Responses of tropical maize landraces to damage by Chilo partellus stem borer

The potential to manage insect pests using host-plant resistance exists, but has not been exploited adequately. The objective of this study was to determine the resistance of 75 tropical maize landraces through artificial infestation with Chilo partellus Swinhoe. The trial was laid in alpha-lattice design and each seedling was infested with five neonates three weeks after planting, over two seasons in 2009 and 2010. The number of exit holes, tunnel length, ear diameter, ear length, plant height, stem diameter, stem lodging and grain yield were measured and a selection index computed. GUAT 1050 was the most resistant with an index of 0.56, while BRAZ 2179 was the most susceptible with an index of 1.66. Ear characteristics were negatively correlated with damage parameters. The principal component biplot suggested that exit holes, cumulative tunnel length, leaf damage, cob diameter, stem lodging, selection index, ear and plant height contributed 71.2% of the variation in resistance. The mean number of exit holes and tunnel length for resistant landraces and resistant hybrid checks were similar; at 5.5 and 2.48 cm, respectively. The identified resistant landraces (GUAT 1050, GUAT 280, GUAT 1093, GUAT 1082, GUAT 1014, CHIS 114, and GUAN 34) could be used to develop C. partellus stem borer-resistant maize genotypes.Key words: Chilo partellus, ear length, exit holes, stem borer resistance, tunnel length

Genetic diversity analysis in tropical maize germplasm for stem borer and storage pest resistance using molecular markers and phenotypic traits

One hundred maize inbred lines and eighty four hybrids were characterized for resistance to maize stem borer and post-harvest insect pests. This was achieved using genetic distance and population structure based on simple sequence repeat (SSR) markers and biophysical traits. The test materials were evaluated for stem borer, maize weevil and larger grain borer (LGB) resistance. Leaf samples were harvested from 10 healthy plants per genotype and bulked. Genomic DNA was extracted using a modified version of mini-prep Cetyl Trimethyl Ammonium Bromide (CTAB) method. The samples were genotyped with 55 SSRs makers. Univariate analysis of variance was done using the general linear model procedure of SAS statistical package. Rodgers genetic distance was calculated for all data sets as a measure of genetic distance using NTSYS-pc for Windows. The distance matrices were used to generate phenograms using the unweighted pair group method based on arithmetic average (UPGMA) method in MEGA5. The genotypes were assigned into different populations using population structure software. The data was further subjected to discriminant and principal component analysis to group the gnotyoes. Analysis of molecular variance within and among the different populations was done using arlequin. There were significant differences (P ≤ 0.001) for all the biophysical traits evaluated. The SSR marker data estimated successfully the close relationship among different hybrids and inbred lines within clusters. Comparisons of the different multivariate analyses revealed high concordance among the different approaches of analyses. The results of this study can be directly used by breeding programs to develop resistant genotypes

A perspective on proteomics: current applications, challenges and potential uses

Biological sciences are experiencing an ongoing information revolution. Proteome-wide functional classification using bioinformatics approaches is becoming an important method for revealing unknown protein functions. Most successful computational approaches for protein function prediction integrate multiple genomics and proteomics data sources to make inferences about the function of unknown proteins. Research into gene expression and proteomics enable scientists to decipher the functions of genes and their protein products, and to get a clearer picture of the complex regulatory networks that control fundamental biological processes. The global study of cellular proteins by proteomics may be able to provide the complete picture. Use of proteins to study gene function and genetic information is possibly the most reliable method but costly and labour intensive. Analysis of gene-expression patterns is no less powerful concept than proteomics when it comes to identification of the characteristics of signalling pathways or disease states. This review discusses current applications of proteomics, challenges and potential uses