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Selection and Validation of Reliable Reference Genes for Gene Expression Studies in Different Genotypes and TRV-Infected Fruits of Peach (Prunus persica L. Batsch) during Ripening.
Xu, Z, Dai, J, Su, W, Wu, H, Shah, K, Xing, L, Ma, J, Zhang, D, Zhao, C
Genes. 2022;(1)
Abstract
Real-time quantitative PCR (RT-qPCR) is a powerful tool to detect and quantify transcription abundance, and the stability of the reference gene determines its success. However, the most suitable reference gene for different genotypes and tobacco rattle virus (TRV) infected fruits was unclear in peach (Prunus persica L. Batsch). In this study, 10 reference genes were selected and gene expression was characterized by RT-qPCR across all samples, including different genotypes and TRV-infected fruits during ripening. Four statistical algorithms (geNorm, NormFinder, BestKeeper, and RefFinder) were used to calculate the stability of 10 reference genes. The geNorm analysis indicated that two suitable reference genes should be used for gene expression normalization. In general, the best combination of reference genes was CYP2 and Tua5 for TRV-infected fruits and CYP2 and Tub1 for different genotypes. In 18S, GADPH, and TEF2, there is an unacceptable variability of gene expression in all experimental conditions. Furthermore, to confirm the validity of the reference genes, the expression levels of PpACO1, PpEIN2, and PpPL were normalized at different fruit storage periods. In summary, our results provide guidelines for selecting reliable reference genes in different genotypes and TRV-infected fruits and lay the foundation for accurate evaluation of gene expression for RT-qPCR analysis in peach.
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MicroRNA expression profiles analysis of apheresis platelets treated with vitamin B2 and ultraviolet-B during storage.
Ye, H, Xu, H, Qiao, M, Guo, R, Ji, Y, Yu, Y, Chen, Y, Gai, X, Li, H, Liu, Q, et al
Transfusion and apheresis science : official journal of the World Apheresis Association : official journal of the European Society for Haemapheresis. 2021;(3):103079
Abstract
Whether platelet (PLT) microRNA (miRNA) profiles are affected by pathogen reduction technology (PRT) using vitamin B2 and ultraviolet-B (VB2-PRT) remains unclear. Samples from VB2-PRT-treated (experimental group, E_) and untreated (control group, C_) apheresis PLTs were taken on days 1, 3 and 5 of storage, designated as E_1, E_3, E_5, C_1, C_3 and C_5, respectively. The miRNA expression profiles were assessed by DNA Nano Ball (DNB) sequencing technology, and verified by quantitive real-time fluorescence quantitative PCR (qRT-PCR). Compared with the expression profiles of PLT miRNAs, 3895 miRNAs were identified in the E_ groups while 4106 were in the C_ groups. There were 487 significant differentially expressed miRNAs in E_1 vs C_1 group, including 220 upregulated and 287 downregulated, such as miR-146a-5p and let-7b-5p. There were 908 significant differentially expressed miRNAs in E_3 vs C_3 group, including 297 upregulated and 611 downregulated, such as miR-142-5p and miR-7-5p. There were 229 significant differentially expressed miRNAs in E_5 vs C_5 group, including 80 upregulated and 149 downregulated, such as miR-3529-3p and miR-451a. These differentially expressed miRNAs had been suggested to have functional roles in energy homeostasis, cell communication, proliferation, migration and apoptosis. GO analysis showed a significant enrichmen in relevant biological process categories as receptor activity, signal transduction, cell transport, motility and chemotaxis. The significantly enriched KEGG pathway of predicted target genes was Glycosaminoglycan biosynthesis in E_ vs C_ groups. These new observation could provide insights on the understanding of change of miRNA profiles of PLT treated with VB2-PRT.
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A non-radioactive, improved PAR-CLIP and small RNA cDNA library preparation protocol.
Anastasakis, DG, Jacob, A, Konstantinidou, P, Meguro, K, Claypool, D, Cekan, P, Haase, AD, Hafner, M
Nucleic acids research. 2021;(8):e45
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Abstract
Crosslinking and immunoprecipitation (CLIP) methods are powerful techniques to interrogate direct protein-RNA interactions and dissect posttranscriptional gene regulatory networks. One widely used CLIP variant is photoactivatable ribonucleoside enhanced CLIP (PAR-CLIP) that involves in vivo labeling of nascent RNAs with the photoreactive nucleosides 4-thiouridine (4SU) or 6-thioguanosine (6SG), which can efficiently crosslink to interacting proteins using UVA and UVB light. Crosslinking of 4SU or 6SG to interacting amino acids changes their base-pairing properties and results in characteristic mutations in cDNA libraries prepared for high-throughput sequencing, which can be computationally exploited to remove abundant background from non-crosslinked sequences and help pinpoint RNA binding protein binding sites at nucleotide resolution on a transcriptome-wide scale. Here we present a streamlined protocol for fluorescence-based PAR-CLIP (fPAR-CLIP) that eliminates the need to use radioactivity. It is based on direct ligation of a fluorescently labeled adapter to the 3'end of crosslinked RNA on immobilized ribonucleoproteins, followed by isolation of the adapter-ligated RNA and efficient conversion into cDNA without the previously needed size fractionation on denaturing polyacrylamide gels. These improvements cut the experimentation by half to 2 days and increases sensitivity by 10-100-fold.
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A comparison of metabolic labeling and statistical methods to infer genome-wide dynamics of RNA turnover.
Boileau, E, Altmüller, J, Naarmann-de Vries, IS, Dieterich, C
Briefings in bioinformatics. 2021;(6)
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Abstract
Metabolic labeling of newly transcribed RNAs coupled with RNA-seq is being increasingly used for genome-wide analysis of RNA dynamics. Methods including standard biochemical enrichment and recent nucleotide conversion protocols each require special experimental and computational treatment. Despite their immediate relevance, these technologies have not yet been assessed and benchmarked, and no data are currently available to advance reproducible research and the development of better inference tools. Here, we present a systematic evaluation and comparison of four RNA labeling protocols: 4sU-tagging biochemical enrichment, including spike-in RNA controls, SLAM-seq, TimeLapse-seq and TUC-seq. All protocols are evaluated based on practical considerations, conversion efficiency and wet lab requirements to handle hazardous substances. We also compute decay rate estimates and confidence intervals for each protocol using two alternative statistical frameworks, pulseR and GRAND-SLAM, for over 11 600 human genes and evaluate the underlying computational workflows for their robustness and ease of use. Overall, we demonstrate a high inter-method reliability across eight use case scenarios. Our results and data will facilitate reproducible research and serve as a resource contributing to a fuller understanding of RNA biology.
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EpiPanGI Dx: A Cell-free DNA Methylation Fingerprint for the Early Detection of Gastrointestinal Cancers.
Kandimalla, R, Xu, J, Link, A, Matsuyama, T, Yamamura, K, Parker, MI, Uetake, H, Balaguer, F, Borazanci, E, Tsai, S, et al
Clinical cancer research : an official journal of the American Association for Cancer Research. 2021;(22):6135-6144
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Abstract
PURPOSE DNA methylation alterations have emerged as front-runners in cell-free DNA (cfDNA) biomarker development. However, much effort to date has focused on single cancers. In this context, gastrointestinal (GI) cancers constitute the second leading cause of cancer-related deaths worldwide; yet there is no blood-based assay for the early detection and population screening of GI cancers. EXPERIMENTAL DESIGN Herein, we performed a genome-wide DNA methylation analysis of multiple GI cancers to develop a pan-GI diagnostic assay. By analyzing DNA methylation data from 1,781 tumor and adjacent normal tissues, we first identified differentially methylated regions (DMR) between individual GI cancers and adjacent normal, as well as across GI cancers. We next prioritized a list of 67,832 tissue DMRs by incorporating all significant DMRs across various GI cancers to design a custom, targeted bisulfite sequencing platform. We subsequently validated these tissue-specific DMRs in 300 cfDNA specimens and applied machine learning algorithms to develop three distinct categories of DMR panels RESULTS We identified three distinct DMR panels: (i) cancer-specific biomarker panels with AUC values of 0.98 (colorectal cancer), 0.98 (hepatocellular carcinoma), 0.94 (esophageal squamous cell carcinoma), 0.90 (gastric cancer), 0.90 (esophageal adenocarcinoma), and 0.85 (pancreatic ductal adenocarcinoma); (ii) a pan-GI panel that detected all GI cancers with an AUC of 0.88; and (iii) a multi-cancer (tissue of origin) prediction panel, EpiPanGI Dx, with a prediction accuracy of 0.85-0.95 for most GI cancers. CONCLUSIONS Using a novel biomarker discovery approach, we provide the first evidence for a cfDNA methylation assay that offers robust diagnostic accuracy for GI cancers.
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Transcriptomics View over the Germination Landscape in Biofortified Rice.
Dueñas, CJ, Slamet-Loedin, I, Macovei, A
Genes. 2021;(12)
Abstract
Hidden hunger, or micronutrient deficiency, is a worldwide problem. Several approaches are employed to alleviate its effects (e.g., promoting diet diversity, use of dietary supplements, chemical fortification of processed food), and among these, biofortification is considered as one of the most cost-effective and highly sustainable. Rice is one of the best targets for biofortification since it is a staple food for almost half of the world's population as a high-energy source but with low nutritional value. Multiple biofortified rice lines have been produced during the past decades, while few studies also reported modifications in germination behavior (in terms of enhanced or decreased germination percentage or speed). It is important to underline that rapid, uniform germination, and seedling establishment are essential prerequisites for crop productivity. Combining the two traits, biofortified, highly-nutritious seeds with improved germination behavior can be envisaged as a highly-desired target for rice breeding. To this purpose, information gathered from transcriptomics studies can reveal useful insights to unveil the molecular players governing both traits. The present review aims to provide an overview of transcriptomics studies applied at the crossroad between biofortification and seed germination, pointing out potential candidates for trait pyramiding.
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Molecular Mechanism of Lipid Accumulation and Metabolism of Oleaginous Chlorococcum sphacosum GD from Soil under Salt Stress.
Su, H, Feng, J, Lv, J, Liu, Q, Nan, F, Liu, X, Xie, S
International journal of molecular sciences. 2021;(3)
Abstract
The oleaginous microalgae species Chlorococcum sphacosum GD is a promising feedstock for biodiesel production from soil. However, its metabolic mechanism of lipid production remains unclear. In this study, the lipid accumulation and metabolism mechanisms of Chlorococcum sphacosum GD were analyzed under salt stress based on transcriptome sequencing. The biomass and lipid content of the alga strain were determined under different NaCl concentrations, and total RNA from fresh cells were isolated and sequenced by HiSeq 2000 high throughput sequencing technology. As the salt concentration increased in culture medium, the algal lipid content increased but the biomass decreased. Following transcriptome sequencing by assembly and splicing, 24,128 unigenes were annotated, with read lengths mostly distributed in the 200-300 bp interval. Statistically significant differentially expressed unigenes were observed in different experimental groups, with 2051 up-regulated genes and 1835 down-regulated genes. The lipid metabolism pathway analysis showed that, under salt stress, gene-related fatty acid biosynthesis (ACCase, KASII, KAR, HAD, FATA) was significantly up-regulated, but some gene-related fatty acid degradation was significantly down-regulated. The comprehensive results showed that salt concentration can affect the lipid accumulation and metabolism of C. sphacosum GD, and the lipid accumulation is closely related to the fatty acid synthesis pathway.
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Molecular diagnosis of polycystic ovary syndrome in obese and non-obese women by targeted plasma miRNA profiling.
Romero-Ruiz, A, Pineda, B, Ovelleiro, D, Perdices-Lopez, C, Torres, E, Vazquez, MJ, Guler, I, Jiménez, Á, Pineda, R, Persano, M, et al
European journal of endocrinology. 2021;(5):637-652
Abstract
OBJECTIVE Polycystic ovary syndrome (PCOS) is diagnosed based on the clinical signs, but its presentation is heterogeneous and potentially confounded by concurrent conditions, such as obesity and insulin resistance. miRNA have recently emerged as putative pathophysiological and diagnostic factors in PCOS. However, no reliable miRNA-based method for molecular diagnosis of PCOS has been reported. The aim of this study was to develop a tool for accurate diagnosis of PCOS by targeted miRNA profiling of plasma samples, defined on the basis of unbiased biomarker-finding analyses and biostatistical tools. METHODS A case-control PCOS cohort was cross-sectionally studied, including 170 women classified into four groups: non-PCOS/lean, non-PCOS/obese, PCOS/lean, and PCOS/obese women. High-throughput miRNA analyses were performed in plasma, using NanoString technology and a 800 human miRNA panel, followed by targeted quantitative real-timePCR validation. Statistics were applied to define optimal normalization methods, identify deregulated biomarker miRNAs, and build classification algorithms, considering PCOS and obesity as major categories. RESULTS The geometric mean of circulating hsa-miR-103a-3p, hsa-miR-125a-5p, and hsa-miR-1976, selected among 125 unchanged miRNAs, was defined as optimal reference for internal normalization (named mR3-method). Ten miRNAs were identified and validated after mR3-normalization as differentially expressed across the groups. Multinomial least absolute shrinkage and selection operator regression and decision-tree models were built to reliably discriminate PCOS vs non-PCOS, either in obese or non-obese women, using subsets of these miRNAs as performers. CONCLUSIONS We define herein a robust method for molecular classification of PCOS based on unbiased identification of miRNA biomarkers and decision-tree protocols. This method allows not only reliable diagnosis of non-obese women with PCOS but also discrimination between PCOS and obesity. CAPSULE We define a novel protocol, based on plasma miRNA profiling, for molecular diagnosis of PCOS. This tool not only allows proper discrimination of the condition in non-obese women but also permits distinction between PCOS and obesity, which often display overlapping clinical presentations.
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Precise regulation of the relative rates of surface area and volume synthesis in bacterial cells growing in dynamic environments.
Shi, H, Hu, Y, Odermatt, PD, Gonzalez, CG, Zhang, L, Elias, JE, Chang, F, Huang, KC
Nature communications. 2021;(1):1975
Abstract
The steady-state size of bacterial cells correlates with nutrient-determined growth rate. Here, we explore how rod-shaped bacterial cells regulate their morphology during rapid environmental changes. We quantify cellular dimensions throughout passage cycles of stationary-phase cells diluted into fresh medium and grown back to saturation. We find that cells exhibit characteristic dynamics in surface area to volume ratio (SA/V), which are conserved across genetic and chemical perturbations as well as across species and growth temperatures. A mathematical model with a single fitting parameter (the time delay between surface and volume synthesis) is quantitatively consistent with our SA/V experimental observations. The model supports that this time delay is due to differential expression of volume and surface-related genes, and that the first division after dilution occurs at a tightly controlled SA/V. Our minimal model thus provides insight into the connections between bacterial growth rate and cell shape in dynamic environments.
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Spatiotemporal Gene Expression Profiling and Network Inference: A Roadmap for Analysis, Visualization, and Key Gene Identification.
Spurney, R, Schwartz, M, Gobble, M, Sozzani, R, Van den Broeck, L
Methods in molecular biology (Clifton, N.J.). 2021;:47-65
Abstract
Gene expression data analysis and the prediction of causal relationships within gene regulatory networks (GRNs) have guided the identification of key regulatory factors and unraveled the dynamic properties of biological systems. However, drawing accurate and unbiased conclusions requires a comprehensive understanding of relevant tools, computational methods, and their workflows. The topics covered in this chapter encompass the entire workflow for GRN inference including: (1) experimental design; (2) RNA sequencing data processing; (3) differentially expressed gene (DEG) selection; (4) clustering prior to inference; (5) network inference techniques; and (6) network visualization and analysis. Moreover, this chapter aims to present a workflow feasible and accessible for plant biologists without a bioinformatics or computer science background. To address this need, TuxNet, a user-friendly graphical user interface that integrates RNA sequencing data analysis with GRN inference, is chosen for the purpose of providing a detailed tutorial.