Mapping the coevolution, leadership and financing of research on viral vectors, RNAi, CRISPR/Cas9 and other genomic editing technologies

Abstract

Genomic editing technologies are developing rapidly, promising significant developments for biomedicine, agriculture and other fields. In the present investigation, we analyzed and compared the process of innovation for six genomic technologies: viral vectors, RNAi, TALENs, meganucleases, ZFNs and CRISPR/Cas including the profile of the main research institutions and their funders, to understand how innovation evolved and what institutions influenced research trajectories. A Web of Science search of papers on viral vectors RNAi, CRISPR/Cas, TALENs, ZFNs and meganucleases was used to build a citation network of 16,746 papers. An analysis of network clustering combined with text mining was performed. For viral vectors, a long-term process of incremental innovation was identified, which was largely publicly funded in the United States and the European Union. The trajectory of RNAi research included clusters related to the study of RNAi as a biological phenomenon and its use in functional genomics, biomedicine and pest control. A British philanthropic organization and a US pharmaceutical company played a key role in the development of basic RNAi research and clinical application respectively, in addition to government and academic institutions. In the case of CRISPR/Cas research, basic science discoveries led to the technical improvements, and these two in turn provided the information required for the development of biomedical, agricultural, livestock and industrial applications. The trajectory of CRISPR/Cas research exhibits a geopolitical division of the investigation efforts between the US, as the main producer and funder of basic research and technical improvements, and Chinese research institutions increasingly leading applied research. Our results reflect a change in the model for financing science, with reduced public financing for basic science and applied research on publicly funded technological developments in the US, and the emergence of China as a scientific superpower, with implications for the development of applications of genomic technologies.

Fig 1. Citation network model of papers on viral vectors (Green nodes), RNAi (Blue nodes) and CRISPR/CAS (Red), meganucleases (Yellow), TALENS (Blush pink), and ZFNs (Brown).

In this network model, nodes represent the papers on these genomic biotechnologies whereas edges (lines) represent the citations between these papers.

Fig 2. Annual number of papers on viral vectors, RNAi and genomic editing platforms in the network model between 1980 and 2018.

Fig 3. Evolution of the citation network model of papers on viral vectors RNAi and genomic editing platforms.

The network model shown in Fig 1 is divided into the following time periods: 1966–2000, 2001–2005, 2006–2010, 2011–2015 and 2016–2019. In each of the time periods only the giant component (the biggest subnetwork in which any two vertices are connected to each other by paths, and which is connected to no additional vertices in the rest of the network) is shown except for the periods 1966–2000 and 2006–2010 in which the second biggest component is shown, which is related to the emergence of RNAi and CRISPR/Cas respectively.

Fig 4. Main interactions among the clusters of papers on viral vectors (green bordered rounded squares), RNAi (Blue) meganucleases (Yellow), TALENs (Blush pink), ZFNs (brown) and CRISPR/Cas (Red).

The networks of clusters in Fig 4 correspond to the following periods: 1966–2000 (A), 2001–2005 (B), 2006–2010 (C), 2011–2015 (D) and 2015–2018 (E). When a cluster is labelled with two colours it means it is composed by papers of two different types of genomic biotechnologies each one with at least 10% of the papers. The arrows represent the sum of the citations between two clusters showing the direction of the flow of information. The pair of numbers inside the arrows represent the number of times that each cluster cited another. If the number of inter-citations is equal in both directions, the arrow is replaced by an edge. The clusters are shown separately depending on whether the most cited investigations in the cluster were conducted only in publicly funded academic institutions or if they also included the participation of philanthropic foundations and/or for-profit organizations. Clusters were also separated according to whether the most cited investigations were conducted exclusively in US institutions or if these included the participation of organizations from other countries. When leading institutions or funding agencies could not be identified, the clusters were labelled with an asterisk. For a more detailed description of the clusters please see S1 Table.

Fig 5. Evolution of the interaction zone between 1980 and 2018.

A) Number of papers in the contact zone per year. B) Citations received from other technologies.