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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
01/10/2014 |
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Actualizado : |
11/12/2018 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
LEMOS, M.V.A.; CHIAIA, H.L.J.; BERTON, M.P.; FEITOSA, F.L.B.; ABOUJAOUD, C.; CAMARGO, G.M.F.; PEREIRA, A.S.C.; ALBUQUERQUE, L.G.; FERRINHO, A.M.; MUELLER, L.F.; MAZALLI, M.R.; FURLAN, J.J.M.; CARVALHEIRO, R.; GORDO, D.M.; TONUSSI, R.; ESPIGOLAN, R.; SILVA, R.M.O.; DE OLIVEIRA, H.N.; DUCKETT, S.; AGUILAR, I.; BALDI, F. |
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Afiliación : |
MARCOS V. A. LEMOS, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista; HERMENEGILDO LUCAS JUSTINO CHIAIA, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista; MARIANA PIATTO BERTON, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista; FABIELI L. B. FEITOSA, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista; CAROLYN ABOUJAOUD, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista; GREGÓRIO M. F. CAMARGO, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista; ANGÉLICA S. C. PEREIRA, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo; LUCIA G. ALBUQUERQUE, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista; ADRIELLE M. FERRINHO, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo; LENISE F. MUELLER, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo; MONICA R. MAZALLI, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo; JOYCE J. M. FURLAN, Faculdade de Medicina Veterinária e Zootecnia, Universidade de São Paulo; ROBERTO CARVALHEIRO, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista; DANIEL M. GORDO, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista; RAFAEL TONUSSI, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista; RAFAEL ESPIGOLAN, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista; RAFAEL MEDEIROS DE OLIVEIRA SILVA, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista; HENRIQUE NUNES DE OLIVEIRA, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista; SUSAN DUCKETT, Department of Animal and Veterinary Science, Clemson University; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BALDI, Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista. |
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Título : |
Genome-wide association between single nucleotide polymorphisms with beef fatty acid profile in Nellore cattle using the single step procedure. |
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Fecha de publicación : |
2016 |
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Fuente / Imprenta : |
BMC Genomics, 2016, v. 17:213. |
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DOI : |
10.1186/s12864-016-2511-y |
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Idioma : |
Inglés |
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Notas : |
Received: 19 November 2015 / Accepted: 23 February 2016 /Published: 9 March 2016 |
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Contenido : |
ABSTRACT.
Background: Saturated fatty acids can be detrimental to human health and have received considerable attention in recent years. Several studies using taurine breeds showed the existence of genetic variability and thus the possibility of genetic improvement of the fatty acid profile in beef. This study identified the regions of the genome associated with saturated, mono- and polyunsaturated fatty acids, and n-6 to n-3 ratios in the Longissimus thoracis of Nellore finished in feedlot, using the single-step method.
Results: The results showed that 115 windows explain more than 1 % of the additive genetic variance for the 22 studied fatty acids. Thirty-one genomic regions that explain more than 1 % of the additive genetic variance were observed for total saturated fatty acids, C12:0, C14:0, C16:0 and C18:0. Nineteen genomic regions, distributed in sixteen different chromosomes accounted for more than 1 % of the additive genetic variance for the monounsaturated fatty acids, such as the sum of monounsaturated fatty acids, C14:1 cis-9,
C18:1 trans-11, C18:1 cis-9, and C18:1 trans-9. Forty genomic regions explained more than 1 % of the additive variance for the polyunsaturated fatty acids group, which are related to the total polyunsaturated fatty acids, C20:4 n-6, C18:2 cis-9 cis12 n-6, C18:3 n-3, C18:3 n-6, C22:6 n-3 and C20:3 n-6 cis-8 cis-11 cis-14. Twenty-one genomic regions accounted for more than 1 % of the genetic variance for the group of omega-3, omega-6 and the n-6:n-3 ratio.
Conclusions: The identification of such regions and the respective candidate genes, such as ELOVL5, ESSRG, PCYT1A and genes of the ABC group (ABC5, ABC6 and ABC10), should contribute to form a genetic basis of the fatty acid profile of Nellore (Bos indicus) beef, contributing to better selection of the traits associated with improving human health.
© Lemos et al. 2016 MenosABSTRACT.
Background: Saturated fatty acids can be detrimental to human health and have received considerable attention in recent years. Several studies using taurine breeds showed the existence of genetic variability and thus the possibility of genetic improvement of the fatty acid profile in beef. This study identified the regions of the genome associated with saturated, mono- and polyunsaturated fatty acids, and n-6 to n-3 ratios in the Longissimus thoracis of Nellore finished in feedlot, using the single-step method.
Results: The results showed that 115 windows explain more than 1 % of the additive genetic variance for the 22 studied fatty acids. Thirty-one genomic regions that explain more than 1 % of the additive genetic variance were observed for total saturated fatty acids, C12:0, C14:0, C16:0 and C18:0. Nineteen genomic regions, distributed in sixteen different chromosomes accounted for more than 1 % of the additive genetic variance for the monounsaturated fatty acids, such as the sum of monounsaturated fatty acids, C14:1 cis-9,
C18:1 trans-11, C18:1 cis-9, and C18:1 trans-9. Forty genomic regions explained more than 1 % of the additive variance for the polyunsaturated fatty acids group, which are related to the total polyunsaturated fatty acids, C20:4 n-6, C18:2 cis-9 cis12 n-6, C18:3 n-3, C18:3 n-6, C22:6 n-3 and C20:3 n-6 cis-8 cis-11 cis-14. Twenty-one genomic regions accounted for more than 1 % of the genetic variance for the group of omega-3, omega-6 and the ... Presentar Todo |
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Palabras claves : |
BOS INDICUS; FATTY ACID COMPOSITION; GENETIC MARKERS; HERITABILITY; SSGWAS. |
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Thesagro : |
CEBU. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/5871/1/Lemos-M.V.A.-2016.-BMC-Genomics.pdf
https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-016-2511-y
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Marc : |
LEADER 03229naa a2200457 a 4500
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008 2016 bl uuuu u00u1 u #d
024 7 $a10.1186/s12864-016-2511-y$2DOI
100 1 $aLEMOS, M.V.A.
245 $aGenome-wide association between single nucleotide polymorphisms with beef fatty acid profile in Nellore cattle using the single step procedure.$h[electronic resource]
260 $c2016
500 $aReceived: 19 November 2015 / Accepted: 23 February 2016 /Published: 9 March 2016
520 $aABSTRACT. Background: Saturated fatty acids can be detrimental to human health and have received considerable attention in recent years. Several studies using taurine breeds showed the existence of genetic variability and thus the possibility of genetic improvement of the fatty acid profile in beef. This study identified the regions of the genome associated with saturated, mono- and polyunsaturated fatty acids, and n-6 to n-3 ratios in the Longissimus thoracis of Nellore finished in feedlot, using the single-step method. Results: The results showed that 115 windows explain more than 1 % of the additive genetic variance for the 22 studied fatty acids. Thirty-one genomic regions that explain more than 1 % of the additive genetic variance were observed for total saturated fatty acids, C12:0, C14:0, C16:0 and C18:0. Nineteen genomic regions, distributed in sixteen different chromosomes accounted for more than 1 % of the additive genetic variance for the monounsaturated fatty acids, such as the sum of monounsaturated fatty acids, C14:1 cis-9, C18:1 trans-11, C18:1 cis-9, and C18:1 trans-9. Forty genomic regions explained more than 1 % of the additive variance for the polyunsaturated fatty acids group, which are related to the total polyunsaturated fatty acids, C20:4 n-6, C18:2 cis-9 cis12 n-6, C18:3 n-3, C18:3 n-6, C22:6 n-3 and C20:3 n-6 cis-8 cis-11 cis-14. Twenty-one genomic regions accounted for more than 1 % of the genetic variance for the group of omega-3, omega-6 and the n-6:n-3 ratio. Conclusions: The identification of such regions and the respective candidate genes, such as ELOVL5, ESSRG, PCYT1A and genes of the ABC group (ABC5, ABC6 and ABC10), should contribute to form a genetic basis of the fatty acid profile of Nellore (Bos indicus) beef, contributing to better selection of the traits associated with improving human health. © Lemos et al. 2016
650 $aCEBU
653 $aBOS INDICUS
653 $aFATTY ACID COMPOSITION
653 $aGENETIC MARKERS
653 $aHERITABILITY
653 $aSSGWAS
700 1 $aCHIAIA, H.L.J.
700 1 $aBERTON, M.P.
700 1 $aFEITOSA, F.L.B.
700 1 $aABOUJAOUD, C.
700 1 $aCAMARGO, G.M.F.
700 1 $aPEREIRA, A.S.C.
700 1 $aALBUQUERQUE, L.G.
700 1 $aFERRINHO, A.M.
700 1 $aMUELLER, L.F.
700 1 $aMAZALLI, M.R.
700 1 $aFURLAN, J.J.M.
700 1 $aCARVALHEIRO, R.
700 1 $aGORDO, D.M.
700 1 $aTONUSSI, R.
700 1 $aESPIGOLAN, R.
700 1 $aSILVA, R.M.O.
700 1 $aDE OLIVEIRA, H.N.
700 1 $aDUCKETT, S.
700 1 $aAGUILAR, I.
700 1 $aBALDI, F.
773 $tBMC Genomics, 2016$gv. 17:213.
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Registro original : |
INIA Las Brujas (LB) |
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Biblioteca
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Identificación
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Origen
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Tipo / Formato
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Clasificación
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Registro
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Volver
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
09/09/2014 |
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Actualizado : |
23/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
A - 1 |
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Autor : |
LOURENCO, D.A.L.; MISZTAL, I.; TSURUTA, S.; AGUILAR, I.; EZRA, E.; RON, M.; SHIRAK, A.; WELLER, J.I. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
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Título : |
Methods for genomic evaluation of a relatively small genotyped dairy population and effect of genotyped cow information in multiparity analyses. |
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Fecha de publicación : |
2014 |
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Fuente / Imprenta : |
Journal of Dairy Science, 2014, v.97, no.3, p.1742-1752. OPEN ACCESS. |
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ISSN : |
0022-0302 |
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DOI : |
10.3168/jds.2013-6916 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received September 10, 2013. / Accepted December 6, 2013. |
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Contenido : |
ABSTRACTS.
Methods for genomic prediction were evaluated for an Israeli Holstein dairy population of 713,686 cows and 1,305 progeny-tested bulls with genotypes. Inclusion of genotypes of 343 elite cows in an evaluation method that considers pedigree, phenotypes, and genotypes simultaneously was also evaluated. Two data sets were available: a complete data set with production records from 1985 through 2011, and a reduced data set with records after 2006 deleted. For each production trait, a multitrait animal model was used to compute traditional genetic evaluations for parities 1 through 3 as separate traits. Evaluations were calculated for the reduced and complete data sets. The evaluations from the reduced data set were used to calculate parent average for validation bulls, which was the benchmark for comparing gain in predictive ability from genomics. Genomic predictions for bulls in 2006 were calculated using a Bayesian regression method (BayesC), genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), and weighted ssGBLUP (WssGBLUP). Predictions using BayesC and GBLUP were calculated either with or without an index that included parent average. Genomic predictions that included elite cow genotypes were calculated using ssGBLUP and WssGBLUP. Predictive ability was assessed by coefficients of determination (R2) and regressions of predictions of 135 validation bulls with no daughters in 2006 on deregressed evaluations of those bulls in 2011. A reduction in R2 and regression coefficients was observed from parities 1 through 3. Fat and protein yields had the lowest R2 for all the methods. On average, R2 was lowest for parent averages, followed by GBLUP, BayesC, ssGBLUP, and WssGBLUP. For some traits, R2 for direct genomic values from BayesC and GBLUP were lower than those for parent averages. Genomic estimated breeding values using ssGBLUP were the least biased, and this method appears to be a suitable tool for genomic evaluation of a small genotyped population, as it automatically accounts for parental index, allows for inclusion of female genomic information without preadjustments in evaluations, and uses the same model as in traditional evaluations. Weighted ssGBLUP has the potential for higher evaluation accuracy.
© 2014 American Dairy Science Association. MenosABSTRACTS.
Methods for genomic prediction were evaluated for an Israeli Holstein dairy population of 713,686 cows and 1,305 progeny-tested bulls with genotypes. Inclusion of genotypes of 343 elite cows in an evaluation method that considers pedigree, phenotypes, and genotypes simultaneously was also evaluated. Two data sets were available: a complete data set with production records from 1985 through 2011, and a reduced data set with records after 2006 deleted. For each production trait, a multitrait animal model was used to compute traditional genetic evaluations for parities 1 through 3 as separate traits. Evaluations were calculated for the reduced and complete data sets. The evaluations from the reduced data set were used to calculate parent average for validation bulls, which was the benchmark for comparing gain in predictive ability from genomics. Genomic predictions for bulls in 2006 were calculated using a Bayesian regression method (BayesC), genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), and weighted ssGBLUP (WssGBLUP). Predictions using BayesC and GBLUP were calculated either with or without an index that included parent average. Genomic predictions that included elite cow genotypes were calculated using ssGBLUP and WssGBLUP. Predictive ability was assessed by coefficients of determination (R2) and regressions of predictions of 135 validation bulls with no daughters in 2006 on deregressed evaluations of those bulls in 2011. A reduction in R2 and regression coe... Presentar Todo |
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Thesagro : |
MEJORAMIENTO GENÉTICO ANIMAL; MODELOS MATEMÁTICOS; SELECCIÓN DE GENOTIPOS; SELECCIÓN GENÓMICA. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/3043/1/Aguilar-I.-2014-Jr.Dairy-Sci.-v.973-p.1742-1752.pdf
https://www.journalofdairyscience.org/article/S0022-0302(14)00052-6/pdf
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Marc : |
LEADER 03270naa a2200289 a 4500
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008 2014 bl uuuu u00u1 u #d
022 $a0022-0302
024 7 $a10.3168/jds.2013-6916$2DOI
100 1 $aLOURENCO, D.A.L.
245 $aMethods for genomic evaluation of a relatively small genotyped dairy population and effect of genotyped cow information in multiparity analyses.$h[electronic resource]
260 $c2014
500 $aArticle history: Received September 10, 2013. / Accepted December 6, 2013.
520 $aABSTRACTS. Methods for genomic prediction were evaluated for an Israeli Holstein dairy population of 713,686 cows and 1,305 progeny-tested bulls with genotypes. Inclusion of genotypes of 343 elite cows in an evaluation method that considers pedigree, phenotypes, and genotypes simultaneously was also evaluated. Two data sets were available: a complete data set with production records from 1985 through 2011, and a reduced data set with records after 2006 deleted. For each production trait, a multitrait animal model was used to compute traditional genetic evaluations for parities 1 through 3 as separate traits. Evaluations were calculated for the reduced and complete data sets. The evaluations from the reduced data set were used to calculate parent average for validation bulls, which was the benchmark for comparing gain in predictive ability from genomics. Genomic predictions for bulls in 2006 were calculated using a Bayesian regression method (BayesC), genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), and weighted ssGBLUP (WssGBLUP). Predictions using BayesC and GBLUP were calculated either with or without an index that included parent average. Genomic predictions that included elite cow genotypes were calculated using ssGBLUP and WssGBLUP. Predictive ability was assessed by coefficients of determination (R2) and regressions of predictions of 135 validation bulls with no daughters in 2006 on deregressed evaluations of those bulls in 2011. A reduction in R2 and regression coefficients was observed from parities 1 through 3. Fat and protein yields had the lowest R2 for all the methods. On average, R2 was lowest for parent averages, followed by GBLUP, BayesC, ssGBLUP, and WssGBLUP. For some traits, R2 for direct genomic values from BayesC and GBLUP were lower than those for parent averages. Genomic estimated breeding values using ssGBLUP were the least biased, and this method appears to be a suitable tool for genomic evaluation of a small genotyped population, as it automatically accounts for parental index, allows for inclusion of female genomic information without preadjustments in evaluations, and uses the same model as in traditional evaluations. Weighted ssGBLUP has the potential for higher evaluation accuracy. © 2014 American Dairy Science Association.
650 $aMEJORAMIENTO GENÉTICO ANIMAL
650 $aMODELOS MATEMÁTICOS
650 $aSELECCIÓN DE GENOTIPOS
650 $aSELECCIÓN GENÓMICA
700 1 $aMISZTAL, I.
700 1 $aTSURUTA, S.
700 1 $aAGUILAR, I.
700 1 $aEZRA, E.
700 1 $aRON, M.
700 1 $aSHIRAK, A.
700 1 $aWELLER, J.I.
773 $tJournal of Dairy Science, 2014$gv.97, no.3, p.1742-1752. OPEN ACCESS.
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