Improved structural annotation of protein-coding genes in the Meloidogyne hapla genome using RNA-Seq

SLIDR and SLOPPR: flexible identification of spliced leader trans-splicing and prediction of eukaryotic operons from RNA-Seq data

BACKGROUND

Spliced leader (SL) trans-splicing replaces the 5' end of pre-mRNAs with the spliced leader, an exon derived from a specialised non-coding RNA originating from elsewhere in the genome. This process is essential for resolving polycistronic pre-mRNAs produced by eukaryotic operons into monocistronic transcripts. SL trans-splicing and operons may have independently evolved multiple times throughout Eukarya, yet our understanding of these phenomena is limited to only a few well-characterised organisms, most notably C. elegans and trypanosomes. The primary barrier to systematic discovery and characterisation of SL trans-splicing and operons is the lack of computational tools for exploiting the surge of transcriptomic and genomic resources for a wide range of eukaryotes.

RESULTS

Here we present two novel pipelines that automate the discovery of SLs and the prediction of operons in eukaryotic genomes from RNA-Seq data. SLIDR assembles putative SLs from 5' read tails present after read alignment to a reference genome or transcriptome, which are then verified by interrogating corresponding SL RNA genes for sequence motifs expected in bona fide SL RNA molecules. SLOPPR identifies RNA-Seq reads that contain a given 5' SL sequence, quantifies genome-wide SL trans-splicing events and predicts operons via distinct patterns of SL trans-splicing events across adjacent genes. We tested both pipelines with organisms known to carry out SL trans-splicing and organise their genes into operons, and demonstrate that (1) SLIDR correctly detects expected SLs and often discovers novel SL variants; (2) SLOPPR correctly identifies functionally specialised SLs, correctly predicts known operons and detects plausible novel operons.

CONCLUSIONS

SLIDR and SLOPPR are flexible tools that will accelerate research into the evolutionary dynamics of SL trans-splicing and operons throughout Eukarya and improve gene discovery and annotation for a wide range of eukaryotic genomes. Both pipelines are implemented in Bash and R and are built upon readily available software commonly installed on most bioinformatics servers. Biological insight can be gleaned even from sparse, low-coverage datasets, implying that an untapped wealth of information can be retrieved from existing RNA-Seq datasets as well as from novel full-isoform sequencing protocols as they become more widely available.

SLFinder, a pipeline for the novel identification of splice-leader sequences: a good enough solution for a complex problem

BACKGROUND

Spliced Leader trans-splicing is an important mechanism for the maturation of mRNAs in several lineages of eukaryotes, including several groups of parasites of great medical and economic importance. Nevertheless, its study across the tree of life is severely hindered by the problem of identifying the SL sequences that are being trans-spliced.

RESULTS

In this paper we present SLFinder, a four-step pipeline meant to identify de novo candidate SL sequences making very few assumptions regarding the SL sequence properties. The pipeline takes transcriptomic de novo assemblies and a reference genome as input and allows the user intervention on several points to account for unexpected features of the dataset. The strategy and its implementation were tested on real RNAseq data from species with and without SL Trans-Splicing.

CONCLUSIONS

SLFinder is capable to identify SL candidates with good precision in a reasonable amount of time. It is especially suitable for species with unknown SL sequences, generating candidate sequences for further refining and experimental validation.

Heterodera glycines utilizes promiscuous spliced leaders and demonstrates a unique preference for a species-specific spliced leader over C. elegans SL1

Spliced leader trans-splicing (SLTS) plays a part in the maturation of pre-mRNAs in select species across multiple phyla but is particularly prevalent in Nematoda. The role of spliced leaders (SL) within the cell is unclear and an accurate assessment of SL occurrence within an organism is possible only after extensive sequencing data are available, which is not currently the case for many nematode species. SL discovery is further complicated by an absence of SL sequences from high-throughput sequencing results due to incomplete sequencing of the 5'-ends of transcripts during RNA-seq library preparation, known as 5'-bias. Existing datasets and novel methodology were used to identify both conserved SLs and unique hypervariable SLs within Heterodera glycines, the soybean cyst nematode. In H. glycines, twenty-one distinct SL sequences were found on 2,532 unique H. glycines transcripts. The SL sequences identified on the H. glycines transcripts demonstrated a high level of promiscuity, meaning that some transcripts produced as many as nine different individual SL-transcript combinations. Most uniquely, transcriptome analysis revealed that H. glycines is the first nematode to demonstrate a higher SL trans-splicing rate using a species-specific SL over well-conserved Caenorhabditis elegans SL-like sequences.

Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes

Complementing genome sequence with deep transcriptome and proteome data could enable more accurate assembly and annotation of newly sequenced genomes. Here, we provide a proof-of-concept of an integrated approach for analysis of the genome and proteome of Anopheles stephensi, which is one of the most important vectors of the malaria parasite. To achieve broad coverage of genes, we carried out transcriptome sequencing and deep proteome profiling of multiple anatomically distinct sites. Based on transcriptomic data alone, we identified and corrected 535 events of incomplete genome assembly involving 1196 scaffolds and 868 protein-coding gene models. This proteogenomic approach enabled us to add 365 genes that were missed during genome annotation and identify 917 gene correction events through discovery of 151 novel exons, 297 protein extensions, 231 exon extensions, 192 novel protein start sites, 19 novel translational frames, 28 events of joining of exons, and 76 events of joining of adjacent genes as a single gene. Incorporation of proteomic evidence allowed us to change the designation of more than 87 predicted “noncoding RNAs” to conventional mRNAs coded by protein-coding genes. Importantly, extension of the newly corrected genome assemblies and gene models to 15 other newly assembled Anopheline genomes led to the discovery of a large number of apparent discrepancies in assembly and annotation of these genomes. Our data provide a framework for how future genome sequencing efforts should incorporate transcriptomic and proteomic analysis in combination with simultaneous manual curation to achieve near complete assembly and accurate annotation of genomes.

Optimizing k-mer size using a variant grid search to enhance de novo genome assembly

Largely driven by huge reductions in per-base costs, sequencing nucleic acids has become a near-ubiquitous technique in laboratories performing biological and biomedical research. Most of the effort goes to re-sequencing, but assembly of de novogenerated, raw sequence reads into contigs that span as much of the genome as possible is central to many projects. Although truly complete coverage is not realistically attainable, maximizing the amount of sequence that can be correctly assembled into contigs contributes to coverage. Here we compare three commonly used assembly algorithms (ABySS, Velvet and SOAPdenovo2), and show that empirical optimization of k-mer values has a disproportionate influence on de novo assembly of a eukaryotic genome, the nematode parasite Meloidogynechitwoodi. Each assembler was challenged with about 40 million Iluumina II paired-end reads, and assemblies performed under a range of k-mer sizes. In each instance, the optimal k-mer was 127, although based on N50 values,ABySS was more efficient than the others. That the assembly was not spurious was established using the "Core Eukaryotic Gene Mapping Approach", which indicated that 98.79% of the M. chitwoodi genome was accounted for by the assembly. Subsequent gene finding and annotation are consistent with this and suggest that k-mer optimization contributes to the robustness of assembly.