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GenTech
Database of the project "Genetic technologies in poultry farming"
Genetic technologies for assessing the potential of genome modification in poultry farming. Decoding and annotation of the chicken genome allows genetic engineering methods to improve the properties of breeds. The project is being implemented within the framework of the Federal Scientific and Technical Program for the Development of Genetic Technologies.
General approach
To edit the genome to improve the properties of breeds, it is necessary to determine the target points in the genome responsible for the variable trait. For this purpose, a resource population of chickens divergent by the target trait is created and studied. In order to increase the growth rate of chickens, a resource population of F2 chickens was studied, obtained by crossing the Cornish and Russian Snow White breeds, and having a high diversity in the trait of growth rate.
Genomes of F2 hybrids
The genomes of F2 hybrids of the Russian Snow White and Cornish breeds have been sequenced. Genomic loci associated with the growth rate of chickens have been identified. Changes in these loci can increase the growth rate.
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Genome of the Russian Snow White chicken breed
We have sequences the genome of the Russian Snow White chicken breed for the first time. The Russian White was bred in the USSR by crossing the White Leghorn breed with local chickens. Work on creating the breed began in 1929, and the breed was approved in 1953. Subsequently, the Russian Snow White breed was bred by selection for resistance to low temperatures in the first days and high egg production. The chickens of this breed can successfully tolerate temperatures 8-10 degrees below normal, as well as many diseases. In addition, as a result of the action of a recessive gene, 25% of day-old chicks in the population have completely white (not yellow) down, hence the name "Russian Snow White".
Download » View in genome browser »Transcriptome of F2 hybrids
Genes were identified and their expression measured in the brain, heart, kidney, liver, chest and legs using the CAGE-seq method. Transcriptome analysis allowed us to identify specific nucleotides in genomic loci associated with growth rate and suggest a mechanism of their action.
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Transcriptomic data were integrated into the iES1300 metabolic model. Analysis of this model allowed us to identify reactions associated with growth rate. Editing genes involved in the identified reactions is a promising direction for increasing the growth rate of chickens. Download »Target genes
By integrating experimental data of different types, the genes most suitable for genome editing to increase the growth rate of chickens were found. The list is updated as new data is received.
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Genes identified during joint analysis of genomes and transcriptomes of the F2 generation.
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Genes identified based on differential expression analysis.
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Genes identified based on metabolic modeling.
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