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| 8. |  | RUBIO, L.; HERNÁNDEZ, L.; BENÍTEZ, M. J.; ARRUABARRENA, A.; RIVAS, F.; COLINA, R.; MAESO, D. Biological and molecular characterization of Uruguayan citrus tristeza virus field isolates. Journal of Plant Pathology, 2019, volume 101, Issue 1, pages 97-105. Article history: Received 06 June 2018 // Accepted 29 July 2018 // First Online 13 August 2018 // Published 15 February 2019.
Acknowledgements: This research was funded by Instituto Nacional de Investigación Agropecuaria, Uruguay...| Biblioteca(s): INIA Las Brujas. |
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| 9. | | ESTEVES, P.; MASTROPIERRO, M.M.; CASTILLO, A.; DALLA RIZZA, M.; BELZILE, F.; HERNANDEZ, L.; QUINCKE, M. Métodos para aumentar la eficiencia del mejoramiento de trigo. In: CONGRESO NACIONAL DE TRIGO, 8o. ; SIMPOSIO DE CEREALES DE SIEMBRA OTOÑO INVERNAL, 6o. ; ENCUENTRO DEL MERCOSUR, 2º, Pergamino, Argentina: AIANBA, 14-16 setiembre,2016.| Biblioteca(s): INIA La Estanzuela. |
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| 10. | | ESTEVES, P.; HERNANDEZ, L.; CASTILLO, A.; DALLA RIZZA, M.; QUINCKE, M. Tecnologías para el desarrollo de líneas recombinantes de trigo. MV 20 - COMUNICACIONES LIBRES - MV. MEJORAMIENTO VEGETAL In: JOURNAL OF BASIC & APPLIED GENETICS, 2016, Vol.27, Iss. 1 (Supp.). XVI LATIN AMERICAN CONGRESS OF GENETICS, IV CONGRESS OF THE URUGUAYAN SOCIETY OF GENETICS, XLIX ANNUAL MEETING OF THE GENETICS SOCIETY OF CHILE, XLV ARGENTINE CONGRESS OF GENETICS, 9-12 October 2016. PROCEEDINGS. Montevideo (Uruguay): SAG, 2016. p. 290| Biblioteca(s): INIA Las Brujas. |
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| 11. | | MAESO, D.; RUBIO, L.; BENÍTEZ-GALEANO, M.J.; HERNÁNDEZ, L.; BERTALMIO, A.; ARRUABARRENA, A.; RIVAS, F.; COLINA, R. Aportes al conocimiento de Citrus tristeza virus en Uruguay. [resumen] In: INIA (Instituto Nacional de Investigación Agropecuaria); INIA Las Brujas; Biotecnología. Jornada de Agrobiotecnología, XI. Encuentro Nacional de REDBIO, III. Jornada técnica. Las Brujas, Canelones (UY): INIA, 2018. p. 12 (Serie Actividades de Difusión; 786)| Biblioteca(s): INIA Las Brujas. |
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| 12. | | TANA-HERNÁNDEZ, L.; CABRERA, A.; VALENTÍN, A.; GONZÁLEZ, F.; FIERRO, S.; DORSCH, M.; GIANNITTI, F.; FRANCIA, M. Development and evaluation of detection and control techniques based on serological and molecular methodologies for Toxoplasma gondii in sheep in Uruguay. 103. (abstract) Área temática: Biología Celular y Molecular. In: Physiological Mini Reviews, 2022, volume 15, Special Issue: III (3er) Congreso Nacional de Biociencias Octubre 2022, Montevideo, Uruguay. p.117. Resumen publicado en las jornadas de BIOCIENCIAS: II Jornadas Binacionales Argentina-Uruguay; III Congreso Nacional 2022 "Ciencia para el desarrollo sustentable".| Biblioteca(s): INIA Las Brujas. |
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| 13. | | ESTEVES, P.; MASTROPIERRO, M.; CASTILLO, A.; HERNANDEZ, L.; RODRIGUEZ, M.; DE LEON, W.; PEREIRA, F.; QUINCKE, M. Herramientas biotecnológicas para el mejoramiento genético de cultivos. Revista INIA Uruguay, 2017, no.48, p. 62-66. (Revista INIA; 48)| Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
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| 14. | | RUBIO, L.; HERNÁNDEZ, L.; BERTALMIO, A.; ARRUABARRENA, A.; RIVAS, F.; BENÍTEZ, M.J.; COLINA, R.; MAESO, D. Obtención de aislados de Citrus tristeza virus promisorios para protección cruzada en cítricos. [o4]. Bloque 1: Detección y caracterización de plagas y enfermedades. In: Sociedad Uruguaya de Fitopatología Jornada Uruguaya de Fitopatología, 4., Jornada Uruguaya de Protección Vegetal, 2., 1° setiembre, 2017, Montevideo, Uruguay. Libro de resúmenes. Montevideo (UY): Sociedad Uruguay de Fitopatología (SUFIT), 2017. p. 15| Biblioteca(s): INIA Las Brujas. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
26/11/2015 |
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Actualizado : |
18/06/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
FORNERIS, N. S.; LEGARRA, A.; VITEZICA, Z. G.; TSURUTA, S.; AGUILAR, I.; MISZTAL, I.; CANTET, R. J. C. |
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Afiliación : |
NATALIA S. FORNERIS, Universidad de Buenos Aires (UBA)/ Facultad de Agronomía; INRA (Institut National de la Recherche Agronomique); ANDRÉS LEGARRA, INRA (Institut National de la Recherche Agronomique); Université de Toulouse; ZULMA G. VITEZICA, INRA (Institut National de la Recherche Agronomique); Université de Toulouse; SHOGO TSURUTA, Universidad de Georgia (UG); IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IGNACY MISZTAL, Universidad de Georgia (UG); RODOLFO J. C. CANTET, Universidad de Buenos Aires (UBA)/ Facultad de Agronomía; INRA (Institut National de la Recherche Agronomique). |
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Título : |
Quality control of genotypes using heritability estimates of gene content at the marker. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Genetics, 2015, v. 199, p. 675-681. OPEN ACCESS. |
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DOI : |
10.1534/genetics.114.173559 |
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Idioma : |
Inglés |
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Notas : |
Manuscript received September 26, 2014; accepted for publication December 18, 2014; published Early Online January 6, 2015. |
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Contenido : |
ABSTRACT
Quality control filtering of single-nucleotide polymorphisms (SNPs) is a key step when analyzing genomic data. Here we present a practical method to identify low-quality SNPs, meaning markers whose genotypes are wrongly assigned for a large proportion of individuals, by estimating the heritability of gene content at each marker, where gene content is the number of copies of a particular reference allele in a genotype of an animal (0, 1, or 2). If there is no mutation at the marker, gene content has an additive heritability of 1 by construction. The method uses restricted maximum likelihood (REML) to estimate heritability of gene content at each SNP and also builds a likelihood-ratio test statistic to test for zero error variance in genotyping. As a by-product, estimates of the allele frequencies of markers at the base population are obtained. Using simulated data with 10% permutation error (4% actual error) in genotyping, the method had a specificity of 0.96 (4% of correct markers are rejected) and a sensitivity of 0.99 (1% of wrong markers are accepted) if markers with heritability lower than 0.975 are discarded. Checking of Mendelian errors resulted in a lower sensitivity (0.84) for the same simulation. The proposed method is further illustrated with a real data set with genotypes from 3534 animals genotyped for 50,433 markers from the Illumina PorcineSNP60 chip and a pedigree of 6473 individuals; those markers underwent very little quality control. A total of 4099 markers with P-values lower than 0.01 were discarded based on our method, with associated estimates of heritability as low as 0.12. Contrary to other techniques, our method uses all information in the population simultaneously, can be used in any population with markers and pedigree recordings, and is simple to implement using standard software for REML estimation. Scripts for its use are provided.
Copyright © 2015 by the Genetics Society of America MenosABSTRACT
Quality control filtering of single-nucleotide polymorphisms (SNPs) is a key step when analyzing genomic data. Here we present a practical method to identify low-quality SNPs, meaning markers whose genotypes are wrongly assigned for a large proportion of individuals, by estimating the heritability of gene content at each marker, where gene content is the number of copies of a particular reference allele in a genotype of an animal (0, 1, or 2). If there is no mutation at the marker, gene content has an additive heritability of 1 by construction. The method uses restricted maximum likelihood (REML) to estimate heritability of gene content at each SNP and also builds a likelihood-ratio test statistic to test for zero error variance in genotyping. As a by-product, estimates of the allele frequencies of markers at the base population are obtained. Using simulated data with 10% permutation error (4% actual error) in genotyping, the method had a specificity of 0.96 (4% of correct markers are rejected) and a sensitivity of 0.99 (1% of wrong markers are accepted) if markers with heritability lower than 0.975 are discarded. Checking of Mendelian errors resulted in a lower sensitivity (0.84) for the same simulation. The proposed method is further illustrated with a real data set with genotypes from 3534 animals genotyped for 50,433 markers from the Illumina PorcineSNP60 chip and a pedigree of 6473 individuals; those markers underwent very little quality control. A total of 4... Presentar Todo |
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Palabras claves : |
GENE CONTENT; GENOMIC SELECTION; GENPRED; QUALITY CONTROL; REML; SHARED DATA RESOURCE; SNP. |
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Thesagro : |
MEJORAMIENTO GENETICO ANIMAL. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/5302/1/Forneris-et-al-2015-Genetics.pdf
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Marc : |
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024 7 $a10.1534/genetics.114.173559$2DOI
100 1 $aFORNERIS, N. S.
245 $aQuality control of genotypes using heritability estimates of gene content at the marker.$h[electronic resource]
260 $c2015
500 $aManuscript received September 26, 2014; accepted for publication December 18, 2014; published Early Online January 6, 2015.
520 $aABSTRACT Quality control filtering of single-nucleotide polymorphisms (SNPs) is a key step when analyzing genomic data. Here we present a practical method to identify low-quality SNPs, meaning markers whose genotypes are wrongly assigned for a large proportion of individuals, by estimating the heritability of gene content at each marker, where gene content is the number of copies of a particular reference allele in a genotype of an animal (0, 1, or 2). If there is no mutation at the marker, gene content has an additive heritability of 1 by construction. The method uses restricted maximum likelihood (REML) to estimate heritability of gene content at each SNP and also builds a likelihood-ratio test statistic to test for zero error variance in genotyping. As a by-product, estimates of the allele frequencies of markers at the base population are obtained. Using simulated data with 10% permutation error (4% actual error) in genotyping, the method had a specificity of 0.96 (4% of correct markers are rejected) and a sensitivity of 0.99 (1% of wrong markers are accepted) if markers with heritability lower than 0.975 are discarded. Checking of Mendelian errors resulted in a lower sensitivity (0.84) for the same simulation. The proposed method is further illustrated with a real data set with genotypes from 3534 animals genotyped for 50,433 markers from the Illumina PorcineSNP60 chip and a pedigree of 6473 individuals; those markers underwent very little quality control. A total of 4099 markers with P-values lower than 0.01 were discarded based on our method, with associated estimates of heritability as low as 0.12. Contrary to other techniques, our method uses all information in the population simultaneously, can be used in any population with markers and pedigree recordings, and is simple to implement using standard software for REML estimation. Scripts for its use are provided. Copyright © 2015 by the Genetics Society of America
650 $aMEJORAMIENTO GENETICO ANIMAL
653 $aGENE CONTENT
653 $aGENOMIC SELECTION
653 $aGENPRED
653 $aQUALITY CONTROL
653 $aREML
653 $aSHARED DATA RESOURCE
653 $aSNP
700 1 $aLEGARRA, A.
700 1 $aVITEZICA, Z. G.
700 1 $aTSURUTA, S.
700 1 $aAGUILAR, I.
700 1 $aMISZTAL, I.
700 1 $aCANTET, R. J. C.
773 $tGenetics, 2015$gv. 199, p. 675-681. OPEN ACCESS.
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