Quantifying structural variants in chromosomes using landmark-based disparity
Abstract
Background: Chromosomal architecture has played a key role in the evolution of biodiversity. Detecting structural variants (SVs) on chromosomes has informed the study of speciation, sex determination, adaptation, and some of the earliest divergences in the tree of life. Here we present a computationally non-intensive approach based on geometric morphometrics, that uses coordinate data from conserved, single-copy DNA sequences as landmarks to quantify structural disparities of focal chromosomes via primary or haploid genome assemblies across multiple species, individuals, or cell types.
Results: Based on two approaches, we show that this ‘geno-metric’ method can be applied at micro- and macroevolutionary scales to discover and diagnose SVs. Using human X-linked single-copy genes and ultraconserved elements as genomic ‘landmarks’, we provide empirical demonstrations with amniote sex chromosomes, the Drosophila virilis group, and placental mammal genomes. Landmark-based structural disparity analysis effectively identifies chromosomal SVs and has parallels with traditional morphometrics regarding chromosome size, landmark orientation and landmark availability. Using simulations, we show that structural disparity inferred from ultraconserved elements is correlated with overall levels of chromosome evolution; an attribute which is consistent with observed disparity between and within mammalian orders. We found that the disparity patterns of SVs have significant phylogenetic signal, giving them broad importance for studying evolutionary biology. We also discuss alternative approaches that may be used to extract genomic coordinates and SV data for multi-species comparisons.
Conclusions: Structural disparity analysis is a reference free, whole-genome alignment free, non-pairwise comparative method that uses coordinates of single-copy genomic markers and dimensionality reduction methods to measure SVs on homologous chromosome sets. The method offers an intuitive, rapid mechanism to detect and measure SVs and consequently, offers the potential to reveal broader patterns of chromosome evolution related to expansions, contractions, rearrangements and phylogenetic history.
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BibTeX
@article{mohan2026quantifying,
title = {{Quantifying structural variants in chromosomes using landmark-based disparity}},
author = {Ashwini V. Mohan and Anjali Goswami and Jeffrey W. Streicher},
journal = {BMC Biology},
year = {2026},
month = nov,
doi = {10.1186/s12915-026-02783-5},
url = {https://link.springer.com/article/10.1186/s12915-026-02783-5},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Quantifying structural variants in chromosomes using landmark-based disparity
AU - Ashwini V. Mohan
AU - Anjali Goswami
AU - Jeffrey W. Streicher
PY - 2026
DA - 2026/11/09
JO - BMC Biology
DO - 10.1186/s12915-026-02783-5
UR - https://link.springer.com/article/10.1186/s12915-026-02783-5
AB - Background: Chromosomal architecture has played a key role in the evolution of biodiversity. Detecting structural variants (SVs) on chromosomes has informed the study of speciation, sex determination, adaptation, and some of the earliest divergences in the tree of life. Here we present a computationally non-intensive approach based on geometric morphometrics, that uses coordinate data from conserved, single-copy DNA sequences as landmarks to quantify structural disparities of focal chromosomes via primary or haploid genome assemblies across multiple species, individuals, or cell types. Results: Based on two approaches, we show that this ‘geno-metric’ method can be applied at micro- and macroevolutionary scales to discover and diagnose SVs. Using human X-linked single-copy genes and ultraconserved elements as genomic ‘landmarks’, we provide empirical demonstrations with amniote sex chromosomes, the Drosophila virilis group, and placental mammal genomes. Landmark-based structural disparity analysis effectively identifies chromosomal SVs and has parallels with traditional morphometrics regarding chromosome size, landmark orientation and landmark availability. Using simulations, we show that structural disparity inferred from ultraconserved elements is correlated with overall levels of chromosome evolution; an attribute which is consistent with observed disparity between and within mammalian orders. We found that the disparity patterns of SVs have significant phylogenetic signal, giving them broad importance for studying evolutionary biology. We also discuss alternative approaches that may be used to extract genomic coordinates and SV data for multi-species comparisons. Conclusions: Structural disparity analysis is a reference free, whole-genome alignment free, non-pairwise comparative method that uses coordinates of single-copy genomic markers and dimensionality reduction methods to measure SVs on homologous chromosome sets. The method offers an intuitive, rapid mechanism to detect and measure SVs and consequently, offers the potential to reveal broader patterns of chromosome evolution related to expansions, contractions, rearrangements and phylogenetic history.
SN - 1741-7007
ER -