Eco-Dormancy Transition in Prunus Species

10.21203/rs.3.rs-141833/v1 ◽

2021 ◽

Author(s):

Monica Canton ◽

Cristian Forestan ◽

Claudio Bonghi ◽

Serena Varotto

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Meta Analysis ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Fruit Trees ◽

Day Length ◽

Specific Gene ◽

Flower Buds ◽

Flower Bud

Abstract In deciduous fruit trees, entrance into dormancy occurs in later summer/fall, concomitantly with the shortening of day length and decrease in temperature. Dormancy can be divided into endodormancy, ecodormancy and paradormancy. In Prunus species flower buds, entrance into the dormant stage occurs when the apical meristem is partially differentiated; during dormancy, flower verticils continue their growth and differentiation. Each species and/or cultivar requires exposure to low winter temperature followed by warm temperatures, quantified as chilling and heat requirements, to remove the physiological blocks that inhibit budburst. A comprehensive meta-analysis of transcriptomic studies on flower buds of sweet cherry, apricot and peach was conducted, by investigating the gene expression profiles during bud endo- to ecodormancy transition in genotypes differing in chilling requirements. Conserved and distinctive expression patterns were observed, allowing the identification of gene specifically associated with endodormancy or ecodormancy. In addition to the MADS-box transcription factor family, hormone-related genes, chromatin modifiers, macro- and micro-gametogenesis related genes and environmental integrators, were identified as novel biomarker candidates for flower bud development during winter in stone fruits. In parallel, flower bud differentiation processes were associated to dormancy progression and termination and to environmental factors triggering dormancy phase-specific gene expression.

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Sinorhizobium meliloti Differentiation During Symbiosis with Alfalfa: A Transcriptomic Dissection

Molecular Plant-Microbe Interactions ◽

10.1094/mpmi-19-0363 ◽

2006 ◽

Vol 19 (4) ◽

pp. 363-372 ◽

Cited By ~ 85

Author(s):

Delphine Capela ◽

Cédric Filipe ◽

Christine Bobik ◽

Jacques Batut ◽

Claude Bruand

Keyword(s):

Gene Expression ◽

Sinorhizobium Meliloti ◽

Expression Patterns ◽

Global Gene Expression ◽

Global Changes ◽

Individual Gene ◽

Transcription Profiles ◽

Bacterial Mutant ◽

Infection Threads ◽

Cultured Bacteria

Sinorhizobium meliloti is a soil bacterium able to induce the formation of nodules on the root of specific legumes, including alfalfa (Medicago sativa). Bacteria colonize nodules through infection threads, invade the plant intracellularly, and ultimately differentiate into bacteroids capable of reducing atmospheric nitrogen to ammonia, which is directly assimilated by the plant. As a first step to describe global changes in gene expression of S. meliloti during the symbiotic process, we used whole genome microarrays to establish the transcriptome profile of bacteria from nodules induced by a bacterial mutant blocked at the infection stage and from wild-type nodules harvested at various timepoints after inoculation. Comparison of these profiles to those of cultured bacteria grown either to log or stationary phase as well as examination of a number of genes with known symbiotic transcription patterns allowed us to correlate global gene-expression patterns to three known steps of symbiotic bacteria bacteroid differentiation, i.e., invading bacteria inside infection threads, young differentiating bacteroids, and fully differentiated, nitrogen-fixing bacteroids. Finally, analysis of individual gene transcription profiles revealed a number of new potential symbiotic genes.

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LBH589, a Novel Deacetylase Inhibitor (DACi), Treatment of Patients with Cutaneous T-Cell Lymphoma (CTCL). Skin Gene Expression Profiles in the First 24 Hours Related to Clinical Response Following Therapy.

Blood ◽

10.1182/blood.v108.11.2715.2715 ◽

2006 ◽

Vol 108 (11) ◽

pp. 2715-2715 ◽

Cited By ~ 7

Author(s):

Miles Prince ◽

D.J. George ◽

R. Johnstone ◽

C. McCormack ◽

L. Ellis ◽

...

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Gene Expression Patterns ◽

Functional Categories ◽

Patient Response ◽

Individual Gene ◽

Tumor Gene Expression ◽

Tumor Gene

Abstract Background: LBH589 is a novel DACi in Phase I trials. Pre-clinical studies have demonstrated that DACi alter gene expression and other DACi have induced disease regression in CTCL. Indeed, CTCL is an ideal disease to assess variation in tumor gene expression over time following drug administration. In this study we evaluated the safety and activity of LBH589 in CTCL and examined changes in tumor gene expression in the first 24 hours following oral LBH589. Methods: Pts with advanced-stage CTCL, who had progressed following prior systemic therapy were entered into the oral DLT dose level 30 mg M,W,F cohort (n=1), the subsequent MTD dose level 20 mg M,W, F weekly (n=9). LBH589 was continued until disease progression or unacceptable toxicity. Intensive cardiac monitoring was performed. Six pts had 3 mm punch biopsies from CTCL-involved skin lesions at 0, 4, 8 and 24 h after administration, which were subjected to gene expression profiling using Affymetrix U133 plus 2.0 GeneChips with 47,000 probesets. Alteration in gene expression patterns was confirmed by QRT-PCR of selected genes. Individual gene expression analysis is underway, utilizing set enrichment analysis to elucidate the functional categories which correlate with degree of patient response. Results: 10 pts are currently evaluable for response. 2 of the pts attained a complete response (CR), 4 attained a partial response (PR), 1 achieved stable disease (SD) with ongoing improvement, and 2 progressed on treatment (PD). (RR = 6/10; 60%). Microarray data on 5 pts demonstrated distinct gene expression response profiles between pts. Individual gene expression within patient tumors varied over the timepoints in the first 24 hours following treatment. To demonstrate effects of LBH589 as an epigenetic modulator, global changes in gene expression patterns in responding versus progressing patients have been delineated. In addition, functional categories of genes which correlate with degree of patient response have been identified. Conclusions: LBH589 induces CR’s in CTCL pts. Preliminary microarray analysis of tumor samples have identified distinct gene expression profiles.

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Genome-Wide Identification of microRNAs in Response to Salt/Alkali Stress in Medicago truncatula through High-Throughput Sequencing

International Journal of Molecular Sciences ◽

10.3390/ijms19124076 ◽

2018 ◽

Vol 19 (12) ◽

pp. 4076 ◽

Cited By ~ 5

Author(s):

Chunyu Cao ◽

Ruicai Long ◽

Tiejun Zhang ◽

Junmei Kang ◽

Zhen Wang ◽

...

Keyword(s):

Medicago Truncatula ◽

Molecular Mechanisms ◽

High Throughput Sequencing ◽

Expression Patterns ◽

Plant Stress ◽

Alkaline Stress ◽

Alkaline Soils ◽

Illumina Hiseq ◽

Sequencing Platform

Saline-alkaline stress is a universal abiotic stress that adversely affects plant growth and productivity. Saline-alkaline conditions results in plant abnormal transcriptome expression finally manifesting as defective phenotypes. Considerable research has revealed the active role of microRNA in various stress conditions. This study was aimed to identify novel miRNAs and the miRNA expression patterns in the leguminous model plant R108 (Medicago truncatula). The miRNA contained in the total RNA extracted from Medicago truncatula seedlings (72 h) that had been treated with solutions mimicking saline and alkaline soils was subjected to miRNA deep sequencing. The Illumina HiSeq sequencing platform was used to analyze nine small RNA libraries of three treatment groups: distilled water, 20 mM NaCl + Na2SO4 and 5 mM Na2CO3 + NaHCO3. Sequencing revealed that 876 miRNAs including 664 known miRNAs and 212 potential novel miRNAs were present in all the libraries. The miR159 family, miR156 family, miR2086-3p, miR396, miR166, miR319, miR167, miR5213-5p, miR1510 and miR2643 were among the most expressed miRNAs in all libraries. The results of miRNAs expression under treatments were validated by reverse-transcription quantitative PCR (RT-qPCR). Target gene prediction through computational analysis and pathway annotation analysis revealed that the primary pathways affected by stress were related to plant development, including metabolic processes, single-organism processes and response to the stimulus. Our results provide valuable information towards elucidating the molecular mechanisms of salt/alkali tolerance in Medicago truncatula and provide insight into the putative role of miRNAs in plant stress resistance.

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Meta-analysis of RNA-Seq studies reveals genes with dominant functions during flower bud endo- to eco-dormancy transition in Prunus species

Scientific Reports ◽

10.1038/s41598-021-92600-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Monica Canton ◽

Cristian Forestan ◽

Claudio Bonghi ◽

Serena Varotto

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Meta Analysis ◽

Expression Patterns ◽

Gene Expression Profiles ◽

Fruit Trees ◽

Day Length ◽

Specific Gene ◽

Flower Buds ◽

Flower Bud

AbstractIn deciduous fruit trees, entrance into dormancy occurs in later summer/fall, concomitantly with the shortening of day length and decrease in temperature. Dormancy can be divided into endodormancy, ecodormancy and paradormancy. In Prunus species flower buds, entrance into the dormant stage occurs when the apical meristem is partially differentiated; during dormancy, flower verticils continue their growth and differentiation. Each species and/or cultivar requires exposure to low winter temperature followed by warm temperatures, quantified as chilling and heat requirements, to remove the physiological blocks that inhibit budburst. A comprehensive meta-analysis of transcriptomic studies on flower buds of sweet cherry, apricot and peach was conducted, by investigating the gene expression profiles during bud endo- to ecodormancy transition in genotypes differing in chilling requirements. Conserved and distinctive expression patterns were observed, allowing the identification of gene specifically associated with endodormancy or ecodormancy. In addition to the MADS-box transcription factor family, hormone-related genes, chromatin modifiers, macro- and micro-gametogenesis related genes and environmental integrators, were identified as novel biomarker candidates for flower bud development during winter in stone fruits. In parallel, flower bud differentiation processes were associated to dormancy progression and termination and to environmental factors triggering dormancy phase-specific gene expression.

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