Legume Genomics and Genetics 2024, Vol.15, No.5, 232-243 http://cropscipublisher.com/index.php/lgg 236 drought tolerance and yield (Dutra et al., 2018). Backcrossing helps in retaining the desirable traits of the recurrent parent while incorporating new traits from the donor parent. 4.3 Modern breeding techniques Marker-assisted selection (MAS) is a modern breeding technique that uses genetic markers to select for desirable traits. MAS has been successfully applied in peanut breeding to improve traits such as disease resistance, oil content, and drought tolerance. For example, significant marker-trait associations have been identified for various agronomic traits, which can be used in MAS to accelerate the development of improved peanut cultivars (Pandey et al., 2014; Zhang et al., 2018). Genomic selection (GS) involves using genome-wide markers to predict the breeding value of individuals. This technique has been shown to enhance crop productivity and resilience by improving multiple traits simultaneously. GS can harness allelic diversity and increase selection efficiency, making it a valuable tool for peanut improvement (Dwivedi et al., 2017). Genome-wide association studies (GWAS) are used to identify genetic variants associated with specific traits. GWAS has been employed in peanut to study traits such as yield, disease resistance, and nutritional quality. For instance, a GWAS study identified numerous genomic regions associated with plant height-related traits, providing insights into the genetic basis of these traits (Wang et al., 2021). Additionally, GWAS has been used to identify marker-trait associations for various agronomic traits in peanut (Figure 2) (Pandey et al., 2014). CRISPR/Cas9 and other gene editing technologies offer precise tools for modifying specific genes in peanut. These technologies have the potential to introduce or enhance traits such as disease resistance, drought tolerance, and nutritional quality. Genetic engineering techniques, including CRISPR/Cas9, have been used to develop transgenic peanut plants with improved resistance to biotic and abiotic stresses (Krishna et al., 2015). The continued development and application of gene editing technologies will further accelerate peanut improvement efforts. 5 Case Study: Breeding for Aflatoxin Resistance in Peanut 5.1 Background on aflatoxin contamination and its impact Aflatoxin contamination in peanuts, primarily caused by the fungus Aspergillus flavus, poses a significant threat to food safety and public health due to its toxic, carcinogenic, and immunosuppressive properties (Bhatnagar-Mathur et al., 2015; Yu et al., 2020; Jiang et al., 2021). This contamination can occur at various stages, including pre-harvest, post-harvest, and during storage, severely affecting the quality and marketability of peanuts (Nigam et al., 2009). The presence of aflatoxins in peanuts not only hampers international trade but also poses serious health risks to consumers, making it a critical issue for the peanut industry worldwide (Njoki et al., 2023). 5.2 Genetic resources for aflatoxin resistance Efforts to combat aflatoxin contamination have led to the identification of several genetic resources and resistance-associated genes in peanuts. For instance, quantitative trait loci (QTL) mapping has identified six novel resistant QTLs in the peanut variety J11, which significantly improve resistance to A. flavus infection (Jiang et al., 2021). Additionally, two peanut genotypes, Zh.h0551 and Zh.h2150, have been identified with significantly lower aflatoxin production, and 60 single nucleotide polymorphism (SNP) markers associated with this resistance have been detected (Yu et al., 2020). The AhRAF4 gene family, induced by A. flavus inoculation, has also been characterized, providing insights into the genetic basis of resistance (Deng et al., 2018). 5.3 Breeding approaches and achievements Breeding for aflatoxin resistance in peanuts has employed various approaches, including traditional breeding, molecular breeding, and biotechnological advancements. At ICRISAT, efforts have focused on identifying and utilizing genetic resistance to pre-harvest seed infection and aflatoxin production, although progress has been limited due to the complex nature of resistance and high genotype-environment interactions (Nigam et al., 2009). Transcriptome analyses have identified differentially expressed genes and pathways associated with resistance, such as those involved in disease resistance, hormone biosynthesis, and reactive oxygen species detoxification (Figure 3) (Wang et al., 2013; Soni et al., 2020). Gene co-expression network analysis has further revealed key hub genes that play major roles in resistance to A. flavus (Cui et al., 2022).
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