scholarly journals Transcriptomics provides a genetic signature of vineyard site with insight into vintage-independent regional wine characteristics

2021 ◽  
Author(s):  
Taylor Reiter ◽  
Rachel Montpetit ◽  
Shelby Byer ◽  
Isadora Frias ◽  
Esmeralda Leon ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Ribosomal Dna ◽  
Transcript Abundance ◽  
Amplicon Sequencing ◽  
Sequencing Data ◽  
Fungal Organisms ◽  
Genetic Signatures ◽  
Insight Into ◽  
Regional Wine ◽  
Grape Musts

In wine fermentations, the metabolic activity of both Saccharomyces cerevisiae and non-Saccharomyces organisms impact wine chemistry. Ribosomal DNA amplicon sequencing of grape musts has demonstrated that microorganisms occur non-randomly and are associated with the vineyard of origin, suggesting a role for the vineyard, grape, and wine microbiome in shaping wine fermentation outcomes. We used ribosomal DNA amplicon sequencing of grape must and RNA sequencing of primary fermentations to profile fermentations from 15 vineyards in California and Oregon across two vintages. We find that the relative abundance of fungal organisms detected by ribosomal DNA amplicon sequencing did not correlate with transcript abundance from those organisms within the RNA sequencing data, suggesting that the majority of the fungi detected in must by ribosomal DNA amplicon sequencing are not active during these inoculated fermentations. Additionally, we detect genetic signatures of vineyard site and region during fermentation that are predictive for each vineyard site, identifying nitrogen, sulfur, and thiamine metabolism as important factors for distinguishing vineyard site and region.

scholarly journals Transcriptomics Provides a Genetic Signature of Vineyard Site and Offers Insight into Vintage-Independent Inoculated Fermentation Outcomes

mSystems ◽  
2021 ◽  
Vol 6 (2) ◽  
Author(s):  
Taylor Reiter ◽  
Rachel Montpetit ◽  
Shelby Byer ◽  
Isadora Frias ◽  
Esmeralda Leon ◽  
...  
Keyword(s):  
Gene Expression ◽  
Saccharomyces Cerevisiae ◽  
Environmental Factors ◽  
Ribosomal Dna ◽  
Amplicon Sequencing ◽  
Content Type ◽  
Genetic Signatures ◽  
Insight Into ◽  
Regional Wine ◽  
Grape Musts

ABSTRACT Ribosomal DNA amplicon sequencing of grape musts has demonstrated that microorganisms occur nonrandomly and are associated with the vineyard of origin, suggesting a role for the vineyard, grape, and wine microbiome in shaping wine fermentation outcomes. Here, ribosomal DNA amplicon sequencing from grape musts and RNA sequencing of eukaryotic transcripts from primary fermentations inoculated with the wine yeast Saccharomyces cerevisiae RC212 were used to profile fermentations from 15 vineyards in California and Oregon across two vintages. These data demonstrate that the relative abundance of fungal organisms detected by ribosomal DNA amplicon sequencing correlated with neither transcript abundance from those same organisms within the RNA sequencing data nor gene expression of the inoculated RC212 yeast strain. These data suggest that the majority of the fungi detected in must by ribosomal DNA amplicon sequencing were not active during the primary stage of these inoculated fermentations and were not a major factor in determining RC212 gene expression. However, unique genetic signatures were detected within the ribosomal DNA amplicon and eukaryotic transcriptomic sequencing that were predictive of vineyard site and region. These signatures included S. cerevisiae gene expression patterns linked to nitrogen, sulfur, and thiamine metabolism. These genetic signatures of site offer insight into specific environmental factors to consider with respect to fermentation outcomes and vineyard site and regional wine characteristics. IMPORTANCE The wine industry generates billions of dollars of revenue annually, and economic productivity is in part associated with regional distinctiveness of wine sensory attributes. Microorganisms associated with grapes and wineries are influenced by region of origin, and given that some microorganisms play a role in fermentation, it is thought that microbes may contribute to the regional distinctiveness of wine. In this work, as in previous studies, it is demonstrated that specific bacteria and fungi are associated with individual wine regions and vineyard sites. However, this work further shows that their presence is not associated with detectable fungal gene expression during the primary fermentation or the expression of specific genes by the inoculate Saccharomyces cerevisiae strain RC212. The detected RC212 gene expression signatures associated with region and vineyard site also allowed the identification of flavor-associated metabolic processes and environmental factors that could impact primary fermentation outcomes. These data offer novel insights into the complexities and subtleties of vineyard-specific inoculated wine fermentation and starting points for future investigations into factors that contribute to regional wine distinctiveness.

scholarly journals RNA Sequencing Data Sets Identifying Differentially Expressed Transcripts during Campylobacter jejuni Biofilm Formation

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Greg Tram ◽  
William P. Klare ◽  
Joel A. Cain ◽  
Basem Mourad ◽  
Stuart J. Cordwell ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Campylobacter Jejuni ◽  
Biofilm Formation ◽  
Foodborne Pathogen ◽  
Data Sets ◽  
Sequencing Data ◽  
Content Type ◽  
Differential Gene ◽  
Insight Into

Campylobacter jejuni is a foodborne pathogen and an important contributor to gastroenteritis in humans. C. jejuni readily forms biofilms which may play a role in the transmission of the pathogen from animals to humans. Herein, we present RNA sequencing data investigating differential gene expression in biofilm and planktonic C. jejuni. These data provide insight into pathways which may be important to biofilm formation in this organism.

scholarly journals Probabilistic outlier identification for RNA sequencing generalized linear models

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Stefano Mangiola ◽  
Evan A Thomas ◽  
Martin Modrák ◽  
Aki Vehtari ◽  
Anthony T Papenfuss
Keyword(s):  
Rna Sequencing ◽  
Large Scale ◽  
Negative Binomial ◽  
Differential Expression Analysis ◽  
Transcript Abundance ◽  
Negative Binomial Model ◽  
Probabilistic Methods ◽  
Binomial Model ◽  
Sequencing Data ◽  
Quality Control Tool

Abstract Relative transcript abundance has proven to be a valuable tool for understanding the function of genes in biological systems. For the differential analysis of transcript abundance using RNA sequencing data, the negative binomial model is by far the most frequently adopted. However, common methods that are based on a negative binomial model are not robust to extreme outliers, which we found to be abundant in public datasets. So far, no rigorous and probabilistic methods for detection of outliers have been developed for RNA sequencing data, leaving the identification mostly to visual inspection. Recent advances in Bayesian computation allow large-scale comparison of observed data against its theoretical distribution given in a statistical model. Here we propose ppcseq, a key quality-control tool for identifying transcripts that include outlier data points in differential expression analysis, which do not follow a negative binomial distribution. Applying ppcseq to analyse several publicly available datasets using popular tools, we show that from 3 to 10 percent of differentially abundant transcripts across algorithms and datasets had statistics inflated by the presence of outliers.

scholarly journals Delayed processing of blood samples impairs the accuracy of mRNA-based biomarkers

2022 ◽  
Author(s):  
Chace Wilson ◽  
Nicolas Dias ◽  
Stefania Pancini ◽  
Vitor Mercadante ◽  
Fernando Biase
Keyword(s):  
Rna Sequencing ◽  
Whole Blood ◽  
Biomarker Discovery ◽  
White Blood Cells ◽  
Transcript Abundance ◽  
Prolonged Storage ◽  
Gene Transcript ◽  
Sequencing Data ◽  
Blood Samples ◽  
Whole Blood Samples

Background: The transcriptome of peripheral white blood cells (PWBCs) contains valuable physiological information, thus making them a prime biological sample for investigating mRNA-based biomarkers. However, prolonged storage of whole blood samples can alter gene transcript abundance in PWBCs, compromising the results of biomarker discovery. Here, we designed an experiment to interrogate the impacts of delayed processing of whole blood samples on gene transcript abundance in PWBCs. We hypothesized that storing blood samples for 24 hours at 4°C would cause RNA degradation resulting in altered transcriptome profiles. Results: We produced RNA-sequencing data for 30 samples collected from five estrus synchronized heifers (Bos taurus). We quantified transcript abundance for 12,414 protein-coding genes in PWBCs. Analysis of parameters of RNA quality revealed no statistically significant differences (P>0.05) between samples collected from the jugular vein and coccygeal vein, as well as among samples processed after one, three, six, or eight hours. However, samples processed after 24 hours of storage had a lower RNA integrity number value (P=0.03) in comparison to those processed after one hour of storage. Next, we analyzed RNA-sequencing data between samples using those processed after one hour of storage as the baseline for comparison. Interestingly, evaluation of 3/5 prime bias revealed no differences between genes with lower transcript abundance in samples stored for 24 hours relative to one hour. In addition, sequencing coverage of transcripts was similar between samples from the 24-hour and one-hour groups. We identified four and 515 genes with differential transcript abundance in samples processed after storage for eight and 24 hours, respectively, relative to samples processed after one hour. Conclusions: The PWBCs respond to prolonged cold storage by increasing genes related to active chromatin compaction which in turn reduces gene transcription. This alteration in transcriptome profiles can impair the accuracy of mRNA-based biomarkers. Therefore, blood samples collected for mRNA-based biomarker discovery should be refrigerated immediately and processed within six hours post sampling.

scholarly journals A primer for generating and using transcriptome data and gene sets

Development ◽  
2020 ◽  
Vol 147 (24) ◽  
pp. dev193854
Author(s):  
Chad Cockrum ◽  
Kiyomi R. Kaneshiro ◽  
Andreas Rechtsteiner ◽  
Tomoko M. Tabuchi ◽  
Susan Strome
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
High Throughput ◽  
Single Cells ◽  
Transcript Abundance ◽  
Specific Gene ◽  
Transcriptome Data ◽  
Sequencing Data ◽  
Gene Sets ◽  
Genome Wide

ABSTRACTTranscriptomic approaches have provided a growing set of powerful tools with which to study genome-wide patterns of gene expression. Rapidly evolving technologies enable analysis of transcript abundance data from particular tissues and even single cells. This Primer discusses methods that can be used to collect and profile RNAs from specific tissues or cells, process and analyze high-throughput RNA-sequencing data, and define sets of genes that accurately represent a category, such as tissue-enriched or tissue-specific gene expression.

scholarly journals Nanopore direct RNA sequencing maps an Arabidopsis N6 methyladenosine epitranscriptome

2019 ◽  
Author(s):  
Matthew T. Parker ◽  
Katarzyna Knop ◽  
Anna V. Sherwood ◽  
Nicholas J. Schurch ◽  
Katarzyna Mackinnon ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Single Molecule ◽  
Tail Length ◽  
Transcript Abundance ◽  
Full Length ◽  
Untranslated Regions ◽  
Transcription Start Sites ◽  
Defective Rna ◽  
A Site ◽  
Insight Into

AbstractUnderstanding genome organization and gene regulation requires insight into RNA transcription, processing and modification. We adapted nanopore direct RNA sequencing to examine RNA from a wild-type accession of the model plant Arabidopsis thaliana and a mutant defective in mRNA methylation (m6A). Here we show that m6A can be mapped in full-length mRNAs transcriptome-wide and reveal the combinatorial diversity of cap-associated transcription start sites, splicing events, poly(A) site choice and poly(A) tail length. Loss of m6A from 3’ untranslated regions is associated with decreased relative transcript abundance and defective RNA 3′ end formation. A functional consequence of disrupted m6A is a lengthening of the circadian period. We conclude that nanopore direct RNA sequencing can reveal the complexity of mRNA processing and modification in full-length single molecule reads. These findings can refine Arabidopsis genome annotation. Further, applying this approach to less well-studied species could transform our understanding of what their genomes encode.

scholarly journals Comparative transcriptome profiling of the human and mouse dorsal root ganglia: An RNA-seq-based resource for pain and sensory neuroscience research

2017 ◽  
Author(s):  
Pradipta Ray ◽  
Andrew Torck ◽  
Lilyana Quigley ◽  
Andi Wangzhou ◽  
Matthew Neiman ◽  
...  
Keyword(s):  
Chronic Pain ◽  
Rna Sequencing ◽  
Dorsal Root Ganglia ◽  
Dorsal Root ◽  
Expression Patterns ◽  
Rna Seq ◽  
Sequencing Data ◽  
Mouse Tissues ◽  
Human And Mouse ◽  
Insight Into

AbstractMolecular neurobiological insight into human nervous tissues is needed to generate next generation therapeutics for neurological disorders like chronic pain. We obtained human Dorsal Root Ganglia (DRG) samples from organ donors and performed RNA-sequencing (RNA-seq) to study the human DRG (hDRG) transcriptional landscape, systematically comparing it with publicly available data from a variety of human and orthologous mouse tissues, including mouse DRG (mDRG). We characterized the hDRG transcriptional profile in terms of tissue-restricted gene co-expression patterns and putative transcriptional regulators, and formulated an information-theoretic framework to quantify DRG enrichment. Our analyses reveal an hDRG-enriched protein-coding gene set (~140), some of which have not been described in the context of DRG or pain signaling. A majority of these show conserved enrichment in mDRG, and were mined for known drug - gene product interactions. Comparison of hDRG and tibial nerve transcriptomes suggest pervasive mRNA transport of sensory neuronal genes to axons in adult hDRG, with potential implications for mechanistic insight into chronic pain in patients. Relevant gene families and pathways were also analyzed, including transcription factors (TFs), g-protein coupled receptors (GCPRs) and ion channels. We present our work as an online, searchable repository (http://www.utdallas.edu/bbs/painneurosciencelab/DRGtranscriptome), creating a valuable resource for the community. Our analyses provide insight into DRG biology for guiding development of novel therapeutics, and a blueprint for cross-species transcriptomic analyses.SummaryWe generated RNA sequencing data from human DRG samples and comprehensively compared this transcriptome to other human tissues and a matching panel of mouse tissues. Our analysis uncovered functionally enriched genes in the human and mouse DRG with important implications for understanding sensory biology and pain drug discovery.

scholarly journals Concordance between RNA-sequencing data and DNA microarray data in transcriptome analysis of proliferative and quiescent fibroblasts

2015 ◽  
Vol 2 (9) ◽  
pp. 150402 ◽  
Author(s):  
Brett Trost ◽  
Catherine A. Moir ◽  
Zoe E. Gillespie ◽  
Anthony Kusalik ◽  
Jennifer A. Mitchell ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Microarray Data ◽  
Dna Microarrays ◽  
Geometric Mean ◽  
Transcript Abundance ◽  
Cdna Libraries ◽  
Rna Seq ◽  
Sequencing Data ◽  
High Throughput Analysis ◽  
Qrt Pcr

DNA microarrays and RNA sequencing (RNA-seq) are major technologies for performing high-throughput analysis of transcript abundance. Recently, concerns have been raised regarding the concordance of data derived from the two techniques. Using cDNA libraries derived from normal human foreskin fibroblasts, we measured changes in transcript abundance as cells transitioned from proliferative growth to quiescence using both DNA microarrays and RNA-seq. The internal reproducibility of the RNA-seq data was greater than that of the microarray data. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarray values were moderate. The two technologies had good agreement when considering probes with the largest (both positive and negative) fold change (FC) values. An independent technique, quantitative reverse-transcription PCR (qRT-PCR), was used to measure the FC of 76 genes between proliferative and quiescent samples, and a higher correlation was observed between the qRT-PCR data and the RNA-seq data than between the qRT-PCR data and the microarray data.

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