Grand Challenges for Plant Genomics
Plant genomics uses mapping, sequencing, and analysis of the complete genetic makeup of plants, and their genomes, to determine the function of genes and translation for crop improvement. Increased knowledge in plant genomics can benefit all aspects of crop improvement.
A grand challenge in plant genomics is to identify those gene combinations that lead to significant innovation in agriculture and the production of raw materials for food, feed, fiber, and fuel. An interdisciplinary approach such as molecular plant breeding may be able to meet this challenge and revolutionize 21st century plant improvement.
Molecular plant breeding is founded on the integration of advances in biotechnology, genomic research, and molecular marker applications with conventional plant breeding practices. This integration would require a combination of molecular markers and high-throughput genome sequencing efforts, new knowledge of genome structure and function, statistical approaches to estimate genetic effects, experience in both laboratory molecular methods and field-based breeding practice, and the ability to manage large datasets with diverse data types.
Other key challenges for plant genomics include:
Expand molecular marker selection tools to create high-resolution genetic maps that can exploit linkage between markers and agronomic traits to include marker assisted selection, QTL discovery, positional cloning, and comparative genomics. These resources should be developed to translate and integrate basic research endeavors with applied plant improvement outcomes.
Expand molecular breeding technology to develop high-throughput approaches to genotype and phenotype key traits.
Expand structural genomic research to develop or improve the physical maps of economically important plants and to utilize next generation sequencing technologies to advance knowledge of the gene space.
Expand functional genomics research to increase understanding of the biological role of genomic sequence, including coding, regulatory and repeated sequences, and to link these sequences to physiological function.
Expand bioinformatic tools to enable breeder-centric high-throughput data management and visualization tools and platforms necessary to integrate genome sequence information with other data types, and breeder-centric views of map and trait data that best serve their needs.
Train the next generation of plant researchers broadly to reach full mastery of key areas such as bioinformatics, quantitative genetics and breeding. Develop partnerships with university, federal laboratories and industry to take advantage of the best training opportunities and develop a new cohort of researchers able to undertake and translate basic discovery.
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