scholarly journals Modeling Spatial Correlation of Transcripts With Application to Developing Pancreas

2018 ◽  
Author(s):  
Ruishan Liu ◽  
Marco Mignardi ◽  
Robert Jones ◽  
Martin Enge ◽  
Seung K Kim ◽  
...  
Keyword(s):  
Gene Expression ◽  
Spatial Distribution ◽  
Tissue Sample ◽  
Spatial Relationship ◽  
Developmental Time ◽  
Analysis Tool ◽  
Spatial Correlations ◽  
Fixed Tissue ◽  
Time Points ◽  
Spatially Resolved

AbstractRecently high-throughput image-based transcriptomic methods were developed and enabled researchers to spatially resolve gene expression variation at the molecular level for the first time. In this work, we develop a general analysis tool to quantitatively study the spatial correlations of gene expression in fixed tissue sections. As an illustration, we analyze the spatial distribution of single mRNA molecules measured by in situ sequencing on human fetal pancreas at three developmental time points 80, 87 and 117 days post-fertilization. We develop a density profile-based method to capture the spatial relationship between gene expression and other morphological features of the tissue sample such as position of nuclei and endocrine cells of the pancreas. In addition, we build a statistical model to characterize correlations in the spatial distribution of the expression level among different genes. This model enables us to infer the inhibitory and clustering effects throughout different time points. Our analysis framework is applicable to a wide variety of spatially-resolved transcriptomic data to derive biological insights.

A new method for gene expression analysis of pure lymphocytes recovered from heterogeneous fixed mouse tissue.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e23089-e23089
Author(s):  
Jennifer Chow ◽  
Ana Paula Galvão Da Silva ◽  
Gianni Medoro ◽  
Nicolò Manaresi ◽  
Paul David Lira ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Analysis ◽  
Gene Expression Analysis ◽  
Tissue Sample ◽  
Critical Role ◽  
Rna Extraction ◽  
Response To Treatment ◽  
Mouse Tissue ◽  
Fixed Tissue ◽  
Mouse Splenocytes

e23089 Background: Tumor infiltrating lymphocytes (TILs) are biomarkers that play a critical role in cancer diseases, including differential diagnosis, determination of prognosis, prediction of response to treatment, and evaluation of disease progression. Gene expression analysis in TILs derived from fresh tissue may not accurately depict the gene profile of the tissue microenvironment as it can change aggressively during lymphocyte isolation and RNA extraction. In addition, tissue sample size can limit the isolation of TILs with current technologies. In this study, we demonstrate the use of the DEPArray™platform to isolate pure populations of lymphocytes from a fixed mouse tissue for RNA analysi. Methods: Mouse splenocytes were activated in vitro with anti-CD3 and -CD28 for 72hs. Cells were harvested, fixed with 2% paraformaldehyde (PFA) for 20 min at RT, and stained for either CD4 or CD8 expression. Gene expression analysis of CD45, ADORA2A, GLS and GAPDH was performed in CD4+ and CD8+ DEPArray™sorted cells using the TaqMan PreAmp Cells-to-Ct kit. Results: The table below summarizes the Ct values for CD45, ADORA2A, GLS and GAPDH expression in 300 fixed unsorted control and DEPArray™sorted lymphocytes. Conclusions: We have demonstrated the feasibility of gene expression analysis on pure populations of CD4+ and CD8+ cells isolated from a fixed tissue using the DEPArray™ platform. The advantage of this approach is the DEPArray’s ability to identify and isolate subpopulations of cells from complex heterogeneous samples and/or specimens that are limited by size or content. This methodology will be applied for isolation of TILs in syngeneic and xenograft models of cancers for downstream RNA applications. [Table: see text]

scholarly journals RNA Interference in Aquatic Beetles as a Powerful Tool for Manipulating Gene Expression at Specific Developmental Time Points

10.3791/61477 ◽  
2020 ◽  
Author(s):  
Shubham Rathore ◽  
Jenni Hassert ◽  
Courtney M. Clark-Hachtel ◽  
Aaron Stahl ◽  
Yoshinori Tomoyasu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Interference ◽  
Developmental Time ◽  
Time Points ◽  
Aquatic Beetles

scholarly journals Developmental Transcriptional Model Describing Regulated Genes, Qtls And Pathways During The Primary And Secondary Cell Walls Of Pima Fibers

2016 ◽  
Author(s):  
Magdy S. Alabady ◽  
Bulak A. Arpat
Keyword(s):  
Gene Expression ◽  
Developmental Stages ◽  
Expression Profiles ◽  
Fiber Quality ◽  
Time Frame ◽  
Developmental Time ◽  
Transcriptional Level ◽  
Specific Expression ◽  
Time Points ◽  
Cotton Genotypes

AbstractGossypium barbadense L. (Egyptian and Pima) produces single celled fiber trichomes that are the longest and richest in cellulosic contents in the plant kingdom. Developmental dissection of fiber at the transcriptional level is crucial to unveiling the genetic mechanisms underpinning fiber morphogenesis. We profiled the transcriptome of developing Pima fibers, as well as genes associated with consensus fiber quality QTLs, at seven developmental time points covering both primary (PCW) and secondary (SCW) cell wall stages. A total of 2,934 genes were differentially expressed at only one (45.19%) or at multiple (54.81%) developmental time points. Based on the coincidence between gene expression dynamics and the time frame of fiber developmental stages, five stage-specific expression profiles were identified. As a link between fiber QTLs and gene expression, 5 potential developmentally regulated QTLs (drQTLs) corresponding to different fiber developmental stages were identified. Genes in the ubiquitin proteolytic pathway, particularly QTL associated genes, appeared to be involved in regulating the transition stage between PCW and SCW; a stage that is crucial to both fiber length and strength in the extra-long staple cotton genotypes. In this respect, Yeast-two-hybrids identified interactions between UBC9 and genes involved in cell and organ elongation, polar cell expansion, microtubule cytoskeleton dynamics and organization, and basic amino acids transportation during the SCW/SCW transition. Altogether, these results were integrated into a proposed model linking fiber developmental stages with the Pima fiber traits.

scholarly journals Single-cell transcriptomics of the Drosophila wing disc reveals instructive epithelium-to-myoblast interactions

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Nicholas J Everetts ◽  
Melanie I Worley ◽  
Riku Yasutomi ◽  
Nir Yosef ◽  
Iswar K Hariharan
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Developmental Time ◽  
Wing Disc ◽  
Fibroblast Growth ◽  
Transcriptional Program ◽  
Time Points ◽  
Drosophila Wing ◽  
Direct Flight ◽  
Flight Muscles

In both vertebrates and invertebrates, generating a functional appendage requires interactions between ectoderm-derived epithelia and mesoderm-derived cells. To investigate such interactions, we used single-cell transcriptomics to generate a temporal cell atlas of theDrosophilawing disc from two developmental time points. Using these data, we visualized gene expression using a multilayered model of the wing disc and cataloged ligand–receptor pairs that could mediate signaling between epithelial cells and adult muscle precursors (AMPs). We found that localized expression of the fibroblast growth factor ligands, Thisbe and Pyramus, in the disc epithelium regulates the number and location of the AMPs. In addition, Hedgehog ligand from the epithelium activates a specific transcriptional program within adjacent AMP cells, defined by AMP-specific targetsNeurotactinandmidline, that is critical for proper formation of direct flight muscles. More generally, our annotated temporal cell atlas provides an organ-wide view of potential cell–cell interactions between epithelial and myogenic cells.

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.

scholarly journals Species diversity and spatial distribution of CL/VL vectors: assessing bioclimatic effect on expression plasticity of genes possessing vaccine properties isolated from wild-collected sand flies in endemic areas of Iran

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ali Bordbar ◽  
Parviz Parvizi
Keyword(s):  
Gene Expression ◽  
Spatial Distribution ◽  
Interpolation Method ◽  
Diversity Index ◽  
Fold Change ◽  
Control Measures ◽  
Pcr Analysis ◽  
Physiological Status ◽  
Sand Flies ◽  
Risk Maps

Abstract Background Leishmaniasis is one of the ten most important neglected tropical diseases worldwide. Understanding the distribution of vectors of visceral and cutaneous leishmaniasis (VL/CL) is one of the significant strategic frameworks to control leishmaniasis. In this study, the extent of the bioclimatic variability was investigated to recognize a rigorous cartographic of the spatial distribution of VL/CL vectors as risk-maps using ArcGIS modeling system. Moreover, the effect of bioclimatic diversity on the fold change expression of genes possessing vaccine traits (SP15 and LeIF) was evaluated in each bioclimatic region using real-time PCR analysis. Methods The Inverse Distance Weighting interpolation method was used to obtain accurate geography map in closely-related distances. Bioclimatic indices were computed and vectors spatial distribution was analyzed in ArcGIS10.3.1 system. Species biodiversity was calculated based on Shannon diversity index using Rv.3.5.3. Expression fold change of SP15 and LeIF genes was evaluated using cDNA synthesis and RT-qPCR analysis. Results Frequency of Phlebotomus papatasi was predominant in plains areas of Mountainous bioclimate covering the CL hot spots. Mediterranean region was recognized as an important bioclimate harboring prevalent patterns of VL vectors. Semi-arid bioclimate was identified as a major contributing factor to up-regulate salivary-SP15 gene expression (P = 0.0050, P < 0.05). Also, Mediterranean bioclimate had considerable effect on up-regulation of Leishmania-LeIF gene in gravid and semi-gravid P. papatasi population (P = 0.0109, P < 0.05). Conclusions The diversity and spatial distribution of CL/VL vectors associated with bioclimatic regionalization obtained in our research provide epidemiological risk maps and establish more effectively control measures against leishmaniasis. Oscillations in gene expression indicate that each gene has its own features, which are profoundly affected by bioclimatic characteristics and physiological status of sand flies. Given the efficacy of species-specific antigens for vaccine production, it is essential to consider bioclimatic factors that have a fundamental role in affecting the regulatory regions of environmentally responsive loci for genes used in vaccine design.

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