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Fedorkov A. L. Genomic Selection in Tree Breeding

genomic prediction, DNA-markers, wood quality traits, growth traits, breeding value


UDC 630*165.4:016

Fedorkov A. L. Genomic selection in tree breeding // Sibirskij Lesnoj Zurnal (Sib. J. For. Sci.). 2020. N. 6. P. 86–90 (in Russian with English abstract and references).

DOI: 10.15372/SJFS20200608

© Fedorkov A. L., 2020

The literature review concerning genomic selection in forest tree breeding is given. Genomic selection is based on relationships between phenotypic traits and genetic markers (single nucleotide polymorphism, SNP). Using genomic selection it is possible to get genomic estimated breeding value of plus tree without long tree progeny testing in field and selection cycle is significantly shortened. Tree breeding programs with genomic selection for Scots pine Pinus sylvestris L., lodgepole pine P. contorta Douglas ex Loudon, maritime pine P. pinaster Aiton, loblolly pine P. taeda L., Norway spruce Picea abies (L.) Karst., white spruce P. glauca (Moench) Voss, black spruce P. mariana (Mill.) Britton, Sterns & Poggenb., hybrid spruce P. glauca (Moench) Voss. × P. engelmannii Parry ex Engelm., Douglas spruce Pseudotsuga menziesii Mirb. (Franco), eucalypt Eucalyptus L'Hеr. and chestnut Castanea Mill. realized in Sweden, Canada, France, United States, Brazil and New Zealand are shortly described. It is shown that genomic selection is applied mainly for growth traits (height and diameter), quality traits of wood (microfibril angle, wood elasticity and density), as well resistance to fungal diseases and insects. The literature data about optimal number of DNA-markers on the accuracy of genomic prediction are presented. In general estimates of genomic prediction for traits studied were high enough. Taken together these estimates and high economic efficiency due to shortening of breeding cycle it is possible to conclude about prospects of genomic selection in forest tree breeding. The lack of progeny field tests established by full-sib families is limiting factor to apply genomic selection in our country, but clonal archives of plus trees can be used. 



Приказ Минприроды РФ от 20 октября 2015 г. № 438 «Об утверждении Правил создания и выделения объектов лесного семеноводства (лесосеменных плантаций, постоянных лесосеменных участков и подобных объектов)». Зарег. в Минюсте РФ 12 февраля 2016 г. № 41078 [Prikaz Ministerstva prirodnykh resursov i ekologii RF ot 20 oktyabrya 2015 N. 438 «Ob utverzhdenii Pravil sozdaniya i vydeleniya obyektov lesnogo semenovodstva (lesosemennykh plantatsy, postoyannykh lesosemennykh uchastkov i podobnykh obyektov)». Zareg. v Minyuste RF 12 fevralya 2016 g. N. 41078 (Order of Natural Resources and Ecology of the Russian Federation of October 20, 2015 N. 438 «On Approval of the Rules for the Creation and Allocation of Forest Seed Objects (Forest Seed Plantations, Permanent Forest Seed Plots and Similar Objects)». Reg. Min. Justice Rus. Fed. 12 February 2016 N. 41078) (in Russian)].

Beaulieu J., Doerksen T. K., MacKay J., Rainville A., Bousquet J. Genomic selection accuracies within and between environments and small breeding groups in white spruce // BMC Genomics. 2014. N. 15. P. 1048.

Calleja-Rodriguez A., Pan J., Funda T., Chen Z-Q., Baison J., Isik F., Abrahamsson S., Wu H. X. Genomic prediction accuracies and abilities for growth and wood quality traits of Scots pine, using genotyping-by-sequencing (GBS) data // BioRxiv. 2019.

Chen Z-Q., Baison J., Pan B., Karlsson B., Andersson B., Westin J., García-Gil1 M. R., Wu H. X. Accuracy of genomic selection for growth and wood quality traits in two control-pollinated progeny trials using exome capture as the genotyping platform in Norway spruce // BMC Genomics. 2018. N. 19. P. 1–16.

Grattapaglia D., Resende M. D. Genomic selection in forest tree breeding // Tree Genet. Genomes. 2011. V. 7. Iss. 2. P. 241–255.

Isik F. Genomic selection in forest tree breeding: the concept and an outlook to the future // New Forests. 2014. V. 45. N. 3. P. 379–401.

Isik F., Bartholomé J., Farjat A., Chancerel E., Raffin A., Sanchez L., Plomion C., Bouffier L. Genomic selection in maritime pine // Plant Sci. 2016. V. 242. P. 108–119.

Lenz P. R., Beaulieu J., Mansfield S. D., Clément S., Desponts M., Bousquet J. Factors affecting the accuracy of genomic selection for growth and wood quality traits in an advanced-breeding population of black spruce (Picea mariana) // BMC Genomics. 2017. N. 18. P. 1–17.

Lenz P. R., Nadeau S., Mottet M-J., Perron M., Isabel N., Beaulieu J., Bousquet J. Multi‐trait genomic selection for weevil resistance, growth, and wood quality in Norway spruce // Evolut. Appl. 2019. V. 13. Iss. 1. P. 76–94.

Meuwissen T. H., Hayes B. J., Goddard M. E. Prediction of total genetic value using genome-wide dense marker maps // Genetics. 2001. V. 157. N. 4. P. 1819–1829.

Ratcliffe B., El-Dien O. G., Klápště J., Porth I., Chen C., Jaquish B., El-Kassaby Y. A. A comparison of genomic selection models across time in interior spruce (Picea engelmannii × glauca) using unordered SNP imputation methods // Heredity. 2015. V. 115. P. 547–555.

Resende M. F., Munoz P., Acosta J. J., Peter G. F., Davis J. M., Grattapaglia D., Resende M. D., Kirst M. Accelerating the domestication of trees using genomic selection: accuracy of prediction models across ages and environments // New Phytol. 2012. V. 193. N. 3. P. 617–624.

Suontama M., Klápště J., Telfer E., Graham N., Stovold T., Low C., McKinley R., Dungey H. Efficiency of genomic prediction across two Eucalyptus nitens seed orchards with different selection histories // Heredity. 2019. V. 122. P. 370–379.

Tan B., Grattapaglia D., Martins G. S., Ferreira K. Z., Sundberg B., Ingvarsson P. K. Evaluating the accuracy of genomic prediction of growth and wood traits in two Eucalyptus species and their F1 hybrids // BMC Plant Biol. 2017. N. 17. P. 1–15.

Thistlethwaite F. R., El-Dien O. G., Ratcliffe B., Klápště J., Porth I., Chen C., Stoehr M. U., Ingvarsson P. K., El-Kassaby Y. A. Linkage disequilibrium vs. pedigree: Genomic selection prediction accuracy in conifer species // PLoS ONE. 2020. V. 15. N. 6. Р. 1–14. e0232201.

Ukrainetz N. K., Mansfield S. D. Assessing the sensitivities of genomic selection for growth and wood quality traits in lodgepole pine using Bayesian models // Tree Genet. Genomes. 2020. N. 16. Iss. 1. P. 14.

Westbrook J. W., Zhang Q., Mandal M. K., Jenkins E. V., Barth L. E., Jenkins J. W., Grimwood J., Schmutz, J., Holliday J. A. Optimizing genomic selection for blight resistance in American chestnut backcross populations: A trade‐off with American chestnut ancestry implies resistance is polygenic // Evolut. Appl. 2020. N. 13. Iss. 1. P. 31–47.

Zapata-Valenzuela J., Whetten R. W., Neale D., McKeand S., Isik F. Genomic estimated breeding values using genomic relationship matrices in a cloned population of loblolly pine // G3: Genes, Genomes, Genetics. 2013. V. 3. Iss. 5. P. 909–916. 

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