Genome-wide Transcriptome Analysis Of Ovaries Between Jining Grey Goat And Laiwu Black Goat Using RNA-Seq

Objectives:RNA-Seq was used to sequence the genes of estrous ovarian tissue in Jining grey goats and Laiwu blackgoat and analyze their function in order to identify the differences of the transcription level of goatovaries. This study mainly focuses on the analysis of the newly discovered genes. After analyzing thegoat specific gene transcription expression in the process of breeding, we have obtained new genes andgenetic variations, both of which are associated with reproductive performance. The discovery can lay afoundation for the study of fecundity difference between Laiwu black goat and Jining grey goat, andprovide the basis for the research of goat fecundity related genes.Methods:1.5ewes of each small Jining grey goat and Laiwu black goat in Qingdao breeding farm in Shandongprovince, which meet the test requirment and were in good health, their estrous state were detectedusing vaginal test and RAMS marker method, they were sacrificed between4and5h after theirspontaneous estrus was determined. Whole ovaries were excised and samples were collected with betterovulation points and were immediately removed in RNAlater protection reagent, for total RNAextraction.2. Total RNA was extracted and purified from ovaries in Jining grey goats and Laiwu black goats.mRNA was enriched and sequencing library was constructed. The library products were ready forsequencing analysis. the high solexa sequencing technology RNA-Seq was employed to sequence thegenes of Jining grey goats as well as Laiwu black goat estrus ovarian tissue and their functions wereanalyzed in order to study the differences of the transcription level of goat ovaries. Specifically, thisstudy focuses on the analysis of the newly discovered genes. After protein and COG functionalannotation, according to the protein database annotation information, the GO functional annotationswere obtained. According to KEGG database, through significant enrichment analysis, the differentiallyexpressed genes involved in the main biochemical metabolic pathways and the signal pathway weredetermine.Results:1. Solexa high-sequencing we got About4g Reads data in each sample of Laiwu black goats and Jininggrey goats were obtained using RNA-Seq. The percentage of GC content is below50%in all data,Cycle Q20value is close to100%, this indicate higher sequencing accuracy, good data quality, meetingthe requirements of the further analysis.2. Insert size is a very important parameter in bioinformatic analysis, Insert size inspection reflects theactual range of cutting segments in rubber cutting. Based on the detection of distribution of the insertsegment sample, each insert segments sample are mainly distributed in the100-150bp, and within therange of the rubber cutting range; The Laiwu black goat sample, insert fragment peak in130or so, and concentrated,which show that sample rubber cutting effect and sequencing effect are very good. Also,the insertion fragment in Jining grey goat is centralized distribution at around130, it further shows thequality of sequencing data is very good, meeting the demand of bioinformatic analysis.3. Statistics of comparied information is the statistics of the whole situation reads in reference genome.To a certain extent, it can reflect the level of sequencing or select reference genome quality, and analysislevel of reliability later. Results showed that the perfect matching segment in two samples is more thanhalf of the number of match segments.Conclusion:1.Through the Solexa sequence, we have obtained about four gigabytes of high quality sequencing data,including9732297Reads of Laiwu black goats,9613952Reads of Jining grey goats; we also havefound the new genes which were not predicted before, of which there are3060genes in Laiwu blackgoats,3348in Jining grey goats.2. Differentially expressed genes were screened and enriched GO and Pathway analysis were conductedon differentially expressed genes between the two samples, goats breed related pathways are:CAMligands, Focal adhesion, Cell antigen, ECM-receptor interaction, Cell adhesion molecules, Purinemetabolism.