CN109545281B - Analysis method of trio family genetic mutation mode based on second-generation high-throughput sequencing - Google Patents

Analysis method of trio family genetic mutation mode based on second-generation high-throughput sequencing Download PDF

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CN109545281B
CN109545281B CN201811394656.0A CN201811394656A CN109545281B CN 109545281 B CN109545281 B CN 109545281B CN 201811394656 A CN201811394656 A CN 201811394656A CN 109545281 B CN109545281 B CN 109545281B
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CN109545281A (en
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刘港彪
杨帆
孙子奎
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Nanjing Personal Gene Technology Co ltd
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Abstract

The invention discloses a trio family genetic mutation mode analysis method based on second-generation high-throughput sequencing, which is characterized by comprising a multi-index information matrix creation step, a genetic mode judgment step and a result information integration step. According to the analysis method, specific mutation site conditions are considered, and meanwhile, the relevant genetic modes of mutation sites are analyzed in a targeted mode by combining the relevant phenotypes of individuals such as gender and disease state information, and the genetic modes of the pathogenic mutation sites are judged more accurately through comprehensive analysis of a plurality of indexes. The flow of the analysis method of the invention judges the mutation genetic pattern of the trio family and comprises 6 types: the variety of the sex-linked type and the sex-linked type are comprehensively judged by the sex-linked type and the sex-linked type. A plurality of index information of trio family individuals is given. All analysis processes are integrated, one-key operation can produce results, and complicated operation steps are not needed.

Description

Analysis method of trio family genetic mutation mode based on second-generation high-throughput sequencing
Technical Field
The invention belongs to the field of biological information data processing, and mainly relates to a trio family genetic mutation mode analysis method based on second-generation high-throughput sequencing.
Background
Monogenic genetic disease, also known as mendelian genetic disease, refers to a disease caused by single or single pair gene mutations, primarily determined by genetic factors, with a lower incidence in the population. Monogenic inherited diseases are generally classified into five types, i.e., autosomal dominant, autosomal recessive, X-concomitant dominant, X-concomitant recessive, and Y-concomitant inherited diseases, depending on the genetic pattern. Most monogenic genetic diseases are caused by alterations in the quality and/or quantity of the protein encoded by the gene, and by analysis of high throughput sequencing data, disease-related variations can be found. Therefore, the analysis of the genetic pattern of the mutation is of great importance for understanding the pathogenesis and preventing and treating diseases.
The existing judging software related to mutation genetic patterns has the following problems:
the genetic mode judgment is single: most of the existing methods carry out mutation genetic mode judgment according to the type of a sample mutation site, and neglect specific related phenotypes of individuals;
lack of comprehensive information assessment analysis: the existing analysis flow does not combine with the comparison type in judging the mutation genetic mode, such as the specificity of the sex, the disease state, the number and the like of the comparison;
the results show a single: the mutation types of the table individuals and the mutation frequencies of other control individuals in the analysis results are not displayed correspondingly, and the later application cannot be obviously assisted.
Disclosure of Invention
In order to solve the problems in the prior art, the invention aims to provide an analysis method of a trio family genetic mutation mode based on second-generation high-throughput sequencing.
In order to achieve the purpose of the invention, the technical scheme adopted is as follows: the analysis method of the genetic mutation pattern of the trio family based on the second-generation high-throughput sequencing is characterized by comprising the following steps:
(1) A multi-index information matrix creation step: considering specific mutation site conditions and simultaneously combining the relevant phenotype information such as sex and disease state information of an individual, and constructing the information into a matrix so as to analyze corresponding genetic patterns of mutation sites in a targeted manner;
(2) A genetic pattern judgment step: correspondingly judging mutation genetic modes of the trio family according to the multi-index information matrix, wherein the judging genetic modes comprise: a sex-linked dominant recessive genetic pattern, an X-linked dominant recessive genetic pattern, a compound heterozygous mutation, and a new mutation;
(3) And a result information integration step: the trio family individuals can be subjected to mutation types, mutation frequencies, genetic patterns, mutation notes and other information, so that further information mining can be performed.
In a preferred embodiment of the present invention, the step (1) specifically includes:
1) Phenotype information classification: classifying and identifying the disease state of the individual to be used for assisting in screening corresponding possible pathogenic mutation sites;
2) Gender information identification: identifying the diseased state of the individual for judging the genetic mode of the subsequent mutation site;
3) Creating a mutation site matrix: comparing mutation site information of a plurality of individuals to generate a mutation matrix for subsequent mutation mode judgment.
In a preferred embodiment of the present invention, in the step (2), the determining of the dominant inheritance pattern of the autosomal dominant specifically includes:
1) A dominant inheritance pattern of autosomal dominant;
2) Extracting the autosomal region exon and exon splice region non-synonymous mutation;
3) Screening the patient for all heterozygous or homozygous sites;
4) Retaining variant sites that did not occur in all normal individuals;
5) Further screening the sites of variation on at least one of the parents;
6) Candidate deleterious variant sites are obtained.
In a preferred embodiment of the present invention, in the step (2), the determining of the dominant sex-recessive genetic pattern specifically includes:
1) Extracting the autosomal region exon and exon splice region non-synonymous mutation;
2) Screening all homozygous sites in the patient;
3) Retaining all mutation sites that were 0/1|0/0 in normal individuals;
4) The mutation sites which are 0/1 in the parent are reserved;
5) Candidate deleterious variant sites are obtained.
In a preferred embodiment of the present invention, in the step (2), the determining of the complex heterozygous mutant genetic pattern specifically includes:
1) Extracting the autosomal region exon and exon splice region non-synonymous mutation;
2) Screening the patient for all heterozygous sites;
3) A gene retaining at least 2 heterozygous mutation sites;
4) Excluding heterozygous sites present in normal individuals;
5) Excluding sites where no corresponding mutation is found on the parents;
6) Genes with only one mutation site are excluded.
In a preferred embodiment of the present invention, in the step (2), the determining of the X-linked recessive genetic pattern specifically includes:
1) Extracting non-synonymous mutation of exon and exon cutting region of X chromosome region;
2) Screening the patient for all homozygous or semi-homozygous sites;
3) A site with a mutation type of 0/0|0/1 remaining in a normal female individual;
4) A site with mutation type 0 remaining in normal men;
5) The sites where all the variants were present in the parent were retained;
6) If the patient is female, the father is normal, such variant sites are excluded.
In a preferred embodiment of the present invention, in the step (2), the judging of the dominant genetic pattern of the X-linked specifically includes:
1) Extracting non-synonymous mutation of exon and exon cutting region of X chromosome region;
2) Screening the patient for all heterozygous or semi-homozygous sites;
3) A site that retains a mutation type of 0/0 in a normal female individual;
4) A site with mutation type 0 remaining in normal men;
5) These sites are excluded if the patient is female, the parent is normal, or the patient is male, the mother is normal.
In a preferred embodiment of the present invention, in the step (2), the determining of the genetic pattern of the new-born mutation specifically includes:
1) Extracting the non-synonymous mutation of the exon in the chromosome region and the exon cutting region;
2) Screening the patient for all homozygous or semi-homozygous sites;
3) A mutation site that remains at 0/0|0 in normal individuals;
4) A mutation site where only one individual appears in the offspring individuals is retained;
5) The mutation sites that also occur in other patients are excluded.
The invention has the beneficial effects that:
the analysis method not only considers the specific mutation site condition, but also combines the relevant phenotype of the individual such as sex and disease state information to analyze the corresponding genetic mode of the mutation site in a targeted way. And a plurality of indexes are comprehensively analyzed, so that the genetic mode judgment of the pathogenic mutation sites is more accurate.
The flow of the analysis method of the invention judges the mutation genetic pattern of the trio family and comprises 6 types: the variety of the sex-linked type and the sex-linked type are comprehensively judged by the sex-linked type and the sex-linked type.
In order to facilitate subsequent information mining, the analysis result of the analysis method provided by the invention can provide a plurality of index information such as mutation types, mutation frequencies, genetic patterns, mutation comments and the like of trio family individuals.
The analysis method integrates all analysis flows, can output results by one-key operation, and does not need complicated operation steps.
Drawings
FIG. 1 is a flowchart showing the judgment of the autosomal dominant genetic mutation pattern of the present invention;
FIG. 2 is a flowchart for determining the autosomal recessive genetic mutation pattern according to the present invention;
FIG. 3 is a flowchart for determining the autosomal compound heterozygous mutant pattern of the present invention;
FIG. 4 is a flowchart of the X-linked recessive genetic pattern judgment of the present invention;
FIG. 5 is a flowchart showing the judgment of the dominant genetic pattern of X-linked according to the present invention;
FIG. 6 is a flow chart showing the judgment of the genetic pattern of a new mutation according to the present invention.
Detailed Description
The present invention is further illustrated by the following examples, which are not intended to be construed as limiting the invention.
TABLE 1
Group SampleID Sex Status Relationship
Trio1 ID1 M C case
Trio1 ID2 M N father
Trio1 ID3 F N mother
Trio1 ID4 F N control
Trio1 ID5 M N control
Trio1 ID6 M N control
Referring to FIGS. 1-6 and Table 1, a method for analyzing a genetic mutation pattern of a trio family based on second-generation high-throughput sequencing, comprising the steps of:
(1) Creating a multi-index information matrix: the analysis method not only considers the specific mutation site situation, but also combines the relevant phenotype information of the individual such as sex and disease state information, and constructs the information into a matrix (shown in the attached table 1) for carrying out the analysis of the corresponding genetic patterns of the mutation sites in a targeted manner.
(2) Judging a genetic mode: the analysis flow judges the mutation genetic mode of the trio family, which comprises the following steps: a sex-linked recessive genetic pattern, an X-linked recessive genetic pattern, a compound heterozygous mutation, a new mutation, and the judgment type is comprehensive.
(3) And (3) result information integration: in the analysis result, various information such as mutation types, mutation frequencies, genetic patterns, mutation notes and the like of the trio family individuals are provided for integration so as to facilitate subsequent further information mining.
Wherein the above (1) specifically comprises
1.1 classification of phenotypic information: the disease states of individuals are classified and marked, normal individuals are marked as 'N', and diseased individuals are marked as 'C', so that the screening of corresponding possible pathogenic mutation sites is assisted.
1.2 sex information identification: the disease state of the individual is identified, the female is labeled "F", the male is labeled "M", and the genetic pattern for subsequent mutation sites is determined.
1.3 creating a mutation site matrix: comparing mutation site information of a plurality of individuals to generate a mutation matrix for subsequent mutation mode judgment.
Wherein the above (2) specifically comprises
2.1 dominant inheritance pattern of autofection
2.1.1 extracting the autosomal region exon and exon splice region non-synonymous mutations;
2.1.2 screening patients for all heterozygous (0/1) or homozygous sites (1/1);
2.1.3 retaining variant sites not present in all normal individuals;
2.1.4 further screening the parents for sites having variation on at least one of the parents;
2.1.5 obtaining candidate deleterious variant sites.
2.2 sex-limiting recessive genetic patterns
2.2.1 extraction of autosomal region exons and exon cleavage region non-synonymous mutations;
2.2.2 screening of patients for all homozygous sites (1/1);
2.2.3 retaining all mutation sites that are 0/1|0/0 in normal individuals;
2.2.4 mutation sites which are all 0/1 in the parent;
2.2.5 obtaining candidate deleterious variant sites.
2.3 Compound heterozygous mutation sites
2.3.1 extraction of autosomal region exons and exon cleavage region non-synonymous mutations;
2.3.2 screening patients for all heterozygous loci (0/1);
2.3.3 genes retaining at least 2 heterozygous mutation sites;
2.3.4 exclude heterozygous sites present in normal individuals;
2.3.5 excluding sites where neither parent had the corresponding mutation;
2.3.6 excludes genes having only one mutation site.
2.4X-linked recessive genetic patterns;
2.4.1 extracting X chromosome region exons and exon cleavage region nonsensical mutations;
2.4.2 screening of patients for all homozygous sites (1/1) or semi-homozygous sites (1);
2.4.3 the site with mutation type 0/0|0/1 in normal female individuals;
2.4.4 the site with mutation type 0 in normal men;
2.4.5 reserving the locus where all variants are present in the parent;
2.4.6 if the patient is female, the father is normal, such variant sites are excluded.
2.5X-linked dominant inheritance pattern;
2.5.1 extracting X chromosome region exons and exon cleavage region nonsensical mutations;
2.5.2 screening patients for all heterozygous sites (0/1) or semi-homozygous sites (1);
2.5.3 the site with a mutation type of 0/0 in normal female individuals;
2.5.4 remains at the site of mutation type 0 in normal men;
2.5.5 these sites are excluded if the patient is female, the parent is normal, or the patient is male, the mother is normal.
2.6 New mutations
2.6.1 extracting chromosomal region exons and exon cleavage region non-synonymous mutations;
2.6.2 screening of patients for all homozygous sites (1/1) or semi-homozygous sites (1);
2.6.3 retains a mutation site of 0/0|0 in normal individuals;
2.6.4 the mutation site where only one individual appears in the offspring individuals;
2.6.5 the mutation sites that also occur in other patients are excluded.
Wherein the above (3) specifically comprises
3.1 based on the analysis of the steps, in the analysis result of the method of the patent, a plurality of index information such as mutation types, mutation frequencies, genetic patterns, mutation notes and the like of the trio family individuals can be given so as to facilitate subsequent further information mining.

Claims (1)

1. The analysis method of the genetic mutation pattern of the trio family based on the second-generation high-throughput sequencing is characterized by comprising the following steps:
(1) A multi-index information matrix creation step: considering specific mutation site conditions and simultaneously combining the relevant phenotype information such as sex and disease state information of an individual, and constructing the information into a matrix so as to analyze corresponding genetic patterns of mutation sites in a targeted manner;
(2) A genetic pattern judgment step: correspondingly judging mutation genetic modes of the trio family according to the multi-index information matrix, wherein the judging genetic modes comprise: a sex-linked dominant recessive genetic pattern, an X-linked dominant recessive genetic pattern, a composite heterozygous mutant genetic pattern, and a new-born mutant genetic pattern;
(3) And a result information integration step: the variety of information such as mutation types, mutation frequencies, genetic patterns, mutation notes and the like of trio family individuals is convenient for subsequent further information mining;
the step (1) specifically comprises the following steps:
1) Phenotype information classification: classifying and identifying the disease state of the individual to be used for assisting in screening corresponding possible pathogenic mutation sites;
2) Gender information identification: identifying the diseased state of the individual for judging the genetic mode of the subsequent mutation site;
3) Creating a mutation site matrix: comparing the mutation site information of a plurality of individuals to generate a mutation matrix for judging the subsequent mutation mode;
in the step (2), the judgment of the dominant inheritance pattern of the autofection body is specifically:
1) A dominant inheritance pattern of autosomal dominant;
2) Extracting the autosomal region exon and exon splice region non-synonymous mutation;
3) Screening the patient for all heterozygous or homozygous sites;
4) Retaining variant sites that did not occur in all normal individuals;
5) Further screening the sites of variation on at least one of the parents;
6) Obtaining candidate harmful mutation sites;
in the step (2), the judgment of the dominant sex-recessive genetic pattern is specifically:
1) Extracting the autosomal region exon and exon splice region non-synonymous mutation;
2) Screening all homozygous sites in the patient;
3) Retaining all mutation sites that were 0/1|0/0 in normal individuals;
4) The mutation sites which are 0/1 in the parent are reserved;
5) Obtaining candidate harmful mutation sites;
in the step (2), the judgment of the composite heterozygous mutation genetic mode specifically includes:
1) Extracting the autosomal region exon and exon splice region non-synonymous mutation;
2) Screening the patient for all heterozygous sites;
3) A gene retaining at least 2 heterozygous mutation sites;
4) Excluding heterozygous sites present in normal individuals;
5) Excluding sites where no corresponding mutation is found on the parents;
6) Excluding genes with only one mutation site;
in the step (2), the judgment of the X-linked recessive genetic pattern is specifically:
1) Extracting non-synonymous mutation of exon and exon cutting region of X chromosome region;
2) Screening the patient for all homozygous or semi-homozygous sites;
3) A site with a mutation type of 0/0|0/1 remaining in a normal female individual;
4) A site with mutation type 0 remaining in normal men;
5) The sites where all the variants were present in the parent were retained;
6) If the patient is female and the father is normal, such variant sites are excluded;
in the step (2), the judgment of the dominant inheritance pattern of the X-linked specifically includes:
1) Extracting non-synonymous mutation of exon and exon cutting region of X chromosome region;
2) Screening the patient for all heterozygous or semi-homozygous sites;
3) A site that retains a mutation type of 0/0 in a normal female individual;
4) A site with mutation type 0 remaining in normal men;
5) These sites are excluded if the patient is female, the parent is normal, or the patient is male, the mother is normal;
in the step (2), the determination of the genetic pattern of the new-born mutation specifically includes:
1) Extracting the non-synonymous mutation of the exon in the chromosome region and the exon cutting region;
2) Screening the patient for all homozygous or semi-homozygous sites;
3) A mutation site that remains at 0/0|0 in normal individuals;
4) A mutation site where only one individual appears in the offspring individuals is retained;
5) The mutation sites that also occur in other patients are excluded.
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CN110648722B (en) * 2019-09-19 2022-05-31 首都医科大学附属北京儿童医院 Device for evaluating neonatal genetic disease risk
CN111354418B (en) * 2020-01-19 2023-02-10 上海欧易生物医学科技有限公司 High-throughput sequencing technology animal tRFs data analysis method based on reference genome annotation file
CN111653316A (en) * 2020-05-27 2020-09-11 上海寻因生物科技有限公司 Visualization analysis method, system and storage medium based on next generation sequencing
CN112908412A (en) * 2021-02-10 2021-06-04 北京贝瑞和康生物技术有限公司 Methods, devices and media for compounding the applicability of heterozygous variant pathogenic evidence
CN112967756B (en) * 2021-03-30 2022-07-26 上海欧易生物医学科技有限公司 High-throughput sequencing quality control analysis method based on Snakeman language and capable of rapidly feeding back mail feedback results in batches

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105925685A (en) * 2016-05-13 2016-09-07 万康源(天津)基因科技有限公司 Exome potential pathogenic mutation detection method based on family line
CN106119353A (en) * 2016-06-25 2016-11-16 广州泰因生物科技有限公司 A kind of quick screening method of dominant family heredopathia pathogenic sites
WO2018051072A1 (en) * 2016-09-16 2018-03-22 Genomics Plc Methods and apparatus for identifying one or more genetic variants associated with disease in an individual or group of related individuals
CN108220403A (en) * 2017-12-26 2018-06-29 北京科迅生物技术有限公司 Detection method, detection device, storage medium and the processor in specific mutation site

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102222175A (en) * 2011-05-06 2011-10-19 西南大学 Method for developing functional molecular marker related to miRNA
CN105349617A (en) * 2014-08-19 2016-02-24 复旦大学 High-throughput RNA sequencing data quality control method and high-throughput RNA sequencing data quality control apparatus
CN105528532B (en) * 2014-09-30 2019-08-16 深圳华大基因科技有限公司 A kind of characteristic analysis method in rna editing site
CN105112569B (en) * 2015-09-14 2017-11-21 中国医学科学院病原生物学研究所 Virus infection detection and authentication method based on metagenomics
CN107103205A (en) * 2017-05-27 2017-08-29 湖北普罗金科技有限公司 A kind of bioinformatics method based on proteomic image data notes eukaryotic gene group
CN107577919A (en) * 2017-08-21 2018-01-12 上海派森诺生物科技股份有限公司 A kind of grand genomic data analysis method based on high throughput sequencing technologies
CN107828857A (en) * 2017-11-23 2018-03-23 南宁科城汇信息科技有限公司 A kind of transcript profile sequencing and RNAseq data analysing methods

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105925685A (en) * 2016-05-13 2016-09-07 万康源(天津)基因科技有限公司 Exome potential pathogenic mutation detection method based on family line
CN106119353A (en) * 2016-06-25 2016-11-16 广州泰因生物科技有限公司 A kind of quick screening method of dominant family heredopathia pathogenic sites
WO2018051072A1 (en) * 2016-09-16 2018-03-22 Genomics Plc Methods and apparatus for identifying one or more genetic variants associated with disease in an individual or group of related individuals
CN108220403A (en) * 2017-12-26 2018-06-29 北京科迅生物技术有限公司 Detection method, detection device, storage medium and the processor in specific mutation site

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
C3肾病遗传特征分析及基因突变检测;赵玮玮;《中国优秀硕士学位论文全文数据库 医药卫生科技辑》;20180915(第09期);全文 *

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