Utilization of STMS markers to verify admixture in clonal progenies of Acacia mapping populations and relabelling using assignment tests

Abstract

Clonal propagation is widely used for Acacia breeding and commercial planting. When a large number of clones are handled, problems with mixings are commonly confronted. Detection of admixture in Acacia clones based on morphology particularly at seedling stage is not feasible. However, molecular markers are commonly used to test the genetic fidelity of planting materials. This paper reports the detection of mislabelling in Acacia clonal progenies using a sequence tagged microsatellite (STMS) genetic marker system. Progenies from two mapping populations were clonally propagated and field planted for phenotypic and genotypic evaluation at three locations in Malaysia: (a) Forest Research Institute Malaysia field station at Segamat, Johor, (b) Borneo Tree Seeds and Seedlings Supplies Sdn, Bhd. (BTS) field trial site at Bintulu, Sarawak and (c) Asiaprima RCF field trial site at Lancang, Pahang. During field planting mislabelling was reported at Segamat, Johor and similar was suspected for Bintulu, Sarawak. Screening revealed mislabelling events in both populations. A total of 18.52% mislabelling incidences were detected from both sites, of which 17.39% of mislabelling was detected for fibre length cross and 20% for wood density cross. The assignment test efficiently reestablished the mislabelled ramets to the respective clones. Future studies should be focused on the utilization of a higher number of markers, e.g. SSR or SNPs to increase a discrimination power. A high number of SNPs can be generated within a short period of time compared to SSR, but SNPs could be cost inhibitory. Multiplexing microsatellite combinations along with sample bulking will further reduce the processing time when screening large populations. The use of assignment test would efficiently assign mislabelled individuals to the respective clones. It is concluded that checking for mislabelling is imperative for future breeding and for analyses such as QTL mapping where a correlation between genotypic and phenotypic data is determined.

Keywords

• tree breeding
• dna markers
• quantitative trait loci (qtl)
• linkage mapping