Between forest and homegarden, geographic patterns of genetic variation in the Mesoamerican Soncoya (Annona purpurea)

Study species

Annona purpurea Moc. & Sessé ex Dunal is a native Mesoamerican fruit tree of high cultural, nutritional, and medicinal importance. Unlike intensively domesticated crops, it represents a system of incipient and heterogeneous domestication, where traditional management practices vary geographically and may promote contrasting levels of connectivity with surrounding wild populations. This combination of ecological breadth, cultural relevance, and variable management intensity makes A. purpurea an ideal model for investigating the effects of domestication on genetic and morphological variation.

Sampling

A geographic survey of wild and managed populations of Annona purpurea will be conducted across its distribution in Mexico. Individuals will be classified according to management context, including traditional homegardens, agricultural systems, and natural or minimally disturbed environments. This characterization will be complemented through semi-structured interviews documenting traditional uses, management practices, and cultural importance. Leaf tissue will be collected for genomic analyses and mature fruits for morphological characterization.

Generation of genomic data

Genomic DNA will be extracted from leaf tissue and used to generate high-coverage sequencing data through target enrichment of hundreds of nuclear genes shared across Annonaceae. This approach provides genome-wide markers suitable for investigating genetic diversity, population structure, demographic history, and local adaptation.

Genomic processing and SNP identification

Sequencing reads will be processed to recover orthologous nuclear loci and remove ambiguous or potentially duplicated regions. Single nucleotide polymorphisms (SNPs), representing variable positions in the genome among individuals, will then be identified. Only high-quality variants will be retained to generate a robust dataset for downstream population genomic analyses.

Population structure and gene flow

Genetic structure will be evaluated using multivariate and ancestry-based approaches that identify genetically differentiated groups and estimate the degree of admixture among them. The relationship between genetic differentiation and geographic distance will also be examined to assess patterns of isolation by distance. In addition, shared ancestry among wild and managed populations will be used to infer levels of connectivity and gene flow associated with different management contexts. These analyses will help identify evolutionary lineages and evaluate the impact of domestication on population connectivity.

Genetic diversity

Genetic diversity indices will be estimated for populations, genetic groups, and management categories. These metrics provide a measure of the amount and distribution of genetic variation across the landscape and will be used to evaluate whether domestication has promoted the loss, maintenance, or redistribution of genetic diversity. Comparisons among management systems will help determine how different domestication intensities have influenced contemporary patterns of genetic variation.

Analysis of molecular variance (AMOVA)

The distribution of genetic variation within and among populations, genetic groups, management categories, and biogeographic regions will be quantified using hierarchical analyses of molecular variance. This approach partitions total genetic variation across different levels of organization and evaluates the relative contribution of management practices and geographic barriers to population differentiation.

Morphological variation

Fruit morphology will be characterized using traits associated with human selection, including fruit size and weight. Morphological variation will be compared among populations and management categories to evaluate whether domestication has promoted consistent patterns of phenotypic differentiation across the species’ range.

Historical demographic inference

The demographic history of the major genetic groups identified within A. purpurea will be reconstructed from genome-wide allele frequency distributions. This approach allows inference of changes in effective population size through time and the detection of signals of expansion, contraction, or demographic stability. Comparisons among genetic groups will help determine whether domestication and management have resulted in bottlenecks, reductions in genetic diversity, or the maintenance of large and interconnected populations.

Ecological niche modeling and genomic vulnerability to climate change

Occurrence records will be used to model the current and future potential distribution of Annona purpurea under alternative climate scenarios. Genomic and environmental data will also be integrated through genomic offset analyses based on climate-associated SNPs. This approach estimates the mismatch between the current genetic composition of populations and that expected to be optimal under future climatic conditions, allowing identification of populations with elevated vulnerability or adaptive potential in the face of climate change.