scholarly journals Computational and experimental performance of CRISPR homing gene drive strategies with multiplexed gRNAs

2019 ◽  
Author(s):  
Samuel E. Champer ◽  
Suh Yeon Oh ◽  
Chen Liu ◽  
Zhaoxin Wen ◽  
Andrew G. Clark ◽  
...  
Keyword(s):  
Large Scale ◽  
Optimal Number ◽  
Activity Level ◽  
Gene Drive ◽  
Factors Affecting ◽  
Homology Directed Repair ◽  
Scale Population ◽  
And Performance ◽  
Using Data ◽  
Gene Drives

ABSTRACTCRISPR homing gene drives potentially have the capacity for large-scale population modification or suppression. However, resistance alleles formed by the drives can prevent them from successfully spreading. Such alleles have been found to form at high rates in most studies, including those in both insects and mammals. One possible solution to this issue is the use of multiple guide RNAs (gRNAs), thus allowing cleavage by the drive even if resistance sequences are present at some of the gRNA target sequences. Here, we develop a high-fidelity model incorporating several factors affecting the performance of drives with multiple gRNAs, including timing of cleavage, reduction in homology-directed repair efficiency due to imperfect homology around the cleavage site, Cas9 activity saturation, variance in the activity level of individual gRNAs, and formation of resistance alleles due to incomplete homology-directed repair. We parameterize the model using data from homing drive experiments designed to investigate these factors and then use it to analyze several types of homing gene drives. We find that each type of drive has an optimal number of gRNAs, usually between two and eight, dependent on drive type and performance parameters. Our model indicates that utilization of multiple gRNAs is insufficient for construction of successful gene drives, but that it provides a critical boost to drive efficiency when combined with other strategies for population modification or suppression.

scholarly journals Computational and experimental performance of CRISPR homing gene drive strategies with multiplexed gRNAs

2020 ◽  
Vol 6 (10) ◽  
pp. eaaz0525 ◽  
Author(s):  
Samuel E. Champer ◽  
Suh Yeon Oh ◽  
Chen Liu ◽  
Zhaoxin Wen ◽  
Andrew G. Clark ◽  
...  
Keyword(s):  
Genetic Manipulation ◽  
Rapid Evolution ◽  
Experimental Studies ◽  
Optimal Number ◽  
Activity Level ◽  
Gene Drive ◽  
Factors Affecting ◽  
Resistance Evolution ◽  
Homology Directed Repair ◽  
And Performance

The rapid evolution of resistance alleles poses a major obstacle for genetic manipulation of populations with CRISPR homing gene drives. One proposed solution is using multiple guide RNAs (gRNAs), allowing a drive to function even if some resistant target sites are present. Here, we develop a model of homing mechanisms parameterized by experimental studies. Our model incorporates several factors affecting drives with multiple gRNAs, including timing of cleavage, reduction in homology-directed repair efficiency due to imperfect homology, Cas9 activity saturation, gRNA activity level variance, and incomplete homology-directed repair. We find that homing drives have an optimal number of gRNAs, usually between two and eight, depending on the specific drive type and performance parameters. These results contradict the notion that resistance rates can be reduced to arbitrarily low levels by gRNA multiplexing and highlight the need for combined approaches to counter resistance evolution in CRISPR homing drives.

scholarly journals Analysis of Factors Influencing Effective Utilization Coefficient of Irrigation Water in the Manas River Basin

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 189
Author(s):  
Lili Yang ◽  
Tong Heng ◽  
Guang Yang ◽  
Xinchen Gu ◽  
Jiaxin Wang ◽  
...  
Keyword(s):  
Irrigation Water ◽  
Large Scale ◽  
Grey Model ◽  
Analytic Hierarchy ◽  
Effective Utilization ◽  
Factors Affecting ◽  
Factors Influencing ◽  
Utilization Coefficient ◽  
Using Data ◽  
Effective Use

The factors influencing the effective utilization coefficient of irrigation water are not understood well. It is usually considered that this coefficient is lower in areas with large-scale irrigation. With this background, we analyzed the effective utilization coefficient of irrigation water using the analytic hierarchy process using data from 2014 to 2019 in Shihezi City, Xinjiang. The weights of the influencing factors on the effective utilization coefficient of irrigation water in different irrigation areas were analyzed. Predictions of the coefficient’s values for different years were made by understanding the trends based on the grey model. The results show that the scale of the irrigation area is not the only factor determining the effective utilization coefficient of irrigation water. Irrigation technology, organizational integrity, crop types, water price management, local economic level, and channel seepage prevention are the most critical factors affecting the effective use of irrigation water. The grey model prediction results show that the effective utilization coefficient of farmland irrigation water will continuously increase and reach 0.7204 in 2029. This research can serve as a reference for government authorities to make scientific decisions on water-saving projects in irrigation districts in terms of management, operation, and investment.

scholarly journals Key factors affecting people’s unwillingness to be confined during the COVID-19 pandemic in Spain: a large-scale population study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marina Martinez-Garcia ◽  
Alejandro Rabasa ◽  
Xavier Barber ◽  
Kristina Polotskaya ◽  
Kristof Roomp ◽  
...  
Keyword(s):  
Large Scale ◽  
Psychological Impact ◽  
Important Variable ◽  
Policy Makers ◽  
Factors Affecting ◽  
Time Period ◽  
Economic Support ◽  
Gender And Age ◽  
Scale Population ◽  
The Impact

AbstractPopulation confinements have been one of the most widely adopted non-pharmaceutical interventions (NPIs) implemented by governments across the globe to help contain the spread of the SARS-CoV-2 virus. While confinement measures have been proven to be effective to reduce the number of infections, they entail significant economic and social costs. Thus, different policy makers and social groups have exhibited varying levels of acceptance of this type of measures. In this context, understanding the factors that determine the willingness of individuals to be confined during a pandemic is of paramount importance, particularly, to policy and decision-makers. In this paper, we study the factors that influence the unwillingness to be confined during the COVID-19 pandemic by the means of a large-scale, online population survey deployed in Spain. We perform two types of analyses (logistic regression and automatic pattern discovery) and consider socio-demographic, economic and psychological factors, together with the 14-day cumulative incidence per 100,000 inhabitants. Our analysis of 109,515 answers to the survey covers data spanning over a 5-month time period to shed light on the impact of the passage of time. We find evidence of pandemic fatigue as the percentage of those who report an unwillingness to be in confinement increases over time; we identify significant gender differences, with women being generally less likely than men to be able to sustain long-term confinement of at least 6 months; we uncover that the psychological impact was the most important factor to determine the willingness to be in confinement at the beginning of the pandemic, to be replaced by the economic impact as the most important variable towards the end of our period of study. Our results highlight the need to design gender and age specific public policies, to implement psychological and economic support programs and to address the evident pandemic fatigue as the success of potential future confinements will depend on the population’s willingness to comply with them.

Data Quality

2011 ◽  
pp. 265-286
Author(s):  
Jeretta Horn Nord ◽  
G. Daryl Nord ◽  
Hongjiang Xu ◽  
Elizabeth S. Myrin
Keyword(s):  
Data Quality ◽  
Large Scale ◽  
Critical Success Factors ◽  
Success Factors ◽  
Actual Performance ◽  
Factors Affecting ◽  
Accounting Information Systems ◽  
Critical Success ◽  
Large Scale Survey ◽  
And Performance

This chapter presents results from a large-scale survey of Australian CPA members regarding data quality. The research investigates and reports major stakeholders’ opinions on the importance of critical success factors affecting data quality and the actual performance on each of those factors. The results reveal whether dissimilarly sized organizations differ in the way they measure the importance and performance of critical success factors for data quality in accounting information systems.

scholarly journals Analysis of off-target effects in CRISPR-based gene drives in the human malaria mosquito

2021 ◽  
Vol 118 (22) ◽  
pp. e2004838117
Author(s):  
William T. Garrood ◽  
Nace Kranjc ◽  
Karl Petri ◽  
Daniel Y. Kim ◽  
Jimmy A. Guo ◽  
...  
Keyword(s):  
Mendelian Inheritance ◽  
Gene Drive ◽  
Guide Rna ◽  
Human Malaria ◽  
Homology Directed Repair ◽  
Cas9 Nuclease ◽  
Set Up ◽  
Gene Drives ◽  
Target Effects ◽  
Important Milestone

CRISPR-Cas9 nuclease-based gene drives have been developed toward the aim of control of the human malaria vector Anopheles gambiae. Gene drives are based on an active source of Cas9 nuclease in the germline that promotes super-Mendelian inheritance of the transgene by homology-directed repair (“homing”). Understanding whether CRISPR-induced off-target mutations are generated in Anopheles mosquitoes is an important aspect of risk assessment before any potential field release of this technology. We compared the frequencies and the propensity of off-target events to occur in four different gene-drive strains, including a deliberately promiscuous set-up, using a nongermline restricted promoter for SpCas9 and a guide RNA with many closely related sites (two or more mismatches) across the mosquito genome. Under this scenario we observed off-target mutations at frequencies no greater than 1.42%. We witnessed no evidence that CRISPR-induced off-target mutations were able to accumulate (or drive) in a mosquito population, despite multiple generations’ exposure to the CRISPR-Cas9 nuclease construct. Furthermore, judicious design of the guide RNA used for homing of the CRISPR construct, combined with tight temporal constriction of Cas9 expression to the germline, rendered off-target mutations undetectable. The findings of this study represent an important milestone for the understanding and managing of CRISPR-Cas9 specificity in mosquitoes, and demonstrates that CRISPR off-target editing in the context of a mosquito gene drive can be reduced to minimal levels.

scholarly journals Burden of Lesser-Known Unintentional Non-Fatal Injuries in Rural Bangladesh: Findings from a Large-Scale Population-Based Study

2019 ◽  
Vol 16 (18) ◽  
pp. 3366
Author(s):  
Lamisa Ashraf ◽  
Priyanka Agrawal ◽  
Aminur Rahman ◽  
Shumona Sharmin Salam ◽  
Qingfeng Li
Keyword(s):  
Large Scale ◽  
Population Based ◽  
Morbidity Rate ◽  
Unintentional Injuries ◽  
Middle Income ◽  
Home Setting ◽  
Rural Bangladesh ◽  
Scale Population ◽  
Using Data ◽  
Socio Demographic Factors

Around 90% of all fatal and non-fatal unintentional injuries occur in low- and middle-income countries (LMICs). The magnitude of unintentional injuries is unclear due to limited research and data. This paper describes the burden of lesser-known injuries (LKIs—cut injuries, unintentional poisoning, machine injuries, electrocution, injury by blunt objects, and suffocation) in rural Bangladesh, using data from the Saving of Lives from Drowning (SoLiD) project in Bangladesh. Descriptive statistics were used to report counts and rates of injuries by socio-demographic factors, injury characteristics, and circumstantial details. The annual morbidity rate of LKIs was 6878 injuries per 100,000 persons, involving 3.4% (40,520) of the population. Cut injury (44,131.2/100,000 per year) and injury by blunt objects (19768.6/100,000 per year) attributed in large numbers to the overall burden of LKIs. Males (66.1%) suffered more injuries than females. More than half (52.9%) occurred among people aged 25 to 64 years. Those involved in agriculture suffered the most injuries, mainly cut injuries (9234.1/100,000 per year) and machine-related injuries (582.9/100,000 per year). Most injuries occurred in the home setting. Increased awareness about packaging, storage, and the proper handling of appliances can help lower the frequency of LKIs. Safe architecture and awareness about home injuries is required to reduce injuries occurring in the home environment.

scholarly journals A Hybrid GA–PSO–CNN Model for Ultra-Short-Term Wind Power Forecasting

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6500
Author(s):  
Jie Liu ◽  
Quan Shi ◽  
Ruilian Han ◽  
Juan Yang
Keyword(s):  
Wind Power ◽  
Large Scale ◽  
Wind Farm ◽  
Pso Algorithm ◽  
Stable Operation ◽  
Feature Maps ◽  
Wind Power Forecasting ◽  
Factors Affecting ◽  
Using Data ◽  
Power Forecasting

Accurate and timely wind power forecasting is essential for achieving large-scale wind power grid integration and ensuring the safe and stable operation of the power system. For overcoming the inaccuracy of wind power forecasting caused by randomness and volatility, this study proposes a hybrid convolutional neural network (CNN) model (GA–PSO–CNN) integrating genetic algorithm (GA) and a particle swarm optimization (PSO). The model can establish feature maps between factors affecting wind power such as wind speed, wind direction, and temperature. Moreover, a mix-encoding GA–PSO algorithm is introduced to optimize the network hyperparameters and weights collaboratively, which solves the problem of subjective determination of the optimal network in the CNN and effectively prevents local optimization in the training process. The prediction effectiveness of the proposed model is verified using data from a wind farm in Ningxia, China. The results show that the MAE, MSE, and MAPE of the proposed GA–PSO–CNN model decreased by 1.13–9.55%, 0.46–7.98%, and 3.28–19.29%, respectively, in different seasons, compared with Single–CNN, PSO–CNN, ISSO–CNN, and CHACNN models. The convolution kernel size and number in each convolution layer were reduced by 5–18.4% in the GA–PSO–CNN model.

scholarly journals Multiple loci of small effect confer wide variability in efficiency and resistance rate of CRISPR gene drive

2018 ◽  
Author(s):  
Jackson Champer ◽  
Zhaoxin Wen ◽  
Anisha Luthra ◽  
Riona Reeves ◽  
Joan Chung ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Early Embryo ◽  
Resistance Rate ◽  
Pathogen Transmission ◽  
Gene Drive ◽  
Natural Genetic Variation ◽  
Homology Directed Repair ◽  
Conversion Rates ◽  
A Genome ◽  
Gene Drives

ABSTRACTGene drives could allow for control of vector-borne diseases by directly suppressing vector populations or spreading genetic payloads designed to reduce pathogen transmission. CRISPR homing gene drives work by cleaving wild-type alleles, which are then converted to drive alleles by homology-directed repair, increasing the frequency of the drive in a population. However, resistance alleles can form when end-joining repair takes place in lieu of homology-directed repair. Such alleles cannot be converted to drive alleles, which would halt the spread of a drive through a population. To investigate the effects of natural genetic variation on resistance formation, we developed a CRISPR homing gene drive in Drosophila melanogaster and crossed it into the genetically diverse Drosophila Genetic Reference Panel (DGRP) lines, measuring several performance parameters. Most strikingly, resistance allele formation post-fertilization in the early embryo ranged from 7% to 79% among lines and averaged 42±18%. We performed a Genome-Wide Association Study (GWAS) using our results in the DGRP lines and found that the resistance and conversion rates were polygenic, with several genetic polymorphisms showing relatively weak association. RNAi knockdown of several of these genes confirmed their effect, but their small effect sizes implies that their manipulation will yield only modest improvements to the efficacy of gene drives.

scholarly journals A homing suppression gene drive with multiplexed gRNAs maintains high drive conversion efficiency and avoids functional resistance alleles

2021 ◽  
Author(s):  
Emily Yang ◽  
Matthew Metzloff ◽  
Anna M. Langmüller ◽  
Andrew G. Clark ◽  
Philipp W Messer ◽  
...  
Keyword(s):  
Conversion Efficiency ◽  
Target Gene ◽  
Gene Drive ◽  
Wild Type ◽  
Homology Directed Repair ◽  
High Drive ◽  
Target Sites ◽  
Cage Population ◽  
Gene Drives ◽  
Population Suppression

Gene drives are engineered alleles that can bias inheritance in their favor, allowing them to spread throughout a population. They could potentially be used to modify or suppress pest populations, such as mosquitoes that spread diseases. CRISPR/Cas9 homing drives, which copy themselves by homology-directed repair in drive/wild-type heterozygotes, are a powerful form of gene drive, but they are vulnerable to resistance alleles that preserve the function of their target gene. Such resistance alleles can prevent successful population suppression. Here, we constructed a homing suppression drive in Drosophila melanogaster that utilized multiplexed gRNAs to inhibit the formation of functional resistance alleles in its female fertility target gene. The gRNA target sites were placed close together, preventing reduction in drive conversion efficiency. The construct reached a moderate equilibrium frequency in cage populations without apparent formation of resistance alleles. However, a moderate fitness cost prevented suppression of the cage population. Nevertheless, our results experimentally demonstrate the viability of the multiplexed gRNAs strategy in homing type suppression gene drives.

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