Efficient High-throughput Techniques for the Analysis of Disease- Resistant Plant Varieties and Detection of Food Adulteration

Curr Protein Pept Sci. 2022;23(1):20-32. doi: 10.2174/1389203723666211223111238.

Abstract

Over the past two decades, the advances in the next generation sequencing (NGS) platforms have led to the identification of numerous genes/QTLs at high-resolution for their potential use in crop improvement. The genomic resources generated through these high-throughput sequencing techniques have been efficiently used in screening of particular gene of interest particularly for numerous types of plant stresses and quality traits. Subsequently, the identified-markers linked to particular trait have been used in Marker-Assisted Backcross Breeding (MABB) activities. Besides, these markers are also being used to catalogue the food crops for detection of adulteration to improve the quality of food. With the advancement of technologies, the genomic resources are originating with new markers; however, to use these markers efficiently in crop breeding, High-Throughput Techniques (HTT) such as multiplex PCR and Capillary Electrophoresis (CE) can be exploited. Robustness, ease of operation, good reproducibility and low cost are the main advantages of multiplex PCR and CE. The CE is capable of separating and characterizing proteins with simplicity, speed and small sample requirements. Keeping in view the availability of vast data generated through NGS techniques and development of numerous markers, there is a need to use these resources efficiently in crop improvement programmes. In summary, this review describes the use of molecular markers in the screening of resistance genes in breeding programme and detection of adulterations in food crops using high-throughput techniques.

Keywords: Biotic stress; NGS technique; genomic approach; quality; security; varietal mixture.

Publication types

  • Review

MeSH terms

  • Crops, Agricultural / genetics
  • Food Contamination
  • Plant Breeding* / methods
  • Quantitative Trait Loci*
  • Reproducibility of Results