Journal Article

Next-generation transcriptome assembly

Wang, Zhong, Martin, Jeffrey A.

2011

Overview

Key Points The protocols used for library construction, sequencing and data pre-processing can have a great impact on the quality of an assembled transcriptome and the accuracy of gene expression quantification. Before starting an RNA sequencing (RNA-seq) experiment, one should carefully consider using protocols that are strand-specific, that remove ribosomal RNA and that do not require PCR amplification of the template. Strand-specific RNA-seq protocols are important for correctly assembling overlapping transcripts, especially for compact genomes. The reference-based, or ab initio , assembly strategy requires a reference genome and uses much fewer computing resources than the de novo strategy. However, the quality of the genome and the ability of the short-read aligner to align reads across introns will directly influence the accuracy of the assembled transcripts when using the reference-based strategy. The de novo assembly strategy does not use a reference genome but instead uses a De Bruijn graph to represent overlaps between sequences and assemble transcripts. Most de novo approaches require significant computing resources: random access memory (RAM) is the typical limitation. However, de novo assemblers can assemble trans -spliced genes and novel transcripts that are not present in the genome assembly. To take full advantage of the current assembly strategies, a combined assembly approach should be considered that leverages the strengths of reference-based and de novo assembly strategies. Most transcriptome assemblers are still being developed, and the results from these programs should be evaluated using unbiased quantitative metrics. Transcriptome assembly involves an informatics approach to solve an experimental limitation. As sequencing strategies continually improve, it may no longer be necessary in the near future to assemble transcriptomes, as the read length will be longer than any individual transcript. Advances in sequencing technologies, assembly algorithms and computing power are making it feasible to assemble the entire transcriptome from short RNA reads. The article reviews the transcriptome assembly strategies, their advantages and limitations and how to apply them effectively. Transcriptomics studies often rely on partial reference transcriptomes that fail to capture the full catalogue of transcripts and their variations. Recent advances in sequencing technologies and assembly algorithms have facilitated the reconstruction of the entire transcriptome by deep RNA sequencing (RNA-seq), even without a reference genome. However, transcriptome assembly from billions of RNA-seq reads, which are often very short, poses a significant informatics challenge. This Review summarizes the recent developments in transcriptome assembly approaches — reference-based, de novo and combined strategies — along with some perspectives on transcriptome assembly in the near future.

• Publisher: Nature Publishing Group UK,Nature Publishing Group
• Subject: 631/208/212/2019 / 631/208/514/1949 / 631/208/514/2254 / Agriculture / Algorithms / Animal Genetics and Genomics / Animals / Base Sequence / BASIC BIOLOGICAL SCIENCES / Biological and medical sciences / Biomedical and Life Sciences / Biomedicine / Cancer Research / Cloning, Molecular / Experiments / Fundamental and applied biological sciences. Psychology / Gene Expression Profiling - methods / Gene Expression Profiling - trends / Gene Function / Gene Library / Genetics of eukaryotes. Biological and molecular evolution / Genomes / Human Genetics / Humans / Informatics / Models, Biological / Molecular Sequence Annotation - methods / Molecular Sequence Annotation - trends / Molecular Sequence Data / Next-generation, transcriptome, assembly, RNAs / review-article / Sequence Analysis, DNA - methods / Sequence Analysis, DNA - trends / Sequence Analysis, RNA - methods / Sequence Analysis, RNA - trends