An RNA-Seq based gene expression atlas of the common bean

Abstract The lakes on the Qinghai-Tibet Plateau (QTP) are the largest and highest lake group in the world. Gymnocypris selincuoensis is the only cyprinid fish living in lake Selincuo, the largest lake on QTP. However, its genetic resource is still blank, limiting studies on molecular and genetic analysis. In this study, the transcriptome of G. selincuoensis was first generated by using PacBio Iso-Seq and Illumina RNA-seq. A full-length (FL) transcriptome with 75,435 transcripts was obtained by Iso-Seq with N50 length of 3,870 bp. Among all transcripts, 75,016 were annotated to public databases, 64,710 contain complete open reading frames and 2,811 were long non-coding RNAs. Based on all- vs.-all BLAST, 2,069 alternative splicing events were detected, and 80% of them were validated by reverse transcription polymerase chain reaction (RT-PCR). Tissue gene expression atlas showed that the number of detected expressed transcripts ranged from 37,397 in brain to 19,914 in muscle, with 10,488 transcripts detected in all seven tissues. Comparative genomic analysis with other cyprinid fishes identified 77 orthologous genes with potential positive selection (Ka/Ks > 0.3). A total of 56,696 perfect simple sequence repeats were identified from FL transcripts. Our results provide valuable genetic resources for further studies on adaptive evolution, gene expression and population genetics in G. selincuoensis and other congeneric fishes.

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Gene expression atlas of fruit ripening and transcriptome assembly from RNA-seq data in octoploid strawberry (Fragaria × ananassa)

Scientific Reports ◽

10.1038/s41598-017-14239-6 ◽

2017 ◽

Vol 7 (1) ◽

Cited By ~ 36

Author(s):

José F. Sánchez-Sevilla ◽

José G. Vallarino ◽

Sonia Osorio ◽

Aureliano Bombarely ◽

David Posé ◽

...

Keyword(s):

Gene Expression ◽

Fruit Ripening ◽

Transcriptome Assembly ◽

Fragaria Ananassa ◽

Rna Seq ◽

Gene Expression Atlas ◽

Expression Atlas

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Melonet-DB, a Grand RNA-Seq Gene Expression Atlas in Melon (Cucumis melo L.)

Plant and Cell Physiology ◽

10.1093/pcp/pcx193 ◽

2017 ◽

Vol 59 (1) ◽

pp. e4-e4 ◽

Cited By ~ 16

Author(s):

Ryoichi Yano ◽

Satoko Nonaka ◽

Hiroshi Ezura

Keyword(s):

Gene Expression ◽

Cucumis Melo ◽

Rna Seq ◽

Gene Expression Atlas ◽

Expression Atlas ◽

Cucumis Melo L

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Elimination of reference mapping bias reveals robust immune related allele-specific expression in crossbred sheep

10.1101/619122 ◽

2019 ◽

Cited By ~ 1

Author(s):

Mazdak Salavati ◽

Stephen J. Bush ◽

Sergio Palma-Vera ◽

Mary E. B. McCulloch ◽

David A. Hume ◽

...

Keyword(s):

Gene Expression ◽

Complex Traits ◽

Allelic Imbalance ◽

Cell Types ◽

Rna Seq ◽

Specific Expression ◽

Allele Specific Expression ◽

Gene Expression Atlas ◽

Expression Atlas ◽

Allele Specific

AbstractPervasive allelic variation at both gene and single nucleotide level (SNV) between individuals is commonly associated with complex traits in humans and animals. Allele-specific expression (ASE) analysis, using RNA-Seq, can provide a detailed annotation of allelic imbalance and infer the existence of cis-acting transcriptional regulation. However, variant detection in RNA-Seq data is compromised by biased mapping of reads to the reference DNA sequence. In this manuscript we describe an unbiased standardised computational pipeline for allele-specific expression analysis using RNA-Seq data, which we have adapted and developed using tools available under open licence. The analysis pipeline we present is designed to minimise reference bias while providing accurate profiling of allele-specific expression across tissues and cell types. Using this methodology, we were able to profile pervasive allelic imbalance across tissues and cell types, at both the gene and SNV level, in Texel x Scottish Blackface sheep, using the sheep gene expression atlas dataset. ASE profiles were pervasive in each sheep and across all tissue types investigated. However, ASE profiles shared across tissues were limited and instead they tended to be highly tissue-specific. These tissue-specific ASE profiles may underlie the expression of economically important traits and could be utilized as weighted SNVs, for example, to improve the accuracy of genomic selection in breeding programmes for sheep. An additional benefit of the pipeline is that it does not require parental genotypes and can therefore be applied to other RNA-Seq datasets for livestock, including those available on the Functional Annotation of Animal Genomes (FAANG) data portal. This study is the first global characterisation of moderate to extreme ASE in tissues and cell types from sheep. We have applied a robust methodology for ASE profiling, to provide both a novel analysis of the multi-dimensional sheep gene expression atlas dataset, and a foundation for identifying the regulatory and expressed elements of the genome that are driving complex traits in livestock.

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An Organ-Wide Gene Expression Atlas of the Developing Human Heart

SSRN Electronic Journal ◽

10.2139/ssrn.3219263 ◽

2018 ◽

Cited By ~ 1

Author(s):

Michaela Asp ◽

Stefania Giacomello ◽

Daniel Fürth ◽

Johan Reimegård ◽

Eva Wärdell ◽

...

Keyword(s):

Gene Expression ◽

Human Heart ◽

Gene Expression Atlas ◽

Expression Atlas

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A gene expression atlas for different kinds of stress in the mouse brain

Scientific Data ◽

10.1038/s41597-020-00772-z ◽

2020 ◽

Vol 7 (1) ◽

Author(s):

Tiziano Flati ◽

Silvia Gioiosa ◽

Giovanni Chillemi ◽

Andrea Mele ◽

Alberto Oliverio ◽

...

Keyword(s):

Gene Expression ◽

Coping With Stress ◽

Gene Expression Atlas ◽

Sequence Read Archive ◽

Brain Transcriptome ◽

Expression Atlas ◽

Differential Gene ◽

Stress Related Genes ◽

Public Repositories ◽

The Brain

AbstractStressful experiences are part of everyday life and animals have evolved physiological and behavioral responses aimed at coping with stress and maintaining homeostasis. However, repeated or intense stress can induce maladaptive reactions leading to behavioral disorders. Adaptations in the brain, mediated by changes in gene expression, have a crucial role in the stress response. Recent years have seen a tremendous increase in studies on the transcriptional effects of stress. The input raw data are freely available from public repositories and represent a wealth of information for further global and integrative retrospective analyses. We downloaded from the Sequence Read Archive 751 samples (SRA-experiments), from 18 independent BioProjects studying the effects of different stressors on the brain transcriptome in mice. We performed a massive bioinformatics re-analysis applying a single, standardized pipeline for computing differential gene expression. This data mining allowed the identification of novel candidate stress-related genes and specific signatures associated with different stress conditions. The large amount of computational results produced was systematized in the interactive “Stress Mice Portal”.

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