Guidelines for RNA-seq projects: applications and opportunities in non-model decapod crustacean species

Abstract

Next Generation Sequencing (NGS) has dramatically changed the way biological research is being conducted in the post-genomic era and they have only been utilized widely over the recent decade for studies of non-model decapod crustacean species, predominantly by sequencing the transcriptome of various tissues across different life stages. NGS can now provide a rapid, costeffective solution for discovery of genetic markers crucial in many applications that would previously have otherwise taken years to develop. Sequencing of the entire transcriptome (referred to as RNA sequencing; RNA-seq) is one of the most popular NGS tools. RNA-seq studies of non-model species in crustacean taxa however, have faced some problems, including a lack of "good" experimental study design, a relative paucity of gene annotations, combined with limited knowledge of genomic technologies and analyses. The aim of the current review is to assist crustacean biologists to develop a better appreciation of the applications and scope of RNA-seq analysis, understand the basic requirements for optimal RNA-seq studies and provide an overview of each step from RNA-seq experimental design to bioinformatics approaches to data analysis. Insights that have resulted from RNA-seq studies across a wide range of non-model decapod species are also summarized.

American lobster postlarvae alter gene regulation in response to ocean warming and acidification

“…Differential expression of transcripts was analyzed statistically between treatments using both DESeq2 (Love et al., 2014; Galaxy Version 2.11.40.2) and edgeR (Conesa et al., 2016; Liu et al., 2015; Robinson et al., 2009; Galaxy Version 3.20.7.2), as the integration of multiple methods has been shown to improve accuracy and reduce error rates (Costa‐Silva et al., 2017). While edgeR and DESeq2 are based on a negative binomial distribution and are both recommended for small sample sizes, DESeq2 uses a geometric normalization method, whereas edgeR calculates a weighted mean of log‐ratios for normalization (Dillies et al., 2013; Nguyen et al., 2018). The integration of both tools in our methodology produces a more robust gene expression analysis (Nguyen et al., 2018).…”

Parameter estimation of laboratory-reared Panulirus ornatus

“…It is important to take into consideration the needs of integrating discontinuity in growth because when crustaceans grow, they periodically shed their exoskeletons to make room for new exoskeletons [9,11]. However, some obstacles to moult-process estimation such as the stepwise function throughout the moulting cycle which caused difficulty in determining a crustacean growth at one time.…”

Molecular physiology of copepods - from biomarkers to transcriptomes and back again

“…Toward this end, if appropriately leveraged, RNA-seq studies can help to improve gene predictions, reveal alternative splicing and allelic variants, and provide functional insights. Annotation of genomic and transcriptomic databases would benefit from integration with ongoing efforts toward annotating other crustacean databases (e.g., RNA-seq studies in decapods, reviewed by Nguyen et al, 2018) and incorporating emerging results from functional studies conducted in crustaceans (e.g., knockout and knockdown approaches).…”