Data from: Reference-free transcriptome assembly in non-model animals from next generation sequencing data

Next-generation sequencing (NGS) technologies offer the opportunity for population genomic study of non-model organisms sampled in the wild. The transcriptome is a convenient and popular target for such purposes. However, designing genetic markers from NGS transcriptome data requires assembling gene-coding sequences out of short reads. This is a complex task owing to gene duplications, genetic polymorphism, alternative splicing and transcription noise. Typical assembling programmes return thousands of predicted contigs, whose connection to the species true gene content is unclear, and from which SNP definition is uneasy. Here, the transcriptomes of five diverse non-model animal species (hare, turtle, ant, oyster and tunicate) were assembled from newly generated 454 and Illumina sequence reads. In two species for which a reference genome is available, a new procedure was introduced to annotate each predicted contig as either a full-length cDNA, fragment, chimera, allele, paralogue, genomic sequence or other, based on the number of, and overlap between, blast hits to the appropriate reference. Analyses showed that (i) the highest quality assemblies are obtained when 454 and Illumina data are combined, (ii) typical de novo assemblies include a majority of irrelevant cDNA predictions and (iii) assemblies can be appropriately cleaned by filtering contigs based on length and coverage. We conclude that robust, reference-free assembly of thousands of genes from transcriptomic NGS data is possible, opening promising perspectives for transcriptome-based population genomics in animals. A Galaxy pipeline implementing our best-performing assembling strategy is provided.下一代测序（Next-generation sequencing, NGS）技术为野生采样的非模式生物的群体基因组学研究提供了可行路径。转录组正是此类研究便捷且热门的研究靶点。然而，基于NGS转录组数据开发遗传标记，需从短读长序列中组装基因编码序列。由于基因重复、遗传多态性、可变剪接及转录噪声的存在，该任务极具挑战性。常规组装程序会产出数千条预测得到的重叠群（contig），但这些重叠群与物种真实基因组分的关联尚不明确，且难以从中准确界定单核苷酸多态性（Single Nucleotide Polymorphism, SNP）。本研究针对野兔、龟、蚂蚁、牡蛎及被囊动物这五种不同的非模式动物物种，基于新产出的454与Illumina测序读长序列完成了其转录组组装。针对其中两个已拥有参考基因组的物种，本研究提出了一套全新的注释流程：基于比对至对应参考基因组的BLAST（Basic Local Alignment Search Tool）命中数及其重叠情况，将每条预测重叠群注释为全长cDNA、片段、嵌合体、等位基因、旁系同源基因、基因组序列或其他类型。分析结果显示：其一，整合454与Illumina数据可获得最高质量的组装结果；其二，常规从头组装产物中多数为无关的cDNA预测结果；其三，可通过基于长度和覆盖度对重叠群进行过滤，实现组装结果的有效净化。本研究证实，无需参考基因组即可从转录组NGS数据中稳健组装出数千个基因，这为基于转录组的动物群体基因组学研究开辟了极具前景的方向。本研究还提供了一套可实现最优组装策略的Galaxy流程工具。