中文摘要
隨著全球生活環境改善與醫療科技的突飛猛進，人類生活品質因而普遍提升，平均壽命也因此延長，但對許多已開發或開發中國家而言，伴隨而來的是高齡化人口結構的形成，造成慢性病患者數目逐漸增加，成為國家醫療支出與社會福利負擔的一大隱憂。隨著基因體學(genomics)的興起，科學家開始探討「個人基因體學」(personal genomics)的基因、飲食與疾病間的相互關聯性，期望能解碼上述系統，達到生活管理與疾病預防，甚至預測之目的，如藉由個人基因檢測確認是否容易罹患代謝症候群(metabolic syndrome)，並針對飲食調整達到預防效果。

使用次世代定序技術可以清楚明確的檢視我們的生命遺傳密碼，再結合過去累積的醫療知識，若是能夠在生命尚未受到疾病的侵襲之前，就能對其由所防範甚至是事先處理這正是醫學上的終極目標。現代醫學中，基因檢查已經占據越來越重要的地位，近年來癌症治療也多有藉由多基因檢查來預測效果，由於次世代定序的發展，基因數目已從過去的單一基因到現在大量基因檢查。

本文規劃了一套次世代定序資料的處理流程，並展現了公共資料庫在解讀基因體資料的可行性與方式，在分析疾病方面則是展現了單基因疾病、多基因疾病、粒線體變異疾病的檢索方式。

關鍵字: 次世代定序、遺傳疾病、預防醫學

Next Generation Sequencing for Genetic disorder information retrieval

Chiang-Ni Lu
Chi-Chuan Hwang
Department of Engineering Science National Cheng Kung University

SUMMARY
With the improvement of the living environment and the technology medical science. Thus enhance the quality of our life in general, the average life expectancy is therefore extended. And for many developed or developing countries, accompanied by the formation of Population aging. Resulting in increasing number of patients with chronic, and become one of major concerns of healthy spending and social welfare burden.

In modern medical science, Oncogene detection has occupied an increasingly important position. There are also many cancer treatment in recent years by multiple gene detection to predict the effect. Due to the development of next-generation sequencing, the number of genes from single gene to large number of gene detection.

In this paper, we plan a set of data processing of next-generation sequencing data. And demonstrate the feasibility of a public database in the way of interpretation of genomics. In terms of the disease analysis is to show the retrieval methods of Single gene disorder, Multifactorial and polygenic (complex) disorders, Mitochondrial disease.

Key words: Next-generation sequencing, genetic diseases, preventive medicine

Introduction

Genetic testing, also known as DNA testing, allows the genetic diagnosis of vulnerabilities to inherited diseases, and can also be used to determine a child's parentage (genetic mother and father) or in general a person's ancestry. In addition to studying chromosomes to the level of individual genes, genetic testing in a broader sense includes biochemical tests for the possible presence of genetic diseases, or mutant forms of genes associated with increased risk of developing genetic disorders. Genetic testing identifies changes in chromosomes, genes, or proteins. Most of the time, testing is used to find changes that are associated with inherited disorders. The results of a genetic test can confirm or rule out a suspected genetic condition or help determine a person's chance of developing or passing on a genetic disorder.

In the past, Oncogene detection is mainly for genetic diseases of single gene. However, most of these diseases are rare diseases, and the probability of getting such disease is less than a million. Currently, the new mainstream of preventive Oncogene detection is aimed to check for the Multifactorial and polygenic (complex) disorders. The complex multi-gene is caused by multiple genetic abnormalities.

The purpose of this study is based on preventive medicine. Through next-generation sequencing machine to detect Oncogene, and read the genetic code using Next-generation sequencing technology. Sequencing detection of Multiple-gene, which allows some of the symptoms of the disease complex judgments become more simple.

In this paper, we plan a set of data processing of next-generation sequencing data. And demonstrate the feasibility of a public database in the way of interpretation of genomic . In terms of the disease analysis is to show the retrieval methods of Single gene disorder, Multifactorial and polygenic (complex) disorders, Mitochondrial disease.

Materials and Methods

This study has been cooperate with Genetech Biotech company (GTBio) which is the agents of Illumina in Taiwan. We obtain three whole-genome sequencing from GTBio, and the sequence data is a family with depth sequencing about 42x. We use the code NA12878 (female, mother), NA12891 (male, father), NA12892 (female, daughter) to show them.

Using the database of OMIM, KEGG, GWAS, MalaCards & GeneCards to describe the characteristics of genetic diseases within the human genome.

Results and Discussion

In this paper, we plan a set of data processing of next-generation sequencing data. And demonstrate the feasibility of a public database in the way of interpretation of genomic. In terms of the disease analysis is to show the retrieval methods of Single gene disorder, Multifactorial and polygenic (complex) disorders, Mitochondrial disease.

Currently, analysis of genetic variation in polygenic disease only reached a rough estimate of someone's risk of common diseases level. With the discovery of more variation, we will make some adjustment to improve the accuracy of detection.

Most of various diseases is not result from a single factor. In addition to differences of gene expression of each person, the environmental factors, exposure to harmful substances, living and eating habits are likely to interact with gene expression, and changes susceptibility to the disease. Therefore, cumulate the haplotype data to create a Haplotype database of Chinese is the basic method to further illustrate the variation.

Table 1 NA12891 point mutation in each of the functional distribution of the original
SNVs Deletions Insertios
Total Number 3495306 189164 189941
Number in Genes 1585193 86955 86894
Number in Exons 47933 1933 2079
Number in Coding Regions 21604 221 249
Splice Site Regions 3102 209 198
Stop Gained 76 0 1
Stop Lots 10 0 0
Frameshift 0 95 111
Non-synonymous 10217 126 138
Synonymous 11301 0 0
Mature miRNA 38 8 2
UTR Region 26329 1712 1830

Table 2 NA12891 distribution of structural variation
SV Type Count % in Genes
CNV 61 37.70%
Tandem Duplication 142 32.39%
Inversion 287 35.89%
Deletion 54702 10.53%
Insertion 16756 38.91%

Conclusion
1. We show the retrieval methods of Single gene disorder, Multifactorial and polygenic (complex) disorders, Mitochondrial disease by using the example of Huntington's disease, familial hypercholesterolemia, gastric cancer, Leber's optic atrophy.
2. Using the next-generation sequencing to conduct large number of gene detection.
3. We plan a set of data processing of next-generation sequencing data.

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