Shani, E. | Search bioRxiv

bioRxiv2018

A seed resource for screening functionally redundant genes and isolation of new mutants impaired in CO2 and ABA responses

The identification of homologous genes with functional overlap in forward genetic screens is severely limited. Here we report the generation of over 14,000 amiRNA-expressing plants that enable screens of the functionally redundant gene space in Arabidopsis. A protocol is developed here for isolating robust and reproducible amiRNA-mutants. Examples of validation approaches and essential controls are presented for two new amiRNA mutants that exhibit genetically redundant phenotypes and circumvent double mutant lethality. In a forward genetic screen for abscisic acid (ABA)-mediated inhibition of seed germination, amiRNAs that target combinations of known redundant ABA receptor and SnRK2 kinase genes were rapidly isolated, providing a strong proof of principle for this approach. A new ABA insensitive amiRNA line is isolated, which targets three genes encoding avirulence-induced gene2-like (AIG2) genes. A thermal imaging screen for plants with impaired stomatal opening in response to low CO2 exposure led here to isolation of a new amiRNA targeting two essential proteasomal subunits, PAB1 and PAB2. The seed library of 14,000 T2 amiRNA lines generated here provides a new platform for forward genetic screens and is being made available to the Arabidopsis Biological Resource Center (ABRC) and optimized procedures for amiRNA screening and controls are described.\n\nHighlightThe generation of over 14,000 amiRNA-expressing plants is reported that are being made publicly available enabling screens of redundant genes in Arabidopsis. Identification of known and new genes is reported.

plant biology↗

bioRxiv2017

CRISPys: Optimal sgRNA design for editing multiple members of a gene family using the CRISPR system

The discovery and development of the CRISPR-Cas9 system in the past few years has made eukaryotic genome editing, and specifically gene knockout for reverse genetics, a simpler, efficient, and effective task. The system is directed to the genomic target site by a programmed single-guide RNA (sgRNA) that base-pairs with the DNA target, subsequently leading to site-specific double-strand breaks. However, many gene families in eukaryotic genomes exhibit partially overlapping functions and, thus, the knockout of one gene might be concealed by the function of the other. In such cases, the reduced specificity of the CRISPR-Cas9 system, which may lead to the cleavage of genomic sites that are not identical to the sgRNA, can be harnessed for the simultaneous knockout of multiple homologous genes. Here, we introduce CRISPys, an algorithm for the optimal design of sgRNAs that would potentially target multiple members of a given gene family. CRISPys first clusters all the potential targets in the input sequences into a hierarchical tree structure that specifies the similarity among them. Then, sgRNAs are proposed in the internal nodes of the tree by embedding mismatches where needed, such that the cleavage efficiencies of the induced targets are maximized. We suggest several approaches for designing the optimal individual sgRNA, and an approach that provides a set of sgRNAs that also accounts for the homologous relationships among gene-family members. We further show by in-silico examination over all gene families in the Solanum lycopersicum genome that our suggested approach outperforms simpler alignment-based techniques.\n\nGraphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY\n\nHighlightsO_LIMany genes in eukaryotic genomes exhibit partially overlapping functions. This imposes difficulties on reverse-genetics, as the knockout of one gene might be concealed by the function of the other.\nC_LIO_LIWe present CRISPys, a graph-based algorithm for the optimal design of CRISPR systems given a set of redundant genes.\nC_LIO_LICRISPys harnesses the lack of specificity of the CRISPR-Cas9 genome editing technique, providing researchers the ability to simultaneously mutate multiple genes.\nC_LIO_LIWe show that CRISPys outperforms existing approaches that are based on simple alignment of the input gene family.\nC_LI

bioinformatics↗