scholarly journals Transcriptional analysis of Bemisia tabaci MEAM1 cryptic species under the selection pressure of neonicotinoids imidacloprid, acetamiprid and thiamethoxam

BMC Genomics ◽  
2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Cheng Song Zhou ◽  
Huan Huan Lv ◽  
Xiao Hu Guo ◽  
Qian Cao ◽  
Rui Xingyue Zhang ◽  
...  
Keyword(s):  
Bemisia Tabaci ◽  
Sequence Data ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Transcriptional Analysis ◽  
Cross Resistance ◽  
Rna Seq ◽  
Severe Problem ◽  
Cuticle Protein ◽  
Resistant Strains

Abstract Background Neonicotinoids are widely applied in the control of the destructive agricultural pest Bemisia tabaci, and resistance against these chemicals has become a common, severe problem in the control of whiteflies. To investigate the molecular mechanism underlying resistance against nenonicotinoids in whiteflies, RNA-seq technology was applied, and the variation in the transcriptomic profiles of susceptible whiteflies and whiteflies selected by imidacloprid, acetamiprid and thiamethoxam treatment was characterized. Results A total of 90.86 GB of clean sequence data were obtained from the 4 transcriptomes. Among the 16,069 assembled genes, 584, 110 and 147 genes were upregulated in the imidacloprid-selected strain (IMI), acetamiprid-selected strain (ACE), and thiamethoxam (THI)-selected strain, respectively, relative to the susceptible strain. Detoxification-related genes including P450s, cuticle protein genes, GSTs, UGTs and molecular chaperone HSP70s were overexpressed in the selected resistant strains, especially in the IMI strain. Five genes were downregulated in all three selected resistant strains, including 2 UDP-glucuronosyltransferase 2B18-like genes (LOC 109030370 and LOC 109032577). Conclusions Ten generations of selection with the three neonicotinoids induced different resistance levels and gene expression profiles, mainly involving cuticle protein and P450 genes, in the three selected resistant whitefly strains. The results provide a reference for research on resistance and cross-resistance against neonicotinoids in B. tabaci.

scholarly journals A tensor decomposition-based integrated analysis applicable to multiple gene expression profiles without sample matching

2021 ◽  
Author(s):  
Taguchi Y-h. ◽  
Turki Turki
Keyword(s):  
Gene Expression ◽  
Learning Strategies ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Tensor Decomposition ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Prior Learning ◽  
Multiple Gene ◽  
Machine Learning Applications

Abstract The integrated analysis of multiple gene expression profiles measured in distinct studies is always problematic. Especially, missing sample matching and missing common labeling between distinct studies prevent the integration of multiple studies in fully data-driven and unsupervised manner. In this study, we propose a strategy enabling the integration of multiple gene expression profiles among multiple independent studies without either labeling or sample matching, using tensor decomposition-based unsupervised feature extraction. As an example, we applied this strategy to Alzheimer’s disease (AD)-related gene expression profiles that lack exact correspondence among samples as well as AD single-cell RNA-seq (scRNA-seq) data. We found that we could select biologically reasonable genes with integrated analysis. Overall, integrated gene expression profiles can function analogously to prior learning and/or transfer learning strategies in other machine learning applications. For scRNA-seq, the proposed approach was able to drastically reduce the required computational memory.

The characteristics of mesenteric adipose tissue attached to different intestinal segments and their roles in immune regulation

2022 ◽  
Author(s):  
Haowei Zhang ◽  
Yujin Ding ◽  
Qin Zeng ◽  
Dandan Wang ◽  
Ganglei Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Adipose Tissue ◽  
Immune Regulation ◽  
Expression Profiles ◽  
Critical Role ◽  
Gene Expression Profiles ◽  
Rna Seq ◽  
Mesenteric Adipose Tissue ◽  
Cell Components ◽  
Subsequent Effect

Background: Mesenteric adipose tissue (MAT) plays a critical role in the intestinal physiological ecosystems. Small and large intestines have evidently intrinsic and distinct characteristics. However, whether there exist any mesenteric differences adjacent to the small and large intestines (SMAT and LMAT) has not been properly characterized. We studied the important facets of these differences, such as morphology, gene expression, cell components and immune regulation of MATs, to characterize the mesenteric differences. Methods: The SMAT and LMAT of mice were utilized for comparison of tissue morphology. Paired mesenteric samples were analyzed by RNA-seq to clarify gene expression profiles. MAT partial excision models were constructed to illustrate the immune regulation roles of MATs, and 16S-seq was applied to detect the subsequent effect on microbiota. Results: Our data show that different segments of mesenteries have different morphological structures. SMAT not only has smaller adipocytes but also contains more fat-associated lymphoid clusters than LMAT. The gene expression profile is also discrepant between these two MATs in mice. B-cell markers were abundantly expressed in SMAT, while development-related genes were highly expressed in LMAT. Adipose-derived stem cells of LMAT exhibited higher adipogenic potential and lower proliferation rates than those of SMAT. In addition, SMAT and LMAT play different roles in immune regulation and subsequently affect microbiota components. Finally, our data clarified the described differences between SMAT and LMAT in humans. Conclusions: There were significant differences in cell morphology, gene expression profiles, cell components, biological characteristics, and immune and microbiota regulation roles between regional MATs.

scholarly journals Comparative Transcriptome Analysis of Different Dendrobium Species Reveals Active Ingredients-Related Genes and Pathways

2020 ◽  
Vol 21 (3) ◽  
pp. 861 ◽  
Author(s):  
Yingdan Yuan ◽  
Bo Zhang ◽  
Xinggang Tang ◽  
Jinchi Zhang ◽  
Jie Lin
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Rna Seq ◽  
Active Ingredients ◽  
Hub Genes ◽  
Transcriptome Database ◽  
Gene Modules ◽  
Functional Investigation ◽  
First Time

Dendrobium is widely used in traditional Chinese medicine, which contains many kinds of active ingredients. In recent years, many Dendrobium transcriptomes have been sequenced. Hence, weighted gene co-expression network analysis (WGCNA) was used with the gene expression profiles of active ingredients to identify the modules and genes that may associate with particular species and tissues. Three kinds of Dendrobium species and three tissues were sampled for RNA-seq to generate a high-quality, full-length transcriptome database. Based on significant changes in gene expression, we constructed co-expression networks and revealed 19 gene modules. Among them, four modules with properties correlating to active ingredients regulation and biosynthesis, and several hub genes were selected for further functional investigation. This is the first time the WGCNA method has been used to analyze Dendrobium transcriptome data. Further excavation of the gene module information will help us to further study the role and significance of key genes, key signaling pathways, and regulatory mechanisms between genes on the occurrence and development of medicinal components of Dendrobium.

scholarly journals NASA GeneLab RNA-Seq Consensus Pipeline: Standardized Processing of Short-Read RNA-Seq Data

2020 ◽  
Author(s):  
Eliah G. Overbey ◽  
Amanda M. Saravia-Butler ◽  
Zhe Zhang ◽  
Komal S. Rathi ◽  
Homer Fogle ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Rna Seq ◽  
Sequencing Data ◽  
Analysis Pipeline ◽  
Short Read ◽  
Gene Quantification ◽  
Working Groups ◽  
Using Data ◽  
Data Analysis Pipeline

SummaryWith the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility and reusability of pipeline data, to provide a template for data processing of future spaceflight-relevant datasets, and to encourage cross-analysis of data from other databases with the data available in GeneLab.

scholarly journals Interferon-regulated genetic programs and JAK/STAT pathway activate the intronic promoter of the short ACE2 isoform in renal proximal tubules

2021 ◽  
Author(s):  
Jakub Jankowski ◽  
Hye Kyung Lee ◽  
Julia Wilflingseder ◽  
Lothar Hennighausen
Keyword(s):  
Gene Expression ◽  
Proximal Tubule ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Regulatory Elements ◽  
Rna Seq ◽  
Angiotensin Converting Enzyme 2 ◽  
Genome Wide ◽  
Cytokine Stimulation

SummaryRecently, a short, interferon-inducible isoform of Angiotensin-Converting Enzyme 2 (ACE2), dACE2 was identified. ACE2 is a SARS-Cov-2 receptor and changes in its renal expression have been linked to several human nephropathies. These changes were never analyzed in context of dACE2, as its expression was not investigated in the kidney. We used Human Primary Proximal Tubule (HPPT) cells to show genome-wide gene expression patterns after cytokine stimulation, with emphasis on the ACE2/dACE2 locus. Putative regulatory elements controlling dACE2 expression were identified using ChIP-seq and RNA-seq. qRT-PCR differentiating between ACE2 and dACE2 revealed 300- and 600-fold upregulation of dACE2 by IFNα and IFNβ, respectively, while full length ACE2 expression was almost unchanged. JAK inhibitor ruxolitinib ablated STAT1 and dACE2 expression after interferon treatment. Finally, with RNA-seq, we identified a set of genes, largely immune-related, induced by cytokine treatment. These gene expression profiles provide new insights into cytokine response of proximal tubule cells.

scholarly journals Comprehensive analysis and genome-wide association studies of biomass, chlorophyll, seed and salinity tolerance related traits in rice highlight genetic hotspots for crop improvement

2020 ◽  
Author(s):  
Md Nafis Ul Alam ◽  
G.M. Nurnabi Azad Jewel ◽  
Tomalika Azim ◽  
Zeba I. Seraj
Keyword(s):  
Candidate Genes ◽  
Sequence Data ◽  
Expression Profiles ◽  
Association Studies ◽  
Crop Improvement ◽  
Gene Expression Profiles ◽  
Fixed Effect Model ◽  
Specific Gene ◽  
Genome Wide Association Studies ◽  
Multiple Trait

AbstractFarmland is on the decline and worldwide food security is at risk. Rice is the staple of choice for over half the Earth’s people. To sustain current demands and ascertain a food secure future, substandard farmland affected by abiotic stresses must be utilized. For rapid crop improvement, a broader understanding of polygenic traits like stress tolerance and crop yield is indispensable. To this end, the hidden diversity of resilient and neglected wild varieties must be traced back to their genetic roots. In this study, we separately assayed 15 phenotypes in a panel of 176 diverse accessions predominantly comprised of local landraces from Bangladesh. We compiled high resolution sequence data for these accessions. We collectively studied the ties between the observed phenotypic differences and the examined additive genetic effects underlying these variations. We applied a sophisticated fixed effect model to associate phenotypes with genotypes on a genomic scale. Discovered QTLs were mapped to known genes. Candidate genes were sorted by tissue specific gene expression profiles and protein level consequence of existing polymorphisms. Our explorations yielded 17 QTLs related to various traits in multiple trait classes. 12 identified QTLs were equivalent to findings from previous studies. Integrative analysis assumes novel functionality for 21 candidate genes on multiple evidence levels. These findings will usher novel avenues for the bioengineering of high yielding crops of the future fortified with genetic defenses against abiotic stressors.

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