Homing based gene drives, engineered using CRISPR/Cas9, have been proposed to spread desirable genes throughout populations. However, invasion of such drives can be hindered by the accumulation of resistant alleles. To limit this obstacle, we engineer a confinable population modification Home-and-Rescue (HomeR) drive in Drosophila targeting an essential gene. In our experiments, resistant alleles that disrupt the target gene function were recessive lethal, and therefore disadvantaged. We demonstrate that HomeR can achieve an increase in frequency in population cage experiments, but that fitness costs due to the Cas9 insertion limit drive efficacy. Finally, we conduct mathematical modeling comparing HomeR to contemporary gene drive architectures for population modification over wide ranges of fitness costs, transmission rates, and release regimens. HomeR could potentially be adapted to other species, as a means for safe, confinable, modification of wild populations.
All data are represented fully within the tables and figures. The gRNA#1PolG2, gRNA#2PolG2, HomeRPolG2, HomeR(B)PolG2, exuL-Cas9, Rcd1r-Cas9, and βTub-Cas9 plasmids and corresponding fly lines are deposited at Addgene.org (159671-159677) and the Bloomington Drosophila Stock Center (91375-91378), respectively.
- Omar S Akbari
- Omar S Akbari
- Omar S Akbari
- Omar S Akbari
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Claude Desplan, New York University, United States
© 2021, Kandul 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.
Haemoglobinopathies are the commonest monogenic diseases worldwide and are caused by variants in the globin gene clusters. With over 2400 variants detected to date, their interpretation using the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) guidelines is challenging and computational evidence can provide valuable input about their functional annotation. While many in silico predictors have already been developed, their performance varies for different genes and diseases. In this study, we evaluate 31 in silico predictors using a dataset of 1627 variants in HBA1, HBA2, and HBB. By varying the decision threshold for each tool, we analyse their performance (a) as binary classifiers of pathogenicity and (b) by using different non-overlapping pathogenic and benign thresholds for their optimal use in the ACMG/AMP framework. Our results show that CADD, Eigen-PC, and REVEL are the overall top performers, with the former reaching moderate strength level for pathogenic prediction. Eigen-PC and REVEL achieve the highest accuracies for missense variants, while CADD is also a reliable predictor of non-missense variants. Moreover, SpliceAI is the top performing splicing predictor, reaching strong level of evidence, while GERP++ and phyloP are the most accurate conservation tools. This study provides evidence about the optimal use of computational tools in globin gene clusters under the ACMG/AMP framework.
We aimed to elucidate the evolutionary trajectories of gallbladder adenocarcinoma (GBAC) using multi-regional and longitudinal tumor samples. Using whole-exome sequencing data, we constructed phylogenetic trees in each patient and analyzed mutational signatures. A total of 11 patients including 2 rapid autopsy cases were enrolled. The most frequently altered gene in primary tumors was ERBB2 and TP53 (54.5%), followed by FBXW7 (27.3%). Most mutations in frequently altered genes in primary tumors were detectable in concurrent precancerous lesions (biliary intraepithelial neoplasia, BilIN), but a substantial proportion was subclonal. Subclonal diversity was common in BilIN (n=4). However, among subclones in BilIN, a certain subclone commonly shrank in concurrent primary tumors. In addition, selected subclones underwent linear and branching evolution, maintaining subclonal diversity. Combined analysis with metastatic tumors (n=11) identified branching evolution in 9 patients (81.8%). Of these, 8 patients (88.9%) had a total of 11 subclones expanded at least 7-fold during metastasis. These subclones harbored putative metastasis-driving mutations in cancer-related genes such as SMAD4, ROBO1, and DICER1. In mutational signature analysis, 6 mutational signatures were identified: 1, 3, 7, 13, 22, and 24 (cosine similarity >0.9). Signatures 1 (age) and 13 (APOBEC) decreased during metastasis while signatures 22 (aristolochic acid) and 24 (aflatoxin) were relatively highlighted. Subclonal diversity arose early in precancerous lesions and clonal selection was a common event during malignant transformation in GBAC. However, selected cancer clones continued to evolve and thus maintained subclonal diversity in metastatic tumors.