Cow Mastitis QTL And Microarray Datasets Mining And Genome Wide Association Analysis

Mastitis is one of the most common and complex diseases affecting dairy industry.As a kind of mammary gland inflammation,mastitis affect by genetic,environmental,pathogens and many other factors,however,the mechanism of mastitis in dairy cows is not clear.As the development of the statistic genomics,chip technology and high-throughput sequencing technologies,it make us study mastitis resistance mechanism from the genome and expression level possible.At the genome level,though studies have been carried out and large numbers of quantitative trait loci?quantitative trait loci,QTL?have been found,but the results can't be well applied to breeding practice because the QTL is too big,so it is necessary to dig deep for QTL.At the expressing level,quite a few researchers have use gene chip to study cow mastitis,but repeatability is not high and each study results have some differences,so we preprocessing microarray data in the same method and implement enrichment of gene analysis,then integrate the results of the analysis.So this study from two aspect of genome and expressing to mining related set of candidate genes,then using real phenotypic and sequencing data to verified the result gene set,details and results are described below:Genome level mining mastitis related set of candidate genes:first,we collected 76 cow mastitis QTLs from QTL database,by comparing the database,we found 1336 genes within QTL,then these genes were analyzed from the GO,KEGG,IPA three aspects,42,182,91 genes were found associated with mastitis respectively,after redundancy a total of 248 genes were identified.There was one common gene in three analysis results that is FABP4 gene,7 common gene in GO and KEGG analysis results that is LIAS,HPSE,COQ3,ENPP3,ENPP1,APOA1 and IDO1 gene,2 common gene in GO and IPA analysis results that is BMPR1B and FAM103A1,20 common gene in KEGG and IPA analysis results that is gene PPT1,GCNT1,ST3GAL1,ATP6V1F,ATP6V1H,FUT9,FUT4,ATP6V1B1,ATP6V1B2,ATP6V1C1,ST3GAL3,ATP6V0B,PTS,DGKD,AASS,MTHFD1L,LAP3,SCD5,MYC and UCHL1.Expression level mining mastitis related set of candidate:we searched NCBI GEO?Gene Expression Omnibus?database and selected five recently published commercial Affymetrix microarray datasets,GSE24560,GSE24217,GSE32186,GSE25413 and GSE15025 which were all about cow mastitis.Then applied gene set enrichment analysis,and up-regulated and down-regulated pathways were identified.There were 15,30,17 common up-regulated pathways in 1,6,24 h result respectively.Five common pathways in all result,including Chemokine signaling pathway,Toll-like receptor signaling pathway,Chagas disease?American trypanosomiasis?,Toxoplasmosis and MAPK signaling pathway.Mastitis candidate gene set verification:we first use GGRS sequencing platform for 278cows simplified genome sequencing,a total of 108936 SNPs were found.Then using GWAS ssGWAS method,found that 716 significant SNPs(threshold is 0.05/108936=4.59*10^-7),which is0.66%of all the SNPs.Among 108936 SNPs there were 497 SNPs within the 248 genes which were identified by GO,KEGG and IPA analysis,and among 497 SNPs there were 48 SNPs significant,and 9.66%of all SNPs within gene set.Chi-square test was carried on two significant SNPs ratio,result showed that they were significant differences,this shows that the accuracy of cow mastitis gene sets that we found is high.