scholarly journals De novo transcriptomes of 14 gammarid individuals for proteogenomic analysis of seven taxonomic groups

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Yannick Cogne ◽  
Davide Degli-Esposti ◽  
Olivier Pible ◽  
Duarte Gouveia ◽  
Adeline François ◽  
...  
Keyword(s):  
Aquatic Ecosystems ◽  
Molecular Diversity ◽  
De Novo ◽  
Model Organisms ◽  
Rna Seq ◽  
Specific Expression ◽  
Gammarus Fossarum ◽  
Male Individual ◽  
Taxonomic Groups ◽  
Whole Transcriptome

Abstract Gammarids are amphipods found worldwide distributed in fresh and marine waters. They play an important role in aquatic ecosystems and are well established sentinel species in ecotoxicology. In this study, we sequenced the transcriptomes of a male individual and a female individual for seven different taxonomic groups belonging to the two genera Gammarus and Echinogammarus: Gammarus fossarum A, G. fossarum B, G. fossarum C, Gammarus wautieri, Gammarus pulex, Echinogammarus berilloni, and Echinogammarus marinus. These taxa were chosen to explore the molecular diversity of transcribed genes of genotyped individuals from these groups. Transcriptomes were de novo assembled and annotated. High-quality assembly was confirmed by BUSCO comparison against the Arthropod dataset. The 14 RNA-Seq-derived protein sequence databases proposed here will be a significant resource for proteogenomics studies of these ecotoxicologically relevant non-model organisms. These transcriptomes represent reliable reference sequences for whole-transcriptome and proteome studies on other gammarids, for primer design to clone specific genes or monitor their specific expression, and for analyses of molecular differences between gammarid species.

scholarly journals Identification and Expression Analysis of the Genes Involved in the Raffinose Family Oligosaccharides Pathway of Phaseolus vulgaris and Glycine max

Plants ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1465
Author(s):  
Ramon de Koning ◽  
Raphaël Kiekens ◽  
Mary Esther Muyoka Toili ◽  
Geert Angenon
Keyword(s):  
Common Bean ◽  
Seed Development ◽  
Expression Analysis ◽  
De Novo ◽  
Expression Patterns ◽  
Gene Families ◽  
Rna Seq ◽  
Raffinose Family Oligosaccharides ◽  
Specific Expression ◽  
Raffinose Synthase

Raffinose family oligosaccharides (RFO) play an important role in plants but are also considered to be antinutritional factors. A profound understanding of the galactinol and RFO biosynthetic gene families and the expression patterns of the individual genes is a prerequisite for the sustainable reduction of the RFO content in the seeds, without compromising normal plant development and functioning. In this paper, an overview of the annotation and genetic structure of all galactinol- and RFO biosynthesis genes is given for soybean and common bean. In common bean, three galactinol synthase genes, two raffinose synthase genes and one stachyose synthase gene were identified for the first time. To discover the expression patterns of these genes in different tissues, two expression atlases have been created through re-analysis of publicly available RNA-seq data. De novo expression analysis through an RNA-seq study during seed development of three varieties of common bean gave more insight into the expression patterns of these genes during the seed development. The results of the expression analysis suggest that different classes of galactinol- and RFO synthase genes have tissue-specific expression patterns in soybean and common bean. With the obtained knowledge, important galactinol- and RFO synthase genes that specifically play a key role in the accumulation of RFOs in the seeds are identified. These candidate genes may play a pivotal role in reducing the RFO content in the seeds of important legumes which could improve the nutritional quality of these beans and would solve the discomforts associated with their consumption.

scholarly journals De novo gonad transcriptome analysis of the common littoral shrimp Palaemon serratus: novel insights into sex-related genes

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Inés González-Castellano ◽  
Chiara Manfrin ◽  
Alberto Pallavicini ◽  
Andrés Martínez-Lage
Keyword(s):  
Transcriptome Analysis ◽  
De Novo ◽  
Expression Patterns ◽  
Gonadal Development ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Illumina Hiseq ◽  
Specific Expression ◽  
Development Processes ◽  
The Common

Abstract Background The common littoral shrimp Palaemon serratus is an economically important decapod resource in some European communities. Aquaculture practices prevent the genetic deterioration of wild stocks caused by overfishing and at the same time enhance the production. The biotechnological manipulation of sex-related genes has the proved potential to improve the aquaculture production but the scarcity of genomic data about P. serratus hinders these applications. RNA-Seq analysis has been performed on ovary and testis samples to generate a reference gonadal transcriptome. Differential expression analyses were conducted between three ovary and three testis samples sequenced by Illumina HiSeq 4000 PE100 to reveal sex-related genes with sex-biased or sex-specific expression patterns. Results A total of 224.5 and 281.1 million paired-end reads were produced from ovary and testis samples, respectively. De novo assembly of ovary and testis trimmed reads yielded a transcriptome with 39,186 transcripts. The 29.57% of the transcriptome retrieved at least one annotation and 11,087 differentially expressed genes (DEGs) were detected between ovary and testis replicates. Six thousand two hundred seven genes were up-regulated in ovaries meanwhile 4880 genes were up-regulated in testes. Candidate genes to be involved in sexual development and gonadal development processes were retrieved from the transcriptome. These sex-related genes were discussed taking into account whether they were up-regulated in ovary, up-regulated in testis or not differentially expressed between gonads and in the framework of previous findings in other crustacean species. Conclusions This is the first transcriptome analysis of P. serratus gonads using RNA-Seq technology. Interesting findings about sex-related genes from an evolutionary perspective (such as Dmrt1) and for putative future aquaculture applications (Iag or vitellogenesis genes) are reported here. We provide a valuable dataset that will facilitate further research into the reproductive biology of this shrimp.

scholarly journals A practical guide to buildde-novoassemblies for single tissues of non-model organisms: the example of a Neotropical frog

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3702 ◽  
Author(s):  
Santiago Montero-Mendieta ◽  
Manfred Grabherr ◽  
Henrik Lantz ◽  
Ignacio De la Riva ◽  
Jennifer A. Leonard ◽  
...  
Keyword(s):  
Defense Mechanisms ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Cost Effective ◽  
Model Organisms ◽  
Rna Seq ◽  
Assembly Pipeline ◽  
Wide Variability ◽  
History Of ◽  
Inexperienced User

Whole genome sequencing (WGS) is a very valuable resource to understand the evolutionary history of poorly known species. However, in organisms with large genomes, as most amphibians, WGS is still excessively challenging and transcriptome sequencing (RNA-seq) represents a cost-effective tool to explore genome-wide variability. Non-model organisms do not usually have a reference genome and the transcriptome must be assembledde-novo. We used RNA-seq to obtain the transcriptomic profile forOreobates cruralis, a poorly known South American direct-developing frog. In total, 550,871 transcripts were assembled, corresponding to 422,999 putative genes. Of those, we identified 23,500, 37,349, 38,120 and 45,885 genes present in the Pfam, EggNOG, KEGG and GO databases, respectively. Interestingly, our results suggested that genes related to immune system and defense mechanisms are abundant in the transcriptome ofO. cruralis. We also present a pipeline to assist with pre-processing, assembling, evaluating and functionally annotating ade-novotranscriptome from RNA-seq data of non-model organisms. Our pipeline guides the inexperienced user in an intuitive way through all the necessary steps to buildde-novotranscriptome assemblies using readily available software and is freely available at:https://github.com/biomendi/TRANSCRIPTOME-ASSEMBLY-PIPELINE/wiki.

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 The evaluation of RNA-Seq de novo assembly by PacBio long read sequencing

2019 ◽  
Author(s):  
Yifan Yang ◽  
Michael Gribskov
Keyword(s):  
Real Time ◽  
De Novo ◽  
Critical Issue ◽  
Evaluation Methods ◽  
Model Organisms ◽  
Rna Seq ◽  
Long Reads ◽  
Long Read ◽  
Set Up ◽  
Downstream Analysis

AbstractRNA-Seq de novo assembly is an important method to generate transcriptomes for non-model organisms before any downstream analysis. Given many great de novo assembly methods developed by now, one critical issue is that there is no consensus on the evaluation of de novo assembly methods yet. Therefore, to set up a benchmark for evaluating the quality of de novo assemblies is very critical. Addressing this challenge will help us deepen the insights on the properties of different de novo assemblers and their evaluation methods, and provide hints on choosing the best assembly sets as transcriptomes of non-model organisms for the further functional analysis. In this article, we generate a “real time” transcriptome using PacBio long reads as a benchmark for evaluating five de novo assemblers and two model-based de novo assembly evaluation methods. By comparing the de novo assmblies generated by RNA-Seq short reads with the “real time” transcriptome from the same biological sample, we find that Trinity is best at the completeness by generating more assemblies than the alternative assemblers, but less continuous and having more misassemblies; Oases is best at the continuity and specificity, but less complete; The performance of SOAPdenovo-Trans, Trans-AByss and IDBA-Tran are in between of five assemblers. For evaluation methods, DETONATE leverages multiple aspects of the assembly set and ranks the assembly set with an average performance as the best, meanwhile the contig score can serve as a good metric to select assemblies with high completeness, specificity, continuity but not sensitive to misassemblies; TransRate contig score is useful for removing misassemblies, yet often the assemblies in the optimal set is too few to be used as a transcriptome.

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 OMGene: Mutual improvement of gene models through optimisation of evolutionary conservation

2017 ◽  
Author(s):  
Michael P. Dunne ◽  
Steven Kelly
Keyword(s):  
Experimental Data ◽  
De Novo ◽  
Gene Prediction ◽  
Expression Profiles ◽  
Accurate Determination ◽  
Subcellular Localisation ◽  
Rna Seq ◽  
Gene Model ◽  
Specific Expression ◽  
Gene Models

AbstractBackgroundThe accurate determination of the genomic coordinates for a given gene – its gene model – is of vital importance to the utility of its annotation, and the accuracy of bioinformatic analyses derived from it. Currently-available methods of computational gene prediction, while on the whole successful, often disagree on the model for a given predicted gene, with some or all of the variant gene models failing to match the biologically observed structure. Many prediction methods can be bolstered by using experimental data such as RNA-seq and mass spectrometry. However, these resources are not always available, and rarely give a comprehensive portrait of an organism’s transcriptome due to temporal and tissue-specific expression profiles.ResultsOrthology between genes provides evolutionary evidence to guide the construction of gene models. OMGene (Optimise My Gene) aims to optimise gene models in the absence of experimental data by optimising the derived amino acid alignments for gene models within orthogroups. Using RNA-seq data sets from plants and fungi, considering intron/exon junction representation and exon coverage, and assessing the intra-orthogroup consistency of subcellular localisation predictions, we demonstrate the utility of OMGene for improving gene models in annotated genomes.ConclusionsWe show that significant improvements in the accuracy of gene model annotations can be made in both established and de novo annotated genomes by leveraging information from multiple species.

scholarly journals TransPi – a comprehensive TRanscriptome ANalysiS PIpeline for de novo transcriptome assembly

2021 ◽  
Author(s):  
R.E. Rivera-Vicéns ◽  
C. Garcia Escudero ◽  
N. Conci ◽  
M. Eitel ◽  
G. Wörheide
Keyword(s):  
De Novo ◽  
Transcriptome Assembly ◽  
Model Organisms ◽  
Rna Seq ◽  
Analysis Pipeline ◽  
User Input ◽  
Genome Data ◽  
Differential Gene ◽  
Transcriptomic Level ◽  
Genome Information

AbstractThe use of RNA-Seq data and the generation of de novo transcriptome assemblies have been pivotal for studies in ecology and evolution. This is distinctly true for non-model organisms, where no genome information is available; yet, studies of differential gene expression, DNA enrichment baits design, and phylogenetics can all be accomplished with the data gathered at the transcriptomic level. Multiple tools are available for transcriptome assembly, however, no single tool can provide the best assembly for all datasets. Therefore, a multi assembler approach, followed by a reduction step, is often sought to generate an improved representation of the assembly. To reduce errors in these complex analyses while at the same time attaining reproducibility and scalability, automated workflows have been essential in the analysis of RNA-Seq data. However, most of these tools are designed for species where genome data is used as reference for the assembly process, limiting their use in non-model organisms. We present TransPi, a comprehensive pipeline for de novo transcriptome assembly, with minimum user input but without losing the ability of a thorough analysis. A combination of different model organisms, kmer sets, read lengths, and read quantities were used for assessing the tool. Furthermore, a total of 49 non-model organisms, spanning different phyla, were also analyzed. Compared to approaches using single assemblers only, TransPi produces higher BUSCO completeness percentages, and a concurrent significant reduction in duplication rates. TransPi is easy to configure and can be deployed seamlessly using Conda, Docker and Singularity.

Glutton: large-scale integration of non-model organism transcriptome data for comparative analysis

2016 ◽  
Author(s):  
Alan Medlar ◽  
Laura Laakso ◽  
Andreia Miraldo ◽  
Ari Löytynoja
Keyword(s):  
Comparative Analysis ◽  
Large Scale ◽  
De Novo ◽  
Sequence Data ◽  
Model Organism ◽  
Model Organisms ◽  
Rna Seq ◽  
Reference Species ◽  
Wide Range ◽  
The Impact

AbstractHigh-throughput RNA-seq data has become ubiquitous in the study of non-model organisms, but its use in comparative analysis remains a challenge. Without a reference genome for mapping, sequence data has to be de novo assembled, producing large numbers of short, highly redundant contigs. Preparing these assemblies for comparative analyses requires the removal of redundant isoforms, assignment of orthologs and converting fragmented transcripts into gene alignments. In this article we present Glutton, a novel tool to process transcriptome assemblies for downstream evolutionary analyses. Glutton takes as input a set of fragmented, possibly erroneous transcriptome assemblies. Utilising phylogeny-aware alignment and reference data from a closely related species, it reconstructs one transcript per gene, finds orthologous sequences and produces accurate multiple alignments of coding sequences. We present a comprehensive analysis of Glutton’s performance across a wide range of divergence times between study and reference species. We demonstrate the impact choice of assembler has on both the number of alignments and the correctness of ortholog assignment and show substantial improvements over heuristic methods, without sacrificing correctness. Finally, using inference of Darwinian selection as an example of downstream analysis, we show that Glutton-processed RNA-seq data give results comparable to those obtained from full length gene sequences even with distantly related reference species. Glutton is available from http://wasabiapp.org/software/glutton/ and is licensed under the GPLv3.

scholarly journals Discovery of an evolutionarily conserved smooth muscle cell-specific lncRNA CARMN

2020 ◽  
Author(s):  
Kunzhe Dong ◽  
Jian Shen ◽  
Xiangqin He ◽  
Liang Wang ◽  
Guoqing Hu ◽  
...  
Keyword(s):  
Smooth Muscle ◽  
De Novo ◽  
Gene Expression Signature ◽  
Vascular Diseases ◽  
Cardiac Differentiation ◽  
Rna Seq ◽  
Specific Expression ◽  
Contractile Phenotype ◽  
Evolutionarily Conserved

AbstractDifferentiated vascular smooth muscle cells (VSMCs) are critical in maintaining vascular homeostasis by expressing a unique repertoire of contractile genes. Despite the well-defined coding transcriptome in differentiated VSMCs, little is known about the non-coding gene expression signature. Herein, by de novo analyzing publicly available RNA-seq and single cell RNA-seq datasets generated from different tissues and cell types, we unambiguously identified CARMN (CARdiac Mesoderm Enhancer-associated Non-coding RNA) as an evolutionarily conserved, SMC-specific lncRNA. CARMN was initially annotated as the host gene of MIR143/145 cluster and recently reported to play roles in cardiac differentiation. Here, we generated a Carmn GFP knock-in reporter mouse model and confirmed its specific expression in SMCs in vivo. In addition, we found Carmn is transcribed independently from Mir143/145 and only expressed transiently in embryonic cardiomyocytes and thereafter becomes restricted to adult SMCs in both human and mouse. Furthermore, we demonstrated that CARMN expression is not only dramatically decreased in human vascular diseases but functionally critical in maintaining VSMC contractile phenotype in vitro. In conclusion, we provided the first evidence showing that CARMN is an evolutionarily conserved SMC-specific lncRNA, down-regulated in different human vascular diseases, and a key lncRNA for maintaining SMC contractile phenotype.

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