Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Diet of Sable Antelope in Texas analyzed via microhistology and Illumina metabarcoding

ABSTRACT: Diet of Sable Antelope

PROVIDER: PRJEB23870 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Sable antelope coronavirus US/OH1/2003

Project description:Sable antelope coronavirus US/OH1/2003

| PRJNA18591 | ENA

Project description:metagenome data of sable antelope feces

| PRJNA738686 | ENA

Hippotragus niger

Project description:Whole-genome re-sequencing of five sable antelope

| PRJNA403774 | ENA

Barn Swallow diet - metabarcoding analyzis

Project description:Barn Swallow diet - metabarcoding analyzis

| PRJEB46476 | ENA

Barn Swallow diet - metabarcoding analyzis

Project description:Barn Swallow diet - metabarcoding analyzis

| PRJEB46477 | ENA

An Illumina metabarcoding pipeline for fungi.

Project description:High-throughput metabarcoding studies on fungi and other eukaryotic microorganisms are rapidly becoming more frequent and more complex, requiring researchers to handle ever increasing amounts of raw sequence data. Here, we provide a flexible pipeline for pruning and analyzing fungal barcode (ITS rDNA) data generated as paired-end reads on Illumina MiSeq sequencers. The pipeline presented includes specific steps fine-tuned for ITS, that are mostly missing from pipelines developed for prokaryotes. It (1) employs state of the art programs and follows best practices in fungal high-throughput metabarcoding; (2) consists of modules and scripts easily modifiable by the user to ensure maximum flexibility with regard to specific needs of a project or future methodological developments; and (3) is straightforward to use, also in classroom settings. We provide detailed descriptions and revision techniques for each step, thus giving the user maximum control over data treatment and avoiding a black-box approach. Employing this pipeline will improve and speed up the tedious and error-prone process of cleaning fungal Illumina metabarcoding data.

| S-EPMC4113289 | biostudies-literature

Proteomics data for identification of Saiga antelope horn

Project description:Proteomics data for identification of Saiga antelope horn

2024-05-09 | PXD052162 |

Gut metagenomic raw data of 68 Tibetan antelope

Project description:Gut metagenomic raw data of 68 Tibetan antelope Metagenome

| PRJNA1257558 | ENA

DNA metabarcoding of Podarcis lilfordi diet

Project description:DNA metabarcoding of Podarcis lilfordi diet

| PRJNA777557 | ENA

Evaluating metabarcoding to analyse diet composition of species foraging in anthropogenic landscapes using Ion Torrent and Illumina sequencing.

Project description:DNA metabarcoding of faecal samples is being successfully used to study the foraging niche of species. We assessed the ability of two benchtop high-throughput sequencing (HTS) platforms, to identify a large taxonomic array of food items from domestic cats Felis silvestris catus, including prey and human-related food taxa (pet food and leftovers leaving undetectable solid remains in faeces). Scats from a captive feeding trial (n = 41) and from free-ranging individuals (n = 326) were collected and analysed using a cytb mini-barcode in independent PCR replicates on the Ion PGM and the MiSeq platforms. Outputs from MiSeq were more sensitive and reproducible than those from Ion PGM due to a higher sequencing depth and sequence quality on MiSeq. DNA from intact prey taxa was detected more often (82% of the expected occurrences) than DNA from pet food (54%) and raw fish and meat (31%). We assumed that this variability was linked to different degree of DNA degradation: The Ion PGM detected significantly less human-linked food, birds, field voles, murids and shrews in the field-collected samples than the MiSeq platform. Pooling the replicates from both platforms and filtering the data allowed identification of at least one food item in 87.4% of the field-collected samples. Our DNA metabarcoding approach identified 29 prey taxa, of which 25 to species level (90% of items) including 9 rodents, 3 insectivores, 12 birds and 1 reptile and 33 human-related food taxa of which 23 were identified to genus level (75% of items). Our results demonstrate that using HTS platforms such as MiSeq, which provide reads of sufficiently high quantity and quality, with sufficient numbers of technical replicates, is a robust and non-invasive approach for further dietary studies on animals foraging on a wide range of food items in anthropogenic landscapes.

| S-EPMC6244006 | 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