Spaceflight Induces Novel Regulatory Responses in Arabidopsis Seedling as Revealed by Combined Proteomic and Transcriptomic Analyses

Abstract Background: Understanding of gravity sensing and response is critical to long-term human habitation in space and can provide new advantages for terrestrial agriculture. To this end, the altered gene expression profile induced by microgravity has been repeatedly queried by microarray and RNA-seq experiments to understand gravitropism. However, the quantification of altered protein abundance in space has been minimally investigated. Results: Proteomic (iTRAQ-labelled LC-MS/MS) and transcriptomic (RNA-seq) analyses simultaneously quantified protein and transcript differential expression of three-day old, etiolated Arabidopsis thaliana seedlings grown aboard the International Space Station along with their ground control counterparts. Protein extracts were fractionated to isolate soluble and membrane proteins and analyzed to detect differentially phosphorylated peptides. In total, 968 RNAs, 107 soluble proteins, and 103 membrane proteins were identified as differentially expressed. In addition, the proteomic analyses identified 16 differential phosphorylation events. Proteomic data delivered novel insights and simultaneously provided new context to previously made observations of gene expression in microgravity. There is a sweeping shift in post-transcriptional mechanisms of gene regulation including RNA-decapping protein DCP5, the splicing factors GRP7 and GRP8, and AGO4,. These data also indicate AHA2 and FERONIA as well as CESA1 and SHOU4 as central to the cell wall adaptations seen in spaceflight. Patterns of tubulin-a 1, 3,4 and 6 phosphorylation further reveal an interaction of microtubule and redox homeostasis that mirrors osmotic response signaling elements. The absence of gravity also results in a seemingly wasteful dysregulation of plastid gene transcription. Conclusions: The datasets gathered from Arabidopsis seedlings exposed to microgravity revealed marked impacts on post-transcriptional regulation, cell wall synthesis, redox/microtubule dynamics, and plastid gene transcription. The impact of post-transcriptional regulatory alterations represents an unstudied element of the plant microgravity response with the potential to significantly impact plant growth efficiency and beyond. What’s more, addressing the effects of microgravity on AHA2, CESA1, and alpha tubulins has the potential to enhance cytoskeletal organization and cell wall composition, thereby enhancing biomass production and growth in microgravity. Finally, understanding and manipulating the dysregulation of plastid gene transcription has further potential to address the goal of enhancing plant growth in the stressful conditions of microgravity.

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Spaceflight Induces Novel Regulatory Responses in Arabidopsis Seedling as Revealed by Combined Proteomic and Transcriptomic Analyses

10.21203/rs.2.21481/v1 ◽

2020 ◽

Author(s):

Colin Peter Singer Kruse ◽

Alexander D Meyers ◽

Proma Basu ◽

Sarahann Hutchinson ◽

Darron R Luesse ◽

...

Keyword(s):

Gene Expression ◽

Cell Wall ◽

Membrane Proteins ◽

Plant Growth ◽

Gene Transcription ◽

Space Station ◽

Growth Efficiency ◽

Rna Seq ◽

Plastid Gene ◽

The Impact

Abstract Background: Understanding of gravity sensing and response is critical to long-term human habitation in space and can provide new advantages for terrestrial agriculture. To this end, the altered gene expression profile induced by microgravity has been repeatedly queried by microarray and RNA-seq experiments to understand gravitropism. However, the quantification of altered protein abundance in space has been minimally investigated.Results: Proteomic (iTRAQ-labelled LC-MS/MS) and transcriptomic (RNA-seq) analyses simultaneously quantified protein and transcript differential expression of three-day old, etiolated Arabidopsis thaliana seedlings grown aboard the International Space Station along with their ground control counterparts. Protein extracts were fractionated to isolate soluble and membrane proteins and analyzed to detect differentially phosphorylated peptides. In total, 968 RNAs, 107 soluble proteins, and 103 membrane proteins were identified as differentially expressed. In addition, the proteomic analyses identified 16 differential phosphorylation events. Proteomic data delivered novel insights and simultaneously provided new context to previously made observations of gene expression in microgravity. There is a sweeping shift in post-transcriptional mechanisms of gene regulation including RNA-decapping protein DCP5, the splicing factors GRP7 and GRP8, and AGO4. These data also indicate AHA2 and FERONIA as well as CESA1 and SHOU4 as central to the cell wall adaptations seen in spaceflight. Patterns of tubulin-a 1, 3,4 and 6 phosphorylation further reveal an interaction of microtubule and redox homeostasis that mirrors osmotic response signaling elements. The absence of gravity also results in a seemingly wasteful dysregulation of plastid gene transcription. Conclusions: The datasets gathered from Arabidopsis seedlings exposed to microgravity revealed marked impacts on post-transcriptional regulation, cell wall synthesis, redox/microtubule dynamics, and plastid gene transcription. The impact of post-transcriptional regulatory alterations represents an unstudied element of the plant microgravity response with the potential to significantly impact plant growth efficiency and beyond. What’s more, addressing the effects of microgravity on AHA2, CESA1, and alpha tubulins has the potential to enhance cytoskeletal organization and cell wall composition, thereby enhancing biomass production and growth in microgravity. Finally, understanding and manipulating the dysregulation of plastid gene transcription has further potential to address the goal of enhancing plant growth in the stressful conditions of microgravity.

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Impact of RNA-seq data analysis algorithms on gene expression estimation and downstream prediction

Scientific Reports ◽

10.1038/s41598-020-74567-y ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Li Tong ◽

◽

Po-Yen Wu ◽

John H. Phan ◽

Hamid R. Hassazadeh ◽

...

Keyword(s):

Gene Expression ◽

Data Analysis ◽

Disease Outcome ◽

Rna Seq ◽

Next Generation Sequencing Technology ◽

Normalization Methods ◽

The Us ◽

Sequencing Quality ◽

Improved Accuracy ◽

The Impact

Abstract To use next-generation sequencing technology such as RNA-seq for medical and health applications, choosing proper analysis methods for biomarker identification remains a critical challenge for most users. The US Food and Drug Administration (FDA) has led the Sequencing Quality Control (SEQC) project to conduct a comprehensive investigation of 278 representative RNA-seq data analysis pipelines consisting of 13 sequence mapping, three quantification, and seven normalization methods. In this article, we focused on the impact of the joint effects of RNA-seq pipelines on gene expression estimation as well as the downstream prediction of disease outcomes. First, we developed and applied three metrics (i.e., accuracy, precision, and reliability) to quantitatively evaluate each pipeline’s performance on gene expression estimation. We then investigated the correlation between the proposed metrics and the downstream prediction performance using two real-world cancer datasets (i.e., SEQC neuroblastoma dataset and the NIH/NCI TCGA lung adenocarcinoma dataset). We found that RNA-seq pipeline components jointly and significantly impacted the accuracy of gene expression estimation, and its impact was extended to the downstream prediction of these cancer outcomes. Specifically, RNA-seq pipelines that produced more accurate, precise, and reliable gene expression estimation tended to perform better in the prediction of disease outcome. In the end, we provided scenarios as guidelines for users to use these three metrics to select sensible RNA-seq pipelines for the improved accuracy, precision, and reliability of gene expression estimation, which lead to the improved downstream gene expression-based prediction of disease outcome.

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Comparative Transcriptomic Signature of the Simulated Microgravity Response in Caenorhabditis elegans

10.1101/531335 ◽

2019 ◽

Author(s):

İrem Çelen ◽

Aroshan Jayasinghe ◽

Jung H. Doh ◽

Chandran R. Sabanayagam

Keyword(s):

Caenorhabditis Elegans ◽

Simulated Microgravity ◽

Space Station ◽

Integrative Approach ◽

Biological Processes ◽

Rna Seq ◽

Transcriptomic Response ◽

Transcriptomic Signature ◽

Ground Conditions ◽

The Impact

AbstractBackgroundGiven the growing interest in human exploration of space, it is crucial to identify the effect of space conditions on biological processes. The International Space Station (ISS) greatly helps researchers determine these effects. However, the impact of the ISS-introduced potential confounders (e.g., the combination of radiation and microgravity exposures) on the biological processes are often neglected, and separate investigations are needed to uncover the impact of individual conditions.ResultsHere, we analyze the transcriptomic response of Caenorhabditis elegans to simulated microgravity and observe the maintained transcriptomic response after return to ground conditions for four, eight, and twelve days. Through the integration of our data with those in NASA GeneLab, we identify the gravitome, which we define as microgravity-responsive transcriptomic signatures. We show that 75% of the simulated microgravity-induced changes on gene expression persist after return to ground conditions for four days while most of these changes are reverted after twelve days return to ground conditions. Our results from integrative RNA-seq and mass spectrometry analyses suggest that simulated microgravity affects longevity regulating insulin/IGF-1 and sphingolipid signaling pathways.ConclusionsOur results address the sole impact of simulated microgravity on transcriptome by controlling for the other space-introduced conditions and utilizing RNA-seq. Using an integrative approach, we identify a conserved transcriptomic signature to microgravity and its sustained impact after return to the ground. Moreover, we present the effect of simulated microgravity on distinct ceramide profiles. Overall, this work can provide insights into the sole effect of microgravity on biological systems.

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Acquisition of VanB‐type vancomycin resistance by Bacillus subtilis: the impact on gene expression, cell wall composition and morphology

Molecular Microbiology ◽

10.1111/j.1365-2958.2011.07684.x ◽

2011 ◽

Vol 81 (1) ◽

pp. 157-178 ◽

Cited By ~ 17

Author(s):

Paola Bisicchia ◽

Nhat Khai Bui ◽

Christine Aldridge ◽

Waldemar Vollmer ◽

Kevin M. Devine

Keyword(s):

Gene Expression ◽

Cell Wall ◽

Bacillus Subtilis ◽

Vancomycin Resistance ◽

Cell Wall Composition ◽

The Impact

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Full Length Transcriptome Highlights the Coordination of Plastid Transcript Processing

10.20944/preprints202108.0571.v1 ◽

2021 ◽

Author(s):

Marine Guilcher ◽

Arnaud Liehrmann ◽

Chloé Seyman ◽

Thomas Blein ◽

Guillem Rigaill ◽

...

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Full Length ◽

Nanopore Sequencing ◽

Rna Seq ◽

Plastid Gene ◽

Plastid Gene Expression ◽

Short Read ◽

Transcript Processing

Plastid gene expression involves many post-transcriptional maturation steps resulting in a complex transcriptome composed of multiple isoforms. Although short read RNA-seq has considerably improved our understanding of the molecular mechanisms controlling these processes, it is unable to sequence full-length transcripts. This information is however crucial when it comes to understand the interplay between the various steps of plastid gene expression. Here, the study of the Arabidopsis leaf plastid transcriptome using Nanopore sequencing showed that many splicing and editing events were not independent but co-occurring. For a given transcript, maturation events also appeared to be chronologically ordered with splicing happening after most sites are edited.

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Robust normalization and transformation techniques for constructing gene coexpression networks from RNA-seq data

Genome Biology ◽

10.1186/s13059-021-02568-9 ◽

2022 ◽

Vol 23 (1) ◽

Author(s):

Kayla A. Johnson ◽

Arjun Krishnan

Keyword(s):

Gene Expression ◽

Expression Data ◽

Rna Seq ◽

Functional Relationships ◽

Gene Coexpression ◽

Transformation Methods ◽

Network Transformation ◽

Almost All ◽

Coexpression Networks ◽

The Impact

Abstract Background Constructing gene coexpression networks is a powerful approach for analyzing high-throughput gene expression data towards module identification, gene function prediction, and disease-gene prioritization. While optimal workflows for constructing coexpression networks, including good choices for data pre-processing, normalization, and network transformation, have been developed for microarray-based expression data, such well-tested choices do not exist for RNA-seq data. Almost all studies that compare data processing and normalization methods for RNA-seq focus on the end goal of determining differential gene expression. Results Here, we present a comprehensive benchmarking and analysis of 36 different workflows, each with a unique set of normalization and network transformation methods, for constructing coexpression networks from RNA-seq datasets. We test these workflows on both large, homogenous datasets and small, heterogeneous datasets from various labs. We analyze the workflows in terms of aggregate performance, individual method choices, and the impact of multiple dataset experimental factors. Our results demonstrate that between-sample normalization has the biggest impact, with counts adjusted by size factors producing networks that most accurately recapitulate known tissue-naive and tissue-aware gene functional relationships. Conclusions Based on this work, we provide concrete recommendations on robust procedures for building an accurate coexpression network from an RNA-seq dataset. In addition, researchers can examine all the results in great detail at https://krishnanlab.github.io/RNAseq_coexpression to make appropriate choices for coexpression analysis based on the experimental factors of their RNA-seq dataset.

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Exogenous proanthocyanidins improve tolerance of Cu-toxicity by amelioration of oxidative damage and re-programming of gene expression in Medicago sativa

PLoS ONE ◽

10.1371/journal.pone.0259100 ◽

2021 ◽

Vol 16 (10) ◽

pp. e0259100

Author(s):

Siyi Zhao ◽

Yanqiao Zhu ◽

Wenwen Liu ◽

Xiaoshan Wang ◽

Han Wang ◽

...

Keyword(s):

Oxidative Stress ◽

Cell Wall ◽

Ascorbic Acid ◽

Plant Growth ◽

Medicago Sativa ◽

Agricultural Practices ◽

Cell Wall Synthesis ◽

Genes Encoding ◽

Stress Damage ◽

The Impact

Excess copper (Cu) in soil due to industrial and agricultural practices can result in reduced plant growth. Excess Cu resulted in severely retarded root growth with severe discoloration of Alfalfa (Medicago sativa) and Medicago truncatula. Growth in the presence of hydrogen peroxide resulted in similar symptoms that could be partially recovered by the addition of the reductant ascorbic acid revealing damage was likely due to oxidative stress. The addition of proanthocyanidins (PAs) in the presence of Cu prevented much of the damage, including plant growth and restoration of lignin synthesis which was inhibited in the presence of excess Cu. Transcriptome analyses of the impact of excess Cu and the amelioration after PAs treatment revealed that changes were enriched in functions associated with the cell wall and extracellular processes, indicating that inhibition of cell wall synthesis was likely the reason for retarded growth. Excess Cu appeared to induce a strong defense response, along with alterations in the expression of a number of genes encoding transcription factors, notably related to ethylene signaling. The addition of PAs greatly reduced this response, and also induced novel genes that likely help ameliorate the effects of excess Cu. These included induction of genes involved in the last step of ascorbic acid biosynthesis and of enzymes involved in cell wall synthesis. Combined, these results show that excess Cu causes severe oxidative stress damage and inhibition of cell wall synthesis, which can be relieved by the addition of PAs.

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Impacts of Nitrogen Deficiency on Wheat (Triticum aestivum L.) Grain During the Medium Filling Stage: Transcriptomic and Metabolomic Comparisons

Frontiers in Plant Science ◽

10.3389/fpls.2021.674433 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yanjie Wang ◽

Demei Wang ◽

Zhiqiang Tao ◽

Yushuang Yang ◽

Zhenxian Gao ◽

...

Keyword(s):

Triticum Aestivum ◽

Cell Wall ◽

Grain Yield ◽

Seedling Stage ◽

Sugar Accumulation ◽

Grain Protein ◽

Rna Seq ◽

Filling Stage ◽

N Deficiency ◽

The Impact

Nitrogen (N) supplementation is essential to the yield and quality of bread wheat (Triticum aestivum L.). The impact of N-deficiency on wheat at the seedling stage has been previously reported, but the impact of distinct N regimes applied at the seedling stage with continuous application on filling and maturing wheat grains is lesser known, despite the filling stage being critical for final grain yield and flour quality. Here, we compared phenotype characteristics such as grain yield, grain protein and sugar quality, plant growth, leaf photosynthesis of wheat under N-deficient and N-sufficient conditions imposed prior to sowing (120 kg/hm2) and in the jointing stage (120 kg/hm2), and then evaluated the effects of this continued stress through RNA-seq and GC-MS metabolomics profiling of grain at the mid-filling stage. The results showed that except for an increase in grain size and weight, and in the content of total sugar, starch, and fiber in bran fraction and white flour, the other metrics were all decreased under N-deficiency conditions. A total of 761 differentially expressed genes (DEGs) and 77 differentially accumulated metabolites (DAMs) were identified. Under N-deficiency, 51 down-regulated DEGs were involved in the process of impeding chlorophyll synthesis, chloroplast development, light harvesting, and electron transfer functions of photosystem, which resulted in the SPAD and Pn value decreased by 32 and 15.2% compared with N-sufficiency, inhibited photosynthesis. Twenty-four DEGs implicated the inhibition of amino acids synthesis and protein transport, in agreement with a 17–42% reduction in ornithine, cysteine, aspartate, and tyrosine from metabolome, and an 18.6% reduction in grain protein content. However, 14 DEGs were implicated in promoting sugar accumulation in the cell wall and another six DEGs also enhanced cell wall synthesis, which significantly increased fiber content in the endosperm and likely contributed to increasing the thousands-grain weight (TGW). Moreover, RNA-seq profiling suggested that wheat grain can improve the capacity of DNA repair, iron uptake, disease and abiotic stress resistance, and oxidative stress scavenging through increasing the content levels of anthocyanin, flavonoid, GABA, galactose, and glucose under N-deficiency condition. This study identified candidate genes and metabolites related to low N adaption and tolerance that may provide new insights into a comprehensive understanding of the genotype-specific differences in performance under N-deficiency conditions.

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Association of novel rare coding variants with juvenile idiopathic arthritis

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-218359 ◽

2021 ◽

pp. annrheumdis-2020-218359

Author(s):

Xinyi Meng ◽

Xiaoyuan Hou ◽

Ping Wang ◽

Joseph T Glessner ◽

Hui-Qi Qu ◽

...

Keyword(s):

Gene Expression ◽

Juvenile Idiopathic Arthritis ◽

Autoimmune Diseases ◽

Rare Variants ◽

Variant Calling ◽

Rna Seq ◽

Common Variants ◽

Association Analyses ◽

Coding Variants ◽

The Impact

ObjectiveJuvenile idiopathic arthritis (JIA) is the most common type of arthritis among children, but a few studies have investigated the contribution of rare variants to JIA. In this study, we aimed to identify rare coding variants associated with JIA for the genome-wide landscape.MethodsWe established a rare variant calling and filtering pipeline and performed rare coding variant and gene-based association analyses on three RNA-seq datasets composed of 228 JIA patients in the Gene Expression Omnibus against different sets of controls, and further conducted replication in our whole-exome sequencing (WES) data of 56 JIA patients. Then we conducted differential gene expression analysis and assessed the impact of recurrent functional coding variants on gene expression and signalling pathway.ResultsBy the RNA-seq data, we identified variants in two genes reported in literature as JIA causal variants, as well as additional 63 recurrent rare coding variants seen only in JIA patients. Among the 44 recurrent rare variants found in polyarticular patients, 10 were replicated by our WES of patients with the same JIA subtype. Several genes with recurrent functional rare coding variants have also common variants associated with autoimmune diseases. We observed immune pathways enriched for the genes with rare coding variants and differentially expressed genes.ConclusionThis study elucidated a novel landscape of recurrent rare coding variants in JIA patients and uncovered significant associations with JIA at the gene pathway level. The convergence of common variants and rare variants for autoimmune diseases is also highlighted in this study.

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The Oviductal Extracellular Vesicles’ RNA Cargo Regulates the Bovine Embryonic Transcriptome

International Journal of Molecular Sciences ◽

10.3390/ijms21041303 ◽

2020 ◽

Vol 21 (4) ◽

pp. 1303 ◽

Cited By ~ 7

Author(s):

Stefan Bauersachs ◽

Pascal Mermillod ◽

Carmen Almiñana

Keyword(s):

Gene Expression ◽

Extracellular Vesicles ◽

Sequencing Analysis ◽

Rna Seq ◽

High Throughput Analysis ◽

Positive Effects ◽

Early Embryos ◽

And Control ◽

The Impact

Oviductal extracellular vesicles (oEVs) are emerging as key players in the gamete/embryo–oviduct interactions that contribute to successful pregnancy. Various positive effects of oEVs on gametes and early embryos have been found in vitro. To determine whether these effects are associated with changes of embryonic gene expression, the transcriptomes of embryos supplemented with bovine fresh (FeEVs) or frozen (FoEVs) oEVs during in vitro culture compared to controls without oEVs were analyzed by low-input RNA sequencing. Analysis of RNA-seq data revealed 221 differentially expressed genes (DEGs) between FoEV treatment and control, 67 DEGs for FeEV and FoEV treatments, and minor differences between FeEV treatment and control (28 DEGs). An integrative analysis of mRNAs and miRNAs contained in oEVs obtained in a previous study with embryonic mRNA alterations pointed to direct effects of oEV cargo on embryos (1) by increasing the concentration of delivered transcripts; (2) by translating delivered mRNAs to proteins that regulate embryonic gene expression; and (3) by oEV-derived miRNAs which downregulate embryonic mRNAs or modify gene expression in other ways. Our study provided the first high-throughput analysis of the embryonic transcriptome regulated by oEVs, increasing our knowledge on the impact of oEVs on the embryo and revealing the oEV RNA components that potentially regulate embryonic development.

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