Multiple sequence alignment (MSA)

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Gerard Brooks
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1 Multiple sequence alignment (MSA)

2 From pairwise to multiple A T _ A T C A... A _ C A T _ A... A T _ G C G _... A _ C G T _ A... A T C A C _ A... _ T C G A G A... Relationship of sequences (Tree)

4 NODE : a node represents a taxonomic unit. This can be a taxon (an existing species) or an ancestor (unknown species : represents the ancestor of 2 or more species). BRANCH : defines the relationship between the taxa in terms of descent and ancestry. TOPOLOGY : is the branching pattern. BRANCH LENGTH : often represents the number of changes that have occurred in that branch. ROOT : is the common ancestor of all taxa. DISTANCE SCALE : scale which represents the number of differences between sequences (e.g. 0.1 means 10 % differences between two sequences)

5 MSA is useful for bioinformatics Phylogenetic tree Motifs Structure prediction (RNA, protein) Gene Logo Conserved sequence elements

7 ClustalW procedure The progressive method e.g. ClustalW Step 1.) Pairwise alignments Step 2.) Build guide tree Step 3.) Progressive alignment guided by the tree

9 The BLOSUM62 matrix Step1. Pairwise alignments Pairwise sequence alignments Scoring matrix Gap penalties Global/Local alignments

11 Step 2. Build guide tree Neighbor-Joining Algorithm UPGMA

12 Neighbor-Joining Algorithm Step1: 準備三個 matrix: P T Q A B C D = 18 A B C D A A 18 B B 24 C C 18 D D 20 P TotalDistance T Q i,j = (n-2)*p i,j - T i - T j A B C D A B C D Q Q i,j = (4-2)* = -26

13 Neighbor-Joining Algorithm Step2: 從 Q 找出最小的值, 選其中一組出來合併 A B A B C D A A 18 A B C D A B B 24 B C D C D C 18 D 20 C D P T Q A,C B,D

14 Neighbor-Joining Algorithm Step3: 合併 A,C, 產生新的 P T Q A 2 B A,C B A,C B D A,C B A,C B A,C B D C D D D P T D Q 1) 從前一個 P T, 計算 A,C 的距離 : n = 4 ( 因為 P 是 4x4 的 matrix) 4/2 + (18-18)/2(n-2) = 2 2) 把前一個 P 的對應值 ( 有跟 A,C 相關的 ) 都減去 2, 其他不受影響的值不變產生新的 P 再由新的 P 計算出新的 T Q

15 Neighbor-Joining Algorithm Step3: 合併 A,C, 產生新的 P T Q A 2 B A,C B D A,C B A,C 10 B 14 A,C B D A,C B C D D D 12 P T D Q 1) 從前一個 P T, 計算 A,C 的距離 : n = 4 ( 因為 P 是 4x4 的 matrix) 4/2 + (18-18)/2(n-2) = 2 2) 把前一個 P 的對應值 ( 有跟 A,C 相關的 ) 都減去 2, 其他不受影響的值不變產生新的 P 再由新的 P 計算出新的 T Q

16 A 2 B C D A 2 B =2 C D

17 重複 Step2, 合併 A,C,B 請同學算一次新的 P T Q

18 UPGMA Algorithm A B C D E A B C D E A B C D E

19 UPGMA Algorithm A,C B D E A B C D E A B C 找出最小的值, 選其中一組出來合併合併 A,C ( 距離直接對分 4/2=2) A,C B D E D E C A 2 2 B D E A B C D E

20 UPGMA Algorithm A,C B D E A B C D E A B C 找出最小的值, 選其中一組出來合併合併 A,C ( 距離直接對分 4/2=2) A,C B D E D E C A 2 2 B D E A B C D E 選擇最小的合併合併 B 與 E ( 距離直接對分 4/2=2) A,C B,E D A,C B,E D C A 2 2 B E 2 2 D

21 UPGMA 有時候有二組以上最小的圖片出處

22 UPGMA 有時 branch length 無法分配完美圖片出處

23 Step3. progressive alignment

24 Problems with progressive alignments Dependence of the initial pair-wise sequence alignment. Propagating errors form initial alignments.

25 Example This and next figures examples are from T-coffee paper: Noterdame, Higgins, Heringa, JMB 2000,

26 MUSCLE Robert C. Edgar* Nucleic Acids Research, 2004, Vol. 32, No There are three main stages: Stage 1. draft progressive Stage 2. improved progressive Stage 3. refinement

27 Robert C. Edgar* Nucleic Acids Research, 2004, Vol. 32, No

30 MUSCLE

31 MAFFT

34 Newick format (B,(A,C,E),D); (B:2,(A:1,C:1,E:1),D:3); More detailed:

35 MEGA

Homework APOBEC ("apolipoprotein B mrna editing enzyme, catalytic polypeptide-like") is a family of evolutionarily conserved cytidine deaminases.

40 Homework APOBEC ("apolipoprotein B mrna editing enzyme, catalytic polypeptide-like") is a family of evolutionarily conserved cytidine deaminases. A mechanism of generating protein diversity is mrna editing. Members of this family are C-to-U editing enzymes. The N-terminal domain of APOBEC like proteins is the catalytic domain, while the C-terminal domain is a pseudocatalytic domain. More specifically, the catalytic domain is a zinc dependent cytidine deaminase domain and is essential for cytidine deamination. RNA editing by APOBEC-1 requires homodimerisation and this complex interacts with RNA binding proteins to form the editosome. In humans/mammals they help protect from viral infections. [3] These enzymes, when misregulated, are a major source of mutation in numerous cancer types. (...from wiki)

41 Chen et al., APOBEC3A is an oral cancer prognostic biomarker in Taiwanese carriers of an APOBEC deletion polymorphism. Nature Communications 8:465, 2017

42 請用 Microsoft Word 或 PDF 格式編輯作業, 檔案名稱請用學號 _ 姓名例 : u _ 姓名繳交時間 : 3/28 15:30 前上傳至 ilms (1) How many human APOBEC family deposited in NCBI? (2) Do MSA and Tree visualization analysis using MAFFT, T-coffee, and MUSCLE. (DNA) (3) Are the MSA results the same? If not, why?

0 0 = 1 0 = 0 1 = = 1 1 = 0 0 = 1

0 0 = 1 0 = 0 1 = = 1 1 = 0 0 = 1 0 0 = 1 0 = 0 1 = 0 1 1 = 1 1 = 0 0 = 1 : = {0, 1} : 3 (,, ) = + (,, ) = + + (, ) = + (,,, ) = ( + )( + ) + ( + )( + ) + = + = = + + = + = ( + ) + = + ( + ) () = () ( + ) = + + = ( + )( + ) + = = + 0