Abstract
Wheat is the most consumed grain crop in the world. It is also an excellent model of allopolyploid inheritance. Genomic analysis of wheat is essential for understanding the genetic mechanisms underlying allopolyploid evolution and speciation as well as the biology of agronomically important traits influencing production. In spite of the large genome and polyploidy, researchers have devised novel strategies for in depth structural and functional analysis of the wheat genome. Beginning with the 1920s, wheat has been a model crop for cytogenetic studies, and a plethora of cytogenetic stocks of various types have been developed. Today, a combined cytogenetic and molecular approach has greatly advanced wheat genome analysis. The comparison of physical maps of wheat chromosomes based on chromosome deletion mapping with molecular genetic linkage maps led to the notion that genes were not distributed at random throughout the wheat genome, but rather exist in gene-rich recombination hot spots along the chromosomes. Recent construction and sequencing of local BAC contigs has verified this hypothesis, suggesting that most genes in wheat are amenable to positional cloning. Wheat is now moving into the functional genomics era as researchers focus on the expressed portion of the wheat genome. A database of expressed sequence tags (ESTs) is growing rapidly as researchers work to assign gene function. High-throughput production and identification of mutants will be necessary for the assignment of function to the many genes being discovered in wheat.
Call for Papers in Thematic Issues
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In the era of personalized medicine, understanding the relationship between genetics and drug response is crucial. This issue delves into innovative methodologies, leveraging deep computational analysis and artificial intelligence, to enhance the field of Clinical Pharmacogenomics. The interdisciplinary approach harnesses the power of advanced high-throughput genotyping technologies, sophisticated computational analysis, ...read more
Applications of Single-cell Sequencing Technology in Reproductive Medicine
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Big Data in Cancer Research
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Current Genomics in Cardiovascular Research
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