Editorial Book

Book Title: Handbook of Plant Breeding

PAID ACCESS | Published on : 20-May-2026 | Pages: 46-55 | Doi : 10.37446/edibook152024/46-55

Genome-Wide Association Studies - Unveiling hidden traits in Modern Plant Breeding

• Akshita Awasthi
• Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India.


• Indu Rialch
• Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India.

Abstract

Genome-Wide Association Studies (GWAS) have revolutionized the field of plant breeding by enabling the identification of genetic variants linked to complex traits. By analyzing variations in the DNA of diverse plant populations and correlating them with phenotypic traits, GWAS facilitates the discovery of genetic loci that contribute to important agronomic characteristics such as yield, disease resistance, drought tolerance, and nutrient use efficiency. Unlike traditional breeding methods that rely on phenotypic selection, GWAS offers a more precise approach by providing insights into the genetic architecture of these traits at a molecular level. The advent of high-throughput sequencing technologies has accelerated the application of GWAS in modern plant breeding. By leveraging large-scale genetic data from diverse germplasm collections, GWAS aids in the identification of single nucleotide polymorphisms (SNPs) and other genetic markers that can be used in marker-assisted selection (MAS). This allows breeders to select plants with desirable traits at an early stage of development, reducing breeding cycles and enhancing the efficiency of the breeding process. Moreover, GWAS plays a pivotal role in the customization of breeding programs tailored to specific environmental conditions, such as those posed by climate change. The ability to identify loci associated with stress tolerance enables breeders to develop varieties that are resilient to changing environmental factors. In conclusion, the integration of GWAS into plant breeding is transforming the development of crops with improved productivity, resilience, and sustainability, addressing the challenges of modern agriculture.

Keywords

Genome-wide association study, Plant breeding, Genetic architecture, Linkage disequilibrium, Complex traits, Marker-assisted selection

References

Abdurakhmonov I Y and Abdukarimov A (2008) Application of association mapping to understanding the genetic diversity of plant germplasm resources. Int J Plant Genomics1—18

 Ardlie K G, Kruglyak L and Seielstad M (2002) Patterns of linkage disequilibrium in the human genome. Nat Rev Genet 3: 299–309.

Benjamini Y and Hochberg Y (1995) Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57:289– 300

Ersoz E S, Yu J and Buckler E S (2007) Applications of linkage disequilibrium and association mapping in crop plants. In R. K. Varshney, & R. Tuberosa (Eds.), Genomics-assisted crop improvement (pp. 97– 119). Dordrecht, Netherlands: Springer

Flint-Garcia S A, Thornsberry J M and Buckler E S IV (2003) Structure of linkage disequilibrium in plants. Annu Rev Plant Biol 54: 357–374

Gaut B S and Long A D (2003) The lowdown on linkage disequilibrium. Plant Cell 15: 1502–1506

Gupta P K and Rustgi S (2004) Molecular markers from the transcribed/expressed region of the genome in higher plants. Funct. Integr. Genomics 4: 137–162

Hedrick P W (1987) Gametic disequilibrium measures: proceed with caution. Genetics 117: 331–341

Jannink J L and Walsh B (2002) Association mapping in plant populations. In: M.S. Kang (Ed.), Quantitative Genetics, Genomics and Plant Breeding, CAB International, pp. 59–68

Lander E S and Schork N J (1994). Genetic dissection of complex traits. Science 265:2037–2048

Mackay T F C, Stone E A and Ayroles J F (2009) The genetics of quantitative traits: Challenges and prospects. Nature Reviews Genetics 10: 565–577

Meuwissen T H E and Goddard M E (2000) Fine mapping of quantitative trait loci using linkage disequilibria with closely linked marker loci. Genetics 155: 421–430

Nordborg M and Tavare´ S (2002) Linkage disequilibrium: what history has to tell us? Trends. Genet. 18: 83–90.

Palaisa K A, Morgante M, Williams M and Rafalski A (2003) Contrasting effects of selection on sequence diversity and linkage disequilibrium at two phytoene synthase loci. Plant Cell 15: 1795–1806

Palaisa K, Morgante, M, Tingey S and Rafalski A (2004) Long-range patterns of diversity and linkage disequilibrium surrounding the maize Y1 gene are indicative of an asymmetric selective sweep. Proc. Natl. Acad. Sci. USA. 101: 9885–9890

Pritchard J K, Stephens M, Donnelly P (2000b) Inference of population structure using multilocus genotype data. Genetics 155:945–959

Pritchard J K, Stephens M, Rosenberg NA et al. (2000a) Association mapping in structured populations. Am J Hum Genet 67:170–181

Rafalski A and Morgante M (2004) Corn and humans: recombination and linkage disequilibrium in two genomes of similar size. Trends Genet. 20: 103–111

Storey J D and Tibshirani R (2003) Statistical significance for genome wide studies. Proceedings of the National Academy of Sciences 100:9440–9494

Terwilliger J D and Weiss K M (1998) Linkage disequilibrium mapping of complex disease: fantasy or reality? Curr. Opin. Biotech. 9: 578–594

Weiss K M and Clark A G (2002) Linkage disequilibrium and the mapping of complex human traits. Trends Genet. 18: 19–24.

PDF Download