Single Nucleotide Polymorphism

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Presentation transcript:

Single Nucleotide Polymorphism “ From Genetics to Pharmacogenomics ” What are SNPs ? Single Nucleotide Polymorphism 1. 리포솜의 정의 = 화면 2. 리포솜은 표적 지향화에 쓰이는 약물운반체로써, 1. 분자성 운반체- 저분자성운반체(프로드럭), 고분자성 운반체(알부민, 키토산,텍스트 린, 합성고분자 등) but, 약물결합위한 관능기, 합성방법 필요 2. 미립자성 운반체 - 어떤 화학구조도 가능, 간단히 조제가능. 지질과 고분자 매트릭스 지질 제제의 대표가 리포솜과 에멀전이다. 리포솜은 1965년 bangham에 의해 리 포솜 생성 보고이래 생체막의 모델로 연구됨. ( 에멀젼 - 액체중 서로 혼합안된는 액체를 유화제의 도움으로 안정하게 분산시키는것 ) 3. 생물유래의 운반체 , 항원 등이 있다. 3. 약물 운반체로 쓰이는 이유 - 수용성 약물및 지용성 먁물을 봉입할 수 있고 리포솜에 사용하는 인지질이 체내에서 분해가 가능하며, 독성이 없고, 항원성이 없는 장점이 있기 때문이다. 특히 약물의 지속화가 가장 큰 중요 요소중의 하나이다. 리포솜 봉입 약물의 방출은 약물의 물리화학적 성질, 인지질 이중막의 물리적인 상태와 화학적 조성에 달려 있으며 리포솜이 생체조직이나 생체액과의 상호작용에도 달려있다. 4. 즉, 약물에의 적용은 = 화면 5. 참고로 크기와 인지질 수로 3종류로 구분 ( 지질 2분자막과 내부수상으로 구성) MLV(multilamellar vesicle-다중층 리포솜 - 지질 2분자막이 여러층으로 겹쳐진 구조로 직경 수백-수천nm의 소포체로 가장 많이 이용된다.) LUV (large unilamellar vesicle- 큰 단일막 리포솜- 에테르 주입법이나 Ca2+이용 SUV 를 융합시킨다. 단백질이나 DNA같은 고분자 봉입에 좋다. ) SUV (small unilamellar vesicle0 작은 단일막 리포솜- MLV를 초음파 처리하여 만들고 지경이 수십 nm인 SUV를 만들수 있따. 이외 익스트루더, 에테르주입법, french press등을 이용한다. (단점이 있다. =====>) SNP Genetics

What are SNPs ? Single nucleotide polymorphisms consist of a single ACGTTTGGATAC ACGTTTGTATAC TGCAAACCTATG TGCAAACATATG Single nucleotide polymorphisms consist of a single change in the DNA code SNPs occur with various allele frequencies. Those in the 20-40% range are useful for genetic mapping. Those at frequencies between 1% and 20% may be used with candidate gene approaches. Usually bi-allelic. Changes at 〈1% are called variants 1. 리포솜의 정의 = 화면 2. 리포솜은 표적 지향화에 쓰이는 약물운반체로써, 1. 분자성 운반체- 저분자성운반체(프로드럭), 고분자성 운반체(알부민, 키토산,텍스트 린, 합성고분자 등) but, 약물결합위한 관능기, 합성방법 필요 2. 미립자성 운반체 - 어떤 화학구조도 가능, 간단히 조제가능. 지질과 고분자 매트릭스 지질 제제의 대표가 리포솜과 에멀전이다. 리포솜은 1965년 bangham에 의해 리 포솜 생성 보고이래 생체막의 모델로 연구됨. ( 에멀젼 - 액체중 서로 혼합안된는 액체를 유화제의 도움으로 안정하게 분산시키는것 ) 3. 생물유래의 운반체 , 항원 등이 있다. 3. 약물 운반체로 쓰이는 이유 - 수용성 약물및 지용성 먁물을 봉입할 수 있고 리포솜에 사용하는 인지질이 체내에서 분해가 가능하며, 독성이 없고, 항원성이 없는 장점이 있기 때문이다. 특히 약물의 지속화가 가장 큰 중요 요소중의 하나이다. 리포솜 봉입 약물의 방출은 약물의 물리화학적 성질, 인지질 이중막의 물리적인 상태와 화학적 조성에 달려 있으며 리포솜이 생체조직이나 생체액과의 상호작용에도 달려있다. 4. 즉, 약물에의 적용은 = 화면 5. 참고로 크기와 인지질 수로 3종류로 구분 ( 지질 2분자막과 내부수상으로 구성) MLV(multilamellar vesicle-다중층 리포솜 - 지질 2분자막이 여러층으로 겹쳐진 구조로 직경 수백-수천nm의 소포체로 가장 많이 이용된다.) LUV (large unilamellar vesicle- 큰 단일막 리포솜- 에테르 주입법이나 Ca2+이용 SUV 를 융합시킨다. 단백질이나 DNA같은 고분자 봉입에 좋다. ) SUV (small unilamellar vesicle0 작은 단일막 리포솜- MLV를 초음파 처리하여 만들고 지경이 수십 nm인 SUV를 만들수 있따. 이외 익스트루더, 에테르주입법, french press등을 이용한다. (단점이 있다. =====>)

What are the effects of SNPs ? Where Result Effect In coding region May be silent, o.g.,UUG→CUG, leu in both cases sSNP Usually no change in phenotype In coding region May change amino acid sequence, e.g., UUC→UUA, phe to leu, Some characterize these as the least common and most valuable SNPs, Many being patented cSNP Phenotype change (may be subtle depending on amino acid replacement and position) In coding region May create a "Stop"codon, e. g., UCA→UGA, ser to stop May affect the rate of transcription (up-or down-regulate) Possible phenotype Change Other regions No affect on gene products(7). May act as genetic markers for multi-component diseases. These are sometimes called anonymous SNPs and are the most common. rSNP

How many SNPs are there ? It is estimated that the human genome contains between 3 million and 6 million SNPs spaced irregularly at intervals of 500 to 1,000 bases. The SNP Consortium estimates that as many as 300,000 SNPs may be needed to fuel studies. 100.000 or more SNPs may be required for complex disease gene discovery

SNP Discovery Applications SNP Validation - Fine Mapping SNP Screening - Testing

SNP Discovery SNP Discovery refers to the initial identification of new SNPs. The established method is electrophoresis(DNA sequencing) with subsequent data analysis. Some indirect Discovery techniques (e.g., dHPLC, SSCP) only indicate that a SNP (or other mutation) exists. DNA sequencing of multiple individuals is used to determine the point and type of polymorphism. Low throughput, based on established DNA sequencing analyses or collected data (also based on electrophoretic data)

SNP Validation SNP Validation refers to genetic validation, the process of ensuring that the SNP is not due to sequencing error and that it is not extremely rear. This should not be confused with assay, target or regulatory validation. Confirmation of SNPs found in Discovery Larger numbers of individual samples to get statistical data on occurrence in the population

SNP Screening SNP Screening refers to researchers running thousands of genotypes (may SNPs or many individuals or both) Thousands to hundreds of thousands of samples per day Two different screening strategies - Many SNPs in a few individuals - A few SNPs in many individuals Different strategies will require different tools Important in determining markers for complex genetic states

SNP analysis costs are dependent on volume Costs per assay are dependent upon the number of SNPs being analyzed and the number of individuals. Running cost - one SNP in 100 individuals∼range $5∼$8/assay - one SNP in 1,000 individuals∼range $3∼$5/assay. - 1000 SNPs in 1000 individuals∼range $1.5~$3.00/assay. - All these costs include the cost of the PCR step. Future high through-put costs/assay will be driven toward pennies per SNP.

What is a DNA Array ? A collection of nucleic acid probes which are attached to a surface in a predetermined grid This grid is exposed to targets from a biological sample and the complementary pairs are detected ("hybridization") The complementary pairs are scored by software

What Good are DNA Arrays ? - nucleotide changes anywhere in a genome - identity of and amount of unique mRNAs - re-sequencing Ideal for Screening large# SNPs: Present formats not really a high throughput format but by their massive parallelism they enable certain types of analyses, e.g. global expression profiling or genome wide SNP screening

DNA Arrays Are Valuable Arrays allow massively parallel analysis for certain applications this parallelism is enabling...i.e., global expression profiling For certain applications there may be labor savings..i.e., comparative sequencing But...the present formats are not yet high throughput technology Platform Extensions for SNP Screening in Pharmaceuticals

Researcher determinants Infrastructure: - Lab. Instrument, labor & expertise Investment: - Start-up cost & running cost Jobs: - How big sample size ? - How many SNPs ? Best Choice - Out-sourcing ?

Technology Platform Extension for SNP Screening High Array # of SNPs Mass Spec. RFLP TaqMan SBE Low Low # of Individuals High

Addendum

TSC I : The SNP Consortium Pharmaceutical Partners: AstraZeneca, Bayer, Bristol-Myers Squibb Co., GlaxoWellcome PLC, Hoffmann-LaRoche, Hoechst Marion Roussei, (now merged with RPR to form Aventis), Merck, Pfizer lnc, Searle, SmithKline Beecham PLC. Academic Partners: The Whitehead lnstitute at MIT, Wellcome Trust at the Sanger Center,Stanford

TSC II : The SNP Consortium At least $45 million ($3 million per pharmaceutical company, $14 million form Wellcome Trust) Reduction from %150 million in large part to the efforts of Celera and NHGRI to sequence entire genome.

What is happening now ? Japanese SNP Project: $ 5 Million over next two years to map 100K to 150K SNPs. Probably concentrated at one site (U. Tokyo's Human Genome Center) Funded by Science & Technology Agency, Ministry of Health & Welfare and private sector.