New technologies in gene editing, vertical farming, and digital solutions promise resilience to climate change, higher yields, and reduced environmental impact. Gene editing enables precise crop improvements, while vertical farming aims to produce food in controlled urban environments. Digital and artificial intelligence (AI) tools are already providing farmers with data-driven insights, market access, and automation. However, neither widespread adoption nor beneficial outcomes are guaranteed. Venture capitalists have invested billions, but the very nature of the industry risks instability and missed opportunities. The viability of many of these technologies is clear, but market adoption will depend on finding ways to provide tangible benefits to consumer groups. The future these technologies create – one of widespread prosperity or deeper inequality – hinges on our choices today. We must build trust, forge partnerships, and develop financing models that ensure these tools benefit all humanity, not just a privileged few.

Various in-vitro (induced pluripotent stem cells–derived) and in-vivo genetic models (animal models like Caenorhabditis elegans, Drosophila melanogaster, zebrafish, rodents, and non-human primates) have been used to study movement disorders such as Parkinson’s disease, hereditary ataxia, Huntington’s disease, dystonia, and essential tremor. These genetic models have provided important clues on the underlying pathophysiologic mechanisms of these diseases and serve as useful platforms to unravel potential therapeutic targets. The next generation of genetic models is promising with the advancement of gene-editing techniques, such as CRISPR-Cas9, brain organoid technology, and identification of novel genes and loci from large-scale genetic studies will facilitate development of new genetic models.

To understand what genes “do,” we have to consider what happens during development. The first and most striking evidence that the local environment matters for the outcome of development was provided by the experiments of embryologists Wilhelm Roux and Hans Driesch in the late nineteenth and early twentieth centuries. Roux had hypothesized that during the cell divisions of the embryo, hereditary particles were unevenly distributed in its cells, thus driving their differentiation. This view entailed that even the first blastomeres (the cells emerging from the first few divisions of the zygote – that is, the fertilized ovum) would each have different hereditary material and that the embryo would thus become a kind of mosaic. Roux decided to test this hypothesis. He assumed that if it were true, destroying a blastomere in the two-cell or the four-cell stage would produce a partially deformed embryo. If it were not true, then the destruction of a blastomere would have no effect. With a hot sterilized needle, Roux punctured one of the blastomeres in a two-cell frog embryo that was thus killed. The other blastomere was left to develop. The outcome was a half-developed embryo; the part occupied by the punctured blastomere was highly disorganized and undifferentiated, whereas those cells resulting from the other blastomere were well-developed and partially differentiated. This result stood as confirmation for Roux’s hypothesis.

During the 1970s, more puzzling observations were made. The first was that the genome of animals contained large amounts of DNA with unique sequences that should correspond to a larger number of genes than anticipated. It was also observed that the RNA molecules in the nuclei of cells were much longer than those found outside the nucleus, in the cytoplasm. These observations started making sense in 1977, when sequences of mRNA were compared to the corresponding DNA sequences. It was shown that certain sequences that existed in the DNA did not exist in the mRNA, and that therefore they must have been somehow removed. It was thus concluded that the genes encoding various proteins in eukaryotes included both coding sequences and ones that were not included in the mRNA that would reach the ribosomes for translation. These “removed” sequences were called introns, to contrast them with the ones that were expressed in translation, which were called exons. The procedure that removed the intron sequences from the initial mRNA and that left only the exon sequences in the mature mRNA was named “RNA splicing.”

One important, and for some the most surprising, conclusion of genome-wide association studies (GWAS) has been that in most cases numerous single nucleotide polymorphism (SNPs) in several genes were found to be associated with the development of a characteristic or the risk of developing a disease. As already mentioned, the main conclusion has been that the relationship between genes and characteristics or diseases is usually a many-to-many one, as many genes may be implicated in the same condition, and the same gene may be implicated in several different conditions. In fact, the same allele may be protective for one disease but increase the risk for another. For example, a variation in the PTPN22 (protein tyrosine phosphatase, nonreceptor type 22) gene on chromosome 1 seems to protect against Crohn’s disease but to predispose to autoimmune diseases. In other cases, certain variants are associated with more than one disease, such as the JAZF1 (JAZF1 zinc finger 1) gene on chromosome 7 that is implicated in prostate cancer and in type 2 diabetes. Therefore, we should forget the simple scheme of gene 1 → condition 1/gene 2 → condition 2, and adopt a richer – and certainly more complicated – representation of the relationship between genes and disease. Additional GWAS on more variants in larger populations might provide a better picture in the future. But insofar as we do not understand all biological processes in detail, all we are left with are probabilistic associations between genes and characteristics (or diseases). The “associated gene” may be informative, but its explanatory potential and clinical value are limited – at least for now.

This chapter is about the public image of genes. But what exactly do we mean by “public”? Here, I use the word as a noun or an adjective vaguely, in order to refer to all ordinary people who are not experts in genetics. I thus contrast them with scientists who are experts in genetics – that is, who have mastered genetics-related knowledge and skills, who practice these as their main occupation, and who have valid genetics-related credentials, confirmed experience, and affirmation by their peers. I must note that both “experts” and “the public” are complex categories that depend on the context and that change over time. There is no single group of nonexperts that we can define as “the” public, as people around the world differ in their perceptions of science, depending on their cultural contexts. We had therefore better refer to “publics.” The differences among experts nowadays might be less significant than those among nonexperts, given today’s global scientific communities, but they do exist. Finally, both the categories of experts and publics have changed across time, depending, on the one hand, on the level of experts’ knowledge and understanding of the natural world, and, on the other hand, on publics’ attitudes toward that knowledge and understanding.

If you were taught Mendelian genetics at school (see Figures 2.1 and 2.2) you should be aware that it is an oversimplified model that does not work for most cases of inherited characteristics. Human eye color is a textbook example of a monogenic characteristic. It refers to the color of the iris – the colored circle in the middle of the eye. The iris comprises two tissue layers, an inner one called the iris pigment epithelium and an outer one called the anterior iridial stroma. It is the density and cellular composition of the latter that mostly affects the color of the iris. The melanocyte cells of the anterior iridial stroma store melanin in organelles called melanosomes. White light entering the iris can absorb or reflect a spectrum of wavelengths, giving rise to the three common iris colors (blue, green–hazel, and brown) and their variations. Blue eyes contain minimal pigment levels and melanosome numbers; green–hazel eyes have moderate pigment levels and melanosome numbers; and brown eyes are the result of high melanin levels and melanosome numbers. Textbook accounts often explain that a dominant allele B is responsible for brown color, whereas a recessive allele b is responsible for blue color (Figure 4.1). According to such accounts, parents with brown eyes can have children with blue eyes, but it is not possible for parents with blue eyes to have children with brown eyes. This pattern of inheritance was first described at the beginning of the twentieth century and it is still taught in schools, although it became almost immediately evident that there were exceptions, such as that two parents with blue eyes could have offspring with brown or dark hazel eyes.

Perhaps you were taught at school that genetics began with Gregor Mendel. Because of his experiments with peas, Mendel is considered to be a pioneer of genetics and the person who discovered the laws of heredity. According to the model of “Mendelian inheritance,” things are rather simple and straightforward with inherited characteristics. Some alleles are dominant – that is, they impose their effects on other alleles that are recessive. An individual who carries two recessive alleles exhibits the respective “recessive” characteristic, whereas a single dominant allele is sufficient for the “dominant” version of the characteristic to appear. In this sense, particular genes determine particular characteristics (e.g., seed color in peas), and particular alleles of those genes determine particular versions of the respective characteristics. Mendel, the story goes, discovered that characteristics are controlled by hereditary factors, the inheritance of which follows two laws: the law of segregation and the law of independent assortment.

A large and highly heterogeneous group of individuals conducts genetic and genomic research outside of traditional corporate and academic settings. They can be an important source of innovation, but their activities largely take place beyond the purview of existing regulatory systems for promoting safe and ethical practices. Historically the gene-targeting technology available for non-traditional biology (NTB) experiments has been limited, and therefore they have attracted little regulatory attention. New techniques such as CRISPR-cas9, however, may create a need for alternate governance approaches. This chapter explores whether alternate governance approaches might be needed and, if so, what governance approaches would be most likely to enable non-traditional experiments to be conducted safely and ethically.