Generalisable Methods for Improving CRISPR Efficiency and Outcome Specificity using Machine Learning Algorithms

CRISPR (clustered regularly interspaced short palindromic repeats) based genome editing has become a popular tool for a range of disciplines, including microbiology, agricultural science, and health. Driving these applications is the ability of the "programmable" system to target a predefined location in the genome. A single guide RNA (sgRNA) defines the target through Watson-Crick base pairing, and a class 2 type II CRISPR associated protein 9 (Cas9) nuclease cleaves the target, resulting in a double-strand break (DSB). This activates DNA repair, and depending on the repair pathway initiated, can result in arbitrary insertions/deletions or a predefined variant. Despite the versatility and ease of design enabled by this RNA-guided nuclease, it lacks specificity, regarding off-target effects, and efficiency, regarding the rate of successful editing outcomes. The overarching hypothesis of my thesis is to solve the disadvantages of CRISPR systems by using machine learning to train generalisable models on existing and novel datasets. One pathway that demonstrates the need for prediction models is homology directed repair (HDR). HDR enables researchers to induce nearly any editing outcome, however, it is inefficient. And with an incomplete knowledge of its kinetics, no models existed for predicting its efficiency. I generated a novel dataset representing the efficiency of HDR. Using the Random Forests algorithm, I identified the sgRNA and the 3' region of the template to modulate HDR efficiency. This novel finding relates to the kinetics of template interaction during HDR repair. Even with efficient gene editing, a potential problem is unwanted side effects, such as embryonic lethality. This can be solved by using CRISPR to create conditional knockout alleles, to control when and where knockouts occur. To investigate the efficiency of this process, I used statistical analyses and the Random Forest algorithm to analyse a dataset generated by a consortium of 19 laboratories. I identified the inherent inefficiency of this method as defined by the efficiency of two simultaneous HDR events. Other experimental variables, like reagent concentrations or technician skill level, had no significant influence on efficiency. Because of the unrivalled versatility of this method, I created a statistical model for forecasting the efficiency of this technique from a low number of attempts, aiming to overcome its inherent inefficiency. While Cas9 is the most cited CRISPR system, alternative CRISPR systems can further expand the gene editing repertoire. To support the uptake of the more-recent Cas12a, I performed a comprehensive comparison between the two nucleases. I found support for Cas12a having a superior specificity. Despite this, editing outcome and efficiency prediction tools for Cas12a were scarce. Aiming to address this, I trained a Cas12a cleavage efficiency prediction model on representative data. This outperformed the current top model despite the dataset being 300x smaller, demonstrating the importance of clean data. Altogether, this thesis improves the knowledge of different CRISPR gene editing techniques. These findings can enable researchers to design efficient experiments as well as provide researchers guidance where certain techniques may be inherently inefficient. As well as resulting in CUNE (Computational Universal Nucleotide Editor) and Cas12aRF, it also identifies the generalisability of prediction models due to the high degree of influence on efficiency by the sgRNA and repair template design

Domain-specific introduction to machine learning terminology, pitfalls and opportunities in CRISPR-based gene editing

The use of machine learning (ML) has become prevalent in the genome engineering space, with applications ranging from predicting target site efficiency to forecasting the outcome of repair events. However, jargon and ML-specific accuracy measures have made it hard to assess the validity of individual approaches, potentially leading to misinterpretation of ML results. This review aims to close the gap by discussing ML approaches and pitfalls in the context of CRISPR gene-editing applications. Specifically, we address common considerations, such as algorithm choice, as well as problems, such as overestimating accuracy and data interoperability, by providing tangible examples from the genome-engineering domain. Equipping researchers with the knowledge to effectively use ML to better design gene-editing experiments and predict experimental outcomes will help advance the field more rapidly

Flip-chip integration of tilted VCSELs onto a silicon photonic integrated circuit

In this article we describe a cost-effective approach for hybrid laser integration, in which vertical cavity surface emitting lasers (VCSELs) are passively-aligned and flip-chip bonded to a Si photonic integrated circuit (PIC), with a tilt-angle optimized for optical-insertion into standard grating-couplers. A tilt-angle of 10 degrees is achieved by controlling the reflow of the solder ball deposition used for the electrical-contacting and mechanical-bonding of the VCSEL to the PIC. After flip-chip integration, the VCSEL-to-PIC insertion loss is -11.8 dB, indicating an excess coupling penalty of -5.9 dB, compared to Fibre-to-PIC coupling. Finite difference time domain simulations indicate that the penalty arises from the relatively poor match between the VCSEL mode and the grating-coupler. (C) 2016 Optical Society of Americ

The simulated environmental impact of incorporating white clover into pasture-based dairy production systems

peer-reviewedWhite clover (WC) offers an alternative source of nitrogen (N) for pasture-based systems. Substituting energy- and carbon-intensive synthetic N fertilizers with N derived from biological fixation by WC has been highlighted as a promising environmental mitigation strategy through the omission of emissions, pollutants, and energy usage during the production and application of synthetic fertilizer. Therefore, the objective was to investigate the effect of the inclusion of WC in perennial ryegrass (PRG) swards on the environmental impact of pasture-based dairy systems. Cradle-to-farm gate life cycle assessment of 3 pasture-based dairy systems were conducted: (1) a PRG–WC sward receiving 150 kg of N/ha per year (CL150), (2) a PRG–WC sward receiving 250 kg of N/ha per year (CL250), and (3) a PRG-only sward receiving 250 kg of N/ha per year (GR250). A dairy environmental model was updated with country-specific N excretion equations and recently developed N2O, NH3, and NO3− emission factors. The environmental impact categories assessed were global warming potential, nonrenewable energy, acidification potential, and eutrophication potential (marine and freshwater). Impact categories were expressed using 2 functional units: per hectare and per metric tonne of fat- and protein-corrected milk. The GR250 system had the lowest milk production and highest global warming potential, nonrenewable energy, and acidification potential per tonne of fat- and protein-corrected milk for all systems. The CL250 system produced the most milk and had the highest environmental impact across all categories when expressed on an area basis. It also had the highest marine eutrophication potential for both functional units. The impact category freshwater eutrophication potential did not differ across the 3 systems. The CL150 system had the lowest environmental impact across all categories and functional units. This life cycle assessment study demonstrates that the substitution of synthetic N fertilizer with atmospheric N fixed by WC has potential to reduce the environmental impact of intensive pasture-based dairy systems in temperate regions, not only through improvement in animal performance but also through the reduction in total emissions and pollutants contributing to the environmental indicators assessed

Beef production from feedstuffs conserved using new technologies to reduce negative environmental impacts

End of project reportMost (ca. 86%) Irish farms make some silage. Besides directly providing feed for livestock, the provision of grass silage within integrated grassland systems makes an important positive contribution to effective grazing management and improved forage utilisation by grazing animals, and to effective feed budgeting by farmers. It can also contribute to maintaining the content of desirable species in pastures, and to livestock not succumbing to parasites at sensitive times of the year. Furthermore, the optimal recycling of nutrients collected from housed livestock can often be best achieved by spreading the manures on the land used for producing the conserved feed. On most Irish farms, grass silage will remain the main conserved forage for feeding to livestock during winter for the foreseeable future. However, on some farms high yields of whole-crop (i.e. grain + straw) cereals such as wheat, barley and triticale, and of forage maize, will be an alternative option provided that losses during harvesting, storage and feedout are minimised and that input costs are restrained. These alternative forages have the potential to reliably support high levels of animal performance while avoiding the production of effluent. Their production and use however will need to advantageously integrate into ruminant production systems. A range of technologies can be employed for crop production and conservation, and for beef production, and the optimal options need to be identified. Beef cattle being finished indoors are offered concentrate feedstuffs at rates that range from modest inputs through to ad libitum access. Such concentrates frequently contain high levels of cereals such as barley or wheat. These cereals are generally between 14% to 18% moisture content and tend to be rolled shortly before being included in coarse rations or are more finely processed prior to pelleting. Farmers thinking of using ‘high-moisture grain’ techniques for preserving and processing cereal grains destined for feeding to beef cattle need to know how the yield, conservation efficiency and feeding value of such grains compares with grains conserved using more conventional techniques. European Union policy strongly encourages a sustainable and multifunctional agriculture. Therefore, in addition to providing European consumers with quality food produced within approved systems, agriculture must also contribute positively to the conservation of natural resources and the upkeep of the rural landscape. Plastics are widely used in agriculture and their post-use fate on farms must not harm the environment - they must be managed to support the enduring sustainability of farming systems. There is an absence of information on the efficacy of some new options for covering and sealing silage with plastic sheeting and tyres, and an absence of an inventory of the use, re-use and post-use fate of plastic film on farms. Irish cattle farmers operate a large number of beef production systems, half of which use dairy bred calves. In the current, continuously changing production and market conditions, new beef systems must be considered. A computer package is required that will allow the rapid, repeatable simulation and assessment of alternate beef production systems using appropriate, standardised procedures. There is thus a need to construct, evaluate and utilise computer models of components of beef production systems and to develop mathematical relationships to link system components into a network that would support their integration into an optimal system model. This will provide a framework to integrate physical and financial on-farm conditions with models for estimating feed supply and animal growth patterns. Cash flow and profit/loss results will be developed. This will help identify optimal systems, indicate the cause of failure of imperfect systems and identify areas where applied research data are currently lacking, or more basic research is required

Beef production from feedstuffs conserved using new technologies to reduce negative environmental impacts

End of Project ReportThe three separate components with parallel objectives to this programme were to: 1. Develop technologies for conserving and optimally feeding alternative/complimentary feedstuffs to grass silage. 2. Quantify the use and re-use of plastic sheeting or film used to seal ensiled feedstuffs or mulch maize, and evaluate some new options. 3. Develop computer programs that will facilitate investigating prototype models of forage-based beef production systems

Reproducibility of CRISPR-Cas9 methods for generation of conditional mouse alleles: A multi-center evaluation

Background CRISPR-Cas9 gene-editing technology has facilitated the generation of knockout mice, providing an alternative to cumbersome and time-consuming traditional embryonic stem cell-based methods. An earlier study reported up to 16% efficiency in generating conditional knockout (cKO or floxed) alleles by microinjection of 2 single guide RNAs (sgRNA) and 2 single-stranded oligonucleotides as donors (referred herein as “two-donor floxing” method). Results We re-evaluate the two-donor method from a consortium of 20 laboratories across the world. The dataset constitutes 56 genetic loci, 17,887 zygotes, and 1718 live-born mice, of which only 15 (0.87%) mice contain cKO alleles. We subject the dataset to statistical analyses and a machine learning algorithm, which reveals that none of the factors analyzed was predictive for the success of this method. We test some of the newer methods that use one-donor DNA on 18 loci for which the two-donor approach failed to produce cKO alleles. We find that the one-donor methods are 10- to 20-fold more efficient than the two-donor approach. Conclusion We propose that the two-donor method lacks efficiency because it relies on two simultaneous recombination events in cis, an outcome that is dwarfed by pervasive accompanying undesired editing events. The methods that use one-donor DNA are fairly efficient as they rely on only one recombination event, and the probability of correct insertion of the donor cassette without unanticipated mutational events is much higher. Therefore, one-donor methods offer higher efficiencies for the routine generation of cKO animal models.This work was supported by the National Collaborative Research Infrastructure (NCRIS) via the Australian Phenomics Network (APN) (to Gaetan Burgio and Paul Thomas), by an Institutional Development Award (PI: Shelley Smith) P20GM103471 (to CBG, RMQ, DWH, JDE, and RR), by NIGMS 1P30GM110768-01 and P30CA036727 (as part of support to University of Nebraska Mouse Genome Engineering and DNA Sequencing Cores), the British Heart Foundation FS12-57, FS12/57/29717, and CH/13/2/30154 and the program grant RG/15/12/31616 (to Kathryn Hentges and Bernard Keavney), the Wellcome Trust grants 107849/Z/ 15/Z, 097820/Z11/B, and 105610/Z/14/Z, the Medical Research Council MR/ N029992/1 (to DB and CBL), the National BioResource Project of Ministry of Education, Culture, Sports, Science and Technology/Japan Agency for Medical Research and Development (MEXT/AMED), Japan, the Canadian Institutes of Health Research MOP#142452 (MCB and LJM). LJM is a member of the Research Centre of the McGill University Health Centre which is supported in part by FQRS. Dr. William Thompson was supported by the Indiana Clinical and Translational Sciences Institute, funded in part by grant #UL1 TR001108 from the National Institute of Health (NIH), National Center for Advancing Translational Sciences, Clinical and Translational Sciences Award. KC Kent Lloyd is supported by the NIH (UM1OD023221), and work contributed by staff from the UC Davis Mouse Biology Program (MBP) is supported by a grant from the American College of Laboratory Animal Medicine. The work contributed from Xiande Liu, Chad Smith, Eric Jonasch, Xuesong Zhang, and Jan ParkerThornburg is supported by the NIH under the award number P30CA16672 (XL, CS, EJ, XZ, JPT) and R50CA211121 (JPT). Joseph Miano is supported by the NIH under the award number HL138987. R Sedlacek was supported by LM2015040 (Czech Centre for Phenogenomics), CZ.1.05/1.1.00/02.0109 (BIOCEV), and CZ.1.05/2.1.00/19.0395 by the Ministry of Education, Youth and Sports (MEYS) and by Academy of Sciences of the Czech Republic (RVO 68378050). David Ray was supported by a Wellcome Trust Investigator (107849/Z/15/Z) and the Medical Research Council (MR/P011853/1 and MR/P023576/) grants. Andrew Loudon was supported by a Wellcome Trust Investigator (107849/Z/15/Z), Biotechnology and Biological Sciences Research Council (BB/N015584/1), Medical Research Council (MR/P023576/1). The work contributed from Gloria Lopez-Castejon is supported by the Wellcome Trust (104192/Z/14/Z) and the Royal Society. Pilar Alcaide was supported by the NIH (HL 123658). The work contributed from Surinder K. Batra is supported by the NIH under the award number P01 CA217798

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

The Evolutionary Map of the Universe Pilot Survey

We present the data and initial results from the first pilot survey of the Evolutionary Map of the Universe (EMU), observed at 944 MHz with the Australian Square Kilometre Array Pathfinder (ASKAP) telescope. The survey covers 270 deg2 of an area covered by the Dark Energy Survey, reaching a depth of 25–30 μJy beam−1 rms at a spatial resolution of ∼11–18 arcsec, resulting in a catalogue of ∼220 000 sources, of which ∼180 000 are single-component sources. Here we present the catalogue of single-component sources, together with (where available) optical and infrared cross-identifications, classifications, and redshifts. This survey explores a new region of parameter space compared to previous surveys. Specifically, the EMU Pilot Survey has a high density of sources, and also a high sensitivity to low surface brightness emission. These properties result in the detection of types of sources that were rarely seen in or absent from previous surveys. We present some of these new results here