Literature DB >> 27252213

Next-Generation Sequencing and the Crustacean Immune System: The Need for Alternatives in Immune Gene Annotation.

K F Clark1, Spencer J Greenwood2.   

Abstract

Next-generation sequencing has been a huge benefit to investigators studying non-model species. High-throughput gene expression studies, which were once restricted to animals with extensive genomic resources, can now be applied to any species. Transcriptomic studies using RNA-Seq can discover hundreds of thousands of transcripts from any species of interest. The power and limitation of these techniques is the sheer size of the dataset that is acquired. Parsing these large datasets is becoming easier as more bioinformatic tools are available for biologists without extensive computer programming expertise. Gene annotation and physiological pathway tools such as Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology enable the application of the vast amount of information acquired from model organisms to non-model species. While noble in nature, utilization of these tools can inadvertently misrepresent transcriptomic data from non-model species via annotation omission. Annotation followed by molecular pathway analysis highlights pathways that are disproportionately affected by disease, stress, or the physiological condition being examined. Problems occur when gene annotation procedures only recognizes a subset, often 50% or less, of the genes differently expressed from a non-model organisms. Annotated transcripts normally belong to highly conserved metabolic or regulatory genes that likely have a secondary or tertiary role, if any at all, in immunity. They appear to be disproportionately affected simply because conserved genes are most easily annotated. Evolutionarily induced specialization of physiological pathways is a driving force of adaptive evolution, but it results in genes that have diverged sufficiently to prevent their identification and annotation through conventional gene or protein databases. The purpose of this manuscript is to highlight some of the challenges faced when annotating crustacean immune genes by using an American lobster (Homarus americanus) transcriptome as an example. Immune genes have evolved rapidly over time, facilitating speciation and adaption to highly divergent ecological niches. Complete and proper annotation of immune genes from invertebrates has been challenging. Modulation of the crustacean immune system occurs in a variety of physiological responses including biotic and abiotic stressors, molting and reproduction. A simple method for the identification of a greater number of potential immune genes is proposed, along with a short introductory primer on crustacean immune response. The intended audience is not the advanced bioinformatic user, but those investigating physiological responses who require rudimentary understanding of crustacean immunological principles, but where immune gene regulation is not their primary interest.
© The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

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Year:  2016        PMID: 27252213     DOI: 10.1093/icb/icw023

Source DB:  PubMed          Journal:  Integr Comp Biol        ISSN: 1540-7063            Impact factor:   3.326


  8 in total

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4.  Host-pathogen coevolution drives innate immune response to Aphanomyces astaci infection in freshwater crayfish: transcriptomic evidence.

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5.  Specific Pathogen Recognition by Multiple Innate Immune Sensors in an Invertebrate.

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7.  Common Gene Expression Patterns in Environmental Model Organisms Exposed to Engineered Nanomaterials: A Meta-Analysis.

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8.  The American lobster genome reveals insights on longevity, neural, and immune adaptations.

Authors:  Jennifer M Polinski; Aleksey V Zimin; K Fraser Clark; Andrea B Kohn; Norah Sadowski; Winston Timp; Andrey Ptitsyn; Prarthana Khanna; Daria Y Romanova; Peter Williams; Spencer J Greenwood; Leonid L Moroz; David R Walt; Andrea G Bodnar
Journal:  Sci Adv       Date:  2021-06-23       Impact factor: 14.136

  8 in total

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