Dr Tanja Pyhäjärvi , University of Oulu, Finland
All breeding is based on genetic differences among individuals. In traditional breeding, the similarity of genetic background and the relatedness among individuals is predicted from pedigrees. Pedigrees have been an important part of breeding for a long time. All of us have that friend who has a pure bred dog with a fancy pedigree on some database or on paper. Mom, dad, mom’s mom, mom’s dad etc., you know it.
In modern breeding, the exact pedigree information is not always needed. Why? Because we can use information from DNA level variation to figure out relatedness among individuals. On top of that, it is also possible to follow which of the thousands of variable sites in a genome are linked to a certain desired or unwanted characteristics. DNA level information also tells us directly about the amount of genetic diversity and extent of inbreeding within a given individual.
Many breeding methods that use DNA level information have one problem. They need a lot of it! Often information is needed from tens of thousands of DNA locations and from thousands of individuals. So, what do you do when you want to peek into DNA level differences among thousands of trees? One of the goals of B4EST project is to develop new high throughput methods for easier and cheaper genotyping to tackle this issue.
Luckily there are multiple technological options to achieve this goal. In B4EST, we have chosen a method called genotyping arrays. These postcard size arrays have 384 wells, and each well contains 50 000 different type of small DNA pieces that are designed to capture a different variable site in a tree’s genome. Short, sticky custom designed pieces of DNA are attached to a glass surface and form microscopic clusters. Then the sample genome’s DNA is fragmented in small pieces and allowed to find a matching sticky piece on the surface. And that’s not all: samples are also labeled with fluorescent dyes. With a special light conditions and a very good camera, an image of the array can be obtained.
Just add some image processing and algorithms and voilá!, different genotypes (heterozygotes and homozygotes) can be identified. And that is how you can genotype hundreds of trees and tens of thousands genetic markers in one go.
Of course making all this to work smoothly requires a lot of existing genetic and technical knowledge. The arragys that we intend to design in B4EST project will be publicly available for anyone who needs efficient genotyping of Norway spruce, Scots pine, poplars, maritime pine, ash and stone pine.