Standardizing methods to address clonality in population studies

Abstract

Although clonal species are dominant in many habitats, from unicellular organisms to plants and animals, ecological and particularly evolutionary studies on clonal species have been strongly limited by the difficulty in assessing the number, size and longevity of genetic individuals within a population. The development of molecular markers has allowed progress in this area, and although allozymes remain of limited use due to their typically low level of polymorphism, more polymorphic markers have been discovered during the last decades, supplying powerful tools to overcome the problem of clonality assessment. However, population genetics studies on clonal organisms lack a standardized framework to assess clonality, and to adapt conventional data analyses to account for the potential bias due to the possible replication of the same individuals in the sampling. Moreover, existing studies used a variety of indices to describe clonal diversity and structure such that comparison among studies is difficult at best. We emphasize the need for standardizing studies on clonal organisms, and particularly on clonal plants, in order to clarify the way clonality is taken into account in sampling designs and data analysis, and to allow further comparison of results reported in distinct studies. In order to provide a first step towards a standardized framework to address clonality in population studies, we review, on the basis of a thorough revision of the literature on population structure of clonal plants and of a complementary revision on other clonal organisms, the indices and statistics used so far to estimate genotypic or clonal diversity and to describe clonal structure in plants. We examine their advantages and weaknesses as well as various conceptual issues associated with statistical analyses of population genetics data on clonal organisms. We do so by testing them on results from simulations, as well as on two empirical data sets of microsatellites of the seagrasses Posidonia oceanica and Cymodocea nodosa. Finally, we also propose a selection of new indices and methods to estimate clonal diversity and describe clonal structure in a way that should facilitate comparison between future studies on clonal plants, most of which may be of interest for clonal organisms in general.

High male incidence and evolutionary implications of triploid form in northeast Asia Carassius auratus complex

“…S1). Previous studies had shown that triploid individuals with identical transferrin phenotype patterns might be regarded as one gynogenetic clone (Yang et al, 2001), and the clone identity has been confirmed by SCAR markers (Zhou et al, 2001), microsatellites (Guo and Gui, 2008), mtDNA sequences (Li and Gui, 2008), and AFLP profiles (Wang et al, 2011), which is consistent with the standardizing methods suggested by Arnaud-Haond et al (2007). Thereby, about 64 various clones could be distinguished from the triploid form, and their geographical distribution in the 4 sampled sites was detailed in Electronic supplementary material, Table S3.…”

Scaling of processes shaping the clonal dynamics and genetic mosaic of seagrasses through temporal genetic monitoring

“…The first step of the genetic analyses was the clonal discrimination, based on the probability that identical multilocus genotype (MLG) arise from distinct events of sexual reproduction, as described in Arnaud-Haond et al (2007a). When P sex(FIS) (estimated taking departure from Hardy-Weinberg into account) falls below a threshold value fixed at 0.01, the two identical MLGs are considered as belonging to the same clonal lineage.…”

Best Practices for Population Genetic Analyses

“…However, SSR markers are subject to significantly higher levels of homoplasy as compared with SNP markers. A genotype accumulation curve, available in the R packages poppr and RClone, is a useful tool for determining if more markers are needed (Arnaud-Haond et al 2007;Bailleul et al 2016;Kamvar et al 2014Kamvar et al , 2015a (Fig. 3).…”

“…All the population-level distances are based on population-level allele frequencies, which are readily obtained for haploids and diploids in several programs. For clonal populations, because population frequencies can be skewed due to the presence of repeated genotypes, it is recommended to calculate allele frequencies from clone-corrected data or by using a round-robin approach as implemented in both RClone and poppr (Arnaud-Haond et al 2007;Bailleul et al 2016;Kamvar et al 2014Kamvar et al , 2015a. For autopolyploid data, one can calculate frequencies in the polysat R package.…”

“…These types of comparisons are recommended for all microbial populations that may have both a sexual and asexual mode of reproduction. Several groups have developed tools for working with clonal organisms (Ali et al 2016;Arnaud-Haond et al 2007;Bailleul et al 2016;Kamvar et al 2014Kamvar et al , 2015a.…”