Single nucleotide polymorphisms (SNPs) discovery and linkage disequilibrium (LD) in forest trees |
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| Authors: | Zhang?De-qiang Email author" target="_blank">Zhang?Zhi-yi?Email author |
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| Institution: | 1. Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, Beijing Forestry University, Beijing 100083, P. R. China;Laboratory of Biotechnology, Institute of Forestry, Chinese Academy of Forestry, Beijing 100091,P.R.China
2. Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, Beijing Forestry University, Beijing 100083, P. R. China |
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| Abstract: | With completion of the Populus genome sequencing project and the availability of many expressed sequence tags (ESTs) databases in forest trees, attention is now rapidly shifting towards the study of individual genetic variation in natural popula-tions. The most abundant form of genetic variation in many eukaryotic species is represented by single nucleotide polymorphisms (SNPs), which can account for heritable inter-individual differences in complex phenotypes. Unlike humans, the linkage disequilib-rium (LD) rapidly decays within candidate genes in forest trees. Thus, SNPs-based candidate gene association studies are considered to be a most effective approach to dissect the complex quantitative traits in forest trees. The present study demonstrates that LD map-ping can be used to identify alleles associated with quantitative traits and suggests that this new approach could be particularly useful for performing breeding programs in forest trees. In this review, we will describe the fundamentals, patterns of SNPs distribution and frequency, summarize recent advances in SNPs discovery and LD and comment on the application of LD in the dissection of com-plex quantitative traits in forest tress. We also put forward the outlook for future SNPs-based association analysis of quantitative traits in forest trees. |
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| Keywords: | single nucleotide polymorphisms (SNPs) linkage disequilibrium (LD) quantitative traits association studies for-est tree |
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