Delivering genes across the blood-brain barrier: LY6A, a novel cellular receptor for AAV-PHP.B capsids

The engineered AAV-PHP.B family of adeno-associated virus efficiently delivers genes throughout the mouse central nervous system. To guide their application across disease models, and to inspire the development of translational gene therapy vectors useful for targeting neurological diseases in humans, we sought to elucidate the host factors responsible for the CNS tropism of AAV-PHP.B vectors. Leveraging CNS tropism differences across mouse strains, we conducted a genome-wide association study, and rapidly identified and verified LY6A as an essential receptor for the AAV-PHP.B vectors in brain endothelial cells. Importantly, this newly discovered mode of AAV binding and transduction is independent of other known AAV receptors and can be imported into different cell types to confer enhanced transduction by the AAV-PHP.B vectors.

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Integrated computational and experimental identification of p53, KRAS and VHL mutant selection associated with CRISPR-Cas9 editing

10.1101/407767 ◽

2018 ◽

Cited By ~ 2

Author(s):

Sanju Sinha ◽

Karina Barbosa Guerra ◽

Kuoyuan Cheng ◽

Mark DM Leiserson ◽

David M Wilson ◽

...

Keyword(s):

Gene Editing ◽

Mutant Cell ◽

Cell Types ◽

Driver Mutations ◽

Mutant Selection ◽

Cancer Driver ◽

Genome Wide ◽

A Genome ◽

Induced Changes ◽

Different Cell Types

AbstractRecent studies have reported that CRISPR-Cas9 gene editing induces a p53-dependent DNA damage response in primary cells, which may select for cells with oncogenic p53 mutations11,12. It is unclear whether these CRISPR-induced changes are applicable to different cell types, and whether CRISPR gene editing may select for other oncogenic mutations. Addressing these questions, we analyzed genome-wide CRISPR and RNAi screens to systematically chart the mutation selection potential of CRISPR knockouts across the whole exome. Our analysis suggests that CRISPR gene editing can select for mutants of KRAS and VHL, at a level comparable to that reported for p53. These predictions were further validated in a genome-wide manner by analyzing independent CRISPR screens and patients’ tumor data. Finally, we performed a new set of pooled and arrayed CRISPR screens to evaluate the competition between CRISPR-edited isogenic p53 WT and mutant cell lines, which further validated our predictions. In summary, our study systematically charts and points to the potential selection of specific cancer driver mutations during CRISPR-Cas9 gene editing.

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Review: Population Structure in Genetic Studies: Confounding Factors and Mixed Models

10.1101/092106 ◽

2016 ◽

Author(s):

Lana S. Martin ◽

Eleazar Eskin

Keyword(s):

Population Structure ◽

Mixed Models ◽

Genome Wide Association Study ◽

Association Studies ◽

Laboratory Mouse ◽

Mouse Strains ◽

Genetic Studies ◽

The Past ◽

Genome Wide ◽

A Genome

AbstractA genome-wide association study (GWAS) seeks to identify genetic variants that contribute to the development and progression of a specific disease. Over the past 10 years, new approaches using mixed models have emerged to mitigate the deleterious effects of population structure and relatedness in association studies. However, developing GWAS techniques to effectively test for association while correcting for population structure is a computational and statistical challenge. Using laboratory mouse strains as an example, our review characterizes the problem of population structure in association studies and describes how it can cause false positive associations. We then motivate mixed models in the context of unmodeled factors.

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DeeReCT-TSS: A novel meta-learning-based method annotates TSS in multiple cell types based on DNA sequences and RNA-seq data

10.1101/2021.07.14.452328 ◽

2021 ◽

Author(s):

Juexiao Zhou ◽

Bin Zhang ◽

Haoyang Li ◽

Longxi Zhou ◽

Zhongxiao Li ◽

...

Keyword(s):

Dna Sequences ◽

Cell Types ◽

Rna Seq ◽

Sources Of Information ◽

Genome Wide ◽

A Genome ◽

Meta Learning ◽

Multiple Cell ◽

Different Cell Types ◽

Genome Scale

The accurate annotation of TSSs and their usage is critical for the mechanistic understanding of gene regulation under different biological contexts. To fulfill this, specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner. Various computational tools have also been developed for in silico prediction of TSSs solely based on genomic sequences. Most of these tools have drastic false positive predictions when applied on the genome-scale. Here, we present DeeReCT-TSS, a deep-learning-based method that is capable of TSSs identification across the whole genome based on DNA sequences and conventional RNA-seq data. We show that by effectively incorporating these two sources of information, DeeReCT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell types. Furthermore, we develop a meta-learning-based extension for simultaneous transcription start site (TSS) annotation on 10 cell types, which enables the identification of cell-type-specific TSS. Finally, we demonstrate the high precision of DeeReCT-TSS on two independent datasets from the ENCODE project by correlating our predicted TSSs with experimentally defined TSS chromatin states.

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Identification of 13 independent genetic loci associated with cognitive resilience in healthy aging in 330,097 individuals in the UK Biobank

10.1101/2021.01.22.427640 ◽

2021 ◽

Author(s):

Joan Fitzgerald ◽

Laura Fahey ◽

Laurena Holleran ◽

Pilib Ó Broin ◽

Gary Donohoe ◽

...

Keyword(s):

Healthy Aging ◽

Genome Wide Association Study ◽

Cell Types ◽

Brain Regions ◽

Specific Cell ◽

Uk Biobank ◽

Negative Effects ◽

Genome Wide ◽

A Genome ◽

The Uk

AbstractCognitive resilience is the ability to withstand the negative effects of stress on cognitive functioning and is important for maintaining quality of life while aging. Here we employed a proxy phenotype approach to create a longitudinal cognitive resilience phenotype using past education years and current processing speed, reflecting an average time span of 40 years, in 330,097 individuals from the UK Biobank. A genome-wide association study identified 13 independent genome-wide significant loci that implicate 33 genes. A portion of resilience’s genetic signal is distinct from the genetics of intelligence. Functional analyses showed enrichment in several brain regions and involvement of specific cell types, including GABAergic neurons (P=6.59×10−8) and glutamatergic neurons (P=6.98×10−6) in the cortex. Gene-set analyses implicated the biological process “neuron differentiation” (P=9.7×10−7) and the cellular component “synaptic part” (P=2.14×10−6). Mendelian randomization analysis showed a causative effect of white matter volume on cognitive resilience. These results enhance neurobiological understanding of resilience.

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Genetic Determinants of Blood Cell Traits Influence Susceptibility to Childhood Acute Lymphoblastic Leukemia

10.1101/2021.04.17.21255679 ◽

2021 ◽

Author(s):

Linda Kachuri ◽

Soyoung Jeon ◽

Andrew T. DeWan ◽

Catherine Metayer ◽

Xiaomei Ma ◽

...

Keyword(s):

Acute Lymphoblastic Leukemia ◽

Blood Cell ◽

Genome Wide Association Study ◽

Lymphoblastic Leukemia ◽

Cell Types ◽

Genetic Determinants ◽

Childhood All ◽

Genome Wide ◽

A Genome ◽

The Uk

ABSTRACTAcute lymphoblastic leukemia (ALL) is the most common childhood cancer. Despite overlap between genetic risk loci for ALL and hematologic traits, the etiological relevance of dysregulated blood cell homeostasis remains unclear. We investigated this question in a genome-wide association study (GWAS) of ALL (2666 cases, 60,272 controls) and multi-trait GWAS of 9 blood cell indices in the UK Biobank. We identified 3000 blood cell trait-associated (P<5.0×10−8) variants, explaining 4.0% to 23.9% of trait variation, and including 115 loci associated with blood cell ratios (LMR: lymphocyte/monocyte, NLR: neutrophil/lymphocyte, PLR: platelet/lymphocyte). ALL susceptibility was genetically correlated with lymphocyte counts (rg=0.088, p=4.0×10−4) and PLR (rg= −0.072, p=0.0017). In Mendelian randomization analyses, genetically predicted increase in lymphocyte counts was associated with increased ALL risk (Odds ratio (OR)=1.16, p=0.031) and strengthened after accounting for other cell types (OR=1.48, p=8.8×10−4). We observed positive associations with increasing LMR (OR=1.22, p=0.0017) and inverse effects for NLR (OR=0.67, p=3.1×10−4) and PLR (OR=0.80, p=0.002). Our study shows that a genetically induced shift towards higher lymphocyte counts, overall and in relation to monocytes, neutrophils, and platelets, confers an increased susceptibility to childhood ALL.

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