Efficient genomics based ‘end-to-end’ selective tree breeding framework

Since their initiation in the 1950s, worldwide selective tree breeding
programs followed the recurrent selection scheme of repeated cycles of
selection, breeding (mating), and testing phases and essentially remained
unchanged to accelerate this process or address environmental contingences
and concerns. Here, we introduce an “end-to-end” selective tree breeding
framework that: 1) leverages strategically preselected GWAS-based sequence
data capturing trait architecture information, 2) generates unprecedented
resolution of genealogical relationships among tested individuals, and 3)
leads to the elimination of the breeding phase through the utilization of
readily available wind-pollinated (OP) families. Individuals’ breeding
values generated from multi-trait multi-site analysis were also used in an
optimum contribution selection protocol to effectively manage genetic
gain/co-ancestry trade-offs and traits’ correlated response to selection.
The proof-of-concept study involved a 40-year-old spruce OP testing
population growing on three sites in British Columbia, Canada, clearly
demonstrating our method's superiority in capturing most of the
available genetic gains in a substantially reduced timeline relative to
the traditional approach. The proposed framework is expected to increase
the efficiency of existing selective breeding programs, accelerate the
start of new programs for ecologically and environmentally important tree
species, and address climate-change caused biotic and abiotic stress
concerns more effectively.