Integrated Genomic Selection for Accelerating Breeding Programs of Climate-Smart Cereals

Abstract

Rapidly rising population and climate changes are two critical issues that require immediate action to achieve sustainable development goals. The rising population is posing increased demand for food, thereby pushing for an acceleration in agricultural production. Furthermore, increased anthropogenic activities have resulted in environmental pollution such as water pollution and soil degradation as well as alterations in the composition and concentration of environmental gases. These changes are affecting not only biodiversity loss but also affecting the physio-biochemical processes of crop plants, resulting in a stress-induced decline in crop yield. To overcome such problems and ensure the supply of food material, consistent efforts are being made to develop strategies and techniques to increase crop yield and to enhance tolerance toward climate-induced stress. Plant breeding evolved after domestication and initially remained dependent on phenotype-based selection for crop improvement. But it has grown through cytological and biochemical methods, and the newer contemporary methods are based on DNA-marker-based strategies that help in the selection of agronomically useful traits. These are now supported by high-end molecular biology tools like PCR, high-throughput genotyping and phenotyping, data from crop morpho-physiology, statistical tools, bioinformatics, and machine learning. After establishing its worth in animal breeding, genomic selection (GS), an improved variant of marker-assisted selection (MAS), has made its way into crop-breeding programs as a powerful selection tool. To develop novel breeding programs as well as innovative marker-based models for genetic evaluation, GS makes use of molecular genetic markers. GS can amend complex traits like yield as well as shorten the breeding period, making it advantageous over pedigree breeding and marker-assisted selection (MAS). It reduces the time and resources that are required for plant breeding while allowing for an increased genetic gain of complex attributes. It has been taken to new heights by integrating innovative and advanced technologies such as speed breeding, machine learning, and environmental/weather data to further harness the GS potential, an approach known as integrated genomic selection (IGS). This review highlights the IGS strategies, procedures, integrated approaches, and associated emerging issues, with a special emphasis on cereal crops. In this domain, efforts have been taken to highlight the potential of this cutting-edge innovation to develop climate-smart crops that can endure abiotic stresses with the motive of keeping production and quality at par with the global food demand.

Toward Food Security in 2050: Gene Pyramiding for Climate-Smart Rice

“…Genomic selection is a subset of MAB in which each QTL is examined for linkage disequilibrium (LD) with at least one genetic marker [195]. This selection holds great potential to accelerate breeding progress and is cost-effective via early selection before phenotypes are measured [196], the ability to assess both additive and non-additive genetic variations accelerates the breeding cycle, making it easier to find superior genotypes quickly [197], and it is a possible strategy for improving complicated trait genetics while significantly reducing breeding cycles [195]. By incorporating machine learning-based predictive modelling in MAS, genomic selection achieves even more genetic gain while shortening crop life cycles.…”

Genetic and Genomic Pathways to Improved Wheat (Triticum aestivum L.) Yields: A Review

“…Marker-assisted breeding is one of the most innovative methods for crop improvement, made possible by the development of technology in biological sciences MAB [22]. This method uses molecular markers to identify and select genetic features in plants enabling a more accurate and effective breeding procedure.…”

“…Researchers have discovered important genes and regulatory networks linked to productivity, stress resistance, and other agronomic traits by deciphering the complex genomic architecture of wheat [37]. Breeders may now expedite the development of high-yielding wheat varieties that are adaptable to changing environmental conditions through markerassisted selection, genome-wide association studies, and genomic selection made possible by NGS data [22,38]. Furthermore, these advanced sequencing tools allow for the early detection of genetic markers related to yield, facilitating quicker and more efficient breeding cycles.…”

“…Molecular diagnostics has become a crucial tool, in this context, to identify and characterize allelic variants linked to these high-impact genes. Researchers can successfully identify the specific allelic variations that lead to improved yield, disease resistance, and other desired features by utilizing cutting-edge molecular approaches, including marker-assisted selection and genome sequencing [22,55].…”

A Look at Genomic Selection Techniques for Climate Change Adaptation and Production in Livestock

“…Notably, traits such as the slick hair coat phenotype play pivotal roles in thermoregulatory mechanisms observed in tropically adapted cattle breeds [6]. Climate change poses significant challenges to existing livestock systems on a global scale, exerting profound influences on feed availability, water resources, animal health, and overall production dynamics [7,8]. The resultant implications extend across the entire livestock product supply chain, encompassing processing, storage, transport, retail, and consumption [9].…”