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Mimosa catherinensis SNP data sets

Citation

Nazareno, Alison; Martins, Thais (2021), Mimosa catherinensis SNP data sets, Dryad, Dataset, https://doi.org/10.5061/dryad.j9kd51ccz

Abstract

To inform management strategies for conservation of Mimosa catharinensis – a narrow endemic, critically endangered plant species – we identified 1,497 unlinked SNP markers derived from a reduced representation sequencing method (i.e., ddRADseq). This set of molecular markers was employed to assess intrapopulation genetic parameters and the demographic history of one extremely small population of M. catharinensis located in the Brazilian Atlantic Forest. We observed a moderate level of genetic diversity for M. catharinensis. Interestingly, M. catharinensis, which is a lianescent shrub with no indication of seed production for at least two decades, presented high levels of outcrossing and no evidence of inbreeding. However, the reconstruction of demographic history of M. catharinensis indicate that the population should be suffered a recent bottleneck.

Methods

DNA was extracted from leaf samples of all collected individuals employing the NucleoSpin® kit (Machereney-Nagel GmbH & Co. KG) following manufacturer’s guidelines. After extraction, the quality of each sample was verified using Thermo Scientific NanoDrop 2000 Spectrophotometer (Thermo Fisher Scientific Inc.) and the concentration of double-strand DNA (dsDNA) was obtained by using Qubit dsDNA Assay Kit (Invitrogen). The genomic library was prepared using a double-digest restriction site-associated DNA sequencing (i.e., ddRADseq) protocol with modifications proposed by Nazareno et al. (2017).

Data quality was checked using the program FastQC version: 0.11.8. The file containing raw sequence reads was analyzed in Stacks 2.41 (Catchen et al. 2011; Catchen et al. 2013; Rochette et al. 2019) using de novo assembly.

Usage Notes

There are seven csv files that contain the genotypes for all the 33 samples (column A, rows 4 to 36) for each locus. Each csv file contains data with different percentage of missing data, varying from 0% to 30%. At each csv file, the locus name always starts in column B.

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico, Award: 429266/2018-9

Conselho Nacional de Desenvolvimento Científico e Tecnológico, Award: 306182/2020-3