PLACE:319 Snedecor Hall

SPEAKER:
Ron Mowers

TITLE:
Multiple Regression for Molecular-Marker, Quantitative-Trail Measurement with an Example, Gray Leaf Spot Tolerance in Maize

ABSTRACT:

When marker classes at a locus are coded 1, 0, -1 for MM, Mm, and mm, respectively, the multiple regression for data from large F2 populations has some elegant properties:

1. The vector of regression coefficients b = (X’X)^-1X’Y may be considered a product of marker relationship information contained in X’X and simple linear regression estimates for each marker locus, X’Y.

2. As sample size , n, gets large, 2X’X/n approaches the correlation matrix among markers, R.

3. The inverse of R has been derived for the no-interference case by Wright and Mowers (1994).

4. With evenly spaced markers on a chromosome, R has the same form as an error variance matrix for a first-order autoregressive process.

5. Marker-pair regressions using linked markers give reasonable estimates of positions and effects of additive genetic factors located between markers.

6. Less promising is the result that variances of multiple regression are strongly affected by closeness to flanking markers of the nearest distal markers.

A practical example of use of marker-pair and multiple regressions is given for gray leaf spot tolerance in maize.  Magnitude of effects and location of possible genetic factors are estimated from the regressions.
 
 

COFFEE: 3:45 p.m., 104 Snedecor Hall