Genome-wide mapping uncovers significant quantitative trait loci associated with yam mosaic virus infection, yield and dry matter content in White Guinea yam (Dioscorea rotundata Poir.)

Emmanuel Amponsah Adjei; Emmanuel Amponsah Adjei; Emmanuel Amponsah Adjei; Thomas Lapaka Odong; Williams Esuma; Ranjana Bhattacharjee; Paterne Angelot Agre; Patrick Olusanmi Adebola; Emmanuel Boache Chamba; Asrat Asfaw; Isaac Onziga Dramadri; Isaac Onziga Dramadri; Sharon Tusiime Mbabazi; Sharon Tusiime Mbabazi; Richard Edema; Richard Edema; Alfred Adebo Ozimati; Alfred Adebo Ozimati; Mildred Ochwo-Ssemakula; Titus Alicai

Genome-wide mapping uncovers significant quantitative trait loci associated with yam mosaic virus infection, yield and dry matter content in White Guinea yam (Dioscorea rotundata Poir.)

2024

IntroductionYam is an important crop for food security in East and West Africa due to its high market value and customer demand. High tuber quality with yield and disease resistance are the main traits for acceptability of yam cultivars across the tropical zone. There has been limited progress in enhancing the production and quality traits of yams, despite the significant socio-economic significance of this crop.MethodTo expedite the development of high-quality yam cultivars in Uganda, traits association study was conducted to identify genomic regions associated with key traits such as disease resistance, high yields, and dry matter content. The association mapping was conducted with multi-random mixed linear model (mrMLM) to compute the associations using five genetic models.ResultsA total of 16 significant single nucleotide polymorphisms (SNPs) markers were identified to be associated with the traits studied. Gene identification analysis revealed the presence of key putative genes such as Vicilin-like seed storage protein At2g28490 (ARATH)and Growth-regulating factor 1 involved in a variety of functions ranging from storage and gene regulation for disease resistance.DiscussionThe results obtained from this work have significant implications for the in-depth analysis of the genetic structure underlying key traits in yam. Additionally, this study emphasizes the identification of SNP variants and genes that may be utilized for genomic-informed selection in order to enhance yield and disease resistance in yams.

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