Genome‑wide DNA methylation and transcriptome analyses reveal the key gene for wool type variation in sheep

Background Wool fibers are valuable materials for textile industry.Typical wool fibers are divided into medullated and non-medullated types,with the former generated from primary wool follicles and the latter by either primary or secondary wool follicles.The medullated wool is a common wool type in the ancestors of fine wool sheep before breeding.The fine wool sheep have a non-medullated coat.However,the critical period determining the type of wool follicles is the embryonic stage,which limits the phenotypic observation and variant contrast,making both selection and studies of wool type variation fairly difficult.Results During the breeding of a modern fine(MF)wool sheep population with multiple-ovulation and embryo transfer technique,we serendipitously discovered lambs with ancestral-like coarse(ALC)wool.Whole-genome rese-quencing confirmed ALC wool lambs as a variant type from the MF wool population.We mapped the significantly associated methylation locus on chromosome 4 by using whole genome bisulfite sequencing signals,and in turn identified the SOSTDC1 gene as exons hypermethylated in ALC wool lambs compare to their half/full sibling MF wool lambs.Transcriptome sequencing found that SOSTDC1 was expressed dozens of times more in ALC wool lamb skin than that of MF and was at the top of all differentially expressed genes.An analogy with the transcriptome of coarse/fine wool breeds revealed that differentially expressed genes and enriched pathways at postnatal lamb stage in ALC/MF were highly similar to those at the embryonic stage in the former.Further experiments validated that the SOSTDC1 gene was specifically highly expressed in the nucleus of the dermal papilla of primary wool follicles.Conclusion In this study,we conducted genome-wide differential methylation site association analysis on differen-tial wool type trait,and located the only CpG locus that strongly associated with primary wool follicle development.Combined with transcriptome analysis,SOSTDC1 was identified as the only gene at this locus that was specifically overexpressed in the primary wool follicle stem cells of ALC wool lamb skin.The discovery of this key gene and its epigenetic regulation contributes to understanding the domestication and breeding of fine wool sheep.

Effects of pituitary-specific overexpression of FSHα/β on reproductive traits in transgenic boars

Background： Follicle-stimulating hormone（FSH） is a gonadotropin synthesized and secreted by the pituitary gland.FSH stimulates follicle development and maturation in females. It also plays an important role in spermatogenesis in males, including humans and mice. However, the effects of FSH on male pigs are largely unknown. In this study,we generated transgenic pigs to investigate the effects of FSHα/β overexpression on reproductive traits in boars.Results： After five transgenic F0 founders were crossed with wide-type pigs, 193 F_1 animals were obtained. Of these,96 were confirmed as transgenic. FSHα and FSHβ m RNAs were detected only in pituitary tissue. Transgenic boars exhibited significantly higher levels of FSHα and FSHβ m RNA, serum FSH, and serum testosterone, compared to ful-sib non-transgenic boars. Significant increases in testis weight, vas deferens diameter, seminiferous tubule diameter,and the number of Leydig cel s were observed, suggesting that the exogenous FSHα/β affects reproductive traits. Final y,transgenic and non-transgenic boars had similar growth performance and biochemical profiles.Conclusions： Pituitary-specific overexpression of FSHα/β genes is likely to impact reproductive traits positively, as indicated by enhancements in serum testosterone level, testis weight, the development of vas deferens, seminiferous tubules, and Leydig cells in transgenic boars. A high level of serum FSH induces secretion of serum testosterone,possibly by boosting the number of Leydig cells, which presumably increases the libido and the frequency of sexual activity in transgenic boars. Our study provides a preliminary foundation for the genetic improvement of reproductive traits in male pigs.

The effect of SARS-CoV-2 infection on human embryo early development:a multicenter prospective cohort study

Dear Editor,Severe acute respiratory syndrome coronavirus 2(SARSCo V-2)infection has swept the globe for 3 years(Zhou et al.,2020).With the nationwide relaxation of controls on the coronavirus disease 2019(COVID-19)epidemic since December 2022 in China,fertility and in vitro fertilization(IVF)centers are receiving increasing numbers of infected patients.

Microbiome and ileum transcriptome revealed the boosting effects of selenium yeast on egg production in aged laying hens

The declines in laying performance during the late productionperiod have adverse effects on the length of theproduction cycle. Improving the nutrition of laying hens is a crucialmeasure to reverse this declination. Thisstudy investigatedthe effect of seleniumyeast (SY)on egg production, ileal gene expressionandmicrobiota, aswell as elucidating their associations in aged laying hens. A total of 375 Jinghong laying hens at 76weeks oldwere randomly assigned into 5 dietary treatments, which included a selenium-deficient basal diet based oncorn-soybean meal, and dietary supplementation of SY at 0.15, 0.30 and 0.45 mg/kg, and sodium selenite at0.45mg/kg.The results showed that SYamelioratedthe depressionin aged layingperformance inthe 0.30mg/kg group (P < 0.01). Selenium yeast significantly increased ileum selenium concentration (P < 0.05), and SYgroups had higher seleniumdeposition efficiency than the sodiumselenite group. Functional enrichment andShort Time-series Expression Miner (STEM) analysis indicated that SY activated metabolic progress (e.g.,glycerolipidmetabolism, glycerophospholipidmetabolism, andfattyacidmetabolism),immune responseandoxidative stress response. Four hub genes including thioredoxin reductase 1 (TXNRD1), dihydrolipoamidedehydrogenase (DLD), integrin linked kinase (ILK) and leucine zipper tumor suppressor 2 (LZTS2) wereinvolved in intestinal metabolismwhich was closely associated with selenium deposition/status. Moreover,the relative abundance of Veillonella, Turicibacter and Lactobacillus was significantly increased, but the relativeabundance of Stenotrophomonas was significantly decreased by SY supplementation. Multi-omics dataintegration and Canonical correspondence analysis (CCA) showed that both the ileumselenium content andthe laying rate were highly correlated with pathways and bacteria enriched in metabolism and immuneresponse. Meanwhile, the “switched on” gene prostate stem cell antigen (PSCA) had a positive relationshipwith Veillonella and a negative relationship with the opportunistic pathogens Stenotrophomonas. Overall, ourstudy offered insight for the further exploration of the role of SY on boosting egg production and balancingileum intestinal flora in aged laying hens.

A novel black TiO2/ZnO nanocone arrays heterojunction on carbon cloth for highly efficient photoelectrochemical performance

ZnO nanocone arrays(NCAs)decorated with black TiO2 nanoparticles(BTiO2 NPs)were uniformly anchored on the surface of carbon cloth(CC)directly by a simply electrochemical deposition method.Thus a novel B-TiO2 NPs/ZnO NCAs-CC hierarchical heterostructure was formed.It displayed superior performance and achieved a higher photocurrent over 0.4 mA·cm^-2 before the onset of the dark current,attributed to the separation of the photogenerated electron-hole pair.Based on the B-TiO2 NPs/ZnO NCAs-CC heterostructure,the catalyst was fabricated for promoting the separation of charge carriers.Moreover,the introduction of Ti^3+ and oxygen vacancies on the surface of TiO2 NPs expanded the absorption band edge and enhanced the electrical conductivity as well as the charge transportation on the catalytic surface.It indicates that the B-TiO2 NPs/ZnO NCAs-CC composite is beneficial to the improvement of the photoelectrochemical(PEC)activity.

Artificial intelligence system for outcome evaluations of human in vitro fertilization-derived embryos

Background:In vitro fertilization(IVF)has emerged as a transformative solution for infertility.However,achieving favorable live-birth outcomes remains challenging.Current clinical IVF practices in IVF involve the collection of heterogeneous embryo data through diverse methods,including static images and temporal videos.However,traditional embryo selection methods,primarily reliant on visual inspection of morphology,exhibit variability and are contingent on the experience of practitioners.Therefore,an automated system that can evaluate heterogeneous embryo data to predict the final outcomes of live births is highly desirable.Methods:We employed artificial intelligence(AI)for embryo morphological grading,blastocyst embryo selection,aneuploidy prediction,and final live-birth outcome prediction.We developed and validated the AI models using multitask learning for embryo morphological assessment,including pronucleus type on day 1 and the number of blastomeres,asymmetry,and fragmentation of blastomeres on day 3,using 19,201 embryo photographs from 8271 patients.A neural network was trained on embryo and clinical metadata to identify good-quality embryos for implantation on day 3 or day 5,and predict live-birth outcomes.Additionally,a 3D convolutional neural network was trained on 418 time-lapse videos of preimplantation genetic testing(PGT)-based ploidy outcomes for the prediction of aneuploidy and consequent live-birth outcomes.Results:These two approaches enabled us to automatically assess the implantation potential.By combining embryo and maternal metrics in an ensemble AI model,we evaluated live-birth outcomes in a prospective cohort that achieved higher accuracy than experienced embryologists(46.1%vs.30.7%on day 3,55.0%vs.40.7%on day 5).Our results demonstrate the potential for AI-based selection of embryos based on characteristics beyond the observational abilities of human clinicians(area under the curve:0.769,95%confidence interval:0.709-0.820).These findings could potentially provide a noninvasive,high-throughput,and low-cost screening tool to facilitate embryo selection and achieve better outcomes.Conclusions:Our study underscores the AI model’s ability to provide interpretable evidence for clinicians in assisted reproduction,highlighting its potential as a noninvasive,efficient,and cost-effective tool for improved embryo selection and enhanced IVF outcomes.The convergence of cutting-edge technology and reproductive medicine has opened new avenues for addressing infertility challenges and optimizing IVF success rates.