Background Mastitis caused by multiple factors remains one of the most common and costly disease of the dairy industry.Multi-omics approaches enable the comprehensive investigation of the complex interactions between ...Background Mastitis caused by multiple factors remains one of the most common and costly disease of the dairy industry.Multi-omics approaches enable the comprehensive investigation of the complex interactions between mul-tiple layers of information to provide a more holistic view of disease pathogenesis.Therefore,this study investigated the genomic and epigenomic signatures and the possible regulatory mechanisms underlying subclinical mastitis by integrating RNA sequencing data(mRNA and lncRNA),small RNA sequencing data(miRNA)and DNA methylation sequencing data of milk somatic cells from 10 healthy cows and 20 cows with naturally occurring subclinical mastitis caused by Staphylococcus aureus or Staphylococcus chromogenes.Results Functional investigation of the data sets through gene set analysis uncovered 3458 biological process GO terms and 170 KEGG pathways with altered activities during subclinical mastitis,provided further insights into subclin-ical mastitis and revealed the involvement of multi-omics signatures in the altered immune responses and impaired mammary gland productivity during subclinical mastitis.The abundant genomic and epigenomic signatures with sig-nificant alterations related to subclinical mastitis were observed,including 30,846,2552,1276 and 57 differential methylation haplotype blocks(dMHBs),differentially expressed genes(DEGs),lncRNAs(DELs)and miRNAs(DEMs),respectively.Next,5 factors presenting the principal variation of differential multi-omics signatures were identified.The important roles of Factor 1(DEG,DEM and DEL)and Factor 2(dMHB and DEM),in the regulation of immune defense and impaired mammary gland functions during subclinical mastitis were revealed.Each of the omics within Factors 1 and 2 explained about 20%of the source of variation in subclinical mastitis.Also,networks of impor-tant functional gene sets with the involvement of multi-omics signatures were demonstrated,which contributed to a comprehensive view of the possible regulatory mechanisms underlying subclinical mastiti展开更多
This paper investigates the numerical solution of two-dimensional nonlinear stochastic Itô-Volterra integral equations based on block pulse functions. The nonlinear stochastic integral equation is transformed...This paper investigates the numerical solution of two-dimensional nonlinear stochastic Itô-Volterra integral equations based on block pulse functions. The nonlinear stochastic integral equation is transformed into a set of algebraic equations by operational matrix of block pulse functions. Then, we give error analysis and prove that the rate of convergence of this method is efficient. Lastly, a numerical example is given to confirm the method.展开更多
基金The help and support of owners of the dairy farms enrolled in this study is gratefully acknowledged.The financial support from the program of China Scholarship Council during the PhD study of Mengqi Wang in Canada is acknowledged(No.202008880009).
文摘Background Mastitis caused by multiple factors remains one of the most common and costly disease of the dairy industry.Multi-omics approaches enable the comprehensive investigation of the complex interactions between mul-tiple layers of information to provide a more holistic view of disease pathogenesis.Therefore,this study investigated the genomic and epigenomic signatures and the possible regulatory mechanisms underlying subclinical mastitis by integrating RNA sequencing data(mRNA and lncRNA),small RNA sequencing data(miRNA)and DNA methylation sequencing data of milk somatic cells from 10 healthy cows and 20 cows with naturally occurring subclinical mastitis caused by Staphylococcus aureus or Staphylococcus chromogenes.Results Functional investigation of the data sets through gene set analysis uncovered 3458 biological process GO terms and 170 KEGG pathways with altered activities during subclinical mastitis,provided further insights into subclin-ical mastitis and revealed the involvement of multi-omics signatures in the altered immune responses and impaired mammary gland productivity during subclinical mastitis.The abundant genomic and epigenomic signatures with sig-nificant alterations related to subclinical mastitis were observed,including 30,846,2552,1276 and 57 differential methylation haplotype blocks(dMHBs),differentially expressed genes(DEGs),lncRNAs(DELs)and miRNAs(DEMs),respectively.Next,5 factors presenting the principal variation of differential multi-omics signatures were identified.The important roles of Factor 1(DEG,DEM and DEL)and Factor 2(dMHB and DEM),in the regulation of immune defense and impaired mammary gland functions during subclinical mastitis were revealed.Each of the omics within Factors 1 and 2 explained about 20%of the source of variation in subclinical mastitis.Also,networks of impor-tant functional gene sets with the involvement of multi-omics signatures were demonstrated,which contributed to a comprehensive view of the possible regulatory mechanisms underlying subclinical mastiti
基金NSF Grants 11471105 of China, NSF Grants 2016CFB526 of Hubei Province, Innovation Team of the Educational Department of Hubei Province T201412, and Innovation Items of Hubei Normal University 2018032 and 2018105
文摘This paper investigates the numerical solution of two-dimensional nonlinear stochastic Itô-Volterra integral equations based on block pulse functions. The nonlinear stochastic integral equation is transformed into a set of algebraic equations by operational matrix of block pulse functions. Then, we give error analysis and prove that the rate of convergence of this method is efficient. Lastly, a numerical example is given to confirm the method.
