# A Multi-Tissue Yak (Bos grunniens) ceRNA Atlas with Ribo-Seq–Informed lncRNA Curation and Candidate Prioritization

## TL;DR

This study maps tissue-specific RNA regulatory networks in yaks, using Ribo-seq to improve accuracy and identify how gene regulation supports adaptation to high-altitude stress.

## Contribution

A novel Ribo-seq-informed workflow reduces false positives in ceRNA networks and provides a curated multi-tissue yak ceRNA atlas.

## Key findings

- Tissue-specific ceRNA networks show strong variation in connectivity, with testis having the highest.
- Ribo-seq filtering reduced false positives by removing lncRNA candidates with ribosome-occupancy signals.
- miRNA usage patterns were more consistent across tissues than ceRNA connections.

## Abstract

Yaks live at high altitude, where low oxygen and cold temperatures place long-term stress on multiple organs. How different tissues coordinate gene regulation to support this adaptation is still not fully understood. Here, we analyzed RNA sequencing and microRNA sequencing data from several yak tissues (pooled from three animals per tissue) to build tissue-specific regulatory networks based on the competing endogenous RNA (ceRNA) idea, in which RNAs can influence each other by sharing microRNA binding sites. A major challenge in ceRNA analysis is that some transcripts labeled as “noncoding” by computational prediction may still show evidence of translation, which can create false links in network inference. To reduce this risk, we used ribosome profiling (Ribo-seq) as an additional quality-control step and removed lncRNA candidates with clear ribosome-occupancy signals before constructing the networks. We found that ceRNA connections differed strongly between tissues, whereas microRNA usage patterns were relatively more consistent, supporting a “conserved core–tissue-specific periphery” organization. The testis network was the most highly connected, consistent with complex post-transcriptional regulation during reproduction. Overall, our results provide reusable multi-tissue resources and a prioritized candidate list for future experimental studies on yak physiology and high-altitude adaptation.

The yak (Bos grunniens) thrives under chronic hypoxia and cold on the Qinghai–Tibet Plateau, yet a cross-tissue view of post-transcriptional regulation in this species remains limited. Here, we integrated multi-tissue RNA-seq and miRNA-seq data (tissues pooled from three Maiwa yaks) to construct and compare tissue-specific competing endogenous RNA (ceRNA) networks, while explicitly addressing a major source of false positives in ceRNA inference—misclassified lncRNA candidates with translational signatures. We cataloged 10,037 high-confidence lncRNAs (9360 non-redundant), 234 circRNAs, and 1030 miRNAs across six tissues. We then used Ribo-seq as an orthogonal quality-control layer to remove lncRNA candidates showing clear ribosome-association signals prior to network construction. Using a shared-target strategy (7mer-m8 seed matches; a ceRNA edge required ≥5 shared miRNAs), we assembled ceRNA networks for liver, lung, spleen, testis, and small intestine; skeletal muscle was excluded owing to insufficient Ribo-seq support for consistent filtering. Network topology varied substantially across tissues, with the testis network exhibiting the highest connectivity. ceRNA edges showed minimal overlap between tissues, indicating strong tissue dependence, whereas miRNA load/use profiles were moderately concordant, supporting a hierarchical conserved core—variable periphery organization. Importantly, the Ribo-seq–filtered lncRNA set provides a separate pool of ribosome-associated candidates for targeted follow-up, although ribosome association alone does not establish stable micropeptide production. Together, our results deliver a multi-tissue ceRNA resource and a reproducible, evidence-aware workflow for prioritizing candidate regulators while reducing annotation-driven false positives in yak.