One-step efficient generation of dual-function conditional knockout and geno-tagging alleles in zebrafish
- Peking University, China
- Peking University Shenzhen Graduate School, China
- Gcrispr (Tianjin) Genetic Technology, China
Abstract
CRISPR/Cas systems are widely used to knockout genes by inducing indel mutations, which are prone to genetic compensation. Complex genome modifications such as knockin (KI) might bypass compensation, though difficult to practice due to low efficiency. Moreover, no 'two-in-one' KI strategy combining conditional knockout (CKO) with fluorescent gene-labeling or further allele-labeling has been reported. Here, we developed a dual-cassette-donor strategy and achieved one-step and efficient generation of dual-function KI alleles at tbx5a and kctd10 loci in zebrafish via targeted insertion. These alleles display fluorescent gene-tagging and CKO effects before and after Cre induction, respectively. By introducing a second fluorescent reporter, geno-tagging effects were achieved at tbx5a and sox10 loci, exhibiting CKO coupled with fluorescent reporter switch upon Cre induction, enabling tracing of three distinct genotypes. We found that LiCl purification of gRNA is critical for highly efficient KI, and preselection of founders allows the efficient germline recovery of KI events.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files.
Article and author information
Author details
Funding
National Key Research and Development Program of China (2018YFA0801000)
- Bo Zhang
National Key Research and Development Program of China (2016YFA0100500)
- Bo Zhang
National Key Basic Research Program of China (2015CB942803)
- Bo Zhang
National Natural Science Foundation of China (31671500)
- Bo Zhang
National Natural Science Foundation of China (31871458)
- Bo Zhang
National Natural Science Foundation of China (81371264)
- Bo Zhang
PKU Qidong-SLS Innovation Fund
- Bo Zhang
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Darius Balciunas, Temple University, United States
Ethics
Animal experimentation: All animal experiments were approved by Institutional Animal Care and Use Committee (IACUC) of Peking University. The reference from IACUC of Peking University is LSC-ZhangB-2.
Version history
- Received: April 30, 2019
- Accepted: October 30, 2019
- Accepted Manuscript published: October 30, 2019 (version 1)
- Version of Record published: November 11, 2019 (version 2)
Copyright
© 2019, Li et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 8,210
- views
-
- 1,132
- downloads
-
- 30
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
One-step efficient generation of dual-function conditional knockout and geno-tagging alleles in zebrafish
eLife 8:e48081.
https://doi.org/10.7554/eLife.48081
Further reading
-
- Genetics and Genomics
- Neuroscience
Genome-wide association studies have revealed >270 loci associated with schizophrenia risk, yet these genetic factors do not seem to be sufficient to fully explain the molecular determinants behind this psychiatric condition. Epigenetic marks such as post-translational histone modifications remain largely plastic during development and adulthood, allowing a dynamic impact of environmental factors, including antipsychotic medications, on access to genes and regulatory elements. However, few studies so far have profiled cell-specific genome-wide histone modifications in postmortem brain samples from schizophrenia subjects, or the effect of antipsychotic treatment on such epigenetic marks. Here, we conducted ChIP-seq analyses focusing on histone marks indicative of active enhancers (H3K27ac) and active promoters (H3K4me3), alongside RNA-seq, using frontal cortex samples from antipsychotic-free (AF) and antipsychotic-treated (AT) individuals with schizophrenia, as well as individually matched controls (n=58). Schizophrenia subjects exhibited thousands of neuronal and non-neuronal epigenetic differences at regions that included several susceptibility genetic loci, such as NRG1, DISC1, and DRD3. By analyzing the AF and AT cohorts separately, we identified schizophrenia-associated alterations in specific transcription factors, their regulatees, and epigenomic and transcriptomic features that were reversed by antipsychotic treatment; as well as those that represented a consequence of antipsychotic medication rather than a hallmark of schizophrenia in postmortem human brain samples. Notably, we also found that the effect of age on epigenomic landscapes was more pronounced in frontal cortex of AT-schizophrenics, as compared to AF-schizophrenics and controls. Together, these data provide important evidence of epigenetic alterations in the frontal cortex of individuals with schizophrenia, and remark for the first time on the impact of age and antipsychotic treatment on chromatin organization.
-
- Computational and Systems Biology
- Genetics and Genomics
We propose a new framework for human genetic association studies: at each locus, a deep learning model (in this study, Sei) is used to calculate the functional genomic activity score for two haplotypes per individual. This score, defined as the Haplotype Function Score (HFS), replaces the original genotype in association studies. Applying the HFS framework to 14 complex traits in the UK Biobank, we identified 3619 independent HFS–trait associations with a significance of p < 5 × 10−8. Fine-mapping revealed 2699 causal associations, corresponding to a median increase of 63 causal findings per trait compared with single-nucleotide polymorphism (SNP)-based analysis. HFS-based enrichment analysis uncovered 727 pathway–trait associations and 153 tissue–trait associations with strong biological interpretability, including ‘circadian pathway-chronotype’ and ‘arachidonic acid-intelligence’. Lastly, we applied least absolute shrinkage and selection operator (LASSO) regression to integrate HFS prediction score with SNP-based polygenic risk scores, which showed an improvement of 16.1–39.8% in cross-ancestry polygenic prediction. We concluded that HFS is a promising strategy for understanding the genetic basis of human complex traits.
