Recovering genotypes and phenotypes using allele-specific genes.
Ontology highlight
ABSTRACT:
SUBMITTER: Gursoy G
PROVIDER: S-EPMC8425091 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Allele-specific expression (ASE) assays can be used to identify cis, trans, and cis-by-trans regulatory variation. Understanding the source of expression variation has important implications for disease susceptibility, phenotypic diversity, and adaptation. While ASE is commonly measured via relative fluorescence at a SNP, next generation sequencing provides an opportunity to measure ASE in an accurate and high-throughput manner using read counts.We introduce a Solexa-based method to perform large numbers of ASE assays using only a single lane of a Solexa flowcell. In brief, transcripts of interest, which contain a known SNP, are PCR enriched and barcoded to enable multiplexing. Then high-throughput sequencing is used to estimate allele-specific expression using sequencing counts. To validate this method, we measured the allelic bias in a dilution series and found high correlations between measured and expected values (r>0.9, p < 0.001). We applied this method to a set of 5 genes in a Drosophila simulans parental mix, F1 and introgression and found that for these genes the majority of expression divergence can be explained by cis-regulatory variation.We present a new method with the capacity to measure ASE for large numbers of assays using as little as one lane of a Solexa flowcell. This will be a valuable technique for molecular and population genetic studies, as well as for verification of genome-wide data sets.
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Project description:The bacterial CRISPR/Cas system has proven to be an efficient gene-targeting tool in various organisms. Here we employ CRISPR/Cas for accurate and efficient genome editing in rats. The synthetic chimeric guide RNAs (gRNAs) discriminate a single-nucleotide polymorphism (SNP) difference in rat embryonic fibroblasts, allowing allele-specific genome editing of the dominant phenotype in (F344 × DA)F1 hybrid embryos. Interestingly, the targeted allele, initially assessed by the allele-specific gRNA, is repaired by an interallelic gene conversion between homologous chromosomes. Using single-stranded oligodeoxynucleotides, we recover three recessive phenotypes: the albino phenotype by SNP exchange; the non-agouti phenotype by integration of a 19-bp DNA fragment; and the hooded phenotype by eliminating a 7,098-bp insertional DNA fragment, evolutionary-derived from an endogenous retrovirus. Successful in vivo application of the CRISPR/Cas system confirms its importance as a genetic engineering tool for creating animal models of human diseases and its potential use in gene therapy.
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Project description:Sequencing reads overlapping polymorphic sites in diploid mammalian genomes may be assigned to one allele or the other. This holds the potential to detect gene expression, chromatin modifications, DNA methylation or nuclear interactions in an allele-specific fashion. SNPsplit is an allele-specific alignment sorter designed to read files in SAM/BAM format and determine the allelic origin of reads or read-pairs that cover known single nucleotide polymorphic (SNP) positions. For this to work libraries must have been aligned to a genome in which all known SNP positions were masked with the ambiguity base 'N' and aligned using a suitable mapping program such as Bowtie2, TopHat, STAR, HISAT2, HiCUP or Bismark. SNPsplit also provides an automated solution to generate N-masked reference genomes for hybrid mouse strains based on the variant call information provided by the Mouse Genomes Project. The unique ability of SNPsplit to work with various different kinds of sequencing data including RNA-Seq, ChIP-Seq, Bisulfite-Seq or Hi-C opens new avenues for the integrative exploration of allele-specific data.
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Project description:Small interfering RNA (siRNA) holds therapeutic promise for silencing dominantly acting disease genes, particularly if mutant alleles can be targeted selectively. In mammalian cell models we demonstrate that allele-specific silencing of disease genes with siRNA can be achieved by targeting either a linked single-nucleotide polymorphism (SNP) or the disease mutation directly. For a polyglutamine neurodegenerative disorder in which we first determined that selective targeting of the disease-causing CAG repeat is not possible, we took advantage of an associated SNP to generate siRNA that exclusively silenced the mutant Machado-Joseph disease/spinocerebellar ataxia type 3 allele while sparing expression of the WT allele. Allele-specific suppression was accomplished with all three approaches currently used to deliver siRNA: in vitro-synthesized duplexes as well as plasmid and viral expression of short hairpin RNA. We further optimized siRNA to specifically target a missense Tau mutation, V337M, that causes frontotemporal dementia. These studies establish that siRNA can be engineered to silence disease genes differing by a single nucleotide and highlight a key role for SNPs in extending the utility of siRNA in dominantly inherited disorders.
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Project description:Although gene-environment interactions are known to play an important role in the inheritance of complex traits, it is still unknown how a genotype and the environmental factors result in an observable phenotype. Understanding this complex interaction in the pathogenesis of diabetic retinopathy (DR) remains a big challenge as DR appears to be a disease with heterogenous phenotypes with multifactorial influence. In this review, we examine the natural history and risk factors related to DR, emphasizing distinct clinical phenotypes and their natural course in retinopathy. Although there is strong evidence that duration of diabetes and metabolic factors play a key role in the pathogenesis of DR, accumulating new clinical studies reveal that this disease can develop independently of duration of diabetes and metabolic dysfunction. More recently, studies have emphasized the role of genetic factors in DR. However, linkage analyses, candidate gene studies, and genome-wide association studies (GWAS) have not produced any statistically significant results. Our recently initiated genomics study, the Diabetic Retinopathy Genomics (DRGen) Study, aims to examine the contribution of rare and common variants in the development DR, and how they can contribute to clinical phenotype, rate of progression, and response to available therapies. Our preliminary findings reveal a novel set of genetic variants associated with proangiogenic and inflammatory pathways that may contribute to DR pathogenesis. Further investigation of these variants is necessary and may lead to development of novel biomarkers and new therapeutic targets in DR.
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Project description:In the past decade, population genetics has gained tremendous success in identifying genetic variations that are statistically relevant to renal diseases and kidney function. However, it is challenging to interpret the functional relevance of the genetic variations found by population genetics studies. In this review, we discuss studies that integrate multiple levels of data, especially transcriptome profiles and phenotype data, to assign functional roles of genetic variations involved in kidney function. Furthermore, we introduce state-of-the-art machine learning algorithms, Bayesian networks, support vector machines, and Gaussian process regression, which have been applied successfully to integrating genetic, regulatory, and clinical information to predict clinical outcomes. These methods are likely to be deployed successfully in the nephrology field in the near future.
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Project description:Significant human diseases/phenotypes exist which require both an environmental trigger event and a genetic predisposition before the disease/phenotype emerges, e.g. Carbamazepine with the rare SNP allele of rs3909184 causing Stevens Johnson syndrome, and aminoglycosides with rs267606617 causing sensory neural deafness. The underlying genotypes are fully penetrant only when the correct environmental trigger(s) occur, otherwise they are silent and harmless. Such diseases/phenotypes will not appear to have a Mendelian inheritance pattern, unless the environmental trigger is very common (>50% per lifetime). The known causative genotypes are likely to be protein-altering SNPs with dominant/semi-dominant effect. We questioned whether other diseases and phenotypes could have a similar aetiology.We wrote the fSNPd program to analyse multiple exomes from a test cohort simultaneously with the purpose of identifying SNP alleles at a significantly different frequency to that of the general population. fSNPd was tested on trial cohorts, iteratively improved, and modelled for performance against an idealised association study under mutliple parameters. We also assessed the seqeuncing depath of all human exons to determine which were sufficiently well sequenced in an exome to be sued by fSNPd - by assessing forty exomes base by base.We describe a simple methodology for the detection of SNPs capable of causing a phenotype triggered by an environmental event. This uses cohorts of relatively small size (30-100 individuals) with the phenotype being investigated, their exomes, and thence seeks SNP allele frequencies significantly different from expected to identify potentially clinically important, protein altering SNP alleles. The strengths and weaknesses of this approach for discovering significant genetic causes of human disease are comparable to Mendelian disease mutation detection and Association Studies.The fSNPd methodology is another approach, and has potentially significant advantage over Association studies in needing far fewer individuals, to detect genes involved in the pathogenesis of a diseases/phenotypes. Furthermore, the SNP alleles identified alter amino acids, potentially making it easier to devise functional assays of protein function to determine pathogenicity.
| S-EPMC5716007 | biostudies-literature
Project description:BackgroundThe presence of strain-specific modifier genes is known to modulate the phenotype and pathophysiology of mice harboring genetically engineered mutations. Thus, identification of genetic modifier genes is requisite to understanding control of phenotypic expression. c-Ski is a transcriptional regulator. Ski(-/-) mice on a C57BL6J (B6) background exhibit facial clefting, while Ski(-/-) mice on a 129P3 (129) background present with exencephaly.MethodsIn the present study, oligonucleotide-based gene expression profiling was used to identify potential strain-specific modifier gene candidates present in wild type mice of B6 and 129 genetic backgrounds. Changes in gene expression were verified by TaqMan quantitative real-time PCR.ResultsSteady-state levels of 89 genes demonstrated a significantly higher level of expression, and those of 68 genes demonstrated a significantly lower level of expression in the developing neural tubes from embryonic day (E) 8.5, B6 embryos when compared to expression levels in neural tubes derived from E 8.5, 129 embryos.ConclusionsBased on the results from the current comparative microarray study, and taking into consideration a number of relevant published reports, several potential strain-specific gene candidates, likely to modify the craniofacial phenotypes in various knockout mouse models have been identified.
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Project description:Measuring allele-specific RNA expression provides valuable insights into cis-acting genetic and epigenetic regulation of gene expression. Widespread adoption of high-throughput sequencing technologies for studying RNA expression (RNA-Seq) permits measurement of allelic RNA expression imbalance (AEI) at heterozygous single nucleotide polymorphisms (SNPs) across the entire transcriptome, and this approach has become especially popular with the emergence of large databases, such as GTEx. However, the existing binomial-type methods used to model allelic expression from RNA-seq assume a strong negative correlation between reference and variant allele reads, which may not be reasonable biologically.Here we propose a new strategy for AEI analysis using RNA-seq data. Under the null hypothesis of no AEI, a group of SNPs (possibly across multiple genes) is considered comparable if their respective total sums of the allelic reads are of similar magnitude. Within each group of "comparable" SNPs, we identify SNPs with AEI signal by fitting a mixture of folded Skellam distributions to the absolute values of read differences. By applying this methodology to RNA-Seq data from human autopsy brain tissues, we identified numerous instances of moderate to strong imbalanced allelic RNA expression at heterozygous SNPs. Findings with SLC1A3 mRNA exhibiting known expression differences are discussed as examples.The folded Skellam mixture model searches for SNPs with significant difference between reference and variant allele reads (adjusted for different library sizes), using information from a group of "comparable" SNPs across multiple genes. This model is particularly suitable for performing AEI analysis on genes with few heterozygous SNPs available from RNA-seq, and it can fit over-dispersed read counts without specifying the direction of the correlation between reference and variant alleles.
| S-EPMC4521363 | biostudies-literature
Project description:BackgroundInfants and children with dominant de novo mutations in GNAO1 exhibit movement disorders, epilepsy, or both. Children with loss-of-function (LOF) mutations exhibit Epileptiform Encephalopathy 17 (EIEE17). Gain-of-function (GOF) mutations or those with normal function are found in patients with Neurodevelopmental Disorder with Involuntary Movements (NEDIM). There is no animal model with a human mutant GNAO1 allele.ObjectivesHere we develop a mouse model carrying a human GNAO1 mutation (G203R) and determine whether the clinical features of patients with this GNAO1 mutation, which includes both epilepsy and movement disorder, would be evident in the mouse model.MethodsA mouse Gnao1 knock-in GOF mutation (G203R) was created by CRISPR/Cas9 methods. The resulting offspring and littermate controls were subjected to a battery of behavioral tests. A previously reported GOF mutant mouse knock-in (Gnao1+/G184S), which has not been found in patients, was also studied for comparison.ResultsGnao1+/G203R mutant mice are viable and gain weight comparably to controls. Homozygotes are non-viable. Grip strength was decreased in both males and females. Male Gnao1+/G203R mice were strongly affected in movement assays (RotaRod and DigiGait) while females were not. Male Gnao1+/G203R mice also showed enhanced seizure propensity in the pentylenetetrazole kindling test. Mice with a G184S GOF knock-in also showed movement-related behavioral phenotypes but females were more strongly affected than males.ConclusionsGnao1+/G203R mice phenocopy children with heterozygous GNAO1 G203R mutations, showing both movement disorder and a relatively mild epilepsy pattern. This mouse model should be useful in mechanistic and preclinical studies of GNAO1-related movement disorders.
| S-EPMC6347370 | biostudies-literature