Research Progress on Genomic Regions and Candidate Genes Related to Milk Composition Traits of Dairy Goats Based on Functional Genomics: A Narrative Review.

BACKGROUND: Goat milk has gained global attention for its unique nutritional properties and potential health benefits. Advancements in functional genomic technologies have significantly progressed genetic research on milk composition traits in dairy goats. RESULTS: This review summarizes various research methodologies applied in this field. Genome-wide association studies (GWAS) have identified genomic regions associated with major milk components, with the diacylglycerol acyltransferase 1 (DGAT1) gene and casein gene cluster consistently linked to milk composition traits. Transcriptomics has revealed gene expression patterns in mammary tissue across lactation stages, while the role of non-coding RNAs (such as miRNAs and circRNAs) in regulating milk composition has been confirmed. Proteomic and metabolomic studies have not only helped us gain a more comprehensive understanding of goat milk composition characteristics but have also provided crucial support for the functional validation of genes related to milk components. The integration of multi-omics data has emerged as an effective strategy for elucidating complex regulatory networks from a systems biology perspective. CONCLUSIONS: Despite progress, challenges remain, including refining reference genomes, collecting large-scale phenotypic data, and conducting functional validations. Future research should focus on improving reference genomes, expanding study populations, investigating functional milk components, exploring epigenetic regulation and non-coding RNAs, and studying microbiome-host genome interactions. These efforts will inform more precise genomic and marker-assisted selection strategies, advancing genetic improvements in milk composition traits in dairy goats.

Development of a Routine Serological Test Index Panel for the Surveillance of Gastric Cancer Risk in a High-Risk Population.

OBJECTIVE: This study aims to develop a predictive model for the detection of gastric cancer risk utilizing non-invasive parameters and to assess the model's effectiveness in risk stratification for gastric cancer (GC). METHODS: A case-control study was conducted among inpatients with various gastric diseases. These individuals were categorized into two groups: the gastric cancer group (138 cases) and the chronic non-atrophic gastritis (CNAG) group (319 cases). We employed a comprehensive panel of hematological, biochemical, and coagulation parameters derived from routine blood tests. Random Forest and Logistic regression analysis was used for feature selection and model building. Statistical analyses were performed using R version 4.2.3. RESULTS: Logistic regression analysis was employed to establish risk prediction models for GC, incorporating variables such as D-dimer, carcinoembryonic antigen (CEA), carbohydrate antigen 724 (CA724), and hemoglobin (HGB). A visual nomogram was generated as the final prediction model. The area under the receiver operating characteristic curve (AUC) for the training and test sets were 0.8093 [95% confidence interval (CI), 0.7541-0.8644], and 0.8076 [95% CI 0.7237-0.8915], respectively. Furthermore, we have developed an HTML file, featuring the Logistic equation, which enables real-time assessment of GC risk scores. CONCLUSION: The performance of this predictive model demonstrates its adequacy, making it a valuable and cost-effective noninvasive tool for identifying early gastric cancer (EGC) in patients. Consequently, this model may facilitate the implementation of targeted preventive and intervention strategies in clinical practice.

Marker Density and Models to Improve the Accuracy of Genomic Selection for Growth and Slaughter Traits in Meat Rabbits.

The selection and breeding of good meat rabbit breeds are fundamental to their industrial development, and genomic selection (GS) can employ genomic information to make up for the shortcomings of traditional phenotype-based breeding methods. For the practical implementation of GS in meat rabbit breeding, it is necessary to assess different marker densities and GS models. Here, we obtained low-coverage whole-genome sequencing (lcWGS) data from 1515 meat rabbits (including parent herd and half-sibling offspring). The specific objectives were (1) to derive a baseline for heritability estimates and genomic predictions based on randomly selected marker densities and (2) to assess the accuracy of genomic predictions for single- and multiple-trait linear mixed models. We found that a marker density of 50 K can be used as a baseline for heritability estimation and genomic prediction. For GS, the multi-trait genomic best linear unbiased prediction (GBLUP) model results in more accurate predictions for virtually all traits compared to the single-trait model, with improvements greater than 15% for all of them, which may be attributed to the use of information on genetically related traits. In addition, we discovered a positive correlation between the performance of the multi-trait GBLUP and the genetic correlation between the traits. We anticipate that this approach will provide solutions for GS, as well as optimize breeding programs, in meat rabbits.

Staphylococcus aureus promotes its intracellular survival by inhibiting Rab11-Rab11FIP4-mediated vesicle trafficking.

Mastitis in dairy cows is mainly caused by bacteria, in which Staphylococcus aureus appears frequently. Epithelial cells, as a major physical barrier of mammary gland, play an important role in preventing mastitis in dairy cows. Our previous study reported that Rab11fip4 (an effector of Rab11) was significantly changed in response to stimulation by S. aureus. So, in this study, the role of Rab11A in phagocytosis of bovine mammary epithelial cells (MAC-T) against S. aureus was evaluated. First, changes of Rab11A and Rab11fip4 were analyzed in response to S. aureus by immunofluorescence and western blotting. Subsequently, the effects of Rab11A and Rab11fip4 on proliferation of S. aureus, as well as formation and function of late endosomes (LEs) and lysosomes (LYSs) were investigated. The results showed that, after infection, Rab11A and Rab11fip4 were recruited to phagosomes containing S. aureus. Rab11A promoted bacterial clearance and rescues the destruction of LEs and LYSs by S. aureus, whereas Rab11fip4 did the opposite. These findings provide new insights into phagocytosis and control of S. aureus in host cells, thus lay the foundation to elucidate the pathogenesis of S. aureus in bovine mastitis.

Exploring blood metabolites and thyroid disorders: a bidirectional mendelian randomization study.

Background: Human blood metabolites have demonstrated close associations with thyroid disorders in observational studies. However, it's essential to determine whether these correlations imply causation. Mendelian Randomization (MR) offers a promising approach to investigate these patterns. Aims: The primary aim of our investigation is to establish causality between blood metabolites and three thyroid disorders: TC, GD, and HT. Methods: We employed a two-sample bidirectional MR analysis approach to assess the relationships between 452 blood metabolites and the three aforementioned thyroid disorders. Causal links were estimated using the IVW method, with sensitivity analyses conducted via MR-Egger, Weighted Median, and MR-PRESSO. We assessed potential heterogeneity and pleiotropy using MR-Egger intercept and Cochran's Q statistic. Additionally, we conducted pathway analysis to identify potential metabolic pathways. Results: We found 46 metabolites that showed suggestive associations with thyroid disease risk, especially Aspartate (ORIVW=7.41; 95%CI: 1.51-36.27; PIVW=0.013) and C-glycosyltryptophan (ORIVW=0.04; 95%CI: 0.00-0.29; PIVW=0.001) impacted TC, Kynurenine (ORIVW=2.69; 95%CI: 1.08-6.66; PIVW=0.032) and 4-androsten-3beta,17beta-diol disulfate 2 (ORIVW=0.78; 95%CI: 0.48-0.91; PIVW=0.024) significantly impacted GD, and Alpha-ketoglutarate (ORIVW=46.89; 95%CI: 4.65-473.28; PIVW=0.001) and X-14189-leucylalanine (ORIVW=0.31; 95%CI: 0.15-0.64 PIVW=0.001) significantly impacted HT. We also detected 23 metabolites influenced by TC and GD. Multiple metabolic pathways have been found to be involved in thyroid disease. Conclusion: Our MR findings suggest that the identified metabolites and pathways can serve as biomarkers for clinical thyroid disorder screening and prevention, while also providing new insights for future mechanistic exploration and drug target selection.

Type I Interferon Pathway-Related Hub Genes as a Potential Therapeutic Target for SARS-CoV-2 Omicron Variant-Induced Symptoms.

BACKGROUND: The global pandemic of COVID-19 is caused by the rapidly evolving severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The clinical presentation of SARS-CoV-2 Omicron variant infection varies from asymptomatic to severe disease with diverse symptoms. However, the underlying mechanisms responsible for these symptoms remain incompletely understood. METHODS: Transcriptome datasets from peripheral blood mononuclear cells (PBMCs) of COVID-19 patients infected with the Omicron variant and healthy volunteers were obtained from public databases. A comprehensive bioinformatics analysis was performed to identify hub genes associated with the Omicron variant. Hub genes were validated using quantitative RT-qPCR and clinical data. DSigDB database predicted potential therapeutic agents. RESULTS: Seven hub genes (IFI44, IFI44L, MX1, OAS3, USP18, IFI27, and ISG15) were potential biomarkers for Omicron infection's symptomatic diagnosis and treatment. Type I interferon-related hub genes regulated Omicron-induced symptoms, which is supported by independent datasets and RT-qPCR validation. Immune cell analysis showed elevated monocytes and reduced lymphocytes in COVID-19 patients, which is consistent with retrospective clinical data. Additionally, ten potential therapeutic agents were screened for COVID-19 treatment, targeting the hub genes. CONCLUSIONS: This study provides insights into the mechanisms underlying type I interferon-related pathways in the development and recovery of COVID-19 symptoms during Omicron infection. Seven hub genes were identified as promising biological biomarkers for diagnosing and treating Omicron infection. The identified biomarkers and potential therapeutic agent offer valuable implications for Omicron's clinical manifestations and treatment strategies.

Nonstructural protein 2A2 from Duck hepatitis A virus type 1 inhibits interferon beta production by interaction with mitochondrial antiviral signaling protein and TANK-binding kinase 1.

Type I interferon (IFN-I) is essential for the regulation of host-virus interactions, and viruses have evolved strategies to escape the host immune response. Duck hepatitis A virus type 1 (DHAV-1) causes severe liver necrosis and hemorrhage, neurological symptoms, and high mortality in ducklings. However, how DHAV-1 interacts with the duck innate immune system remains unclear. In this study, DHAV-1-encoded proteins were cloned, and DHAV-1 2A2 was shown to strongly suppress IFN-ß-luciferase activity, triggered by Sendai virus and polyriboinosinic polyribocytidylic acid [poly(I:C)], along with the transcription of IFN-ß and downstream antiviral genes, including OASL, PKR, and TNF-a. In addition, 2A2 interacts with the central adaptor proteins mitochondrial antiviral signaling (MAVS) and TANK-binding kinase 1 (TBK1) by its N-terminal 1-100 amino acids (aa), thus leading to the inhibition of IFN-ß production. Importantly, the deletion of the N-terminal 1-100 aa region of 2A2 abolished inhibition of IFN-I production. Moreover, the transmembrane domain of the MAVS protein and the ubiquitin domain of TBK1 were demonstrated to be required for interaction with DHAV-1 2A2. These findings revealed a novel strategy by which DHAV-1 hijacks cellular immunosurveillance and provided new insights into controlling the disease.

Cost-effectively dissecting the genetic architecture of complex wool traits in rabbits by low-coverage sequencing.

BACKGROUND: Rabbit wool traits are important in fiber production and for model organism research on hair growth, but their genetic architecture remains obscure. In this study, we focused on wool characteristics in Angora rabbits, a breed well-known for the quality of its wool. Considering the cost to generate population-scale sequence data and the biased detection of variants using chip data, developing an effective genotyping strategy using low-coverage whole-genome sequencing (LCS) data is necessary to conduct genetic analyses. RESULTS: Different genotype imputation strategies (BaseVar + STITCH, Bcftools + Beagle4, and GATK + Beagle5), sequencing coverages (0.1X, 0.5X, 1.0X, 1.5X, and 2.0X), and sample sizes (100, 200, 300, 400, 500, and 600) were compared. Our results showed that using BaseVar + STITCH at a sequencing depth of 1.0X with a sample size larger than 300 resulted in the highest genotyping accuracy, with a genotype concordance higher than 98.8% and genotype accuracy higher than 0.97. We performed multivariate genome-wide association studies (GWAS), followed by conditional GWAS and estimation of the confidence intervals of quantitative trait loci (QTL) to investigate the genetic architecture of wool traits. Six QTL were detected, which explained 0.4 to 7.5% of the phenotypic variation. Gene-level mapping identified the fibroblast growth factor 10 (FGF10) gene as associated with fiber growth and diameter, which agrees with previous results from functional data analyses on the FGF gene family in other species, and is relevant for wool rabbit breeding. CONCLUSIONS: We suggest that LCS followed by imputation can be a cost-effective alternative to array and high-depth sequencing for assessing common variants. GWAS combined with LCS can identify new QTL and candidate genes that are associated with quantitative traits. This study provides a cost-effective and powerful method for investigating the genetic architecture of complex traits, which will be useful for genomic breeding applications.

Marker density and statistical model designs to increase accuracy of genomic selection for wool traits in Angora rabbits.

The Angora rabbit, a well-known breed for fiber production, has been undergoing traditional breeding programs relying mainly on phenotypes. Genomic selection (GS) uses genomic information and promises to accelerate genetic gain. Practically, to implement GS in Angora rabbit breeding, it is necessary to evaluate different marker densities and GS models to develop suitable strategies for an optimized breeding pipeline. Considering a lack in microarray, low-coverage sequencing combined with genotype imputation was used to boost the number of SNPs across the rabbit genome. Here, in a population of 629 Angora rabbits, a total of 18,577,154 high-quality SNPs were imputed (imputation accuracy above 98%) based on low-coverage sequencing of 3.84X genomic coverage, and wool traits and body weight were measured at 70, 140 and 210 days of age. From the original markers, 0.5K, 1K, 3K, 5K, 10K, 50K, 100K, 500K, 1M and 2M were randomly selected and evaluated, resulting in 50K markers as the baseline for the heritability estimation and genomic prediction. Comparing to the GS performance of single-trait models, the prediction accuracy of nearly all traits could be improved by multi-trait models, which might because multiple-trait models used information from genetically correlated traits. Furthermore, we observed high significant negative correlation between the increased prediction accuracy from single-trait to multiple-trait models and estimated heritability. The results indicated that low-heritability traits could borrow more information from correlated traits and hence achieve higher prediction accuracy. The research first reported heritability estimation in rabbits by using genome-wide markers, and provided 50K as an optimal marker density for further microarray design, genetic evaluation and genomic selection in Angora rabbits. We expect that the work could provide strategies for GS in early selection, and optimize breeding programs in rabbits.

Advanced glycation endproducts mediate chronic kidney injury with characteristic patterns in different stages.

Advanced glycation endproducts (AGEs) have been confirmed to play a causative role in the development of diabetic nephropathy (DN). In this study, we revealed that AGE-induced kidney injury with characteristic patterns in different stages and moesin phosphorylation plays a role in these processes. In WT mice treated with AGE-modified bovine serum albumin (AGE-BSA), distinct abnormal angiogenesis in Bowman's capsule of the kidney emerged early after 1 m under AGE-BSA stimulation, while these neovessels became rare after 6 m. AGE-BSA also induced glomerular hypertrophy and mesangial expansion at 1 m but glomerular atrophy and fibrosis at 6 m. Electron microscopy imaging demonstrated the damage of foot process integrity in podocytes and the uneven thickening of the glomerular basement membrane in the AGE-BSA-treated group, which was more significant after 6 m of AGE-BSA treatment than 1 m. The kidney dysfunction appeared along with these AGE-induced morphological changes. However, these AGE-BSA-induced pathological changes were significantly attenuated in RAGE-knockout mice. Moreover, moesin phosphorylation was accompanied by AGE-BSA-induced alterations and moesin deficiency in mice attenuated by AGE-BSA-induced fibrosis. The investigation on glomerular endothelial cells (GECs) also confirmed that the phosphorylation of moesin T558 is critical in AGE-induced tube formation. Overall, this study suggests that AGEs mediate kidney injury with characteristic patterns by binding with RAGE and inducing moesin phosphorylation.

Role of moesin and its phosphorylation in VE-cadherin expression and distribution in endothelial adherens junctions.

BACKGROUND AND AIM: Vascular endothelial cadherin (VE-cadherin) is an important element of adherens junctions (AJs) between endothelial cells. Its expression and proper distribution are critical for AJ formation and vascular integrity. Our previous studies have demonstrated that moesin phosphorylation mediated the hyper-permeability in endothelial monolayer and microvessels. However, the role of moesin and its phosphorylation in VE-cadherin expression and distribution is not clear. METHODS AND RESULTS: In vivo, expression of VE-cadherin was significantly reduced in retina and other various tissues in moesin knock out mice (Msn-/Y). In vitro, by regulating moesin expression with siRNA and adenovirus transfection, we verified that moesin has an effect on VE-cadherin expression in HUVECs, while transcription factor KLF4 may participate in this process. In addition, treatment of advanced glycation end products (AGEs) induced abnormal distribution of VE-cadherin in retinal microvessels from C57BL/6 wild type mice, and in vitro studies indicated that moesin Thr558 phosphorylation had a critical role in AGE-induced VE-cadherin internalization from cytomembrane to cytoplasm. Further investigation demonstrated that the inhibition of F-actin polymerization with cytochalasin D could abolish AGE- and Thr558 phosphor-moesin-mediated VE-cadherin internalization. CONCLUSION: This study suggests that moesin regulates VE-cadherin expression through KLF4 and the state of moesin phosphorylation at Thr558 affects the integrity of VE-cadherin-based AJs. Thr558 phosphor-moesin mediates AGE-induced VE-cadherin internalization through cytoskeleton reassembling.

Effects of Artemisinin on Escherichia coli-Induced Mastitis in Bovine Mammary Epithelial Cells and Mice.

Bovine mastitis is an important disease affecting dairy farming, and it causes large economic losses to the dairy industry. Escherichia coli (E. coli) is considered to be a causative environmental pathogen and frequently enters into mammary glands, causing inflammation. Artemisinin is a highly effective malaria remedy and is not easy to develop drug resistance to. In recent years, other effects of artemisinin (including antitumor, anti-inflammatory, antifungal, etc.) have been increasingly discovered and applied. The current study aimed to investigate whether artemisinin could attenuate E. coli-induced inflammation. Through the E. coli mastitis model in MAC-T cells and mice, the protective effects of artemisinin were analyzed by CCK-8 (Cell Counting Kit-8), Western blot, and RT-qPCR. The results showed that artemisinin reversed the decrease of cell viability and upregulated TLR4 (toll-like receptor 4)/NF-κB (nuclear factor κB) and MAPK (mitogen activated protein kinase)/p38 signaling pathways, as well as restrained the expression of TNF-α, IL-6, and IL-1ß mRNA caused by E. coli. Meanwhile, artemisinin also alleviated mammary tissue damage, reduced inflammatory cells' infiltration, and decreased the levels of inflammatory factors in a mice mastitis model. This study demonstrated that artemisinin alleviated the inflammatory response of mouse mastitis and MAC-T cells induced by E. coli, thus providing a practical approach for the clinical control of mastitis.

Long Noncoding RNA Expression Rofiles Elucidate the Potential Roles of lncRNA- XR_003496198 in Duck Hepatitis A Virus Type 1 Infection.

Duck hepatitis A virus type 1 (DHAV-1) is a highly lethal virus that severely affects the duck industry worldwide. Long noncoding RNAs (lncRNAs) exert crucial roles in pathogen attacks. Here, we conducted deep transcriptome analysis to investigate the dynamic changes of host lncRNAs profiles in DHAV-1-infected duck embryo fibroblasts. We identified 16,589 lncRNAs in total and characterized their genomic features. Moreover, 772 and 616 differentially expressed lncRNAs (DELs) were screened at 12 and 24 h post-infection. Additionally, we predicted the DELs' cis- and trans-target genes and constructed lncRNA-target genes regulatory networks. Functional annotation analyses indicated that the putative target genes of DELs participated in diverse vital biological processed, including immune responses, cellular metabolism, and autophagy. For example, we confirmed the dysregulation of pattern recognition receptors (TLR3, RIG-I, MDA5, LGP2, cGAS), signal transducers (STAT1), transcription factors (IRF7), immune response mediators (IL6, IL10, TRIM25, TRIM35, TRIM60, IFITM1, IFITM3, IFITM5), and autophagy-related genes (ULK1, ULK2, EIF4EBP2) using RT-qPCR. Finally, we confirmed that one DHAV-1 induced lncRNA-XR_003496198 is likely to inhibit DHAV-1 replication in DEFs. Our study comprehensively analyzed the lncRNA profiles upon DHAV-1 infection and screened the target genes involved in the innate immune response and autophagy signaling pathway, thereby revealing the essential roles of duck lncRNAs and broadening our understanding of host-virus interactions.

Characterization of microRNA Profiles in Pasteurella multocida-Infected Rabbits and Identification of miR-29-5p as a Regulator of Antibacterial Immune Response.

Pasteurella multocida is the pathogenic agent for a variety of severe diseases in livestock, including rabbits. MicroRNAs (miRNAs) participate in the immune response to the pathogen. Distinct miRNA expression patterns were explored in rabbit lung by small-RNA deep sequencing to assess dysregulated miRNAs during P. multocida infection. Totally, 571 miRNAs were screened, of which, 62 were novel, and 32 exhibited differential expression (DE). Of the 32 known DE-miRNAs, 13 and 15 occurred at 1 day and 3 days post-infection (dpi); and ocu-miR-107-3p and ocu-miR-29b-5p were shared between the two time points. Moreover, 7,345 non-redundant target genes were predicted for the 32 DE-miRNAs. Putative target genes were enriched in diverse GO and KEGG pathways and might be crucial for disease resistance. Interestingly, upregulation of ocu-miR-29-5p suppresses P. multocida propagation and downregulates expression of epithelial membrane protein-2 (EMP2) and T-box 4 (TBX4) genes by binding to their 3' untranslated region in RK13 cells. Thus, ocu-miR-29-5p may indirectly inhibit P. multocida invasion by modulating genes related to the host immune response, such as EMP2 and TBX4.

The Profiles of Long Non-coding RNA and mRNA Transcriptome Reveals the Genes and Pathway Potentially Involved in Pasteurella multocida Infection of New Zealand Rabbits.

Infection with Pasteurella multocida (P. multocida) causes severe epidemic diseases in rabbits and is responsible for the pronounced economic losses in the livestock industry. Long non-coding RNAs (lncRNAs) have been proven to exert vital functions in regulating the host immune responses to bacterial attacks. However, little is known about how lncRNAs participate in the rabbit's immune response against P. multocida infection in the lungs. LncRNA and mRNA expression profiles were analyzed by transcriptomics and bioinformatics during P. multocida infection. A total of 336 lncRNAs and 7,014 mRNAs were differentially regulated at 1 day and 3 days post infection (dpi). Nearly 80% of the differentially expressed lncRNAs exhibited an increased expression at 3 dpi suggesting that the P. multocida genes are responsible for regulation. Moreover, GO and KEGG enriched analysis indicated that the immune-related pathways including pattern recognition receptors (PRRs), cytokines, and chemokines were significantly enriched at 3 dpi. These results indicate that the dysregulated immune-related genes may play crucial roles in defending against P. multocida attacks. Overall, these results advance our cognition of the role of lncRNAs and mRNAs in modulating the rabbit's innate immune response against P. multocida attacks, which will offer a valuable clue for further studies into exploring P. multocida-related diseases in human.

Integrated miRNA and mRNA Expression Profiles Reveal Differentially Expressed miR-222a as an Antiviral Factor Against Duck Hepatitis A Virus Type 1 Infection.

Duck hepatitis A virus 1 (DHAV-1) is a highly contagious etiological agent that causes acute hepatitis in young ducklings. MicroRNAs (miRNAs) play important regulatory roles in response to pathogens. However, the interplay between DHAV-1 infection and miRNAs remains ambiguous. We characterized and compared miRNA and mRNA expression profiles in duck embryo fibroblasts cells (DEFs) infected with DHAV-1. In total, 36 and 96 differentially expressed (DE) miRNAs, and 4110 and 2595 DE mRNAs, were identified at 12 and 24 h after infection. In particular, 126 and 275 miRNA-mRNA pairs with a negative correlation were chosen to construct an interaction network. Subsequently, we identified the functional annotation of DE mRNAs and target genes of DE miRNAs enriched in diverse Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, which may be important for virus resistance, cell proliferation, and metabolism. Moreover, upregulated miR-222a could negatively regulate DHAV-1 replication in DEFs and downregulate integrin subunit beta 3 (ITGB3) expression by targeting the 3' untranslated region (3'UTR), indicating that miR-222a may modulate DHAV-1 replication via interaction with ITGB3. In conclusion, the results reveal changes of mRNAs and miRNAs during DHAV-1 infection and suggest miR-222a as an antiviral factor against DHAV-1.

Role of Moesin Phosphorylation in Retinal Pericyte Migration and Detachment Induced by Advanced Glycation Endproducts.

Proliferative diabetic retinopathy (PDR) involves persistent, uncontrolled formation of premature blood vessels with reduced number of pericytes. Our previous work showed that advanced glycation endproducts (AGEs) induced angiogenesis in human umbilical vein endothelial cells, mouse retina, and aortic ring, which was associated with moesin phosphorylation. Here we investigated whether moesin phosphorylation may contribute to pericyte detachment and the development of PDR. Primary retinal microvascular pericytes (RMPs) were isolated, purified from weanling rats, and identified by cellular markers α-SMA, PDGFR-ß, NG2, and desmin using immunofluorescence microscopy. Effects of AGE-BSA on proliferation and migration of RMPs were examined using CCK-8, wound healing, and transwell assays. Effects on moesin phosphorylation were examined using western blotting. The RMP response to AGE-BSA was also examined when cells expressed the non-phosphorylatable Thr558Ala mutant or phospho-mimicking Thr558Asp mutant of moesin or were treated with ROCK inhibitor Y27632. Colocalization and interaction between CD44, phospho-moesin, and F-actin were observed. Experiments with cultured primary RMPs showed that AGE-BSA inhibited the proliferation, enhanced the migration, and increased moesin phosphorylation in a dose- and time-dependent manner. AGE-BSA also triggered the rearrangement of F-actin and promoted the interaction of CD44 with phospho-moesin in RMPs. These effects were abrogated in cells expressing the non-phosphorylatable moesin mutant and the application of ROCK inhibitor Y27632 attenuated AGE-induced alteration in cultured RMPs by abolishing the phosphorylation of moesin. However, those AGE-induced pathological process occurred in RMPs expressed the phospho-mimicking moesin without AGE-BSA treatment. It is concluded that AGEs could activate ROCK to mediate moesin phosphorylation at Thr558, and resulting phospho-moesin interacts with CD44 to form CD44 cluster, which might stimulate the migration of RMPs and subsequent RMP detachment in microvessel. This pathway may provide new drug targets against immature neovessel formation in PDR.