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Potato, (Solanum tuberosum), is one of the most common and important food sources for humans. It is not only essential as a food source but also has many benefits for human health. Potato is ranked as the world’s third non-cereal crop after rice and wheat. Biotic stress, such as viruses, is a common stress in potato-growing areas, leading to reduced tuber yield and quality. This review begins with a description of resistance mechanisms to viruses, historical perspective on potato improvement for virus resistance based on classic and next-generation sequencing (NGS) techniques. Classical breeding has been exploited for improving virus resistant potato. In recent years, plant breeding has quickly changed from phenotypic selection to genotype selection, facilitating the selection process both in terms of time and accuracy. The next-generation sequencing techniques have valuable potential to study the genotype selection through whole-genome re-sequencing (WGRS) and genome-wide association study (GWAS), and RNA-seq has been used to identify markers in virus-resistance potato, facilitating potato breeding for virus resistance. Identification of molecular markers based on new generation sequencing methods and in particular NGS along with bioinformatics tools has facilitated the identification of related markers. The objectives of this review were to better understand virus resistance genes and to recommend the most effective technique and/ or combination approaches for identification of molecular markers in order to breed potato plants resistant to viruses.

Context Development of high-yielding potato cultivars represents the most efficient and sustainable strategy to secure global food and nutrition. In the past decades, numerous quantitative trait loci (QTL) mapping studies have identified various QTLs associated with morphological traits in potato. However, the varying genetic backgrounds of germplasm and the diverse QTL analysis algorithms restrict the utility of identified QTLs for research. Aims One of the primary objectives of breeders is to identify consistent chromosomal regions linked to economically significant quantitative traits associated with yield through QTL analysis. To achieve this, an investigation was conducted to pinpoint the most stable QTLs for traits such as maturity, harvest index, plant height, stem diameter, tuber starch content, sprouting, and flesh colour. Methods In order to detect stable QTLs for major agronomic traits, metaQTL analysis was performed using 294 QTLs from 14 publications. Key results A total of 10 metaQTLs were found to be associated with seven morphological traits. Meta-analysis was considerably refined as compared to the initial QTLs and provided the closest flanking markers for investigated traits and reduce confidence interval mainly to five folds as compared to the mean confidence interval of initial QTLs. The metaQTLs of morphological traits juxtaposed along Chromosomes II, III, IV, and V from independent studies were considered the most stable QTLs over different field trails and genetic background. Conclusions Ten metaQTLs were identified that contain major consensus QTLs for various morphological traits in potato. Implications This study will enable the integration of QTLs to create new cultivars with targeted quantitative traits, thereby accelerating breeding initiatives.