A Quantitative Computational Framework for Allopolyploid Single-Cell Data Integration and Core Gene Ranking in Development.

ABSTRACT: Polyploidization drives regulatory and phenotypic innovation. How the merger of different genomes contributes to polyploid development is a fundamental issue in evolutionary developmental biology and breeding research. Clarifying this issue is challenging because of genome complexity and the difficulty in tracking stochastic subgenome divergence during development. Recent single-cell sequencing techniques enabled probing subgenome-divergent regulation in the context of cellular differentiation. However, analyzing single-cell data suffers from high error rates due to high dimensionality, noise, and sparsity, and the errors stack up in polyploid analysis due to the increased dimensionality of comparisons between subgenomes of each cell, hindering deeper mechanistic understandings. In this st

SUBMITTER: Wang M 

PROVIDER: S-EPMC11421573 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature