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Zhang, Z.

Publications and source records attributed to Zhang, Z..

At least 397 records · Page 22Linked to original sources
bioRxiv2025

Melatonin enhances peanut productivity by enriching root-associated nitrogen fixing bacteria

Melatonin, a pleiotropic phytohormone, is widely recognized as a promising bio-stimulant, yet its integrative effects on root development, yield gain, and microbiome assembly in legumes remain underexplored. In this study, we investigated the effects of melatonin seed treatment across three peanut genotypes, focusing on plant productivity, and the composition and structure of bacterial communities in root, rhizosphere, and bulk soil compartments. Melatonin treatment substantially improved root biomass, nodulation, nitrogen balance index, and yield-related traits, with the highest response observed in the genotype Kainong 308. Amplicon sequencing revealed that melatonin induced distinct genotype and compartment specific shifts in bacterial community composition, with the root bacteria showing the increased remodeling, including a 45.9% increase in unique amplicon sequence variants (ASVs). Melatonin selectively enriched key Proteobacteria taxa such as Rhizobium, Sphingomonas, and Enterobacter hormaechei, known for their plant-growth promoting and biocontrol capabilities. Co-occurrence network analysis indicated that melatonin-treated roots harbored more complex bacterial networks, and module #4 dominated by melatonin-induced Proteobacteria was strongly correlated with most of the plant traits. Collectively these findings highlight melatonin dual role as a bio-stimulant and microbiome modulator, promoting a functionally enriched and responsive bacteria that supports enhanced plant performance. This study provides novel insights into the melatonin-mediated coordination of plant performance and bacterial assembly, offering a foundation for microbiome-informed crop improvement strategies.

plant biology↗
bioRxiv2025

Nuclear polysaccharides maintain H3K9me3-heterochromatin and genomic stability

Polysaccharides are known to be synthesized by enzymes in the endoplasmic reticulum and Golgi apparatus and transported through the secretory pathway to the cell surface or extracellular space1, where they mediate essential biological processes2-6. While classical localization and functions of polysaccharides are well established, their presence and potential roles in the nucleus remain unclear. Here, we demonstrate that N-glycans, a type of polysaccharides, are present in the cell nucleus and modify inner nuclear membrane (INM) proteins across diverse cell types--a modification referred to as N-linked glycosylation (N-glycosylation). N-glycosylation is enriched in chromatin regions marked by H3K9me3 and long interspersed nuclear element-1 (LINE-1) retrotransposons. N-glycosylation inhibition and INM protein N-glycosylation site mutation both downregulate H3K9me3 within lamina-associated domains (LADs) and lead to genomic instability. Mechanistically, N-glycosylation regulates the interaction between the histone H3K9 methyltransferase SETDB1 and INM proteins, promotes the association of SETDB1 with the INM, and maintains H3K9me3. Moreover, we reveal that canonical N-glycan biosynthetic machinery in ER contributes to the N-glycosylation of INM proteins. These findings uncover a previously unrecognized nuclear role for polysaccharides, broadening our understanding beyond their traditional subcellular distributions and functional profiles.

molecular biology↗
bioRxiv2025

A complete and near-perfect rhesus macaque reference genome: lessons from subtelomeric repeats and sequencing bias

A truly complete, telomere-to-telomere (T2T), and error-free reference genome remains a foundational resource--and long-standing goal--for unbiased comparative and functional genomics. While recent T2T assemblies of humans and other primates have made substantial progress, most still contain thousands of base-level errors, particularly within highly repetitive regions. Here, we present T2T-MMU8v2.0, a near-perfect T2T assembly of the rhesus macaque (Macaca mulatta), representing the highest base-level accuracy reported in a primate genome to date. By employing an optimized ONT-only assembly strategy, we identify subtelomeric satellite-rich regions as the principal bottleneck to improving assembly quality, owing to technological biases in long-read platforms and limitations in current hybrid assembly frameworks. We discover 268 previously unannotated repeat families and resolve [~]8 Mbp of SATR satellite arrays, with over 99-fold enrichment in historically misassembled subtelomeric regions. These satellites form four distinct genomic architectures, each with unique SATR satellite composition, segmental duplication organization, and epigenetic signatures, distinct from the subtelomeric architectures observed in hominid genomes. Notably, in contrast to the largely gene-poor subtelomeric regions in African hominids, the SATR architectures in macaques harbor 58 actively transcribed genes, supported by open chromatin and expression data, suggesting gene innovation within these repetitive regions. Functionally, T2T-MMU8v2.0 improves read mappability and accuracy across sequencing platforms, and results in a 19% improvement of transcription start site enrichment scores and 5,821 additional chromatin accessibility peaks on average, thereby enhancing variant detection, regulatory annotation, and transcriptomic resolution in population genetics or single-nucleus studies. Together, this work establishes a new benchmark for genomics, offers a roadmap for resolving complex repetitive regions, and reveals previously unrecognized features of subtelomeric genome structure and evolution.

genomics↗
bioRxiv2025

Scaling down protein language modeling with MSA Pairformer

Recent efforts in protein language modeling have focused on scaling single-sequence models and their training data, requiring vast compute resources that limit accessibility. Although models that use multiple sequence alignments (MSA), such as MSA Transformer, offer parameter-efficient alternatives by extracting evolutionary information directly from homologous sequences rather than storing it in parameters, they generally underperform compared to single-sequence-based language due to memory inefficiencies that limit the number of sequences and averaging evolutionary signals across the MSA. We address these challenges with MSA Pairformer, a 111M parameter memory-efficient MSA-based protein language model that extracts evolutionary signals most relevant to a query sequence through bi-directional updates of sequence and pairwise representations. MSA Pairformer achieves state-of-the-art performance in unsupervised contact prediction, outperforming ESM2-15B by 6% points while using two orders of magnitude fewer parameters. In predicting contacts at protein-protein interfaces, MSA Pair-former substantially outperforms all methods with a 24% point increase over MSA Transformer. Unlike single-sequence models that deteriorate in variant effect prediction as they scale, MSA Pairformer maintains strong performance in both tasks. Ablation studies reveal triangle operations remove indirect correlations, and unlike MSA Transformer, MSA Pairformer does not hallucinate contacts after removing covariance, enabling reliable screening of interacting sequence pairs. Overall, our work presents an alternative to the current scaling paradigm in protein language modeling, enabling efficient adaptation to rapidly expanding sequence databases and opening new directions for biological discovery.

biophysics↗
bioRxiv2025

Deficiency of Mesencephalic Astrocyte-derived Neurotrophic Factor Aggravates Acute Pancreatitis in Mice

Acute pancreatitis (AP) is a complex and potentially severe inflammatory disorder of the pancreas and is one of the most common causes of gastrointestinal hospitalization. Although environmental risk factors such as alcohol and gallstones are well recognized, only a subset of exposed individuals develop AP, suggesting that intrinsic factors, including genetic susceptibility, influence disease onset and progression. Endoplasmic reticulum (ER) stress has emerged as a key mechanism in AP pathogenesis, because ER is essential for protein synthesis, folding, degradation and secretion (proteostasis). Mesencephalic astrocyte-derived neurotrophic factor (MANF), an ER stress-inducible protein highly expressed in the pancreas, plays a critical role in maintaining proteostasis, yet its involvement in AP remains unclear. To investigate the functional role of MANF in AP, we generated pancreas-specific MANF knockout (MANF-KO) mice using the Cre/loxP system and subjected them to moderate experimental AP, that is caerulein- or alcohol-induced AP in mice. In the caerulein model, MANF deficiency exacerbated pancreatic injury in both sexes, as indicated by increased apoptosis (cleaved caspase-3, caspase-12), ER stress markers (eIF2, p-eIF2, GRP78), inflammation (IL-6, TNF), regenerative activity (Ki67), and pancreatic lipase levels. Notably, male MANF-KO mice exhibited enhanced inflammation (HMGB1), macrophage infiltration (CD68), and oxidative stress (DNP, HNE), which were not observed in females. In the alcoholic AP model, both male and female MANF-KO mice showed increased ER stress (p-IRE1, p-eIF2, GRP78), apoptosis, inflammation, macrophage infiltration, regeneration, and lipase levels, whereas elevated HMGB1 expression and oxidative stress again predominantly occurred in male MANF-KO mice. Together, these findings reveal a critical and sex-specific role for MANF in regulating pancreatic stress responses and inflammatory injury, supporting its potential contribution as a genetic factor in AP pathogenesis.

pathology↗
bioRxiv2025

Cost-effective genomic prediction for fertility traits: A comparison of machine learning and conventional models using low-coverage sequencing in Holstein heifers

Fertility is one of the major factors affecting the efficiency of dairy herd, and genomic selection (GS) on milk yield, while ignoring fertility, has resulted in a decline in heifer fertility. Consider the cost of breeding, it is important to enhance the accuracy of GS with cost-effective way for fertility traits. This study investigates the genomic prediction (GP) of fertility traits in Holstein heifers using both machine learning (ML) and conventional methods, based on data from SNP arrays and low-coverage sequencing data. In this study, we collected 45,320 Holstein heifers with phenotype and pedigree records, from which we generated genomic data for 3,683 Holstein heifers using lcGWS. We first estimated the heritability for age at first service (AFS), gestation length (GLh) and age at first calving (AFC). We then compared the prediction performance of ML methods, kernel ridge regression (KRR), support vector regression, and random forest regression, with GBLUP, ssGBLUP and BayesR3 regarding GP accuracy and unbiasedness. Inputs for ML includes genomic relationship matrices (GRM), principal components, and SNPs. The results revealed that the heritability for the three fertility traits ranged from 0.09 to 0.48. Prediction accuracy from imputed low-coverage sequencing data was comparable to that from standard SNP chips. When both pedigree and genotypic data were used for GS, ssGBLUP yielded the highest prediction accuracy for AFS and GLh. Crucially, using only genomic data, KRR_GRM improved GP accuracy by up to 28.57% compared to GBLUP and by up to 9.46% compared to BayesR3. Our results highlight the effectiveness of low-coverage sequencing data in breeding applications and the MLs potential to enhance GP accuracy for fertility traits, offering practical insights for dairy breeding programs. ImplicationsTo improve the accuracy of GS with cost-effective way for fertility traits, this study confirms that low-coverage sequencing offers both accuracy and cost-effectiveness for fertility in Holstein heifers. The research provides a decision-making framework for breeding workers: the ssGBLUP model is optimal when combining pedigree data, while machine learning methods are superior with only genomic data. This study offers a practical tool for achieving efficient and economical genetic improvement in dairy cattle.

genomics↗
bioRxiv2025

Age-Related Alterations in the Expression of Mesencephalic Astrocyte-derived Neurotrophic Factor in the Brain and Their Impact on Neurobehavioral Functions

Mesencephalic astrocyte-derived neurotrophic factor (MANF) is a neurotrophic protein localized in the endoplasmic reticulum (ER) and pivotally involved in maintaining ER homeostasis. MANF plays an important role in mitigating neurodegenerative processes. Aging, the primary risk factor for neurodegenerative diseases (NDDs), is associated with significant alterations in ER function. The ER, central to protein synthesis, folding, degradation and secretion (proteostasis), experiences considerable stress in NDDs, which activates the unfolded protein response (UPR). We hypothesized that MANF and UPR is crucial for maintaining proteostasis during aging, but their efficacy declines with age, therefore increasing vulnerability to NDDs. We measured MANF levels in the brain and plasma of 1-, 4-, 11-, and 22-month-old male and female mice. A progressive decline of MANF levels was observed, with the lowest levels detected in 22 months. Reduced MANF expression was found in aged mice across several brain areas, including the cerebral cortex, olfactory bulb, thalamus, hypothalamus, hippocampus, and cerebellum. There was a sex difference in MANF levels in aged mice. Aging also altered the expression of UPR and MANF interacting proteins. Using cerebellar Purkinje cell (PC)-specific MANF deficient mice, we showed that MANF deficiency impaired motor coordination in female, but not male mice. MANF deficiency weakened spatial learning and memory in both male and female mice. Male MANF deficient mice displayed increased sociability, whereas female mice exhibit social withdrawal. Taken together, MANF expression in the brain declined with age and MANF deficiency impacted neurobehaviors in the aging animal in a sex-specific manner.

neuroscience↗
bioRxiv2025

Endothelial cell-specific DNA methylation alterations identified in breast cancer with epigenetic deconvolution

DNA methylation alterations are epigenetic modifications that regulate gene expression and contribute to carcinogenesis. Technical challenges and high costs limit the use of single-cell sequencing approaches to measure and understand cell-specific DNA methylation alterations in the tumor microenvironment (TME). Using cell type deconvolution (HiTIMED) and an interaction testing framework (CellDMC), we identified DNA methylation alterations in tumor endothelial cells (TECs) from measures in bulk biospecimens. Alterations in TECs contribute to abnormal angiogenesis, resulting in disorganized, leaky blood vessels that can hinder drug delivery and immune access. We hypothesize that TECs in the TME exhibit distinct DNA methylation patterns compared to normal endothelial cells, driving phenotypic changes that support tumor growth and vascular dysfunction. We used genome-scale DNA methylation data and a testing and validation set design (tumor, n=1,080; nontumor, n=415) to identify TEC-specific DNA methylation alterations in breast cancer. Between cohorts, we validated 4,562 TEC-specific CpGs (4,163 hypermethylated and 399 hypomethylated), and found that many map to genes regulating angiogenesis and endothelial function. Integration with mRNA data from tumor samples in both discovery and validation sets revealed genes whose expression correlates with TEC-specific DNA methylation patterns and endothelial cell proportions, highlighting potentially novel therapeutic targets. This study demonstrates the utility of cellular deconvolution to uncover cell lineage-specific epigenetic changes in cancer using bulk specimen, and identifies TEC-specific methylation alterations as novel potential targets for therapeutic intervention.

cancer biology↗
bioRxiv2025

An AI-based and coding-free protocol for forests Leaf Area Index (LAI) calculation

O_LISeasonal and spatial variations in leaf area index (LAI) are challenging to detect in tropical forests due to dynamic lighting conditions and the subtle differences in the variation. Many existing LAI software tools offer one-click processing of all images through auto-threshold segmentation (e.g., HemispheR, HemiPy and Hemisfer), but they produce results with large discrepancies. Some software (e.g. CAN-EYE) requires manual tuning of each image, making large-scale analysis impractical. C_LIO_LIWe analysed 19,000 images from four tropical forest subtypes and found that using coding-free AI software to process hemispherical images can significantly improve the consistency of leaf-sky segmentation, thereby enhancing LAI outcomes. C_LIO_LIThe results show that replacing the auto-threshold with AI substantially reduced inter-software disagreement and delineated correct seasonal and spatial patterns. CAN-EYE was able to identify seasonal patterns but produced less accurate results than the CAN-EYE-AI integrated approach due to subjective user bias. C_LIO_LIThe high consistency achieved through AI integration enables reliable cross-site and cross-operator comparisons. As users can customise the AI model according to local images and combine the AI model with other LAI software, our integrated, affordable, and coding-free method offers wide applicability and high consistency of LAI measurements, facilitating the advancement of tropical forest monitoring and research. C_LI Data/Code for peer review statementOne of the key features of this method is coding-free. The method is explained in Protocolv20251118.docx. We have uploaded R codes for drawing figures in a zip pack. These codes and the protocol will be deposited in the Zenodo (or figshare) database under accession link [TBC]. Since Zenodo allows authors to archive updated versions after publication, we may update the protocol by uploading a revised version to Zenodo. Please check the Zenodo archive for any new versions. In the protocol, we note that users can use Image_conversion_20220407.m and lets_change_values.R instead of the Renormalise function of ilastik to modify values in the classification output images. These codes are not essential for users following our protocol, but could be useful for integrating ilastik with other LAI software not covered in this paper. Additionally, the protocol mentions that Gather_LAI_fapar_from_caneye.R can be used to consolidate output Excel files, eliminating the need to manually open each file. Field measurements of LAI and GCC are available on request.

ecology↗
bioRxiv2025

FlyTomo: A streamlined software for on-the-fly cryo-ET data processing and diagnosis

Cryo-electron tomography (Cryo-ET) combined with subtomogram averaging (STA) enables the structural elucidation of macromolecular assemblies in their native environments. However, the widespread adoption of cryo-ET has been limited by its labor-intensive, expertise-dependent data processing workflow. Here we present FlyTomo, a software that streamlines data processing from frame alignment to STA with high-throughput for authentic cryo-ET scenarios. During data acquisition, FlyTomo performs real-time diagnosis, enabling prompt feedback on sample quality, microscope performance and structural features. After acquisition, it aggregates diagnostic metrics into an interactive overview, guiding users through data review and refinement. FlyTomo also curates raw and processed data into structured directories to simplify data management and archiving. We validated FlyTomo across a diverse set of authentic cryo-ET samples, including purified enveloped viruses and cryo-lamellae, on multiple microscopes and cameras, achieving structures at resolutions ranging from 3.4 to 5.7 [A]. Collectively, by integrating accuracy, scalability and usability, FlyTomo reduces the technical barrier for in situ structural biology using cryo-ET.

biophysics↗
bioRxiv2025

Genomic Regions and Variant Analysis Reveal Candidate Genes Associated with Age at First Service in Chinese Holstein Heifers

Understanding the genetic basis and identifying quantitative trait loci (QTL) for age at first service (AFS) is essential for improving reproductive efficiency and reducing economic costs in heifers rearing. We conducted a genome-wide association study (GWAS) for AFS using the genomic estimated breeding values (GEBVs) of 3,686 Chinese Holstein heifers, genotyped with 7,964,217 single nucleotide polymorphisms (SNPs) after quality control. Significant SNPs and candidate genes were identified and investigated through colocalization analysis of GWAS, expression QTL (eQTL), and splicing QTL (sQTL), and expression analysis in blood RNA sequencing (RNA-seq). The heritability estimate for AFS was moderate at 0.276 {+/-}0.025. Three QTL regions associated with AFS were identified: Region 1 on BTA6 (43688837-45007127 bp, 1.3 Mb with three 200kb windows), explaining 0.47% of genetic variance; Region 2 on BTA6 (62770788-62967316 bp) explaining 0.27% of the genetic variance; and Region 3 on BTA18 (6299721-6498934 bp) explaining 0.17% of the genetic variance. Combining GWAS and colocalization analysis, we identified ANAPC4, RBPJ, SEPSECS, SLC34A2, ZCCHC4, CCDC149, GNPDA2, GUF1, DHX15, SOD3, GUF1 and GNPDA2 as candidate genes. These genes are enriched in signaling pathways such as progesterone-mediated oocyte maturation, parathyroid hormone synthesis, secretion and action, and selenocompound metabolism. ANAPC4, DHX15, GUF1, SEPSECS, and SOD3 were also differently expressed genes (DEGs) in blood RNA-seq. Integrating the GWAS, colocalization, differential expression analysis, and existing literature, ANAPC4 and rs136363104 were highlighted as the putative causal gene and variant for puberty, respectively. In conclusion, our study identified three candidate regions and 12 candidate genes, confirming ANAPC4 as a putative causal gene influencing AFS. This research enhances the understanding of the genetic basis of AFS in Chinese Holstein heifers. The identified key genomic regions, candidate genes, and variants have the potential to improve reproductive efficiency and reduce economic costs in heifer rearing. Interpretative summaryThe economic burden of heifer-raising and reproductive inefficiency in dairy cattle is evident. The most important strategy for optimizing heifer-raising is selecting heifers with earlier puberty (sexual maturity) to shorten age at first service (AFS). In this study, we have identified key genomic regions and candidate genes on AFS in Chinese Holstein heifers by genome-wide association study, and validated them by colocalization and RNA-seq analysis. The findings have the potential to enhance the understanding of the genetic basis of reproductive traits, leading to more targeted breeding strategies for improved reproductive efficiency.

genetics↗
bioRxiv2025

bacNeo: a computational toolkit for bacteria-derived neoantigen identification

Intratumour microbiome can restore anti-tumour immunity with bacterial peptides potentially serving as neoantigens, while robust in-silico tools for bacterial neoantigen identification remain lacking. We developed bacterial neoantigen (bacNeo), a multi-omics based computational toolkit that contains three modules to classify bacterial taxonomy, identify host HLA alleles, and predict bacterial neoantigens. bacNeo could enable personalised neoantigen discovery to advance therapeutic strategies across diverse cancer types.

bioinformatics↗
bioRxiv2025

A high-quality bread wheat genome unravels adaptive evolution of wheat end-use quality

Understanding the genetics of superior dough performance is essential for improving wheat end-use quality. Here, we presented a de novo assembly of the genome of JM44, a Chinese wheat cultivar known for its exceptional end-use quality. The JM44 genome achieved reference-level quality (QV = 66.74), depicting a complete picture of complex regions containing gluten genes. Our microsynteny analysis across the Triticum-Aegilops complex showed that high-molecular-weight glutenin subunits (HMW-GSs) loci are highly conserved, while low-molecular-weight glutenin subunits (LMW-GSs) and -/{beta}-gliadins exhibited greater structural variation. These variable loci appear to have been preferentially selected by humans and contributed substantially to the evolution of wheat quality traits. Moreover, we observed that epistatic interactions between gluten genes are strong in modern cultivars, but markedly weaker in landraces, indicating the importance of epistatic selection during modern breeding. Our findings shed light on the genomics and evolution of wheat quality traits, providing valuable guidance for future breeding efforts.

genomics↗
bioRxiv2025

Human ribosome interactions reframe neomycin toxicity

Aminoglycosides such as neomycin are clinically limited by toxicity, commonly attributed to the inhibition of mitoribosomes. Here, we re-evaluate this mechanism by integrating Cryo-EM and functional assays to assess neomycins binding potential in vitro with its cellular engagement and functional consequences. Cryo-EM revealed extensive multi-site binding of neomycin on both human mitochondrial and cytosolic ribosomes in vitro, including conserved regions of the decoding center. In contrast, ribosomes isolated from neomycin-treated cells show markedly remodeled occupancy patterns, with no detectable neomycin bound to the mitoribosomes and reduced occupancy at a subset of cytosolic ribosome sites. However, neomycin remained functionally active in cells, inducing widespread stop-codon readthrough while having minimal effects on global mitochondrial and cytosolic protein synthesis. These findings reveal a disconnect between structural binding potential and cellular target engagement and identify disruption of translational fidelity, rather than global translational inhibition, as a major cellular consequence of neomycin exposure.

biochemistry↗
bioRxiv2025

Genomics of eye number evolution in spiders

Spiders exhibit tremendous variations in eye numbers, but the genomic basis underlying this diversity remains largely unexplored. Here, we analyzed the genomic data of 148 spider species in 31 families, representing all phenotypes of eye numbers including 8, 6, 4, 2, and 0. Our analyses revealed that a core set of 29 genes involved in eye development and phototransduction is conserved across all spiders, irrespective of their eye number, indicating that eye reduction is not caused by the loss of key developmental genes. We found that evolutionary transitions leading to reduced numbers of eyes are primarily associated with parallel genome-wide relaxed selection. While these independent reduction events shared several genes under consistent selective pressures, they did not share any genes under positive selection, indicating putatively divergent molecular mechanisms. In contrast, the evolution of complete eye loss in cave-dwelling spiders is associated with parallel genome-wide intensified selection. Notably, we identified shared genes under both intensified and positive selection across independent origins of eyelessness, suggesting a parallel molecular mechanism. Altogether, our study provides genomic insights into the parallel evolution of eye reduction and complete eye loss in spiders.

evolutionary biology↗
bioRxiv2025

Overcoming breeding constraints in polyploid oat from evolutionary insights

Polyploidy provides adaptive advantages in plants by buffering deleterious mutations1,2. While polyploidization can enhance agronomic traits such as increased biomass, known as the gigas effect1-4, increasing genetic gain in polyploid crops remains a critical but difficult goal due to the difficulty in dissecting complex trait inheritance5,6. Here we present chromosome-scale genome assemblies for 26 Avena taxa, spanning diploid, tetraploid, and hexaploid lineages. We traced four independent polyploidization events across the genus, including the formation of A. agadiriana as an allotetraploid (AgAgAg'Ag'), and revealed a reticulate evolutionary history shaped by gene flow involving four subgenomes (A, B, C, D), for example, the hybrid speciation of A. hirtula. Transcriptomic analysis of 286 samples across 11 tissues, combined with deleterious mutation analysis from a cultivated population of 112 accessions, showed that polyploidization led to widespread functional redundancy among homoeologs, supporting a genome-wide buffering effect. However, derived allele frequency analysis revealed that, while disrupting functional genes may yield desirable traits, the buffering effect impedes the fixation of beneficial loss-of-function mutations and thereby limits breeding efficiency. Based on these integrative analyses, we propose breeding strategies to circumvent these limitations by targeting beneficial loss-of-function alleles within the complex polyploid background of oat. Our study highlights broader challenges in the improvement of polyploid crops and provides a foundation for future breeding strategies.

evolutionary biology↗
bioRxiv2025

Two Spag6 genes control sperm formation and male fertility in mice

Sperm-associated antigen 6 (SPAG6) is the mammalian orthologue of Chlamydomonas PF16, a central axonemal protein essential for flagellar motility. In mice, two homologous genes have been identified: the ancestral Spag6 on chromosome 2 and the evolutionary derived Spag6l on chromosome 16. Although Spag6 knockout mice (Spag6-/-) are phenotypically normal, the surviving Spag6l-/- males are infertile. To further investigate the roles of SPAG6 and SPAG6L, we generated compound mutants by crossing the two knockout lines. Compound heterozygous Spag6+/-; Spag6l+/- mice are fertile, while all Spag6-/-; Spag6l+/- males are infertile despite grossly normal appearance. Histological and ultrastructural analyses revealed defective spermiogenesis, including abnormal chromatin condensation, malformed acrosome and manchette, and disorganized mitochondrial and fibrous sheath. Both SPAG6 and SPAG6L bind to SPINK2, a key regulator of acrosome function, but SPAG6 has an approximately 10-fold higher binding affinity than SPAG6L. Moreover, SPAG6 modulates testicular AKAP4 and SPAG16L levels, which are critical components of the fibrous sheath and central apparatus respectively. Notably, SPAG6 suppresses tubulin acetylation, whereas SPAG6L enhances this post-translational modification, suggesting antagonistic roles in microtubule assembly. Overall, our findings demonstrate that SPAG6 and SPAG6L coordinately regulate sperm formation and male fertility during evolution.

developmental biology↗