Genome-Wide Gene Expression in relation to Age in Large Laboratory Cohorts of Drosophila melanogaster

Aging is a complex process characterized by a steady decline in an organism’s ability to perform life-sustaining tasks. In the present study, two cages of approximately 12,000 mated Drosophila melanogaster females were used as a source of RNA from individuals sampled frequently as a function of age. A linear model for microarray data method was used for the microarray analysis to adjust for the box effect; it identified 1,581 candidate aging genes. Cluster analyses using a self-organizing map algorithm on the 1,581 significant genes identified gene expression patterns across different ages. Genes involved in immune system function and regulation, chorion assembly and function, and metabolism were all significantly differentially expressed as a function of age. The temporal pattern of data indicated that gene expression related to aging is affected relatively early in life span. In addition, the temporal variance in gene expression in immune function genes was compared to a random set of genes. There was an increase in the variance of gene expression within each cohort, which was not observed in the set of random genes. This observation is compatible with the hypothesis that D. melanogaster immune function genes lose control of gene expression as flies age.

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Faculty Opinions recommendation of Genome-wide excision repair in Arabidopsis is coupled to transcription and reflects circadian gene expression patterns.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.733074375.793569726 ◽

2020 ◽

Author(s):

Alex Webb

Keyword(s):

Gene Expression ◽

Excision Repair ◽

Expression Patterns ◽

Wide Excision ◽

Gene Expression Patterns ◽

Circadian Gene ◽

Genome Wide

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Compendium of Methods to Uncover RNA-Protein Interactions In Vivo

Methods and Protocols ◽

10.3390/mps4010022 ◽

2021 ◽

Vol 4 (1) ◽

pp. 22

Author(s):

Mrinmoyee Majumder ◽

Viswanathan Palanisamy

Keyword(s):

Gene Expression ◽

Protein Interactions ◽

Rna Binding ◽

Rna Binding Proteins ◽

Expression Patterns ◽

Control Of Gene Expression ◽

Regulatory Pathways ◽

Advantages And Disadvantages ◽

Protein Nucleic Acid

Control of gene expression is critical in shaping the pro-and eukaryotic organisms’ genotype and phenotype. The gene expression regulatory pathways solely rely on protein–protein and protein–nucleic acid interactions, which determine the fate of the nucleic acids. RNA–protein interactions play a significant role in co- and post-transcriptional regulation to control gene expression. RNA-binding proteins (RBPs) are a diverse group of macromolecules that bind to RNA and play an essential role in RNA biology by regulating pre-mRNA processing, maturation, nuclear transport, stability, and translation. Hence, the studies aimed at investigating RNA–protein interactions are essential to advance our knowledge in gene expression patterns associated with health and disease. Here we discuss the long-established and current technologies that are widely used to study RNA–protein interactions in vivo. We also present the advantages and disadvantages of each method discussed in the review.

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Roles of HIF and 2-Oxoglutarate-Dependent Dioxygenases in Controlling Gene Expression in Hypoxia

Cancers ◽

10.3390/cancers13020350 ◽

2021 ◽

Vol 13 (2) ◽

pp. 350

Author(s):

Julianty Frost ◽

Mark Frost ◽

Michael Batie ◽

Hao Jiang ◽

Sonia Rocha

Keyword(s):

Gene Expression ◽

Hypoxia Inducible Factor ◽

Transcriptional Regulator ◽

Hydroxylase Activity ◽

Control Of Gene Expression ◽

Prolyl Hydroxylases ◽

Chromatin Organisation ◽

Sense And Respond ◽

Almost All ◽

And Function

Hypoxia—reduction in oxygen availability—plays key roles in both physiological and pathological processes. Given the importance of oxygen for cell and organism viability, mechanisms to sense and respond to hypoxia are in place. A variety of enzymes utilise molecular oxygen, but of particular importance to oxygen sensing are the 2-oxoglutarate (2-OG) dependent dioxygenases (2-OGDs). Of these, Prolyl-hydroxylases have long been recognised to control the levels and function of Hypoxia Inducible Factor (HIF), a master transcriptional regulator in hypoxia, via their hydroxylase activity. However, recent studies are revealing that dioxygenases are involved in almost all aspects of gene regulation, including chromatin organisation, transcription and translation. We highlight the relevance of HIF and 2-OGDs in the control of gene expression in response to hypoxia and their relevance to human biology and health.

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Genome-wide identification and analysis of class III peroxidases in Betula pendula

BMC Genomics ◽

10.1186/s12864-021-07622-1 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Kewei Cai ◽

Huixin Liu ◽

Song Chen ◽

Yi Liu ◽

Xiyang Zhao ◽

...

Keyword(s):

Stress Responses ◽

Betula Pendula ◽

Expression Patterns ◽

Class Iii ◽

Physiological Processes ◽

Plant Life ◽

Genome Wide ◽

Plant Life Cycle ◽

Class Iii Peroxidases ◽

And Function

Abstract Background Class III peroxidases (POD) proteins are widely present in the plant kingdom that are involved in a broad range of physiological processes including stress responses and lignin polymerization throughout the plant life cycle. At present, POD genes have been studied in Arabidopsis, rice, poplar, maize and Chinese pear, but there are no reports on the identification and function of POD gene family in Betula pendula. Results We identified 90 nonredundant POD genes in Betula pendula. (designated BpPODs). According to phylogenetic relationships, these POD genes were classified into 12 groups. The BpPODs are distributed in different numbers on the 14 chromosomes, and some BpPODs were located sequentially in tandem on chromosomes. In addition, we analyzed the conserved domains of BpPOD proteins and found that they contain highly conserved motifs. We also investigated their expression patterns in different tissues, the results showed that some BpPODs might play an important role in xylem, leaf, root and flower. Furthermore, under low temperature conditions, some BpPODs showed different expression patterns at different times. Conclusions The research on the structure and function of the POD genes in Betula pendula plays a very important role in understanding the growth and development process and the molecular mechanism of stress resistance. These results lay the theoretical foundation for the genetic improvement of Betula pendula.

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Use of serial analysis of gene expression to generate kidney expression libraries

AJP Renal Physiology ◽

10.1152/ajprenal.2000.279.2.f383 ◽

2000 ◽

Vol 279 (2) ◽

pp. F383-F392 ◽

Cited By ~ 16

Author(s):

M. Ashraf El-Meanawy ◽

Jeffrey R. Schelling ◽

Fatima Pozuelo ◽

Matthew M. Churpek ◽

Eckhard K. Ficker ◽

...

Keyword(s):

Gene Expression ◽

Renal Disease ◽

Ribosomal Proteins ◽

Expressed Sequence Tag ◽

Chronic Renal Disease ◽

Expression Patterns ◽

Expression Library ◽

Parathyroid Hormone Receptor ◽

Homology Searching ◽

Genome Wide

Chronic renal disease initiation and progression remain incompletely understood. Genome-wide expression monitoring should clarify mechanisms that cause progressive renal disease by determining how clusters of genes coordinately change their activity. Serial analysis of gene expression (SAGE) is a technique of expression profiling, which permits simultaneous, comparative, and quantitative analysis of gene-specific, 9- to 13-bp sequence tags. Using SAGE, we have constructed a tag expression library from ROP-+/+ mouse kidney. Tag sequences were sorted by abundance, and identity was determined by sequence homology searching. Analyses of 3,868 tags yielded 1,453 unique kidney transcripts. Forty-two percent of these transcripts matched mRNA sequence entries with known function, 35% of the transcripts corresponded to expressed sequence tag (EST) entries or cloned genes, whose function has not been established, and 23% represented unidentified genes. Previously characterized transcripts were clustered into functional groups, and those encoding metabolic enzymes, plasma membrane proteins (transporters/receptors), and ribosomal proteins were most abundant (39, 14, and 12% of known transcripts, respectively). The most common, kidney-specific transcripts were kidney androgen-regulated protein (4% of all transcripts), sodium-phosphate cotransporter (0.3%), renal cytochrome P-450 (0.3%), parathyroid hormone receptor (0.1%), and kidney-specific cadherin (0.1%). Comprehensively characterizing and contrasting gene expression patterns in normal and diseased kidneys will provide an alternative strategy to identify candidate pathways, which regulate nephropathy susceptibility and progression, and novel targets for therapeutic intervention.

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SOMDE: A scalable method for identifying spatially variable genes with self-organizing map

10.1101/2020.12.10.419549 ◽

2020 ◽

Author(s):

Minsheng Hao ◽

Kui Hua ◽

Xuegong Zhang

Keyword(s):

Gene Expression ◽

Large Scale ◽

Expression Patterns ◽

Self Organizing Map ◽

Expression Data ◽

Spatial Expression ◽

Variable Expression ◽

Sequencing Technologies ◽

Physical Context ◽

Variable Genes

AbstractRecent developments of spatial transcriptomic sequencing technologies provide powerful tools for understanding cells in the physical context of tissue micro-environments. A fundamental task in spatial gene expression analysis is to identify genes with spatially variable expression patterns, or spatially variable genes (SVgenes). Several computational methods have been developed for this task. Their high computational complexity limited their scalability to the latest and future large-scale spatial expression data.We present SOMDE, an efficient method for identifying SVgenes in large-scale spatial expression data. SOMDE uses selforganizing map (SOM) to cluster neighboring cells into nodes, and then uses a Gaussian Process to fit the node-level spatial gene expression to identify SVgenes. Experiments show that SOMDE is about 5-50 times faster than existing methods with comparable results. The adjustable resolution of SOMDE makes it the only method that can give results in ~5 minutes in large datasets of more than 20,000 sequencing sites. SOMDE is available as a python package on PyPI at https://pypi.org/project/somde.

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Behavior Individuality: A Focus on Drosophila melanogaster

Frontiers in Physiology ◽

10.3389/fphys.2021.719038 ◽

2021 ◽

Vol 12 ◽

Author(s):

Rubén Mollá-Albaladejo ◽

Juan A. Sánchez-Alcañiz

Keyword(s):

Gene Expression ◽

Drosophila Melanogaster ◽

High Throughput ◽

High Throughput Sequencing ◽

Great Effort ◽

Behavioral Differences ◽

Adult Behavior ◽

Large Numbers ◽

Environmental Variations ◽

And Function

Among individuals, behavioral differences result from the well-known interplay of nature and nurture. Minute differences in the genetic code can lead to differential gene expression and function, dramatically affecting developmental processes and adult behavior. Environmental factors, epigenetic modifications, and gene expression and function are responsible for generating stochastic behaviors. In the last decade, the advent of high-throughput sequencing has facilitated studying the genetic basis of behavior and individuality. We can now study the genomes of multiple individuals and infer which genetic variations might be responsible for the observed behavior. In addition, the development of high-throughput behavioral paradigms, where multiple isogenic animals can be analyzed in various environmental conditions, has again facilitated the study of the influence of genetic and environmental variations in animal personality. Mainly, Drosophila melanogaster has been the focus of a great effort to understand how inter-individual behavioral differences emerge. The possibility of using large numbers of animals, isogenic populations, and the possibility of modifying neuronal function has made it an ideal model to search for the origins of individuality. In the present review, we will focus on the recent findings that try to shed light on the emergence of individuality with a particular interest in D. melanogaster.

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Characterization of Gene Expression Patterns among Artificially Developed Cancer Stem Cells Using Spherical Self-Organizing Map

Cancer Informatics ◽

10.4137/cin.s39839 ◽

2016 ◽

Vol 15 ◽

pp. CIN.S39839 ◽

Cited By ~ 13

Author(s):

Akimasa Seno ◽

Tomonari Kasai ◽

Masashi Ikeda ◽

Arun Vaidyanath ◽

Junko Masuda ◽

...

Keyword(s):

Gene Expression ◽

Stem Cells ◽

Cancer Stem Cells ◽

Human Cancer ◽

Expression Patterns ◽

Embryonic Stem ◽

Culture Conditions ◽

Self Organizing Map ◽

Cancer Tissues ◽

Self Organizing

We performed gene expression microarray analysis coupled with spherical self-organizing map (sSOM) for artificially developed cancer stem cells (CSCs). The CSCs were developed from human induced pluripotent stem cells (hiPSCs) with the conditioned media of cancer cell lines, whereas the CSCs were induced from primary cell culture of human cancer tissues with defined factors ( OCT3/4, SOX2, and KLF4). These cells commonly expressed human embryonic stem cell (hESC)/hiPSC-specific genes ( POU5F1, SOX2, NANOG, LIN28, and SALL4) at a level equivalent to those of control hiPSC 201B7. The sSOM with unsupervised method demonstrated that the CSCs could be divided into three groups based on their culture conditions and original cancer tissues. Furthermore, with supervised method, sSOM nominated TMED9, RNASE1, NGFR, ST3GAL1, TNS4, BTG2, SLC16A3, CD177, CES1, GDF15, STMN2, FAM20A, NPPB, CD99, MYL7, PRSS23, AHNAK, and LOC152573 genes commonly upregulating among the CSCs compared to hiPSC, suggesting the gene signature of the CSCs.

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Linked genetic variation and not genome structure causes widespread differential expression associated with chromosomal inversions

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1721275115 ◽

2018 ◽

Vol 115 (21) ◽

pp. 5492-5497 ◽

Cited By ~ 17

Author(s):

Iskander Said ◽

Ashley Byrne ◽

Victoria Serrano ◽

Charis Cardeno ◽

Christopher Vollmers ◽

...

Keyword(s):

Gene Expression ◽

Natural Selection ◽

Differential Expression ◽

Expression Profiles ◽

Expression Patterns ◽

Genome Structure ◽

Regulatory Domains ◽

Chromosomal Inversions ◽

Important Variation ◽

Genome Wide

Chromosomal inversions are widely thought to be favored by natural selection because they suppress recombination between alleles that have higher fitness on the same genetic background or in similar environments. Nonetheless, few selected alleles have been characterized at the molecular level. Gene expression profiling provides a powerful way to identify functionally important variation associated with inversions and suggests candidate phenotypes. However, altered genome structure itself might also impact gene expression by influencing expression profiles of the genes proximal to inversion breakpoint regions or by modifying expression patterns genome-wide due to rearranging large regulatory domains. In natural inversions, genetic differentiation and genome structure are inextricably linked. Here, we characterize differential expression patterns associated with two chromosomal inversions found in natural Drosophila melanogaster populations. To isolate the impacts of genome structure, we engineered synthetic chromosomal inversions on controlled genetic backgrounds with breakpoints that closely match each natural inversion. We find that synthetic inversions have negligible effects on gene expression. Nonetheless, natural inversions have broad-reaching regulatory impacts in cis and trans. Furthermore, we find that differentially expressed genes associated with both natural inversions are enriched for loci associated with immune response to bacterial pathogens. Our results support the idea that inversions in D. melanogaster experience natural selection to maintain associations between functionally related alleles to produce complex phenotypic outcomes.

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