Multiple-trait analyses improved the accuracy of genomic prediction and the power of genome-wide association of productivity and climate change-adaptive traits in lodgepole pine

被引：0
作者：
Eduardo P. Cappa
Charles Chen
Jennifer G. Klutsch
Jaime Sebastian-Azcona
Blaise Ratcliffe
Xiaojing Wei
Letitia Da Ros
Aziz Ullah
Yang Liu
Andy Benowicz
Shane Sadoway
Shawn D. Mansfield
Nadir Erbilgin
Barb R. Thomas
Yousry A. El-Kassaby
机构：
[1] Instituto Nacional de Tecnología Agropecuaria (INTA),Department of Biochemistry and Molecular Biology
[2] Instituto de Recursos Biológicos,Department of Renewable Resources
[3] Centro de Investigación en Recursos Naturales,Present address: Department of Forestry
[4] Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET),Department of Forest and Conservation Sciences, Faculty of Forestry
[5] Oklahoma State University,Department of Wood Science, Faculty of Forestry
[6] University of Alberta,undefined
[7] New Mexico Highlands University,undefined
[8] Present address: Irrigation and Crop Ecophysiology Group,undefined
[9] Instituto de Recursos Naturales y Agrobiología de Sevilla,undefined
[10] Avenida Reina Mercedes,undefined
[11] University of British Columbia,undefined
[12] University of British Columbia,undefined
[13] Forest Stewardship and Trade Branch,undefined
[14] Alberta Agriculture and Forestry,undefined
[15] Blue Ridge Lumber Inc.,undefined
[16] West Fraser Mills Ltd,undefined
来源：
BMC Genomics | / 23卷
关键词：
Quantitative genetic parameters; Genomic prediction; Genome wide association analyses; Single- and multiple-trait mixed models; Lodgepole pine;
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