Abstract
Co-dominant markers’ data are often analysed as if they were dominant markers, an over-simplification that may be misleading. Addressing this, the present paper aims to provide a practical guide to the analysis of co-dominant data and selection of suitable software. An overview is provided of the computational methods and basic principles necessary for statistical analyses of co-dominant molecular markers to determine genetic diversity and molecular characterization of germplasm collections. The Hardy–Weinberg principle is at the base of statistical methods to determine genetic distance, genetic diversity, and its distribution among and within populations. Six statistical software packages named GenAlEx, GDA, Power Marker, Cervus, Arlequin, and Structure are compared and contrasted. The different software packages were selected based on: (i) The ability to analyze co-dominant data, (ii) open access software, (iii) ease of downloading, and (iv) ease of running using a Microsoft Window interface. The software packages are compared analyzing the same dataset. Differences among parameters are discussed together with the comments on some of the software outputs.
Highlights
IntroductionGenetic diversity of germplasm is assessed by collecting key information, especially: (i) Allele number per locus; (ii) genotype number per locus; (iii) gene diversity; (iv) polymorphic information content (PIC) (polymorphism information content) values; (v) observed and expected heterozygosity; (vi) partition of the diversity into its components within and between populations; and (vii) the genetic distance among the analyzed populations
Genetic diversity of germplasm is assessed by collecting key information, especially: (i) Allele number per locus; (ii) genotype number per locus; (iii) gene diversity; (iv) polymorphic information content (PIC) values; (v) observed and expected heterozygosity; (vi) partition of the diversity into its components within and between populations; and (vii) the genetic distance among the analyzed populations
The analyses are usually performed using a variety of molecular markers grouped into two categories: Co-dominant markers, such as SSR and SNP, which are able to identify the allelic situation at each locus, and dominant markers, such as ISSR, RAPD, and AFLP
Summary
Genetic diversity of germplasm is assessed by collecting key information, especially: (i) Allele number per locus; (ii) genotype number per locus; (iii) gene diversity; (iv) PIC (polymorphism information content) values; (v) observed and expected heterozygosity; (vi) partition of the diversity into its components within and between populations; and (vii) the genetic distance among the analyzed populations. The analyses are usually performed using a variety of molecular markers grouped into two categories: Co-dominant markers, such as SSR (single sequence repeat) and SNP (single nucleotide polymorphism), which are able to identify the allelic situation at each locus, and dominant markers, such as ISSR (inter simple sequence repeats), RAPD (random amplified polymorphic DNA), and AFLP (amplified fragment length polymorphism), which usually have a multi-band pattern and are unable to recognize allelic variants [1] The latter produce a series of bands with unknown relationships (i.e., could be allelic variants of the same genes or mark different genome regions). J 2018, 1 genetics, run under Windows, to highlight the advantages and disadvantages of the various software packages, facilitating appropriate selection and use
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