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2Gs and plant architecture: breaking grain yield ceiling through breeding approaches for next wave of revolution in rice ( Oryza sativa L.).

Gurjeet SinghNavdeep KaurRenu KhannaRupinder KaurSantosh GudiRajvir KaurNavjot SidhuYogesh VikalG S Mangat
Published in: Critical reviews in biotechnology (2022)
Rice is a principal food crop for more than half of the global population. Grain number and grain weight (2Gs) are the two complex traits controlled by several quantitative trait loci (QTLs) and are considered the most critical components for yield enhancement in rice. Novel molecular biology and QTL mapping strategies can be utilized in dissecting the complex genetic architecture of these traits. Discovering the valuable genes/QTLs associated with 2Gs traits hidden in the rice genome and utilizing them in breeding programs may bring a revolution in rice production. Furthermore, the positional cloning and functional characterization of identified genes and QTLs may aid in understanding the molecular mechanisms underlying the 2Gs traits. In addition, knowledge of modern genomic tools aids the understanding of the nature of plant and panicle architecture, which enhances their photosynthetic activity. Rice researchers continue to combine important yield component traits (including 2Gs for the yield ceiling) by utilizing modern breeding tools, such as marker-assisted selection (MAS), haplotype-based breeding, and allele mining. Physical co-localization of GW7 (for grain weight) and DEP2 (for grain number) genes present on chromosome 7 revealed the possibility of simultaneous introgression of these two genes, if desirable allelic variants were found in the single donor parent. This review article will reveal the genetic nature of 2Gs traits and use this knowledge to break the yield ceiling by using different breeding and biotechnological tools, which will sustain the world's food requirements.
Keyphrases
  • genome wide
  • copy number
  • dna methylation
  • healthcare
  • gene expression
  • high resolution
  • weight loss
  • mental health
  • public health
  • climate change
  • weight gain
  • risk assessment
  • single cell