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SPEAKER : TZU-CHUN LO ADVISOR : YAO-TING HAUNG RNA sequencing for differential expression genes.

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Presentation on theme: "SPEAKER : TZU-CHUN LO ADVISOR : YAO-TING HAUNG RNA sequencing for differential expression genes."— Presentation transcript:

1 SPEAKER : TZU-CHUN LO ADVISOR : YAO-TING HAUNG RNA sequencing for differential expression genes

2 Outline Molecular Central Dogma RNA Sequencing Differential Expression Gene Case–Control Study Negative Binomial Distribution Hypothesis Testing Rice SNP, QTL, Pathway

3 Molecular Central Dogma The central dogma of molecular biology describes the flow of genetic information within a biological system. Forest Branches BBQ

4 DNA RNA Alignment RNA Sequencing Gene 1Gene 2 reads exons mRNA Finding differential expression genes via read counts each gene. Spliced alignment Alignment Read counts DEG process

5 Differential Expression Gene We want to find the cold-resistant genes in rice. Rice genome We should compare with two conditions.  Room temperature  Low temperature Gene 1 Gene 2 Gene 3 Gene 1 Gene 2 Gene 3 Gene 1 Gene 2 Gene Cole-resistant differential expression genes :

6 Strategy for DEG Case–control study  Two existing groups differing in outcome are identified and compared on the basis of some supposed causal attribute. Question  Is the number adequate to the gene?  How to define the gene is differential expression? conditioncasecontrol Gene Gene Gene  69 v.s 71Almost the same  86 v.s 56  66 v.s 111 Possible DEG More likely DEG ……… Gene  80 v.s 60How to judge? It is just one of sample in condition. ? Negative binomial distribution Hypothesis test

7 Negative Binomial Distribution NB is a count data distribution that can substitute Poisson distribution for better variance. i j Gene abundance parameterSmooth function 3 j=1~mi=1~n 69 Library size parameter Smooth function is more complex, so let us forget it. 

8 FPKM An indicator used to represent mRNA expression. Fragments Per Kilobase of transcript per Million mapper reads. Genome Gene 1 Gene 2 Exon length: bases 10 4 reads

9 FPKM Before hypothesis testing, we have to get FPKM and variance of FPKM. K-Readscasecontrol Gene Gene Gene ……… Var(K)casecontrol Gene 1106 Gene Gene ……… FPKMcasecontrol Gene Gene Gene ……… Var(FPKM)casecontrol Gene Gene Gene ………

10 Hypothesis Testing Step 1 : You find some observations or clues support a novel idea. Step 2 : Assume a against opinion that you want to fight it. Step 3 : Go to test it and take a stand. p-value

11 T-test

12 FPKMcasecontrol Gene Gene Gene ……… Var(FPKM)casecontrol Gene Gene Gene ……… T-testGene 1Gene 2Gene 3… p-value …

13 Result Investigating Discussing alpha=0.05 with read counts & p-value. If alpha=0.04 or 0.03 ? We don’t know which alpha is the best, but we can do some subsequent processing. If alpha=0.05casecontrolp-valueresult Gene X Gene V Gene V Gene V

14 RNA sequencing for Rice Plan  Cold-resistant genes Samples  Japonica (TN67): room temperature (R), low temperature (L)  Indica (IR64): room temperature (R), low temperature (L) Rice  粳稻 (TN67) : 米粒闊而短,黏性較大, Q 彈,如 : 蓬萊米。  秈稻 (IR64) : 米粒細而長,黏性較小,易碎,如 : 在來米。 Zone  TN67 : High-latitude, or high altitude  IR64 : Low-latitude, or low altitude

15 TN67R IR64R TN67L IR64L Strategy for DEG Case–control study  Four combinations  Different varieties or distinct temperatures  Four sets of differential expression genes  The DEGs above combination (A,B,C,D) Negative binomial  Inference probability situation by sample Hypothesis test  Which is the DEG that we want Subsequent processing  SNP, QTL, Pathway A B C D

16 SNP A single-nucleotide polymorphism is a sequence variation occurring when a single nucleotide differs between members of a biological species. Case Control Assembly ATGCCCTCGTAA TTACTGCGT ATGCGCTCGAAA TTACTCCGT ATGCCCTCGTAA TTACTGCGT SNP

17 QTL Quantitative traits refer to phenotypes (characteristics) that vary in degree and can be attributed to polygenic effects (product of two or more genes) Quantitative trait loci (QTLs) are stretches of DNA containing or linked to the genes that underlie a quantitative trait. Ex : QT(cold) Loci : 599~799 (base) DNA Cold tolerance (29) & pollen fertility (43) QTL length : ~million bases genes QTL

18 Pathway Pathway is a collection of manually drawn pathway maps representing molecular interaction and reaction networks. Gene No.2 Gene No.55 Gene No.99 Rice Cold-resistant

19 Conclusion Review  RNA Sequencing  Differential Expression Gene  Case–Control Study  Negative Binomial Distribution  Hypothesis Testing Rice  SNP  QTL  Pathway

20 Variance of negative binomial NB is a count data distribution that can substitute poisson distribution for better variance.

21 Strategy for DEG

22 QTL 生物的另一類性狀例如人類的身高、體重、高 血壓、糖尿病;水稻株高及產量對疾病的抵抗程度;老鼠 的體脂肪百分比;乳牛的乳產量;雞的產卵量,由 於其變異性是連續性的,不易分類,且易受環境影響,故 稱為數量性狀( quantitative trait )。數量性狀是由多 個基因所控制,由於每個基因對數量性狀均有影響,所以 每一基因的作用便相對地小。這些控制數量性狀的 基因稱為微效基因( polygenes )或又稱為數量性狀基因 座 (quantitative trait loci , QTL) 。 Rice genome size 430Mb

23 QTL

24 Negative binomial distribution NB is a count data distribution that can inference adequate number by sample. i j Smooth function

25 Negative binomial distribution NB is a count data distribution that can substitute Poisson distribution for better variance.

26 Hypothesis test Step 1 : You find some observations or clues support a novel idea.() Step 2 : Assume a against opinion that you want to fight it. Step 3 : Go to test it and take a stand. p-value

27 Case-control example Example Question  Is the number adequate to the gene?  Negative binomial  How to define the gene is differential expression?  Hypothesis test conditioncasecontrol Gene Gene Gene ………  69 v.s 71Almost the same  86 v.s 56  66 v.s 111 Possible DEG More likely DEG

28 Variance of negative binomial NB is a count data distribution that can substitute Poisson distribution for better variance.

29 DNA RNA Alignment RNA sequencing Gene 1Gene 2 reads exons mRNA DNA We should align with regions above blue. Spliced alignment

30 RNA sequencing Spliced alignment  TopHat  Condition 1 : caseCondition 2 : control Sample123…123… Gene …737168… Gene …315649… Gene … … ………………………

31 Readscasecontrol Gene Gene Gene ……… Variancecasecontrol Gene Gene Gene ………


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