Code and Data for manuscript "Floral phenotypic divergence and genomic insights in an Ophrys orchid: Unraveling early speciation processes"

Floral phenotypic divergence and genomic insights in an Ophrys orchid: Unraveling early speciation

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This repository contains all the R code used in the manuscript:

* Title: "Floral phenotypic divergence and genomic insights in an Ophrys orchid: Unraveling early speciation"

* Authors: Anais Gibert, Schatz Bertrand, Buscail Roselyn, Dominique Nguyen, Baguette Michel, Bartes Nicolas and Joris Bertrand

* Year of publication: 2024

* doi: https://doi.org/10.1101/2024.03.21.586062

Synopsis of the study

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Adaptive radiation in Ophrys orchids leads to complex floral phenotypes that vary in scent, color and shape.

Using a novel pipeline to quantify these phenotypes, we investigated trait divergence at early stages of speciation in six populations of Ophrys aveyronensis experiencing recent allopatry. By integrating different genetic/genomic techniques, we investigated: (i) variation and integration of floral components (scent, color and shape), (ii) phenotypes and genomic regions under divergent selection, and (iii) the genomic bases of trait variation.

We identified a large genomic island of divergence, associated with phenotypic variation in particular in floral odor. We detected potential divergent selection on macular color, while convergent selection was suspected on floral morphology and for several volatile olfactive compounds. We also identify candidate genes involved in anthocyanin and in steroid biosynthesis pathways associated with standing genetic variation in color and odor.

This study sheds light on early differentiation in Ophrys, revealing patterns that often become invisible over time, i.e., the geographic mosaic of traits under selection and the early appearance of strong genomic divergence. It also supports a crucial genomic region for future investigation and highlights the value of a multifaceted approach in unraveling speciation within taxa with large genomes.

Running the code

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Here we present the data and code for carrying out the analyses, as well as the figures and tables from the article and the supplementary material. Once you have installed the necessary packages, run the commands in 'analysis_share.R'. This script uses several functions available in the '/R' directory.

Figures and tables are produced in a 'manuscript/figures' and 'manuscript/tables' directory. The `/data' directory contains the data used in the analyses (data/input or data/output), but also the resulting datasets produced by the code (data/RData/).