40 research outputs found
The PeptideAtlas of the Domestic Laying Hen
Proteomics-based biological research
is greatly expanded by high-quality
mass spectrometry studies, which are themselves enabled by access
to quality mass spectrometry resources, such as high-quality curated
proteome data repositories. We present a PeptideAtlas for the domestic
chicken, containing an extensive and robust collection of chicken
tissue and plasma samples with substantial value for the chicken proteomics
community for protein validation and design of downstream targeted
proteome quantitation. The chicken PeptideAtlas contains 6646 canonical
proteins at a protein FDR of 1.3%, derived from ā¼100āÆ000
peptides at a peptide level FDR of 0.1%. The rich collection of readily
accessible data is easily mined for the purposes of data validation
and experimental planning, particularly in the realm of developing
proteome quantitation workflows. Herein we demonstrate the use of
the atlas to mine information on common chicken acute-phase proteins
and biomarkers for cancer detection research, as well as their localization
and polymorphisms. This wealth of information will support future
proteome-based research using this highly important agricultural organism
in pursuit of both chicken and human health outcomes
Metrics for the Human Proteome Project 2016: Progress on Identifying and Characterizing the Human Proteome, Including Post-Translational Modifications
The HUPO Human Proteome Project (HPP)
has two overall goals: (1)
stepwise completion of the protein parts listīøthe draft human proteome including confidently identifying and characterizing at least one protein product
from each protein-coding gene, with increasing emphasis on sequence
variants, post-translational modifications (PTMs), and splice isoforms
of those proteins; and (2) making proteomics an integrated counterpart
to genomics throughout the biomedical and life sciences community.
PeptideAtlas and GPMDB reanalyze all major human mass spectrometry data
sets available through ProteomeXchange with standardized protocols
and stringent quality filters; neXtProt curates and integrates mass
spectrometry and other findings to present the most up to date authorative compendium of the human proteome. The HPP Guidelines for Mass Spectrometry
Data Interpretation version 2.1 were applied to manuscripts submitted
for this 2016 C-HPP-led special issue [www.thehpp.org/guidelines]. The Human Proteome presented as neXtProt version 2016-02 has 16,518
confident protein identifications (Protein Existence [PE] Level 1),
up from 13,664 at 2012-12, 15,646 at 2013-09, and 16,491 at 2014-10.
There are 485 proteins that would have been PE1 under the Guidelines
v1.0 from 2012 but now have insufficient evidence due to the agreed-upon
more stringent Guidelines v2.0 to reduce false positives. neXtProt
and PeptideAtlas now both require two non-nested, uniquely mapping
(proteotypic) peptides of at least 9 aa in length. There are 2,949
missing proteins (PE2+3+4) as the baseline for submissions for this
fourth annual C-HPP special issue of Journal of Proteome Research.
PeptideAtlas has 14,629 canonical (plus 1187 uncertain and 1755 redundant)
entries. GPMDB has 16,190 EC4 entries, and the Human Protein Atlas
has 10,475 entries with supportive evidence. neXtProt, PeptideAtlas,
and GPMDB are rich resources of information about post-translational modifications (PTMs), single amino acid variants (SAAVSs), and splice isoforms. Meanwhile, the Biology- and Disease-driven
(B/D)-HPP has created comprehensive SRM resources, generated popular
protein lists to guide targeted proteomics assays for specific diseases,
and launched an Early Career Researchers initiative
The State of the Human Proteome in 2012 as Viewed through PeptideAtlas
The Human Proteome Project was launched in September
2010 with
the goal of characterizing at least one protein product from each
protein-coding gene. Here we assess how much of the proteome has been
detected to date via tandem mass spectrometry by analyzing PeptideAtlas,
a compendium of human derived LCāMS/MS proteomics data from
many laboratories around the world. All data sets are processed with
a consistent set of parameters using the Trans-Proteomic Pipeline
and subjected to a 1% protein FDR filter before inclusion in PeptideAtlas.
Therefore, PeptideAtlas contains only high confidence protein identifications.
To increase proteome coverage, we explored new comprehensive public
data sources for data likely to add new proteins to the Human PeptideAtlas.
We then folded these data into a Human PeptideAtlas 2012 build and
mapped it to Swiss-Prot, a protein sequence database curated to contain
one entry per human protein coding gene. We find that this latest
PeptideAtlas build includes at least one peptide for each of ā¼12500
Swiss-Prot entries, leaving ā¼7500 gene products yet to be confidently
cataloged. We characterize these āPA-unseenā proteins
in terms of tissue localization, transcript abundance, and Gene Ontology
enrichment, and propose reasons for their absence from PeptideAtlas
and strategies for detecting them in the future
The State of the Human Proteome in 2012 as Viewed through PeptideAtlas
The Human Proteome Project was launched in September
2010 with
the goal of characterizing at least one protein product from each
protein-coding gene. Here we assess how much of the proteome has been
detected to date via tandem mass spectrometry by analyzing PeptideAtlas,
a compendium of human derived LCāMS/MS proteomics data from
many laboratories around the world. All data sets are processed with
a consistent set of parameters using the Trans-Proteomic Pipeline
and subjected to a 1% protein FDR filter before inclusion in PeptideAtlas.
Therefore, PeptideAtlas contains only high confidence protein identifications.
To increase proteome coverage, we explored new comprehensive public
data sources for data likely to add new proteins to the Human PeptideAtlas.
We then folded these data into a Human PeptideAtlas 2012 build and
mapped it to Swiss-Prot, a protein sequence database curated to contain
one entry per human protein coding gene. We find that this latest
PeptideAtlas build includes at least one peptide for each of ā¼12500
Swiss-Prot entries, leaving ā¼7500 gene products yet to be confidently
cataloged. We characterize these āPA-unseenā proteins
in terms of tissue localization, transcript abundance, and Gene Ontology
enrichment, and propose reasons for their absence from PeptideAtlas
and strategies for detecting them in the future
The State of the Human Proteome in 2012 as Viewed through PeptideAtlas
The Human Proteome Project was launched in September
2010 with
the goal of characterizing at least one protein product from each
protein-coding gene. Here we assess how much of the proteome has been
detected to date via tandem mass spectrometry by analyzing PeptideAtlas,
a compendium of human derived LCāMS/MS proteomics data from
many laboratories around the world. All data sets are processed with
a consistent set of parameters using the Trans-Proteomic Pipeline
and subjected to a 1% protein FDR filter before inclusion in PeptideAtlas.
Therefore, PeptideAtlas contains only high confidence protein identifications.
To increase proteome coverage, we explored new comprehensive public
data sources for data likely to add new proteins to the Human PeptideAtlas.
We then folded these data into a Human PeptideAtlas 2012 build and
mapped it to Swiss-Prot, a protein sequence database curated to contain
one entry per human protein coding gene. We find that this latest
PeptideAtlas build includes at least one peptide for each of ā¼12500
Swiss-Prot entries, leaving ā¼7500 gene products yet to be confidently
cataloged. We characterize these āPA-unseenā proteins
in terms of tissue localization, transcript abundance, and Gene Ontology
enrichment, and propose reasons for their absence from PeptideAtlas
and strategies for detecting them in the future
The State of the Human Proteome in 2012 as Viewed through PeptideAtlas
The Human Proteome Project was launched in September
2010 with
the goal of characterizing at least one protein product from each
protein-coding gene. Here we assess how much of the proteome has been
detected to date via tandem mass spectrometry by analyzing PeptideAtlas,
a compendium of human derived LCāMS/MS proteomics data from
many laboratories around the world. All data sets are processed with
a consistent set of parameters using the Trans-Proteomic Pipeline
and subjected to a 1% protein FDR filter before inclusion in PeptideAtlas.
Therefore, PeptideAtlas contains only high confidence protein identifications.
To increase proteome coverage, we explored new comprehensive public
data sources for data likely to add new proteins to the Human PeptideAtlas.
We then folded these data into a Human PeptideAtlas 2012 build and
mapped it to Swiss-Prot, a protein sequence database curated to contain
one entry per human protein coding gene. We find that this latest
PeptideAtlas build includes at least one peptide for each of ā¼12500
Swiss-Prot entries, leaving ā¼7500 gene products yet to be confidently
cataloged. We characterize these āPA-unseenā proteins
in terms of tissue localization, transcript abundance, and Gene Ontology
enrichment, and propose reasons for their absence from PeptideAtlas
and strategies for detecting them in the future
The State of the Human Proteome in 2012 as Viewed through PeptideAtlas
The Human Proteome Project was launched in September
2010 with
the goal of characterizing at least one protein product from each
protein-coding gene. Here we assess how much of the proteome has been
detected to date via tandem mass spectrometry by analyzing PeptideAtlas,
a compendium of human derived LCāMS/MS proteomics data from
many laboratories around the world. All data sets are processed with
a consistent set of parameters using the Trans-Proteomic Pipeline
and subjected to a 1% protein FDR filter before inclusion in PeptideAtlas.
Therefore, PeptideAtlas contains only high confidence protein identifications.
To increase proteome coverage, we explored new comprehensive public
data sources for data likely to add new proteins to the Human PeptideAtlas.
We then folded these data into a Human PeptideAtlas 2012 build and
mapped it to Swiss-Prot, a protein sequence database curated to contain
one entry per human protein coding gene. We find that this latest
PeptideAtlas build includes at least one peptide for each of ā¼12500
Swiss-Prot entries, leaving ā¼7500 gene products yet to be confidently
cataloged. We characterize these āPA-unseenā proteins
in terms of tissue localization, transcript abundance, and Gene Ontology
enrichment, and propose reasons for their absence from PeptideAtlas
and strategies for detecting them in the future
The State of the Human Proteome in 2012 as Viewed through PeptideAtlas
The Human Proteome Project was launched in September
2010 with
the goal of characterizing at least one protein product from each
protein-coding gene. Here we assess how much of the proteome has been
detected to date via tandem mass spectrometry by analyzing PeptideAtlas,
a compendium of human derived LCāMS/MS proteomics data from
many laboratories around the world. All data sets are processed with
a consistent set of parameters using the Trans-Proteomic Pipeline
and subjected to a 1% protein FDR filter before inclusion in PeptideAtlas.
Therefore, PeptideAtlas contains only high confidence protein identifications.
To increase proteome coverage, we explored new comprehensive public
data sources for data likely to add new proteins to the Human PeptideAtlas.
We then folded these data into a Human PeptideAtlas 2012 build and
mapped it to Swiss-Prot, a protein sequence database curated to contain
one entry per human protein coding gene. We find that this latest
PeptideAtlas build includes at least one peptide for each of ā¼12500
Swiss-Prot entries, leaving ā¼7500 gene products yet to be confidently
cataloged. We characterize these āPA-unseenā proteins
in terms of tissue localization, transcript abundance, and Gene Ontology
enrichment, and propose reasons for their absence from PeptideAtlas
and strategies for detecting them in the future
Cassia grandis
The Human Proteome Project was launched in September
2010 with
the goal of characterizing at least one protein product from each
protein-coding gene. Here we assess how much of the proteome has been
detected to date via tandem mass spectrometry by analyzing PeptideAtlas,
a compendium of human derived LCāMS/MS proteomics data from
many laboratories around the world. All data sets are processed with
a consistent set of parameters using the Trans-Proteomic Pipeline
and subjected to a 1% protein FDR filter before inclusion in PeptideAtlas.
Therefore, PeptideAtlas contains only high confidence protein identifications.
To increase proteome coverage, we explored new comprehensive public
data sources for data likely to add new proteins to the Human PeptideAtlas.
We then folded these data into a Human PeptideAtlas 2012 build and
mapped it to Swiss-Prot, a protein sequence database curated to contain
one entry per human protein coding gene. We find that this latest
PeptideAtlas build includes at least one peptide for each of ā¼12500
Swiss-Prot entries, leaving ā¼7500 gene products yet to be confidently
cataloged. We characterize these āPA-unseenā proteins
in terms of tissue localization, transcript abundance, and Gene Ontology
enrichment, and propose reasons for their absence from PeptideAtlas
and strategies for detecting them in the future
The State of the Human Proteome in 2012 as Viewed through PeptideAtlas
The Human Proteome Project was launched in September
2010 with
the goal of characterizing at least one protein product from each
protein-coding gene. Here we assess how much of the proteome has been
detected to date via tandem mass spectrometry by analyzing PeptideAtlas,
a compendium of human derived LCāMS/MS proteomics data from
many laboratories around the world. All data sets are processed with
a consistent set of parameters using the Trans-Proteomic Pipeline
and subjected to a 1% protein FDR filter before inclusion in PeptideAtlas.
Therefore, PeptideAtlas contains only high confidence protein identifications.
To increase proteome coverage, we explored new comprehensive public
data sources for data likely to add new proteins to the Human PeptideAtlas.
We then folded these data into a Human PeptideAtlas 2012 build and
mapped it to Swiss-Prot, a protein sequence database curated to contain
one entry per human protein coding gene. We find that this latest
PeptideAtlas build includes at least one peptide for each of ā¼12500
Swiss-Prot entries, leaving ā¼7500 gene products yet to be confidently
cataloged. We characterize these āPA-unseenā proteins
in terms of tissue localization, transcript abundance, and Gene Ontology
enrichment, and propose reasons for their absence from PeptideAtlas
and strategies for detecting them in the future