AUTHOR=Adjei Emmanuel Amponsah , Odong Thomas Lapaka , Esuma Williams , Bhattacharjee Ranjana , Agre Paterne Angelot , Adebola Patrick Olusanmi , Chamba Emmanuel Boache , Asfaw Asrat , Dramadri Isaac Onziga , Mbabazi Sharon Tusiime , Edema Richard , Ozimati Alfred Adebo , Ochwo-Ssemakula Mildred , Alicai Titus TITLE=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.) JOURNAL=Frontiers in Horticulture VOLUME=3 YEAR=2024 URL=https://www.frontiersin.org/journals/horticulture/articles/10.3389/fhort.2024.1365567 DOI=10.3389/fhort.2024.1365567 ISSN=2813-3595 ABSTRACT=Introduction

Yam 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.

Method

To 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.

Results

A 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.

Discussion

The 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.