Plant tissue culture and biotechnology: perspectives in the history and prospects of the International Association of Plant Biotechnology (IAPB)
. In Vitro Cellular and Developmental Biology - Plant 2019
, 590-594. Publisher's VersionAbstract
The evolutionary route from plant tissue culture (IAPTC) to plant biotechnology (IAPB). Plant biotechnology is an evolutionary scientific process, formulated and maintained by our accumulated cultural-societal knowledge and the invention of new technologies (Altman and Mesoudi submitted). It emerged thousands of years ago when wheat, rice, chickpeas, potatoes, and coffee (and other plants) were first domesticated; when grains were fermented by yeasts to produce bread; and when grape juice, barley, and tubers fermentation resulted in wine, alcohol, and beer. The modern era of plant biotechnology started in the beginning of the twentieth century and is associated with the ability to grow plant cells and tissues in vitro, to regenerate and clone new plants and, later, to modify their genetic characteristics by molecular breeding, including molecular marker-assisted selection (MAS), genetic modification (GM), and, more recently, genome editing. Additional novel procedures will most probably follow in the future. © 2019, The Society for In Vitro Biology.
Understanding Agriculture within the Frameworks of Cumulative Cultural Evolution, Gene-Culture Co-Evolution, and Cultural Niche Construction
. Human Ecology 2019
, 483-497. Publisher's VersionAbstract
Since its emergence around 12,000 years ago, agriculture has transformed our species, other species, and the planet on which we all live. Here we argue that the emergence and impact of agriculture can be understood within new theoretical frameworks developing within the evolutionary human sciences. First, the improvement and diversification of agricultural knowledge, practices, and technology is a case of cumulative cultural evolution, with successive modifications accumulated over multiple generations to exceed what any single person could create alone. We discuss how the factors that permit, facilitate, and hinder cumulative cultural evolution might apply to agriculture. Second, agriculture is a prime example of gene-culture co-evolution, where culturally transmitted agricultural practices generate novel selection pressures for genetic evolution. While this point has traditionally been made for the human genome, we expand the concept to include genetic changes in domesticated plants and animals, both via traditional breeding and molecular breeding. Third, agriculture is a powerful niche-constructing activity that has extensively transformed the abiotic, biotic, and social environments. We examine how agricultural knowledge and practice shapes, and are shaped by, social norms and attitudes. We discuss recent biotechnology and associated molecular breeding techniques and present several case studies, including golden rice and stress resistance. Overall, we propose new insights into the co-evolution of human culture and plant genes and the unprecedented contribution of agricultural activities to the construction of unique agriculture-driven anthropogenic biomes. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
Accelerating Climate Resilient Plant Breeding by Applying Next-Generation Artificial Intelligence
. Trends Biotechnol 2019
Breeding crops for high yield and superior adaptability to new and variable climates is imperative to ensure continued food security, biomass production, and ecosystem services. Advances in genomics and phenomics are delivering insights into the complex biological mechanisms that underlie plant functions in response to environmental perturbations. However, linking genotype to phenotype remains a huge challenge and is hampering the optimal application of high-throughput genomics and phenomics to advanced breeding. Critical to success is the need to assimilate large amounts of data into biologically meaningful interpretations. Here, we present the current state of genomics and field phenomics, explore emerging approaches and challenges for multiomics big data integration by means of next-generation (Next-Gen) artificial intelligence (AI), and propose a workable path to improvement.