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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
Fecha : |
21/02/2014 |
Actualizado : |
13/09/2018 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
NOYES, N.R.; WEINROTH, M.E.; PARKER, J.K.; DEAN, C.J.; LAKIN, S.M.; RAYMOND, R.A.; ROVIRA, P.J.; DOSTER, E.; ABDO, Z.; MARTIN, J.N.; JONES, K.L.; RUIZ, J.; BOUCHER, C.A.; BELK, K.E.; MORLEY, P.S. |
Afiliación : |
NOELLE R. NOYES; MAGGIE E. WEINROTH; JENNIFER K. PARKER; CHRIS J. DEAN; STEVEN M. LAKIN; ROBERT A. RAYMOND; PABLO JUAN ROVIRA SANZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ENRIQUE DOSTER; ZAID ABDO; JENNIFER N. MARTIN; KENNETH L. JONES; JAIME RUIZ; CHRISTINA A. BOUCHER; KEITH E. BELK; PAUL S. MORLEY. |
Título : |
Enrichment allows identification of diverse, rate elements in metagenomic resistome-virulome sequencing. |
Fecha de publicación : |
2017 |
Fuente / Imprenta : |
Microbiome, 2017, 5, p. 142 |
Páginas : |
13 p. |
DOI : |
10.1186/s40168-017-0361-8 |
Idioma : |
Inglés |
Notas : |
Article History: Received: 29 May 2017, Accepted: 5 October 2017, Published: 17 October 2017 |
Contenido : |
Background: Shotgun metagenomic sequencing is increasingly utilized as a tool to evaluate ecological-level dynamics of antimicrobial resistance and virulence, in conjunction with microbiome analysis. Interest in use of this method for environmental surveillance of antimicrobial resistance and pathogenic microorganisms is also increasing. In published metagenomic datasets, the total of all resistance- and virulence-related sequences accounts for < 1% of all sequenced DNA, leading to imitations in detection of low-abundance resistome-virulome elements. This study describes the extent and composition of the low-abundance portion of the resistome-virulome, using a bait-capture and enrichment system that incorporates unique molecular indices to count DNA molecules and correct for enrichment bias.
Results: The use of the bait-capture and enrichment system significantly increased on-target sequencing of the resistome-virulome, enabling detection of an additional 1441 gene accessions and revealing a low-abundance portion of the resistome-virulome that was more diverse and compositionally different than that detected by more traditional
metagenomic assays. The low-abundance portion of the resistome-virulome also contained resistance genes with public health importance, such as extended-spectrum betalactamases, that were not detected using traditional shotgun metagenomic sequencing. In addition, the use of the bait-capture and enrichment system enabled identification of rare resistance gene haplotypes that were used to discriminate between sample origins.
Conclusions: These results demonstrate that the rare resistome-virulome contains valuable and unique information that can be utilized for both surveillance and population genetic investigations of resistance. Access to the rare resistomevirulome using the bait-capture and enrichment system validated in this study can greatly advance our understanding of
microbiome-resistome dynamics. MenosBackground: Shotgun metagenomic sequencing is increasingly utilized as a tool to evaluate ecological-level dynamics of antimicrobial resistance and virulence, in conjunction with microbiome analysis. Interest in use of this method for environmental surveillance of antimicrobial resistance and pathogenic microorganisms is also increasing. In published metagenomic datasets, the total of all resistance- and virulence-related sequences accounts for < 1% of all sequenced DNA, leading to imitations in detection of low-abundance resistome-virulome elements. This study describes the extent and composition of the low-abundance portion of the resistome-virulome, using a bait-capture and enrichment system that incorporates unique molecular indices to count DNA molecules and correct for enrichment bias.
Results: The use of the bait-capture and enrichment system significantly increased on-target sequencing of the resistome-virulome, enabling detection of an additional 1441 gene accessions and revealing a low-abundance portion of the resistome-virulome that was more diverse and compositionally different than that detected by more traditional
metagenomic assays. The low-abundance portion of the resistome-virulome also contained resistance genes with public health importance, such as extended-spectrum betalactamases, that were not detected using traditional shotgun metagenomic sequencing. In addition, the use of the bait-capture and enrichment system enabled identification of rare resistan... Presentar Todo |
Palabras claves : |
ANTIMICROBIAL RESISTANCE; METAGENÓMICA; MICROBIAL ECOLOGY; MOLECULAR ENRICHMENT; RARE MICROBIOME; RESISTOME. |
Thesagro : |
ANALISIS BIOLOGICO; ECOLOGIA MICROBIANA; RESISTENCIA A AGENTES DANINOS. |
Asunto categoría : |
U30 Métodos de investigación |
Marc : |
LEADER 03225naa a2200433 a 4500 001 1032862 005 2018-09-13 008 2017 bl uuuu u00u1 u #d 024 7 $a10.1186/s40168-017-0361-8$2DOI 100 1 $aNOYES, N.R. 245 $aEnrichment allows identification of diverse, rate elements in metagenomic resistome-virulome sequencing.$h[electronic resource] 260 $c2017 300 $a13 p. 500 $aArticle History: Received: 29 May 2017, Accepted: 5 October 2017, Published: 17 October 2017 520 $aBackground: Shotgun metagenomic sequencing is increasingly utilized as a tool to evaluate ecological-level dynamics of antimicrobial resistance and virulence, in conjunction with microbiome analysis. Interest in use of this method for environmental surveillance of antimicrobial resistance and pathogenic microorganisms is also increasing. In published metagenomic datasets, the total of all resistance- and virulence-related sequences accounts for < 1% of all sequenced DNA, leading to imitations in detection of low-abundance resistome-virulome elements. This study describes the extent and composition of the low-abundance portion of the resistome-virulome, using a bait-capture and enrichment system that incorporates unique molecular indices to count DNA molecules and correct for enrichment bias. Results: The use of the bait-capture and enrichment system significantly increased on-target sequencing of the resistome-virulome, enabling detection of an additional 1441 gene accessions and revealing a low-abundance portion of the resistome-virulome that was more diverse and compositionally different than that detected by more traditional metagenomic assays. The low-abundance portion of the resistome-virulome also contained resistance genes with public health importance, such as extended-spectrum betalactamases, that were not detected using traditional shotgun metagenomic sequencing. In addition, the use of the bait-capture and enrichment system enabled identification of rare resistance gene haplotypes that were used to discriminate between sample origins. Conclusions: These results demonstrate that the rare resistome-virulome contains valuable and unique information that can be utilized for both surveillance and population genetic investigations of resistance. Access to the rare resistomevirulome using the bait-capture and enrichment system validated in this study can greatly advance our understanding of microbiome-resistome dynamics. 650 $aANALISIS BIOLOGICO 650 $aECOLOGIA MICROBIANA 650 $aRESISTENCIA A AGENTES DANINOS 653 $aANTIMICROBIAL RESISTANCE 653 $aMETAGENÓMICA 653 $aMICROBIAL ECOLOGY 653 $aMOLECULAR ENRICHMENT 653 $aRARE MICROBIOME 653 $aRESISTOME 700 1 $aWEINROTH, M.E. 700 1 $aPARKER, J.K. 700 1 $aDEAN, C.J. 700 1 $aLAKIN, S.M. 700 1 $aRAYMOND, R.A. 700 1 $aROVIRA, P.J. 700 1 $aDOSTER, E. 700 1 $aABDO, Z. 700 1 $aMARTIN, J.N. 700 1 $aJONES, K.L. 700 1 $aRUIZ, J. 700 1 $aBOUCHER, C.A. 700 1 $aBELK, K.E. 700 1 $aMORLEY, P.S. 773 $tMicrobiome, 2017, 5, p. 142
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INIA Treinta y Tres (TT) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
26/04/2023 |
Actualizado : |
26/04/2023 |
Tipo de producción científica : |
Artículos Indexados |
Autor : |
REBOLLO, I.; SCHEFFEL, S.; BLANCO, P.H.; MOLINA, F.; MARTÍNEZ, S.; CARRACELAS, G.; PÉREZ DE VIDA, F.; ROSAS, J.E. |
Afiliación : |
MARÍA INÉS REBOLLO PANUNCIO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SHEILA SCHEFFEL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; PEDRO HORACIO BLANCO BARRAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FEDERICO MOLINA CASELLA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SEBASTIÁN MARTÍNEZ KOPP, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JULIO GONZALO CARRACELAS GARRIDO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BLAS PEREZ DE VIDA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JUAN EDUARDO ROSAS CAISSIOLS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Instituto Nacional de Investigación Agropecuaria (INIA) Rice Breeding Program Historical Dataset. [Dataset]. |
Fecha de publicación : |
2023 |
Fuente / Imprenta : |
DRYAD Dataset, 2024. https://doi.org/10.5061/dryad.x69p8czn8 |
DOI : |
10.5061/dryad.x69p8czn8 |
Idioma : |
Inglés |
Notas : |
Correspondence author: Juan E. Rosas, email: jrosas@inia.org.uy -- Publication date: February 16, 2024. -- This dataset is embargoed and will be released when the associated article is published. Lists of files and downloads will become available to the public when released. -- FUNDING: Agencia Nacional de Investigación e Innovación, Award: FSDA_1_2018_1_154120; Instituto Nacional de Investigación Agropecuaria, Award: AZ13; Instituto Nacional de Investigación Agropecuaria, Award: AZ35. |
Contenido : |
Breeding programs generate vast amounts of data which are often scattered in separate files. This hinders the application of modern breeding tools such as multi-environment analyses and genomic selection. This dataset is the result of consolidating 23 years of phenotypic, pedigree, and genomic records from the Uruguayan national rice breeding program. All the available data from 1997 to 2020 corresponding to field trials, blast nurseries, laboratory analyses of milling and cooking quality, pedigree information, and genomic information for selected advanced breeding lines are gathered. Records of 996 trials in 12 locations over a span of 23 years, 91,636 field plots with information on 14 phenotypic variables, pedigree for 19,447 genotypes, and genomic information regarding 61,260 SNP markers for 965 genotypes were recovered. The dataset is structured in Trials, Phenotypes, Lines, Genomic Information, and SNP Tables. Genotype identification has been coded. Copyright (c) 2023 Dryad |
Palabras claves : |
Agricultural sciences; Agronomic performance; Breeding trials; Disease phenotype; Genotypic data; Genotyping by sequencing (GBS); Grain yield; Phenotypic data; Rice Breeding Program; SNP; Temperate region. |
Thesagro : |
ORYZA SATIVA L; URUGUAY. |
Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
URL : |
https://datadryad.org/stash/dataset/doi:10.5061/dryad.x69p8czn8
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Marc : |
LEADER 02599naa a2200385 a 4500 001 1064058 005 2023-04-26 008 2023 bl uuuu u00u1 u #d 024 7 $a10.5061/dryad.x69p8czn8$2DOI 100 1 $aREBOLLO, I. 245 $aInstituto Nacional de Investigación Agropecuaria (INIA) Rice Breeding Program Historical Dataset. [Dataset].$h[electronic resource] 260 $c2023 500 $aCorrespondence author: Juan E. Rosas, email: jrosas@inia.org.uy -- Publication date: February 16, 2024. -- This dataset is embargoed and will be released when the associated article is published. Lists of files and downloads will become available to the public when released. -- FUNDING: Agencia Nacional de Investigación e Innovación, Award: FSDA_1_2018_1_154120; Instituto Nacional de Investigación Agropecuaria, Award: AZ13; Instituto Nacional de Investigación Agropecuaria, Award: AZ35. 520 $aBreeding programs generate vast amounts of data which are often scattered in separate files. This hinders the application of modern breeding tools such as multi-environment analyses and genomic selection. This dataset is the result of consolidating 23 years of phenotypic, pedigree, and genomic records from the Uruguayan national rice breeding program. All the available data from 1997 to 2020 corresponding to field trials, blast nurseries, laboratory analyses of milling and cooking quality, pedigree information, and genomic information for selected advanced breeding lines are gathered. Records of 996 trials in 12 locations over a span of 23 years, 91,636 field plots with information on 14 phenotypic variables, pedigree for 19,447 genotypes, and genomic information regarding 61,260 SNP markers for 965 genotypes were recovered. The dataset is structured in Trials, Phenotypes, Lines, Genomic Information, and SNP Tables. Genotype identification has been coded. Copyright (c) 2023 Dryad 650 $aORYZA SATIVA L 650 $aURUGUAY 653 $aAgricultural sciences 653 $aAgronomic performance 653 $aBreeding trials 653 $aDisease phenotype 653 $aGenotypic data 653 $aGenotyping by sequencing (GBS) 653 $aGrain yield 653 $aPhenotypic data 653 $aRice Breeding Program 653 $aSNP 653 $aTemperate region 700 1 $aSCHEFFEL, S. 700 1 $aBLANCO, P.H. 700 1 $aMOLINA, F. 700 1 $aMARTÍNEZ, S. 700 1 $aCARRACELAS, G. 700 1 $aPÉREZ DE VIDA, F. 700 1 $aROSAS, J.E. 773 $tDRYAD Dataset, 2024. https://doi.org/10.5061/dryad.x69p8czn8
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