Linkage disequilibrium and association studies in higher plants: present status and future prospects.
During the last two decades, DNA-based molecular markers have been extensively utilized for a variety of studies in both plant and animal systems. One of the major uses of these markers is the construction of genome-wide molecular maps and the genetic analysis of simple and complex traits. However, these studies are generally based on linkage analysis in mapping populations, thus placing serious limitations in using molecular markers for genetic analysis in a variety of plant systems. Therefore, alternative approaches have been suggested, and one of these approaches makes use of linkage disequilibrium (LD)-based association analysis. Although this approach of association analysis has already been used for studies on genetics of complex traits (including different diseases) in humans, its use in plants has just started. In the present review, we first define and distinguish between LD and association mapping, and then briefly describe various measures of LD and the two methods of its depiction. We then give a list of different factors that affect LD without discussing them, and also discuss the current issues of LD research in plants. Later, we also describe the various uses of LD in plant genomics research and summarize the present status of LD research in different plant genomes. In the end, we discuss briefly the future prospects of LD research in plants, and give a list of softwares that are useful in LD research, which is available as electronic supplementary material (ESM).
Gupta
Pushpendra K
PK
Molecular Biology Laboratory, Department of Genetics & Plant Breeding, Ch. Charan Singh University, Meerut 250 004 (UP), India. pkgupta36@vsnl.com
Rustgi
Sachin
S
Kulwal
Pawan L
PL
D002874:Chromosome Mapping; D005544:Forecasting; D023281:Genomics / Q000379:methods; D015810:Linkage Disequilibrium; D010944:Plants / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci / Q000235:genetics; D012106:Research / Q000639:trends; D012107:Research Design; D012641:Selection, Genetic