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CN-115335910-B - Method for establishing an epigenetic clock for avian species

CN115335910BCN 115335910 BCN115335910 BCN 115335910BCN-115335910-B

Abstract

The present invention relates to a computer-implemented method for establishing an epigenetic clock for an avian species, the method comprising (a.) identifying and determining the methylation level of a specific CpG site within genomic DNA obtained from the avian species and representing a specific time point within the time lifetime of the avian species, (b.) excluding all CpG sites associated with a Single Nucleotide Polymorphism (SNP) from the CpG sites identified in step (a), (c.) excluding all CpG sites located on sex chromosomes (Z and W) from the CpG sites obtained in step (b), (d.) performing a tissue-specific normalization step on the CpG sites obtained in step (c.), and (e.) correlating the CpG methylation level of the CpG sites obtained in step (d) with a chronological age using a punishment regression model.

Inventors

  • G. Ladatz
  • F. Luco
  • F. Boer
  • JOHNSON CONTROLS GMBH
  • E. I. IGU
  • F. Timan
  • S. Pelce

Assignees

  • 赢创运营有限公司

Dates

Publication Date
20260505
Application Date
20210122
Priority Date
20200124

Claims (13)

  1. 1. A computer-implemented method of establishing an epigenetic clock for an avian species, the method comprising (A) identifying and determining methylation levels of specific CpG sites within genomic DNA obtained from a plurality of different biological sample materials from said avian species and representing specific time points within the chronological lifetime of said avian species, (B.) excluding all CpG sites associated with the single nucleotide polymorphism from the CpG sites identified in step (a), (C.) excluding all CpG sites located on the sex chromosome from the CpG sites obtained in step (b), (D.) performing a tissue-specific normalization step on the CpG sites obtained in step (c.), and (E.) correlating the CpG methylation level of the CpG sites obtained in step (d.) with chronological age using a penalized regression model, Wherein specific CpG sites within the genomic DNA of the avian species are distributed within a hypomethylated region (LMR) of the avian species genome.
  2. 2. The method of claim 1, wherein the plurality of different biological sample materials from the avian species and representative of a particular point in time within the chronological lifespan of the avian species comprise a material selected from the group consisting of bodily fluids, fecal materials, tissue materials, and feather materials.
  3. 3. The method of claim 1, wherein the plurality of different biological sample materials from the avian species and representative of a particular point in time over the time-series lifetime of the avian species comprise at least four different tissues.
  4. 4. A method according to any one of claims 1-3, wherein the plurality of different biological sample materials from the avian species and representing a specific point in time over the chronological lifetime of the avian species comprise or consist of tissue material selected from muscle tissue, intestinal tissue, organ tissue and skin tissue.
  5. 5. A method according to any one of claims 1-3, wherein the plurality of different biological sample materials from the avian species and representative of a particular point in time over the chronological lifetime of the avian species comprise breast tissue, spleen tissue, ileum tissue and jejunum tissue.
  6. 6. A method according to any one of claims 1-3, wherein a plurality of different biological sample materials from the avian species and representing a specific point in time over the chronological lifetime of the avian species are selected to represent an age between 3 days and 63 days.
  7. 7. A method according to any one of claims 1 to 3, wherein step (a) involves a whole genome bisulphite sequencing process.
  8. 8. A method according to any one of claims 1-3, wherein specific CpG sites within the genomic DNA of the avian species are distributed throughout the genome of the avian species and are limited to a strand-specific coverage of at least 10.
  9. 9. The method of claim 8, wherein the tissue-specific normalization step is performed by calculating an average value for each CpG for all samples from the same tissue and subtracting the value from the value for the CpG.
  10. 10. The method of claim 9, wherein a particular CpG site within the genomic DNA of the avian species is limited to a strand-specific coverage of at least greater than 5.
  11. 11. A method according to claim 1 wherein the tissue specific normalization step is performed by calculating for each LMR an average of all samples from the same tissue and subtracting the value from the value of that LMR.
  12. 12. A computer program loaded into a computer memory implementing the method of any of claims 1 to 9.
  13. 13. A tangible, computer-readable medium comprising computer-readable code that, when executed by a computer, causes the computer to perform operations comprising: (a.) receiving information corresponding to methylation levels of specific CpG sites within genomic DNA of an avian species obtained from a plurality of different biological sample materials representing specific time points within the chronological lifetime of the avian species, (B.) receiving information corresponding to all CpG sites associated with the single nucleotide polymorphism and excluding said information from the CpG sites of step (a.), (C.) receiving information corresponding to all CpG sites from the sex chromosome and excluding said information from CpG sites of step (b.), (D.) performing a tissue-specific normalization step on the CpG sites of step (c), and (E.) correlating the CpG methylation level of the CpG sites in step (d.) with chronological age using a penalized regression model, Wherein specific CpG sites within the genomic DNA of the avian species are distributed within a hypomethylated region (LMR) of the avian species genome.

Description

Method for establishing an epigenetic clock for avian species Technical Field Methods of establishing a full-tissue epigenetic clock for avian species are described. The epigenetic clocks thus obtained are particularly robust, scalable, and provide high specificity, accuracy and precision. Background Birds, particularly chickens (Galliformes), such as chickens (Gallus gallus) are an important source of commercially produced meats and eggs. Therefore, factors affecting chicken growth, pathogen resistance and meat quality have considerable scientific and economic significance. Extensive genome-wide association studies have been conducted to elucidate the underlying genetic framework. Epigenetic modifications provide important supplements and extensions to genetic variation, but the study of chickens remains relatively inadequate. Animal methylation sets can be highly diverse, ranging from certain insect genomes with sparse methylation patterns and only tens of thousands of methylation signatures to mammalian genomes with dense methylation patterns and tens of millions of methylation signatures. So far, very little is known about the methylation pattern of whole genome DNA in vertebrates, in particular birds, which are not mammals. DNA methylation is associated with the aging process and is an epigenetic modification with high specificity for CpG dinucleotides (5 '-C-phosphate-G-3'), i.e., a region in the linear base sequence of DNA in which a cytosine nucleotide is followed by a guanine nucleotide in the 5 '. Fwdarw.3' direction. The collection of genomic methylation modifications constitutes the methylation group of a particular cell. Hypomethylated regions (LMRs) represent a key feature of the dynamic methylation group. LMR is a localized reduction in DNA methylation landscape, representing CpG-poor remote regulatory regions, generally reflecting the binding of transcription factors to other DNA binding proteins. The LMR was originally described in mice (Stadler et al, nature 480,490-495 (2011)). Evolutionary protection of LMRs other than mammals has not yet been explored. Age-related DNA methylation changes over discrete CpG groups in the human genome have been identified and used to predict age (Horvath, s. (2013). DNA methylation age of human tissues and cell types. Genome Biology 14:3156). These "epigenetic clocks" can estimate DNA methylation age for specific tissue or non-tissue dependencies, and can predict mortality and time to death. Epigenetic age is highly correlated with chronological age, but can also react to environmental factors that accelerate or slow the aging process, resulting in a large deviation from chronological age. Acceleration of the epigenetic age (epigenetic age > chronological age) indicates that the underlying tissue ages faster than expected from chronological age, while negative values (epigenetic age < chronological age, age retardation) indicate that the tissue ages slower than expected. Acceleration of epigenetic age is associated with a number of age-related conditions and diseases, such as inflammatory processes. Given that these conditions accelerate biological/epigenetic age, age-related performance biomarkers are particularly useful tools in the animal farming industry, as they facilitate monitoring large groups of animals and provide objective quality assurance. Avian species present unique challenges for the development of performance biomarkers because they combine considerable economic importance with relatively short life. It is therefore an object of the present invention to provide a method for establishing a whole-tissue epigenetic clock for avian species, which can serve as a performance biomarker for each avian species, and which provides robustness and versatility while having high specificity, accuracy and precision. Summary of The Invention The present invention provides a computer-implemented method of establishing an epigenetic clock for an avian species, the method comprising (a.) identifying and determining methylation levels of specific CpG sites within genomic DNA obtained from the avian species and representing a plurality of different biological sample materials of the avian species at a specific time point over the chronological lifetime of the avian species, (B.) excluding all CpG sites associated with the Single Nucleotide Polymorphism (SNP) from the CpG sites identified in step (a), (C.) excluding all CpG sites located on sex chromosomes (Z and W) from the CpG sites obtained in step (b), (D.) performing a tissue-specific normalization step on the CpG sites obtained in step (c.), and (E.) correlating the CpG methylation level of the CpG site obtained in step (d.) with chronological age using a penalized regression model. Furthermore, a computer program loaded into a computer memory is provided, implementing the above method. Finally, the present invention relates to a tangible computer-readable medium comprising computer-readable code that, wh