Literature DB >> 35298481

Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program.

Eduardo P Cappa1,2, Jennifer G Klutsch3, Jaime Sebastian-Azcona3, Blaise Ratcliffe4, Xiaojing Wei3, Letitia Da Ros5, Yang Liu4, Charles Chen6, Andy Benowicz7, Shane Sadoway8, Shawn D Mansfield5, Nadir Erbilgin3, Barb R Thomas3, Yousry A El-Kassaby4.   

Abstract

Tree improvement programs often focus on improving productivity-related traits; however, under present climate change scenarios, climate change-related (adaptive) traits should also be incorporated into such programs. Therefore, quantifying the genetic variation and correlations among productivity and adaptability traits, and the importance of genotype by environment interactions, including defense compounds involved in biotic and abiotic resistance, is essential for selecting parents for the production of resilient and sustainable forests. Here, we estimated quantitative genetic parameters for 15 growth, wood quality, drought resilience, and monoterpene traits for Picea glauca (Moench) Voss (white spruce). We sampled 1,540 trees from three open-pollinated progeny trials, genotyped with 467,224 SNP markers using genotyping-by-sequencing (GBS). We used the pedigree and SNP information to calculate, respectively, the average numerator and genomic relationship matrices, and univariate and multivariate individual-tree models to obtain estimates of (co)variance components. With few site-specific exceptions, all traits examined were under genetic control. Overall, higher heritability estimates were derived from the genomic- than their counterpart pedigree-based relationship matrix. Selection for height, generally, improved diameter and water use efficiency, but decreased wood density, microfibril angle, and drought resistance. Genome-based correlations between traits reaffirmed the pedigree-based correlations for most trait pairs. High and positive genetic correlations between sites were observed (average 0.68), except for those pairs involving the highest elevation, warmer, and moister site, specifically for growth and microfibril angle. These results illustrate the advantage of using genomic information jointly with productivity and adaptability traits, and defense compounds to enhance tree breeding selection for changing climate.

Entities:  

Mesh:

Year:  2022        PMID: 35298481      PMCID: PMC8929621          DOI: 10.1371/journal.pone.0264549

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  45 in total

1.  Comparing estimates of genetic variance across different relationship models.

Authors:  Andres Legarra
Journal:  Theor Popul Biol       Date:  2015-09-02       Impact factor: 1.570

2.  Genetic variation of lodgepole pine, Pinus contorta var. latifolia, chemical and physical defenses that affect mountain pine beetle, Dendroctonus ponderosae, attack and tree mortality.

Authors:  Daniel S Ott; Alvin D Yanchuk; Dezene P W Huber; Kimberly F Wallin
Journal:  J Chem Ecol       Date:  2011-08-16       Impact factor: 2.626

3.  Genetic control and evolutionary potential of a constitutive resistance mechanism against the spruce budworm (Choristoneura fumiferana) in white spruce (Picea glauca).

Authors:  Claudia Méndez-Espinoza; Geneviève J Parent; Patrick Lenz; André Rainville; Laurence Tremblay; Greg Adams; Andrew McCartney; Éric Bauce; John MacKay
Journal:  Heredity (Edinb)       Date:  2018-02-17       Impact factor: 3.821

4.  Combining genomic and genealogical information in a reproducing kernel Hilbert spaces regression model for genome-enabled predictions in dairy cattle.

Authors:  Silvia Teresa Rodríguez-Ramilo; Luis Alberto García-Cortés; Oscar González-Recio
Journal:  PLoS One       Date:  2014-03-26       Impact factor: 3.240

5.  Factors affecting the accuracy of genomic selection for growth and wood quality traits in an advanced-breeding population of black spruce (Picea mariana).

Authors:  Patrick R N Lenz; Jean Beaulieu; Shawn D Mansfield; Sébastien Clément; Mireille Desponts; Jean Bousquet
Journal:  BMC Genomics       Date:  2017-04-28       Impact factor: 3.969

6.  Insect herbivory (Choristoneura fumiferana, Tortricidea) underlies tree population structure (Picea glauca, Pinaceae).

Authors:  Geneviève J Parent; Isabelle Giguère; Gaby Germanos; Mebarek Lamara; Éric Bauce; John J MacKay
Journal:  Sci Rep       Date:  2017-02-16       Impact factor: 4.379

7.  Gene expression predictions and networks in natural populations supports the omnigenic theory.

Authors:  Aurélien Chateigner; Marie-Claude Lesage-Descauses; Odile Rogier; Véronique Jorge; Jean-Charles Leplé; Véronique Brunaud; Christine Paysant-Le Roux; Ludivine Soubigou-Taconnat; Marie-Laure Martin-Magniette; Leopoldo Sanchez; Vincent Segura
Journal:  BMC Genomics       Date:  2020-06-22       Impact factor: 3.969

8.  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.

Authors:  Zhi-Qiang Chen; John Baison; Jin Pan; Bo Karlsson; Bengt Andersson; Johan Westin; María Rosario García-Gil; Harry X Wu
Journal:  BMC Genomics       Date:  2018-12-18       Impact factor: 3.969

9.  Estimation of heritability from limited family data using genome-wide identity-by-descent sharing.

Authors:  Jørgen Ødegård; Theo H E Meuwissen
Journal:  Genet Sel Evol       Date:  2012-05-08       Impact factor: 4.297

10.  Hydroxyacetophenone defenses in white spruce against spruce budworm.

Authors:  Geneviève J Parent; Claudia Méndez-Espinoza; Isabelle Giguère; Melissa H Mageroy; Martin Charest; Éric Bauce; Joerg Bohlmann; John J MacKay
Journal:  Evol Appl       Date:  2019-12-20       Impact factor: 5.183

View more
  1 in total

1.  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.

Authors:  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
Journal:  BMC Genomics       Date:  2022-07-23       Impact factor: 4.547

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.