RNA-Seq dataset of thoracic ganglia transcriptome across four ovarian development stages in Fenneropenaeus merguiensis

Yodsawat, Prasert; Nuanpirom, Jiratchaya; Sathapondecha, Ponsit; Sangket, Unitsa

doi:10.1016/j.dib.2021.107053

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…The dataset consists of a read counts table and a sample information table. The read counts table was generated from Raw RNA-Seq reads, which must be previously checked for quality control ( Yodsawat et al, 2021 ). The read counts table contains the transcript names in the first column.…”

Section: Methodsmentioning

confidence: 99%

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bestDEG: a web-based application automatically combines various tools to precisely predict differentially expressed genes (DEGs) from RNA-Seq data

Sangket

Yodsawat

Nuanpirom

et al. 2022

PeerJ

Self Cite

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Background Differential gene expression analysis using RNA sequencing technology (RNA-Seq) has become the most popular technique in transcriptome research. Although many R packages have been developed to analyze differentially expressed genes (DEGs), several evaluations have shown that no single DEG analysis method outperforms all others. The validity of DEG identification could be increased by using multiple methods and producing the consensus results. However, DEG analysis methods are complex and most of them require prior knowledge of a programming language or command-line shell. Users who do not have this knowledge need to invest time and effort to acquire it. Methods We developed a novel web application called “bestDEG” to automatically analyze DEGs with different tools and compare the results. A differential expression (DE) analysis pipeline was created combining the edgeR, DESeq2, NOISeq, and EBSeq packages; selected because they use different statistical methods to identify DEGs. bestDEG was evaluated on human datasets from the MicroArray Quality Control (MAQC) project. Results The performance of the bestDEG web application with the human datasets showed excellent results, and the consensus method outperformed the other DE analysis methods in terms of precision (94.71%) and specificity (97.01%). bestDEG is a rapid and efficient tool to analyze DEGs. With bestDEG, users can select DE analysis methods and parameters in the user-friendly web interface. bestDEG also provides a Venn diagram and a table of results. Moreover, the consensus method of this tool can maximize the precision or minimize the false discovery rate (FDR), which reduces the cost of gene expression validation by minimizing wet-lab experiments.

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Section: Methodsmentioning

confidence: 99%

“…The three main steps in identifying DEGs are read mapping, statistical treatment, and DEG searching. Before read mapping can be started, the RNA-Seq dataset must be validated ( Yodsawat et al, 2021 ). RNA-seq expression data can be analyzed by a number of different statistical procedures.…”

Section: Introductionmentioning

confidence: 99%

bestDEG: a web-based application automatically combines various tools to precisely predict differentially expressed genes (DEGs) from RNA-Seq data

Sangket

Yodsawat

Nuanpirom

et al. 2022

PeerJ

Self Cite

View full text Add to dashboard Cite

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Transcriptome profiling of gonad-stimulating factors in thoracic ganglia and a potential role of Indian hedgehog gene in vitellogenesis of banana shrimp Fenneropenaeus merguiensis

Nuanpirom,

Suksri,

Yodsawat

et al. 2023

Comparative Biochemistry and Physiology Part D: Genomics and Pr

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Transcriptome analysis of gonads and brain of giant freshwater prawn (Macrobrachium rosenbergii): screening and validation of genes related to germ cell development

et al. 2022

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Macrobrachium rosenbergii is an important cultured shrimp worldwide, and its precocious puberty has led to serious economic losses. Although reproductive sterilization can avoid this problem, little is known about the molecular mechanisms underlying gonadal development and gametogenesis in M. rosenbergii. Here, we conducted transcriptome analysis of the ovaries, testes, and male/female brain tissues of M. rosenbergii to discover germ cell development-related genes. A total of 60,607 unigenes were identified, of which 20,963 unigenes could be functionally annotated. Eighteen candidate genes were identified by Venn diagram analysis, keyword, and known marker search, followed by elimination of low-expression and repetitive genes. Subsequent real-time quantitative reverse transcription polymerase chain reaction and in situ hybridization identified five genes (RAD51, vasa, SPDS, MRR, and Fem-1C) associated with germ cell development—RAD51, vasa, and SPDS were expressed in both male and female gonads, whereas Fem-1C was specifically expressed in the ovary and MRR in the testis. In the ovary, vasa, SPDS, and Fem-1C were mainly expressed in stage 1–3 oocytes, while RAD51 was expressed in stage 2–3 oocytes. In testis, vasa were significantly expressed in spermatogonia and primary spermatocytes, whereas RAD51 and SPDS were only enriched in spermatogonia and MRR in vas deferens. Our research indicates that these five genes are important germ cell development-related genes, of which RAD51, SPDS, and Fem-1C were proven to function in germ cells of this species for the first time. The discovery of these genes could help develop molecular breeding techniques to overcome precocious puberty in M. rosenbergii.

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RNA-Seq dataset of thoracic ganglia transcriptome across four ovarian development stages in Fenneropenaeus merguiensis

Cited by 3 publications

References 7 publications

bestDEG: a web-based application automatically combines various tools to precisely predict differentially expressed genes (DEGs) from RNA-Seq data

bestDEG: a web-based application automatically combines various tools to precisely predict differentially expressed genes (DEGs) from RNA-Seq data

Transcriptome profiling of gonad-stimulating factors in thoracic ganglia and a potential role of Indian hedgehog gene in vitellogenesis of banana shrimp Fenneropenaeus merguiensis

Transcriptome analysis of gonads and brain of giant freshwater prawn (Macrobrachium rosenbergii): screening and validation of genes related to germ cell development

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