56
Genetic maps from my past, present and future from my Karl W Broman Biostatistics & Medical Informatics University of Wisconsin – Madison www.biostat.wisc.edu/~kbroman

Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

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Page 1: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Genetic mapsfrom my past, present and future from my

Karl W BromanBiostatistics & Medical InformaticsUniversity of Wisconsin – Madison

www.biostat.wisc.edu/~kbroman

Page 2: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Genetic mapsfrom my past, present and future from my

Karl W BromanBiostatistics & Medical InformaticsUniversity of Wisconsin – Madison

www.biostat.wisc.edu/~kbroman

Page 3: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Eucalypt genetic map

Byrne et al., Theor Appl Genet 91:869–875, 1995

3

Page 4: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Meiosis

4

Page 5: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Genetic distance

• Genetic distance between two markers (in cM) =

Average number of crossovers in the intervalin 100 meiotic products.

• “Intensity” of the crossover point process

• Recombination rate varies by– Organism

– Sex

– Chromosome

– Position on chromosome

5

Page 6: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Recombination fraction

We generally do not observe thelocations of crossovers; rather, weobserve the grandparental originalof DNA at a set of genetic markers.

Recombination across an intervalindicates an odd number ofcrossovers.

Recombination fraction =

Pr(recombination in interval) = Pr(odd no. XOs in interval)

6

Page 7: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Map functions

• A map function relates the genetic length of an interval and therecombination fraction.

r = M(d)

• Map functions are related to crossover interference, but a map function isnot sufficient to define the crossover process.

• Haldane map function: no crossover interference

• Kosambi: similar to the level of interference in humans

• Carter-Falconer: similar to the level of interference in mice

7

Page 8: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Ordering markers

ABC

∣∣∣∣∣∣abc

−→

ABC abcABc abCAbc aBCAbC aBc

Marker orders: A–B–C A–C–B B–A–C

With M markers, there are M!/2 possible orderings.

For M = 100, M!/2 ≈ 10157

8

Page 9: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Ordering markers

ABC

∣∣∣∣∣∣abc

−→

ABC abcABc abCAbc aBCAbC aBc

Marker orders: A–B–C A–C–B B–A–C

With M markers, there are M!/2 possible orderings.

For M = 100, M!/2 ≈ 10157

9

Page 10: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Ordering markers

ABC

∣∣∣∣∣∣abc

−→

ABC abcABc abCAbc aBCAbC aBc

Marker orders: A–B–C A–C–B B–A–C

With M markers, there are M!/2 possible orderings.

For M = 100, M!/2 ≈ 10157

10

Page 11: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Ordering markers

ABC

∣∣∣∣∣∣abc

−→

ABC abcABc abCAbc aBCAbC aBc

Marker orders: A–B–C A–C–B B–A–C

With M markers, there are M!/2 possible orderings.

For M = 100, M!/2 ≈ 10157

11

Page 12: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Eucalypt pedigree

A B C D● ●

● ●

● ● ●

118 progeny

12

Page 13: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Inferring phase(

A1

A2

∣∣∣∣ B1

B2or

A1

B2

∣∣∣∣ B1

A2

(C1

C2

∣∣∣∣ D1

D2or

C1

D2

∣∣∣∣ D1

C2

)

locus 1locus 2 AC AD BC BC

AC •AD •BC •BD •

• • • •• • • •• • • •• • • •

13

Page 14: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Eucalypt genetic map

Byrne et al., Theor Appl Genet 91:869–875, 1995

14

Page 15: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

CEPH pedigrees

1331 1332 1347

1362 1413 1416

884 102

● ●

● ●●●● ●

● ●

● ● ●● ●

● ●

● ●●

● ●

●● ●● ●● ●

● ●

●● ● ●

● ●

● ● ●● ●●

● ●

●●● ●● ●●

● ●●● ● ●●●

● ●

● ●●●● ●

● ●

● ● ●● ●

● ●

● ●●

● ●

●● ●● ●● ●

● ●

●● ● ●

● ●

● ● ●● ●●

● ●

●●● ●● ●●

● ●●● ● ●●●

15 14 13 12

2 1

3 4 5 6 7 8 9 10 11 16 17

16 15 14 13

2 1

3 4 5 6 7 8 9 10 11 12 17

15 14 13 12

2 1

3 4 5 6 7 8 9 10 11 16

16 15 14 13

2 1

3 4 5 6 7 8 9 10 11 12 17

19 21 18 20

2 1

3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

14 13 12 11

2 1

3 4 5 6 7 8 9 10 11 15 16

18 17 16 15

2 1

3 4 5 6 7 8 9 10 11 12 13 14

2 1

3 4 5 6 7 8 9 10 11 12 13 14 15 16

15

Page 16: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Marshfield maps: Tasks

• Assemble data

• Understand marker namesAFM, UT, CHLC (GATA etc.), Mfd, D*S*

• Identify cryptic duplicates

• Order markers and identify genotyping errorsRemoved 764 / 969,425 genotypes

16

Page 17: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

CRIMAP chrompic

1332-03 ma -11-i--11--111-i111-11-1111i--1111i-1111-i--11---1--11-1111-1-1i1---1...1332-03 pa 0000----0000000o00o00-000-000-0000o00-000-00000-00001---000-00-o000-0...

1332-04 ma -11-i--11--111-1111-11-i111i--i1111-1111-i--11---1--11-1111-1-11i--11...1332-04 pa 1111----1111111111i11-1i1-111-i111i11-111-11111-11111---111-11-1i1111...

1332-05 ma -11-i--11--111-i111-11-1111o--0000o-0000-o--00---0--00-0000-0-0o0--00...1332-05 pa 0000----0000000o00o00-000-111-1111i11-111-1111--11111---111-11-i11111...

1332-06 ma -00-o--00--000-o000-00-0000o--0000o-0000-o--00---0--00-0000-1-11i--11...1332-06 pa 1111----1111111i11i11-111-111-1111i11-111-11111-11111---111-11-1i1111...

1332-07 ma -00-o--00--000-o000-00-0000o--0000o-0000-o--00---0--00-0000-0-0o0--00...1332-07 pa 1111----1111111i11i11-111-111-1111i11-111-1111--11111---111-11-i11111...

1332-08 ma -10-o--00--000-00-0-00-0000o--o0000-0000-o--00---0--11-1111-1-1i1--11...1332-08 pa 0000----000000000-o00-010-000-o000o00-000-00000-00000---000-00-o00000...

1332-10 ma -11-i--1---111-i111-11-1111i--1111i-1111-i--11---1--11-1111-1-1i1--11...1332-10 pa 1000-----000000o00o00-000-000-0000o00-000-00000-00000---000-00-o00000...

1332-11 ma -11-o--00--000-o000-00-0000o--0000o-0000-o--00---0--00-0000-0-0o0--00...1332-11 pa 1111----1111111i11i11-111-111-1111i11-111-11111-11111---111-11-i11111...

1332-12 ma -00-i--11--111-i111-11---11i--1111i-1111-i--11---1--11-1111-1-1i1---1...1332-12 pa 0000----0000000o00o00-0---000-0000o00-000-00000-00000---000-00-o000-0...

1332-17 ma -11-i--1---11--i111-1--1111i--1111i-1111-i--11---1--11-1100-0-00o--00...1332-17 pa 0000-----0000--o00o00-000-000-0000o-0-000-0000--00000---000-00-0o0000...

17

Page 18: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

CRIMAP chrompic

1332-03 ma -11-i--11--111-i111-11-1111i--1111i-1111-i--11---1--11-1111-1-1i1---1...1332-03 pa 0000----0000000o00o00-000-000-0000o00-000-00000-00001---000-00-o000-0...

1332-04 ma -11-i--11--111-1111-11-i111i--i1111-1111-i--11---1--11-1111-1-11i--11...1332-04 pa 1111----1111111111i11-1i1-111-i111i11-111-11111-11111---111-11-1i1111...

1332-05 ma -11-i--11--111-i111-11-1111o--0000o-0000-o--00---0--00-0000-0-0o0--00...1332-05 pa 0000----0000000o00o00-000-111-1111i11-111-1111--11111---111-11-i11111...

1332-06 ma -00-o--00--000-o000-00-0000o--0000o-0000-o--00---0--00-0000-1-11i--11...1332-06 pa 1111----1111111i11i11-111-111-1111i11-111-11111-11111---111-11-1i1111...

1332-07 ma -00-o--00--000-o000-00-0000o--0000o-0000-o--00---0--00-0000-0-0o0--00...1332-07 pa 1111----1111111i11i11-111-111-1111i11-111-1111--11111---111-11-i11111...

1332-08 ma -10-o--00--000-00-0-00-0000o--o0000-0000-o--00---0--11-1111-1-1i1--11...1332-08 pa 0000----000000000-o00-010-000-o000o00-000-00000-00000---000-00-o00000...

1332-10 ma -11-i--1---111-i111-11-1111i--1111i-1111-i--11---1--11-1111-1-1i1--11...1332-10 pa 1000-----000000o00o00-000-000-0000o00-000-00000-00000---000-00-o00000...

1332-11 ma -11-o--00--000-o000-00-0000o--0000o-0000-o--00---0--00-0000-0-0o0--00...1332-11 pa 1111----1111111i11i11-111-111-1111i11-111-11111-11111---111-11-i11111...

1332-12 ma -00-i--11--111-i111-11---11i--1111i-1111-i--11---1--11-1111-1-1i1---1...1332-12 pa 0000----0000000o00o00-0---000-0000o00-000-00000-00000---000-00-o000-0...

1332-17 ma -11-i--1---11--i111-1--1111i--1111i-1111-i--11---1--11-1100-0-00o--00...1332-17 pa 0000-----0000--o00o00-000-000-0000o-0-000-0000--00000---000-00-0o0000...

18

Page 19: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Top of chr 22

Marker Dnumber sex-ave(cM) female(cM) male(cM)

1 ATA2G02 Unknown 0.00 0.00 0.00

1.79 0.00 2.60

2 GATA198B05 Unknown 1.79 0.00 2.60

2.27 3.32 0.00

3 AFM217xf4 D22S420 4.06 3.32 2.60

4.26 4.51 5.42

4 AFM288we5 D22S427 8.32 7.83 8.02

5.25 7.52 3.00

5 265yf5 D22S425 13.57 15.35 11.02

0.03 0.00 0.65

6 GGAA10F06 D22S686 13.60 15.35 11.67

0.84 0.00 0.82

7 AFMa037zd1 D22S539 14.44 15.35 12.49

0.00 0.00 0.00

8 AFM292va9 D22S446 14.44 15.35 12.49

3.27 5.91 0.00

9 Mfd51 D22S257 17.71 21.26 12.49

19

Page 20: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Marker search

http://research.marshfieldclinic.org/genetics/MarkerSearch/searchMarkers.asp

20

Page 21: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

10th worst graph

Broman et al., Am J Hum Genet 63: 861–869, 199821

Page 22: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Total no. crossovers

Broman et al., Am J Hum Genet 63: 861–869, 199822

Page 23: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Crossover locations

Broman and Weber, Am J Hum Genet 66:1911–1926, 200023

Page 24: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Family 884, chr 6

Maternal chromosomes34567891011121314

Paternal chromosomes34567891011121314

24

Page 25: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Autozygosity

Broman and Weber, Am J Hum Genet 65:1493–1500, 199925

Page 26: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Crossover interference

Broman and Weber, Am J Hum Genet 66:1911–1926, 200026

Page 27: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Maternal chr 8

27

Page 28: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Apparent triple XOs

Broman et al., In: Science and Statistics: A Festschrift for Terry Speed, 2003

28

Page 29: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Chr 8p inversion

Broman et al., In: Science and Statistics: A Festschrift for Terry Speed, 2003

29

Page 30: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Comparison to sequence

Matise et al., Am J Hum Genet 70:1398–1410, 200230

Page 31: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Comparison to sequence(revisited)

15 20 25 30 35 40 45

0

10

20

30

40

50

60

Sequence Position (Mbp)

Gen

etic

map

pos

ition

(cM

)

D22S534(UT7213)

D22S529(UT1963)

D22S531(UT5900)

D22S1174(AFM331wc9)

Thanks to UCSC and Ensembl!31

Page 32: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Dog genetic map

Neff et al., Genetics 151:803–820, 199932

Page 33: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Dog genetic map

Neff et al., Genetics 151:803–820, 199933

Page 34: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

The first dog map

Mellersh et al., Genomics 46:326–336, 199734

Page 35: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

The dog X

Mellersh et al., Genomics 46:326–336, 1997

35

Page 36: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

The dog X

Mellersh et al., Genomics 46:326–336, 1997 Neff et al., Genetics 151:803–820, 1999

36

Page 37: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

JAX backcrosses

(C57BL/6J × SPRET/Ei) × SPRET/Ei94 individuals4913 markers

(C57BL/6J × SPRET/Ei) × C57BL/6J94 individuals1659 markers

Rowe et al., Mamm Genome 5:253–274, 1994Broman et al., Genetics 160:1123–1131, 2002

37

Page 38: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Mouse chr 14p

●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●82●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●85

●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●2

●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●1●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●1

●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●1

●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●1●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●2

●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●1●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●1

●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●2●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●4

●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●2

●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●1●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●1

●●●● ●● ● ●● ● ● ●● ● ● ●●●●● ●● ● ●● ● ● ●● ● ● ●1

D14

Mit1

0D

14M

it11

D14

Mit4

9D

14M

it98

D14

Mit1

D14

Mit1

32

D14

Mit1

79

D14

Mit2

D14

Mit1

2

D14

Mit2

09

D14

Mit4

4

D14

Mit1

4D

14M

it174

D14

Mit1

5

D14

Mit3

D14

Mit2

12

0 2 4 6 8 10 12cM

1 2 3 4 5 6 7 8 9 10 11 1213 14 15 16

38

Page 39: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Mouse chr 14p

● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●82● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●85

● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●2

● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●1● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●1

● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●1

● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●1● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●2

● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●1● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●1

● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●2● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●4

● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●2

● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●1

● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●1● ● ●●● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ● ● ● ● ●1

D14

Mit1

0

D14

Mit1

1D

14M

it49

D14

Mit9

8D

14M

it1

D14

Mit1

32

D14

Mit1

79

D14

Mit2

D14

Mit1

2

D14

Mit2

09

D14

Mit4

4

D14

Mit1

4

D14

Mit1

74

D14

Mit1

5

D14

Mit3

D14

Mit2

12

10 15 20 25 30 35 40Mbp

7 6 5 21 3 4 9 8 10 11 12 13 14 15 16

39

Page 40: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

C. savignyi (sea squirt)

Aim: Build linkage map to improve long-range ordering of draftgenome sequence (which is currently represented as a fewhundred “reftigs”)

40

Page 41: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

C. savignyi pedigree

●●

48 progeny

Markers: PCR amplicon (primers in exons, spanning anintron), digested with a restriction enzyme

−→ 2, 3 or 4 banding patterns

Tricky bits: Which marker “phenotype” corresponds to whichgenotype?

Using information on locations of markers within“reftigs”

41

Page 42: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Example of two markers

99481-HaeIII

114467-MboI AC AD BC BC

AC 8 3 1 0

AD 0 10 0 1

BC 2 0 11 1

BD 0 1 0 9

42

Page 43: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Example of two markers

99481-HaeIII

114467-MboI AC AD BC BC

AC 8 3 1 0

AD 0 10 0 1

BC 2 0 11 1

BD 0 1 0 9

43

Page 44: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Example of two markers

99481-HaeIII

114467-MboI AC AD BC BC

AC 8 3 1 0

AD 0 10 0 1

BC 2 0 11 1

BD 0 1 0 9

44

Page 45: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Example of two markers

99481-HaeIII

114467-MboI AC AD BC BC

AC 8 3 1 0

AD 0 10 0 1

BC 2 0 11 1

BD 0 1 0 9

45

Page 46: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

C. savignyi LG 5

46

Page 47: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Culex tarsalis pedigree

● ● ● ● ● ● ● ● ● ●

● ● ● ● ● ● ● ● ● ● ●

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●

● ● ● ● ● ● ● ● ● ● ●

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

pf pm

33 3 53 5 224 22 63 6 121 12

47

Page 48: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Marker TB1

● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●

pf pm

33 3 53 5 224 22 63 6 121 12

129 129/ 109 109/

129 109/ 129 109/ 129 109/ 129 129/ 129 109/

129

109

109

129

129

109

/

/

/

6

1

0

129

109

109

129

129

109

/

/

/

3

5

4

129

109

109

129

129

109

/

/

/

9

6

1

129

109

109

129

129

109

/

/

/

4

9

5

129

109

109

129

129

109

/

/

/

22

10

11

48

Page 49: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Marker TB1

● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●

pf pm

33 3 53 5 224 22 63 6 121 12

129 129/ 109 109/

129 109/ 129 109/ 129 109/ 129 109/ 129 109/

129

109

109

129

129

109

/

/

/

6

1

0

129

109

109

129

129

109

/

/

/

3

5

4

129

109

109

129

129

109

/

/

/

9

6

1

129

109

109

129

129

109

/

/

/

4

9

5

129

109

109

129

129

109

/

/

/

22

10

11

49

Page 50: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Marker TB1

● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●

pf pm

33 3 53 5 224 22 63 6 121 12

129 129/ 109 109/

129 109/ 129 109/ 129 109/ 129 109/ 129 109/ 129 109/ 129 109/ 129 109/ 129 109/ 129 109/

129

109

109

129

129

109

/

/

/

6

1

0

129

109

109

129

129

109

/

/

/

3

5

4

129

109

109

129

129

109

/

/

/

9

6

1

129

109

109

129

129

109

/

/

/

4

9

5

129

109

109

129

129

109

/

/

/

22

10

11

50

Page 51: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Marker TB1

● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●

pf pm

33 3 53 5 224 22 63 6 121 12

129 129/ 109 109/

129 109/ 129 109/ 129 109/ 129 109/ 129 109/ 129 109/ 129 109/ 129 109/ 129 109/ 129 109/

129

109

109

129

129

109

/

/

/

6

1

0

129

109

109

129

129

109

/

/

/

3

5

4

129

109

109

129

129

109

/

/

/

9

6

1

129

109

109

129

129

109

/

/

/

4

9

5

129

109

109

129

129

109

/

/

/

22

10

11

129

109

109

129

129

109

/

/

/

44

31

21

Overall:

51

Page 52: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Marker TB1

● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●

pf pm

33 3 53 5 224 22 63 6 121 12

129 129/ 109 null/

129 109/ 129 109/ 129 109/ 129 null/ 129 109/

129

109

109

129

129

109

/

/

/

6

1

0

129

109

109

129

129

109

/

/

/

3

5

4

129

109

109

129

129

109

/

/

/

9

6

1

129

109

109

129

129

109

/

/

/

4

9

5

129

109

109

129

129

109

/

/

/

22

10

11

52

Page 53: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Marker TB1

● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●

pf pm

33 3 53 5 224 22 63 6 121 12

129 129/ 109 null/

129 109/ 129 null/ 129 109/ 129 null/ 129 109/ 129 null/ 129 null/ 129 109/ 129 109/ 129 null/

129

109

109

129

null

/

/

/

6

1

0

129

109

109

129

null

/

/

/

3

5

4

129

109

109

129

null

/

/

/

9

6

1

129

109

109

129

null

/

/

/

4

9

5

129

109

109

129

null

/

/

/

22

10

11

53

Page 54: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Marker TB1

● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ●

pf pm

33 3 53 5 224 22 63 6 121 12

129 129/ 109 null/

129 109/ 129 null/ 129 109/ 129 null/ 129 109/ 129 null/ 129 null/ 129 109/ 129 109/ 129 null/

129

109

109

129

null

/

/

/

6

1

0

129

109

109

129

null

/

/

/

3

5

4

129

109

109

129

null

/

/

/

9

6

1

129

109

109

129

null

/

/

/

4

9

5

129

109

109

129

null

/

/

/

22

10

11

129

109

109

129

null

/

/

/

44

31

21

Overall:

54

Page 55: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Morals

• Genetic maps continue to be useful

• Be careful about automated map construction

• Careful, tedious work is often necessary

• The simplest things can have the greatest impact

• Artifacts can be more interesting than anything else

• Don’t give a sex-averaged map of the X chromosome

• Genotype the F1 parents

• Null alleles are a pain

55

Page 56: Genetic maps - Biostatistics and Medical Informaticskbroman/presentations/geneticmaps08.pdf · Eucalypt genetic map Byrne et al., Theor Appl Genet 91:869–875, 1995 3

Acknowledgments

Terry Speed, Univ. California, Berkeley

Jim Weber, PreventionGenetics

Mark Neff, Univ. California, Davis

Lucy Rowe, The Jackson Lab

Matt Hill and Arend Sidow, Stanford

Meera Venkatesan and Jason Rasgon, Johns Hopkins

56