Here We Are, But Where Do We Go? A Systematic Review of Crustacean Transcriptomic Studies from 2014-2015
Here We Are, But Where Do We Go? A Systematic Review of Crustacean Transcriptomic Studies from 2014-2015
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DOI：
10.1093/icb/icw061
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发表时间：
2016-12-01
影响因子：
2.6
通讯作者：
Santos, Scott R.
中科院分区：
文献类型：
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作者：
Havird, Justin C.;Santos, Scott R.
尽管基因组资源在经济、生态和实验方面具有重要意义，但对甲壳类动物来说，基因组资源仍然稀缺。代替基因组，许多研究人员利用技术进步对甲壳类转录进行重新排序和组装。然而，对于什么是或应该是该领域的标准操作程序，几乎没有达成共识。在这里，我们系统地审查了2014-2015年间发表的53项研究，这些研究利用了这个分类小组的转录资源，以努力确定除甲壳类外具有适用性的共同点和潜在的弱点。总的来说，这些研究利用了新的和公开可用的RNA-Seq数据来表征转录本和/或识别不同治疗之间的差异表达基因(Deg)。尽管三一软件套件在组装流水线中很受欢迎，其他程序也经常使用，但许多研究未能报告关于生物信息学方法的关键细节，包括读取映射器和在识别和表征DEG时所利用的参数。组装的转录重叠群的注释百分比很低，总体平均为32%。虽然其他指标，如报告的重叠群和DEG的数量，与每个样本使用的序列读取数量相关，但随着测序深度的增加，这些指标确实达到了明显的饱和。最令人不安的是，一些研究(55%)报告了基于非重复实验设计和每个治疗的单一生物重复的DEGS。有鉴于此，我们建议未来针对转录组特征的RNA-Seq实验进行更深层次的(即50-100M读数)测序，而那些研究差异表达的实验则更多地关注较浅(即类似于10-20M读数/样本)测序深度的生物复制增加。此外，社区必须避免提交审查或接受发表非复制的差异表达研究。最后，挖掘不断增长的公开可用的甲壳类转录数据将使未来的研究能够专注于假说驱动的研究，而不是继续简单地描述转录本的特征。作为一个例子，我们利用最近描述的雷米足类毒腺转录组的神经毒素序列，结合公开可用的甲壳类动物转录组数据，得出了关于甲壳类毒液进化的初步结果和假设。
Despite their economic, ecological, and experimental importance, genomic resources remain scarce for crustaceans. In lieu of genomes, many researchers have taken advantage of technological advancements to instead sequence and assemble crustacean transcriptomes de novo. However, there is little consensus on what standard operating procedures are, or should be, for the field. Here, we systematically reviewed 53 studies published during 2014-2015 that utilized transcriptomic resources from this taxonomic group in an effort to identify commonalities as well as potential weaknesses that have applicability beyond just crustaceans. In general, these studies utilized RNA-Seq data, both novel and publicly available, to characterize transcriptomes and/or identify differentially expressed genes (DEGs) between treatments. Although the software suite Trinity was popular in assembly pipelines and other programs were also commonly employed, many studies failed to report crucial details regarding bioinformatic methodologies, including read mappers and the utilized parameters in identifying and characterizing DEGs. Annotation percentages for assembled transcriptomic contigs were low, averaging 32% overall. While other metrics, such as numbers of contigs and DEGs reported, correlated with the number of sequence reads utilized per sample, these did reach apparent saturation with increasing sequencing depth. Most disturbingly, a number of studies (55%) reported DEGs based on non-replicated experimental designs and single biological replicates for each treatment. Given this, we suggest future RNA-Seq experiments targeting transcriptome characterization conduct deeper (i.e., 50-100 M reads) sequencing while those examining differential expression instead focus more on increased biological replicates at shallower (i.e., similar to 10-20 M reads/sample) sequencing depths. Moreover, the community must avoid submitting for review, or accepting for publication, nonreplicated differential expression studies. Finally, mining the ever growing publicly available transcriptomic data from crustaceans will allow future studies to focus on hypothesis-driven research instead of continuing to simply characterize transcriptomes. As an example of this, we utilized neurotoxin sequences from the recently described remipede venom gland transcriptome in conjunction with publicly available crustacean transcriptomic data to derive preliminary results and hypotheses regarding the evolution of venom in crustaceans.