Detecting mislabeling and identifying unique progeny in Acacia mapping population using SNP markers

Asif Javed Muhammad , Mohd Zaki Abdullah , Norwati Muhammad , Wickneswari Ratnam

Journal of Forestry Research ›› 2017, Vol. 28 ›› Issue (6) : 1119 -1127.

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Journal of Forestry Research ›› 2017, Vol. 28 ›› Issue (6) : 1119 -1127. DOI: 10.1007/s11676-017-0405-8
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Detecting mislabeling and identifying unique progeny in Acacia mapping population using SNP markers

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Abstract

Acacia hybrids offer a great potential for paper industry in Southeast Asia due to their fast growth and ability to grow on abandoned or marginal lands. Breeding Acacia hybrids with desirable traits can be achieved through marker assisted selection (MAS) breeding. To develop a MAS program requires development of linkage maps and QTL analysis. Two mapping populations were developed through interspecific hybridization for linkage mapping and QTL analysis. All seeds per pod were cultured initially to improve hybrid yield as quality and density of linkage mapping is affected by the size of the mapping population. Progenies from two mapping populations were field planted for phenotypic and genotypic evaluation at three locations in Malaysia, (1) Forest Research Institute Malaysia field station at Segamat, Johor, (2) Borneo Tree Seeds and Seedlings Supplies Sdn, Bhd. (BTS) field trial site at Bintulu, Sarawak, and (3) Asiaprima RCF field trial site at Lancang, Pahang. During field planting, mislabeling was reported at Segamat, Johor, and a similar problem was suspected for Bintulu, Sarawak. Early screening with two isozymes effectively selected hybrid progenies, and these hybrids were subsequently further confirmed by using species-specific SNPs. During field planting, clonal mislabeling was reported and later confirmed by using a small set of STMS markers. A large set of SNPs were also used to screen all ramets in both populations. A total of 65.36% mislabeled ramets were encountered in the wood density population and 60.34% in the fibre length mapping population. No interpopulation pollen contamination was detected because all ramets found their match within the same population in question. However, mislabeling was detected among ramets of the same population. Mislabeled individuals were identified and grouped as they originated from 93 pods for wood density and 53 pods for fibre length mapping populations. On average 2 meiotically unique seeds per pod (179 seeds/93 pods) for wood density and 3 meiotically unique seeds per pod (174 seeds/53 pods) for fibre length mapping population were found. A single step statistical method was used to evaluate the most informative set of SNPs that could subsequently be used for routine checks for mislabeling in multi-location field trials and for labelling superior clones to protect breeder’s rights. A preliminary set of SNPs with a high degree of informativeness was selected for the mislabeling analysis in conjunction with an assignment test. Two subsets were successfully identified, i.e., 51 SNPs for wood density and 64 SNPs for fibre length mapping populations to identify all mislabeled ramets which had been previously identified. Mislabeling seems to be a common problem due to the complexity involved in the production of mapping populations. Therefore, checking for mislabeling is imperative for breeding activities and for analyses such as linkage mapping in which a correlation between genotypic and phenotypic data is determined.

Keywords

Tree breeding / SNP markers / Mislabeling / Linkage mapping / Quantitative trait loci (QTL) mapping

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Asif Javed Muhammad, Mohd Zaki Abdullah, Norwati Muhammad, Wickneswari Ratnam. Detecting mislabeling and identifying unique progeny in Acacia mapping population using SNP markers. Journal of Forestry Research, 2017, 28(6): 1119-1127 DOI:10.1007/s11676-017-0405-8

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