Spatial ploidy inference using quantitative imaging

TL;DR

iSPy is a new method that uses imaging to map ploidy levels in intact tissues, helping researchers study how chromosome copy numbers vary across different organisms and biological conditions.

Contribution

iSPy introduces a high-throughput pipeline for spatial ploidy inference in intact tissues using unsupervised learning.

Findings

iSPy generates spatial ploidy maps without destroying tissue architecture.

The method is validated in Arabidopsis, Drosophila, and human tissues.

iSPy enables rapid and accurate quantification of nuclear ploidy.

Abstract

Polyploidy (whole-genome duplication) is a common yet under-surveyed property of tissues across multicellular organisms. Polyploidy plays a critical role during tissue development, following acute stress, and during disease progression. Common methods to reveal polyploidy involve either destroying tissue architecture by cell isolation or tedious identification of individual nuclei in intact tissue. Therefore, there is a critical need for rapid and high-throughput ploidy quantification using images of nuclei in intact tissues. Here, we present iSPy (inferring Spatial Ploidy), an unsupervised learning pipeline that is designed to create a spatial map of nuclear ploidy across a tissue of interest. We demonstrate the use of iSPy in Arabidopsis, Drosophila, and human tissue. iSPy can be adapted for a variety of tissue preparations, including whole mount and sectioned. This high-throughput pipeline will facilitate rapid and sensitive identification of nuclear ploidy in diverse biological contexts and organisms.

•iSPy is a computational pipeline to generate spatial ploidy maps across a tissue•iSPy rapidly and accurately quantifies nuclear ploidy in intact tissues•We apply the method to Arabidopsis, Drosophila, and human nuclei•The spatial ploidy maps reveal insights into ploidy patterning across a tissue

iSPy is a computational pipeline to generate spatial ploidy maps across a tissue

iSPy rapidly and accurately quantifies nuclear ploidy in intact tissues

We apply the method to Arabidopsis, Drosophila, and human nuclei

The spatial ploidy maps reveal insights into ploidy patterning across a tissue

Ploidy, the number of chromosome copies in a nucleus, can vary spatially throughout a tissue, and this variation plays a critical role in eukaryotic organisms during tissue development, following acute stress, and during disease progression. However, common methods to reveal nuclear ploidy destroy the tissue and lose spatial ploidy information. As the importance of ploidy in tissue biology is increasingly recognized, powerful methods are needed to quantify nuclear ploidy throughout a tissue of interest at a given time and position without destroying tissue architecture. Therefore, we developed a high-throughput computational pipeline using quantitative image analysis from microscopy images to infer nuclear ploidy while retaining spatial information.

Russell et al. construct a high-throughput experimental and computational pipeline that calculates nuclear ploidy from microscopy images and outputs a representative ploidy map showing the spatial arrangement of the nuclear ploidies. They demonstrate and validate their pipeline using Arabidopsis, Drosophila, and human tissue.

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