Ontology highlight
ABSTRACT:
PROVIDER: PRJNA277030 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR1824480.fastq.gz | Fastqsanger.gz | |||
| SRR1824490.fastq.gz | Fastqsanger.gz | |||
| SRR1824490_1.fastq.gz | Fastqsanger.gz | |||
| SRR1824490_2.fastq.gz | Fastqsanger.gz | |||
| SRR1824481.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 56 |
Similar Datasets
Project description:Free-breeding dogs have occupied the Galápagos islands at least since the 1830s, however, it was not until the 1900s that dog populations grew substantially, endangering wildlife and spreading disease. In 1981, authorities sanctioned the culling of free-roaming dogs. Yet there are currently large free-roaming dog populations of unknown ancestry on the islands of Isabela and Santa Cruz, whose ancestry has never been assessed on a genome-wide scale. Thus, we performed a complete genomic analysis of the current Galápagos dog population as well as historical Galápagos dogs sampled between 1969 and 2003, testing for population structure, admixture, and shared ancestry. Our dataset included samples from 187 modern and six historical Galápagos dogs, together with whole genome sequence from over 2,000 modern purebred and village dogs. Our results indicate that modern Galápagos dogs are recently admixed with purebred dogs but show no evidence of a population bottleneck related to the culling. Additionally, IBD analyses reveal evidence of shared shepherd-dog ancestry in the historical Galápagos dogs. Overall, our results demonstrate that the 1980s culling of dogs was ineffective in controlling population size and did little to reduce genetic diversity, instead producing a stable and expanding population with genomic signatures of historical dogs remaining today. The insights from this study can be used to improve population control strategies for the Galápagos Islands and other endangered endemic communities worldwide.
2024-10-01 | GSE276576 | GEO
Project description:The Kashmiri population is an ethno-linguistic group that resides in the Kashmir Valley in northern India. A longstanding hypothesis is that this population derives ancestry from Jewish and/or Greek sources. There is historical and archaeological evidence of ancient Greek presence in India and Kashmir. Further, some historical accounts suggest ancient Hebrew ancestry as well. To date, it has not been determined whether signatures of Greek or Jewish admixture can be detected in the Kashmiri population. Using genome-wide genotyping and admixture detection methods, we determined there are no significant or substantial signs of Greek or Jewish admixture in modern-day Kashmiris. The ancestry of Kashmiri Tibetans was also determined, which showed signs of admixture with populations from northern India and west Eurasia. These results contribute to our understanding of the existing population structure in northern India and its surrounding geographical areas.
2016-08-16 | GSE85594 | GEO
Project description:How and when the Americas were populated remains contentious. Using ancient and modern genome-wide data, we find that the ancestors of all present-day Native Americans, including Athabascans and Amerindians, entered the Americas as a single migration wave from Siberia no earlier than 23 thousand years ago (KYA), and after no more than 8,000-year isolation period in Beringia. Native Americans diversified into two basal genetic branches around 13 KYA, one in North and South America and the other restricted to North America. Subsequent gene flow resulted in some Native Americans sharing ancestry with present-day East Asians and Australo-Melanesians, the latter possibly through the ancestors of Aleutian Islanders. Putative relict populations in South America, including the historical Pericúes and Fuego-Patagonians, are not directly related to modern Australo-Melanesians.
2015-07-20 | GSE70987 | GEO
Project description:Natural history museum specimens of historical honeybees have been successfully used to explore the genomic past of the honeybee, indicating fast and rapid changes between historical and modern specimens, possibly as a response to current challenges. In our study we explore a potential untapped archive from natural history collections - specimens of beeswax. We examine an Apis mellifera mellifera queen cell specimen from the 19th century. The intact and closed cell was analysed by X-ray Computed Tomography (CT) to reveal a perfectly preserved queen bee inside her cell. Subsequently, a micro-destructive approach was used to evaluate the possibility of protein extraction from the cell. Our results show that studies on specimens such as these provide valuable information about the past rearing of queens, their diet and development, which is relevant for understanding current honeybee behaviour. In addition we evaluate the feasibility of using historical beeswax as a biomolecular archive for ancient proteins to study honeybees.
2024-09-05 | PXD034106 | Pride
Project description:Here we report the first recovery, sequencing, and identification of fossil biomineral proteins from a Pleistocene invertebrate. Fossils of the Caribbean stony coral Orbicella annularis retain total hydrolyzable amino acids of a similar composition to extracts from modern O. annularis skeletons and ~10% of the modern skeletal proteome was sequenced by LC-MS/MS over multiple trials in the best-preserved fossil coral specimen. The data are rich in acidic amino acids such as aspartate and glutamate typical of skeletal proteins, and one of the four sequenced fossil proteins, a highly acidic protein, has been previously characterized in modern coral skeletons. A combination of degradation, or amino acid racemization inhibition of trypsin digestion, appears to limit greater recovery. Nevertheless, our workflow determines optimal samples for effective sequencing of fossil coral proteins, allowing comparison of modern and fossil invertebrate protein sequences, and will likely lead to further improvements of the methods. Sequencing of endogenous organic mand biotic responses to paleoenvironments.
2020-10-27 | PXD017816 | Pride
Project description:Staphylococcus aureus is a high-priority pathogen causing severe infections with high morbidity and mortality worldwide. Many S. aureus strains are methicillin-resistant (MRSA) or even multi-drug resistant. It is one of the most successful and prominent modern pathogens. An effective fight against S. aureus infections requires novel targets for antimicrobial and antistaphylococcal therapies. Recent advances in whole-genome sequencing and high-throughput techniques facilitate the generation of genome-scale metabolic models (GEMs). Among the multiple applications of GEMs is drug-targeting in pathogens. Hence, comprehensive and predictive metabolic reconstructions of S. aureus could facilitate the identification of novel targets for antimicrobial therapies. This review aims at giving an overview of all available GEMs of multiple S. aureus strains. We downloaded all 114 available GEMs of S. aureus for further analysis. The scope of each model was evaluated, including the number of reactions, metabolites, and genes.Furthermore, all models were quality-controlled using Mᴇᴍᴏᴛᴇ, an open-source application with standardized metabolic tests. Growth capabilities and model similarities were examined. This review should lead as a guide for choosing the appropriate GEM for a given research question. With the information about the availability, the format, and the strengths and potentials of each model, one can either choose an existing model or combine several models to create models with even higher predictive values. This facilitates model-driven discoveries of novel antimicrobial targets to fight multi-drug resistant S. aureus strains.
2022-02-16 | MODEL2007110001 | BioModels
Project description:Staphylococcus aureus is a high-priority pathogen causing severe infections with high morbidity and mortality worldwide. Many S. aureus strains are methicillin-resistant (MRSA) or even multi-drug resistant. It is one of the most successful and prominent modern pathogens. An effective fight against S. aureus infections requires novel targets for antimicrobial and antistaphylococcal therapies. Recent advances in whole-genome sequencing and high-throughput techniques facilitate the generation of genome-scale metabolic models (GEMs). Among the multiple applications of GEMs is drug-targeting in pathogens. Hence, comprehensive and predictive metabolic reconstructions of S. aureus could facilitate the identification of novel targets for antimicrobial therapies. This review aims at giving an overview of all available GEMs of multiple S. aureus strains. We downloaded all 114 available GEMs of S. aureus for further analysis. The scope of each model was evaluated, including the number of reactions, metabolites, and genes. Furthermore, all models were quality-controlled using Mᴇᴍᴏᴛᴇ, an open-source application with standardized metabolic tests. Growth capabilities and model similarities were examined. This review should lead as a guide for choosing the appropriate GEM for a given research question. With the information about the availability, the format, and the strengths and potentials of each model, one can either choose an existing model or combine several models to create models with even higher predictive values. This facilitates model-driven discoveries of novel antimicrobial targets to fight multi-drug resistant S. aureus strains.
2022-02-16 | MODEL2007150001 | BioModels
Project description:Staphylococcus aureus is a high-priority pathogen causing severe infections with high morbidity and mortality worldwide. Many S. aureus strains are methicillin-resistant (MRSA) or even multi-drug resistant. It is one of the most successful and prominent modern pathogens. An effective fight against S. aureus infections requires novel targets for antimicrobial and antistaphylococcal therapies. Recent advances in whole-genome sequencing and high-throughput techniques facilitate the generation of genome-scale metabolic models (GEMs). Among the multiple applications of GEMs is drug-targeting in pathogens. Hence, comprehensive and predictive metabolic reconstructions of S. aureus could facilitate the identification of novel targets for antimicrobial therapies. This review aims at giving an overview of all available GEMs of multiple S. aureus strains. We downloaded all 114 available GEMs of S. aureus for further analysis. The scope of each model was evaluated, including the number of reactions, metabolites, and genes.Furthermore, all models were quality-controlled using Mᴇᴍᴏᴛᴇ, an open-source application with standardized metabolic tests. Growth capabilities and model similarities were examined. This review should lead as a guide for choosing the appropriate GEM for a given research question. With the information about the availability, the format, and the strengths and potentials of each model, one can either choose an existing model or combine several models to create models with even higher predictive values. This facilitates model-driven discoveries of novel antimicrobial targets to fight multi-drug resistant S. aureus strains.
2022-02-16 | MODEL2007150002 | BioModels
Project description:The study is intended to collect specimens to support the application of genome analysis technologies, including large-scale genome sequencing. This study will ultimately provide cancer researchers with specimens that they can use to develop comprehensive catalogs of genomic information on at least 50 types of human cancer. The study will create a resource available to the worldwide research community that could be used to identify and accelerate the development of new diagnostic and prognostic markers, new targets for pharmaceutical interventions, and new cancer prevention and treatment strategies. This study will be a competitive enrollment study conducted at multiple institutions.
| 2140168 | ecrin-mdr-crc