scholarly journals Methods detecting rhythmic gene expression are biologically relevant only for strong signal

2019 ◽  
Author(s):  
David Laloum ◽  
Marc Robinson-Rechavi
Keyword(s):  
Gene Expression ◽  
Reference Group ◽  
Biologically Relevant ◽  
Rna Molecules ◽  
Time Points ◽  
Rhythmic Expression ◽  
Large Sets ◽  
Naive Method ◽  
Highly Expressed Genes ◽  
Rhythmic Gene

AbstractThe nycthemeral transcriptome embodies all genes displaying a rhythmic variation of their mRNAs periodically every 24 hours, including but not restricted to circadian genes. In this study, we show that the nycthemeral rhythmicity at the gene expression level is biologically functional and that this functionality is more conserved between orthologous genes than between random genes. We used this conservation of the rhythmic expression to assess the ability of seven methods (ARSER, Lomb Scargle, RAIN, JTK, empirical-JTK, GeneCycle, and meta2d) to detect rhythmic signal in gene expression. We have contrasted them to a naive method, not based on rhythmic parameters. By taking into account the tissue-specificity of rhythmic gene expression and different species comparisons, we show that no method is strongly favored. The results show that these methods designed for rhythm detection, in addition to having quite similar performances, are consistent only among genes with a strong rhythm signal. Rhythmic genes defined with a standard p-value threshold of 0.01 for instance, could include genes whose rhythmicity is biologically irrelevant. Although these results were dependent on the datasets used and the evolutionary distance between the species compared, we call for caution about the results of studies reporting or using large sets of rhythmic genes. Furthermore, given the analysis of the behaviors of the methods on real and randomized data, we recommend using primarily ARS, empJTK, or GeneCycle, which verify expectations of a classical distribution of p-values. Experimental design should also take into account the circumstances under which the methods seem more efficient, such as giving priority to biological replicates over the number of time-points, or to the number of time-points over the quality of the technique (microarray vs RNAseq). GeneCycle, and to a lesser extent empirical-JTK, might be the most robust method when applied to weakly informative datasets. Finally, our analyzes suggest that rhythmic genes are mainly highly expressed genes.Author SummaryTo be active, genes have to be transcribed to RNA. For some genes, the transcription rate follows a circadian rhythm with a periodicity of approximately 24 hours; we call these genes “rhythmic”. In this study, we compared methods designed to detect rhythmic genes in gene expression data. The data are measures of the number of RNA molecules for each gene, given at several time-points, usually spaced 2 to 4 hours, over one or several periods of 24 hours. There are many such methods, but it is not known which ones work best to detect genes whose rhythmic expression is biologically functional. We compared these methods using a reference group of evolutionarily conserved rhythmic genes. We compared data from baboon, mouse, rat, zebrafish, fly, and mosquitoes. Surprisingly, no method was particularly effective. Furthermore, we found that only very strong rhythmic signals were relevant with each method. More precisely, when we use a usual cut-off to define rhythmic genes, the group of genes considered as rhythmic contains many genes whose rhythmicity cannot be confirmed to be biologically relevant. We also show that rhythmic genes mainly contain highly expressed genes. Finally, based on our results, we provide recommendations on which methods to use and how, and suggestions for future experimental designs.

The G-CSF Produces Long-Term Changes in Gene and Mirnas Expression Profiles in CD34+ From Healthy Donors

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 588-588
Author(s):  
Alicia Báez ◽  
Concepción Prats-Martín ◽  
Isabel Álvarez-Laderas ◽  
Estefania Garcia ◽  
Luis Ignacio Sanchez-Abarca ◽  
...  
Keyword(s):  
Gene Expression ◽  
Conflicts Of Interest ◽  
Reference Group ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Long Term Effects ◽  
Time Points ◽  
Healthy Donors ◽  
Mirnas Expression

Abstract Abstract 588 Introduction: The G-CSF (granulocyte colony-stimulating factor) is the cytokine most commonly used for the mobilization of hematopoietic progenitor cells (HPCs) from healthy donors used in allogenic transplantation (allo-HSCT). Although the administration of G-CSF is considered safe, the knowledge about its long-term effects, especially in HPCs, is limited. The aim of this study was to analyze whether G-CSF induces changes in gene and miRNAs expression profiles in HPCs from healthy donors, and determine whether or not these changes persist at the long term. Materials and Method: CD34 + cells were isolated by immunomagnetic separation and sorting from 5 healthy donors before mobilization with G-CSF and at afterwards at 5, 30 and 365 days after mobilization. A pool of samples from PB not mobilized was used as reference group. We analyzed the expression of 375 miRNAs using TaqMan MicroRNA Arrays Human v2.0 (Applied Biosystems), and the gene expression profile using Whole Human Genome Oligo microarray kit 4×44K (Agilent). The expression levels of genes and miRNAs were obtained by the 2-ΔΔCTmethod. From expression data hierarchical clustering was performed using the Euclidean distance. To identify genes and miRNAs differentially expressed due to the effect of G-CSF at different time-points a cut-off value of level expression 2,5 above or below the control values was used and non-parametric Mann-Whitney test was applied. All analysis were performed using the Multi-experiment Viewer 4.7.1. The function of the miRNAs and genes of interest was determined from the various databases available online (TAM database, Gene Ontology, TargetScan Human). Results: Seven miRNAs were differentially expressed in HPCs at 5, 30 and 365 days after mobilization with G-CSF, as compared to HPCs obtained from not mobilized PB. In addition, 67 genes were also differentially expressed after administration of G-CSF, whose expression profiles remained abnormal 1 year after mobilization. These genes are involved in biological processes such as hematopoietic cell proliferation, ribosomal protein synthesis, cell metabolism and transmembrane transportation. Interestingly, 8 of these genes are target of the miRNAs also identified in the current study, which suggests that their expression might be regulated by these miRNAs. Conclusion: The G-CSF modifies gene expression profiles and miRNAs in HPCs from healthy donors. Remarkably, these changes were observed from early time-points and persisted at least 1 year after exposure to the drug. This effect of G-CSF on HPCs have not been previously reported and might be clinically relevant. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Isoform-specific regulation of rhythmic gene expression by alternative polyadenylation

2020 ◽  
Author(s):  
Ben J Greenwell ◽  
Joshua R Beytebiere ◽  
Teresa M Lamb ◽  
Deborah Bell-Pedersen ◽  
Christine Merlin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Alternative Polyadenylation ◽  
Active Phase ◽  
Specific Expression ◽  
Rhythmic Expression ◽  
Rhythmic Gene ◽  
Specific Regulation ◽  
Underlying Mechanisms

Alternative polyadenylation (APA) generates transcript isoforms with different 3′ ends. Differences in polyadenylation sites usage, which have been associated with diseases like cancer, regulate mRNA stability, subcellular localization, and translation. By characterizing APA across the 24-hour day in mouse liver, here we show that rhythmic gene expression occurs largely in an APA isoform-specific manner, and that hundreds of arrhythmically expressed genes surprisingly exhibit a rhythmic APA isoform. The underlying mechanisms comprise isoform-specific post-transcriptional regulation, transcription factor driven expression of specific isoform, co-transcriptional recruitment of RNA binding proteins that regulate mRNA cleavage and polyadenylation, and, to a lesser extent, cell subtype-specific expression. Remarkably, rhythmic expression of specific APA isoforms generates 24-hour rhythms in 3′ UTR length, with shorter UTRs in anticipation of the mouse active phase. Taken together, our findings demonstrate that cycling transcriptomes are regulated by APA, and suggest that APA strongly impacts the rhythmic regulation of biological functions.

scholarly journals Evidence of transfer of miRNAs from the diet to the blood still inconclusive

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9567
Author(s):  
Fermín Mar-Aguilar ◽  
Alejandra Arreola-Triana ◽  
Daniela Mata-Cardona ◽  
Vianey Gonzalez-Villasana ◽  
Cristina Rodríguez-Padilla ◽  
...  
Keyword(s):  
Gene Expression ◽  
Model Organism ◽  
Food Sources ◽  
Plant Mirnas ◽  
Biologically Relevant ◽  
Rna Molecules ◽  
Cooking Process ◽  
Caste Development ◽  
Harsh Conditions

MicroRNAs (miRNAs) are short, non-coding, single-strand RNA molecules that act as regulators of gene expression in plants and animals. In 2012, the first evidence was found that plant miRNAs could enter the bloodstream through the digestive tract. Since then, there has been an ongoing discussion about whether miRNAs from the diet are transferred to blood, accumulate in tissues, and regulate gene expression. Different research groups have tried to replicate these findings, using both plant and animal sources. Here, we review the evidence for and against the transfer of diet-derived miRNAs from plants, meat, milk and exosome and their assimilation and putative molecular regulation role in the consuming organism. Some groups using both miRNAs from plant and animal sources have claimed success, whereas others have not shown transfer. In spite of the biological barriers that may limit miRNA transference, several diet-derived miRNAs can transfer into the circulating system and targets genes for transcription regulation, which adds arguments that miRNAs can be absorbed from the diet and target specific genes by regulating their expression. However, many other studies show that cross-kingdom transfer of exogenous miRNAs appears to be insignificant and not biologically relevant. The main source of controversy in plant studies is the lack of reproducibility of the findings. For meat-derived miRNAs, studies concluded that the miRNAs can survive the cooking process; nevertheless, our evidence shows that the bovine miRNAs are not transferred to human bloodstream. The most important contributions and promising evidence in this controversial field is the transference of milk miRNAs in exosomes and the finding that plant miRNAs in beebread regulate honeybee caste development, and cause similar changes when fed to Drosophila. MiRNAs encapsulated in exosomes ensure their stability and resistance in the harsh conditions presented in milk, bloodstream, and gastrointestinaltract to reinforce the idea of transference. Regardless of the model organism, the idea of source of miRNAs, or the approach—bioinformatics or in vivo—the issue of transfer of miRNAs from the diet remains in doubt. Our understanding of the cross-kingdom talk of miRNAs needs more research to study the transfer of “xenomiRs” from different food sources to complement and expand what we know so far regarding the interspecies transfer of miRNAs.

scholarly journals Transcriptomal dissection of soybean circadian rhythmicity in two geographically, phenotypically and genetically distinct cultivars

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yanlei Yue ◽  
Ze Jiang ◽  
Enoch Sapey ◽  
Tingting Wu ◽  
Shi Sun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Circadian Clock ◽  
Chromosome Structure ◽  
Clock Genes ◽  
Expression Profiles ◽  
Circadian Rhythmicity ◽  
Rna Seq ◽  
Night Time ◽  
Time Points ◽  
Circadian Clock Genes

Abstract Background In soybean, some circadian clock genes have been identified as loci for maturity traits. However, the effects of these genes on soybean circadian rhythmicity and their impacts on maturity are unclear. Results We used two geographically, phenotypically and genetically distinct cultivars, conventional juvenile Zhonghuang 24 (with functional J/GmELF3a, a homolog of the circadian clock indispensable component EARLY FLOWERING 3) and long juvenile Huaxia 3 (with dysfunctional j/Gmelf3a) to dissect the soybean circadian clock with time-series transcriptomal RNA-Seq analysis of unifoliate leaves on a day scale. The results showed that several known circadian clock components, including RVE1, GI, LUX and TOC1, phase differently in soybean than in Arabidopsis, demonstrating that the soybean circadian clock is obviously different from the canonical model in Arabidopsis. In contrast to the observation that ELF3 dysfunction results in clock arrhythmia in Arabidopsis, the circadian clock is conserved in soybean regardless of the functional status of J/GmELF3a. Soybean exhibits a circadian rhythmicity in both gene expression and alternative splicing. Genes can be grouped into six clusters, C1-C6, with different expression profiles. Many more genes are grouped into the night clusters (C4-C6) than in the day cluster (C2), showing that night is essential for gene expression and regulation. Moreover, soybean chromosomes are activated with a circadian rhythmicity, indicating that high-order chromosome structure might impact circadian rhythmicity. Interestingly, night time points were clustered in one group, while day time points were separated into two groups, morning and afternoon, demonstrating that morning and afternoon are representative of different environments for soybean growth and development. However, no genes were consistently differentially expressed over different time-points, indicating that it is necessary to perform a circadian rhythmicity analysis to more thoroughly dissect the function of a gene. Moreover, the analysis of the circadian rhythmicity of the GmFT family showed that GmELF3a might phase- and amplitude-modulate the GmFT family to regulate the juvenility and maturity traits of soybean. Conclusions These results and the resultant RNA-seq data should be helpful in understanding the soybean circadian clock and elucidating the connection between the circadian clock and soybean maturity.

scholarly journals Comparative neurotranscriptomics reveal widespread species differences associated with bonding

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Joel A. Tripp ◽  
Alejandro Berrio ◽  
Lisa A. McGraw ◽  
Mikhail V. Matz ◽  
Jamie K. Davis ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brain Region ◽  
Molecular Mechanisms ◽  
Species Differences ◽  
Cell Structure ◽  
Bond Formation ◽  
Pair Bonding ◽  
Prairie Voles ◽  
Meadow Voles ◽  
Time Points

Abstract Background Pair bonding with a reproductive partner is rare among mammals but is an important feature of human social behavior. Decades of research on monogamous prairie voles (Microtus ochrogaster), along with comparative studies using the related non-bonding meadow vole (M. pennsylvanicus), have revealed many of the neural and molecular mechanisms necessary for pair-bond formation in that species. However, these studies have largely focused on just a few neuromodulatory systems. To test the hypothesis that neural gene expression differences underlie differential capacities to bond, we performed RNA-sequencing on tissue from three brain regions important for bonding and other social behaviors across bond-forming prairie voles and non-bonding meadow voles. We examined gene expression in the amygdala, hypothalamus, and combined ventral pallidum/nucleus accumbens in virgins and at three time points after mating to understand species differences in gene expression at baseline, in response to mating, and during bond formation. Results We first identified species and brain region as the factors most strongly associated with gene expression in our samples. Next, we found gene categories related to cell structure, translation, and metabolism that differed in expression across species in virgins, as well as categories associated with cell structure, synaptic and neuroendocrine signaling, and transcription and translation that varied among the focal regions in our study. Additionally, we identified genes that were differentially expressed across species after mating in each of our regions of interest. These include genes involved in regulating transcription, neuron structure, and synaptic plasticity. Finally, we identified modules of co-regulated genes that were strongly correlated with brain region in both species, and modules that were correlated with post-mating time points in prairie voles but not meadow voles. Conclusions These results reinforce the importance of pre-mating differences that confer the ability to form pair bonds in prairie voles but not promiscuous species such as meadow voles. Gene ontology analysis supports the hypothesis that pair-bond formation involves transcriptional regulation, and changes in neuronal structure. Together, our results expand knowledge of the genes involved in the pair bonding process and open new avenues of research in the molecular mechanisms of bond formation.

scholarly journals Bayesian approach for predicting responses to therapy from high-dimensional time-course gene expression profiles

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Arika Fukushima ◽  
Masahiro Sugimoto ◽  
Satoru Hiwa ◽  
Tomoyuki Hiroyasu
Keyword(s):  
Gene Expression ◽  
Time Course ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Response To Therapy ◽  
Hcv Infection ◽  
Entire Treatment Period ◽  
Time Points ◽  
Time Course Data ◽  
Conventional Methods

Abstract Background Historical and updated information provided by time-course data collected during an entire treatment period proves to be more useful than information provided by single-point data. Accurate predictions made using time-course data on multiple biomarkers that indicate a patient’s response to therapy contribute positively to the decision-making process associated with designing effective treatment programs for various diseases. Therefore, the development of prediction methods incorporating time-course data on multiple markers is necessary. Results We proposed new methods that may be used for prediction and gene selection via time-course gene expression profiles. Our prediction method consolidated multiple probabilities calculated using gene expression profiles collected over a series of time points to predict therapy response. Using two data sets collected from patients with hepatitis C virus (HCV) infection and multiple sclerosis (MS), we performed numerical experiments that predicted response to therapy and evaluated their accuracies. Our methods were more accurate than conventional methods and successfully selected genes, the functions of which were associated with the pathology of HCV infection and MS. Conclusions The proposed method accurately predicted response to therapy using data at multiple time points. It showed higher accuracies at early time points compared to those of conventional methods. Furthermore, this method successfully selected genes that were directly associated with diseases.

scholarly journals Chronic complement dysregulation drives neuroinflammation after traumatic brain injury: a transcriptomic study

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Amer Toutonji ◽  
Mamatha Mandava ◽  
Silvia Guglietta ◽  
Stephen Tomlinson
Keyword(s):  
Gene Expression ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Complement System ◽  
Classical Pathway ◽  
Post Injury ◽  
Complement Inhibition ◽  
Time Points ◽  
Complement Gene ◽  
The Complement System

AbstractActivation of the complement system propagates neuroinflammation and brain damage early and chronically after traumatic brain injury (TBI). The complement system is complex and comprises more than 50 components, many of which remain to be characterized in the normal and injured brain. Moreover, complement therapeutic studies have focused on a limited number of histopathological outcomes, which while informative, do not assess the effect of complement inhibition on neuroprotection and inflammation in a comprehensive manner. Using high throughput gene expression technology (NanoString), we simultaneously analyzed complement gene expression profiles with other neuroinflammatory pathway genes at different time points after TBI. We additionally assessed the effects of complement inhibition on neuropathological processes. Analyses of neuroinflammatory genes were performed at days 3, 7, and 28 post injury in male C57BL/6 mice following a controlled cortical impact injury. We also characterized the expression of 59 complement genes at similar time points, and also at 1- and 2-years post injury. Overall, TBI upregulated the expression of markers of astrogliosis, immune cell activation, and cellular stress, and downregulated the expression of neuronal and synaptic markers from day 3 through 28 post injury. Moreover, TBI upregulated gene expression across most complement activation and effector pathways, with an early emphasis on classical pathway genes and with continued upregulation of C2, C3 and C4 expression 2 years post injury. Treatment using the targeted complement inhibitor, CR2-Crry, significantly ameliorated TBI-induced transcriptomic changes at all time points. Nevertheless, some immune and synaptic genes remained dysregulated with CR2-Crry treatment, suggesting adjuvant anti-inflammatory and neurotropic therapy may confer additional neuroprotection. In addition to characterizing complement gene expression in the normal and aging brain, our results demonstrate broad and chronic dysregulation of the complement system after TBI, and strengthen the view that the complement system is an attractive target for TBI therapy.

Light-Induced Gene Expression Using Messenger RNA Molecules

2010 ◽  
Vol 20 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Sigurd Bøe ◽  
Stein Sæbøe-Larssen ◽  
Eivind Hovig
Keyword(s):  
Gene Expression ◽  
Messenger Rna ◽  
Rna Molecules

scholarly journals Multi-species transcriptome meta-analysis of the response to retinoic acid in vertebrates and comparative analysis of the effects of retinol and retinoic acid on gene expression in LMH cells

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Clemens Falker-Gieske ◽  
Andrea Mott ◽  
Sören Franzenburg ◽  
Jens Tetens
Keyword(s):  
Gene Expression ◽  
Retinoic Acid ◽  
Cellular Response ◽  
Homo Sapiens ◽  
Meta Analysis ◽  
Early Response ◽  
Rna Seq ◽  
Transcriptomic Response ◽  
Time Points ◽  
Lmh Cells

Abstract Background Retinol (RO) and its active metabolite retinoic acid (RA) are major regulators of gene expression in vertebrates and influence various processes like organ development, cell differentiation, and immune response. To characterize a general transcriptomic response to RA-exposure in vertebrates, independent of species- and tissue-specific effects, four publicly available RNA-Seq datasets from Homo sapiens, Mus musculus, and Xenopus laevis were analyzed. To increase species and cell-type diversity we generated RNA-seq data with chicken hepatocellular carcinoma (LMH) cells. Additionally, we compared the response of LMH cells to RA and RO at different time points. Results By conducting a transcriptome meta-analysis, we identified three retinoic acid response core clusters (RARCCs) consisting of 27 interacting proteins, seven of which have not been associated with retinoids yet. Comparison of the transcriptional response of LMH cells to RO and RA exposure at different time points led to the identification of non-coding RNAs (ncRNAs) that are only differentially expressed (DE) during the early response. Conclusions We propose that these RARCCs stand on top of a common regulatory RA hierarchy among vertebrates. Based on the protein sets included in these clusters we were able to identify an RA-response cluster, a control center type cluster, and a cluster that directs cell proliferation. Concerning the comparison of the cellular response to RA and RO we conclude that ncRNAs play an underestimated role in retinoid-mediated gene regulation.

Sign in / Sign up

Export Citation Format

Share Document