1. 2010/07/01
kaneko.satoko(at)ocha.ac.jp

2. ( )

3. 1
O E
2 F2
3 1
2 2
O
E
(O‐E)
(O‐E)2
(O‐E)2/E
5475
5493
‐19
361
0.06572
1850
1831
19
361
0.19716
1 5% 3.84 chi square
F2
: 3:1

4. 1
5% 3.84, 1% 6.63
3.84 0.95(95%)
0.05(5%) 3.84 5%
O E
3.84
6.63

5. 1 R
2 F2
3 1
> obs1 <‐ 5474
> obs2 <‐ 1850
> exp1 <‐ (obs1+obs2)*(3/4) 3:1
> exp1
> exp2 <‐ (obs1+obs2)*(1/4)
> exp2
> dev1 <‐ obs1‐exp1
5474
1850
> num1 <‐ (dev1)^2
> dev2 <‐ obs2‐exp2
5493
1831
> num2 <‐ (dev2)^2
> chi1 <‐ num1/exp1
> chi2 <‐ num2/exp2
> chi <‐ chi1+chi2 O E
> chi
[1] 0.2628800

6. 2
Makorin1‐p1 regionB regionC
regionB regionC number of differences
(region B 617bp, regionC 639bp )
domesVcus molossinus
2 2
O
E
(O‐E)
(O‐E)2
(O‐E)2/E
regionB
6
6.758998 ‐0.758998 0.576078
0.08523127
regionC
7
6.213938 0.786062 0.6178935
0.0994367
* regionB regionC (7/639)*617
regionC regionB (6/617)*639
processed pseudogene

7. 2 R
Makorin1‐p1 regionB regionC
regionB regionC number of differences
region B 617bp, regionC 639bp
regionB
regionC
> obsB <‐ 6
dom‐mol 6 7
> obsC <‐ 7
> expB <‐ (obsC/639)*617 dom‐mol 6.758998 6.213938
> expB
[1] 6.758998
expC <‐ (obsB/617)*639
> expC
[1] 6.213938
> devB <‐ (obsB‐expB) O E
> devC <‐ (obsC‐expC)
> chiB <‐ (devB^2) /expB
> chiC <‐ (devC^2)/expC
> chisqrt <‐ chiB+chiC
> chisqrt
[1] 0.1846679 # 3

8. region B 617 bp
region C 639 bp
pair
observed
expected
observed
expected
chi square
dom – mol
6
6.758998 7 6.213938
0.18
dom – cas
6
7
dom – mus
8
8
dom – spr
16
14
dom – car
30
39
mol – spr
14
17
mol – car
28
38
cas – spr
14
17
cas – car
28
38
mus – spr
14
18
mus – car
28
39
spr – car
32
37

9. 3 R
CotEditor chi‐square‐test.R
[Macintosh HD/ /tg03/bin]
expB <‐ (obsC/639)*617
expC <‐ (obsB/617)*639
devB <‐ (obsB‐expB)
devC <‐ (obsC‐expC)
chiB <‐ (devB^2) /expB O E
chiC <‐ (devC^2)/expC
chisqrt <‐ chiB+chiC
obsB obsC
> obsB <‐
> obsC <‐
> source("/Users/tg03/bin/chi‐square‐test.R")
bin
> source("chi‐square‐test.R")
> expB
> expC
> chisqrt

10. ( )
Makorin1‐p1 regionB regionC
regionB regionC number of differences
O E
pair
regionB regionC
95%, 1
> qchisq(0.95, 1)

11. ( )
region B 617 bp
region C 639 bp
pair
observed
expected
observed
expected
chi square
dom – mol
6
6.759 7 6.214 0.18
dom – cas
6
6.759 7
6.214 0.18
dom – mus
8
7.725 8
8.285 0.02
dom – spr
16
13.518 14
16.571 0.85
dom – car
30
37.657 39
31.070 3.58
mol – spr
14
16.415 17
14.499 0.79
mol – car
28
36.692 38
28.998 4.85 *
cas – spr
14
16.415 17
14.499 0.79
cas – car
28
36.692 38
28.998 4.85 *
mus – spr
14
17.380 18
14.499 1.50
mus – car
28
37.657 39
28.998 5.93 *
spr – car
32
35.726 37
33.141 0.84
* : p < 0.05
molossinus, castaneus, musculus caroli regionB regionC
5%

12. Makorin1‐p1 Makorin1 mRNA
Makorin1‐p1 regionB Makorin1
Makorin1‐p1 regionB
regionC
regionB regionC
molossinus, castaneus, musculus caroli regionB regionC
5%
regionB
‐ ‐
Makorin1‐p1 M. caroli
regionI
processed pseudogene CpG
regionII 600bp
5

13. ‐hemoglobin ‐
(molecular clock)
1960 c
DNA
Hemoglobin subunit alpha (Hemoglobin alpha chain)
3 exons, CDS 577bp (142a.a.)
2

14. 1 – hemoglobin‐
1) TogoWS REST
2) R p distance
3) x y p distance
human
human
uniprot ID
p distance
( )
human
HBA_HUMAN
‐
horse
HBA_HORSE
80
wallaby
HBA_MACEU
150
chicken
HBA_CHICK
300
frog
HBA_XENTR
350
zebra fish
HBA_DANRE
420

15. 2 – hemoglobin‐
1) TogoWS REST
apple mark+a R
2) R p distance
> library(Biostrings)
> human <‐ “HBA_human ”
> len <‐ AAString(human)
> total <‐ length(len) #
> horse <‐ “”
> comp <‐ c(compareStrings(human, horse)) #
> subs <‐ gsub(“([‘?’])”, “”, comp) #compareStrings ?
> aas <‐ AAString(subs)
> aasame <‐ length(aas) #
> dif <‐ (total‐aasame) #
> pdis <‐ dif/total
#human‐horse, human‐wallaby, human‐chicken, human‐frog, human‐zebra fish
#compareStrings() zebra fish
YFSHW A DLSPG A(48 ) R
3) x y p distance

16. – hemoglobin‐
x <‐ c(80,150,300,350,420)
y <‐ c(0.120,0.197,0.296,0.423,0.465)
plot(x,y,xlim=c(0,450), ylim=c(0,0.5))
human
uniprot ID
p distance
( )
human
HBA_HUMAN
‐
horse
HBA_HORSE
80
0.120
wallaby
HBA_MACEU
150
0.197
chicken
HBA_CHICK
300
0.296
frog
HBA_XENTR
350
0.423
zebra fish
HBA_DANRE
420
0.465
1960
olfactory receptor

17. –Makorin1, Makorin2‐
1) TogoWS REST
2) R p distance
3) x y p distance
human
alignment
* 1 Makorin1
2 Makorin2 Makorin1 alignment
human
uniprot ID
p distance
( )
human
MKRN1_HUMAN
193‐401
‐
mouse
MKRN1_MOUSE
193‐401
80
wallaby
MKRN1_MACEU
189‐397
150
frog
MKRN1_XENLA
159‐367
350
zebra fish
MKRN1_DANRE
148‐356
420
mouse
MKRN2_MOUSE
150‐358
80

18. –Makorin1, Makorin2‐
1) TogoWS REST
2) R p distance
library(Biostrings)
> human <‐ ""
> all1 <‐ AAString(human)
> humanc <‐ substring(all1, 193, 401) #
> total <‐length(humanc)
> mouse <‐ ""
> all2 <‐ AAString(mouse)
> mousec <‐ substring(all2, 193, 401)
> comp <‐c(compareStrings(humanc, mousec)) #
> subs <‐gsub("(['?'])", "", comp)
> aas <‐ AAString(subs)
> aasame <‐ length(aas)
> diff <‐ (total‐aasame)
> pdis <‐ diff/total
#human‐mouse, human‐wallaby, human‐frog, human‐zebra fish, human‐mouse2
3) x y p distance

19. –Makorin1, Makorin2‐
x <‐ c(80,150,420,350,80)
y <‐ c(0.024,0.053,0.177,0.139,0.407)
plot(x,y,xlim=c(0,450), ylim=c(0,0.5))
human
uniprot ID
p distance
( )
human
MKRN1_HUMAN
‐
mouse
MKRN1_MOUSE
80
0.024
wallaby
MKRN1_MACEU
150
0.053
frog
MKRN1_XENLA
350
0.139
zebra fish
MKRN1_DANRE
420
0.177
mouse
MKRN2_MOUSE
80
0.407
Makorin1 hemoglobin
Makorin1
Makorin1
Makorin1 Makorin2 Makorin1
Makorin1 human‐zebra fish
Makorin2
ortholog

20.
R Biostrings