Zatha, R. | Search bioRxiv

bioRxiv2024

Introgression dynamics of sex-linked chromosomal inversions shape the Malawi cichlid adaptive radiation

Chromosomal inversions contribute to adaptive speciation by linking co-adapted alleles. Querying 1,375 genomes of the species-rich Malawi cichlid fish radiation, we discovered five large inversions segregating in the benthic subradiation that each suppress recombination over more than half a chromosome. Two inversions were transferred from deepwater pelagic Diplotaxodon via admixture, while the others established early in the deep benthic clade. Introgression of haplotypes from lineages inside and outside the Malawi radiation coincided with bursts of species diversification. Inversions show evidence for transient sex linkage and a striking excess of protein changing substitutions points towards selection on neuro-sensory, physiological and reproductive genes. We conclude that repeated interplay between depth adaptation and sex-specific selection on large inversions has been central to the evolution of this iconic system.

evolutionary biology↗

bioRxiv2023

A deep learning phenotyping method for genetic analysis of 3D micro-CT data

The number of Genome-Wide Association Studies (GWAS) has been growing rapidly in recent years due to developments in genotyping and sequencing platforms. When applied to quantitative traits, these and other statistical genetics approaches require large amounts of consistently and accurately measured phenotypes. Here, we introduce a computational toolbox based on deep convolutional neural networks that we have developed to phenotype quantitative traits describing morphology from micro-CT-scan image datasets. We illustrate the use of this Deep Learning Phenotyper (DLP) on a sample set of craniofacial CT scans of 118 samples from two very closely related species of Lake Malawi cichlid fish, Maylandia zebra and Cynotilapia zebroides. We show that the pipeline constructed and implemented here is capable of measuring morphological skeletal phenotypes with high accuracy. We also demonstrate how this pipeline can be integrated with existing GWAS frameworks to identify candidate association loci. We believe the methods we present here will be valuable for groups studying quantitative morphological traits not only in fishes, but in other vertebrates using CT scan datasets.

genetics↗