Grant: Alliance Grants
Lakehead University
$68,200.00
Development and validation of genomic-assisted breeding models for increased productivity and wood quality of black spruce in Ontario, Canada_x000d_ _x000d_ _x000d_ _x000d_
FY 2020-21
Summary
The objective of the proposed research is to develop and test genomic selection models to improve the growth and wood quality of black spruce in northwestern Ontario. Black spruce is one of the most abundant and widely planted tree species in the boreal forest of Canada and is of great economic value to Canada's forest products sector. Traditional tree improvement programs for black spruce in Ontario have produced modest gains in growth but take long periods of time to achieve. Here, we propose to test the application of a relatively new approach to improved breeding, termed genomic selection, to increase the growth per unit time that can be achieved for Ontario's black spruce breeding programs. We will collect data on tree growth and wood quality to estimate the pedigree-based genetic worth of individuals in an existing black spruce breeding program in Ontario and test the accuracy of those models when applied to more advanced generation test populations. This study will be the first proposed to evaluate the accuracy of genomic selection applied to an operational breeding program of black spruce in Ontario. The development of a genomic selection model will enable the rapid identification of individual trees with superior genotypes for wood quality and growth traits, providing a much shorter time to operational seed supply. Project partners will utilize the information gained from this study to identify genetically superior individuals that can form the basis of advanced generation breeding programs. Increases in forest productivity expected to result from this study will benefit Canadians by contributing to the economic growth of the forest industry and by helping to mitigate climate change through increased carbon sequestration.
Program
Alliance Grants
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
548769-2020
Name nom
Thomson, Ashley
Department département
Natural Resources Management, Faculty of
Organization id
25
Institution établissement
Lakehead University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2020
Award amount
68200
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
201
Area of application group en
Natural resources (economic aspects)
Area of application group fr
Ressources naturelles (aspects économiques)
Area of application en
Forestry (silviculture, forest management)
Area of application fr
Foresterie (sylviculture, aménagement forestier)
Research subject code
5004
Research subject group en
Genetics
Research subject group fr
Génétique
Research subject en
Genome analysis
Research subject fr
Analyse du génome
Installment
inst:1 - 1
Partie
1
Nb partie
1
Application title
Development and validation of genomic-assisted breeding models for increased productivity and wood quality of black spruce in Ontario, Canada_x000d_
_x000d_
_x000d_
_x000d_
Keyword
NSERC
Application summary
The objective of the proposed research is to develop and test genomic selection models to improve the growth and wood quality of black spruce in northwestern Ontario. Black spruce is one of the most abundant and widely planted tree species in the boreal forest of Canada and is of great economic value to Canada's forest products sector. Traditional tree improvement programs for black spruce in Ontario have produced modest gains in growth but take long periods of time to achieve. Here, we propose to test the application of a relatively new approach to improved breeding, termed genomic selection, to increase the growth per unit time that can be achieved for Ontario's black spruce breeding programs. We will collect data on tree growth and wood quality to estimate the pedigree-based genetic worth of individuals in an existing black spruce breeding program in Ontario and test the accuracy of those models when applied to more advanced generation test populations. This study will be the first proposed to evaluate the accuracy of genomic selection applied to an operational breeding program of black spruce in Ontario. The development of a genomic selection model will enable the rapid identification of individual trees with superior genotypes for wood quality and growth traits, providing a much shorter time to operational seed supply. Project partners will utilize the information gained from this study to identify genetically superior individuals that can form the basis of advanced generation breeding programs. Increases in forest productivity expected to result from this study will benefit Canadians by contributing to the economic growth of the forest industry and by helping to mitigate climate change through increased carbon sequestration.