High-throughput SNP discovery and transcriptome expression profiles from the salmon louse Caligus rogercresseyi (Copepoda: Caligidae)

Abstract Background High-throughput sequencing (HTS) has been applied successfully for virus and viroid discovery in many agricultural crops leading to the current drive to apply this technology in routine pathogen detection. The validation of HTS-based pathogen detection is therefore paramount. Methods Plant infections were established by graft inoculating a suite of viruses and viroids from established sources for further study. Four plants (one healthy plant and three infected) were sampled in triplicate and total RNA was extracted using two different methods (CTAB extraction protocol and the Zymo Research Quick-RNA Plant Miniprep Kit) and sent for Illumina HTS. One replicate sample of each plant for each RNA extraction method was also sent for HTS on an Ion Torrent platform. The data were evaluated for biological and technical variation focussing on RNA extraction method, platform used and bioinformatic analysis. Results The study evaluated the influence of different HTS protocols on the sensitivity, specificity and repeatability of HTS as a detection tool. Both extraction methods and sequencing platforms resulted in significant differences between the data sets. Using a de novo assembly approach, complemented with read mapping, the Illumina data allowed a greater proportion of the expected pathogen scaffolds to be inferred, and an accurate virome profile was constructed. The complete virome profile was also constructed using the Ion Torrent data but analyses showed that more sequencing depth is required to be comparative to the Illumina protocol and produce consistent results. The CTAB extraction protocol lowered the proportion of viroid sequences recovered with HTS, and the Zymo Research kit resulted in more variation in the read counts obtained per pathogen sequence. The expression profiles of reference genes were also investigated to assess the suitability of these genes as internal controls to allow for the comparison between samples across different protocols. Conclusions This study highlights the need to measure the level of variation that can arise from the different variables of an HTS protocol, from sample preparation to data analysis. HTS is more comprehensive than any assay previously used, but with the necessary validations and standard operating procedures, the implementation of HTS as part of routine pathogen screening practices is possible.

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Pineal gland transcriptomic profiling reveals the differential regulation of lncRNA and mRNA related to prolificacy in STH sheep with two FecB genotypes

BMC Genomic Data ◽

10.1186/s12863-020-00957-w ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Chunyan Li ◽

Xiaoyun He ◽

Zijun Zhang ◽

Chunhuan Ren ◽

Mingxing Chu

Keyword(s):

Pineal Gland ◽

Expression Pattern ◽

Noncoding Rna ◽

Target Genes ◽

Expression Profiles ◽

Enrichment Analysis ◽

Rna Seq ◽

Important Regulator ◽

Gsh Metabolism ◽

Transcriptome Expression

Abstract Background Long noncoding RNA (lncRNA) has been identified as important regulator in hypothalamic-pituitary-ovarian axis associated with sheep prolificacy. However, little is known of their expression pattern and potential roles in the pineal gland of sheep. Herein, RNA-Seq was used to detect transcriptome expression pattern in pineal gland between follicular phase (FP) and luteal phase (LP) in FecBBB (MM) and FecB++ (ww) STH sheep, respectively, and differentially expressed (DE) lncRNAs and mRNAs associated with reproduction were identified. Results Overall, 135 DE lncRNAs and 1360 DE mRNAs in pineal gland between MM and ww sheep were screened. Wherein, 39 DE lncRNAs and 764 DE mRNAs were identified (FP vs LP) in MM sheep, 96 DE lncRNAs and 596 DE mRNAs were identified (FP vs LP) in ww sheep. Moreover, GO and KEGG enrichment analysis indicated that the targets of DE lncRNAs and DE mRNAs were annotated to multiple biological processes such as phototransduction, circadian rhythm, melanogenesis, GSH metabolism and steroid biosynthesis, which directly or indirectly participate in hormone activities to affect sheep reproductive performance. Additionally, co-expression of lncRNAs-mRNAs and the network construction were performed based on correlation analysis, DE lncRNAs can modulate target genes involved in related pathways to affect sheep fecundity. Specifically, XLOC_466330, XLOC_532771, XLOC_028449 targeting RRM2B and GSTK1, XLOC_391199 targeting STMN1, XLOC_503926 targeting RAG2, XLOC_187711 targeting DLG4 were included. Conclusion All of these differential lncRNAs and mRNAs expression profiles in pineal gland provide a novel resource for elucidating regulatory mechanism underlying STH sheep prolificacy.

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High-throughput sequencing of Bacillus anthracis in France: investigating genome diversity and population structure using whole-genome SNP discovery

BMC Genomics ◽

10.1186/1471-2164-15-288 ◽

2014 ◽

Vol 15 (1) ◽

pp. 288 ◽

Cited By ~ 36

Author(s):

Guillaume Girault ◽

Yann Blouin ◽

Gilles Vergnaud ◽

Sylviane Derzelle

Keyword(s):

Population Structure ◽

Bacillus Anthracis ◽

High Throughput ◽

High Throughput Sequencing ◽

Whole Genome ◽

Genome Diversity ◽

Snp Discovery

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P02.10 FocuSCOPE: a single cell, multi-omics solution to simultaneously analyze tumor variants and microenvironment

Journal for ImmunoTherapy of Cancer ◽

10.1136/jitc-2021-itoc8.22 ◽

2021 ◽

Vol 9 (Suppl 1) ◽

pp. A12.1-A12

Author(s):

Y Arjmand Abbassi ◽

N Fang ◽

W Zhu ◽

Y Zhou ◽

Y Chen ◽

...

Keyword(s):

Gene Expression ◽

Tumor Microenvironment ◽

Single Cell ◽

High Throughput ◽

Immune Cells ◽

Genetic Variants ◽

Expression Profiles ◽

Single Cells ◽

Gene Expression Profiles ◽

Single Cell Sequencing

Recent advances of high-throughput single cell sequencing technologies have greatly improved our understanding of the complex biological systems. Heterogeneous samples such as tumor tissues commonly harbor cancer cell-specific genetic variants and gene expression profiles, both of which have been shown to be related to the mechanisms of disease development, progression, and responses to treatment. Furthermore, stromal and immune cells within tumor microenvironment interact with cancer cells to play important roles in tumor responses to systematic therapy such as immunotherapy or cell therapy. However, most current high-throughput single cell sequencing methods detect only gene expression levels or epigenetics events such as chromatin conformation. The information on important genetic variants including mutation or fusion is not captured. To better understand the mechanisms of tumor responses to systematic therapy, it is essential to decipher the connection between genotype and gene expression patterns of both tumor cells and cells in the tumor microenvironment. We developed FocuSCOPE, a high-throughput multi-omics sequencing solution that can detect both genetic variants and transcriptome from same single cells. FocuSCOPE has been used to successfully perform single cell analysis of both gene expression profiles and point mutations, fusion genes, or intracellular viral sequences from thousands of cells simultaneously, delivering comprehensive insights of tumor and immune cells in tumor microenvironment at single cell resolution.Disclosure InformationY. Arjmand Abbassi: None. N. Fang: None. W. Zhu: None. Y. Zhou: None. Y. Chen: None. U. Deutsch: None.

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Network Analysis of Different Exogenous Hormones on the Regulation of Deep Sowing Tolerance in Maize Seedlings

Frontiers in Plant Science ◽

10.3389/fpls.2021.739101 ◽

2021 ◽

Vol 12 ◽

Author(s):

Fenqi Chen ◽

Xiangzhuo Ji ◽

Mingxing Bai ◽

Zelong Zhuang ◽

Yunling Peng

Keyword(s):

Inbred Line ◽

Expression Profiles ◽

Lignin Biosynthesis ◽

Maize Seedlings ◽

Deep Soil ◽

Exogenous Hormones ◽

Mesocotyl Elongation ◽

Gene Modules ◽

Transcriptome Expression ◽

Planting Method

The planting method of deep sowing can make the seeds make full use of water in deep soil, which is considered to be an effective way to respond to drought stress. However, deep sowing will affect the growth and development of maize (Zea mays L.) at seedling stage. To better understand the response of maize to deep sowing stress and the mechanism of exogenous hormones [Gibberellin (GA3), Brassinolide (BR), Strigolactone (SL)] alleviates the damaging effects of deep-sowing stress, the physiological and transcriptome expression profiles of seedlings of deep sowing sensitive inbred line Zi330 and the deep-tolerant inbred line Qi319 were compared under deep sowing stress and the conditions of exogenous hormones alleviates stress. The results showed that mesocotyl elongated significantly after both deep sowing stress and application of exogenous hormones, and its elongation was mainly through elongation and expansion of cell volume. Hormone assays revealed no significant changes in zeatin (ZT) content of the mesocotyl after deep sowing and exogenous hormone application. The endogenous GA3 and auxin (IAA) contents in the mesocotyl of the two inbred lines increased significantly after the addition of exogenous GA3, BR, and SL under deep sowing stress compared to deep sowing stress, while BR and SL decreased significantly. Transcriptome analysis showed that the deep seeding stress was alleviated by GA3, BR, and SLs, the differentially expressed genes (DEGs) mainly included cellulose synthase, expansin and glucanase, oxidase, lignin biosynthesis genes and so on. We also found that protein phosphatase 2C and GA receptor GID1 enhanced the ability of resist deep seeding stress in maize by participating in the abscisic acid (ABA) and the GA signaling pathway, respectively. In addition, we identified two gene modules that were significantly related to mesocotyl elongation, and identified some hub genes that were significantly related to mesocotyl elongation by WGCNA analysis. These genes were mainly involved in transcription regulation, hydrolase activity, protein binding and plasma membrane. Our results from this study may provide theoretical basis for determining the maize deep seeding tolerance and the mechanism by which exogenous hormones regulates deep seeding tolerance.

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INFERRING PROTEIN-PROTEIN INTERACTIONS FROM MESSENGER RNA EXPRESSION PROFILES WITH SVM

Journal of Biological System ◽

10.1142/s0218339005001525 ◽

2005 ◽

Vol 13 (03) ◽

pp. 287-298 ◽

Cited By ~ 1

Author(s):

JUN CAI ◽

YING HUANG ◽

LIANG JI ◽

YANDA LI

Keyword(s):

High Throughput ◽

Protein Interactions ◽

Messenger Rna ◽

Expression Profiles ◽

Support Vector ◽

Svm Classifier ◽

Good Prediction ◽

Protein Protein Interactions ◽

Protein Protein Interaction ◽

High Throughput Experiments

In post-genomic biology, researchers in the field of proteome focus their attention on the networks of protein interactions that control the lives of cells and organisms. Protein-protein interactions play a useful role in dynamic cellular machinery. In this paper, we developed a method to infer protein-protein interactions based on the theory of support vector machine (SVM). For a given pair of proteins, a new strategy of calculating cross-correlation function of mRNA expression profiles was used to encode SVM vectors. We compared the performance with other methods of inferring protein-protein interaction. Results suggested that, through five-fold cross validation, our SVM model achieved a good prediction. It enables us to show that expression profiles in transcription level can be used to distinguish physical or functional interactions of proteins as well as sequence contents. Lastly, we applied our SVM classifier to evaluate data quality of interaction data sets from four high-throughput experiments. The results show that high-throughput experiments sacrifice some accuracy in determination of interactions because of limitation of experiment technologies.

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Microbial single-cell RNA sequencing by split-pool barcoding

Science ◽

10.1126/science.aba5257 ◽

2020 ◽

Vol 371 (6531) ◽

pp. eaba5257 ◽

Cited By ~ 2

Author(s):

Anna Kuchina ◽

Leandra M. Brettner ◽

Luana Paleologu ◽

Charles M. Roco ◽

Alexander B. Rosenberg ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Rna Sequencing ◽

High Throughput ◽

Single Cell Analysis ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Growth Stages ◽

High Throughput Analysis ◽

Single Cell Rna Sequencing

Single-cell RNA sequencing (scRNA-seq) has become an essential tool for characterizing gene expression in eukaryotes, but current methods are incompatible with bacteria. Here, we introduce microSPLiT (microbial split-pool ligation transcriptomics), a high-throughput scRNA-seq method for Gram-negative and Gram-positive bacteria that can resolve heterogeneous transcriptional states. We applied microSPLiT to >25,000 Bacillus subtilis cells sampled at different growth stages, creating an atlas of changes in metabolism and lifestyle. We retrieved detailed gene expression profiles associated with known, but rare, states such as competence and prophage induction and also identified unexpected gene expression states, including the heterogeneous activation of a niche metabolic pathway in a subpopulation of cells. MicroSPLiT paves the way to high-throughput analysis of gene expression in bacterial communities that are otherwise not amenable to single-cell analysis, such as natural microbiota.

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Identification of Exogenous Nitric Oxide-Responsive miRNAs from Alfalfa (Medicago sativa L.) under Drought Stress by High-Throughput Sequencing

Genes ◽

10.3390/genes11010030 ◽

2019 ◽

Vol 11 (1) ◽

pp. 30

Author(s):

Yaodong Zhao ◽

Wenjing Ma ◽

Xiaohong Wei ◽

Yu Long ◽

Ying Zhao ◽

...

Keyword(s):

Nitric Oxide ◽

Drought Stress ◽

Medicago Sativa ◽

High Throughput ◽

Drought Resistance ◽

High Throughput Sequencing ◽

Target Genes ◽

Expression Profiles ◽

Differentially Expressed ◽

Medicago Sativa L

Alfalfa (Medicago sativa L.) is a high quality leguminous forage. Drought stress is one of the main factors that restrict the development of the alfalfa industry. High-throughput sequencing was used to analyze the microRNA (miRNA) profiles of alfalfa plants treated with CK (normal water), PEG (polyethylene glycol-6000; drought stress), and PEG + SNP (sodium nitroprusside; nitric oxide (NO) sprayed externally under drought stress). We identified 90 known miRNAs belonging to 46 families and predicted 177 new miRNAs. Real-time quantitative fluorescent PCR (qRT-PCR) was used to validate high-throughput expression analysis data. A total of 32 (14 known miRNAs and 18 new miRNAs) and 55 (24 known miRNAs and 31 new miRNAs) differentially expressed miRNAs were identified in PEG and PEG + SNP samples. This suggested that exogenous NO can induce more new miRNAs. The differentially expressed miRNA maturation sequences in the two treatment groups were targeted by 86 and 157 potential target genes, separately. The function of target genes was annotated by gene ontology (GO) enrichment and kyoto encyclopedia of genes and genomes (KEGG) analysis. The expression profiles of nine selected miRNAs and their target genes verified that their expression patterns were opposite. This study has documented that analysis of miRNA under PEG and PEG + SNP conditions provides important insights into the improvement of drought resistance of alfalfa by exogenous NO at the molecular level. This has important scientific value and practical significance for the improvement of plant drought resistance by exogenous NO.

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