ABSTRACT
Plant-breeding programs made significant strides in improving the productivity of major crop plants in the last century. This was largely made possible by the application of conventional genetic principles. While genetic improvement of qualitative traits was successful as a result of the simple inheritance pattern, progress in manipulating quantitative traits, such as stress tolerance, yield, and yield components, has lagged behind. The major constraint is the lack of knowledge about the mechanisms and complex biological pathways that are involved in the plants’ response in target environments. During the past two decades, developments in molecular biology provided new opportunities in a variety of ways that would have far-reaching impact on cropbreeding programs. Some key areas of crop improvement include: (1) assessment of genetic diversity, (2) new gene discovery, (3) genetic dissection of complex traits, and lastly, the most practical being (4) marker-assisted selection (MAS) of useful traits. Designing new crop cultivars through introgression of useful genes using molecular markers has been routine in many private-and public-sector breeding programs. Molecular linkage maps constructed virtually in all major crop plants have been instrumental in mapping and marker-assisted selection of agronomically important genes. Our understanding about inheritance and expression of complex traits is progressing rapidly through positional cloning of quantitative trait loci (QTL). With the acquisition of overwhelming amount of genomic sequences as a result of whole genome and expressed sequence tags (EST) sequencing initiatives in many crop plants, there has been a dramatic shift in approaches followed by plant biologists to interpret the intricacy of plant biology. Defining the functions of all genomic or EST sequences, their networking, and regulation in the plant system remains as a major challenge for postgenomic researchers. We are now better equipped to apply genome mapping, reverse genetics tools, and expression profiling in a wide array of organisms to understand complex biological processes (Osterlund and Paterson, 2002). Technological breakthrough in genomics promises to provide a comprehensive picture of the various plant growth and development responses to ensure real gain in improving and stabilizing crop productivity. High-throughput
genomics tools, coupled with innovative bioinformatics techniques, offer new avenues to exploit model systems to make rapid advances.
