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Optimization of next-generation sequencing transcriptome annotation for species lacking sequenced genomes.

ABSTRACT: Next-generation sequencing methods, such as RNA-seq, have permitted the exploration of gene expression in a range of organisms which have been studied in ecological contexts but lack a sequenced genome. However, the efficacy and accuracy of RNA-seq annotation methods using reference genomes from related species have yet to be robustly characterized. Here we conduct a comprehensive power analysis employing RNA-seq data from Drosophila melanogaster in conjunction with 11 additional genomes from related Drosophila species to compare annotation methods and quantify the impact of evolutionary divergence between transcriptome and the reference genome. Our analyses demonstrate that, regardless of the level of sequence divergence, direct genome mapping (DGM), where transcript short reads are aligned directly to the reference genome, significantly outperforms the widely used de novo and guided assembly-based methods in both the quantity and accuracy of gene detection. Our analysis also reveals that DGM recovers a more representative profile of Gene Ontology functional categories, which are often used to interpret emergent patterns in genomewide expression analyses. Lastly, analysis of available primate RNA-seq data demonstrates the applicability of our observations across diverse taxa. Our quantification of annotation accuracy and reduced gene detection associated with sequence divergence thus provides empirically derived guidelines for the design of future gene expression studies in species without sequenced genomes.

SUBMITTER: Ockendon NF

PROVIDER: S-EPMC4982090 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Optimization of next-generation sequencing transcriptome annotation for species lacking sequenced genomes.

Ockendon Nina F NF O'Connell Lauren A LA Bush Stephen J SJ Monzón-Sandoval Jimena J Barnes Holly H Székely Tamás T Hofmann Hans A HA Dorus Steve S Urrutia Araxi O AO

Molecular ecology resources 20151014 2

Next-generation sequencing methods, such as RNA-seq, have permitted the exploration of gene expression in a range of organisms which have been studied in ecological contexts but lack a sequenced genome. However, the efficacy and accuracy of RNA-seq annotation methods using reference genomes from related species have yet to be robustly characterized. Here we conduct a comprehensive power analysis employing RNA-seq data from Drosophila melanogaster in conjunction with 11 additional genomes from re ...[more]

PMID: 26358618

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Project description:BackgroundAccumulating evidence implicates mitochondrial DNA (mtDNA) alleles, which are independent of the nuclear genome, in disease, especially in human metabolic diseases. However, this area of investigation has lagged behind in researching the nuclear alleles in complex traits, for example, in gout.MethodsNext-generation sequencing was utilized to investigate the relationship between mtDNA alleles and phenotypic variations in 52 male patients with gout and 104 age-matched male non-gout controls from the Taiwan Biobank whole-genome sequencing samples. Differences from a reference sequence (GRCh38) were identified. The sequence kernel association test (SKAT) was applied to identify gout-associated alleles in mitochondrial genes. The tools Polymorphism Phenotyping, Sorting Intolerant From Tolerant (SIFT), Predict the pathology of Mutations (PMUT), Human Mitochondrial Genome Database (mtDB), Multiple Alignment using Fast Fourier Transform (MAFFT), and Mammalian Mitochondrial tRNA Genes (Mamit-tRNA) were used to evaluate pathogenicity of alleles. Validation of selected alleles by quantitative polymerase chain reaction of single nucleotide polymorphisms (qPCR SNPs) was also performed.ResultsWe identified 456 alleles in patients with gout and 640 alleles in non-gout controls with 274 alleles shared by both. Mitochondrial genes were associated with gout, with MT-CO3, MT-TA, MT-TC, and MT-TT containing potentially pathogenic gout-associated alleles and displaying evidence of gene-gene interactions. All heteroplasmy levels of potentially pathogenic alleles exceeded metabolic thresholds for pathogenicity. Validation assays confirmed the next-generation sequencing results of selected alleles. Among them, potentially pathogenic MT-CO3 alleles correlated with high-density lipoprotein (HDL) levels (P?=?0.034).ConclusionThis study provided two scientific insights. First, this was the most extensive mitochondrial genomic profiling associated with gout. Second, our results supported the roles of mitochondria in gout and HDL, and this comprehensive analysis framework can be applied to other diseases in which mitochondrial dysfunction has been implicated.

Project description:BACKGROUND:Next-Generation Sequencing (NGS) technology has exceptionally increased the ability to sequence DNA in a massively parallel and cost-effective manner. Nevertheless, NGS data analysis requires bioinformatics skills and computational resources well beyond the possibilities of many "wet biology" laboratories. Moreover, most of projects only require few sequencing cycles and standard tools or workflows to carry out suitable analyses for the identification and annotation of genes, transcripts and splice variants found in the biological samples under investigation. These projects can take benefits from the availability of easy to use systems to automatically analyse sequences and to mine data without the preventive need of strong bioinformatics background and hardware infrastructure. RESULTS:To address this issue we developed an automatic system targeted to the analysis of NGS data obtained from large-scale transcriptome studies. This system, we named NGS-Trex (NGS Transcriptome profile explorer) is available through a simple web interface http://www.ngs-trex.org and allows the user to upload raw sequences and easily obtain an accurate characterization of the transcriptome profile after the setting of few parameters required to tune the analysis procedure. The system is also able to assess differential expression at both gene and transcript level (i.e. splicing isoforms) by comparing the expression profile of different samples.By using simple query forms the user can obtain list of genes, transcripts, splice sites ranked and filtered according to several criteria. Data can be viewed as tables, text files or through a simple genome browser which helps the visual inspection of the data. CONCLUSIONS:NGS-Trex is a simple tool for RNA-Seq data analysis mainly targeted to "wet biology" researchers with limited bioinformatics skills. It offers simple data mining tools to explore transcriptome profiles of samples investigated taking advantage of NGS technologies.

Project description:BACKGROUND: We have developed a simulation approach to help determine the optimal mixture of sequencing methods for most complete and cost effective transcriptome sequencing. We compared simulation results for traditional capillary sequencing with "Next Generation" (NG) ultra high-throughput technologies. The simulation model was parameterized using mappings of 130,000 cDNA sequence reads to the Arabidopsis genome (NCBI Accession SRA008180.19). We also generated 454-GS20 sequences and de novo assemblies for the basal eudicot California poppy (Eschscholzia californica) and the magnoliid avocado (Persea americana) using a variety of methods for cDNA synthesis. RESULTS: The Arabidopsis reads tagged more than 15,000 genes, including new splice variants and extended UTR regions. Of the total 134,791 reads (13.8 MB), 119,518 (88.7%) mapped exactly to known exons, while 1,117 (0.8%) mapped to introns, 11,524 (8.6%) spanned annotated intron/exon boundaries, and 3,066 (2.3%) extended beyond the end of annotated UTRs. Sequence-based inference of relative gene expression levels correlated significantly with microarray data. As expected, NG sequencing of normalized libraries tagged more genes than non-normalized libraries, although non-normalized libraries yielded more full-length cDNA sequences. The Arabidopsis data were used to simulate additional rounds of NG and traditional EST sequencing, and various combinations of each. Our simulations suggest a combination of FLX and Solexa sequencing for optimal transcriptome coverage at modest cost. We have also developed ESTcalc http://fgp.huck.psu.edu/NG_Sims/ngsim.pl, an online webtool, which allows users to explore the results of this study by specifying individualized costs and sequencing characteristics. CONCLUSION: NG sequencing technologies are a highly flexible set of platforms that can be scaled to suit different project goals. In terms of sequence coverage alone, the NG sequencing is a dramatic advance over capillary-based sequencing, but NG sequencing also presents significant challenges in assembly and sequence accuracy due to short read lengths, method-specific sequencing errors, and the absence of physical clones. These problems may be overcome by hybrid sequencing strategies using a mixture of sequencing methodologies, by new assemblers, and by sequencing more deeply. Sequencing and microarray outcomes from multiple experiments suggest that our simulator will be useful for guiding NG transcriptome sequencing projects in a wide range of organisms.

Dataset Information

Optimization of next-generation sequencing transcriptome annotation for species lacking sequenced genomes.

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Optimization of next-generation sequencing transcriptome annotation for species lacking sequenced genomes.

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