TY - JOUR
T1 - The Sorcerer II global ocean sampling expedition
T2 - Expanding the universe of protein families
AU - Yooseph, Shibu
AU - Sutton, Granger
AU - Rusch, Douglas B.
AU - Halpern, Aaron L.
AU - Williamson, Shannon J.
AU - Remington, Karin
AU - Eisen, Jonathan A.
AU - Heidelberg, Karla B.
AU - Manning, Gerard
AU - Li, Weizhong
AU - Jaroszewski, Lukasz
AU - Cieplak, Piotr
AU - Miller, Christopher S.
AU - Li, Huiying
AU - Mashiyama, Susan T.
AU - Joachimiak, Marcin P.
AU - Van Belle, Christopher
AU - Chandonia, John Marc
AU - Soergel, David A.
AU - Zhai, Yufeng
AU - Natarajan, Kannan
AU - Lee, Shaun
AU - Raphael, Benjamin J.
AU - Bafna, Vineet
AU - Friedman, Robert
AU - Brenner, Steven E.
AU - Godzik, Adam
AU - Eisenberg, David
AU - Dixon, Jack E.
AU - Taylor, Susan S.
AU - Strausberg, Robert L.
AU - Frazier, Marvin
AU - Venter, J. Craig
PY - 2007/3
Y1 - 2007/3
N2 - Metagenomics projects based on shotgun sequencing of populations of micro-organisms yield insight into protein families. We used sequence similarity clustering to explore proteins with a comprehensive dataset consisting of sequences from available databases together with 6.12 million proteins predicted from an assembly of 7.7 million Global Ocean Sampling (GOS) sequences. The GOS dataset covers nearly all known prokaryotic protein families. A total of 3,995 medium- and large-sized clusters consisting of only GOS sequences are identified, out of which 1,700 have no detectable homology to known families. The GOS-only clusters contain a higher than expected proportion of sequences of viral origin, thus reflecting a poor sampling of viral diversity until now. Protein domain distributions in the GOS dataset and current protein databases show distinct biases. Several protein domains that were previously categorized as kingdom specific are shown to have GOS examples in other kingdoms. About 6,000 sequences (ORFans) from the literature that heretofore lacked similarity to known proteins have matches in the GOS data. The GOS dataset is also used to improve remote homology detection. Overall, besides nearly doubling the number of current proteins, the predicted GOS proteins also add a great deal of diversity to known protein families and shed light on their evolution. These observations are illustrated using several protein families, including phosphatases, proteases, ultraviolet-irradiation DNA damage repair enzymes, glutamine synthetase, and RuBisCO. The diversity added by GOS data has implications for choosing targets for experimental structure characterization as part of structural genomics efforts. Our analysis indicates that new families are being discovered at a rate that is linear or almost linear with the addition of new sequences, implying that we are still far from discovering all protein families in nature.
AB - Metagenomics projects based on shotgun sequencing of populations of micro-organisms yield insight into protein families. We used sequence similarity clustering to explore proteins with a comprehensive dataset consisting of sequences from available databases together with 6.12 million proteins predicted from an assembly of 7.7 million Global Ocean Sampling (GOS) sequences. The GOS dataset covers nearly all known prokaryotic protein families. A total of 3,995 medium- and large-sized clusters consisting of only GOS sequences are identified, out of which 1,700 have no detectable homology to known families. The GOS-only clusters contain a higher than expected proportion of sequences of viral origin, thus reflecting a poor sampling of viral diversity until now. Protein domain distributions in the GOS dataset and current protein databases show distinct biases. Several protein domains that were previously categorized as kingdom specific are shown to have GOS examples in other kingdoms. About 6,000 sequences (ORFans) from the literature that heretofore lacked similarity to known proteins have matches in the GOS data. The GOS dataset is also used to improve remote homology detection. Overall, besides nearly doubling the number of current proteins, the predicted GOS proteins also add a great deal of diversity to known protein families and shed light on their evolution. These observations are illustrated using several protein families, including phosphatases, proteases, ultraviolet-irradiation DNA damage repair enzymes, glutamine synthetase, and RuBisCO. The diversity added by GOS data has implications for choosing targets for experimental structure characterization as part of structural genomics efforts. Our analysis indicates that new families are being discovered at a rate that is linear or almost linear with the addition of new sequences, implying that we are still far from discovering all protein families in nature.
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U2 - 10.1371/journal.pbio.0050016
DO - 10.1371/journal.pbio.0050016
M3 - Article
C2 - 17355171
AN - SCOPUS:33947235074
SN - 1544-9173
VL - 5
SP - 432
EP - 466
JO - PLoS biology
JF - PLoS biology
IS - 3
ER -