Browse
Submit Data
Databases
API
Help

Dataset Information

16 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Pincho: A Modular Approach to High Quality De Novo Transcriptomics.

ABSTRACT: Transcriptomic reconstructions without reference (i.e., de novo) are common for data samples derived from non-model biological systems. These assemblies involve massive parallel short read sequence reconstructions from experiments, but they usually employ ad-hoc bioinformatic workflows that exhibit limited standardization and customization. The increasing number of transcriptome assembly software continues to provide little room for standardization which is exacerbated by the lack of studies on modularity that compare the effects of assembler synergy. We developed a customizable management workflow for de novo transcriptomics that includes modular units for short read cleaning, assembly, validation, annotation, and expression analysis by connecting twenty-five individual bioinformatic tools. With our software tool, we were able to compare the assessment scores based on 129 distinct single-, bi- and tri-assembler combinations with diverse k-mer size selections. Our results demonstrate a drastic increase in the quality of transcriptome assemblies with bi- and tri- assembler combinations. We aim for our software to improve de novo transcriptome reconstructions for the ever-growing landscape of RNA-seq data derived from non-model systems. We offer guidance to ensure the most complete transcriptomic reconstructions via the inclusion of modular multi-assembly software controlled from a single master console.

SUBMITTER: Ortiz R

PROVIDER: S-EPMC8304035 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

The Stability Landscape of de novo TIM Barrels Explored by a Modular Design Approach.

Project description:The ability to design stable proteins with custom-made functions is a major goal in biochemistry with practical relevance for our environment and society. Understanding and manipulating protein stability provide crucial information on the molecular determinants that modulate structure and stability, and expand the applications of de novo proteins. Since the (β/⍺)8-barrel or TIM-barrel fold is one of the most common functional scaffolds, in this work we designed a collection of stable de novo TIM barrels (DeNovoTIMs), using a computational fixed-backbone and modular approach based on improved hydrophobic packing of sTIM11, the first validated de novo TIM barrel, and subjected them to a thorough folding analysis. DeNovoTIMs navigate a region of the stability landscape previously uncharted by natural TIM barrels, with variations spanning 60 degrees in melting temperature and 22 kcal per mol in conformational stability throughout the designs. Significant non-additive or epistatic effects were observed when stabilizing mutations from different regions of the barrel were combined. The molecular basis of epistasis in DeNovoTIMs appears to be related to the extension of the hydrophobic cores. This study is an important step towards the fine-tuned modulation of protein stability by design.

| S-EPMC8404036 | biostudies-literature

A De Novo Transcriptomics Approach Reveals Genes Involved in Thrips Tabaci Resistance to Spinosad.

Project description:The onion thrip, Thrips tabaci (Thysanoptera: Thripidae) is a major polyphagous pest that attacks a wide range of economically important crops, especially Allium species. The thrip's damage can result in yield loss of up to 60% in onions (Allium cepa). In the past few decades, thrip resistance to insecticides with various modes of actions have been documented. These include resistance to spinosad, a major active compound used against thrips, which was reported from Israel. Little is known about the molecular mechanisms underlying spinosad resistance in T. tabaci. We attempted to characterize the mechanisms involved in resistance to spinosad using quantitative transcriptomics. Susceptible (LC50 = 0.6 ppm) and resistant (LC50 = 23,258 ppm) thrip populations were collected from Israel. An additional resistant population (LC50 = 117 ppm) was selected in the laboratory from the susceptible population. De novo transcriptome analysis on the resistant and susceptible population was conducted to identify differently expressed genes (DGEs) that might be involved in the resistance against spinosad. In this analysis, 25,552 unigenes were sequenced, assembled, and functionally annotated, and more than 1500 DGEs were identified. The expression levels of candidate genes, which included cytochrome P450 and vittelogenin, were validated using quantitative RT-PCR. The cytochrome P450 expression gradually increased with the increase of the resistance. Higher expression levels of vitellogenin in the resistant populations were correlated with higher fecundity, suggesting a positive effect of the resistance on resistant populations. This research provides a novel genetic resource for onion thrips and a comprehensive molecular examination of resistant populations to spinosad. Those resources are important for future studies concerning thrips and resistance in insect pests regarding agriculture.

| S-EPMC7828677 | biostudies-literature

De novo design of modular and tunable protein biosensors.

Project description:Naturally occurring protein switches have been repurposed for the development of biosensors and reporters for cellular and clinical applications1. However, the number of such switches is limited, and reengineering them is challenging. Here we show that a general class of protein-based biosensors can be created by inverting the flow of information through de novo designed protein switches in which the binding of a peptide key triggers biological outputs of interest2. The designed sensors are modular molecular devices with a closed dark state and an open luminescent state; analyte binding drives the switch from the closed to the open state. Because the sensor is based on the thermodynamic coupling of analyte binding to sensor activation, only one target binding domain is required, which simplifies sensor design and allows direct readout in solution. We create biosensors that can sensitively detect the anti-apoptosis protein BCL-2, the IgG1 Fc domain, the HER2 receptor, and Botulinum neurotoxin B, as well as biosensors for cardiac troponin I and an anti-hepatitis B virus antibody with the high sensitivity required to detect these molecules clinically. Given the need for diagnostic tools to track the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)3, we used the approach to design sensors for the SARS-CoV-2 spike protein and antibodies against the membrane and nucleocapsid proteins. The former, which incorporates a de novo designed spike receptor binding domain (RBD) binder4, has a limit of detection of 15 pM and a luminescence signal 50-fold higher than the background level. The modularity and sensitivity of the platform should enable the rapid construction of sensors for a wide range of analytes, and highlights the power of de novo protein design to create multi-state protein systems with new and useful functions.

| S-EPMC8074680 | biostudies-literature

A general approach for discriminative de novo motif discovery from high-throughput data.

Project description:De novo motif discovery has been an important challenge of bioinformatics for the past two decades. Since the emergence of high-throughput techniques like ChIP-seq, ChIP-exo and protein-binding microarrays (PBMs), the focus of de novo motif discovery has shifted to runtime and accuracy on large data sets. For this purpose, specialized algorithms have been designed for discovering motifs in ChIP-seq or PBM data. However, none of the existing approaches work perfectly for all three high-throughput techniques. In this article, we propose Dimont, a general approach for fast and accurate de novo motif discovery from high-throughput data. We demonstrate that Dimont yields a higher number of correct motifs from ChIP-seq data than any of the specialized approaches and achieves a higher accuracy for predicting PBM intensities from probe sequence than any of the approaches specifically designed for that purpose. Dimont also reports the expected motifs for several ChIP-exo data sets. Investigating differences between in vitro and in vivo binding, we find that for most transcription factors, the motifs discovered by Dimont are in good accordance between techniques, but we also find notable exceptions. We also observe that modeling intra-motif dependencies may increase accuracy, which indicates that more complex motif models are a worthwhile field of research.

| S-EPMC3834837 | biostudies-other

High quality de novo sequencing and assembly of the Saccharomyces arboricolus genome.

Project description:Comparative genomics is a formidable tool to identify functional elements throughout a genome. In the past ten years, studies in the budding yeast Saccharomyces cerevisiae and a set of closely related species have been instrumental in showing the benefit of analyzing patterns of sequence conservation. Increasing the number of closely related genome sequences makes the comparative genomics approach more powerful and accurate.Here, we report the genome sequence and analysis of Saccharomyces arboricolus, a yeast species recently isolated in China, that is closely related to S. cerevisiae. We obtained high quality de novo sequence and assemblies using a combination of next generation sequencing technologies, established the phylogenetic position of this species and considered its phenotypic profile under multiple environmental conditions in the light of its gene content and phylogeny.We suggest that the genome of S. arboricolus will be useful in future comparative genomics analysis of the Saccharomyces sensu stricto yeasts.

| S-EPMC3599269 | biostudies-literature

A high-quality de novo genome assembly for clapper rail (Rallus crepitans).

Project description:The clapper rail (Rallus crepitans), of the family Rallidae, is a secretive marsh bird species that is adapted for high salinity habitats. They are very similar in appearance to the closely related king rail (R. elegans), but while king rails are limited primarily to freshwater marshes, clapper rails are highly adapted to tolerate salt marshes. Both species can be found in brackish marshes where they freely hybridize, but the distribution of their respective habitats precludes the formation of a continuous hybrid zone and secondary contact can occur repeatedly. This system, thus, provides unique opportunities to investigate the underlying mechanisms driving their differential salinity tolerance as well as the maintenance of the species boundary between the 2 species. To facilitate these studies, we assembled a de novo reference genome assembly for a female clapper rail. Chicago and HiC libraries were prepared as input for the Dovetail HiRise pipeline to scaffold the genome. The pipeline, however, did not recover the Z chromosome so a custom script was used to assemble the Z chromosome. We generated a near chromosome level assembly with a total length of 994.8 Mb comprising 13,226 scaffolds. The assembly had a scaffold N50 was 82.7 Mb, L50 of four, and had a BUSCO completeness score of 92%. This assembly is among the most contiguous genomes among the species in the family Rallidae. It will serve as an important tool in future studies on avian salinity tolerance, interspecific hybridization, and speciation.

| S-EPMC10484055 | biostudies-literature

A high-throughput de novo sequencing approach for shotgun proteomics using high-resolution tandem mass spectrometry.

Project description:BACKGROUND: High-resolution tandem mass spectra can now be readily acquired with hybrid instruments, such as LTQ-Orbitrap and LTQ-FT, in high-throughput shotgun proteomics workflows. The improved spectral quality enables more accurate de novo sequencing for identification of post-translational modifications and amino acid polymorphisms. RESULTS: In this study, a new de novo sequencing algorithm, called Vonode, has been developed specifically for analysis of such high-resolution tandem mass spectra. To fully exploit the high mass accuracy of these spectra, a unique scoring system is proposed to evaluate sequence tags based primarily on mass accuracy information of fragment ions. Consensus sequence tags were inferred for 11,422 spectra with an average peptide length of 5.5 residues from a total of 40,297 input spectra acquired in a 24-hour proteomics measurement of Rhodopseudomonas palustris. The accuracy of inferred consensus sequence tags was 84%. According to our comparison, the performance of Vonode was shown to be superior to the PepNovo v2.0 algorithm, in terms of the number of de novo sequenced spectra and the sequencing accuracy. CONCLUSIONS: Here, we improved de novo sequencing performance by developing a new algorithm specifically for high-resolution tandem mass spectral data. The Vonode algorithm is freely available for download at http://compbio.ornl.gov/Vonode.

| S-EPMC2838866 | biostudies-other

Uncovering de novo gene birth in yeast using deep transcriptomics.

Project description:De novo gene origination has been recently established as an important mechanism for the formation of new genes. In organisms with a large genome, intergenic and intronic regions provide plenty of raw material for new transcriptional events to occur, but little is know about how de novo transcripts originate in more densely-packed genomes. Here, we identify 213 de novo originated transcripts in Saccharomyces cerevisiae using deep transcriptomics and genomic synteny information from multiple yeast species grown in two different conditions. We find that about half of the de novo transcripts are expressed from regions which already harbor other genes in the opposite orientation; these transcripts show similar expression changes in response to stress as their overlapping counterparts, and some appear to translate small proteins. Thus, a large fraction of de novo genes in yeast are likely to co-evolve with already existing genes.

| S-EPMC7841160 | biostudies-literature

Next generation sequencing and de novo transcriptomics to study gene evolution.

Project description:BACKGROUND:Studying gene evolution in non-model species by PCR-based approaches is limited to highly conserved genes. The plummeting cost of next generation sequencing enables the application of de novo transcriptomics to any species. RESULTS:Here we describe how to apply de novo transcriptomics to pursue the evolution of a single gene of interest. We follow a rapidly evolving seed protein that encodes small, stable peptides. We use software that needs limited bioinformatics background and assemble four de novo seed transcriptomes. To demonstrate the quality of the assemblies, we confirm the predicted genes at the peptide level on one species which has over ten copies of our gene of interest. We explain strategies that favour assembly of low abundance genes, what assembly parameters help capture the maximum number of transcripts, how to develop a suite of control genes to test assembly quality and we compare several sequence depths to optimise cost and data volume. CONCLUSIONS:De novo transcriptomics is an effective approach for studying gene evolution in species for which genome support is lacking.

| S-EPMC4216380 | biostudies-literature

De novo clustering of long reads by gene from transcriptomics data.

Project description:Long-read sequencing currently provides sequences of several thousand base pairs. It is therefore possible to obtain complete transcripts, offering an unprecedented vision of the cellular transcriptome. However the literature lacks tools for de novo clustering of such data, in particular for Oxford Nanopore Technologies reads, because of the inherent high error rate compared to short reads. Our goal is to process reads from whole transcriptome sequencing data accurately and without a reference genome in order to reliably group reads coming from the same gene. This de novo approach is therefore particularly suitable for non-model species, but can also serve as a useful pre-processing step to improve read mapping. Our contribution both proposes a new algorithm adapted to clustering of reads by gene and a practical and free access tool that allows to scale the complete processing of eukaryotic transcriptomes. We sequenced a mouse RNA sample using the MinION device. This dataset is used to compare our solution to other algorithms used in the context of biological clustering. We demonstrate that it is the best approach for transcriptomics long reads. When a reference is available to enable mapping, we show that it stands as an alternative method that predicts complementary clusters.

| S-EPMC6326815 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data