Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Ancient nuclear genomes enable repatriation of Indigenous human remains

ABSTRACT: Ancient nuclear genomes enable repatriation of Indigenous human remains

PROVIDER: PRJEB29663 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	ERR2898720.fastq.gz	Fastqsanger.gz
	ERR2898721.fastq.gz	Fastqsanger.gz
	ERR2898722.fastq.gz	Fastqsanger.gz
	ERR2898723.fastq.gz	Fastqsanger.gz
	ERR2898724.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 10

Similar Datasets

Ancient nuclear genomes enable repatriation of Indigenous human remains

Project description:For many decades Indigenous people, including Native Americans and Aboriginal Australians, have fought for their return of their ancient people. By sequencing ten ancient nuclear genomes of Aboriginal Australians and 27 mitogenomes from ancient pre-European Aboriginal Australians (up to 1,540 yr BP) of known provenance we demonstrate the feasibility of successfully identifying the geographic origins of unprovenanced ancestral remains using genomic methods.

| EGAS00001003359 | EGA

Ancient nuclear genomes enable repatriation of Indigenous human remains.

Project description:After European colonization, the ancestral remains of Indigenous people were often collected for scientific research or display in museum collections. For many decades, Indigenous people, including Native Americans and Aboriginal Australians, have fought for their return. However, many of these remains have no recorded provenance, making their repatriation very difficult or impossible. To determine whether DNA-based methods could resolve this important problem, we sequenced 10 nuclear genomes and 27 mitogenomes from ancient pre-European Aboriginal Australians (up to 1540 years before the present) of known provenance and compared them to 100 high-coverage contemporary Aboriginal Australian genomes, also of known provenance. We report substantial ancient population structure showing strong genetic affinities between ancient and contemporary Aboriginal Australian individuals from the same geographic location. Our findings demonstrate the feasibility of successfully identifying the origins of unprovenanced ancestral remains using genomic methods.

| S-EPMC6300400 | biostudies-literature

Metagenomics analysis of ancient human remains

Project description:Metagenomics analysis of ancient human remains

| PRJEB43969 | ENA

Metaproteomic analyses of microbial community from ancient permafrost

Project description:It remains challenging to study the viability and metabolic activity of microorganisms buried in ancient permafrost. We coupled aspartic acid racemization assay with metaproteomics to constraint the microbial activity of indigenous microbial community entrappped in permafrost sediment over 100 kyr ago.

2021-09-09 | PXD022683 | Pride

Ancient Iberian genomes

Project description:This study includes mitogenomes and whole nuclear genomes from prehistoric Iberian remains

| PRJEB29189 | ENA

Ancient genomes from Bronze Age remains reveal deep diversity and recent adaptive episodes for human oral pathobionts

Project description:Ancient genomes from Bronze Age remains reveal deep diversity and recent adaptive episodes for human oral pathobionts

| PRJEB64128 | ENA

Imputation of ancient genomes

Project description:Ancient human trio (Koszyce)

| PRJEB61632 | ENA

Aligned Ancient Genomes

Project description:Alignment of publicly available ancient genomes to hg38

| PRJEB64654 | ENA

Hunyadi descendant's ancient genomes

Project description:Matthias Hunyadi son and grandson ancient genomes

| PRJEB47418 | ENA

Species identification of ancient Lithuanian fish remains using collagen fingerprinting

Project description:Morphological identification of ancient bone is often problematic due to heavy fragmentation that generally influences zooarchaeological assemblages. Fish bones are more taphonomically sensitive than those of other vertebrates as they are typically smaller and less biomineralised. Thus, taxonomic identification based on the preservation of morphological features is often extremely limited and can reduce or eliminate the usefulness of an assemblage for inferring taxon information. Currently, one of the most time- and cost-efficient methods of achieving faunal identity from ancient bone is by the collagen fingerprinting technique known as ZooMS (Zooarchaeology by Mass Spectrometry). ZooMS harnesses the potential of preserved collagen, which is the most dominant and time-stable protein in bone. In this research, ZooMS is applied to ancient Baltic region fish assemblages that are between 500 and 6000 years old in order to define species identity and construct assemblage compositions. Alongside inferences into environmental and biological shifts from the Neolithic era to present day in the Baltic region, we demonstrate for the first time the ability to distinguish between recently diverged members of the Salmo (salmon) and Scophthalmus (turbot) genera. ZooMS analysis highlights 7% of the collagen-containing assemblage as having been morphologically identified incorrectly and has facilitated taxonomic refinement of a further 28% of samples, including some of the morphologically indeterminate bone fragments. This research emphasises the great potential of ZooMS in identifying ichthyoarchaeological bone remains to species-level, and provides a case for the use of collagen fingerprinting in contributing to baseline fisheries and ecological data, to inform modern management.

2018-08-29 | PXD010041 | Pride

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