slide1 n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Selective Breeding & cDNA Microarrays PowerPoint Presentation
Download Presentation
Selective Breeding & cDNA Microarrays

Loading in 2 Seconds...

play fullscreen
1 / 10

Selective Breeding & cDNA Microarrays - PowerPoint PPT Presentation


  • 308 Views
  • Uploaded on

Applied quantitative genetics in a genomics world. Selective Breeding & cDNA Microarrays. Toni Reverter Bioinformatics Group CSIRO Livestock Industries Queensland Bioscience Precinct 306 Carmody Rd., St. Lucia, QLD 4067, Australia. Bribie Island – 26-27 July 2004.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Selective Breeding & cDNA Microarrays' - Jimmy


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
slide1

Applied quantitative genetics in a genomics world

Selective Breeding

&

cDNA Microarrays

Toni Reverter

Bioinformatics Group

CSIRO Livestock Industries

Queensland Bioscience Precinct

306 Carmody Rd., St. Lucia, QLD 4067, Australia

Bribie Island – 26-27 July 2004

slide2

Applied quantitative genetics in a genomics world

Selective Breeding & cDNA Microarray

Tissue Samples

Treat A

Treat B

Analysis

mRNA Extraction & Amplification

+

Image Capture

cDNA “A” Cy5

cDNA “B” Cy3

Laser 1 Laser 2

Hybridization

Optical Scanner

The Process

Bribie Island – 26-27 July 2004

slide3

Applied quantitative genetics in a genomics world

Selective Breeding & cDNA Microarray

The Possibilities

  • Determine genes which are differentially expressed (DE).
  • Connect DE genes to sequence databases to search for common upstream regions.
  • Overlay DE genes on pathway diagrams.
  • Relate expression levels to other information on cells, e.g. tumor types.
  • Identify temporal and spatial trends in gene expression.
  • Seek roles of genes based on patterns of co-regulation.
  • …Applications to Selective Breeding Schemes?

Bribie Island – 26-27 July 2004

slide4

Applied quantitative genetics in a genomics world

Selective Breeding & cDNA Microarray

How to relate them?

3 Types of Data

Phenotype

+ Pedigree

Phenotype

+ Marker

Gene

Expression

Bribie Island – 26-27 July 2004

slide5

Applied quantitative genetics in a genomics world

Selective Breeding & cDNA Microarray

Mixed-Inheritance Model

Wang, Fernando & Grossman, 1998

Many authors and many species

NB: Segregation Variance Issues

Infinitesimal Model

ANOVA Model

Henderson, 1975

Many authors and many species

Dimension Reduction

Genetical Genomics

Jansen and Nap, 2001 (arabidopsis)

Brem et al, 2002 (yeast)

Schadt et al., 2003 (mice)

Chiaromonte & Matinelli, 2002

(leukemia, humans)

ANOVA Model

Cui and Churchill, 2003

Predict Future Performance

Phenotype

+ Pedigree

Phenotype

+ Marker

Gene

Expression

Bribie Island – 26-27 July 2004

slide6

Applied quantitative genetics in a genomics world

Selective Breeding & cDNA Microarray

Genetical Genomics

Use arrays to identify genes that are DE in relevant tissues of individuals

sorted by QTL genotype. If those DE genes map the chromosome region

Of interest, they would become very strong candidates for QTL.

Source: Jansen and Nap, 2001

Bribie Island – 26-27 July 2004

slide7

Applied quantitative genetics in a genomics world

Selective Breeding & cDNA Microarray

High EBV Low EBV

1

0

2

2

GeneStar

Marbling

Genotype

(N Stars/Alleles)

3

1

1

7

8

4

5

2

0

6

Genetical Genomics

Use arrays to identify genes that are DE in relevant tissues of individuals

sorted by QTL genotype. If those DE genes map the chromosome region

Of interest, they would become very strong candidates for QTL.

For lots of $, this will find lots of genes affecting a trait of interest.

…….……Selective Breeding Needs Additivity:

Bribie Island – 26-27 July 2004

slide8

Applied quantitative genetics in a genomics world

Selective Breeding & cDNA Microarray

Never enough! …not greed but algebra:

Ability to score individuals rapidly (and

cheaply) at a very large number of loci.

Genetical Genomics

Use arrays to identify genes that are DE in relevant tissues of individuals

sorted by QTL genotype. If those DE genes map the chromosome region

Of interest, they would become very strong candidates for QTL.

  • …………particularly useful for:
  • Speed up and enhance power to finding New QTL
  • Developing “Diagnostic Kits”
  • Deciphering the genetics of Complex Traits

A trait that is affected by many, often

interacting, environmental and genetic

factors such that no factor is completely

sufficient nor are all factors necessary.

(Andersson and Georges, 2004)

Bribie Island – 26-27 July 2004

slide9

Applied quantitative genetics in a genomics world

Selective Breeding & cDNA Microarray

Final Thoughts

Where does this leave us (Quantitative Geneticists)?

Where does this leave Phenotypes (the need to measure)?

Very well, ………I’m afraid

  • Quantitative Geneticists:
  • Never enough QTL
  • Association studies
  • Study of variation
  • When QTL not additive, the individual is needed but not so with BLUP
  • Phenotypes:
  • Mutation is continuously generating new variation
  • Selective breeding on genotypes reduces effective population size
  • Integration of the 3 types of data

Bribie Island – 26-27 July 2004

slide10

Applied quantitative genetics in a genomics world

Selective Breeding & cDNA Microarray

References

Andersson, L. and Georges (2004) Domestic-animal genomics: deciphering the

genetics of complex traits. Nature Reviews 5:202-212.

Brem, R.B., G. Yvert, R. Clinton, and L. Kruglyak. (2002) Genetic dissection of

transcriptional regulation in budding yeast. Science 296:752-755.

Chiaromonte, F., and Martinelli, J. (2002) Dimension reduction strategies for

analysing global gene expression data with a response. Math. Biosciences, 176:123-144.

Cui, X., and G. A. Churchill. (2003) Statistical tests for differential expression in

cDNA microarray experiments. Genome Biol., 4:210.

Henderson, C.R. (1975) Best linear unbiased estimation and prediction under a

selection model. Biometrics, 31:423.

Jansen, R.C. and J.P. Nap (2001) Genetical genomics: the added value from

segregation. Trend Genet., 17:388-391.

Schadt, E.E., Monks, S.A., Drake, T.A., et al. (2003) Genetics of gene expression

surveyed in maize, mouse and man. Nature 422:297-302.

Wang, T., R.L. Fernando, and M. Grossman (1998) Genetic evaluation by best linear

unbiased prediction using marker and trait information in a multibreed population.

Genetics, 148:507-515.

Bribie Island – 26-27 July 2004