BACKGROUND: Decoding human genomic sequences requires comprehensive analysis of DNA sequence functionality. Through computational and experimental approaches, researchers have studied the genotype-phenotype relationship and generate important datasets that help unravel complicated genetic blueprints. Thus, the recently developed artificial intelligence methods can be used to interpret the functions of those DNA sequences.
METHODS: This study explores the use of deep learning, particularly pre-trained genomic models like DNA_bert_6 and human_gpt2-v1, in interpreting and representing human genome sequences. Initially, we meticulously constructed multiple datasets linking genotypes and phenotypes to fine-tune those models for precise DNA sequence classification. Additionally, we evaluate the influence of sequence length on classification results and analyze the impact of feature extraction in the hidden layers of our model using the HERV dataset. To enhance our understanding of phenotype-specific patterns recognized by the model, we perform enrichment, pathogenicity and conservation analyzes of specific motifs in the human endogenous retrovirus (HERV) sequence with high average local representation weight (ALRW) scores.
RESULTS: We have constructed multiple genotype-phenotype datasets displaying commendable classification performance in comparison with random genomic sequences, particularly in the HERV dataset, which achieved binary and multi-classification accuracies and F1 values exceeding 0.935 and 0.888, respectively. Notably, the fine-tuning of the HERV dataset not only improved our ability to identify and distinguish diverse information types within DNA sequences but also successfully identified specific motifs associated with neurological disorders and cancers in regions with high ALRW scores. Subsequent analysis of these motifs shed light on the adaptive responses of species to environmental pressures and their co-evolution with pathogens.
CONCLUSIONS: These findings highlight the potential of pre-trained genomic models in learning DNA sequence representations, particularly when utilizing the HERV dataset, and provide valuable insights for future research endeavors. This study represents an innovative strategy that combines pre-trained genomic model representations with classical methods for analyzing the functionality of genome sequences, thereby promoting cross-fertilization between genomics and artificial intelligence.

UNASSIGNED: Computational studies were performed to investigate the unknown status of endosomal and cell surface receptors in SARS-CoV-2 infection. The interactions between Toll-like receptors (TLRs)- 4/7/8/9 or ACE2 receptor and different SARS-CoV-2 variants were investigated.
UNASSIGNED: The RNA motifs for TLR7, TLR8 and a CpG motif for TLR9 were analyzed in different variants. Molecular docking and molecular dynamics (MD) simulations were performed to investigate receptor-ligand interactions.
UNASSIGNED: The number of motifs recognized by TLR7/8/9 in the Alpha, Delta and Iranian variants was lower than in the wild type (WT). Docking analysis revealed that the Alpha, Delta and some Iranian spike variants had a higher affinity for ACE2 and TLR4 than the WT, which may account for their higher transmission rate. The MD simulation also showed differences in stability and structure size between the variants and the WT, indicating potential variations in viral load.
UNASSIGNED: It appears that Alpha and some Iranian isolates are the variants of concern due to their higher transmissibility and rapid spread. The Delta mutant is also a variant of concern, not only because of its closer interaction with ACE2, but also with TLR4. Our results emphasize the importance of ACE2 and TLR4, rather than endosomal TLRs, in mediating the effects of different viral mutations and suggest their potential therapeutic applications.

The FK506 Binding Protein (FKBP), ubiquitously present across diverse species, is characterized by its evolutionarily conserved FK506 binding domain (FKBd). In plants, evidence suggests that this gene family plays integral roles in regulating growth, development, and responses to environmental stresses. Notably, research on the identification and functionality of FKBP genes in rice remains limited. Therefore, this study utilized bioinformatic tools to identify 30 FKBP-encoding genes in rice. It provides a detailed analysis of their chromosomal locations, evolutionary relationships with the Arabidopsis thaliana FKBP family, and gene structures. Further analysis of the promoter elements of these rice FKBP genes revealed a high presence of stress-responsive elements. Quantitative PCR assays under drought and heat stress conditions demonstrated that genes OsFKBP15-2, OsFKBP15-3, OsFKBP16-3, OsFKBP18, and OsFKBP42b are inducible by these adverse conditions. These findings suggest a significant role for the rice FKBP gene family in stress adaptation. This research establishes a critical foundation for deeper explorations of the functional roles of the OsFKBP genes in rice.

Bos taurus is known for its tolerance of coarse grains, adaptability, high temperature, humidity, and disease resistance. Primarily, cattle are raised for their meat and milk, and pinpointing genes associated with traits relevant to meat production can enhance their overall productivity. The aim of this study was to identify the genome, analyze the evolution, and explore the function of the Pax gene family in B. taurus to provide a new molecular target for breeding in meat-quality-trait cattle. In this study, 44 Pax genes were identified from the genome database of five species using bioinformatics technology, indicating that the genetic relationships of bovids were similar. The Pax3 and Pax7 protein sequences of the five animals were highly consistent. In general, the Pax gene of the buffalo corresponds to the domestic cattle. In summary, there are differences in affinity between the Pax family genes of buffalo and domestic cattle in the Pax1/9, Pax2/5/8, Pax3/7, and Pax4/6 subfamilies. We believe that Pax1/9 has an effect on the growth traits of buffalo and domestic cattle. The Pax3/7 gene is conserved in the evolution of buffalo and domestic animals and may be a key gene regulating the growth of B. taurus. The Pax2/5/8 subfamily affects coat color, reproductive performance, and milk production performance in cattle. The Pax4/6 subfamily had an effect on the milk fat percentage of B. taurus. The results provide a theoretical basis for understanding the evolutionary, structural, and functional characteristics of the Pax family members of B. taurus and for molecular genetics and the breeding of meat-production B. taurus species.

MicroRNAs (miRNAs) in oral squamous cell carcinoma (OSCC)-derived small extracellular vesicles (sEVs) play a pivotal role in modulating intercellular communications between tumor cells and other cells in the microenvironment, thereby influencing tumor progression and the efficacy of therapeutic interventions. However, a comprehensive inventory of these secretory miRNAs in sEVs and their biological and clinical implications remains elusive. This study aims to profile the miRNA content of OSCC cell line sEVs and computationally elucidate their biological and clinical relevance. We conducted miRNA sequencing to compare the miRNA profiles of OSCC cells and their corresponding sEVs. Our motif enrichment analysis identified specific sorting motifs that are implicated in either cellular retention or preferential sEV secretion. Target cell analysis suggested that the sEV miRNAs potentially interact with various immune cell types, including natural killer cells and dendritic cells. Additionally, we explored the clinical relevance of these miRNAs by correlating their expression levels with TNM stages and patient survival outcomes. Intriguingly, our findings revealed that a distinct sEV miRNA signature is associated with lymph node metastasis and poorer survival in patients in TCGA-HNSC dataset. Collectively, this research furthers our understanding of the miRNA sorting mechanisms in OSCC and underscores their clinical implications.

The establishment of high-quality pork breeds for improving meat quality in the pig industry is needed. The Chuxiang Black (CX) pig is a new breed developed from Chinese local pigs and Western lean pigs that has a high proportion of lean meat and excellent meat quality. However, the characteristics of cis-regulatory elements in CX pigs are still unknown. In this study, cis-regulatory elements of muscle and adipose tissues in CX pigs were investigated using ChIP-seq and RNA sequencing. Compared with the reported cis-regulatory elements of muscle and adipose tissues, 1768 and 1012 highly activated enhancers and 433 and 275 highly activated promoters in CX muscle and adipose tissues were identified, respectively. Motif analysis showed that transcription factors, such as MEF2A and MEF2C, were core regulators of highly activated enhancers and promoters in muscle. Similarly, the transcription factors JUNB and CUX1 were identified as essential for highly activated enhancers and promoters in CX adipose tissue. These results enrich the resources for the analysis of cis-regulatory elements in the pig genome and provide new basic data for further meat quality improvement through breeding in pigs.

We aim to accurately distinguish ubiquitin-specific proteases (USPs) from other members within the deubiquitinating enzyme families based on protein sequences. Additionally, we seek to elucidate the specific regulatory mechanisms through which USP26 modulates Krüppel-like factor 6 (KLF6) and assess the subsequent effects of this regulation on both the proliferation and migration of cervical cancer cells.
All the deubiquitinase (DUB) sequences were classified into USPs and non-USPs. Feature vectors, including 188D, n-gram, and 400D dimensions, were extracted from these sequences and subjected to binary classification via the Weka software. Next, thirty human USPs were also analyzed to identify conserved motifs and ascertained evolutionary relationships. Experimentally, more than 90 unique DUB-encoding plasmids were transfected into HeLa cell lines to assess alterations in KLF6 protein levels and to isolate a specific DUB involved in KLF6 regulation. Subsequent experiments utilized both wild-type (WT) USP26 overexpression and shRNA-mediated USP26 knockdown to examine changes in KLF6 protein levels. The half-life experiment was performed to assess the influence of USP26 on KLF6 protein stability. Immunoprecipitation was applied to confirm the USP26-KLF6 interaction, and ubiquitination assays to explore the role of USP26 in KLF6 deubiquitination. Additional cellular assays were conducted to evaluate the effects of USP26 on HeLa cell proliferation and migration.
1. Among the extracted feature vectors of 188D, 400D, and n-gram, all 12 classifiers demonstrated excellent performance. The RandomForest classifier demonstrated superior performance in this assessment. Phylogenetic analysis of 30 human USPs revealed the presence of nine unique motifs, comprising zinc finger and ubiquitin-specific protease domains. 2. Through a systematic screening of the deubiquitinase library, USP26 was identified as the sole DUB associated with KLF6. 3. USP26 positively regulated the protein level of KLF6, as evidenced by the decrease in KLF6 protein expression upon shUSP26 knockdown in both 293T and Hela cell lines. Additionally, half-life experiments demonstrated that USP26 prolonged the stability of KLF6. 4. Immunoprecipitation experiments revealed a strong interaction between USP26 and KLF6. Notably, the functional interaction domain was mapped to amino acids 285-913 of USP26, as opposed to the 1-295 region. 5. WT USP26 was found to attenuate the ubiquitination levels of KLF6. However, the mutant USP26 abrogated its deubiquitination activity. 6. Functional biological assays demonstrated that overexpression of USP26 inhibited both proliferation and migration of HeLa cells. Conversely, knockdown of USP26 was shown to promote these oncogenic properties.
1. At the protein sequence level, members of the USP family can be effectively differentiated from non-USP proteins. Furthermore, specific functional motifs have been identified within the sequences of human USPs. 2. The deubiquitinating enzyme USP26 has been shown to target KLF6 for deubiquitination, thereby modulating its stability. Importantly, USP26 plays a pivotal role in the modulation of proliferation and migration in cervical cancer cells.

Seed dispersal by frugivorous birds facilitates plant invasions, but it is poorly known how invasive plants integrate into native communities in fragmented landscapes. We surveyed plant-frugivore interactions, including an invasive plant (Phytolacca americana), on 22 artificial land-bridge islands (fragmented forests) in the Thousand Island Lake, China. Focusing on frugivory interactions that may lead to seed dispersal, we built ecological networks of studied islands both at the local island (community) and at landscape (metacommunity) levels. On islands with P. americana, we found that P. americana impacted local avian frugivory networks more on islands with species-poor plant communities and on isolated islands. Moreover, as P. americana interacted mainly with local core birds (generalists), this indicates reduced seed dispersal of native plants on invaded islands. At the landscape level, P. americana had established strong interactions with generalist birds that largely maintain seed-dispersal functions across islands, as revealed by their topologically central roles both in the regional plant-bird trophic network and in the spatial metanetwork. This indicates that generalist frugivorous birds may have facilitated the dispersal of P. americana across islands, making P. americana well integrated into the plant-frugivore mutualistic metacommunity. Taken together, our study demonstrates that the impact of plant invasion is context-dependent and that generalist native frugivores with high dispersal potential may accelerate plant invasion in fragmented landscapes. These findings highlight the importance of taking the functional roles of animal mutualists and habitat fragmentation into account when managing plant invasions and their impact on native communities.

Lectins are glycoproteins that can bind to specific carbohydrates, and different lectin families exhibit different biological activities. They are also present in the cyanobacteria and many of them have shown excellent therapeutic effect, which deserve for bioprospecting. However, in comparison to those from terrestrial plants, the current knowledge on cyanobacterial lectins is very limited. To this end, genome-wide analyses were performed to find out their evolutionary mode and motif patterns in 316 genomes of representative taxa. In results, 196 putative cyanobacterial lectins were dig out and 105 of them were classified into known families. Seven lectins were found to be belonged to distinct two lectin families, and they may have the potential activities of both lectin families. Whereas no MFP-2, Chitin, and Nictaba family lectins were found. What\'s more, the Legume lectin-like lectin family was found to be the richest and most complex in cyanobacteria, which could be a main research direction for future cyanobacterial lectin bioprospecting and development. Our classification and prediction of cyanobacteria lectins is expected to provide assistance in the development of lectin-based medicine and provide solutions to the current thorny viral and tumor diseases in humans.

Disorders of consciousness are impaired states of consciousness caused by severe brain injuries. Previous resting-state functional magnetic resonance imaging studies have reported abnormal brain network properties at different topological scales in patients with disorders of consciousness by using graph theoretical analysis. However, it is still unclear how inter-regional directed propagation activities affect the topological organization of functional brain networks in patients with disorders of consciousness. To reveal the altered topological organization in patients with disorders of consciousness, we constructed whole-brain directed functional networks by combining functional connectivity analysis and time delay estimation. Then we performed graph theoretical analysis based on the directed functional brain networks at three topological scales, from the nodal scale, the resting-state network scale to the global scale. Finally, the canonical correlation analysis was used to determine the correlations between altered topological properties and clinical scores in patients with disorders of consciousness. At the nodal scale, we observed decreased in-degree and increased out-degree in the precuneus in patients with disorders of consciousness. At the resting-state network scale, the patients with disorders of consciousness showed reorganized motif patterns within the default mode network and between the default mode network and other resting-state networks. At the global scale, we found a lower global clustering coefficient in the patients with disorders of consciousness than in the controls. The results of the canonical correlation analysis showed that the abnormal degree and the disrupted motif were significantly correlated with the clinical scores of the patients with disorders of consciousness. Our findings showed that consciousness impairment can be revealed by abnormal directed connection patterns at multiple topological scales in the whole brain, and the disrupted directed connection patterns may serve as clinical biomarkers to assess the dysfunction of patients with disorders of consciousness.