Genomic prediction in family bulks using different traits and cross-validations in pine.

Autor:	Rios EF; Agronomy Department, University of Florida, Gainesville, FL 32611, USA., Andrade MHML; Agronomy Department, University of Florida, Gainesville, FL 32611, USA., Resende MFR; Horticultural Sciences Department, University of Florida, Gainesville, FL 32611, USA., Kirst M; School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA., de Resende MDV; EMBRAPA Café/Department of Statistics, Federal University of Viçosa, Avenida PH Rolfs S/N, Viçosa 36570-000, Brazil., de Almeida Filho JE; Bayer Crop Science, Estrada da Invernadinha, 2000, Coxilha-RS 99145-000, Brazil., Gezan SA; VSN International Ltd, Hemel Hempstead HP2 4TP, UK., Munoz P; Horticultural Sciences Department, University of Florida, Gainesville, FL 32611, USA.
Jazyk:	angličtina
Zdroj:	G3 (Bethesda, Md.) [G3 (Bethesda)] 2021 Sep 06; Vol. 11 (9).
DOI:	10.1093/g3journal/jkab249
Abstrakt:	Genomic prediction integrates statistical, genomic, and computational tools to improve the estimation of breeding values and increase genetic gain. Due to the broad diversity in mating systems, breeding schemes, propagation methods, and unit of selection, no universal genomic prediction approach can be applied in all crops. In a genome-wide family prediction (GWFP) approach, the family is the basic unit of selection. We tested GWFP in two loblolly pine (Pinus taeda L.) datasets: a breeding population composed of 63 full-sib families (5-20 individuals per family), and a simulated population with the same pedigree structure. In both populations, phenotypic and genomic data was pooled at the family level in silico. Marker effects were estimated to compute genomic estimated breeding values (GEBV) at the individual and family (GWFP) levels. Less than six individuals per family produced inaccurate estimates of family phenotypic performance and allele frequency. Tested across different scenarios, GWFP predictive ability was higher than those for GEBV in both populations. Validation sets composed of families with similar phenotypic mean and variance as the training population yielded predictions consistently higher and more accurate than other validation sets. Results revealed potential for applying GWFP in breeding programs whose selection unit are family, and for systems where family can serve as training sets. The GWFP approach is well suited for crops that are routinely genotyped and phenotyped at the plot-level, but it can be extended to other breeding programs. Higher predictive ability obtained with GWFP would motivate the application of genomic prediction in these situations. (© The Author(s) 2021. Published by Oxford University Press on behalf of Genetics Society of America.)
Databáze:	MEDLINE
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