CN112365923A - Matching algorithm of genes related to exercise capacity - Google Patents
Matching algorithm of genes related to exercise capacity Download PDFInfo
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- CN112365923A CN112365923A CN202011333555.XA CN202011333555A CN112365923A CN 112365923 A CN112365923 A CN 112365923A CN 202011333555 A CN202011333555 A CN 202011333555A CN 112365923 A CN112365923 A CN 112365923A
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- G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
- G16B20/20—Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
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- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
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- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
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Abstract
The invention discloses a matching algorithm of genes related to motor ability, which comprises the following steps: s1, obtaining individual gene data; s2, calculating the weight of the related SNP locus; and S3, calculating the movement capacity. The motion ability related gene matching algorithm is characterized in that SNP is selected after comprehensive papers and a Qiyunned database are considered, the weight of SNP sites and the relation among the SNP sites and the like aiming at a certain motion related item are calculated according to the Qiyunned database and the data significance, the number of the selected SNP sites is more, more targeted and more comprehensive, and more accurate in describing motion ability, and the SNP refers to a single nucleotide polymorphism site which refers to DNA sequence polymorphism caused by single nucleotide variation on the genome level.
Description
Technical Field
The invention relates to the field of biological information, in particular to a matching algorithm of genes related to motor ability.
Background
The gene is a basic unit of heredity, a DNA sequence carrying the genetic information transfers the genetic information to the next generation through copying, and guides the protein to express the genetic information, thereby regulating and controlling the biological properties, the gene detection is a technology for detecting the base sequence of the DNA through blood, body fluid and the like, the gene information in the sample is amplified after the sample is obtained, the amplified DNA is analyzed through specific equipment for information monitoring and analysis, and the gene detection can diagnose the heredity diseases, predict the disease risk, judge the motion ability and the like. In recent years, there have been increasing studies to reveal the genetic mechanism of human motor ability from the molecular level and have achieved some research results, and the main research mode is to discuss certain motor ability, such as endurance quality, aerobic motor ability, etc., by analyzing the corresponding relationship between human Single Nucleotide Polymorphism (SNP) and motor ability. An English research group conducted control research on SNPs on ACE genes of 33 excellent mountain climbers and non-athlete groups, and found that the mountain climbers have significant difference from the non-athlete groups in genotype frequency or allele frequency, and angiotensin converting enzyme encoded by the ACE genes is also related to human cardiopulmonary function; the function of the muscle tissue specific phosphokinase (CKMM) gene is to generate ATP at high concentration in the myosin head and supply energy required for normal body functions, and research shows that the mutation of the coding region of the gene has a certain correlation with endurance level; the aerobic capacity of the population carrying the A2A11 genotype of the histocompatibility antigen (HLA) gene is significantly higher than that of the population not carrying it.
With the continuous deep understanding of human SNP and athletic ability, the influence of the SNP and the athletic ability on the athletic ability is predicted based on the genotype characteristics of individuals so as to provide personalized exercise guidance and suggestions, finally, the purpose of intervening the athletic behavior from the gene level is achieved, good exercise habits are standardized, the exercise injury is effectively avoided, and meanwhile, the exercise efficiency is improved to the maximum extent.
Most of the existing motion gene detection products in the market use some motion gene association researches to make the motion ability analysis corresponding to genotyping, the used background data has no crowd pertinence, and the included SNP sites are less.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a matching algorithm of genes related to the motion ability, and solves the problems that the current common motion gene products have few reference SNP sites, most of the current common motion gene products have one motion ability corresponding to one site, the background data lack the pertinence of Chinese population and the like.
In order to achieve the purpose, the invention provides the following technical scheme: an algorithm for matching genes associated with exercise capacity, comprising the steps of:
s1, obtaining individual gene data;
s2, calculating the weight of the related SNP locus;
and S3, calculating the movement capacity.
Preferably, the acquisition of the gene data SNP site typing in step S1 uses an ASAMD gene chip customized for asian population.
Preferably, the ASAMD gene chip can detect 66 ten thousand effective SNP locus typing results.
Preferably, the step S2 and the step S3 may select thirteen items of exercise capacity interpretation items for people who pay attention to exercise among children, young, middle-aged and old people, including vital capacity, exercise capacity, aerobic exercise capacity, anaerobic exercise capacity, explosive force, influence of exercise on body mass index, exercise recovery capacity, muscle type, muscle strength, endurance, soft tissue injury protection, pain sensitivity and exercise enthusiasm, and the 13 exercise capacities are proved by research literature to be largely related to genotyping.
Preferably, the thirteen exercise capacity, selected over 30 SNP sites that were significantly correlated with the individual's corresponding exercise capacity in a large sample of genome-wide correlation studies.
Preferably, the exercise capacity interpretation item, in the case that one exercise capacity corresponds to one SNP site, can directly use SNP typing to classify the corresponding exercise capacity.
Preferably, the exercise capacity interpretation item is a condition that one exercise capacity corresponds to a plurality of SNP sites, different weights are assigned to each SNP site in view of molecular mechanism, data significance and SNP typing frequency of Chinese population, and finally the corresponding exercise capacity of the item is calculated according to the site and weight information.
The invention has the following beneficial effects:
the characteristic SNP is selected after the comprehensive paper and the Qiyunnade database are considered, the weight of the SNP locus aiming at a certain athletic ability and the relation among the SNPs are calculated according to the Qiyunnade database and the data significance, the number of the selected SNP loci is more, the selected SNP loci are more targeted and more comprehensive to Chinese people, and the athletic ability of the Chinese people is more accurately described.
Detailed Description
All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a technical scheme that: an algorithm for matching genes associated with exercise capacity, comprising the steps of:
s1, obtaining individual gene data, wherein an ASAMD gene chip customized for Asian population is used for obtaining SNP locus typing of the gene data, and the ASAMD gene chip can detect 66 ten thousand effective SNP locus typing results;
s2, calculating the weight of the related SNP locus;
s3, calculating the exercise capacity, selecting thirteen items of exercise capacity interpretation items aiming at the people paying attention to exercise in children, Qing, middle-aged and old people, including vital capacity, exercise capacity, aerobic exercise capacity, anaerobic exercise capacity, explosive force, the influence of exercise on body mass index, exercise recovery capacity, muscle types, muscle strength, endurance, soft tissue injury protection, pain sensitivity and exercise enthusiasm, wherein the 13 exercise capacities are proved by research documents to be related to genotyping to a great extent, the thirteen items of exercise capacity are selected to be more than 30 SNP sites which are obviously related to the exercise capacity corresponding to an individual in the whole genome correlation research of a large sample, and one item of exercise capacity corresponds to the condition of one SNP site, so that the corresponding exercise capacity can be directly divided by using SNP genotyping, and one item of exercise capacity corresponds to the condition of a plurality of SNP sites, considering from the aspects of molecular mechanism, data significance and SNP typing frequency of Chinese population, different weights are distributed to each site, and finally the corresponding motion capability of the item is calculated according to the site and weight information. The SNP refers to a single nucleotide polymorphism site, refers to DNA sequence polymorphism caused by single nucleotide variation on a genome level, is the most common one of human heritable variation, accounts for more than 90% of the human genome polymorphism, and the variation of the SNP comprises the conversion, inversion, insertion and deletion of single base, and is a rich genetic marker, wherein one SNP exists in every 1000 bases in the human genome, and the quantity and the distribution of the SNPs are large, so the SNP also becomes an important step of the planned application of the human genome.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. An algorithm for matching genes associated with exercise ability, comprising: the method comprises the following steps:
s1, obtaining individual gene data;
s2, calculating the weight of the related SNP locus;
and S3, calculating the movement capacity.
2. The algorithm for matching exercise capacity-related genes according to claim 1, wherein: the acquisition of the gene data SNP locus typing in the step S1 uses ASAMD gene chips customized for Asian population.
3. The ASAMD gene chip of claim 2, which can detect 66 ten thousand effective SNP site typing results.
4. The algorithm for matching exercise capacity-related genes according to claim 1, wherein: thirteen items of exercise capacity interpretation items aiming at people paying attention to exercise in children, young, middle-aged and old people can be selected in the step S2 and the step S3, wherein the thirteen items comprise vital capacity, exercise capacity, aerobic exercise capacity, anaerobic exercise capacity, explosive force, influence of exercise on body mass index, exercise recovery capacity, muscle type, muscle strength, endurance, soft tissue injury protection, pain sensitivity and exercise enthusiasm, and the 13 exercise capacities are proved by research documents to be related to genotyping to a great extent.
5. The thirteen-item exercise capacity of claim 4, selecting more than 30 SNP sites that were significantly correlated with individual corresponding exercise capacity in a large sample genome-wide correlation study.
6. The exercise capacity interpretation item of claim 4, wherein an exercise capacity corresponds to a SNP site, and SNP typing can be directly used to classify the corresponding exercise capacity.
7. The exercise capacity interpretation item of claim 4, wherein in the case that one exercise capacity corresponds to a plurality of SNP sites, different weights are assigned to each SNP site in terms of molecular mechanism, data significance and SNP typing frequency of Chinese population, and finally the corresponding exercise capacity of the item is calculated according to the site and weight information.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202011333555.XA CN112365923A (en) | 2020-11-25 | 2020-11-25 | Matching algorithm of genes related to exercise capacity |
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| CN202011333555.XA CN112365923A (en) | 2020-11-25 | 2020-11-25 | Matching algorithm of genes related to exercise capacity |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115521986A (en) * | 2022-09-19 | 2022-12-27 | 大连理工大学 | Human physical ability evaluation method based on biological multigroup knowledge |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115521986A (en) * | 2022-09-19 | 2022-12-27 | 大连理工大学 | Human physical ability evaluation method based on biological multigroup knowledge |
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Application publication date: 20210212 |