scholarly journals Long-Term Impact of Chemical and Alternative Fungicides Applied to Grapevine cv Nebbiolo on Berry Transcriptome

2020 ◽  
Vol 21 (17) ◽  
pp. 6067
Author(s):  
Raffaella Balestrini ◽  
Stefano Ghignone ◽  
Gabriela Quiroga ◽  
Valentina Fiorilli ◽  
Irene Romano ◽  
...  

Viticulture is one of the horticultural systems in which antifungal treatments can be extremely frequent, with substantial economic and environmental costs. New products, such as biofungicides, resistance inducers and biostimulants, may represent alternative crop protection strategies respectful of the environmental sustainability and food safety. Here, the main purpose was to evaluate the systemic molecular modifications induced by biocontrol products as laminarin, resistance inducers (i.e., fosetyl-Al and potassium phosphonate), electrolyzed water and a standard chemical fungicide (i.e., metiram), on the transcriptomic profile of ‘Nebbiolo’ grape berries at harvest. In addition to a validation of the sequencing data through real-time polymerase chain reaction (PCR), for the first-time the expression of some candidate genes in different cell-types of berry skin (i.e., epidermal and hypodermal layers) was evaluated using the laser microdissection approach. Results showed that several considered antifungal treatments do not strongly affect the berry transcriptome profile at the end of season. Although some treatments do not activate long lasting molecular defense priming features in berry, some compounds appear to be more active in long-term responses. In addition, genes differentially expressed in the two-cell type populations forming the berry skin were found, suggesting a different function for the two-cell type populations.

Molecules ◽  
2021 ◽  
Vol 26 (7) ◽  
pp. 1818
Author(s):  
Francisco Hernández-Aparicio ◽  
Purificación Lisón ◽  
Ismael Rodrigo ◽  
José María Bellés ◽  
M. Pilar López-Gresa

New strategies of control need to be developed with the aim of economic and environmental sustainability in plant and crop protection. Metabolomics is an excellent platform for both understanding the complex plant–pathogen interactions and unraveling new chemical control strategies. GC-MS-based metabolomics, along with a phytohormone analysis of a compatible and incompatible interaction between tomato plants and Fusarium oxysporum f. sp. lycopersici, revealed the specific volatile chemical composition and the plant signals associated with them. The susceptible tomato plants were characterized by the over-emission of methyl- and ethyl-salicylate as well as some fatty acid derivatives, along with an activation of salicylic acid and abscisic acid signaling. In contrast, terpenoids, benzenoids, and 2-ethylhexanoic acid were differentially emitted by plants undergoing an incompatible interaction, together with the activation of the jasmonic acid (JA) pathway. In accordance with this response, a higher expression of several genes participating in the biosynthesis of these volatiles, such as MTS1, TomloxC,TomloxD, and AOS, as well as JAZ7, a JA marker gene, was found to be induced by the fungus in these resistant plants. The characterized metabolome of the immune tomato plants could lead to the development of new resistance inducers against Fusarium wilt treatment.


2021 ◽  
Author(s):  
Shahzad Hussain ◽  
Tanveer Ahmad ◽  
Syed Jawad Hussain Shahzad

Abstract We examine the relationship between financial inclusion and carbon emissions. For this purpose, we develop a composite indicator of financial inclusion based on a broad set of attributes through principal component analysis (PCA) for 26 countries in the Asia region. Our robust panel regression analysis reveals a significant positive long-term impact of financial inclusion on carbon emissions. The pairwise causality test reveals unidirectional long-term causality running from financial inclusion to carbon emissions. The study suggests that policy makers may design policies that integrate accessible financial systems into climate change adaptation strategies in order to neutralize the side effect of financial inclusion deteriorating environmental quality and inclusive sustainable economic growth. JEL ClassificationO16; O44, Q54


2021 ◽  
Author(s):  
Yun Zhang ◽  
Brian Aevermann ◽  
Rohan Gala ◽  
Richard H. Scheuermann

Reference cell type atlases powered by single cell transcriptomic profiling technologies have become available to study cellular diversity at a granular level. We present FR-Match for matching query datasets to reference atlases with robust and accurate performance for identifying novel cell types and non-optimally clustered cell types in the query data. This approach shows excellent performance for cross-platform, cross-sample type, cross-tissue region, and cross-data modality cell type matching.


Blood ◽  
1959 ◽  
Vol 14 (7) ◽  
pp. 803-815 ◽  
Author(s):  
JOHN H. BROOKE ◽  
EDWIN E. OSGOOD

Abstract New culture strains containing humman hemic cells of monocytic, lymphocytic, granulocytic, plasmocytic and erythrocytic series are described with suggestions as to maintenance of the desired cell series in culture. The addition of cells from lymphocytic, plasmocytic and erythrocytic series to a previously well established culture has made possible long-term culture of these cell types, since this procedure aids in maintaining the necessary high gradient factor for their growth and multiplication. Although the life span of these cells has been considerably shortened in culture and immature forms predominate, the cells show recognizable characteristics of the cell series of origin. A high population density must be maintained in cultivation of the mixed cultures or the desired cell type may be lost.


Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3296-3296
Author(s):  
Raul Teruel Montoya ◽  
Xianguo Kong ◽  
Shaji Abraham ◽  
Lin Ma ◽  
Leonard C. Edelstein ◽  
...  

Abstract Abstract 3296 Genetic modification of hematopoietic stem cells (HSCs) has the potential to benefit acquired and congenital hematological disorders. Despite the use of so-called “tissue-specific” promoters to drive expression of the desired transgene, off-target (and consequent deleterious) effects have been observed. MicroRNAs (miRNAs) are important regulators of gene expression. They associate with Argonaute proteins and most typically target 3'UTRs, where complementary base-pairing results in repressed gene expression via RNA decay and translation inhibition. Most miRNAs are ubiquitously expressed, and although some are claimed to be “tissue specific,” such claims have generally not been rigorously validated. The long-term goal of this work is identifying “cell preferential” miRNA expression that could be exploited in expression vectors to minimize off-target transgene expression in HSCs. Initially, total RNA was extracted with Trizol from the megakaryocyte and T-lymphocyte cell lines, Meg-01 and Jurkat, and miRNAs were profiled by Nanostring technology (Nanostring Technologies, Denver, CO). MiR-495 was determined to be highly expressed in Meg-01 and very low in Jurkat cells. A luciferase reporter construct was generated with four canonical binding sites for miR-495 in the 3'UTR and transfected into both cell lines. Compared to control vector without miR-495 binding sites, luciferase expression showed a 50% reduction in Meg-01 cells, but no knock down in Jurkat cells. These experiments indicated that different levels of endogenous miRNA levels can regulate transgene expression through a novel design in the 3'UTR. We next turned our attention to human hematopoietic cells. We reasoned that the long-term goal of minimal off-target transgene expression in HSCs would require knowledge of miRNAs that had little or no detectable expression (“selectively reduced [SR]”) in one cell type and were highly expressed in other cell types. In this manner, the transgene expression would be dampened only in the non-target cells. As a surrogate for bone marrow progenitors and as proof of principle, we used primary cells in normal human peripheral blood. T-cells, B-cells, platelets and granulocytes were purified by density centrifugation followed by immunoselection from five healthy human donors. Flow cytometry using membrane specific markers demonstrate >97% purity of each specific cell preparation. Total RNA was extracted and miRNAs were profiled as above. First, we identified 277 miRNAs that were differentially expressed between any pair of cell types (p-value<0.05 by ANOVA). Second, we performed ranked pair-wise comparisons across all cell types to determine SR miRNAs. This analysis revealed 5 platelet SR-miRNAs, 6 B-cell SR-miRNAs, 2 T-cell SR-miRNAs and 4 granulocyte SR-miRNAs. Lastly, we considered which of these 17 SR-miRNAs would be the best single SR-miRNA within and across cell types. SR-miRNAs were normalized to let-7b, a miRNA we determined to be equivalently expressed across all cell types, and hence, an ideal normalizer. Lineage-specific SR-miRNAs were selected based on extremely low expression in only one cell type and highest fold change of expression compared to the other cell types. The best SR-miRNAs were miR-29b (SR in platelets), miR-125a-5p (SR in B-cells) and miR-146a (SR in granulocytes). The SR expression levels of these 3 miRNAs were validated by qRT-PCR. Our analysis identified no good SR-miRNAs in T-cells. On-going experiments are testing the selective effects of the SR miRNAs in lentiviral vector infection of cord blood CD34+ cells differentiated along specific lineages. In summary, we have demonstrated in hematopoietic cell lines that SR endogenous miRNAs can regulate the expression of transgenes via tandem arrangement of their target sites in the 3'UTR. Additionally, we have identified miRNAs that are specifically expressed at a very low level in one blood cell type and at high levels in other cell types. These miRNAs could potentially be utilized as new biological tools in gene therapy for hematological disorders to restrict transgene expression and avoid the negative consequences of off-target expression. Disclosures: No relevant conflicts of interest to declare.


2021 ◽  
Author(s):  
Daniel Osorio ◽  
Marieke Lydia Kuijjer ◽  
James J. Cai

Motivation: Characterizing cells with rare molecular phenotypes is one of the promises of high throughput single-cell RNA sequencing (scRNA-seq) techniques. However, collecting enough cells with the desired molecular phenotype in a single experiment is challenging, requiring several samples preprocessing steps to filter and collect the desired cells experimentally before sequencing. Data integration of multiple public single-cell experiments stands as a solution for this problem, allowing the collection of enough cells exhibiting the desired molecular signatures. By increasing the sample size of the desired cell type, this approach enables a robust cell type transcriptome characterization. Results: Here, we introduce rPanglaoDB, an R package to download and merge the uniformly processed and annotated scRNA-seq data provided by the PanglaoDB database. To show the potential of rPanglaoDB for collecting rare cell types by integrating multiple public datasets, we present a biological application collecting and characterizing a set of 157 fibrocytes. Fibrocytes are a rare monocyte-derived cell type, that exhibits both the inflammatory features of macrophages and the tissue remodeling properties of fibroblasts. This constitutes the first fibrocytes' unbiased transcriptome profile report. We compared the transcriptomic profile of the fibrocytes against the fibroblasts collected from the same tissue samples and confirm their associated relationship with healing processes in tissue damage and infection through the activation of the prostaglandin biosynthesis and regulation pathway. Availability and Implementation: rPanglaoDB is implemented as an R package available through the CRAN repositories https://CRAN.R-project.org/package=rPanglaoDB.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Daniel E. Russ ◽  
Ryan B. Patterson Cross ◽  
Li Li ◽  
Stephanie C. Koch ◽  
Kaya J. E. Matson ◽  
...  

AbstractSingle-cell RNA sequencing data can unveil the molecular diversity of cell types. Cell type atlases of the mouse spinal cord have been published in recent years but have not been integrated together. Here, we generate an atlas of spinal cell types based on single-cell transcriptomic data, unifying the available datasets into a common reference framework. We report a hierarchical structure of postnatal cell type relationships, with location providing the highest level of organization, then neurotransmitter status, family, and finally, dozens of refined populations. We validate a combinatorial marker code for each neuronal cell type and map their spatial distributions in the adult spinal cord. We also show complex lineage relationships among postnatal cell types. Additionally, we develop an open-source cell type classifier, SeqSeek, to facilitate the standardization of cell type identification. This work provides an integrated view of spinal cell types, their gene expression signatures, and their molecular organization.


2021 ◽  
Author(s):  
Sergio Andreu-Sanchez ◽  
Geraldine Aubert ◽  
Aida Ripoll-Cladellas ◽  
Sandra Henkelman ◽  
Daria V. Zhernakova ◽  
...  

The average length of telomere repeats (TL) declines with age and is considered to be a marker of biological ageing. Here, we measured TL in six blood cell types from 1,046 individuals using the clinically validated Flow-FISH method. We identified remarkable cell-type-specific variations in TL. Host genetics, environmental, parental and intrinsic factors such as sex, parental age, and smoking are associated to variations in TL. By analysing the genome-wide methylation patterns, we identified that the association of maternal, but not paternal, age to TL is mediated by epigenetics. Coupling these measurements to single-cell RNA-sequencing data for 62 participants revealed differential gene expression in T-cells. Genes negatively associated with TL were enriched for pathways related to translation and nonsense-mediated decay. Altogether, this study addresses cell-type-specific differences in telomere biology and its relation to cell-type-specific gene expression and highlights how perinatal factors play a role in determining TL, on top of genetics and lifestyle.


2021 ◽  
Author(s):  
Dongshunyi Li ◽  
Jun Ding ◽  
Ziv Bar-Joseph

One of the first steps in the analysis of single cell RNA-Sequencing data (scRNA-Seq) is the assignment of cell types. While a number of supervised methods have been developed for this, in most cases such assignment is performed by first clustering cells in low-dimensional space and then assigning cell types to different clusters. To overcome noise and to improve cell type assignments we developed UNIFAN, a neural network method that simultaneously clusters and annotates cells using known gene sets. UNIFAN combines both, low dimension representation for all genes and cell specific gene set activity scores to determine the clustering. We applied UNIFAN to human and mouse scRNA-Seq datasets from several different organs. As we show, by using knowledge on gene sets, UNIFAN greatly outperforms prior methods developed for clustering scRNA-Seq data. The gene sets assigned by UNIFAN to different clusters provide strong evidence for the cell type that is represented by this cluster making annotations easier.


GigaScience ◽  
2020 ◽  
Vol 9 (8) ◽  
Author(s):  
Andre Macedo ◽  
Alisson M Gontijo

ABSTRACT Background The human body is made up of hundreds—perhaps thousands—of cell types and states, most of which are currently inaccessible genetically. Intersectional genetic approaches can increase the number of genetically accessible cells, but the scope and safety of these approaches have not been systematically assessed. A typical intersectional method acts like an “AND" logic gate by converting the input of 2 or more active, yet unspecific, regulatory elements (REs) into a single cell type specific synthetic output. Results Here, we systematically assessed the intersectional genetics landscape of the human genome using a subset of cells from a large RE usage atlas (Functional ANnoTation Of the Mammalian genome 5 consortium, FANTOM5) obtained by cap analysis of gene expression sequencing (CAGE-seq). We developed the heuristics and algorithms to retrieve and quality-rank “AND" gate intersections. Of the 154 primary cell types surveyed, &gt;90% can be distinguished from each other with as few as 3 to 4 active REs, with quantifiable safety and robustness. We call these minimal intersections of active REs with cell-type diagnostic potential “versatile entry codes" (VEnCodes). Each of the 158 cancer cell types surveyed could also be distinguished from the healthy primary cell types with small VEnCodes, most of which were robust to intra- and interindividual variation. Methods for the cross-validation of CAGE-seq–derived VEnCodes and for the extraction of VEnCodes from pooled single-cell sequencing data are also presented. Conclusions Our work provides a systematic view of the intersectional genetics landscape in humans and demonstrates the potential of these approaches for future gene delivery technologies.


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