scholarly journals Cultivar-specific transcriptome and pan-transcriptome reconstruction of tetraploid potato

2019 ◽  
Author(s):  
Marko Petek ◽  
Maja Zagorščak ◽  
Živa Ramšak ◽  
Sheri Sanders ◽  
Špela Tomaž ◽  
...  
Keyword(s):  
Reference Genome ◽  
De Novo ◽  
Potato Research ◽  
Rna Seq ◽  
Optimal Outcome ◽  
Tetraploid Potato ◽  
Breeding Programmes ◽  
Transcriptome Reconstruction ◽  
Gene Variability ◽  
Group Tuberosum

AbstractAlthough the reference genome of Solanum tuberosum Group Phureja double-monoploid (DM) clone is available, knowledge on the genetic diversity of the highly heterozygous tetraploid Group Tuberosum, representing most cultivated varieties, remains largely unexplored. This lack of knowledge hinders further progress in potato research. In conducted investigation, we first merged and manually curated the two existing partially-overlapping DM genome-based gene models, creating a union of genes in Phureja scaffold. Next, we compiled available and newly generated RNA-Seq datasets (cca. 1.5 billion reads) for three tetraploid potato genotypes (cultivar Désirée, cultivar Rywal, and breeding clone PW363) with diverse breeding pedigrees. Short-read transcriptomes were assembled using several de novo assemblers under different settings to test for optimal outcome. For cultivar Rywal, PacBio Iso-Seq full-length transcriptome sequencing was also performed. EvidentialGene redundancy-reducing pipeline complemented with in-house developed scripts was employed to produce accurate and complete cultivar-specific transcriptomes, as well as to attain the pan-transcriptome. The generated transcriptomes and pan-transcriptome represent a valuable resource for potato gene variability exploration, high-throughput omics analyses, and breeding programmes.

scholarly journals rnaSPAdes: a de novo transcriptome assembler and its application to RNA-Seq data

2018 ◽  
Author(s):  
Elena Bushmanova ◽  
Dmitry Antipov ◽  
Alla Lapidus ◽  
Andrey D. Prjibelski
Keyword(s):  
De Novo ◽  
Transcriptome Assembly ◽  
Model Organisms ◽  
Challenging Problem ◽  
Rna Seq ◽  
De Novo Transcriptome ◽  
Weak Points ◽  
Transcriptome Reconstruction ◽  
Evaluation Approaches ◽  
Genome Assembler

AbstractSummaryPossibility to generate large RNA-seq datasets has led to development of various reference-based and de novo transcriptome assemblers with their own strengths and limitations. While reference-based tools are widely used in various transcriptomic studies, their application is limited to the model organisms with finished and annotated genomes. De novo transcriptome reconstruction from short reads remains an open challenging problem, which is complicated by the varying expression levels across different genes, alternative splicing and paralogous genes. In this paper we describe a novel transcriptome assembler called rnaSPAdes, which is developed on top of SPAdes genome assembler and explores surprising computational parallels between assembly of transcriptomes and single-cell genomes. We also present quality assessment reports for rnaSPAdes assemblies, compare it with modern transcriptome assembly tools using several evaluation approaches on various RNA-Seq datasets, and briefly highlight strong and weak points of different assemblers.Availability and implementationrnaSPAdes is implemented in C++ and Python and is freely available at cab.spbu.ru/software/rnaspades/.

scholarly journals Ion channel profiling of the Lymnaea stagnalis ganglia via transcriptome analysis

2020 ◽  
Author(s):  
Nan Dong ◽  
Julia Bandura ◽  
Zhaolei Zhang ◽  
Yan Wang ◽  
Karine Labadie ◽  
...  
Keyword(s):  
Ion Channels ◽  
Reference Genome ◽  
Lymnaea Stagnalis ◽  
De Novo ◽  
Model Organisms ◽  
Sequence Length ◽  
Pond Snail ◽  
Sequence Information ◽  
Functional Domain ◽  
Rna Seq

Abstract Background. The pond snail Lymnaea stagnalis (L. stagnalis) has been widely used as a model organism in neurobiology, ecotoxicology, and parasitology due to the relative simplicity of its CNS. However, its usefulness is restricted by a limited availability of transcriptome data. While sequence information for the L. stagnalis CNS transcripts has been obtained from EST library and a de novo RNA-seq assembly, the quality of these assemblies is limited by a combination of low coverage of EST libraries, the fragmented nature of de novo assemblies, and lack of reference genome. Results. In this study, taking advantage of the recent availability of the L. stagnalis reference genome, we generated an RNA-seq library from the adult L. stagnalis CNS, using a combination of genome-guided and de novo assembly programs to identify 17,832 protein-coding L. stagnalis transcripts. We combined our library with existing resources to produce a transcript set with greater sequence length, completeness, and diversity than previously available ones. Using our assembly and functional domain analysis, we profiled L. stagnalis CNS transcripts encoding ion channels and ionotropic receptors, which are key proteins for CNS function, and compared their sequences to other vertebrate and invertebrate model organisms. Interestingly, L. stagnalis transcripts encoding numerous putative Ca2+ channels showed the most sequence similarity to those of mouse, zebrafish, Xenopus tropicalis, fruit fly, and C. elegans, suggesting that many calcium channel-related signaling pathways may be evolutionarily conserved. Conclusions. Our study provides the most thorough characterization to date of the L. stagnalis transcriptome and provides insights into differences between vertebrates and invertebrates in CNS transcript diversity, according to function and protein class. Furthermore, this study is, to the best of our knowledge, the first to provide a complete characterization of the ion channels of a single species, opening new avenues for future research on fundamental neurobiological processes.

scholarly journals Necklace: combining reference and assembled transcriptomes for more comprehensive RNA-Seq analysis

2017 ◽  
Author(s):  
Nadia M Davidson ◽  
Alicia Oshlack
Keyword(s):  
Differential Expression ◽  
De Novo Assembly ◽  
Reference Genome ◽  
Reference Data ◽  
De Novo ◽  
Rna Seq ◽  
Software Pipeline ◽  
Standard Methods ◽  
A Genome ◽  
Genome Annotations

AbstractBackgroundRNA-Seq analyses can benefit from performing a genome-guided and de novo assembly, in particular for species where the reference genome or the annotation is incomplete. However, tools for integrating assembled transcriptome with reference annotation are lacking.FindingsNecklace is a software pipeline that runs genome-guided and de novo assembly and combines the resulting transcriptomes with reference genome annotations. Necklace constructs a compact but comprehensive superTranscriptome out of the assembled and reference data. Reads are subsequently aligned and counted in preparation for differential expression testing.ConclusionsNecklace allows a comprehensive transcriptome to be built from a combination of assembled and annotated transcripts which results in a more comprehensive transcriptome for the majority of organisms. In addition RNA-seq data is mapped back to this newly created superTranscript reference to enable differential expression testing with standard methods. Necklace is available from https://github.com/Oshlack/necklace/wiki under GPL 3.0.

scholarly journals The genome sequence of Sorbus pohuashanensis provides insights into population evolution and leaf sunburn response

2021 ◽  
Author(s):  
Dongxue Zhao ◽  
Yan Zhang ◽  
Yizeng Lu ◽  
Mao Chai ◽  
Liqiang Fan ◽  
...  
Keyword(s):  
Heat Shock ◽  
Reference Genome ◽  
De Novo ◽  
Leaf Shape ◽  
Gene Families ◽  
Natural Hybridization ◽  
Rna Seq ◽  
Long Reads ◽  
High Level ◽  
Chromosomal Synteny

Sorbus pohuashanensis is a potential horticulture and medicinal plant, but its genomic and genetic background remains unknown. Here, we de novo sequenced and assembled the S. pohuashanensis (Hance) Hedl. reference genome using PacBio long reads. Based on the new reference genome, we resequenced a core collection of 22 Sorbus spp. samples, which were divided into two groups (G1 and G2) based on phylogenetic and PCA analysis. These phylogenetic clusters were highly in accordance with the classification based on leaf shape. Natural hybridization between the G1 and G2 groups was evidenced by a sample (R21) with a highly heterozygous genotype. Nucleotide diversity (π) analysis showed that G1 has a higher diversity than G2, and that G2 originated from G1. During the evolution process, the gene families involved in photosynthesis pathways expanded and gene families involved in energy consumption contracted. Comparative genome analysis showed that S. pohuashanensis has a high level of chromosomal synteny with Malus domestica and Pyrus communis. RNA-seq data suggested that flavonol biosynthesis and heat-shock protein (HSP)-heat-shock factor (HSF) pathways play important roles in protection against sunburn. This research provides new insight into the evolution of Sorbus spp. genomes. In addition, the genomic resources and the identified genetic variations, especially those genes related to stress resistance, will help future efforts to introduce and breed Sorbus spp.

scholarly journals The Bellerophon pipeline, improving de novo transcriptomes and removing chimeras

2018 ◽  
Author(s):  
Jesse Kerkvliet ◽  
Arthur de Fouchier ◽  
Michiel van Wijk ◽  
Astrid T. Groot
Keyword(s):  
Quality Control ◽  
Quality Assessment ◽  
Reference Genome ◽  
Assessment Tool ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Rna Seq ◽  
Quality Assessment Tool ◽  
Chimeric Sequences

AbstractTranscriptome quality control is an important step in RNA-seq experiments. However, the quality of de novo assembled transcriptomes is difficult to assess, due to the lack of reference genome to compare the assembly to. We developed a method to assess and improve the quality of de novo assembled transcriptomes by focusing on the removal of chimeric sequences. These chimeric sequences can be the result of faulty assembled contigs, merging two transcripts into one. The developed method is incorporated into a pipeline, that we named Bellerophon, which is broadly applicable and easy to use. Bellerophon first uses the quality-assessment tool TransRate to indicate the quality, after which it uses a Transcripts Per Million (TPM) filter to remove lowly expressed contigs and CD-HIT-EST to remove highly identical contigs. To validate the quality of this method, we performed three benchmark experiments: 1) a computational creation of chimeras, 2) identification of chimeric contigs in a transcriptome assembly, 3) a simulated RNAseq experiment using a known reference transcriptome. Overall, the Bellerophon pipeline was able to remove between 40 to 91.9% of the chimeras in transcriptome assemblies and removed more chimeric than non-chimeric contigs. Thus, the Bellerophon sequence of filtration steps is a broadly applicable solution to improve transcriptome assemblies.

scholarly journals RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

2011 ◽  
Vol 12 (1) ◽  
Author(s):  
Bo Li ◽  
Colin N Dewey
Keyword(s):  
Reference Genome ◽  
De Novo ◽  
Software Tool ◽  
Read Length ◽  
Rna Seq ◽  
Efficient Design ◽  
De Novo Transcriptome ◽  
Transcript Quantification ◽  
Abundance Estimates ◽  
User Friendly

Abstract Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.

scholarly journals Compacting and correcting Trinity and Oases RNA-Seq de novo assemblies

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e2988 ◽  
Author(s):  
Cédric Cabau ◽  
Frédéric Escudié ◽  
Anis Djari ◽  
Yann Guiguen ◽  
Julien Bobe ◽  
...  
Keyword(s):  
Reference Genome ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Error Rates ◽  
Rna Seq ◽  
Software Packages ◽  
Redundancy Reduction ◽  
Assembly Pipeline ◽  
Free Open Source

Background De novo transcriptome assembly of short reads is now a common step in expression analysis of organisms lacking a reference genome sequence. Several software packages are available to perform this task. Even if their results are of good quality it is still possible to improve them in several ways including redundancy reduction or error correction. Trinity and Oases are two commonly used de novo transcriptome assemblers. The contig sets they produce are of good quality. Still, their compaction (number of contigs needed to represent the transcriptome) and their quality (chimera and nucleotide error rates) can be improved. Results We built a de novo RNA-Seq Assembly Pipeline (DRAP) which wraps these two assemblers (Trinity and Oases) in order to improve their results regarding the above-mentioned criteria. DRAP reduces from 1.3 to 15 fold the number of resulting contigs of the assemblies depending on the read set and the assembler used. This article presents seven assembly comparisons showing in some cases drastic improvements when using DRAP. DRAP does not significantly impair assembly quality metrics such are read realignment rate or protein reconstruction counts. Conclusion Transcriptome assembly is a challenging computational task even if good solutions are already available to end-users, these solutions can still be improved while conserving the overall representation and quality of the assembly. The de novo RNA-Seq Assembly Pipeline (DRAP) is an easy to use software package to produce compact and corrected transcript set. DRAP is free, open-source and available under GPL V3 license at http://www.sigenae.org/drap.

scholarly journals rnaSPAdes: a de novo transcriptome assembler and its application to RNA-Seq data

GigaScience ◽  
2019 ◽  
Vol 8 (9) ◽  
Author(s):  
Elena Bushmanova ◽  
Dmitry Antipov ◽  
Alla Lapidus ◽  
Andrey D Prjibelski
Keyword(s):  
Rna Sequencing ◽  
De Novo ◽  
Transcriptome Assembly ◽  
The Novel ◽  
Rna Seq ◽  
De Novo Transcriptome ◽  
Weak Points ◽  
Transcriptome Reconstruction ◽  
Evaluation Approaches ◽  
Genome Assembler

Abstract Background The possibility of generating large RNA-sequencing datasets has led to development of various reference-based and de novo transcriptome assemblers with their own strengths and limitations. While reference-based tools are widely used in various transcriptomic studies, their application is limited to the organisms with finished and well-annotated genomes. De novo transcriptome reconstruction from short reads remains an open challenging problem, which is complicated by the varying expression levels across different genes, alternative splicing, and paralogous genes. Results Herein we describe the novel transcriptome assembler rnaSPAdes, which has been developed on top of the SPAdes genome assembler and explores computational parallels between assembly of transcriptomes and single-cell genomes. We also present quality assessment reports for rnaSPAdes assemblies, compare it with modern transcriptome assembly tools using several evaluation approaches on various RNA-sequencing datasets, and briefly highlight strong and weak points of different assemblers. Conclusions Based on the performed comparison between different assembly methods, we infer that it is not possible to detect the absolute leader according to all quality metrics and all used datasets. However, rnaSPAdes typically outperforms other assemblers by such important property as the number of assembled genes and isoforms, and at the same time has higher accuracy statistics on average comparing to the closest competitors.

scholarly journals De novo identification, differential analysis and functional annotation of SNPs from RNA-seq data in non-model species

2015 ◽  
Author(s):  
Helene Lopez Maestre ◽  
Lilia Brinza ◽  
Camille Marchet ◽  
Janice Kielbassa ◽  
Sylvere Bastien ◽  
...  
Keyword(s):  
Reference Genome ◽  
De Novo ◽  
Association Studies ◽  
Nucleotide Polymorphisms ◽  
Differential Analysis ◽  
Rna Seq ◽  
Model Species ◽  
Established Method ◽  
Single Nucleotide ◽  
Similar Accuracy

SNPs (Single Nucleotide Polymorphisms) are genetic markers whose precise identification is a prerequisite for association studies. Methods to identify them are currently well developed for model species, but rely on the availability of a (good) reference genome, and therefore cannot be applied to non-model species. They are also mostly tailored for whole genome (re-)sequencing experiments, whereas in many cases, transcriptome sequencing can be used as a cheaper alternative which already enables to identify SNPs located in transcribed regions. In this paper, we propose a method that identifies, quantifies and annotates SNPs without any reference genome, using RNA-seq data only. Individuals can be pooled prior to sequencing, if not enough material is available for sequencing from one individual. Using human RNA-seq data, we first compared the performance of our method with G<small>ATK</small>, a well established method that requires a reference genome. We showed that both methods predict SNPs with similar accuracy. We then validated experimentally the predictions of our method using RNA-seq data from two non-model species. The method can be used for any species to annotate SNPs and predict their impact on proteins. We further enable to test for the association of the identified SNPs with a phenotype of interest.

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