Breeding method of multi-gene pyramiding of fine breed milk goats

Abstract

The invention discloses a breeding method of multi-gene pyramiding of fine breed milk goats, which comprises the following steps: using genome DNA of milk goats continuously bearing two or more than two goats as a template; using four pairs of primers for respectively amplifying intrones 2 and exons 10 of prolactin receptor genes, and the 5' non-translational region (5' UTR) and exons 1 of luteotropin beta subunit genes; using agarose gel electrophoresis for carrying out size determination on each amplifying product; adopting the DNA sequencing technology for sieving and checking the site-directed mutation of the amplifying products of the four pairs of the primers; then, using polyacrylamide gel electrophoresis for carrying out gene typing and gene frequency analysis on the SNPs of the four sites of the prolactin receptor genes and the luteotropin beta subunit genes; analyzing the relationship between the goat bearing number and the polymorphism of the high-yield milk goat individuals (generation F1) and the relationship between different gene type combinations and the goat bearing number; tracing to the parent generation (generation F0); tracking filial generation (generation F2); detecting the relationship between the goat bearing number and the gene type combinations of the female goat individuals; and analyzing the contribution of different gene types in the prolific trait formation.

Description

technical field [0001] The invention belongs to the field of molecular genetics, and in particular relates to a breeding method for multi-gene polymerization of fine-bred dairy goats. The method uses PCR-SSCP and DNA sequencing techniques to detect prolactin receptor (PRLR) genes and luteinizing hormone beta Single-strand DNA base mutation polymorphism of subunit (LHβ) gene, determine the appropriate molecular marker by analyzing the relationship between polymorphism and litter size of high-yield dairy goat individuals (F1 generation), and analyze high-yield dairy goat individuals (F1) The relationship between the different genotype combinations of ewes and the number of litters, trace the parents (F0 generation), track the offspring (F2 generation), detect the relationship between the genotype combinations of individual ewes and the number of litters, and study the relationship between different genotypes in Then select the genotype combinations of high-yielding individuals, ...

AI Technical Summary

Problems solved by technology

Among these SNP detection techniques, DNA sequence determination is the most accurate SNP detection method, but its detection cost is extremely expensive, and large-scale instruments such as DNA sequencers are required. At the same time, very skilled technicians and Experience, so DNA sequence determination is not an ideal SNP detection method for actual production; of course, the combination of PCR-SSCP and DNA sequencing can be used to detect SNPs can appropriately reduce the detection cost, but the experimental process of PCR-SSCP is relatively long , the operation is cumbersome, and there are false negative problems in the experimental process, so it is not an ideal SNP detection method; as a new SNP detection method, the AS-PCR method has very broad prospects in the future application field, but , this method needs to design special primers, and it can only target specific gene loci. At the same time, there is a probability of false detection in the detection process. Therefore, it is not generally applicable at present; Ligation reaction technology to detect SNP sites requires detection platforms such as plate reader, gene chip, microsphere array technology and mass spectrometer, which is not very practical for general molecular laboratories

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