Construction And Application Of Ruminant Genome Database

Elucidating the function of various sequences in the genome is the main goal of post-genomics era.In the field of animal genetic breeding,identification of causal genes and causal variations that lead to phenotypic differences is of great guiding significance for the analysis of animal genetic mechanisms and gene editing breeding.Previous animal QTL and GWAS studies could only be located in a broader range.If we can use various information that combines multiple omics data,such as comparative genomics,selective signals,gene expression,regulatory regions,and the most comprehensive genome variations of wild and domestic animals,it will be very helpful to narrow the candidate variations to a very small region,or even candidate loci.Ruminants have attracted much attention due to their morphological characteristics,ecological diversity and breeding value.Recently,the ruminant genome project has assembled 47 ruminant genomes,and with the advance of sequencing technologies,a large amount of genomic,transcriptomics and epigenomic data have been accumulated,which provides an opportunity for us to identify potential functional sites of phenotypic differences between and within ruminant species.Using the published ruminant genomes and abundant omics data from cattle and goats,and using the methods of comparative genomics,population genetics,and pan-genome,this study integrates,analyzes and visualizes these resources to develop a ruminant genome database analysis platform on a LAMP?Linux+Apache+My SQL+PHP?environment.The platform provides comprehensive resources for biologists and breeders to study ruminant evolution,identify functional conservative sites,analyze trait-related candidate genes,and find breeding targets of cattle and goats.The main results are as follows:1.We constructed the first comprehensive ruminant genome database?RGD,http://animal.nwsuaf.edu.cn/RGD?,including genome-wide alignments of 55 ruminants and12 outgroup species,orthologous genes and their annotation of GO and KEGG pathway,conservation scores for the five evolutionary scales,gene expression for 1,232transcriptomics data,regulatory signals,and QTL.RGD also introduces genome browser,BLAT and lift Over tools provided by UCSC Genome Browser and the BLAST tool provided by NCBI.RGD provides search module,download module and data visualization interfaces of gene expression,regulation,synteny and QTL.2.We also developed a comprehensive genome variation and selective signatures database for cattle?BGVD,http://animal.nwsuaf.edu.cn/Bos Var?,one representative livestock in ruminants.BGVD contains information on genomic variations comprising?60.44 M SNPs,?6.86 M indels,76,634 CNV regions and signatures of selective sweeps for eight groups?European taurine,Eurasian taurine,East Asian taurine,Chinese indicine,and Indian indicine?using six methods,Pi,H_p,i HS,F_ST,XP-EHH,and XP-CLR.The database provides the frequency distribution patterns of each variation in 54 cattle breeds worldwide or in six?core?cattle groups,and users can search a genomic region in three versions of the bovine genome?ARS-UCD1.2,UMD3.1.1,and Btau 5.0.1?.Signals of selection are displayed as Manhattan plots and this section support viewing the selective regions.A series of examples,such as a height-related gene?PLAG1,rs109815800?,a curly coat-related gene?KRT27,rs384881761?,a coat color-related gene?KIT?,and a malaria and hemolytic anemia-related gene?STOM?,are used to show the application of SNPs,indels,CNV and selective signals in the identification of functional sites.3.We also constructed a pan-genome and its database for goat?GOATPAN,http://animal.nwsuaf.edu.cn/pangoat?,which is the representative livestock of small ruminants.By comparing nine de novo assemblies from seven sibling species of domestic goat with ARS1 and using goat resequencing data for verification and correction,we identified a total of 38.3 Mb sequences that were absent in ARS1,containing partial coding regions of 1,206 genes.These absent sequences include some key genes,such as LOC101114579,PRL and LOC443319.The PRL and LOC443319 was misplaced in ARS1that are scattered on two chromosomes due to the wrong assembly of reference genome.Compared with ARS1,goat pan-genome can improve the mapping ratio and mapping quality of resequencing and transcriptomic data both,and can correct the spurious SNPs effectively.The comparison of bezoar with domestic goat populations revealed that regions with apparent copy numbers variations were enriched in immune-related pathways,and pan-sequences carrying an anti-inflammatory response gene ICAM1 and an anti-intestinal parasite gene MUC6 have presence-absence variation in these two populations,which may be involved in domestication of goats.The construction of GOATPAN can help to further promote the application of this goat pan-genome.4.In order to facilitate users to effectively search goat data resources,we expanded the population and constructed a goat comprehensive genome variation and selective signatures database?GGVD,http://animal.nwsuaf.edu.cn/Goat Var?.GGVD includes?41.44 M SNPs and?5.14 M indels,and provides selection signals for goat domestication and subsequent intensive trait-driven breeding.GGVD uses interactive tables,visual maps that project the allele frequency of each group,as well as optimized selective signal screening modules?such as Manhattan plot and line chart?to demonstrate the application of variation and selection signals in identifying goat candidate sites.In this study,eight genes including C10H15orf41,FGF5,ATP12A,UBE2N,LOC102173935?NEK4?,RAP2B,P2RY1,and NADK were identified to be strongly selected in Tibetan goat,which can serve the goat selection and breeding work.The ruminant genome database analysis platform can help strengthen the research of ruminant functional genomics.Constructing a collection of all variants of a species and combining them with multiple omics data to screen potential functional sites can provide useful targets for cattle and goat breeding.