First core microsatellite panel identification in Apennine brown bears (Ursus arctos marsicanus): a collaborative approach

Erminia Scarpulla,Ettore Randi,Mario Cozzo,Nadia Mucci,Paolo Ciucci,Patrizia Giangregorio,Francesca Davoli,Alessio Boattini

doi:10.1186/s12864-021-07915-5

Abstract

BackgroundThe low cost and rapidity of microsatellite analysis have led to the development of several markers for many species. Because in non-invasive genetics it is recommended to genotype individuals using few loci, generally a subset of markers is selected. The choice of different marker panels by different research groups studying the same population can cause problems and bias in data analysis. A priority issue in conservation genetics is the comparability of data produced by different labs with different methods. Here, we compared data from previous and ongoing studies to identify a panel of microsatellite loci efficient for the long-term monitoring of Apennine brown bears (Ursus arctos marsicanus), aiming at reducing genotyping uncertainty and allowing reliable individual identifications overtimes.ResultsWe examined all microsatellite markers used up to now and identified 19 candidate loci. We evaluated the efficacy of 13 of the most commonly used loci analyzing 194 DNA samples belonging to 113 distinct bears selected from the Italian national biobank. We compared data from 4 different marker subsets on the basis of genotyping errors, allelic patterns, observed and expected heterozygosity, discriminatory powers, number of mismatching pairs, and probability of identity. The optimal marker set was selected evaluating the low molecular weight, the high discriminatory power, and the low occurrence of genotyping errors of each primer. We calibrated allele calls and verified matches among genotypes obtained in previous studies using the complete set of 13 STRs (Short Tandem Repeats), analyzing six invasive DNA samples from distinct individuals. Differences in allele-sizing between labs were consistent, showing a substantial overlap of the individual genotyping.ConclusionsThe proposed marker set comprises 11 Ursus specific markers with the addition of cxx20, the canid-locus less prone to genotyping errors, in order to prevent underestimation (maximizing the discriminatory power) and overestimation (minimizing the genotyping errors) of the number of Apennine brown bears. The selected markers allow saving time and costs with the amplification in multiplex of all loci thanks to the same annealing temperature. Our work optimizes the available resources by identifying a shared panel and a uniform methodology capable of improving comparisons between past and future studies.

Highlights

The low cost and rapidity of microsatellite analysis have led to the development of several markers for many species
Review of microsatellite and panel selection We reviewed 7 peer-reviewed papers that used microsatellite loci to study aspects of Apennine brown bear (ABB) genetics published between 2004 and 2017 (Table 1)
What emerges from the literature review is that the individual brown bears genotyping was performed by three different labs: until 2002 by the Experimental Zooprophylactic Institute of Abruzzo and Molise “G. Caporale” (IZSAM - Lab1, Method 1 described in Lorenzini et al [49]); in 2011 and 2014 by the Wildlife Genetics International lab (WGI - Lab2, Method 2 described in Ciucci et al [52]); and since 2002 until now, except for the core area in 2011 and 2014, by the Unit for Conservation Genetics of the Italian Institute for Environmental Protection and Research (ISPRA BIO-CGE - Lab3, Method 3 described in Gervasi et al [14, 41, 50] and Forconi et al [54])

Summary

Introduction

The low cost and rapidity of microsatellite analysis have led to the development of several markers for many species. It is known that the choice of markers affects the estimates of genetic diversity, so it is possible that by using fewer and not shared loci, research groups may produce different results, limiting the reproducibility of individual studies and reaching erroneous conclusions in comparative studies [32]. They are rarely considered, efforts to identify shared markers sets among different research groups studying the same species are of particular importance in limiting these kinds of errors [33, 34]. The accuracy of DNAbased identifications, obtained by limited numbers of STR, can be improved by using quality-control protocols (QC) to detect and eliminate genotyping errors [3, 36, 37]

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