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Copyright © 2008 by the Genetics Society of America Efficient Ends-Out Gene Targeting In Drosophila *Department of Cell Biology and Physiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennyslvania 15261 and †Howard Hughes Medical Institute, Departments of Physiology and Biochemistry, University of California, San Francisco, California 94143 1These authors contributed equally to this article. 2Corresponding author: Department of Cell Biology and Physiology, University of Pittsburgh School of Medicine, S325 BST, 3500 Terrace St., Pittsburgh, PA 15261. E-mail: yhong/at/pitt.edu Communicating editor: J. A. Lopez Received April 22, 2008; Accepted June 14, 2008. This article has been cited by other articles in PMC.Abstract In this report, we describe several approaches to improve the scalability and throughput of major genetic crosses in ends-out gene targeting. We generated new sets of targeting vectors and fly stocks and introduced a novel negative selection marker that drastically reduced the frequency of false-positive targeting candidates. THE development of homologous recombination-based gene targeting is a landmark breakthrough in Drosophila genetics (Rong and Golic 2000; Gong and Golic 2003). In particular, the so-called “ends-out” or replacement-type gene targeting offers a straightforward approach for generating either knockout or knockin alleles. To date, there are already >20 genes that have been modified by ends-out targeting (supplemental Table 1). Nonetheless, the frequency of target-specific homologous recombination in Drosophila varies tremendously, ranging from >1/200 gametes (Manoli et al. 2005) to <1/350,000 (Jones et al. 2007) (also Y. Hong, unpublished data), i.e., a >1800-fold difference. In cases of low targeting efficiency (<1/100,000 gametes), ends-out targeting can be exceedingly time and labor intensive. Here, we optimized the current ends-out targeting scheme by focusing on improving the scalability and throughput of its major genetic crosses. As illustrated in Figure 1a
For the targeting cross, the number of P{donor}*/hs-FLP, hs-I-SceI virgin females directly determines the scale of the whole targeting experiment. Genes that are resistant to homologous recombination may require collecting and sorting >15,000 virgins from the targeting cross (Larsson et al. 2004), which is extremely labor intensive due to the time-sensitive nature of virgin collection and the genotyping process. To eliminate this major bottleneck in scaling up the targeting cross, we modified the original hs-FLP, hs-I-SceI stocks by replacing their Y chromosomes and balancer chromosomes with ones that contain hs-hid transgenes (Grether et al. 1995). We named these modified stocks “6934-hid” and “6935-hid” (Figure 1b For screening and mapping crosses, we found their throughput was often severely limited by the high background of false positives, which may represent >95–99.9% of preliminary candidates (J. Huang, W. Zhou, and Y. Hong, unpublished results, and see below). Therefore, we introduced a negative selection marker into the current ends-out targeting scheme, so the majority of nontargeted integrations may be directly eliminated before they are subject to any further screening and mapping efforts. Ectopic expression of another cell-death gene reaper (rpr), similar to hid, also causes strong lethality (White et al. 1996). As illustrated in Figure 2b mEosFPKI}). Once the donor DNA fragment is recombined into the target gene locus, UAS-Rpr will be lost due to homologous recombination. In contrast, nontargeted integrations will likely retain the donor DNA fragment with an intact UAS-Rpr module (“Rpr+”). By using proper Gal4 driver stocks to set up the screening cross, Rpr+/Gal4 false-positive candidates will be directly eliminated due to the ectopic expression of Rpr.
To implement the UAS-Rpr selection, we made a new set of ends-out targeting vectors, pRK1 and pRK2 (Figure 2a mEosFPKI knockin construct (Figure 2bTo evaluate the effectiveness of UAS-Rpr without any bias, we first carried out crb mEosFPKI knockin experiments without UAS-Rpr selection (similar to Figure 1a mEosFPKI would eliminate >96% (253/263) of false positives (Table 1). In addition, UAS-Rpr selection also eliminates tandem-insertion mutants (Gong and Golic 2003), which can be difficult to distinguish from true targeting candidates by simple PCR assays (supplemental Figure 1, b and c). The homologous recombination frequency of crb mEosFPKI is ~1/7000 if only considering the male candidates.
We then decided to carry out a large-scale dArf6KO targeting experiment by taking full advantage of the new reagents and methods described here, as we failed at dArf6KO targeting on the basis of the original pEndsOut2 vector by screening ~1.6 × 105 screening cross progenies (W. Zhou and Y. Hong, unpublished results). We recloned the same 5′ and 3′ homologous arms into the pRK2-based vector. By using 6935-hid to set up the targeting cross, we easily collected >2 × 104 virgin females. Twelve thousand of them were mated with w/Y; Pin/CyO; Gal4221[w−] males to set up the screening cross (Figure 1d
Compared with the “rapid scheme” in which preliminary candidates were screened for the loss of FRT sites (Rong et al. 2002; Gong and Golic 2003), UAS-Rpr selection is more efficient since it directly eliminates false positives. In addition, we found that the majority of the false positives (57–87%) had damaged FRT sites (Table 1); therefore, they could only be eliminated by UAS-Rpr selection but not by the FRT test. Since the I-SceI sites are positioned rather close to the FRT sites in ends-out targeting constructs, we speculate that the frequent FRT damage seen here was most likely due to the double-strand DNA repair process triggered by the premature cut of I-SceI sites (Bellaiche et al. 1999; Gong and Golic 2003). Separating FRT and I-SceI sites further away in future pRK-based targeting vectors should further reduce the frequency of false positives. Consistently, the Golic lab reported that the frequency of false positives was low using the pW25 targeting vector in which FRT and I-SceI were separated by 100–150 bp (Gong and Golic 2004). Since pRK-based vectors may not be suitable for making Gal4 knockin alleles, pW25 series vectors should be excellent alternatives. In summary, for a targeting experiment with an expected homologous recombination frequency of ~1/100,000 gametes, we estimate that our 6934-hid/6935-hid stocks and UAS-Rpr selection reduced the work load of genetic crosses to a level comparable to a routine P-excision experiment. In addition, our new targeting vectors, such as pRK2, should significantly facilitate the molecular cloning and transgenesis of targeting constructs due to the enhanced multiple cloning sites and w+ expression. Overall, these new reagents and methods should significantly increase the success rate of targeting experiments on genes that are resistant to homologous recombination. Acknowledgments We are grateful to Jeff Sekelsky for pBS70W and pEndsOut2 plasmids, Leon Perniciaro for help in screening in dArf6KO targeting candidates, Ulrich Nienhaus for EosFP constructs, Fabrice Rogers for hs-hid stocks, and Fen-Biao Gao, Sige Zou, Peizhang Xu, and Koen Venken for comments on the manuscript. Y.N.J is an investigator of the Howard Hughes Medical Institute. pRK1 and pRK2 will be donated to the Drosophila Genomic Resource Center (DGRC) and 6934-hid and 6935-hid stocks will be donated to the Bloomington Stock Center. This work is supported by start-up funds from the University of Pittsburgh School of Medicine (Y.H.). References
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