16
04/01/10 University of North Carolina Techniques for Accelerating Inbreeding in the Collaborative Cross 1 Department of Computer Science, University of North Carolina at Chapel Hill 2 Department of Genetics, University of North Carolina at Chapel Hill Catie Welsh Catie Welsh 1 , Ryan J. Buus , Ryan J. Buus 2 , Jennifer Shockley , Jennifer Shockley 2 , , Stephanie Hansen Stephanie Hansen 2 , Darla Miller , Darla Miller 2 , Fernando Pardo-Manuel de Villena Fernando Pardo-Manuel de Villena 2 , Leonard , Leonard McMillan McMillan 1

04/01/10University of North Carolina Techniques for Accelerating Inbreeding in the Collaborative Cross 1 Department of Computer Science, University of

  • View
    219

  • Download
    0

Embed Size (px)

Citation preview

04/01/10 University of North Carolina

Techniques for Accelerating Inbreeding in the Collaborative Cross

1Department of Computer Science, University of North Carolina at Chapel Hill2Department of Genetics, University of North Carolina at Chapel Hill

Catie WelshCatie Welsh11, Ryan J. Buus, Ryan J. Buus22, Jennifer Shockley, Jennifer Shockley22, , Stephanie HansenStephanie Hansen22, Darla Miller, Darla Miller22,,

Fernando Pardo-Manuel de VillenaFernando Pardo-Manuel de Villena22, Leonard McMillan, Leonard McMillan11

Motivation

2Figures Courtesy of Karl Broman

Motivation

3

Observations

4

• Large difference between selfing and random sibling mating.

• Randomization was an important design decision in the CC.

• Attempt to accelerate inbreeding using marker-assisted techniques.

• Study impact of marker-assisted inbreeding on the genetic structure of the CC.

Backcross

Sib-Mating Pedigree Diagram

Parent-Child Backcross Pedigree Diagram

5

Change breeding scheme after 10 generations of random sib-matings to cross offspring with their parent; alternating sex of parent at each generation.

G2:F10

Backcross

6

100,000 Simulations were done.

No genotyping necessary.

33.538.2

141.2 145.1

Marker-Assisted Inbreeding (MAI)

7

• Random sib-matings for 10 generations

• Starting at generation 11:

– Generate 4 female and 4 male offspring

– Consider all 16 pair matings

– Choose the “best” breeding pair

MAI

DD

Ss

DS

Each of the marked regions is some form of heterozygosity between the 2 animals.

8

SS

Choosing the “Best” Breeding Pair

• Consider all heterozygous regions

• Calculate fraction of the genome that segregates in each pair of mice.

• Take into account the different types of heterozygosity

SS

Ss = Opposite Homozygous DD = Both HeterozygousDS = One Heterozygous, One HomozygousSS = Same Homozygous

MAI Metrics

9

Ss = Opposite Homozygous DD = Both HeterozygousDS = One Heterozygous, One HomozygousSS = Inbred

Relationship between a potential breeding pair at 1 allele

Interval 1 2 3 Probability

Breeding Pair 1 DD DS DD = 1/8 x ¼ x 1/8 = 1/256

Breeding Pair 2 Ss DS DD = 0 x ¼ x 1/8 = 0

MAI

10

Model is very conservative; assume every location fully informative

100,000 simulations

10

23.5

33.5

38.2

137.5141.2

145.1

99% Fixation

11

25.7 generations to reach 99% inbred with a regular 8-way cross

23.5 generations to be 99% inbred using Backcrosses

17.5 generations to be 99% inbred using MAI

17.6

23.5

25.7

MAI Impact

12

Regular 8-way MAI 8-way

Starting Earlier

13

Impact on Number of Generations

Impact on Number of Segments

Maximizing Mapping Power

14

Advanced Intercross – Maximize # of segments for x generations, thereafter minimize heterozygosity until inbred.

Impact on Number of Segments

Impact on Number of Generations

Conclusion

• 2 approaches to accelerating inbreeding• Backcrosses – slight speedup• MAI – dramatic acceleration

• Both have small impact on # of segments (slight decrease)• Use of advanced intercross will increase # of segments• MAI techniques are currently being used at UNC with CC lines• 8 lines in various stages• Considering the use of backcrosses in more lines

15

Acknowledgements

16

UNC Computer ScienceWei WangYi LiuJeremy Wang

FPMV Lab

David Aylor

Tim Bell

John Calaway

Mark Calaway

John Didion

Justin Gooch

Ginger Shaw

Jason Spence

Churchill Lab

Gary Churchill

Hyuna Yang

UNC GeneticsWill Valdar

Funding SourcesNIH U01 CA105417 “Integrative Genetics of Cancer Susceptibility”NSF IIS 0534580 “Visualizing and Exploring High-dimensional Data”NIH GM 076468 “The Center for Genome Dynamics at Jackson Laboratory: An NIGMS National Center of Systems Biology”