Mo-Hua Yang1,2, Yong-Bi Fu1. 1. Plant Gene Resources of Canada, Saskatoon Research and Development Centre, Agriculture and Agri-Food Canada, 107 Science Place, Saskatoon S7N 0X2, Canada. 2. College of Forestry, Central South University of Forestry and Technology, 498 South Shaoshan Avenue, Changsha, Hunan 410004, People's Republic of China.
Abstract
PREMISE OF THE STUDY: Assessing genetic distinctness or redundancy is an important part of plant germplasm characterization. We previously introduced a new marker-based approach using the average dissimilarity of an accession to assess genetic distinctness or redundancy. However, this approach has not been widely applied, largely due to the lack of software to integrate separate analyses involving dissimilarity calculation, analysis of molecular variance, and principal coordinates analysis. METHODS AND RESULTS: An R function, AveDissR, was developed to integrate three separate analyses into one package for assessing genetic distinctness or redundancy. It can analyze large data sets of dominant or codominant markers such as amplified fragment length polymorphisms (AFLPs), simple sequence repeats (SSRs), or single-nucleotide polymorphisms (SNPs), generate a useful set of output files for germplasm assessment, and run in an R environment on any computer platform. CONCLUSIONS: AveDissR can make the assessment of genetic distinctness or redundancy in plant germplasm more feasible and useful.
PREMISE OF THE STUDY: Assessing genetic distinctness or redundancy is an important part of plant germplasm characterization. We previously introduced a new marker-based approach using the average dissimilarity of an accession to assess genetic distinctness or redundancy. However, this approach has not been widely applied, largely due to the lack of software to integrate separate analyses involving dissimilarity calculation, analysis of molecular variance, and principal coordinates analysis. METHODS AND RESULTS: An R function, AveDissR, was developed to integrate three separate analyses into one package for assessing genetic distinctness or redundancy. It can analyze large data sets of dominant or codominant markers such as amplified fragment length polymorphisms (AFLPs), simple sequence repeats (SSRs), or single-nucleotide polymorphisms (SNPs), generate a useful set of output files for germplasm assessment, and run in an R environment on any computer platform. CONCLUSIONS: AveDissR can make the assessment of genetic distinctness or redundancy in plant germplasm more feasible and useful.
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