Correction of the Caulobacter crescentus NA1000 genome annotation
Bacterial genome annotations are accumulating rapidly in the GenBank database and the use of automated annotation technologies to create these annotations has become the norm. However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To impr...
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description | Bacterial genome annotations are accumulating rapidly in the GenBank database and the use of automated annotation technologies to create these annotations has become the norm. However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To improve accuracy and reliability, we analyzed the Caulobacter crescentus NA1000 genome utilizing computer programs Artemis and MICheck to manually examine the third codon position GC content, alignment to a third codon position GC frame plot peak, and matches in the GenBank database. We identified 11 new genes, modified the start site of 113 genes, and changed the reading frame of 38 genes that had been incorrectly annotated. Furthermore, our manual method of identifying protein-coding genes allowed us to remove 112 non-coding regions that had been designated as coding regions. The improved NA1000 genome annotation resulted in a reduction in the use of rare codons since noncoding regions with atypical codon usage were removed from the annotation and 49 new coding regions were added to the annotation. Thus, a more accurate codon usage table was generated as well. These results demonstrate that a comparison of the location of peaks third codon position GC content to the location of protein coding regions could be used to verify the annotation of any genome that has a GC content that is greater than 60%. |
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However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To improve accuracy and reliability, we analyzed the Caulobacter crescentus NA1000 genome utilizing computer programs Artemis and MICheck to manually examine the third codon position GC content, alignment to a third codon position GC frame plot peak, and matches in the GenBank database. We identified 11 new genes, modified the start site of 113 genes, and changed the reading frame of 38 genes that had been incorrectly annotated. Furthermore, our manual method of identifying protein-coding genes allowed us to remove 112 non-coding regions that had been designated as coding regions. The improved NA1000 genome annotation resulted in a reduction in the use of rare codons since noncoding regions with atypical codon usage were removed from the annotation and 49 new coding regions were added to the annotation. Thus, a more accurate codon usage table was generated as well. These results demonstrate that a comparison of the location of peaks third codon position GC content to the location of protein coding regions could be used to verify the annotation of any genome that has a GC content that is greater than 60%.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0091668</identifier><identifier>PMID: 24621776</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Amino acids ; Analysis ; Annotations ; Automation ; Biology ; Caulobacter crescentus - genetics ; Codon, Initiator - genetics ; Codons ; Computer programs ; Computer Science ; Computers ; Genes ; Genes, Bacterial - genetics ; Genomes ; Genomics ; Genomics - methods ; Identification methods ; Molecular Sequence Annotation - methods ; Position (location) ; Proteins ; Proteomics ; Reading ; Software ; Technology application ; Use statistics</subject><ispartof>PloS one, 2014-03, Vol.9 (3), p.e91668-e91668</ispartof><rights>COPYRIGHT 2014 Public Library of Science</rights><rights>2014 Ely, Scott. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To improve accuracy and reliability, we analyzed the Caulobacter crescentus NA1000 genome utilizing computer programs Artemis and MICheck to manually examine the third codon position GC content, alignment to a third codon position GC frame plot peak, and matches in the GenBank database. We identified 11 new genes, modified the start site of 113 genes, and changed the reading frame of 38 genes that had been incorrectly annotated. Furthermore, our manual method of identifying protein-coding genes allowed us to remove 112 non-coding regions that had been designated as coding regions. The improved NA1000 genome annotation resulted in a reduction in the use of rare codons since noncoding regions with atypical codon usage were removed from the annotation and 49 new coding regions were added to the annotation. Thus, a more accurate codon usage table was generated as well. These results demonstrate that a comparison of the location of peaks third codon position GC content to the location of protein coding regions could be used to verify the annotation of any genome that has a GC content that is greater than 60%.</description><subject>Amino acids</subject><subject>Analysis</subject><subject>Annotations</subject><subject>Automation</subject><subject>Biology</subject><subject>Caulobacter crescentus - genetics</subject><subject>Codon, Initiator - genetics</subject><subject>Codons</subject><subject>Computer programs</subject><subject>Computer Science</subject><subject>Computers</subject><subject>Genes</subject><subject>Genes, Bacterial - genetics</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Genomics - methods</subject><subject>Identification methods</subject><subject>Molecular Sequence Annotation - methods</subject><subject>Position (location)</subject><subject>Proteins</subject><subject>Proteomics</subject><subject>Reading</subject><subject>Software</subject><subject>Technology application</subject><subject>Use statistics</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNqNktuL1DAYxYso7rr6H4gWBNGHGXNpbi_CMHgZWFzw9hoyyZeZDp1mNmlF_3vTne4ylX2QPrQkv3OS7_QUxXOM5pgK_G4X-tiaZn4ILcwRUphz-aA4x4qSGSeIPjz5PiuepLRDiFHJ-ePijFScYCH4ebFYhhjBdnVoy-DLbgvl0vRNWBvbQSxthGSh7fpUfllghFC5gTbsoTRtGzozyJ4Wj7xpEjwb3xfFj48fvi8_zy6vPq2Wi8uZ5Yp0M4doRb2RFafUEc4qC5wQJRH20jAg0nHGERHGGYyRVxgEYgaIw5ZTtWb0onh59D00Ielx-qQxQ1xiJRDJxOpIuGB2-hDrvYl_dDC1vlkIcaNN7GrbgEZCOl85t_ZKVsQLYwkhkgnnkKiwguz1fjytX-_BDRlE00xMpzttvdWb8EtTxXDFZDZ4MxrEcN1D6vS-zlE2jWkh9Df3FkJxzHBGX_2D3j_dSG1MHqBufcjn2sFULyohhUAUDynN76Hy42Bf21wVX-f1ieDtRJCZDn53G9OnpFffvv4_e_Vzyr4-Ybdgmm6bQtMPlUlTsDqCNoaUIvi7kDHSQ9Nv09BD0_XY9Cx7cfqD7kS31aZ_Aam69fY</recordid><startdate>20140312</startdate><enddate>20140312</enddate><creator>Ely, Bert</creator><creator>Scott, LaTia Etheredge</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20140312</creationdate><title>Correction of the Caulobacter crescentus NA1000 genome annotation</title><author>Ely, Bert ; Scott, LaTia Etheredge</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-d0343fa84633d2654ce6229801f8a5e28d656027ada110f91e705ae2d1c639b53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Amino acids</topic><topic>Analysis</topic><topic>Annotations</topic><topic>Automation</topic><topic>Biology</topic><topic>Caulobacter crescentus - 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However, these automated methods commonly result in a small, but significant percentage of genome annotation errors. To improve accuracy and reliability, we analyzed the Caulobacter crescentus NA1000 genome utilizing computer programs Artemis and MICheck to manually examine the third codon position GC content, alignment to a third codon position GC frame plot peak, and matches in the GenBank database. We identified 11 new genes, modified the start site of 113 genes, and changed the reading frame of 38 genes that had been incorrectly annotated. Furthermore, our manual method of identifying protein-coding genes allowed us to remove 112 non-coding regions that had been designated as coding regions. The improved NA1000 genome annotation resulted in a reduction in the use of rare codons since noncoding regions with atypical codon usage were removed from the annotation and 49 new coding regions were added to the annotation. Thus, a more accurate codon usage table was generated as well. 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subjects | Amino acids Analysis Annotations Automation Biology Caulobacter crescentus - genetics Codon, Initiator - genetics Codons Computer programs Computer Science Computers Genes Genes, Bacterial - genetics Genomes Genomics Genomics - methods Identification methods Molecular Sequence Annotation - methods Position (location) Proteins Proteomics Reading Software Technology application Use statistics |
title | Correction of the Caulobacter crescentus NA1000 genome annotation |
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