SNPsplit: Allele-specific splitting of alignments between genomes with known SNP genotypes.
Ontology highlight
ABSTRACT:
SUBMITTER: Krueger F
PROVIDER: S-EPMC4934512 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:SNP-association studies are a starting point for identifying genes that may be responsible for specific phenotypes, such as disease traits. The vast bulk of tools for SNP-association studies are directed toward SNPs in the human genome, and I am unaware of any tools designed specifically for such studies in bacterial or viral genomes. The PPFS (Predict Phenotypes From SNPs) package described here is an add-on to kSNP , a program that can identify SNPs in a data set of hundreds of microbial genomes. PPFS identifies those SNPs that are non-randomly associated with a phenotype based on the χ² probability, then uses those diagnostic SNPs for two distinct, but related, purposes: (1) to predict the phenotypes of strains whose phenotypes are unknown, and (2) to identify those diagnostic SNPs that are most likely to be causally related to the phenotype. In the example illustrated here, from a set of 68 E. coli genomes, for 67 of which the pathogenicity phenotype was known, there were 418,500 SNPs. Using the phenotypes of 36 of those strains, PPFS identified 207 diagnostic SNPs. The diagnostic SNPs predicted the phenotypes of all of the genomes with 97% accuracy. It then identified 97 SNPs whose probability of being causally related to the pathogenic phenotype was >0.999. In a second example, from a set of 116 E. coli genome sequences, using the phenotypes of 65 strains PPFS identified 101 SNPs that predicted the source host (human or non-human) with 90% accuracy.
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Project description:Imaging and chromatin capture techniques have provided important insights into our understanding of nuclear organization. A limitation of these techniques is the inability to resolve allele-specific spatiotemporal properties of genomic loci in living cells. Here, we describe an allele-specific CRISPR live-cell DNA imaging technique (SNP-CLING) to provide the first comprehensive insights into allelic positioning across space and time in mouse embryonic stem cells and fibroblasts. With 3D imaging, we studied alleles on different chromosomes in relation to one another and relative to nuclear substructures such as the nucleolus. We find that alleles maintain similar positions relative to each other and the nucleolus; however, loci occupy unique positions. To monitor spatiotemporal dynamics by SNP-CLING, we performed 4D imaging and determined that alleles are either stably positioned or fluctuating during cell state transitions, such as apoptosis. SNP-CLING is a universally applicable technique that enables the dissection of allele-specific spatiotemporal genome organization in live cells.
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Project description:With the recent increase in RNA sequencing efforts using large cohorts of individuals, surveying allele-specific gene expression is becoming increasingly frequent. Here, we report that, despite not containing explicit variant information, a list of genes known to be allele-specific in an individual is enough to recover key variants and link the individuals back to their genotypes and phenotypes. This creates a privacy conundrum.
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Project description:Amplification, deletion, and loss of heterozygosity of genomic DNA are hallmarks of cancer. In recent years a variety of studies have emerged measuring total chromosomal copy number at increasingly high resolution. Similarly, loss-of-heterozygosity events have been finely mapped using high-throughput genotyping technologies. We have developed a probe-level allele-specific quantitation procedure that extracts both copy number and allelotype information from single nucleotide polymorphism (SNP) array data to arrive at allele-specific copy number across the genome. Our approach applies an expectation-maximization algorithm to a model derived from a novel classification of SNP array probes. This method is the first to our knowledge that is able to (a) determine the generalized genotype of aberrant samples at each SNP site (e.g., CCCCT at an amplified site), and (b) infer the copy number of each parental chromosome across the genome. With this method, we are able to determine not just where amplifications and deletions occur, but also the haplotype of the region being amplified or deleted. The merit of our model and general approach is demonstrated by very precise genotyping of normal samples, and our allele-specific copy number inferences are validated using PCR experiments. Applying our method to a collection of lung cancer samples, we are able to conclude that amplification is essentially monoallelic, as would be expected under the mechanisms currently believed responsible for gene amplification. This suggests that a specific parental chromosome may be targeted for amplification, whether because of germ line or somatic variation. An R software package containing the methods described in this paper is freely available at http://genome.dfci.harvard.edu/~tlaframb/PLASQ.
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Project description:BackgroundChromosomal inversion is one of the most important mechanisms of evolution. Recent studies of comparative genomics have revealed that chromosomal inversions are abundant in the human genome. While such previously characterized inversions are large enough to be identified as a single alignment or a string of local alignments, the impact of ultramicro inversions, which are such short that the local alignments completely cover them, on evolution is still uncertain.ResultsIn this study, we developed a method for identifying ultramicro inversions by scanning of local alignments. This technique achieved a high sensitivity and a very low rate of false positives. We identified 2,377 ultramicro inversions ranging from five to 125 bp within the orthologous alignments between the human and chimpanzee genomes. The false positive rate was estimated to be around 4%. Based on phylogenetic profiles using the primate outgroups, 479 ultramicro inversions were inferred to have specifically inverted in the human lineage. Ultramicro inversions exclusively involving adenine and thymine were the most frequent; 461 inversions (19.4%) of the total. Furthermore, the density of ultramicro inversions in chromosome Y and the neighborhoods of transposable elements was higher than average. Sixty-five ultramicro inversions were identified within the exons of human protein-coding genes.ConclusionsWe defined ultramicro inversions as the inverted regions equal to or smaller than 125 bp buried within local alignments. Our observations suggest that ultramicro inversions are abundant among the human and chimpanzee genomes, and that location of the inversions correlated with the genome structural instability. Some of the ultramicro inversions may contribute to gene evolution. Our inversion-identification method is also applicable in the fine-tuning of genome alignments by distinguishing ultramicro inversions from nucleotide substitutions and indels.
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Project description:Sequence similarity search is a fundamental way of analyzing nucleotide sequences. Despite decades of research, this is not a solved problem because there exist many similarities that are not found by current methods. Search methods are typically based on a seed-and-extend approach, which has many variants (e.g. spaced seeds, transition seeds), and it remains unclear how to optimize this approach. This study designs and tests seeding methods for inter-mammal and inter-insect genome comparison. By considering substitution patterns of real genomes, we design sets of multiple complementary transition seeds, which have better performance (sensitivity per run time) than previous seeding strategies. Often the best seed patterns have more transition positions than those used previously. We also point out that recent computer memory sizes (e.g. 60 GB) make it feasible to use multiple (e.g. eight) seeds for whole mammal genomes. Interestingly, the most sensitive settings achieve diminishing returns for human-dog and melanogaster-pseudoobscura comparisons, but not for human-mouse, which suggests that we still miss many human-mouse alignments. Our optimized heuristics find ∼20,000 new human-mouse alignments that are missing from the standard UCSC alignments. We tabulate seed patterns and parameters that work well so they can be used in future research.
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Project description:Aneuploidy and structural variations (SVs) generate cancer genomes containing a mixture of rearranged genomic segments with extensive somatic copy number alterations. However, existing methods can identify either SVs or allele-specific copy number alterations but not both simultaneously, which provides a limited view of cancer genome structure. Here, we introduce Weaver, an algorithm for the quantification and analysis of allele-specific copy numbers of SVs. Weaver uses a Markov random field to estimate joint probabilities of allele-specific copy numbers of SVs and their inter-connectivity based on paired-end whole-genome sequencing data. Weaver also predicts the timing of SVs relative to chromosome amplifications. We demonstrate the accuracy of Weaver using simulations and findings from whole-genome optical mapping. We apply Weaver to generate allele-specific copy numbers of SVs for MCF-7 and HeLa cell lines and identify recurrent SV patterns in 44 TCGA ovarian cancer whole-genome sequencing datasets. Our approach provides a more complete assessment of the complex genomic architectures inherent to many cancer genomes.
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Project description:The proposed method is a modified and improved version of the existing "Allele-specific q-PCR" (ASQ) method for genotyping of single nucleotide polymorphism (SNP) based on fluorescence resonance energy transfer (FRET). This method is similar to frequently used techniques like Amplifluor and Kompetitive allele specific PCR (KASP), as well as others employing common universal probes (UPs) for SNP analyses. In the proposed ASQ method, the fluorophores and quencher are located in separate complementary oligonucleotides. The ASQ method is based on the simultaneous presence in PCR of the following two components: an allele-specific mixture (allele-specific and common primers) and a template-independent detector mixture that contains two or more (up to four) universal probes (UP-1 to 4) and a single universal quencher oligonucleotide (Uni-Q). The SNP site is positioned preferably at a penultimate base in each allele-specific primer, which increases the reaction specificity and allele discrimination. The proposed ASQ method is advanced in providing a very clear and effective measurement of the fluorescence emitted, with very low signal background-noise, and simple procedures convenient for customized modifications and adjustments. Importantly, this ASQ method is estimated as two- to ten-fold cheaper than Amplifluor and KASP, and much cheaper than all those methods that rely on dual-labeled probes without universal components, like TaqMan and Molecular Beacons. Results for SNP genotyping in the barley genes HvSAP16 and HvSAP8, in which stress-associated proteins are controlled, are presented as proven and validated examples. This method is suitable for bi-allelic uniplex reactions but it can potentially be used for 3- or 4-allelic variants or different SNPs in a multiplex format in a range of applications including medical, forensic, or others involving SNP genotyping.
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Project description:Live mRNA detection allows real time monitoring of specific transcripts and genetic alterations. The main challenge of live genetic detection is overcoming the high background generated by unbound probes and reaching high level of specificity with minimal off target effects. The use of Fluorescence Resonance Energy Transfer (FRET) probes allows differentiation between bound and unbound probes thus decreasing background. Probe specificity can be optimized by adjusting the length and through use of chemical modifications that alter binding affinity. Herein, we report the use of two oligonucleotide FRET probe system to detect a single nucleotide polymorphism (SNP) in murine Hras mRNA, which is associated with malignant transformations. The FRET oligonucleotides were modified with phosphorothioate (PS) bonds, 2'OMe RNA and LNA residues to enhance nuclease stability and improve SNP discrimination. Our results show that a point mutation in Hras can be detected in endogenous RNA of living cells. As determined by an Acceptor Photobleaching method, FRET levels were higher in cells transfected with perfect match FRET probes whereas a single mismatch showed decreased FRET signal. This approach promotes in vivo molecular imaging methods and could further be applied in cancer diagnosis and theranostic strategies.
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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.
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