| Milk performance traits have been considered as the most important production traits.With the development of balance breeding sense,much attention has been paid to the disease resistant traits,which is put into breeding programs.Identification of major genes or genetic markers for disease resistant and milk production traits and their applications in genomic selection of dairy cattle are expected to improve the genetic progress of these traits and the accuracy of selection.The rapid advancement of omics technologies have provided a more powerful tool for structural genomics and functional genomics in human,animals and plants.In this thesis,we performed two researches using omics technologies.Part I Identifying candidate genes for paratuberculosis resistance in Chinese Holstein We estimated heritability for susceptibility to Mycobacterium avium subspecies paratuberculosis(MAP)infection in Chinese Holstein cows.By genome-wide association study(GWAS),RNA-seq and small RNA-seq,we identified critical genes related to MAP infection in Chinese Holstein cows.Section 1:Heritability estimates for susceptibility to Mycobacterium avium subspecies paratuberculosis infection in Chinese Holstein cows.In this study,we estimated the variance components and heritability of susceptibility to MAP infection for Chinese Holstein cows.We collected 8,214 serum samples of cows from seven dairy herds in the Beijing region of China and used the ELISA for MAP detection.Preliminary analysis of fixed effects including herd and parity was done using SAS.Three statistical models were implemented to estimate heritability in these animals:(1)a linear model(ELISA S/P ratios as a continuous trait),(2)a binary threshold model(ELISA results as a binary trait,positive = 1,negative = 0),and(3)an ordered threshold model(ELISA results as an ordered categorical model).The estimated heritabilities ranged from 0.0543 to 0.1098.Section 2:Genome wide association study of Mycobacterium avium subspecies Paratuberculos infection in Chinese Holstein.Using Illumina Bovine 50k(54,609 SNPs)and GeneSeek HD(138,893 SNPs)chips,two analytical approaches were performed:GRAMMAR-GC and ROADTRIPS in 945 Chinese Holstein cows(185 cases and 760 controls)of which imlividuals genotyped by 50k chip were imputed to HD SNPs with Beagle software.Consequently,14 and 18 significant SNPs surpassing P value of 5×10-5 were identified with GRAMMAR-GC and ROADTDRIPS,respectively.After merging,a total of 30 SNPs located on 13 chromosomes was obtained.Further,8 functional genes that contain or are nearby these SNPs with less than 1 Mb were revealed,including IL5,IRF1,MyD88,PACSIN1,DEF6,TDP2,ZAP70 and SRF.Section 3:Identification of candidate genes related to Mycobacterium avium subspecies Paratuberculos infection in Chinese Holstein using RNA-Seq and small RNA-Seq.Both RNA-seq and small RNA-seq were used to explore the bovine transcriptome from the jejunum tissue of 7 Chinese Holstein cows those were infected with MAP and showed clinical symptom(DP,2),infected with MAP but no symptom(SP,2),and health(NP,3),respectively.Using Cuffdiff software,we identified 275,301,320 differentially expressed genes(q-value<0.05)between the comparison group of DP vs.NP,DP vs.SP and SP vs.NP respectively.We predicted 12 promising candidate genes affecting MAP infection,CDKN2B,CYBA,FCER1G,HHLA2,IDO1,ITF,JUNB,KCNN4,LGALS3M,S100A12,SNX10 and VNN1 We identified 24,30,37 differentially expressed IncRNA(p-value<0.05)between the comparison group of DP vs.NP,DP vs.SP and SP vs.NP respectively.We set 100 kb of lncRNA as threshold and predicted 47,50 and 69 target genes.We predicted 10 promising candidate lncRNAs' target genes affecting MAP infection.Using small RNA-seq,we identified 564 knowe miRNA and 90 novel miRNA.Using DESeq2,44,28 and 85 differentially expressed miRNA(p-value<0.05)were found between the comparison group of DP vs.NP,DP vs.SP and SP vs.NP respectively.We predicted 11949,15137 and 49101 target genes correspondingly using miRanda and predicted 9 promising candidate miRNAs' target genes affecting MAP infection.Integrated analysis of differentially expressed miRNAs,lncRNAs and mRNA.We obtained 277,108 and 1115 ceRNA pairs,including 50,21 and 75 differentially expressed genes respectively.We predicted 20 promsing candidate genes affecting MAP infection and 144 ceRNA pairs.Part II CNV discovery for milk composition traits in dairy cattle using whole genome resequencingIn this study,CNVs were detected based on whole genome re-sequencing data of eight Holstein bulls from four half-and/or full-sib families,with extremely high and low estimated breeding values(EBVs)of milk protein percentage and fat percentage.The range of coverage depth per individual was 8.2-11.9×.Using CNVnator,we identified a total of 14,821 CNVs,including 5025 duplications and 9796 deletions.Among them,487 differential CNV regions(CNVRs)comprising-8.23 Mb of the cattle genome were observed between the high and low groups.Annotation of these differential CNVRs were performed based on the cattle genome reference assembly(UMD3.1)and totally 235 functional genes were found within the CNVRs.By Gene Ontology and KEGG pathway analyses,we found that genes were significantly enriched for specific biological functions related to protein and lipid metabolism,insulin/IGF pathway-protein kinase B signaling cascade,prolactin signaling pathway and AMPK signaling pathways.These genes included INS,IGF2,FOX03,TH,SCD5,GALNT18,GALNT16,ART3,SNCA and WNT7A,implying their potential association with milk protein and fat traits.In addition,95 CNVRs were overlapped with 75 known QTLs that are associated with milk protein and fat traits of dairy cattle(Cattle QTLdb)... |
PDF Full Text Request