Molecular Genetics and Genomics

Codon usage bias is a fundamental genomic characteristic that prefers non-random preferential use of synonymous codons. It is a major determinant of translational efficiency, gene regulation, and molecular evolution. However, the evolutionary bias and functional relevance of codon usage bias across the plant lineage is poorly defined and yet to understand what are the major factors responsible for relative synonymous codon usage (RSCU) in genomes and how codon usage bias influences the gene regulation, molecular evolution genomes. A genome-wide codon usage bias study of coding DNA sequences of 262 plant genome was conducted. It encompassed more than 4.6 billion codons from > 11 million coding sequences. Relative synonymous codon usage, codon adaptation index, codon-anticodon mapping, effective number of codon (ENC)-GC3, GC1,2-GC3, parity rule 2 (PR2-bias), molecular economy, and machine learning approaches were used for the study. It was found that codon usage bias was strongly non-random and exhibited a clear phylogenetic structuring. The higher plants favoured A/T-ending, whereas early-diverging lineages were enriched in G/C-ending codons. Analysis of RSCU, codon adaptation index, and codon-anticodon pairing indicated that translational selection is mediated by tRNA availability, contributing sustainability to these molecular patterns. Machine-learning approaches identified a small subset of codons having outsized influence on genome-wide codon usage landscapes. Further studies revealed the presence of robust inverse relationships between the effective number of codons and GC content at synonymous third positions. Neutrality analysis revealed approximately 61% of variation was driven by mutational pressure, tempered by selective constraints. Phylogenetic reconstruction showed a progressive relaxation of codon bias from algae to angiosperms while maintaining a conserved molecular economy cost of ~ 30 ATP per codon across the lineages. The study revealed codon usage bias is lineage-specific evolutionary conserved trait governed by mutation, selection, and translational optimization.

BackgroundRecombination rates can be estimated across the genome, underpinning genetic analyses such as identification of regions under selection. Accurate recombination mapping requires observing a large number of recombination events, necessitating large sample sizes to achieve high resolution. This can be prohibitive to some analyses, so population-based estimates can also be used, leveraging the increasing population genomic data available to researchers. ObjectiveThis study aimed to determine the extent to which population-based recombination maps from different human populations are similar and assess to what extent they can be used interchangeably. MethodsWavelet analysis was employed to decompose recombination rate signals along a chromosome and evaluate the proportion of variance explained at different scales. This method also enabled the assessment of correlations across scales and identification of regions with high coherence between datasets. The analysis focused on a region of chromosome 22 in human populations of European and African ancestry. ResultsRecombination rates are not closely conserved across populations, with the greatest divergence observed at fine scales. Coherence between populations varied significantly across all scales. ConclusionAs recombination maps differ substantially between human populations, for genetic analyses involving recombination maps, it is recommended to use maps specific to the population under study.

The natural vector method is an important method for the analysis of biological sequences. In this study, we applied this method to population genetic analysis, with the core purpose of using it to evaluate the characteristics of a set of sequences rather than just pairwise comparison. We used the mitochondrial genome dataset from the human 1000 Genomes Project as a dataset to verify the feasibility of this improved natural vector method. The results showed that the modified natural vector method could be used for various population genetic approaches at least in the sense of population average, including the calculation of principal component analysis, population structure analysis and genetic diversity parameters. The results were in good agreement with those based on traditional molecular genetic markers such as SNP. The new method validates the feasibility of natural vector method for population genetic analysis and provides a framework for the application of matchless pair method to population genomic analysis on a wider scale.

BackgroundGray is one of the relatively rare coat colors in donkeys. The Hetian Gray donkey is a distinctive indigenous breed from the Xinjiang Uygur Autonomous Region of Northwestern China, characterized by progressive hair depigmentation with aging while retaining dark skin pigmentation. However, the genetic basis underlying this unique gray coat color phenotype remains unclear. ResultsTo elucidate the genetic basis, we conducted whole-genome resequencing of Gray and non-Gray donkeys. Genome-wide selection signature analyses identified a candidate region on chromosome 15. Subsequent fine-mapping using mass spectrometry-based genotyping of 42 loci refined the candidate interval and revealed a SNP within intron 2 of the ASIP gene, located in a genomic fragment with highly similar sequences, showing complete association with the gray coat color. Association analysis in an expanded population further confirmed a strong correlation between this variant and the gray phenotype. Gene expression analyses also supported the role of ASIP in regulating pigmentation in donkeys. ConclusionsThese findings identify a genetic determinant of gray coat color in donkeys and provide new insights into the molecular mechanisms underlying age-related depigmentation in domestic animals.

The aim of this study was to explore the scalp bacterial flora structure and functional characteristics in androgenetic alopecia (AGA) patients, analyze its association with disease phenotypes and unhealthy lifestyles, and provide a basis for clarifying AGAs microecological pathogenic mechanism and targeted interventions. A total of 7 AGA patients and 6 healthy controls (HC) were enrolled, with scalp microbial samples collected. High-throughput sequencing of the 16S rRNA V3-V4 region was used to analyze flora alpha/beta diversity, species composition and differential species. LEfSe and KEGG functional prediction screened marker bacteria and differential pathways, and clinical/lifestyle data were collected for inter-group comparisons. No significant difference in Chao index was observed between groups (P>0.05), but Shannon/Simpson indices/Pielou evenness (P<0.01) and intra-group Bray-Curtis distance (P<0.001) were significantly higher in the AGA group, indicating reduced community stability. Staphylococcus dominated healthy scalps; the AGA group had fewer symbiotic bacteria but enriched Acinetobacter, Pseudomonas, andCutibacterium. LEfSe identified Firmicutes/Staphylococcus as HC markers and Proteobacteria/Gammaproteobacteria/Acinetobacter/Pseudomonas as AGA dysbiotic flora. KEGG showed upregulated metabolic, immune and cell motility pathways in AGA (P<0.05), with only infectious diseases pathway enriched in HC. AGA patients had more frequent hair washing and higher rates of staying up late, high-fat diet and insufficient fruits/vegetables (all P<0.05). In conclusion, AGA patients have typical scalp microecological dysbiosis closely related to unhealthy lifestyles, which may accelerate alopecia by inducing follicular inflammation. Scalp flora can be potential biomarkers and targets for AGA assessment and intervention.

The Agaricomycotina accounts for roughly a third of all described fungi. They are important due to their wide range of lifestyles and economic and environmental relevance. Certain agaricomycetes act as lignocellulose degraders, playing a significant role in forest ecosystems and bioremediation processes. These wood-decaying fungi have historically been classified as mostly white- or brown-rot based on their ability to degrade lignin, with white-rot fungi possessing a collection of lignocellulose-degrading enzymes, which are reduced or absent in brown-rot fungi. Here, we sequenced and annotated the genome of the agaricomycete Crepidotus cesatii CBS 511.95 and explored its genome and predicted enzymatic content in a comparative context. The 36.04 Mbp genome is in 235 scaffolds, with 3.34% repeat content and 12,891 predicted genes. We found that the PFAM distributions of identified orthogroups suggested that C. cesatii shows patterns more similar to white-rot fungi compared to brown-rot fungi. Additionally, C. cesatii contained multiple copies of CAZymes CBM1 and AA9 involved in hydrolysis of lignocellulose, similar to white-rot fungi. On the other hand, according to the Conserved Unique Peptide Patterns (CUPP) data for AA2 peroxidases, the key enzymes in lignin degradation, C. cesatii is more similar to brown-rot fungi. Based on our analyses we predict that C. cesatii is another representation of the continuum of wood decaying modes between white and brown rot fungi combining genetic features of both types of fungi.

Trichoderma species are widely used as biological control agents due to their ability to parasitize plant pathogens. However, substantial variability in mycoparasitic performance exists among strains, even within the same species, and the underlying molecular mechanisms remain poorly understood. Here, we performed comparative genomic and transcriptomic analyses of six Trichoderma atroviride strains exhibiting contrasting mycoparasitic performance (weakly or highly parasitic; WP or HP) against Alternaria brassicicola, Rhizoctonia solani, and Globisporangium ultimum. Comparative genomics revealed limited strain-specific differences, mainly restricted to NLR (NOD-like receptor) repertoires, with certain NLR-coding genes absent from WP strain genomes compared to HP strains, while overall genomic variation remained low. In contrast, transcriptomic analyses revealed strong differences in gene expression dynamics between HP and WP strains. Co-expression network analysis identified two modules associated with mycoparasitic performance. The first was specifically induced in response to pathogen contact and was enriched in genes encoding cell wall-degrading enzymes, with stronger expression in HP strains. The second module was more broadly overexpressed in HP strains across all conditions and included genes involved in detoxification and defense-related pathways. In addition, this module encompassed genes involved in specialized metabolite biosynthesis and effector-like protein secretion, with WP and HP strains differentially expressing distinct gene subsets within these categories. Together, these results provide a comprehensive framework for identifying the molecular drivers of mycoparasitic performance in T. atroviride. This study deepens our understanding of the functional diversity within the species and establishes a robust foundation for the future development of molecular markers to predict strain efficiency.

Environmental and dietary factors can exert multigenerational effects on health and development. In this study, we investigated whether early-life metabolic challenge affects the germline genome and epigenome across three generations. Using a murine model of early life obesity via litter size reduction (overnutrition group, ON) and a control group (CT), we followed the paternal lineage focusing on germline genomic and methylation changes employing Genotyping-by-Sequencing (GBS) coupled with methyl-immunoprecipitation (GBS-MeDIP). We found that unrelated ON families clustered together based on identified Single-Nucleotide Polymorphism (SNP), suggesting that the treatment may have genomic impact. Copy number variations (CNVs) events were identified in ON individuals, being enriched in Long Interspersed Nuclear Elements (LINEs) and Long Terminal Repeats (LTRs). While Principal Component Analysis (PCA) of the methylome showed no clear treatment effect, pathway enrichment and regional analyses revealed methylation changes associated with transposable elements and developmental genes. Notably, the ON group exhibited a disruption in the methylation of Repetitive Elements (RE), which was significant in the same type of RE that were also enriched in the observed CNVs. The ON also showed reduced emergence of novel SNPs in offspring compared to the CT group. These findings suggest that multigenerational metabolic challenge can constrain genetic variability and induce genome instability, potentially mediated by transposable element activity rather than widespread changes in DNA methylation. This work highlights the importance of studying both genome and epigenome dynamics under realistic, multigenerational exposure scenarios and suggests that early metabolic challenges can have long-lasting impacts on genomic architecture and evolutionary potential.

BackgroundWomen are disproportionately affected by multimorbid depression and type 2 diabetes (T2D), with prevalence peaking during midlife (40-64 years), a biologically dynamic timeframe due to changes associated with reproductive aging. Yet, phenotypic and mechanistic factors contributing to midlife womens disproportionate risk for co-occurrence remain poorly defined. We previously identified co-expressed microRNAs (miRs) in midlife women with prediabetes that increased odds of assignment to a high psychometabolic risk phenotype. Here, we extend these findings by characterizing putative mRNA targets of these co-expressed miRs and pathways overrepresented among mRNAs, providing insights into potential mechanisms underlying psychometabolic risk in midlife women. MethodsThis study included baseline data from midlife women (ages 40-64 years) with prediabetes who participated in the Diabetes Prevention Program (DPP) (n = 603). In silico analyses were performed using miRTarBase to identify mRNAs regulated by 3 or more of the miRs that most prominently loaded a principal component previously identified to increase odds of assignment to a high psychometabolic risk phenotype defined in this sample. Pathway enrichment analysis was conducted to assess for overrepresentation of KEGG pathways among predicted mRNA targets. To enhance interpretability, pathways were thematically clustered based on their evidenced role in human physiology. ResultsWe identified a total of 13 mRNAs targeted by co-expressed miRs associated with increased odds of assignment to a high psychometabolic risk phenotype in midlife women with prediabetes. Pathway enrichment analysis revealed a total of 71 KEGG pathways with overrepresentation of identified mRNA targets. Four overarching biological themes emerged, reflecting involvement of metabolic, inflammatory, endocrine, and stress/biological weathering-related processes. ConclusionsExperimentally validated mRNA targets related biological pathways were identified, providing multisystem insights into potential mechanisms underlying risk for multimorbid depression and T2D in midlife women. Findings offer mechanistic targets for experimental validation and future precision health research focused on this high-risk population. Overall, this work positions the utility of miRs as context-sensitive biomarkers in the characterization of risk for complex, multimorbid conditions in women during biologically dynamic timeframes.

Morus rubra is native to the eastern United States, with its range extending into the Upper Midwest and southern Ontario, Canada. Its present distribution suggests that past glacial events in North America may have influenced the genetic structure of populations at the species northwestern range boundary. This study assessed genetic variation among six M. rubra populations believed to have experienced postglacial colonization using published nuclear microsatellite markers and sequences from the chloroplast trnL-trnF region. Five nuclear microsatellite markers previously developed for M. alba were successfully transferred to M. rubra, while the chloroplast trnL-trnF region provided an additional marker for evaluating chlorotype diversity. Nuclear microsatellite diversity was higher in southern unglaciated populations than in northern glaciated populations, a pattern consistent with the observed distribution of chlorotype diversity. Together, these results support ancient founder effects associated with leading-edge expansion following glacial recession and suggest that postglacial colonization contributed to the present-day genetic structure of M. rubra at its northwestern range boundary. Because M. rubra hybridizes with the naturalized invasive M. alba, reduced genetic diversity in marginal populations may increase their vulnerability to genetic swamping. The markers characterized in this study provide useful tools for population genetic research in Morus, and the findings have important implications for the conservation and management of marginal and threatened M. rubra populations in the Upper Midwest.

Avian malaria parasites form a highly prevalent and genetically diverse group within the haemosporidians, yet they have long been overlooked relative to their human- and rodent-infecting counterparts. Among these, parasites of the genus Haemoproteus (Haemosporida, Haemoproteidae) are widespread and prevalent blood parasites of birds, transmitted by louse flies (Hippoboscidae) and biting midges (Ceratopogonidae). Recent phylogenomic analyses place Haemoproteus parasites at the root of the haemosporidian tree, making genomic data from these taxa essential for understanding the evolutionary origins of malaria parasites. To date, only two avian Plasmodium and one avian Haemoproteus genomes have been sequenced. We present the first assembled genome of Haemoproteus majoris (lineage WW2), a common blood parasite of passerine birds. As avian erythrocytes are nucleated, parasite DNA was enriched by FACS-based sorting to discriminate and isolate the parasite from host cell nuclei prior to whole-genome amplification. The genome was assembled using Nanopore long-read sequencing and polished with Illumina short-reads, yielding 145 contigs with a total assembly size of 23.9Mb and a G+C content of 27.85%. Genome annotation identified 5501 protein-coding genes, 69 non-coding RNA genes, and 57 long terminal repeat retrotransposons (LRT-RTs), including one full-length element. This genomic resource represents a critical step towards elucidating the evolutionary history and genomic architecture of avian malaria parasites. SIGNIFICANCE STATEMENTWe present the first assembled genome of Haemoproteus majoris (lineage WW2), a prevalent and generalist avian malaria parasite. Taxonomic resolution of this genus is difficult as there are few distinct morphological differences among closely-related species. This genome provides a valuable resource for studying the evolution within the Haemoproteus genus and to elucidate the evolutionary history of malaria parasites.

Genome-wide association studies (GWAS) are the key tools for the discovery of associations between single nucleotide polymorphisms (SNPs) and phenotypic traits and have been successfully applied to many diseases and disorders. However, a great challenge is to find the gene affected by the non-coding fraction of SNPs, especially if the gene is distal in terms of genomic distance. In this study, we present a novel approach, named targPred, which utilises genomic regulatory blocks (GRBs) for inference of a connection between a certain SNP/locus and the target gene located in the same GRB, in a more robust and generalisable manner. We identified that many disease traits such as cancer and psychiatric disease have a propensity for long-range regulation. Furthermore, we showcased a childhood obesity locus which is connected to the distal BDNF gene. Finally, we propose a new web-based service based on enhancer-promoter association, to facilitate finding the causal genes for a wide array of traits and conditions.

Gene model for the ortholog of Insulin-like peptide 3 (Ilp3) in the D. pseudoobscura Apr. 2013 (BCM-HGSC Dpse_3.0/DpseGB3) Genome Assembly (GenBank Accession: GCA_000001765.2) of Drosophila pseudoobscura. This ortholog was characterized as part of a developing dataset to study the evolution of the Insulin/insulin-like growth factor signaling pathway (IIS) across the genus Drosophila using the Genomics Education Partnership gene annotation protocol for Course-based Undergraduate Research Experiences.

In vitro synchronisation is widely used to study circadian clocks in cells, but whether cultured cells recapitulate tissue-level rhythmic outputs remains unclear. Articular cartilage provides a useful model to address this because chondrocytes are the only resident cell type. Here, we compared circadian time series transcriptomes between primary mouse chondrocytes synchronised by heat shock, dexamethasone, or osmotic stress and in vivo cartilage tissue. All three stimuli robustly synchronised core clock gene rhythms but produced distinct circadian phases and markedly different rhythmic transcriptomes, depending on the synchronizer. Heat shock, dexamethasone, and osmotic stress yielded 5255, 2008, and 879 transcripts classified as rhythmic, respectively, in primary chondrocytes, yet only 64 genes were shared across the three in vitro datasets, and only 15 were shared when in vivo cartilage transcriptome was included. Pairwise comparisons between synchronizers revealed some statistically enriched overlaps, but only marginally above chance, and shared genes showed limited conservation of circadian phase. Functional enrichment analysis also revealed stimulus-dependent rhythmic programmes with modest pathway-level overlap. These findings indicate that circadian output in cultured cells is shaped by the synchronising cue and cellular microenvironment. We also present BodyClocks.org, an interactive resource implementing this comparative framework across a curated collection of circadian transcriptomic datasets.

Melittin, a potent amphipathic cationic peptide derived from bee venom, exhibits broad-spectrum antineoplastic efficacy, notably against cervical carcinoma. Despite its established therapeutic potential, the global transcriptional reprogramming orchestrating its acute multi-pathway cytotoxicity remains incompletely understood. To bridge this knowledge gap, we generated the first comprehensive, untargeted RNA-seq dataset profiling the acute phase of melittin-induced cell death in murine cervical carcinoma U14 cells (exposed to 4 g/mL melittin for 20 minutes) alongside untreated controls. Utilizing deep sequencing and rigorous bioinformatics workflows, we quantified genome-wide mRNA abundances and mapped a distinct transcriptomic shift, identifying 254 significantly differentially expressed genes, comprising 158 up- and 96 down-regulated transcripts. Validated by stringent quality control metrics, exceptional genomic mapping rates, and comprehensive functional annotations via the GO and KEGG databases, this high-resolution transcriptomic resource provides a systems-level map of early molecular alterations. All raw and processed sequencing data are publicly available. This transcriptomic resource provides a valuable foundation for elucidating the acute regulatory networks underlying melittin-induced anti-cervical cancer effects. DatasetThe dataset can be accessed through the NGDC website by searching with the BioProject accession number PRJCA068439. Reviewers may use this link for anonymous access during the review process. Direct URL to data: Genome Sequence Archive-CNCB-NGDC

Gene model for the ortholog of Density regulated protein (DENR) in the Apr. 2013 (BCM-HGSC Dpse_3.0/DpseGB3) Genome Assembly (GenBank Accession: GCA_000001765.2) of Drosophila pseudoobscura. This ortholog was characterized as part of a developing dataset to study the evolution of the Insulin/insulin-like growth factor signaling pathway (IIS) across the genus Drosophila using the Genomics Education Partnership gene annotation protocol for Course-based Undergraduate Research Experiences.

This study aims to quantify the genetic similarity of different species (from fish to humans) to the human reference genome (pp6, Homo sapiens.GRCh38) based on the allele presence/absence patterns of 33 language/cognition related gene SNV loci, identify key breakpoints during evolution, and evaluate the enrichment of language and cognition genes at these breakpoints. We designed a similarity calculation method relying on binary features (four columns for A/T/C/G), adopted five difference/distance measures (Sorensen, Rogers, Nei, Reynolds, and Hellinger), and converted them into similarity values (1/(1+distance)). For each method, samples were independently ranked, the first derivative of similarity was computed, and the top 12 peaks were selected as candidate breakpoints. Results show that the similarity curves from the five methods are highly consistent (correlation coefficients >0.9), with major peaks concentrated at positions 355, 363, 381, 382, 390, 400, etc., where the corresponding samples are predominantly ancient hominins and primates. Furthermore, we defined 13 peak groups (starting positions 355-401). For each peak within a group, pairwise SNV differences between the peak apex sample and its immediate left neighbor were compared, and the intersection F_INTERSECTION (shared differential loci) was obtained. For each F_INTERSECTION, we calculated the proportions of language genes and cognition genes. In addition, we computed the differential sets between adjacent groups' F_INTERSECTION to trace the gradual emergence of new loci. In F_INTERSECTION, language genes accounted for an average of 59.5%, and cognition genes for an average of 62.9%. The proportion of language genes reached a peak at position 383 (61.2%), while cognition genes peaked at position 386 (64.9%). High frequency peak samples include c25, c27, and ja2, suggesting that language cognition genes may have undergone independent intensification during Eurasian evolution. Differential analysis between adjacent F_INTERSECTION revealed a stepwise acquisition of new loci from position 355 to 401, with three bursts of newly added loci along the entire evolutionary axis. This study provides a quantitative framework based on similarity curves, offers a novel molecular perspective for understanding the evolution of language and cognitive abilities, and highlights the potential importance of East Asian archaic hominins in the evolution of language cognition genes.

Preeclampsia (PE) is a hypertensive pregnancy-specific disorder and a leading cause of maternal and fetal mortality. A common feature of PE placentas and maternal plasma is dyslipidemia, or abnormal lipid levels, which can increase oxidative stress and endothelial dysfunction. However, the precise transcriptional, post-transcriptional, and epigenetic mechanisms underlying these abnormalities remain poorly characterized. Identifying such changes may clarify disease mechanisms and identify lipid-related PE biomarkers. We conducted a large-scale meta-analysis integrating public placental datasets from NCBI GEO, comprising four DNA methylation (DNAm) datasets (n = 172), three RNA-sequencing datasets (n = 92), and an independent RNA microarray validation cohort (n =146). We evaluated differential DNAm (limma), gene expression (DESeq2), transcript-level shifts (Swish), and alternative splicing (rMATS) in PE versus control placentas, with all analyses stratified by fetal sex via an interaction term model. We also performed placental cell-type deconvolution to quantify PE-associated cell-type proportion changes. Our results demonstrated that lipid-related regulation changes in PE placentas occur primarily at the gene and transcript level, with DNAm showing no changes. We also identified significant isoform switching in PE that were undetected by differential gene expression analysis, and primarily driven by alternative transcription initiation and termination sites rather than alternative splicing. A subset of these isoform switches mapped to pathways dysregulated in PE and were predicted to cause functional protein changes. An interaction term model identified several sex-specific differentially expressed genes (DEGs) in PE, including a subset of male-specific downregulated genes involved in oxidative metabolism. However, many of the remaining sex-specific DEGs across both sexes were previously uncharacterized in the literature. These findings suggest that transcriptional and isoform-level regulation play a role in PE-associated dyslipidemia, with certain regulatory pathways displaying fetal sex-specific patterns. Highlights- Preeclampsia-associated dyslipidemia manifests at the gene and transcript level - Reciprocal isoform switches were missed by standard gene-level analyses - Alternative transcript initiation and termination drove isoform switching - Sex-interaction modeling identified sex-specific transcriptional shifts in PE

ObjectivesModel species are essential for fundamental research in biology. While a complete genomic sequence is a prerequisite for genetic studies, it is not enough on its own. Understanding the three-dimensional organization of the genome is also important, allowing researchers to gain a more realistic understanding of the mechanisms governing genome function. In the fungal model Podospora anserina, although the genomic sequence has been established for a long time, the three-dimensional organization remained unknown. Here we obtained the first Hi-C datasets and present associated 3D models, providing the research community with a valuable resource for better multi-omics data integration. Data descriptionHi-C experiments were performed in duplicate, using nuclei purified from wild-type fungal mycelium. Four FASTQ files were obtained (two per replicate) and used as inputs for the 3DGB workflow with four different output resolutions, to observe the genome organization of P. anserina at different levels of detail (50 kb, 20 kb, 10 kb, and 5 kb). In a context where researchers already have, for this species, a large amount of traditional omics data (ChIP-seq, RNA-seq, etc.), these 3D models are helpful for complementing the linear representation of the genome, which is traditionally used in bioinformatic analyses.

The Gene Version Iteration Hypothesis (GVIH) proposes that mutant genes may originate from the Y chromosome, traverse through the X chromosome to autosomes, undergo interchromosomal transfer, and potentially return to the Y chromosome via the X chromosome. This hypothetical closed transmission loop may facilitate the storage, screening, and elimination of different versions of mutant genes. The hypothesis comprises five core propositions: (1) Mutation reservoir: The Y chromosome may serve as a specialized carrier for generating mutant genes, characterized by elevated mutation rates, reduced gene density, and accelerated evolutionary dynamics; (2) Closed-loop transmission: Mutant genes may follow a unidirectional pathway Y[-&gt;]X[-&gt;]autosomes[-&gt;]X[-&gt;]Y, forming a complete transmission circuit; (3) Coexistence of multiple versions: A single functional gene may exist in multiple versions across different chromosomes, constituting a dynamic gene version library; (4) Reproductive screening: Environmentally adaptive gene versions may persist across generations and potentially migrate to upstream chromosomes, while maladaptive versions may be eliminated; (5) Terminal elimination: Gene versions reaching the Y chromosome may undergo elimination processes, potentially preventing version monopolization and maintaining evolutionary dynamics. This hypothesis provides a novel framework for understanding adaptive evolution at the genetic level. If empirically validated, it may offer new insights into the molecular mechanisms underlying certain genetic phenomena and evolutionary processes.