scholarly journals eQTL regulating Transcript Levels Associated with Diverse Biological Processes in Tomato

2016 ◽  
Author(s):  
Aashish Ranjan ◽  
Jessica M. Budke ◽  
Steven D. Rowland ◽  
Daniel H. Chitwood ◽  
Ravi Kumar ◽  
...  
Keyword(s):  
Gene Expression ◽  
Leaf Development ◽  
Expression Patterns ◽  
Transcript Level ◽  
Phenotypic Traits ◽  
Biological Processes ◽  
Hypocotyl Length ◽  
Solanum Pennellii ◽  
Abundance Pattern ◽  
Transcript Levels

AbstractVariation in gene expression, in addition to sequence polymorphisms, is known to influence developmental, physiological and metabolic traits in plants. Genetic mapping populations have facilitated identification of expression Quantitative Trait Loci (eQTL), the genetic determinants of variation in gene expression patterns. We used an introgression population developed from the wild desert-adapted Solanum pennellii and domesticated tomato Solanum lycopersicum to identify the genetic basis of transcript level variation. We established the effect of each introgression on the transcriptome, and identified ~7,200 eQTL regulating the steady state transcript levels of 5,300 genes. Barnes-Hut t-distributed stochastic neighbor embedding clustering identified 42 modules revealing novel associations between transcript level patterns and biological processes. The results showed a complex genetic architecture of global transcript abundance pattern in tomato. Several genetic hotspots regulating a large number of transcript level patterns relating to diverse biological processes such as plant defense and photosynthesis were identified. Important eQTL regulating transcript level patterns were related to leaf number and complexity, and hypocotyl length. Genes associated with leaf development showed an inverse correlation with photosynthetic gene expression but eQTL regulating genes associated with leaf development and photosynthesis were dispersed across the genome. This comprehensive expression QTL analysis details the influence of these loci on plant phenotypes, and will be a valuable community resource for investigations on the genetic effects of eQTL on phenotypic traits in tomato.

scholarly journals Cocaine induces paradigm-specific changes to the transcriptome within the ventral tegmental area

2021 ◽  
Author(s):  
Rianne R. Campbell ◽  
Siwei Chen ◽  
Joy H. Beardwood ◽  
Alberto J. López ◽  
Lilyana V. Pham ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ventral Tegmental Area ◽  
Home Cage ◽  
Expression Patterns ◽  
Energy Regulation ◽  
Biological Processes ◽  
Cocaine Exposure ◽  
Self Administration ◽  
Drug Reinforcement ◽  
Ventral Tegmental

AbstractDuring the initial stages of drug use, cocaine-induced neuroadaptations within the ventral tegmental area (VTA) are critical for drug-associated cue learning and drug reinforcement processes. These neuroadaptations occur, in part, from alterations to the transcriptome. Although cocaine-induced transcriptional mechanisms within the VTA have been examined, various regimens and paradigms have been employed to examine candidate target genes. In order to identify key genes and biological processes regulating cocaine-induced processes, we employed genome-wide RNA-sequencing to analyze transcriptional profiles within the VTA from male mice that underwent one of four commonly used paradigms: acute home cage injections of cocaine, chronic home cage injections of cocaine, cocaine-conditioning, or intravenous-self administration of cocaine. We found that cocaine alters distinct sets of VTA genes within each exposure paradigm. Using behavioral measures from cocaine self-administering mice, we also found several genes whose expression patterns corelate with cocaine intake. In addition to overall gene expression levels, we identified several predicted upstream regulators of cocaine-induced transcription shared across all paradigms. Although distinct gene sets were altered across cocaine exposure paradigms, we found, from Gene Ontology (GO) term analysis, that biological processes important for energy regulation and synaptic plasticity were affected across all cocaine paradigms. Coexpression analysis also identified gene networks that are altered by cocaine. These data indicate that cocaine alters networks enriched with glial cell markers of the VTA that are involved in gene regulation and synaptic processes. Our analyses demonstrate that transcriptional changes within the VTA depend on the route, dose and context of cocaine exposure, and highlight several biological processes affected by cocaine. Overall, these findings provide a unique resource of gene expression data for future studies examining novel cocaine gene targets that regulate drug-associated behaviors.

scholarly journals Gene expression amplification by nuclear speckle association

2019 ◽  
pp. jcb.201904046 ◽  
Author(s):  
Jiah Kim ◽  
Neha Chivukula Venkata ◽  
Gabriela Andrea Hernandez Gonzalez ◽  
Nimish Khanna ◽  
Andrew S. Belmont
Keyword(s):  
Gene Expression ◽  
Rna Polymerase Ii ◽  
Liquid Droplet ◽  
Transcript Level ◽  
Rna Degradation ◽  
Nuclear Speckles ◽  
Nascent Transcript ◽  
Nuclear Compartment ◽  
Transcript Levels ◽  
Endogenous Genes

Many active genes reproducibly position near nuclear speckles, but the functional significance of this positioning is unknown. Here we show that HSPA1B BAC transgenes and endogenous Hsp70 genes turn on 2–4 min after heat shock (HS), irrespective of their distance to speckles. However, both total HSPA1B mRNA counts and nascent transcript levels measured adjacent to the transgene are approximately twofold higher for speckle-associated alleles 15 min after HS. Nascent transcript level fold-increases for speckle-associated alleles are 12–56-fold and 3–7-fold higher 1–2 h after HS for HSPA1B transgenes and endogenous genes, respectively. Severalfold higher nascent transcript levels for several Hsp70 flanking genes also correlate with speckle association at 37°C. Live-cell imaging reveals that HSPA1B nascent transcript levels increase/decrease with speckle association/disassociation. Initial investigation reveals that increased nascent transcript levels accompanying speckle association correlate with reduced exosome RNA degradation and larger Ser2p CTD-modified RNA polymerase II foci. Our results demonstrate stochastic gene expression dependent on positioning relative to a liquid-droplet nuclear compartment through “gene expression amplification.”

scholarly journals RNA Expression Analysis Using an AntisenseBacillus subtilis Genome Array

2001 ◽  
Vol 183 (24) ◽  
pp. 7371-7380 ◽  
Author(s):  
Jian-Ming Lee ◽  
Shehui Zhang ◽  
Soumitra Saha ◽  
Sonia Santa Anna ◽  
Can Jiang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dynamic Range ◽  
Expression Patterns ◽  
Transcript Level ◽  
Open Reading Frames ◽  
Biosynthetic Genes ◽  
Coding Regions ◽  
Intergenic Regions ◽  
Differential Gene ◽  
Novel Transcripts

ABSTRACT We have developed an antisense oligonucleotide microarray for the study of gene expression and regulation in Bacillus subtilis by using Affymetrix technology. Quality control tests of the B. subtilis GeneChip were performed to ascertain the quality of the array. These tests included optimization of the labeling and hybridization conditions, determination of the linear dynamic range of gene expression levels, and assessment of differential gene expression patterns of known vitamin biosynthetic genes. In minimal medium, we detected transcripts for approximately 70% of the known open reading frames (ORFs). In addition, we were able to monitor the transcript level of known biosynthetic genes regulated by riboflavin, biotin, or thiamine. Moreover, novel transcripts were also detected within intergenic regions and on the opposite coding strand of known ORFs. Several of these novel transcripts were subsequently correlated to new coding regions.

scholarly journals Identifying core biological processes distinguishing human eye tissues with precise systems-level gene expression analyses and weighted correlation networks

2017 ◽  
Author(s):  
John M Bryan ◽  
Temesgen D Fufa ◽  
Kapil Bharti ◽  
Brian P Brooks ◽  
Robert B Hufnagel ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Mouse Retina ◽  
Human Tissues ◽  
Biological Processes ◽  
Rna Seq ◽  
Human Eye ◽  
Correlation Networks ◽  
Eye Tissues ◽  
Study Gene Expression

AbstractThe human eye is built from several specialized tissues which direct, capture, and pre-process information to provide vision. The gene expression of the different eye tissues has been extensively profiled with RNA-seq across numerous studies. Large consortium projects have also used RNA-seq to study gene expression patterning across many different human tissues, minus the eye. There has not been an integrated study of expression patterns from multiple eye tissues compared to other human body tissues. We have collated all publicly available healthy human eye RNA-seq datasets as well as dozens of other tissues. We use this fully integrated dataset to probe the biological processes and pan expression relationships between the cornea, retina, RPE-choroid complex, and the rest of the human tissues with differential expression, clustering, and GO term enrichment tools. We also leverage our large collection of retina and RPE-choroid tissues to build the first human weighted gene correlation networks and use them to highlight known biological pathways and eye gene disease enrichment. We also have integrated publicly available single cell RNA-seq data from mouse retina into our framework for validation and discovery. Finally, we make all these data, analyses, and visualizations available via a powerful interactive web application (https://eyeintegration.nei.nih.gov/).

scholarly journals Tissue-specific impacts of aging and genetics on gene expression patterns in humans

2021 ◽  
Author(s):  
Ryo Yamamoto ◽  
Ryan Chung ◽  
Juan Manuel Vazquez ◽  
Huanjie Sheng ◽  
Philippa Steinberg ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Purifying Selection ◽  
Transcript Level ◽  
Gene Expression Patterns ◽  
Opposite Pattern ◽  
Tissue Specific ◽  
Average Contribution ◽  
Primary Risk Factor ◽  
Expression Variance

Age is the primary risk factor for many common human diseases including heart disease, Alzheimer's dementias, cancers, and diabetes. Determining how and why tissues age differently is key to understanding the onset and progression of such pathologies. Here, we set out to quantify the relative contributions of genetics and aging to gene expression patterns from data collected across 27 tissues from 948 humans. We show that gene expression patterns become more erratic with age in several different tissues reducing the predictive power of expression quantitative trait loci. Jointly modelling the contributions of age and genetics to transcript level variation we find that the heritability (h2) of gene expression is largely consistent among tissues. In contrast, the average contribution of aging to gene expression variance varied by more than 20-fold among tissues with R2age > h2 in 5 tissues. We find that the coordinated decline of mitochondrial and translation factors is a widespread signature of aging across tissues. Finally, we show that while in general the force of purifying selection is stronger on genes expressed early in life compared to late in life as predicted by Medawar's hypothesis, a handful of highly proliferative tissues exhibit the opposite pattern. In contrast, gene expression variation that is under genetic control is strongly enriched for genes under relaxed constraint. Together we present a novel framework for predicting gene expression phenotypes from genetics and age and provide insights into the tissue-specific relative contributions of genes and the environment to phenotypes of aging.

Development of gene expression signatures characterizing the tumor-immune interaction.

2018 ◽  
Vol 36 (5_suppl) ◽  
pp. 205-205 ◽  
Author(s):  
Patrick Danaher ◽  
Sarah Warren ◽  
Alessandra Cesano
Keyword(s):  
Gene Expression ◽  
Candidate Genes ◽  
Tumor Cells ◽  
Expression Patterns ◽  
Sufficient Evidence ◽  
Training Procedure ◽  
Biological Processes ◽  
Immune Signaling ◽  
Gene Expression Signatures ◽  
Immune Oncology

205 Background: The efficacy of anti-tumor immunity depends on diverse factors, including not just abundance of immune cell populations but also activities of those populations and of tumor cells. Many of these processes are onerous to assay, but all are reflected in a tumor’s gene expression profile. Using a novel method, we develop gene expression signatures measuring a variety of biological processes underlying the tumor-immune interaction. These signatures fall into categories including antigen availability, structural barriers to immune infiltration, inhibitory signaling by both immune and tumor cells, inhibitory metabolism, pro-immune signaling, killing of tumor cells, tumor receptiveness to immune signaling, and tumor proliferation and death. Methods: We develop a method to train signatures of biological processed by synthesizing biological knowledge and large gene expression datasets. For a given process, we use literature searches and expert knowledge to derive lists of candidate genes. We then evaluate the co-expression of these candidate genes in data from The Cancer Genome Atlas (TCGA), discarding genes whose co-expression patterns are incompatible with their measuring their putative biological process. This approach safeguards the interpretability of our signatures: we only report signatures whose genes show evidence for measuring the desired biology. Finally, we further exploit co-expression patterns to obtain optimal weights for each signature gene. Results: We attempted to train signatures of over 30 biological processes involved in immune oncology. Of these, 17 candidate gene sets displayed sufficient evidence for measuring their putative biology. We show these signatures provide granular but intelligible descriptions of both immunotherapy datasets and single samples. We find they improve power in differential expression analyses and in training of predictors of drug response. Conclusions: The signatures we derive convert gene expression data into measurements of biological processes central to immune oncology, and they improve statistical power and interpretation of results in immunotherapy studies. Our training procedure ensures these signatures measure their intended biology.

The graft response to transplantation: a gene expression profile analysis

2003 ◽  
Vol 15 (1) ◽  
pp. 52-64 ◽  
Author(s):  
Kenneth Christopher ◽  
Thomas F. Mueller ◽  
Rachel DeFina ◽  
Yurong Liang ◽  
Jianhua Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Microarrays ◽  
Profile Analysis ◽  
Expression Patterns ◽  
Constitutive Expression ◽  
Biological Processes ◽  
Heart Transplants ◽  
Self Organizing Maps ◽  
Gene Ontology Database ◽  
Expression Profile Analysis

Little is known regarding the graft response to transplantation injury. This study investigates the posttransplantation response of genes that are constitutively expressed in the heart. Constitutive heart and lymph node tissue-restricted gene expression was first analyzed with DNA microarrays. To demonstrate changes following transplantation in genes constitutively expressed in the heart, we performed vascularized murine heart transplants in allogeneic (BALB/c to B6), syngeneic (B6 to B6), and alymphoid (BALB/c-RAG2−/− to B6-RAG1−/−) experimental groups. Temporal induction of genes posttransplant relative to constitutive expression was evaluated with DNA microarrays. Dendrograms and self-organizing maps were generated to determine the dissimilarity between the experimental groups and to identify subsets of differentially expressed genes within the groups, respectively. Expression patterns of selected genes were confirmed by real-time PCR. Biological processes were assigned to genes induced posttransplant using the AnnBuilder package via the Gene Ontology Database. Post-transplant, a shift was noted in genes classified as defense, communication, and metabolism. Our results identify novel components of the graft response to transplantation injury and rejection.

scholarly journals MODULARITY FACILITATES FLEXIBLE TUNING OF PLASTIC AND EVOLUTIONARY GENE EXPRESSION RESPONSES DURING EARLY DIVERGENCE

2017 ◽  
Author(s):  
Hannu Mäkinen ◽  
Tiina Sävilammi ◽  
Spiros Papakostas ◽  
Erica Leder ◽  
Leif Asbjørn Vøllestad ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Patterns ◽  
Thermal Adaptation ◽  
Thermal Conditions ◽  
Model System ◽  
Neutral Evolution ◽  
Phenotypic Traits ◽  
Early Stages ◽  
Large Gene ◽  
Population Effects

AbstractGene expression changes have been recognized as important drivers of adaptation to changing environmental conditions. Little is known about the relative roles of plastic and evolutionary responses in complex gene expression networks during the early stages of divergence. Large gene expression data sets coupled with in silico methods for identifying co-expressed modules now enable systems genetics approaches also in non-model species for better understanding of gene expression responses during early divergence. Here, we combined gene co-expression analyses with population genetics to separate plastic and population (evolutionary) effects in expression networks using small salmonid populations as a model system. We show that plastic and population effects were highly variable among the six identified modules and that the plastic effects explained larger proportion of the total eigengene expression than population effects. A more detailed analysis of the population effects using a QST - FST comparison across 16622 annotated transcripts revealed that gene expression followed neutral expectations within modules and at the global level. Furthermore, two modules showed enrichment for genes coding for early developmental traits that have been previously identified as important phenotypic traits in thermal responses in the same model system indicating that co-expression analysis can capture expression patterns underlying ecologically important traits. We suggest that module-specific responses may facilitate the flexible tuning of expression levels to local thermal conditions. Overall, our study indicates that plasticity and neutral evolution are the main drivers of gene expression variance in the early stages of thermal adaptation in this system.

scholarly journals Cis-regulatory divergence underpins the evolution of C3-C4 intermediate photosynthesis in Moricandia

2021 ◽  
Author(s):  
Meng-Ying Lin ◽  
Urte Schlueter ◽  
Benjamin Stich ◽  
Andreas P.M. Weber
Keyword(s):  
Gene Expression ◽  
C4 Photosynthesis ◽  
Expression Patterns ◽  
Transcript Level ◽  
F1 Hybrids ◽  
Gene Expression Patterns ◽  
Specific Gene ◽  
Promoter Regions ◽  
Specific Gene Expression ◽  
The Impact

Altered transcript abundances and cell specific gene expression patterns that are caused by regulatory divergence play an important role in the evolution of C4 photosynthesis. How these altered gene expression patterns are achieved and whether they are driven by cis- or trans-regulatory changes is mostly unknown. To address this question, we investigated the regulatory divergence between C3 and C3-C4 intermediates, using allele specific gene expression (ASE) analyses of Moricandia arvensis (C3-C4), M. moricandioides (C3) and their interspecific F1 hybrids. ASE analysis on SNP-level showed similar relative proportions of regulatory effects among hybrids: 36% and 6% of SNPs were controlled by cis-only and trans-only changes, respectively. GO terms associated with metabolic processes and the positioning of chloroplast in cells were abundant in transcripts with cis-SNPs shared by all studied hybrids. Transcripts with cis-specificity expressed bias toward the allele from the C3-C4 intermediate genotype. Additionally, ASE evaluated on transcript-level indicated that ~27% of transcripts show signals of ASE in Moricandia hybrids. Promoter-GUS assays on selected genes revealed altered spatial gene expression patterns, which likely result from regulatory divergence in their promoter regions. Assessing ASE in Moricandia interspecific hybrids contributes to the understanding of early evolutionary steps towards C4 photosynthesis and highlights the impact and importance of altered transcriptional regulations in this process.

scholarly journals scINSIGHT for interpreting single-cell gene expression from biologically heterogeneous data

2021 ◽  
Author(s):  
Kun Qian ◽  
Shiwei Fu ◽  
Hongwei Li ◽  
Wei Vivian Li
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Patterns ◽  
Real Data ◽  
Heterogeneous Data ◽  
Biological Processes ◽  
Cell Gene Expression ◽  
Improved Performance ◽  
Cell Gene ◽  
Clinical Problems

The increasing number of scRNA-seq data emphasizes the need for integrative analysis to interpret similarities and differences between single-cell samples. Even though different batch effect removal methods have been developed, none of the existing methods is suitable for heterogeneous single-cell samples coming from multiple biological conditions. To address this challenge, we propose a method named scINSIGHT to learn coordinated gene expression patterns that are common among or specific to different biological conditions, offering a unique chance to identify cellular identities and key biological processes across single-cell samples. We have evaluated scINSIGHT in comparison with state-of-the-art methods using simulated and real data, which consistently demonstrate its improved performance. In addition, our results show the applicability of scINSIGHT in diverse biomedical and clinical problems.

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