Optimising true-to-typeness testing in rootstock trials for cost-effective results

Ensuring true-to-typeness is vital in rootstock trials as it guarantees that the propagated trees are genetically identical to the original rootstock cultivar being evaluated. Molecular genetic verification at the DNA level, using simple sequence repeat (SSR) markers, is a recognized method to confirm true-to-typeness and has been successfully applied in the South African apple industry. However, given the large number of samples involved in rootstock trials, and the consequent labour-intensivity, SSR fingerprinting analyses can become prohibitively expensive. To address this challenge, the project aimed to develop a more efficient and cost-effective SNP marker panel for apples in collaboration with South African DNA laboratory, CenGen. The goal was to create a tool optimised for high-throughput analysis, enabling faster, cheaper and more accurate processing of large sample volumes. Additionally, to further reduce costs, a bulking approach was explored by combining leaf samples from up to 10 trees into a single sample for DNA analysis using the developed SNP marker panel. This approach was intended to evaluate the accuracy of true-to-typeness in bulked samples using SNPs.

Leaf samples from nucleus material of the most common apple rootstocks in production, along with eight additional novel samples, were utilised. High-quality DNA was extracted (Step 1A), followed by analysis with a 14-marker SSR panel and a 16-marker SNP panel to generate two sets of fingerprint data for each sample (Steps 1B and 2). This control reference DNA is stored in a biobank for future use. In Step 3 and step 4, samples were combined in different ratios to create bulks that mimic samples from different trees combined in the field, i.e. bulked samples that contain one or more off-type samples. The bulks were screened with the abovementioned SSR and SNP panels and the results were compared to the data of the individual samples prior to bulking.

The generated SSR and SNP fingerprints revealed that each control sample had a unique genetic profile and could be distinctly distinguished from one another. These valuable resources provide the South African apple industry with a choice of marker platforms, depending on their sample size.

Bulking samples proved to be a risky approach, as marker resolution is diminished, and off-types present in the minority within bulks are less likely to be detected. If a bulking approach is employed using SSR markers, it is crucial that the 14-marker set is not reduced. SNP markers are the more cost-effective option for analysing large numbers of samples, whereas SSRs are better suited for smaller projects. Seven control samples, which need to be included in all future SNP analysis experiments, were identified to ensure optimal scoring accuracy.

Additionally, an effort was made to test an alternative, cheaper and faster DNA extraction method (SDS) which could also be used for SNP analysis. The results were successful, however, the CTAB DNA extraction method should remain the method of choice when long-term storage of DNA is expected.

The use of an SNP panel significantly reduces the cost of genotyping, making it more

economical to screen many individual samples compared to the current approach of using an SSR panel on bulked samples. However, SNP marker screening is unable to reliably detect off-types in bulked samples, which means that further cost reductions are not achievable with the existing technology.

In rootstock trials, ensuring true-to-typeness is crucial for verifying that propagated trees are genetically identical to the original rootstock cultivar under evaluation. SNP marker screening has proven to be a cost-effective method for genotyping, especially advantageous for handling large sample sizes compared to SSR panels. However, further cost reductions using SNP marker screening for bulk samples are not advisable, as it was not able to reliably detect off-types in bulked samples. Despite this limitation, SNP marker screening remains a practical solution for high-throughput true-to-typeness testing, while its efficacy in detecting minor genetic variations is acknowledged.