Biological functions are orchestrated by intricate networks of interacting genetic elements. Predicting the interaction landscape remains a challenge for systems biology and new research tools allowing simple and rapid mapping of sequence to function are desirable. Here, we describe CRI-SPA, a method allowing the transfer of chromosomal genetic features from a CRI-SPA Donor strain to arrayed strains in large libraries of Saccharomyces cerevisiae. CRI-SPA is based on mating, CRISPR-Cas9-induced gene conversion, and Selective Ploidy Ablation. CRI-SPA can be massively parallelized with automation and can be executed within a week. We demonstrate the power of CRI-SPA by transferring four genes that enable betaxanthin production into each strain of the yeast knockout collection (≈4800 strains). Using this setup, we show that CRI-SPA is highly efficient and reproducible, and even allows marker-free transfer of genetic features. Moreover, we validate a set of CRI-SPA hits by showing that their phenotypes correlate strongly with the phenotypes of the corresponding mutant strains recreated by reverse genetic engineering. Hence, our results provide a genome-wide overview of the genetic requirements for betaxanthin production. We envision that the simplicity, speed, and reliability offered by CRI-SPA will make it a versatile tool to forward systems-level understanding of biological processes.

Scientists have always played an important role in informing policy decisions. However, many controversial policy problems regarding science and technology, such as agricultural biotechnology, are often characterised by low value consensus and high level of complexity. In these circumstances various policy actors legitimate their policy preferences using science. In this article, we challenge the linear model of science and policy and argue that the stakeholder model of science in policy is more appropriate for governance of controversial policy problems regarding science and technology. We build our argument on available literature and empirical data from interviews and two online surveys. We choose agricultural biotechnology as the case study to illustrate scientists' perception about their role in policy-making. Our study illustrates that agricultural biotechnology scientists sympathise with the stakeholder model of science and policy. However, there is a gap between perceived ideal role for scientists in policy-making and the role, which these scientists actually take.