Browse
Submit Data
Databases
API
Help

Dataset Information

31 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Whole genome sequencing data and de novo draft assemblies for 66 teleost species.

ABSTRACT: Teleost fishes comprise more than half of all vertebrate species, yet genomic data are only available for 0.2% of their diversity. Here, we present whole genome sequencing data for 66 new species of teleosts, vastly expanding the availability of genomic data for this important vertebrate group. We report on de novo assemblies based on low-coverage (9-39×) sequencing and present detailed methodology for all analyses. To facilitate further utilization of this data set, we present statistical analyses of the gene space completeness and verify the expected phylogenetic position of the sequenced genomes in a large mitogenomic context. We further present a nuclear marker set used for phylogenetic inference and evaluate each gene tree in relation to the species tree to test for homogeneity in the phylogenetic signal. Collectively, these analyses illustrate the robustness of this highly diverse data set and enable extensive reuse of the selected phylogenetic markers and the genomic data in general. This data set covers all major teleost lineages and provides unprecedented opportunities for comparative studies of teleosts.

SUBMITTER: Malmstrom M

PROVIDER: S-EPMC5240625 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Evaluation of de novo transcriptome assemblies from RNA-Seq data.

Project description:De novo RNA-Seq assembly facilitates the study of transcriptomes for species without sequenced genomes, but it is challenging to select the most accurate assembly in this context. To address this challenge, we developed a model-based score, RSEM-EVAL, for evaluating assemblies when the ground truth is unknown. We show that RSEM-EVAL correctly reflects assembly accuracy, as measured by REF-EVAL, a refined set of ground-truth-based scores that we also developed. Guided by RSEM-EVAL, we assembled the transcriptome of the regenerating axolotl limb; this assembly compares favorably to a previous assembly. A software package implementing our methods, DETONATE, is freely available at http://deweylab.biostat.wisc.edu/detonate.

| S-EPMC4298084 | biostudies-literature

Norgal: extraction and de novo assembly of mitochondrial DNA from whole-genome sequencing data.

Project description:Whole-genome sequencing (WGS) projects provide short read nucleotide sequences from nuclear and possibly organelle DNA depending on the source of origin. Mitochondrial DNA is present in animals and fungi, while plants contain DNA from both mitochondria and chloroplasts. Current techniques for separating organelle reads from nuclear reads in WGS data require full reference or partial seed sequences for assembling.Norgal (de Novo ORGAneLle extractor) avoids this requirement by identifying a high frequency subset of k-mers that are predominantly of mitochondrial origin and performing a de novo assembly on a subset of reads that contains these k-mers. The method was applied to WGS data from a panda, brown algae seaweed, butterfly and filamentous fungus. We were able to extract full circular mitochondrial genomes and obtained sequence identities to the reference sequences in the range from 98.5 to 99.5%. We also assembled the chloroplasts of grape vines and cucumbers using Norgal together with seed-based de novo assemblers.Norgal is a pipeline that can extract and assemble full or partial mitochondrial and chloroplast genomes from WGS short reads without prior knowledge. The program is available at: https://bitbucket.org/kosaidtu/norgal .

| S-EPMC5699183 | biostudies-literature

The draft nuclear genome assembly of Eucalyptus pauciflora: a pipeline for comparing de novo assemblies.

Project description:Eucalyptus pauciflora (the snow gum) is a long-lived tree with high economic and ecological importance. Currently, little genomic information for E. pauciflora is available. Here, we sequentially assemble the genome of Eucalyptus pauciflora with different methods, and combine multiple existing and novel approaches to help to select the best genome assembly. We generated high coverage of long- (Nanopore, 174×) and short- (Illumina, 228×) read data from a single E. pauciflora individual and compared assemblies from 5 assemblers (Canu, SMARTdenovo, Flye, Marvel, and MaSuRCA) with different read lengths (1 and 35 kb minimum read length). A key component of our approach is to keep a randomly selected collection of ∼10% of both long and short reads separated from the assemblies to use as a validation set for assessing assemblies. Using this validation set along with a range of existing tools, we compared the assemblies in 8 ways: contig N50, BUSCO scores, LAI (long terminal repeat assembly index) scores, assembly ploidy, base-level error rate, CGAL (computing genome assembly likelihoods) scores, structural variation, and genome sequence similarity. Our result showed that MaSuRCA generated the best assembly, which is 594.87 Mb in size, with a contig N50 of 3.23 Mb, and an estimated error rate of ∼0.006 errors per base. We report a draft genome of E. pauciflora, which will be a valuable resource for further genomic studies of eucalypts. The approaches for assessing and comparing genomes should help in assessing and choosing among many potential genome assemblies from a single dataset.

| S-EPMC6939829 | biostudies-literature

De novo whole genome sequencing data of two mangrove-isolated microalgae from Terengganu coastal waters.

Project description:Interest in harvesting potential benefits from microalgae renders it necessary to have the many ecological niches of a single species to be investigated. This dataset comprises de novo whole genome assembly of two mangrove-isolated microalgae (from division Chlorophyta); Chlorella vulgaris UMT-M1 and Messastrum gracile SE-MC4 from Universiti Malaysia Terengganu, Malaysia. Library runs were carried out with 2 × 150 base paired-ends reads, whereas sequencing was conducted using Illumina Novaseq 2500 platform. Sequencing yielded raw reads amounting to ∼11 Gb in total bases for both species and was further assembled de novo. Genome assembly resulted in a 50.15 Mbp and 60.83 Mbp genome size for UMT-M1 and SE-MC4, respectively. All filtered and assembled genomic data sequences have been submitted to National Centre for Biotechnology Information (NCBI) and can be located at DDBJ/ENA/GenBank under the accession of VJNP00000000 (UMT-M1) and VIYE00000000 (SE-MC4).

| S-EPMC6838400 | biostudies-literature

De novo genome assemblies of butterflies.

Project description:BackgroundThe availability of thousands of genomes has enabled new advancements in biology. However, many genomes have not been investigated for their quality. Here we examine quality trends in a taxonomically diverse and well-known group, butterflies (Papilionoidea), and provide draft, de novo assemblies for all available butterfly genomes. Owing to massive genome sequencing investment and taxonomic curation, this is an excellent group to explore genome quality.FindingsWe provide de novo assemblies for all 822 available butterfly genomes and interpret their quality in terms of completeness and continuity. We identify the 50 highest quality genomes across butterflies and conclude that the ringlet, Aphantopus hyperantus, has the highest quality genome. Our post-processing of draft genome assemblies identified 118 butterfly genomes that should not be reused owing to contamination or extremely low quality. However, many draft genomes are of high utility, especially because permissibility of low-quality genomes is dependent on the objective of the study. Our assemblies will serve as a key resource for papilionid genomics, especially for researchers without computational resources.ConclusionsQuality metrics and assemblies are typically presented with annotated genome accessions but rarely with de novo genomes. We recommend that studies presenting genome sequences provide the assembly and some metrics of quality because quality will significantly affect downstream results. Transparency in quality metrics is needed to improve the field of genome science and encourage data reuse.

| S-EPMC8170690 | biostudies-literature

De-novo assemblies of mcr sequencing datasets

Project description:De-novo assemblies of mcr sequencing datasets

| PRJEB61403 | ENA

Whole-Exome Sequencing Identifies Damaging de novo Variants in Anencephalic Cases.

Project description:Background:Anencephaly is a lethal neural tube defect (NTD). Although variants in several genes have been implicated in the development of anencephaly, a more complete picture of variants in the genome, especially de novo variants (DNVs), remains unresolved. We aim to identify DNVs that play an important role in the development of anencephaly by performing whole-exome DNA sequencing (WES) of proband-parent trios. Results:A total of 13 DNVs were identified in 8 anencephaly trios by WES, including two loss of function (LoF) variants detected in pLI > 0.9 genes (SPHKAP, c.2629_2633del, and NCOR1, p.Y1907X). Damaging DNVs were identified in 61.5% (8/13) of the anencephalic cases. Independent validation was conducted in an additional 502 NTD cases. Gene inactivation using targeted morpholino antisense oligomers and rescue assays were conducted in zebrafish, and transfection expression in HEK293T cells. Four DNVs in four cases were identified and predicted to alter protein function, including p.R328Q in WD repeat domain phosphoinositide-interacting 1 (WIPI1). Three variants, p.G313R, p.T418M, and p.L406P, in the WIPI1 gene were identified from the independent replication cohort consisting of 502 cases. Functional analysis suggested that the wipi1 p.L406P and p.R328Q variants most likely displayed loss-of-function effects during embryonic development. Conclusion:De novo damaging variants are the main culprit for majority of anencephalic cases. Missense variants in WIPI1 may play a role in the genetic etiology of anencephaly, and LoF variants in SPHKAP and NCOR1 may also contribute to anencephaly. These findings add to our existing understanding of the genetic mechanisms of NTD formation.

| S-EPMC6896715 | biostudies-literature

HGSVC3 - hifiasm De Novo Assemblies

Project description:HGSVC3 - hifiasm De Novo Assemblies

| PRJEB83624 | ENA

HGSVC3 - Verkko De Novo Assemblies

Project description:HGSVC3 - Verkko De Novo Assemblies

| PRJEB76276 | ENA

De novo species identification using 16S rRNA gene nanopore sequencing.

Project description:Nanopore sequencing is rapidly becoming more popular for use in various microbiota-based applications. Major limitations of current approaches are that they do not enable de novo species identification and that they cannot be used to verify species assignments. This severely limits applicability of the nanopore sequencing technology in taxonomic applications. Here, we demonstrate the possibility of de novo species identification and verification using hexamer frequencies in combination with k-means clustering for nanopore sequencing data. The approach was tested on the human infant gut microbiota of 3-month-old infants. Using the hexamer k-means approach we identified two new low abundant species associated with vaginal delivery. In addition, we confirmed both the vaginal delivery association for two previously identified species and the overall high levels of bifidobacteria. Taxonomic assignments were further verified by mock community analyses. Therefore, we believe our de novo species identification approach will have widespread application in analyzing microbial communities in the future.

| S-EPMC7585375 | 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