Lambertia multiflora microsatellite data
Data files
Apr 12, 2024 version files 90.48 KB
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LambertiaMultifloraOffspringGenalexData.xlsx
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README.md
Abstract
The restoration of diverse self-sustaining ecosystems requires re-establishment of functional interactions among species. For plant communities, pollinators are usually essential for pollination, seed set, and seed quality. A common assumption in ecological restoration for plants pollinated by animals is one of “build it and they will come”, which is rarely tested. Beyond seed set, there may be negative genetic consequences for seed quality if pollinators and their behaviour do not reflect those in reference populations. Here, we conduct an ecological genetic assessment of seed quality via mating system parameters in Lambertia multiflora(Proteaceae), a species dependent on nectar-feeding birds for pollination. Four populations of L. multiflora in disturbed sites that were rehabilitated following mineral sand mining were compared to four natural reference populations, near Eneabba, Western Australia. In each population, approximately 10 offspring from each of 10 maternal plants were genotyped with 11 highly polymorphic microsatellite markers. From these data, genetic diversity and mating system parameters were assessed and found to be equivalent across all populations. Mean allelic diversity and heterozygosity across loci were very high. All populations were completely outcrossing with no bi-parental inbreeding. Mean correlated paternity, sibship, and effective population size estimates for restored and natural populations were not significantly different and reflected uniformly high paternal diversity and wide outcrossing. Results suggest self-incompatibility, a surprising result given high levels of selfing detected in other lambertias. Equivalent genetic results for restored and natural reference populations indicate successful restitution of bird-pollinator services for L. multiflora in these post-mining rehabilitation sites.
Synthesis and applications: Reviewing our results with other published studies suggests a resilience of bird-pollinator services in restored plant communities, a finding of broad reassurance to restoration practitioners working in these global south systems where bird pollination is a feature. Our study also highlights the global contribution of ecological genetics to the objective assessment of functional species interactions in ecological restoration, an increasingly important goal of land managers and regulators seeking to improve restoration standards.
README
Data file is an Excel spreadsheet containing microsatellite data for 682 samples of Lambertia multiflora offspring from 8 populations, 4 natural reference populations (N1-4) and 4 restored populations (R1-4).
Data are formatted for analysis in the software Genalex (Peakall, R. & Smouse, P. E. (2006). GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes, 6, 288-295; Peakall, R.& Smouse, P.E. (2012). GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research – an update. Bioinformatics 28, 2537-2539); https://biology-assets.anu.edu.au/GenAlEx/Welcome.html
Data are as per Genalex formatting requirements:
Row 1: # of loci (11), # of individuals (682), # of populations (8), then number of individuals from each of 8 populations.
Row 2: title, then names of each of 8 populations (R1-4, N1-4), where R refers to a restored population, N refers to a natural reference population.
Row 3: name of each of 11 loci.
Rows 4-695: microsatellite data for each of 11 microsatellite loci for each of 682 samples.
Column A: sample name, eg R1M3 is maternal plant 3 from restored population 1.
Column B: restored population name
Columns C-X: Allele size at each of 11 microsatellite loci for each sample.
Note yellow shaded cells indicate the inference of a maternal null allele.
Note this table can be read and analysed in Genalex. From Genalex, data can be exported as a csv file for analysis in MLTR.
Methods
Study populations and sampling
We identified eight populations of L. multiflora where plants were common and of equivalent size, and populations were of equivalent size and density (range 0.1-0.6 plants/m2). Four populations were in post-mining restoration sites, two older (established 30 and 38 years old) and two younger (established 10 and 11 years old), as well as four nearby undisturbed natural (reference) populations (Suppl Table 1; Fig 2). At all restoration sites, seed of L. multiflora have originated from topsoil or mulch, which has originated from multiple sources across the mine lease. From each population, we arbitrarily selected 10 maternal plants that were spaced >5 m apart and were fruit bearing, from which we collected at least 20 seed-bearing fruit per maternal. Leaves were sampled from all maternal plants and stored in activated silica for extraction of DNA. Seed were extracted from fruits, weighed and germinated, and leaves sampled from seedlings grown in the glasshouses at Kings Park for DNA extraction and genotyping.
Data collection and analysis
Microsatellite markers were developed for mating system analyses from DNA sequences generated by an Ion Torrent next-generation sequencer and the QDD3 pipeline (Meglecz et al 2014). A short list of 35 loci were identified for screening on 8 offspring from each of 3 families, from which 11 reliable polymorphic microsatellite loci exhibiting Mendelian inheritance were identified and scored for all samples. Null alleles were identified and re-scored on the basis of family arrays (supplementary data).
Parameters of genetic variation were analysed with Genalex v6.51b2 (Peakall and Smouse 2006, 2012) for maternal and offspring cohorts that were corrected for null alleles. Mating system parameters (i) multilocus outcrossing rate (tm), (ii) single-locus outcrossing rate (ts), (iii) bi-parental inbreeding (tm – ts), and (iv) correlation of paternal plants (rp), were estimated with MLTR (Ritland 2002). MLTR parameters were set at SE based on 1000 bootstraps, entire families resampled, Expectation-Maximisation method, pollen=ovule gene frequency, initial value of t set at 1, all other parameters at 0.1. The Windows version of the program COLONY (Jones and Wang 2010) was then used to implement maximum-likelihood estimation of the proportion of full- and half-sib relationships among offspring from each population, and likelihood estimates of effective population size from the estimated frequency of siblings (Wang 2009). The number of different sires for each population was estimated from ML configurations of each known offspring-maternal genotypes, from which paternal genotype was inferred. COLONY parameters included allowing polygamy for all males and females, mating system with inbreeding, full-likelihood analysis method, inclusion of known maternal sibships and maternal genotypes, estimate of maternal sibship size of 9, and all other parameters were program defaults.
Usage notes
Excel