Chapter 3: Optimisation of CRISPR-Cas9 genomic editing of mammary cells Overview
In recent years, the widespread application of genome-wide association studies (GWAS) has identified sequence variants associated with bovine milk composition and production. The ultimate goals of these studies are to provide information for genomic selection (GS), and define the genetic underpinnings of these traits to provide insight into mammary gland physiology. However, accomplishing the latter goal requires defining the causative variant(s) that is responsible for the genetic signal at a given locus; its mechanism of action, and implicated gene(s). In GWAS, it is often difficult to determine which genetic variant is responsible for the phenotype using statistical methods alone, as the tight linkage disequilibrium (LD) between markers provides multiple candidates to choose from. As such, dissecting statistically indistinguishable variants from each other requires functional experiments to provide information about the effect of specific associated variants. While the prediction of functional consequences for coding variants may be more straightforward, it is difficult to predict the effects of non-coding variants, given the diverse functions of non-coding DNA, the incomplete annotation of regulatory elements, and the many mechanisms of regulatory control.
Recent advancements in genomic and genetic technologies are providing new approaches to understand the function of non-coding genetic variants, gene function, and how this contributes to complex traits. Namely, the re-engineering of mammalian genomes using genome editing technologies; zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), engineered meganucleases, and most recently the clustered regularly-interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) protein system, enables the targeted investigation of specific variants in isogenic backgrounds. In particular, the CRISPR-Cas9 system is revolutionising the targeted editing of mammalian genomes with unparalleled efficiency, ease of use and scalability. This is reflected in the rapid evolution of the technology and its widespread application, including functional knockout of individual genes (Wagner, Platt, Goldfless, Zhang, & Niles, 2014), large scale knock-out and knock-in screens (T. Wang et al., 2014), in vivo mouse models (Aida et al., 2015), and human clinical trials (Cyranoski, 2016).
The first experimental chapter of this thesis describes the optimisation of CRISPR-Cas9 genome editing of a bovine mammary cell line. Experiments presented include the optimisation of the delivery method and CRISPR-Cas9 expression system, and the evaluation of the NHEJ and HDR editing efficiency of 28 gRNAs. Experiments towards multiplexing targets and the enrichment of transfected cells are also presented, and ultimately continued research using the tools generated here will allow for the establishment of efficient editing of mammary cell lines to study the effects of candidate causative variants for bovine milk composition and production traits.
Investigate the use of the CRISPR-Cas9 system as a method for the genome editing of a bovine mammary cell line.
- Identify the optimal Cas9 and gRNA delivery method and expression system that achieves efficient genome editing at the AGPAT6 chr27:36198117T>TGGC target locus.
- Use the optimal CRISPR-Cas9 protocol identified above to compare the efficiency of the NHEJ and HDR method of gene editing at 28 target loci.
- Identify the optimal concentration of ssODN HDR repair template to achieve maximal HDR at the MGST1 chr5:93946027T>A target locus.
- Identify the optimal CRISPR-Cas9 system that achieves efficient gene editing at multiple loci.
- Identify a cell selection protocol that enriches for putative CRISPR-Cas9 genome editing events.
The research strategy presented in this chapter is adapted from the IDT CRISPR-Cas9 genome editing protocol (http://sg.idtdna.com/; see Chapter 1 for review of CRISPR-Cas9 genome editing). This protocol has been optimised for the lipofection of Alt-R CRISPR-Cas9 RNPs in HEK293 cells but has shown to be translatable to other adherent, immortalised eukaryotic cell lines. Optimisation experiments based on this protocol were conducted to find the conditions that demonstrate maximal editing efficiency and minimal cell toxicity in the bovine mammary epithelial cell line, MAC-T (Huynh et al., 1991). Following this, the efficiency of NHEJ and HDR editing at 28 loci, encompassing candidate causative variants at four QTL influencing bovine milk production, were investigated. The 28 target variants represent 13 candidate causative variants within the MGST1 locus, 13 candidate causative variants in the AGPAT6 locus, and one variant in both the DGAT1 and LGB loci identified previously (Grisart et al., 2004; Kuss et al., 2003; M. D. Littlejohn et al., 2016; M. D. Littlejohn, Tiplady, et al., 2014).
To conduct CRISPR-Cas9 mediated genome editing of the MAC-T mammary cell line, it was first necessary to determine the genetic background of these cells in order to design appropriate gRNAs and ssODN HDR templates. Further, the endogenous expression of AGPAT6, DGAT1, LGB and MGST1 in this cell line needs to be detectable by real time quantitative PCR (RT-qPCR) to ensure that the influence of specific genetic variants introduced through CRISPR-Cas9 on gene expression could be investigated.
‘Wild-type’ genotype determination for target variants of the MAC-T cell line
The genotypes for the target genetic variants in Table 3.1 were established from whole genome sequencing (WGS) of genomic DNA extracted from an early passage of MAC-T cells. At passage (~90% confluent), the MAC-T cells were stripped from a T75 flask using 3 mL trypsin-EDTA (Invitrogen). Following trypsin treatment, cells were resuspended in 1 mL PBS (Invitrogen) and passed through a 25-gauge needle 20 times. Then, genomic DNA was isolated using an AxyPrep MiniPrep Kit (Axygen) as per the manufacturer’s protocol. The isolated DNA was then purified using AMPure Bead purification (Agencourt), by adding a 1.2x volume of AMPure beads to the sample and following the manufacturer’s protocol. The DNA was quantified and the quality of DNA was checked by electrophoresis on a 2% agarose gel. After quantification, an aliquot of the DNA was sent to the Australian Genome Research Facility (AGRF; Brisbane, Australia), who performed WGS using v3 sequencing chemistry and 2 x 125 bp read lengths on the Illumina HiSeq 2000 instrument.
Alignments were performed using Borrow-Wheeler Aligner mem (BWA mem; version 0.7.12; Li, 2013) using the UMD3.1 reference genome and default parameters. The mapped sequence data was interrogated at each of the target loci to determine the MAC-T genotypes for the variants in Table 3.1, and was performed manually to ensure high confidence of genotype assignment.
Gene expression phenotypes
RT-qPCR was used to quantify the endogenous expression of AGPAT6, DGAT1, LGB and MGST1 in the MAC-T cell line. Assays for these genes were designed as described in General Methods, with the primer and probe sequences presented in Appendix I.
RNA was extracted from untransfected MAC-T cells (as described in General Methods), and was DNase-treated and quantified before use as input for cDNA synthesis by RT-qPCR. These reactions used the SuperScript® III First-Strand Synthesis SuperMix Kit (Invitrogen), with 2.5 µg DNase-treated RNA in each 20 µL reaction.
Serial 5x cDNA standard curves were generated from the cDNA and each concentration was run in triplicate for each of the assays. Assays for EIF3K and RPS15A were also conducted to serve endogenous control calculations, performed in the same way as that described for other assays.
All assays readily detected the different transcripts at PCR efficiencies between 1.82 and 2.04. The average relative expression of AGPAT6, DGAT1, LGB and MGST1 is shown in Figure 3.1.
Chapter 1: Introduction
1.2Mammary gland and lactation biology
1.5Genetics of dairy cows and milk production
1.6Causative variant discovery
1.7Molecular methods and technologies to identify causative variants
1. Chapter 2: General Materials and Methods
2.1 General materials
2.2 General methods
3. Chapter 3: Optimisation of CRISPR-Cas9 genomic editing of mammary cells
4 Chapter 4: Detailed investigation of a milk fat percentage QTL underpinned by the MGST1 gene
4.2 General aim
4.6 Summary and conclusions
5 Chapter 5: DGAT1 K232A; A familiar milk fat mutation with a new mechanism
5.2 General aim
5.3 Specific aims
5.7 Summary and Conclusion
6. Chapter 6: Detailed investigation of the AGPAT6 milk fat percentage QTL
Chapter 7: Functional confirmation of PLAG1 as the causative gene underlying major pleiotropic effects on liveweight and milk characteristics
4. Chapter 8: General Discussion
8.2Major research outcomes
8.3Implications and future directions
List of References
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Functional and Genetic Characterisation of Major Effect Milk Composition Variants in Dairy Cattle