Editing Proteome (section)

==Size and contents==
The genomes of '''[[virus]]es''' and '''[[prokaryote]]s''' encode a relatively well-defined proteome as each protein can be predicted with high confidence, based on its [[open reading frame]] (in viruses ranging from ~3 to ~1000, in bacteria ranging from about 500 proteins to about 10,000).<ref>{{cite journal|last1=Kozlowski|first1=LP|date=26 October 2016|title=Proteome-''pI'': proteome isoelectric point database|journal=Nucleic Acids Research|volume=45|issue=D1|pages=D1112–D1116|doi=10.1093/nar/gkw978|pmc=5210655|pmid=27789699}}</ref> However, most [[Gene prediction|protein prediction]] algorithms use certain cut-offs, such as 50 or 100 amino acids, so small proteins are often missed by such predictions.<ref>{{Cite journal|last=Leslie|first=Mitch|date=2019-10-18|title=Outsize impact|url=https://www.science.org/doi/10.1126/science.366.6463.296|journal=Science|language=en|volume=366|issue=6463|pages=296–299|doi=10.1126/science.366.6463.296|pmid=31624194|bibcode=2019Sci...366..296L|s2cid=204774732 |issn=0036-8075}}</ref> In [[eukaryota|'''eukaryotes''']] this becomes much more complicated as more than one [[protein]] can be produced from most [[gene]]s due to [[alternative splicing]] (e.g. human genome encodes about 20,000 proteins, but some estimates predicted 92,179 proteins{{citation needed|date=January 2019}} out of which 71,173 are splicing variants{{citation needed|date=January 2019}}).<ref>{{cite journal|title=UniProt: a hub for protein information|journal=Nucleic Acids Research|volume=43|issue=D1|year=2014|pages=D204–D212|issn=0305-1048|doi=10.1093/nar/gku989|pmid=25348405|pmc=4384041 |last1=Uniprot |first1=Consortium }}</ref>

'''Association of proteome size with DNA repair capability'''

The concept of “proteomic constraint” is that [[DNA repair]] capacity is positively correlated with the information content of a [[genome]], which, in turn, is approximately related to the size of the proteome.<ref name = Acosta2015>Acosta S, Carela M, Garcia-Gonzalez A, Gines M, Vicens L, Cruet R, Massey SE. DNA Repair Is Associated with Information Content in Bacteria, Archaea, and DNA Viruses. J Hered. 2015 Sep-Oct;106(5):644-59. doi: 10.1093/jhered/esv055. Epub 2015 Aug 29. PMID: 26320243</ref>  In [[bacteria]], [[archaea]] and [[DNA virus]]es, DNA repair capability is positively related to genome information content and to genome size.<ref name = Acosta2015/>    “Proteomic constraint” proposes that modulators of mutation rates such as DNA repair genes are subject to selection pressure proportional to the amount of information in a genome.<ref name = Acosta2015/>

'''Proteoforms'''. There are different factors that can add variability to proteins. SAPs (single amino acid polymorphisms) and non-synonymous single nucleotide polymorphisms (nsSNPs) can lead to different "proteoforms"<ref name=":0">{{Cite journal|last1=Aebersold|first1=Ruedi|last2=Agar|first2=Jeffrey N|last3=Amster|first3=I Jonathan|last4=Baker|first4=Mark S|last5=Bertozzi|first5=Carolyn R|last6=Boja|first6=Emily S|last7=Costello|first7=Catherine E|last8=Cravatt|first8=Benjamin F|last9=Fenselau|first9=Catherine|last10=Garcia|first10=Benjamin A|last11=Ge|first11=Ying|date=March 2018|title=How many human proteoforms are there?|url= |journal=Nature Chemical Biology|language=en|volume=14|issue=3|pages=206–214|doi=10.1038/nchembio.2576|issn=1552-4450|pmc=5837046|pmid=29443976|hdl=1721.1/120977}}</ref> or "proteomorphs". Recent estimates have found ~135,000 validated nonsynonymous cSNPs currently housed within SwissProt. In dbSNP, there are 4.7 million candidate cSNPs, yet only ~670,000 cSNPs have been validated in the 1,000-genomes set as nonsynonymous cSNPs that change the identity of an amino acid in a protein.<ref name=":0" />

'''Dark proteome'''. The term [[dark proteome]] coined by Perdigão and colleagues, defines regions of proteins that have no detectable [[sequence homology]] to other proteins of known [[protein tertiary structure|three-dimensional structure]] and therefore cannot be [[homology modeling|modeled by homology]]. For 546,000 Swiss-Prot proteins, 44–54% of the proteome in [[eukaryote]]s and viruses was found to be "dark", compared with only ~14% in [[archaea]] and [[bacteria]].<ref>{{cite journal | last1 = Perdigão | first1 = Nelson | display-authors=etal | year = 2015 | title = Unexpected features of the dark proteome | journal = PNAS | volume = 112 | issue = 52| pages = 15898–15903 | doi = 10.1073/pnas.1508380112 | pmid=26578815 | pmc=4702990| bibcode = 2015PNAS..11215898P | doi-access = free }}</ref>

'''Human proteome'''. Currently, several projects aim to map the human proteome, including the [http://www.humanproteomemap.org/index.php Human Proteome Map], [https://www.proteomicsdb.org/ ProteomicsDB], [https://www.isoform.io isoform.io], and [https://www.hupo.org/human-proteome-project The Human Proteome Project (HPP)]. Much like the [[human genome project]], these projects seek to find and collect evidence for all predicted protein coding genes in the human genome. The Human Proteome Map currently (October 2020) claims 17,294 proteins and ProteomicsDB 15,479, using different criteria. On October 16, 2020, the HPP published a high-stringency blueprint <ref>{{cite journal|last=Adhikari|first=S|title=A high-stringency blueprint of the human proteome|journal=Nature Communications|date=October 2020|volume=11|issue=1|page=5301|doi=10.1038/s41467-020-19045-9|pmid=33067450|pmc=7568584|bibcode=2020NatCo..11.5301A}}</ref> covering more than 90% of the predicted protein coding genes. Proteins are identified from a wide range of fetal and adult tissues and cell types, including [[hematopoietic stem cells|hematopoietic cells]].