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Using Pool-seq To Detect The Whole-genome Structural Variations In Different Chicken Breeds

Posted on:2017-01-15Degree:DoctorType:Dissertation
Country:ChinaCandidate:Z B WuFull Text:PDF
GTID:1223330482492576Subject:Biochemistry and Molecular Biology
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As one of the first domesticated birds, chicken(Gallus gallus domesticus) is one of the major agricultural commercial animals. Chicken’s meat and eggs are the most important supply of animal protein for human beings. After long period of evolution and artificial selection, chicken has formed a range of breeds, which perform a vast diversity of phenotypes. The study of chicken genetic diversity and group evolution has wide biological importance. It has been proved by many studies that structural variations (SVs) play an important role in producing phenotype diversity. With the development of biochip and next-generation sequencing (NGS), whole genome sequencing becomes more economically and efficiently than ever before, which provids an excellent opportunity to discover SVs in the genome.SVs usually defined as those variations covering 50 or more base pairs, including deletions, insertions, inversions, recurring mobile elements and other rearrangements. The absolute number of SVs is inferior to that of SNPs and short indels, but in terms of the number of nucleotides, SVs accounts for more differences to whole genome. It has been showedthat total number of nucleotides covered by SVs can reach to 5% of the whole genome in human. Recently, there is a growing recognition that structural variations are pervasive and important.In this research, we usedwhole-genome sequencing of pools of individuals (Pool-seq),selected fourrepresentative chicken breeds and each pool size is twenty. Pool-seq provides much more genome-wide polymorphism data with considerably lower costs than sequencing of individuals by reducing genomic representation of each pooled samples. Four breeds we selected in the study are Cobe, White Leghorn, Silkie and Dehong respectively. There is vast diversity between these breeds. We used four tools in three methods to detect the whole-genome SVs in individual breeds, then after filtering and merging the results from these tools, get the final results of SVs.Various types of SVs were detected, including deletions, insertions, inversions and copy number variations. There are numerous SVs detected in each breeds, and the total nucleotides of all SVs can covered range from 1.75% to 2.29% of the whole genome in these four breeds. In our study, most of SVs are deletions and length of inversion is the biggest one. Some SVs are overlapped with exon or regulatory region of genes, and these SVs may have potential biological role. In this research, we generated a high resolution structural variations map. We foundthat the SVs were not randomly distributed and there were some hotspots in the genome. The comparisons of detected SVs between four breed showed that 4422 deletion existed in all breeds andabout 20% SVs arespecific in each breed.Via comparing with chicken quantitative trait loci (QTL), taking Gene Ontology (GO) and KEGG analysis, we discover that these species specific SVs may play an important role in species evolution and breed domestication. From overlap between QTL and specific SVs, we found that Cobe has an QTL affecting the gowth speed that don’t detecting in other breeds. From GO analysis, different GO Terms were detected in four breeds, influencing different biological process, molecular function or cellular composition.In summary, we generated the whole genome structural variations map of four representive chicken breeds by an economical and effective sequencing strategy Pool-seq.Our research laid a foundation for future studies on detecting SVs from Pool-seq. First, we illustrated a high-resolution map of whole genome structural variations, and then analysis distribution characteristics and potential biological role of SVs. We found that SVs’ distribution may have relationship with duplication sequence on genome.Secondly, by discoveringspecific SVs with genetic and bioinformatic analysis, we found that SVs may play an important role in many process such as genetic diversity, breed domestication and species evolution.
Keywords/Search Tags:Pool-seq, structural variation, genetic diversity, domestication, evolution
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