Abstract
Recent advances in next generation sequencing have dramatically reduced the cost of whole transcriptome sequencing to measure differential gene expression. Extreme physical performances ...represent a unique model for investigating the combined effects of oxidative stress and eccentric muscle contraction on systemic skeletal muscle injury outcomes. Studying changes in whole transcriptome RNA expression may allow identification of specific potential treatment targets for a variety of disease states associated with chronic inflammation and oxidative stress. The purpose of this study was to investigate changes in whole transcriptome RNA expression in response to prolonged endurance running. The protocols were approved by the University IRB committee (in accordance with the latest Declaration of Helsinki) and subjects gave written informed consent to participate. Blood samples were collected in PAXgene RNA tubes at baseline, 4-h, and 24-h after performing a half-marathon race. After collection, tubes were frozen and total RNA was extracted and verified using accepted methods. RNAseq analysis was conducted using an Illumina NextSeq 500 sequencing platform. RNAseq analysis revealed distinct changes in injury, inflammation, anti-oxidant defense, and stress-associated RNA expression with responses appearing more pronounced at 24-h compared to 4-h post-race. These results confirm the systemic changes that occur following whole-body exercise-induced muscle injury in a human model. The next step in this research is to test potential therapeutic strategies to determine their effectiveness on altering the changes in the transcriptome.
Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and ...trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.
Genome‐, transcriptome‐ and proteome‐wide measurements provide insights into how biological systems are regulated. However, fundamental aspects relating to which human proteins exist, where they are ...expressed and in which quantities are not fully understood. Therefore, we generated a quantitative proteome and transcriptome abundance atlas of 29 paired healthy human tissues from the Human Protein Atlas project representing human genes by 18,072 transcripts and 13,640 proteins including 37 without prior protein‐level evidence. The analysis revealed that hundreds of proteins, particularly in testis, could not be detected even for highly expressed mRNAs, that few proteins show tissue‐specific expression, that strong differences between mRNA and protein quantities within and across tissues exist and that protein expression is often more stable across tissues than that of transcripts. Only 238 of 9,848 amino acid variants found by exome sequencing could be confidently detected at the protein level showing that proteogenomics remains challenging, needs better computational methods and requires rigorous validation. Many uses of this resource can be envisaged including the study of gene/protein expression regulation and biomarker specificity evaluation.
Synopsis
Proteome and transcriptome quantification across tissues reveals which human genes exist as transcripts and proteins, where they are expressed and in which approximate quantities. Tissue‐specific protein expression is found to be a rare and quantitative rather than qualitative characteristic.
The study presents the most comprehensive atlas of protein expression to date, across 29 healthy human tissues.
Protein level evidence is provided for 13,640 genes and 15,257 isoforms, including 37 missing proteins.
Tissue‐specific protein expression is rare and quantitative rather than qualitative characteristic.
Proteogenomics is still challenging and needs rigorous validation by synthetic peptides.
Proteome and transcriptome quantification across tissues reveals which human genes exist as transcripts and proteins, where they are expressed and in which approximate quantities. Tissue‐specific protein expression is found to be a rare and quantitative rather than qualitative characteristic.
Single-cell sequencing technologies, including transcriptomic and epigenomic assays, are transforming our understanding of the cellular building blocks of neural circuits. By directly measuring ...multiple molecular signatures in thousands to millions of individual cells, single-cell sequencing methods can comprehensively characterize the diversity of brain cell types. These measurements uncover gene regulatory mechanisms that shape cellular identity and provide insight into developmental and evolutionary relationships between brain cell populations. Single-cell sequencing data can aid the design of tools for targeted functional studies of brain circuit components, linking molecular signatures with anatomy, connectivity, morphology, and physiology. Here, we discuss the fundamental principles of single-cell transcriptome and epigenome sequencing, integrative computational analysis of the data, and key applications in neuroscience.
Summary
Soluble sugars, organic acids and volatiles are important components that determine unique fruit flavor and consumer preferences. However, the metabolic dynamics and underlying regulatory ...networks that modulate overall flavor formation during fruit development and ripening remain largely unknown for most fruit species.
In this study, by integrating flavor‐associated metabolism and transcriptome data from 12 fruit developmental and ripening stages of Actinidia chinensis cv Hongyang, we generated a global map of changes in the flavor‐related metabolites throughout development and ripening of kiwifruit.
Using this dataset, we constructed complex regulatory networks allowing to identify key structural genes and transcription factors that regulate the metabolism of soluble sugars, organic acids and important volatiles in kiwifruit. Moreover, our study revealed the regulatory mechanism involving key transcription factors regulating flavor metabolism. The modulation of flavor metabolism by the identified key transcription factors was confirmed in different kiwifruit species providing the proof of concept that our dataset provides a suitable tool for clarification of the regulatory factors controlling flavor biosynthetic pathways that have not been previously illuminated.
Overall, in addition to providing new insight into the metabolic regulation of flavor during fruit development and ripening, the outcome of our study establishes a foundation for flavor improvement in kiwifruit.
See also the Commentary on this article by Fernie & Alseekh, 233: 8–10.
The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome from single cells is transforming our understanding of cell biology in health and disease. In less than a ...decade, the field has seen tremendous technological revolutions that enable crucial new insights into the interplay between intracellular and intercellular molecular mechanisms that govern development, physiology and pathogenesis. In this Review, we highlight advances in the fast-developing field of single-cell and spatial multi-omics technologies (also known as multimodal omics approaches), and the computational strategies needed to integrate information across these molecular layers. We demonstrate their impact on fundamental cell biology and translational research, discuss current challenges and provide an outlook to the future.
Hematopoietic stem cells (HSCs) first emerge in the embryonic aorta-gonad-mesonephros (AGM) region. Studies of model organisms defined intersecting signaling pathways that converge to promote HSC ...emergence predominantly in the ventral domain of the dorsal aorta. Much less is known about mechanisms driving HSC development in humans. Here, to identify secreted signals underlying human HSC development, we combined spatial transcriptomics analysis of dorsoventral polarized signaling in the aorta with gene expression profiling of sorted cell populations and single cells. Our analysis revealed a subset of aortic endothelial cells with a downregulated arterial signature and a predicted lineage relationship with the emerging HSC/progenitor population. Analysis of the ventrally polarized molecular landscape identified endothelin 1 as an important secreted regulator of human HSC development. The obtained gene expression datasets will inform future studies on mechanisms of HSC development in vivo and on generation of clinically relevant HSCs in vitro.
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•Spatial transcriptome profiling of the human HSC developmental niche•Characterization of an HSC precursor population at single-cell resolution•Cardiac EGF pathway is ventrally enriched next to developing IAHCs/HSCs•Ventrally secreted endothelin promotes development of HSCs
Crosse et al. combined spatial, population, and single-cell transcriptomics to interrogate signaling in the human hematopoietic stem cell (HSC) embryonic niche. They identified secreted proteins proximal to the site of HSC emergence, including endothelins, which, they demonstrated, can promote hematopoiesis in mouse and human.
The possibility of generating large RNA-sequencing datasets has led to development of various reference-based and de novo transcriptome assemblers with their own strengths and limitations. While ...reference-based tools are widely used in various transcriptomic studies, their application is limited to the organisms with finished and well-annotated genomes. De novo transcriptome reconstruction from short reads remains an open challenging problem, which is complicated by the varying expression levels across different genes, alternative splicing, and paralogous genes.
Herein we describe the novel transcriptome assembler rnaSPAdes, which has been developed on top of the SPAdes genome assembler and explores computational parallels between assembly of transcriptomes and single-cell genomes. We also present quality assessment reports for rnaSPAdes assemblies, compare it with modern transcriptome assembly tools using several evaluation approaches on various RNA-sequencing datasets, and briefly highlight strong and weak points of different assemblers.
Based on the performed comparison between different assembly methods, we infer that it is not possible to detect the absolute leader according to all quality metrics and all used datasets. However, rnaSPAdes typically outperforms other assemblers by such important property as the number of assembled genes and isoforms, and at the same time has higher accuracy statistics on average comparing to the closest competitors.
Aquaculture is an important economic activity for food production all around the world that has experienced an exponential growth during the last few decades. However, several weaknesses and ...bottlenecks still need to be addressed in order to improve the aquaculture productive system. The recent fast development of the omics technologies has provided scientists with meaningful tools to elucidate the molecular basis of their research interests. This reprint compiles different works about the use of transcriptomics and genomics technologies in different aspects of the aquaculture research, such as immunity, stress response, development, sexual dimorphism, among others, in a variety of fish and shellfish, and even in turtles. Different transcriptome (mRNAs and non-coding RNAs (ncRNAs)), genome (Single Nucleotide Polymorphisms (SNPs)), and metatranscriptome analyses were conducted to unravel those different aspects of interest.
Current methods for spatial transcriptomics are limited by low spatial resolution. Here we introduce a method that integrates spatial gene expression data with histological image data from the same ...tissue section to infer higher-resolution expression maps. Using a deep generative model, our method characterizes the transcriptome of micrometer-scale anatomical features and can predict spatial gene expression from histology images alone.
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