Forest Tree Breeding and Challenges Harry Wu SLU Plant Breeding Platform November 11 2014, Uppsala, Sweden
World Forest and Plantation Total area 4 billion ha Net loss per year=7.3 m ha Sweden=23 m ha 0.58%
World Forest and Plantation Productive forest plantation = 120 m ha
World Forest and Plantation Productive Plantation ~ 40 m ha ~ 13 m ha ~ 14 m ha 12%
Presentation Outline 1. Tree breeding process 2. Tree breeding population and breeding strategies 3. Example of two advanced tree breeding programs Radiata and loblolly pine 4. Genetic gain from tree breeding 5. Major breeding and deployment issues 6. Perspectives and opportunities of tree breeding
Tree Breeding Process Breeding population Improved varieties Selection Cross pollinisation Progeny tests
Tree Breeding - Large Base Population Radiata pine 1213 plus tree selection (STBA, Australia) Loblolly pine 3800 selections (NCSU-ICTIP, USA) Scots pine 6000 plus tree selection (Skogforsk, Sweden) Blue gum 1516 plus selection (STBA, Australia)
Tree Breeding - Large Breeding Population Radiata pine 300 (STBA, Australia) Loblolly pine 160 elite (NCSU-ICTIP, USA) Scots pine 1000 (Skogforsk, Sweden) Blue gum 300 (STBA, Australia)
Varied Breeding Strategy Cotterill 1988 Namkoong 1976, Burdon and Namkoong 1983 Van Buijtenen and Lowe 1976 Burdon 1976 Burdon and Namkoong 1983
Varied Breeding Strategy Generation 3 2 1 Population 1 Population 1 Population 1 P P D. Single population with rolling-front (operation) breeding strategy Feature No discreet generation Crosses and new trials are made each year Advantage Greater gain per year due to high selection intensity Disadvantage Need sophisticated software for BV prediction and for inbreeding control P Borralho and Dutkowsks 1998
Varied Breeding Strategy generation E. Inbreed-hybrid breeding strategy 1 self S0 self S0 Feature: 1. Selfing for several generations to purge deleterious genes 2. Best lines for cross to create heterosis 2 self S1 self S1 Advantage: 1. Fast purge of inbreeding depression 2. Create large heterosis 3 S2 S2 Disadvantage: 1. Long-term inbreeding 2. Fixation of deleterious alleles Hybrid Wu et al 2004
Hybrid Breeding Strategies Pure species A Pure species B Selection Selection F1 Selection Selection F1
Ten year old hybrid between E. grandis and E. urophylla
Example of radiata pine breeding in Australia Early commercial plantations 1925-1975 First generation Plus trees (1950-1980) Open-pollinated clonal seed orchard Half-sib progeny testing 1960-1989 Full-sib progeny testing 1960-1989 Second generation breeding population (1992) Control-pollinated clonal seed orchard Full-sib progeny testing from 1996 Fourth g. breeding population 2011/12 Third g. breeding population from 2002 Full-sib progeny testing from 2003/04 Multiple deployment populations Wu et al 2007
Open-pollinated seed orchard
Control-pollinated seed orchard - hedged
Example of loblolly pine tree breeding program in USA Fourth generation scions selected and topgrafted in 2012
Achieved Genetic Gain Radiata pine (New Zealand/Australia/Chile) Fourth generations (genetic gain 30+11=41%) G0 Loblolly pine (USA) Fourth generations (genetic gain 30-40%) Hybrid E. grandis and urophylla (Brazil) Hybrids improvement (one generation 75-100% gain) G1 G2
Major Breeding and Deployment Issues A. Controlling inbreeding (co-ancestry) B. Managing negative genetic correlation C. Capturing genetic gain in deployment A. Clonal forestry B. G by E interaction D. Shortening breeding cycle
A. Controlling Inbreeding Example of radiata pine: Best 300 selections in the 4th generation = effective population size (N e ) ~ 20
B. Managing Negative Genetic Correlation in Multiple Traits 150 Diameter and Wood density Norway spruce 5618 trees 100 Genetic correlation: -0.60 50 32,95 0-80 -60-40 -20 0 20 40 60 80-50 -100-150 Chen et al. 2014
C. Capturing Genetic Gain in Deployment Family deployment VS clonal deployment Family deployment Clonal deployment
D. Shortening Breeding Cycle Tree breeding process = 12 years = 22 years Selection Grafting and mating 5-10 Testing 7-12
Perspective of Tree Breeding in -omics Age 1. Using genomic information for simulation Optimal breeding strategies for controlling inbreeding (inbreeding or outcross breeding strategy) Dealing with negative genetic correlation (single and multiple breeding population) Hallingbäck et al. 2014
Perspective of Tree Breeding in -omics Age Seed Containing Embryo Establishme nt of New Clones 2. Capturing genetic gain using Somatic Embryogenesis 6 Embryo Culture 1 Mass Production of Somatic Embryos 2 Automated Sowing of Somatic Embryos Long Term 3 Frozen Storage Nursery Production Somatic Seedling 4
Perspective of Tree Breeding in -omics Age 3. Genome-wide association and genomic selection Use as a first-stage nursery (early) selection to increase selection intensity Use very early selection to shorten generation interval Testing 7-12 yrs 1-2 yrs
Perspective of Tree Breeding in -omics Age 4. Early flowering Use genomics, proteomics or metabolomics to accelerate the flowering for spruce and eucalypts Grafting and mating 5-10 yrs 2-4 yrs
Thank you Contribution of tree breeding to productivity
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Developing Optimal Plant Breeding Strategy Using Genomics Harry X. Wu, S Henrik Hallingbäck, NS Complete additivity Partial dominance
Developing Optimal Plant Breeding Strategy Using Genomics Within 2 years Meta-data analyses to understand the genetic and genomic structure of quantitative traits Using genomic framework to simulate different breeding strategies of selfing and cross-breeding and population improvement Long-term GWAS to understand genetic control of agronomic traits at genome-wide level Dynamic simulation using whole genome genetic structure Using model species to conduct experiments to verify the optimal breeding strategy