Application of Molecular Marker Technology in Crop Breeding
A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Crop Breeding and Genetics".
Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 22239
Special Issue Editor
Interests: breeding for fruit quality; differential gene expression analysis; genomic selection; GWAS; molecular breeding; plant breeding; QTL mapping; resistance breeding; stress tolerance
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The application of molecular markers in crop improvement first started in the 1980s. Initially, it was in the form of hybridization-based molecular markers, which were relatively less popular. As soon as PCR-based molecular markers became available, however, they became widely and easily applicable in several crop plants. Since then, several plant breeding programs have optimized the use of molecular markers associated with various traits, including disease resistance, quality, and abiotic stress tolerance. Still, there are several traits that need to be optimized, and research on that front is ongoing in various parts of the world. With the availability of genome sequences and SNP markers developed from the use of those sequences, high-density molecular linkage maps can be developed, and molecular markers associated with the traits of interest can be identified more precisely. Furthermore, mapping and fine mapping of QTL can be achieved, and eventually, such research can help us to identify the genes associated with the traits of interest. In the proposed Special Issue of Agronomy, we encourage researchers from around the world to publish their groundbreaking work in these areas of QTL mapping and marker analysis in various plant systems in this Special Issue of Agronomy. Papers directly associated with crop plants of economic importance will be given more priority.
Dr. Dilip R. Panthee
Guest Editor
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Keywords
- GWAS
- linkage analysis
- molecular marker
- QTL
- RNA-seq analysis
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