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Genetic imprints of Brosimum alicastrum (Moraceae) in Mexico

Citation

López-Barrera, Gabriela et al. (2022), Genetic imprints of Brosimum alicastrum (Moraceae) in Mexico, Dryad, Dataset, https://doi.org/10.5061/dryad.8cz8w9gq2

Abstract

PREMISE: Mechanisms generating the geographical distributions of genetic diversity are a central matter in evolutionary biology. The amount of genetic diversity and its distribution are controlled by several factors, including dispersal abilities, physical barriers and environmental and climatic changes. We investigated the patterns of genetic diversity and differentiation among populations of the widespread species Brosimum alicastrum in Mexico.

METHODS: Using nuclear DNA microsatellite data, we determined the current state of genetic diversity and its distribution to determine if the genetic structure was consistent with geographical settings of Mexico and to infer the role of past events in the genetic diversity patterns.

RESULTS: Our results suggested that Mexican B. alicastrum is well differentiated into three main lineages. Patterns of the genetic structure at a finer scale did not entirely correspond with the present-day geographic barriers to gene flow.

CONCLUSIONS: We propose that differentiation patterns might reflect: 1) an ancient differentiation that occurred in Central America and South America; 2) the effects of past climatic changes, and 3) the action of some physical barriers to gene flow. This study provides insights into the possible mechanisms underlying the geographic genetic variation of B. alicastrum along a moisture gradient in tropical lowland forests.

Methods

We collected foliar tissue from 328 adult trees from 33 populations of Brosimum alicastrum Sw. (Moraceae) sampled in tropical and subtropical evergreen and deciduous forests across its distribution in Mexico. Genomic DNA was extracted from ~100 mg of leaf tissue following the CTAB protocol for plants as described by Doyle and Doyle (1987). We amplified 15 nuclear microsatellite loci (Bro5, Bro7, Bro9, Bro10, Bro11, Bro12, Bro13, Bro14, Bro15, Bro16, Bro17, Bro18, Bro20, Bro24, and Bro28), and PCRs were performed individually in a total volume of 5 μL containing 3 μL of 2x QIAGEN Multiplex PCR Master Mix (QIAGEN, Maryland, United States), 0.5 μL of each primer (10 mM), and 1 μL of template DNA (20 ng/μL). Thermal cycling conditions consisted of an initial denaturation step of 95 °C for 15 minutes, 35 cycles of 95 °C for 15 seconds, an annealing temperature for 30 seconds, 72 °C for 1 min and a final extension step at 72 °C for 10 min. Multiplex PCR products were combined with a GeneScan-500 LIZ Size Standard (Applied Biosystems, California, United States) and DNA analysis was performed on an ABI-PRISM 3100 Avant sequencer (Applied Biosystems, California, United States). Fragment sizes were recorded using the Peak Scanner program 1.0 (Thermo Fisher Scientific, Waltham, Massachusetts, United States).

Once the sizes of the fragments have been obtained, to infer the presence of null alleles, we employed two approaches: FreeNA (Chapuis and Estoup, 2007) and Microchecker version 2.2.3 (Van Oosterhout et al., 2004). For FreeNA, we used 103 replicates with 95% confidence intervals (CIs), while for Microchecker, we used 103 bootstrap simulations and 95% CIs. Scoring errors caused by large allele dropout or stuttering in the microsatellite data were assessed using Microchecker with the same parameters. Deviations from Hardy-Weinberg equilibrium (HWE) were evaluated for each population across all loci and locus by locus across all populations. We also tested for nonrandom associations between alleles of different loci. For both analyses, we used Genepop on web version 4.7 (Raymond and Rousset, 1995; Rousset, 2008) with 104 dememorization steps, 103 batches, and 104 iterations per batch. For HWE, we applied a Bonferroni correction with the standard procedure (Miller, 1980; Lessios, 1992) using a critical value of 0.05.

With the revised database we proceeded to carry out the corresponding analyzes.

Usage Notes

The database includes the columns:

1) Name of population. (A)
2) Abbreviation of the name of the population. (B)
3) Individuals by population. (C)
4) Values of the alleles for each individual for each locus. (D-AG)

Missing data are indicated by zero.

Funding

Consejo Nacional de Ciencia y Tecnología, Award: 262638