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SNP Discovery (snp + discovery)
Selected AbstractsSNP Discovery and Haplotype Analysis in the Segmentally Duplicated DRD5 Coding RegionANNALS OF HUMAN GENETICS, Issue 3 2009Donna J. E. Housley Summary The dopamine receptor 5 gene (DRD5) holds much promise as a candidate locus for contributing to neuropsychiatric disorders and other diseases influenced by the dopaminergic system, as well as having potential to affect normal behavioral variation. However, detailed analyses of this gene have been complicated by its location within a segmentally duplicated chromosomal region. Microsatellites and SNPs upstream from the coding region have been used for association studies, but we find, using bioinformatics resources, that these markers all lie within a previously unrecognized second segmental duplication (SD). In order to accurately analyze the DRD5 locus for polymorphisms in the absence of contaminating pseudogene sequences, we developed a fast and reliable method for sequence analysis and genotyping within the DRD5 coding region. We employed restriction enzyme digestion of genomic DNA to eliminate the pseudogenes prior to PCR amplification of the functional gene. This approach allowed us to determine the DRD5 haplotype structure using 31 trios and to reveal additional rare variants in 171 unrelated individuals. We clarify the inconsistencies and errors of the recorded SNPs in dbSNP and HapMap and illustrate the importance of using caution when choosing SNPs in regions of suspected duplications. The simple and relatively inexpensive method presented herein allows for convenient analysis of sequence variation in DRD5 and can be easily adapted to other duplicated genomic regions in order to obtain good quality sequence data. [source] SNP discovery, expression and association analysis for the SDHD gene in pigsJOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 4 2007S.E.F. Guimaraes Summary The SDHD gene was examined for single nucleotide polymorphisms (SNP) as well as for expression changes in the Longissimus dorsi muscle of commercial pigs with different potential for growth. Three SNPs, including one previously described in the coding region and two new ones in the 3,-UTR, were found. The normalized expression of SDHD was correlated with growth, meat quality and sensory traits (p < 0.05). For the commercial pigs used in this study, as well as a Berkshire × Yorkshire resource population, the SNPs have been associated (p < 0.05) with: growth, carcass composition, meat quality and sensory traits. Despite the fact that the described SNPs were not significantly associated with the normalized expression values, the SDHD SNPs and expression were associated with growth and meat quality traits in pigs. [source] SNPs in ecological and conservation studies: a test in the Scandinavian wolf populationMOLECULAR ECOLOGY, Issue 2 2005J. M. SEDDON Abstract Single nucleotide polymorphisms (SNPs) have the potential to become the genetic marker of choice in studies of the ecology and conservation of natural populations because of their capacity to access variability across the genome. In this study, we provide one of the first demonstrations of SNP discovery in a wild population in order to address typical issues of importance in ecology and conservation in the recolonized Scandinavian and neighbouring Finnish wolf Canis lupus populations. Using end sequence from BAC (bacterial artificial chromosome) clones specific for dogs, we designed assays for 24 SNP loci, 20 sites of which had previously been shown to be polymorphic in domestic dogs and four sites were newly identified as polymorphic in wolves. Of the 24 assayed loci, 22 SNPs were found to be variable within the Scandinavian population and, importantly, these were able to distinguish individual wolves from one another (unbiased probability of identity of 4.33 × 10,8), providing equivalent results to that derived from 12 variable microsatellites genotyped in the same population. An assignment test shows differentiation between the Scandinavian and neighbouring Finnish wolf populations, although not all known immigrants are accurately identified. An exploration of the misclassification rates in the identification of relationships shows that neither 22 SNP nor 20 microsatellite loci are able to discriminate across single order relationships. Despite the remaining obstacle of SNP discovery in nonmodel organisms, the use of SNPs in ecological and conservation studies is encouraged by the advent of large scale screening methods. Furthermore, the ability to amplify extremely small fragments makes SNPs of particular use for population monitoring, where faecal and other noninvasive samples are routinely used. [source] Discovery, characterization and validation of single nucleotide polymorphisms within 206 bovine genes that may be considered as candidate genes for beef production and qualityANIMAL GENETICS, Issue 4 2009J. L. Williams Summary A large number of putative single nucleotide polymorphisms (SNPs) have been identified from the bovine genome-sequencing project. However, few of these have been validated and many will turn out to be sequencing artefacts or have low minor allele frequencies. In addition, there is little information available on SNPs within coding regions, which are likely to be responsible for phenotypic variation. Therefore, additional SNP discovery is necessary to identify and validate polymorphisms both in specific genes and genome-wide. Sequence-tagged sites within 286 genes were resequenced from a panel of animals representing a wide range of European cattle breeds. For 80 genes, no polymorphisms were identified, and 672 putative SNPs were identified within 206 genes. Fifteen European cattle breeds (436 individuals plus available parents) were genotyped with these putative SNPs, and 389 SNPs were confirmed to have minor allele frequencies above 10%. The genes containing SNPs were localized on chromosomes by radiation hybrid mapping and on the bovine genome sequence by Blast. Flanking microsatellite loci were identified, to facilitate the alignment of the genes containing the SNPs in relation to mapped quantitative trait loci. Of the 672 putative SNPs discovered in this work, only 11 were found among the validated SNPs and 100 were found among the approximately 2.3 million putative SNPs currently in dbSNP. The genes studied in this work could be considered as candidates for traits associated with beef production and the SNPs reported will help to assess the role of the genes in the genetic control of muscle development and meat quality. The allele frequency data presented allows the general utility of the SNPs to be assessed. [source] SNP discovery in Litopenaeus vannamei with a new computational pipelineANIMAL GENETICS, Issue 1 2009D. M. Gorbach Summary Litopenaeus vannamei (Pacific white shrimp) have been farmed in the Americas for many years and are growing in popularity in Asia with the development of specific pathogen-free stocks. The full genomic sequence of this species might not be available in the near future, so other tools are needed to discover the location of polymorphic sites for quantitative trait loci mapping, association studies and subsequent marker-assisted selection. Currently, 25 937 L. vannamei expressed sequence tags (ESTs) are publicly available. These sequences were manually screened, masked for tandem repeats and inputted into CAP3 for clustering. The resulting 3532 contigs were analysed for possible single nucleotide polymorphisms (SNPs) with snpidentifier, a newly developed computer program for predicting SNPs. snpidentifier is designed for ESTs without accompanying chromatogram sequence quality information, and therefore it performs quality control checks on all data. snpidentifier sets a threshold such that the sequences used have a poor quality nucleotide (N) frequency <0.1, and it trims off the first 10 bases of every sequence to ensure higher sequence quality. For a base to be predicted as an SNP, the minor nucleotide (allele) frequency must be >0.1, it must be observed at least four times and the 15 bases on either side must exactly match the consensus sequence. Using these conservative parameters, 504 SNPs were predicted from 141 contigs for L. vannamei. A small sample of 18 individuals from three lines have been sequenced to verify prediction results and 17 of 39 (44%) of the tested SNPs have been confirmed. [source] A 2.5-Mb contig constructed from Angus, Longhorn and horned Hereford DNA spanning the polled interval on bovine chromosome 1ANIMAL GENETICS, Issue 6 2006K. R. Wunderlich Summary The polled locus has been mapped by genetic linkage analysis to the proximal region of bovine chromosome 1. As an intermediate step in our efforts to identify the polled locus and the underlying causative mutation for the polled phenotype, we have constructed a BAC-based physical map of the interval containing the polled locus. Clones containing genes and markers in the critical interval were isolated from the TAMBT (constructed from Angus and Longhorn genomic DNA) and CHORI-240 (constructed from horned Hereford genomic DNA) BAC libraries and ordered based on fingerprinting and the presence or absence of 80 STS markers. A single contig spanning 2.5 Mb was assembled. Comparison of the physical order of STSs to the corresponding region of human chromosome 21 revealed the same order of genes within the polled critical interval. This contig of overlapping BAC clones from horned and polled breeds is a useful resource for SNP discovery and characterization of positional candidate genes. [source] Single nucleotide polymorphism (SNP) discovery in porcine expressed genesANIMAL GENETICS, Issue 3 2002S. C. Fahrenkrug High-throughput genotyping of swine populations is a potentially efficient method for establishing animal lineage and identification of loci important to animal health and efficient pork production. Markers were developed based upon single nucleotide polymorphisms (SNPs), which are abundant and amenable to automated genotyping platforms. The focus of this research was SNP discovery in expressed porcine genes providing markers to develop the porcine/human comparative map. Locus specific amplification (LSA) and comparative sequencing were used to generate PCR products and allelic information from parents of a swine reference family. Discovery of 1650 SNPs in 403 amplicons and strategies for optimizing LSA-based SNP discovery using alternative methods of PCR primer design, data analysis, and germplasm selection that are applicable to other populations and species are described. These data were the first large-scale assessment of frequency and distribution of porcine SNPs. [source] Tag SNP selection using particle swarm optimizationBIOTECHNOLOGY PROGRESS, Issue 2 2010Li-Yeh Chuang Abstract Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variations amongst species. With the genome-wide SNP discovery, many genome-wide association studies are likely to identify multiple genetic variants that are associated with complex diseases. However, genotyping all existing SNPs for a large number of samples is still challenging even though SNP arrays have been developed to facilitate the task. Therefore, it is essential to select only informative SNPs representing the original SNP distributions in the genome (tag SNP selection) for genome-wide association studies. These SNPs are usually chosen from haplotypes and called haplotype tag SNPs (htSNPs). Accordingly, the scale and cost of genotyping are expected to be largely reduced. We introduce binary particle swarm optimization (BPSO) with local search capability to improve the prediction accuracy of STAMPA. The proposed method does not rely on block partitioning of the genomic region, and consistently identified tag SNPs with higher prediction accuracy than either STAMPA or SVM/STSA. We compared the prediction accuracy and time complexity of BPSO to STAMPA and an SVM-based (SVM/STSA) method using publicly available data sets. For STAMPA and SVM/STSA, BPSO effective improved prediction accuracy for smaller and larger scale data sets. These results demonstrate that the BPSO method selects tag SNP with higher accuracy no matter the scale of data sets is used. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010 [source] | ||||||||||