Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.64898/2026.10.16.759661

Statistical analysis provides new insights into patterns and mechanisms of the WANCY hotspot on vertebrate mitochondrial genomes

Xu, C.·Wilkinson, M.
View original source ↗Export metadata ↓

Abstract

The vertebrate mitochondrial genomes are commonly composed of 37 genes, and the order of these genes act as useful indicator of phylogenetic relationships. Tandem duplication and random loss (TDRL) is considered to be one of the most important mechanisms leading to mitochondrial gene order rearrangement in vertebrates. The WANCY region has been widely recognized as a TDRL hotspot. In the past, the lack of data limited the in-depth exploration of rearrangement patterns and mechanisms in hotspots. Through statistical analysis of a large amount of available NCBI sequencing data, combined with phylogenetic and bioinformatics methods, we obtained statistically significant data from the four classes of Amphibians, Reptiles, Mammalia and Osteichthyes. These data demonstrate three new convergent rearrangements in the WANCY region of vertebrates, which suggests that the frequency of convergent rearrangements in hotspots is higher than previously thought. We also compared the frequency of TDRL rearrangement in the WANCY region with two other similar small gene clusters (the IQM region and the HSL region). The results to a certain extent support the hypothesis that the WANCY region may be a mechanism hotspot. However, more molecular evidence and larger data volumes are needed to confirm the existence of mechanisms that cause rearrangement hotspots.

Explore related subjects

genomicsPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Xu, C., Wilkinson, M.. 2026-10-22. Statistical analysis provides new insights into patterns and mechanisms of the WANCY hotspot on vertebrate mitochondrial genomes. https://doi.org/10.64898/2026.10.16.759661

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Shared genomic signatures of Arctic adaptation among distantly related plant lineages

Extreme environments impose strong selection pressures that can drive convergent adaptation among distantly related species. Arctic plants survive low temperatures, 24-hour light in summer and darkness in winter, short growing seasons, limited precipitation, nutrient-poor soils, and extreme seasonal variation. To test if these conditions are associated with shared genomic signatures, we generated a chromosome-level genome assembly for Oxyria digyna and compared it with existing reference genomes for three distantly related Arctic species (Cochlearia groenlandica, Draba nivalis, Dryas octopetala) and for 16 non-Arctic species from the same families. We identified 214 orthogroups with signatures of positive selection in all Arctic species, 1.6 times the number shared among the non-Arctic species. Although no gene ontology (GO) categories remained significantly enriched after multiple-testing correction, descriptive annotations included genes involved in general functions including protein folding, glycolysis, transcription, and oxidative-stress responses. Orthogroups showing copy number variation were associated with biotic interactions, sexual reproduction, and nutrient acquisition, suggesting that species may respond to biotic and nutrient stresses by shifts in gene copy number. Arctic and alpine genomes contained lower proportions of some repetitive elements, including terminal inverted repeats, and smaller regions of centromeric repeats than non-Arctic genomes. Overall, we see shared genes under positive selection, similar functions of genes with high copy number variation, and lower counts of some repetitive elements in the Arctic plant genomes. Our findings reveal a shared genomic signature of Arctic adaptation across deeply diverged plant lineages, suggesting that evolution in extreme environments repeatedly targets similar genomic features.

genomics↗
bioRxiv2026

MutQA: A Cross-Validated Q&A Dataset for Genetic Mutations

We introduce MutQA, a dataset of 330,387 citation-grounded question-answer (QA) pairs linking genetic mutations to their functional consequences as described in the biomedical literature. Each record pairs a protein-coding mutation with a natural-language question and an evidence-backed answer anchored to sentences in one of 27,442 open-access PubMed Central articles, spanning 6,620 genes and 125,593 gene-variant pairs. The dataset is constructed using CrossValQA, a framework that enforces information isolation between independent LLMs: one model generates QA pairs from an article, a second model answers the same question without access to the first model's response, and a third model judges whether each model's rationale supports the other's answer, so that retained QA pairs are reproducible from the source text rather than hallucinated. Of 401,406 audited QA pairs, 82.7% pass both directions of this cross-validation; those with a recoverable reference protein sequence form the released benchmark. In a 999-pair stratified audit, two expert annotators agree exactly on 86.4% of cross-validated QA pairs (95% CI 83.7-89.0; n = 638), a tier in which about 90% of ratings are "correct". Individual LLM judges agree with individual annotators at a comparable 87.0% on this tier but far less on QA pairs that fail cross-validation. Fine-tuning MutaPLM on MutQA nearly doubles its mean LLM-judge score for question-conditioned mutation-effect answering (1.45 to 2.82 on a 0-5 scale) and improves mutation-recovery accuracy from effect descriptions from 19.4% to 32.1%. Providing variant-matched MutQA retrieval context, without fine-tuning, improves strict answer accuracy across four LLM families by 20.0-28.6 percentage points, demonstrating the framework's ability to improve the reliability of LLM answers. We also apply CrossValQA to proteomics, providing a proof of concept for its use beyond mutation-specific QA. We release the dataset, construction framework, and evaluation code.

genomics↗
bioRxiv2026

Characterisation of cis-regulatory elements and genome wide enhancer prediction in Heliconiini butterflies

The large-scale annotation and spatiotemporal characterisation of cis-regulatory promoters and enhancers remain limited in many non-model organisms, largely due to fragmented availability of multiomic datasets across species and developmental conditions. Heliconius butterflies, which have been used to investigate wing development and patterning, have provided key insights into the genetic architecture underlying morphological diversification and adaptive pigmentation. Despite this, we are limited in what we understand of how cis-regulatory dynamics drive phenotypic wing patterning variation. Here, by re-analysing and re-evaluating available data, we present a comprehensive new description of a cis-regulatory atlas for Heliconius wing development by integrating chromatin accessibility dynamics (ATAC-seq) with histone modification profiling (H3K27ac, H3K4me3). High-confidence peak sets enabled robust annotation of promoters and enhancers, revealing regulatory distributions consistent with canonical regulatory organisation. Promoters displayed comparatively higher conservation of transcription factor motifs, whilst enhancers exhibited greater sequence diversity, broader genomic distributions and more variable motif repertoires. Comparative analysis revealed cis-regulatory divergence to be primarily temporal, with substantial chromatin remodelling and differential histone enrichment across development, while regulatory dynamics were highly conserved between forewing and hindwing tissues. Extending these experimentally characterised regulatory landscapes, a convolutional neural network was trained for sequence-based enhancer prediction, achieving test AUROC and AUPRC values of 0.909 and 0.913, respectively. Predictions across 34 Heliconiini assemblies displayed significant enrichment within independently characterised accessible chromatin and conserved non-exonic elements (CNEEs), supporting their putative regulatory function. Overall, this study provides a large-scale characterisation of cis-regulatory dynamics and extends enhancer annotation across Heliconiini, providing a foundation for comparative investigations of regulatory conservation and diversification.

genomics↗