Precision breeding in a changing climate: unlocking resilience through omics and gene editing.

Journal: Functional & integrative genomics
Published Date:

Abstract

Climate change, rising global food demand, and shrinking resources require transformative innovations in crop breeding. This review outlines recent advances in new breeding technologies (NBTs), including molecular markers, genome-wide association studies (GWAS), genomic selection (GS), next-generation sequencing (NGS), and gene editing (GE) tools such as the clustered regularly interspaced short palindromic repeat (CRISPR/Cas), base editing, and prime editing. These methods enable the accurate improvement of traits, thereby accelerating the development of crops resistant to both abiotic and biotic stresses. The integration of multi-omics platforms, including genomics, transcriptomics, proteomics, metabolomics, and phenomics, provides a comprehensive framework for deciphering and manipulating complex trait architectures. Artificial intelligence (AI) and machine learning (ML) enhance precision breeding by providing data-driven insights and enabling the forecasting of traits. Emphasis is also placed on combining gene editing with other strategies, such as speed breeding, to accelerate the development of traits. This review underscores the importance of an integrated systems biology approach that combines multi-omics, gene editing, AI, and speed breeding to accelerate the development of climate-resilient, high-yielding, and nutritionally enhanced crops. The integration of these innovative technologies holds great promise for addressing global food security, environmental sustainability, and agricultural resilience in the face of climate change. A strategic framework for the future of plant breeding is outlined, emphasizing the importance of interdisciplinary collaboration in building a sustainable agricultural future.

Authors

  • Tarali Borgohain
    Center for Biotechnology, Biological Sciences and Technology Division, CSIR-North East Institute of Science and Technology (CSIR-NEIST), Jorhat, Assam, 785006, India.
  • Remya Suma
    Center for Biotechnology, Biological Sciences and Technology Division, CSIR-North East Institute of Science and Technology (CSIR-NEIST), Jorhat, Assam, 785006, India.
  • Mantesh Muttappagol
    Center for Biotechnology, Biological Sciences and Technology Division, CSIR-North East Institute of Science and Technology (CSIR-NEIST), Jorhat, Assam, 785006, India.
  • Banashree Saikia
    Center for Biotechnology, Biological Sciences and Technology Division, CSIR-North East Institute of Science and Technology (CSIR-NEIST), Jorhat, Assam, 785006, India.
  • Arnika Keithellakpam
    Center for Biotechnology, Biological Sciences and Technology Division, CSIR-North East Institute of Science and Technology (CSIR-NEIST), Jorhat, Assam, 785006, India.
  • Adity Laskar
    Center for Biotechnology, Biological Sciences and Technology Division, CSIR-North East Institute of Science and Technology (CSIR-NEIST), Jorhat, Assam, 785006, India.
  • Shridhar Shivakumar Hiremath
    Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201 002, India.
  • Udita Basu
    Biological Sciences and Technology Division, CSIR-North East Institute of Science and Technology, Jorhat, 785006, Assam, India. [email protected].
  • Natarajan Velmurugan
    Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201 002, India.
  • Sudhakar Reddy Palakolanu
    Cell, Molecular Biology and Trait Engineering Cluster, International Crops Research Institute for the Semi-Arid Tropics, Patancheru, Hyderabad, Telangana, 502 324, India. [email protected].
  • Channakeshavaiah Chikkaputtaiah
    Center for Biotechnology, Biological Sciences and Technology Division, CSIR-North East Institute of Science and Technology (CSIR-NEIST), Jorhat, Assam, 785006, India. [email protected].