<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1405-3195</journal-id>
<journal-title><![CDATA[Agrociencia]]></journal-title>
<abbrev-journal-title><![CDATA[Agrociencia]]></abbrev-journal-title>
<issn>1405-3195</issn>
<publisher>
<publisher-name><![CDATA[Colegio de Postgraduados]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-31952016000500633</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Bayes empírico multivariado para predecir el mérito genético en plantas]]></article-title>
<article-title xml:lang="en"><![CDATA[Multivariate empirical Bayes to predict the plant breeding values]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ceron-Rojas]]></surname>
<given-names><![CDATA[J. Jesus]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Sahagún-Castellanos]]></surname>
<given-names><![CDATA[Jaime]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Autónoma Chapingo Instituto de Horticultura Departamento de Fitotecnia]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>08</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>08</month>
<year>2016</year>
</pub-date>
<volume>50</volume>
<numero>5</numero>
<fpage>633</fpage>
<lpage>648</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-31952016000500633&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-31952016000500633&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-31952016000500633&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: El mérito genético de las plantas es heredable y determina características fenotípicas como altura de planta y rendimiento de grano, y puede predecirse por medio de modelos bayesianos univariados o multivariados con base en la información fenotípica o genómica de las plantas. Estos modelos controlan la incertidumbre asociada a la predicción pero son computacionalmente demandantes, por lo cual se requieren modelos alternativos menos demandantes. Bayes empírico es un método de predicción en el cual la esperanza de la distribución posterior es el estimador del mérito genético. Éste es una variante del estimador bayesiano estándar y es eficiente; es robusto ante las especificaciones erróneas de la distribución a priori de los parámetros y las covarianzas de éstos pueden estimarse por verosimilitud restringida. Para predecir el mérito genético en el contexto Bayes empírico se propuso un modelo lineal multivariado, el cual incorpora las correlaciones genéticas entre caracteres, la información del pedigrí, la información genómica, y contiene al modelo lineal genómico multivariado y al modelo lineal estándar multivariado como casos particulares. El modelo genómico usa solo información genómica mientras que el modelo estándar usa sólo información del pedigrí en la predicción. Para comparar numéricamente la eficiencia de cada uno de los tres modelos se usaron las correlaciones entre los valores predichos y observados obtenidas con los datos de dos poblaciones de maíz (Zea mays) F2 y una población de trigo (Triticum aestivum L.) doble haploide, cada una de éstas con tres características y un conjunto particular de marcadores moleculares y genotipos. En las tres poblaciones los resultados numéricos indicaron que el modelo propuesto proporciona predicciones más precisas que los otros dos. Concluimos que los resultados se deben a que el modelo propuesto usa en la predicción, además de las correlaciones genéticas entre caracteres, la información fenotípica y genómica.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: The plant breeding value is inheritable and determines phenotypic characteristics such as plant height, and grain yield, and it can be predicted by means of univariate or multivariate Bayesian models based on the phenotypic or genomic plants information. These models control the uncertainty associated to prediction better, but this comes at a high computational cost, so less demanding alternative models are required. Empirical Bayes is a prediction method in which the expectation of the posterior distribution is the estimator of the breeding value. This is a variant of the standard Bayesian estimator and is efficient; it is robust to the erroneous specifications of the a priori distribution of parameters, and the parameter covariances can be estimated through restricted maximum likelihood. A multivariate linear model was proposed to predict the breeding value within the empirical Bayes context. This model incorporates the genetic correlations between traits, pedigree information, genomic information, and contains the multivariate genomic linear model and the multivariate standard linear model as particular cases. The genomic model uses only genomic information, whereas the standard model uses only information from the pedigree in the prediction. To compare numerically the efficiency of each of the three models, the correlations between the predicted and observed values obtained with the data from two maize (Zea mays) F2 populations and one double haploid wheat (Triticum aestivum L.) population, each of them with three characteristics and a particular set of molecular markers and genotypes, were used. In the three populations, the numerical results indicated that the model proposed provides more precise predictions than the other two. We concluded that the results were due to the fact that the model proposed used the genetic correlations between traits and the phenotypic, as well as genomic information, in the prediction.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Distribución posterior conjunta]]></kwd>
<kwd lng="es"><![CDATA[marcadores moleculares]]></kwd>
<kwd lng="es"><![CDATA[modelo lineal multivariado]]></kwd>
<kwd lng="es"><![CDATA[Triticum aestivum]]></kwd>
<kwd lng="es"><![CDATA[verosimilitud restringida]]></kwd>
<kwd lng="es"><![CDATA[Zea mays]]></kwd>
<kwd lng="en"><![CDATA[Joint posterior distribution]]></kwd>
<kwd lng="en"><![CDATA[molecular markers]]></kwd>
<kwd lng="en"><![CDATA[multivariate linear model]]></kwd>
<kwd lng="en"><![CDATA[Triticum aestivum]]></kwd>
<kwd lng="en"><![CDATA[restricted likelihood]]></kwd>
<kwd lng="en"><![CDATA[Zea mays]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Blasco]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The Bayesian controversy in animal breeding]]></article-title>
<source><![CDATA[J. Anim. Sci.]]></source>
<year>2001</year>
<volume>79</volume>
<page-range>2023-46</page-range></nlm-citation>
</ref>
<ref id="B2">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Beyene]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Semagn]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
<name>
<surname><![CDATA[Mugo]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Tarekegne]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Babu]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Meise]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
<name>
<surname><![CDATA[Sehabiague]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Makumbi]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Magorokosho]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Oikeh]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Gakunga]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Vargas]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Olsen]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Prasanna]]></surname>
<given-names><![CDATA[B. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Banziger]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Crossa]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Genetic gains in grain yield through genomic selection 1 in eight bi-parental maize populations under drought stress]]></article-title>
<source><![CDATA[Crop Sci.]]></source>
<year>2015</year>
<volume>55</volume>
<page-range>154-63</page-range></nlm-citation>
</ref>
<ref id="B3">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Bulmer]]></surname>
<given-names><![CDATA[M. G.]]></given-names>
</name>
</person-group>
<source><![CDATA[The Mathematical Theory of Quantitative Genetics. Lectures in Biomathematics]]></source>
<year>1980</year>
<publisher-name><![CDATA[University of Oxford]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B4">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Calus]]></surname>
<given-names><![CDATA[M. P. L.]]></given-names>
</name>
<name>
<surname><![CDATA[Veerkamp]]></surname>
<given-names><![CDATA[R. F.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Accuracy of multi-trait genomic selection using different methods]]></article-title>
<source><![CDATA[Genet. Selection Evol.]]></source>
<year>2011</year>
<volume>43</volume>
</nlm-citation>
</ref>
<ref id="B5">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Casella]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
<name>
<surname><![CDATA[George]]></surname>
<given-names><![CDATA[E. I.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Explaining the Gibbs sampler]]></article-title>
<source><![CDATA[The Am. Stat.]]></source>
<year>1992</year>
<volume>46</volume>
<page-range>167-74</page-range></nlm-citation>
</ref>
<ref id="B6">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[de los Campos]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
<name>
<surname><![CDATA[Hickey]]></surname>
<given-names><![CDATA[J. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Pong-Wong]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<name>
<surname><![CDATA[Daetwyler]]></surname>
<given-names><![CDATA[H. D.]]></given-names>
</name>
<name>
<surname><![CDATA[Calus]]></surname>
<given-names><![CDATA[M. P. L.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Whole-genome regression and prediction methods applied to plant and animal breeding]]></article-title>
<source><![CDATA[Genetics]]></source>
<year>2013</year>
<volume>193</volume>
<page-range>327-45</page-range></nlm-citation>
</ref>
<ref id="B7">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Gianola]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Priors in whole-genome regression: the bayesian alphabet returns]]></article-title>
<source><![CDATA[Genetics]]></source>
<year>2013</year>
<volume>194</volume>
<page-range>573-96</page-range></nlm-citation>
</ref>
<ref id="B8">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hayashi]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Iwata]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A Bayesian method and its variational approximation for prediction of genomic breeding values in multiple traits]]></article-title>
<source><![CDATA[BMC Bioinf.]]></source>
<year>2013</year>
<volume>14</volume>
<page-range>34</page-range></nlm-citation>
</ref>
<ref id="B9">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Habier]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Fernando]]></surname>
<given-names><![CDATA[R. L.]]></given-names>
</name>
<name>
<surname><![CDATA[Dekkers]]></surname>
<given-names><![CDATA[J. C. M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The impact of genetic relationship information on genome-assisted breeding values]]></article-title>
<source><![CDATA[Genetics]]></source>
<year>2007</year>
<volume>177</volume>
<page-range>2389-97</page-range></nlm-citation>
</ref>
<ref id="B10">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jia]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Jannink]]></surname>
<given-names><![CDATA[J. L.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Multiple-trait genomic selection methods increase genetic value prediction accuracy]]></article-title>
<source><![CDATA[Genetics]]></source>
<year>2012</year>
<volume>192</volume>
<page-range>1513-22</page-range></nlm-citation>
</ref>
<ref id="B11">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Langville]]></surname>
<given-names><![CDATA[A. N.]]></given-names>
</name>
<name>
<surname><![CDATA[Stewart]]></surname>
<given-names><![CDATA[W. J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The Kronecker product and stochastic automata networks]]></article-title>
<source><![CDATA[J. Comp. Appl. Math.]]></source>
<year>2004</year>
<volume>167</volume>
<page-range>429-44</page-range></nlm-citation>
</ref>
<ref id="B12">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Legarra]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Aguilar]]></surname>
<given-names><![CDATA[I.]]></given-names>
</name>
<name>
<surname><![CDATA[Misztal]]></surname>
<given-names><![CDATA[I.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A relationship matrix including full pedigree and genomic information]]></article-title>
<source><![CDATA[J. Dairy Sci.]]></source>
<year>2009</year>
<volume>92</volume>
<page-range>4656-63</page-range></nlm-citation>
</ref>
<ref id="B13">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lehmann]]></surname>
<given-names><![CDATA[E. L.]]></given-names>
</name>
<name>
<surname><![CDATA[Casella]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
</person-group>
<source><![CDATA[Theory of Point Estimation]]></source>
<year>1998</year>
<edition>2</edition>
<publisher-name><![CDATA[Springer-Verlag New York]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B14">
<nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lynch]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Walsh]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
</person-group>
<source><![CDATA[Genetics and Analysis of Quantitative Traits]]></source>
<year>1998</year>
<publisher-loc><![CDATA[Massachusetts, USA ]]></publisher-loc>
</nlm-citation>
</ref>
<ref id="B15">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Massman]]></surname>
<given-names><![CDATA[J. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Gordillo]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Lorenzana]]></surname>
<given-names><![CDATA[R. E.]]></given-names>
</name>
<name>
<surname><![CDATA[Bernardo]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Genomewide predictions from maize single-cross data]]></article-title>
<source><![CDATA[Theor. Appl. Genet.]]></source>
<year>2013</year>
<volume>126</volume>
<page-range>13-22</page-range></nlm-citation>
</ref>
<ref id="B16">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Meuwissen]]></surname>
<given-names><![CDATA[T. H. E.]]></given-names>
</name>
<name>
<surname><![CDATA[Hayes]]></surname>
<given-names><![CDATA[B. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Goddard]]></surname>
<given-names><![CDATA[M. E.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Prediction of total genetic value using genome-wide dense marker maps]]></article-title>
<source><![CDATA[Genetics]]></source>
<year>2001</year>
<volume>157</volume>
<page-range>1819-29</page-range></nlm-citation>
</ref>
<ref id="B17">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Robinson]]></surname>
<given-names><![CDATA[G. K.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[That BLUP is a good thing: The estimation of random effects]]></article-title>
<source><![CDATA[Stat. Sci.]]></source>
<year>1991</year>
<volume>6</volume>
<page-range>15-51</page-range></nlm-citation>
</ref>
<ref id="B18">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Sorensen]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Gianola]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
</person-group>
<source><![CDATA[Likelihood, Bayesian, and MCMC Methods in Quantitative Genetics]]></source>
<year>2002</year>
<publisher-loc><![CDATA[New York ]]></publisher-loc>
<publisher-name><![CDATA[Springer]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B19">
<nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Tempelman]]></surname>
<given-names><![CDATA[R. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Rosa]]></surname>
<given-names><![CDATA[G. J. M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Empirical Bayes approach to mixed model inference in quantitative genetics]]></article-title>
<person-group person-group-type="editor">
<name>
<surname><![CDATA[Saxto]]></surname>
<given-names><![CDATA[A. M.]]></given-names>
</name>
</person-group>
<source><![CDATA[Genetics Analysis of Complex Traits Using SAS]]></source>
<year>2004</year>
<page-range>149-76</page-range><publisher-loc><![CDATA[Cary N.C. ]]></publisher-loc>
<publisher-name><![CDATA[SAS Institute Inc.]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B20">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[VanRaden]]></surname>
<given-names><![CDATA[P.M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Efficient methods to compute genomic predictions]]></article-title>
<source><![CDATA[J. Dairy Sci.]]></source>
<year>2008</year>
<volume>91</volume>
<page-range>4414-23</page-range></nlm-citation>
</ref>
<ref id="B21">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Vattikuti]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Guo]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Chow]]></surname>
<given-names><![CDATA[C. C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Heritability and genetic correlations explained by common SNPs for metabolic syndrome traits]]></article-title>
<source><![CDATA[PLoS Genet]]></source>
<year>2012</year>
<volume>8</volume>
<numero>3</numero>
<issue>3</issue>
</nlm-citation>
</ref>
<ref id="B22">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Verbyla]]></surname>
<given-names><![CDATA[K. L.]]></given-names>
</name>
<name>
<surname><![CDATA[Hayes]]></surname>
<given-names><![CDATA[B. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Bowman]]></surname>
<given-names><![CDATA[P. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Goddard]]></surname>
<given-names><![CDATA[M. E.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Accuracy of genomic selection using stochastic search variable selection in Australian Holstein Friesian dairy cattle]]></article-title>
<source><![CDATA[Genet. Res. Camb.]]></source>
<year>2009</year>
<volume>91</volume>
<page-range>307-11</page-range></nlm-citation>
</ref>
<ref id="B23">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Verbyla]]></surname>
<given-names><![CDATA[K. L.]]></given-names>
</name>
<name>
<surname><![CDATA[Bowman]]></surname>
<given-names><![CDATA[P. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Hayes]]></surname>
<given-names><![CDATA[B. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Goddard]]></surname>
<given-names><![CDATA[M. E.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Sensitivity of genomic selection to using different prior distributions]]></article-title>
<source><![CDATA[MCM Proceeding]]></source>
<year>2010</year>
<volume>4</volume>
<numero>^s1</numero>
<issue>^s1</issue>
<supplement>1</supplement>
</nlm-citation>
</ref>
</ref-list>
</back>
</article>
