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Influence of RNA-Seq library construction, sampling methods, and tissue harvesting time on gene expression estimation.

Ylenia ChiariGordon LuikartNickolas MorenoScott RelyeaJames DunniganMatthew C BoyerMarty KardosScott GlabermanGordon Luikart
Published in: Molecular ecology resources (2023)
RNA sequencing (RNA-Seq) is popular for measuring gene expression in non-model organisms, including wild populations. While RNA-Seq can detect gene expression variation among wild-caught individuals and yield important insights into biological function, sampling methods can also affect gene expression estimates. We examined the influence of multiple technical variables on estimated gene expression in a non-model fish, the westslope cutthroat trout (Oncorhynchus clarkii lewisi), using two RNA-Seq library types: 3' RNA-Seq (QuantSeq) and whole mRNA-Seq (NEB). We evaluated effects of dip netting versus electrofishing, and of harvesting tissue immediately versus 5 min after euthanasia on estimated gene expression in blood, gill, and muscle. We found no significant differences in gene expression between sampling methods or tissue collection times with either library type. When library types were compared using the same blood samples, 58% of genes detected by both NEB and QuantSeq showed significantly different expression between library types, and NEB detected 31% more genes than QuantSeq. Although the two library types recovered different numbers of genes and expression levels, results with NEB and QuantSeq were consistent in that neither library type showed differences in gene expression between sampling methods and tissue harvesting times. Our study suggests that researchers can safely rely on different fish sampling strategies in the field. In addition, while QuantSeq is more cost effective, NEB detects more expressed genes. Therefore, when it is crucial to detect as many genes as possible (especially low expressed genes), when alternative splicing is of interest, or when working with an organism lacking good genomic resources, whole mRNA-Seq is more powerful.
Keyphrases
  • rna seq
  • gene expression
  • single cell
  • dna methylation
  • genome wide
  • poor prognosis
  • genome wide identification
  • copy number
  • transcription factor
  • multidrug resistant
  • gram negative