| Bioinformatics & Computational Biology Student Seminar Series
Functional analysis of maize CRINKLY4-like receptor kinase genes in Arabidopsis
Xueyuan Cao
B.S. Horticulture, Shandong Agricultural University
M.S. Genetics, Institute of Genetics, Chinese Academia of Sciences
Home Dept: Zoology and Genetics Department
Major Professors: Phil Becraft & Dan Nettleton
Iowa State University |
Friday, February 15, 2002
1:10 p.m.
1420 Molecular Biology Building
|
Abstract
The maize CRINKLY4 (CR4) gene, encoding a novel receptor-like kinase (RLK), controls an array of development processes including cell proliferation, fate, pattern and differentiation. Mutations in CR4 disrupt aleurone cell fate in the endosperm and lead to dramatic defects in the shoot and leaf epidermis. The Arabidopsis genome encodes 5 receptor-like proteins related to maize CR4. AtCR4 is believed to be the CR4 homologue with 60% amino acid identity and all the characteristic motifs of the maize CR4. Proteins encoded by the other 4 CR4-RELATED (CRR) genes lack the carboxyl domain and have lower similarity with the maize CR4. Northern blotting and promoter::GUS fusion showed that AtCR4 is expressed in the shoot apical meristem and leaf primordia, flowers and developing siliques. It is weakly expressed in mature leaves and roots. CRR1 and CRR3 are also expressed. Two knockout lines of AtCR4 have been obtained by screening the Wisconsin collection of T-DNA insertion lines and GARLIC collection from TMRI. We are now analyzing these two lines. cDNA microarray analysis will be performed to identify genes regulated by AtCR4 signal transduction pathway.
Justin Schonfeld
| Bioinformatics & Computational Biology Student Seminar Series
Investigating Evolutionary Lines of Least Resistance Using The Inverse Protein-Folding Problem
Justin Schonfeld
Major Professor: Dr. Dan Ashlock
Iowa State University |
Friday, February 15, 2002
1:10 p.m.
1420 Molecular Biology Building
|
Abstract
I will present a method for constructing a theoretical protein landscape for the purpose of studying evolutionary lines of least resistance. To construct the theoretical landscape a polynomial time algorithm based on Sun et al's Grand Canonical (GC) model was used to generate optimal sequences from 3D structures. Preliminary results suggest: (1) that the GC model captures important biological aspects of the mapping between protein sequences and their corresponding structures, and (2) the set of sequences that map to a target structure with optimal energy is affected by minor differences in structure.
|
URL:
Copyright © 2002, Iowa State University, all rights reserved.
Last Modified:
|
