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Tibetan pig is a geographically isolated pig breed that inhabits high-altitude areas of the Qinghai–Tibetan plateau. At present, there is limited research on viral diseases in Tibetan pigs. This study provides a novel metagenomic exploration of the gut virome in Tibetan pigs (altitude ≈ 3000 m) across three critical developmental stages, including lactation, nursery, and fattening. The composition of viral communities in the Tibetan pig intestine, with a dominant presence of Microviridae phages observed across all stages of development, in combination with the previous literature, suggest that it may be associated with geographical locations with high altitude. Functional annotation of viral operational taxonomic units (vOTUs) highlights that, among the constantly increasing vOTUs groups, the adaptability of viruses to environmental stressors such as salt and heat indicates an evolutionary response to high-altitude conditions. It shows that the lactation group has more abundant viral auxiliary metabolic genes (vAMGs) than the nursery and fattening groups. During the nursery and fattening stages, this leaves only DNMT1 at a high level. which may be a contributing factor in promoting gut health. The study found that viruses preferentially adopt lytic lifestyles at all three developmental stages. These findings not only elucidate the dynamic interplay between the gut virome and host development, offering novel insights into the virome ecology of Tibetan pigs and their adaptation to high-altitude environments, but also provide a theoretical basis for further studies on pig production and epidemic prevention under extreme environmental conditions.

Abstract Understanding phylogenetic relationships among species is essential for many biological studies, which call for an accurate phylogenetic tree to understand major evolutionary transitions. The phylogenetic analyses present a major challenge in estimation accuracy and computational efficiency, especially recently facing a wave of severe emerging infectious disease outbreaks. Here, we introduced a novel, efficient framework called Bases-dependent Rapid Phylogenetic Clustering (Bd-RPC) for new sample placement for viruses. In this study, a brand-new recoding method called Frequency Vector Recoding was implemented to approximate the phylogenetic distance, and the Phylogenetic Simulated Annealing Search algorithm was developed to match the recoded distance matrix with the phylogenetic tree. Meanwhile, the indel (insertion/deletion) was heuristically introduced to foreign sequence recognition for the first time. Here, we compared the Bd-RPC with the recent placement software (PAGAN2, EPA-ng, TreeBeST) and evaluated it in Alphacoronavirus, Alphaherpesvirinae, and Betacoronavirus by using Split and Robinson-Foulds distances. The comparisons showed that Bd-RPC maintained the highest precision with great efficiency, demonstrating good performance in new sample placement on all three virus genera. Finally, a user-friendly website (http://www.bd-rpc.xyz) is available for users to classify new samples instantly and facilitate exploration of the phylogenetic research in viruses, and the Bd-RPC is available on GitHub (http://github.com/Bin-Ma/bd-rpc).

Phosphorus (P) is an essential nutrient for plant growth, and low-phosphorus (LP) stress significantly limits cotton productivity. Here, we conducted single- and multi-locus genome-wide association studies (GWASs) on four LP-related traits using 419 upland cotton (Gossypium hirsutum L.) accessions genotyped with 2.97 million single-nucleotide polymorphisms (SNPs). Phenotypic analysis reveals substantial variation under LP stress, with LP-SDW showing the highest coefficient of variation (33.69%). The GWASs identified thousands of significant SNPs, including pleiotropic loci associated with multiple traits. Chromosomes A08, D09, and D12 harbored novel associated signals. Multi-locus models significantly enhanced detection sensitivity, identifying 123 SNPs undetected by single-locus approaches. Functional annotations prioritized six candidate genes near associated SNPs, including GhM_A08G1315 (remorin protein) and GhM_D06G1152 (carotenoid cleavage dioxygenase), whose LP-induced expression patterns were validated by qRT-PCR. These genes are implicated in membrane signaling, root architecture modulation, and hormone metabolism. Our findings provide novel genetic insights into LP tolerance and establish a foundation for breeding phosphorus-efficient varieties through marker-assisted selection in cotton.

This paper mainly studies on the problem of robust multi-hop routing selection in Cooperative Cognitive Radio Networks (CCRNs). Our objective is to improve the throughput of Primary Users (PUs) while increase the opportunity that Secondary Users (SUs) can access the licensed spectrum. We combine the multi-hop routing selection problem with the graph-based cooperative game and bipartite graph model. A novel effective multi-hop routing selection algorithm called GBRA is proposed for CCRNs. The effect of relays to the routing path on throughput is considered. A novel method is introduced to divide coalition. A fair allocation rule to allocate the total profits of one coalition to its members is also introduced. Finally, based on the proposed coalition division method and the proposed profits allocation scheme in one coalition, the stability of the multi-hop routing path selected by GBRA is proved. Theoretical analysis and performance evaluation show that both PUs and SUs can improve their communication performance when they cooperate with each other.