The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): Illuminating the Functional Diversity of Eukaryotic Life in the Oceans through Transcriptome Sequencing
Creators: name: Keeling, Patrick J.
name: Burki, Fabien
name: Wilcox, Heather M.
name: Allam, Bassem
name: Allen, Eric E.
name: Amaral-Zettler, Linda A.
name: Armbrust, E. Virginia
name: Archibald, John M.
name: Bharti, Arvind K.
name: Bell, Callum J.
name: Beszteri, Bank
name: Bidle, Kay D.
name: Cameron, Connor T.
name: Campbell, Lisa
name: Caron, David A.
name: Cattolico, Rose Ann
name: Collier, Jackie L.
name: Coyne, Kathryn
name: Davy, Simon K.
name: Deschamps, Phillipe
name: Dyhrman, Sonya
name: Edvardsen, Bente
name: Gates, Ruth D.
name: Gobler, Christopher J.
name: Greenwood, Spencer J.
name: Guida, Stephanie M.
name: Jacobi, Jennifer L.
name: Jakobsen, Kjetill S.
name: James, Erick R.
name: Jenkins, Bethany
name: John, Uwe
name: Johnson, Matthew D.
name: Juhl, Andrew R.
name: Kamp, Anja
name: Katz, Laura A.
name: Kiene, Ronald
name: Kudryavtsev, Alexander
name: Leander, Brian S.
name: Lin, Senjie
name: Lovejoy, Connie
name: Lynn, Denis
name: Marchetti, Adrian
name: McManus, George
name: Nedelcu, Aurora M.
name: Menden-Deuer, Susanne
name: Miceli, Cristina
name: Mock, Thomas
name: Montresor, Marina
name: Moran, Mary Ann
name: Murray, Shauna
name: Nadathur, Govind
name: Nagai, Satoshi
name: Ngam, Peter B.
name: Palenik, Brian
name: Pawlowski, Jan
name: Petroni, Giulio
name: Piganeau, Gwenael
name: Posewitz, Matthew C.
name: Rengefors, Karin
name: Romano, Giovanna
name: Rumpho, Mary E.
name: Rynearson, Tatiana
name: Schilling, Kelly B.
name: Schroeder, Declan C.
name: Simpson, Alastair G. B.
name: Slamovits, Claudio H.
name: Smith, David R.
name: Smith, G. Jason
name: Smith, Sarah R.
name: Sosik, Heidi M.
name: Stief, Peter
name: Theriot, Edward
name: Twary, Scott N.
name: Umale, Pooja E.
name: Vaulot, Daniel
name: Wawrik, Boris
name: Wheeler, Glen L.
name: Wilson, William H.
name: Xu, Yan
name: Zingone, Adriana
name: Worden, Alexandra Z.
Publisher: name: Columbia University
Year: 2014
Subjects: subject: Nucleotide sequence
subject: Genomics--Data processing
subject: Marine ecology
subject: Eukaryotic cells
subject: Ecology
subject: FOS: Biological sciences
subject: Microbiology
subject: Genetics

description: Microbial ecology is plagued by problems of an abstract nature. Cell sizes are so small and population sizes so large that both are virtually incomprehensible. Niches are so far from our everyday experience as to make their very definition elusive. Organisms that may be abundant and critical to our survival are little understood, seldom described and/or cultured, and sometimes yet to be even seen. One way to confront these problems is to use data of an even more abstract nature: molecular sequence data. Massive environmental nucleic acid sequencing, such as metagenomics or metatranscriptomics, promises functional analysis of microbial communities as a whole, without prior knowledge of which organisms are in the environment or exactly how they are interacting. But sequence-based ecological studies nearly always use a comparative approach, and that requires relevant reference sequences, which are an extremely limited resource when it comes to microbial eukaryotes [1]. In practice, this means sequence databases need to be populated with enormous quantities of data for which we have some certainties about the source. Most important is the taxonomic identity of the organism from which a sequence is derived and as much functional identification of the encoded proteins as possible. In an ideal world, such information would be available as a large set of complete, well-curated, and annotated genomes for all the major organisms from the environment in question. Reality substantially diverges from this ideal, but at least for bacterial molecular ecology, there is a database consisting of thousands of complete genomes from a wide range of taxa, supplemented by a phylogeny-driven approach to diversifying genomics [2]. For eukaryotes, the number of available genomes is far, far fewer, and we have relied much more heavily on random growth of sequence databases [3],[4], raising the question as to whether this is fit for purpose.