published_or_final_version / Medical Sciences / Master / Master of Medical Sciences

published_or_final_version / Statistics / Master / Master of Philosophy

published_or_final_version / Pathology / Doctoral / Doctor of Philosophy

Single nucleotide polymorphisms (SNPs) have been increasingly popular for a wide range of genetic studies. A high-throughput genotyping technologies usually involves a statistical genotype calling algorithm. Most calling algorithms in the literature, using methods such as k-means and mixturemodels, rely on elliptical structures of the genotyping data; they may fail when the minor allele homozygous cluster is small or absent, or when the data have extreme tails or linear patterns. We propose an automatic genotype calling algorithm by further developing a linear grouping algorithm (Van Aelst et al., 2006). The proposed algorithm clusters unnormalized data points around lines as against around centroids. In addition, we associate a quality value, silhouette width, with each DNA sample and a whole plate as well. This algorithm shows promise for genotyping data generated from TaqMan technology (Applied Biosystems). A key feature of the proposed algorithm is that it applies to unnormalized fluorescent signals when the TaqMan SNP assay is used. The algorithm could also be potentially adapted to other fluorescence-based SNP genotyping technologies such as Invader Assay. Motivated by the SNP genotyping problem, we propose a partial likelihood approach to linear clustering which explores potential linear clusters in a data set. Instead of fully modelling the data, we assume only the signed orthogonal distance from each data point to a hyperplane is normally distributed. Its relationships with several existing clustering methods are discussed. Some existing methods to determine the number of components in a data set are adapted to this linear clustering setting. Several simulated and real data sets are analyzed for comparison and illustration purpose. We also investigate some asymptotic properties of the partial likelihood approach. A Bayesian version of this methodology is helpful if some clusters are sparse but there is strong prior information about their approximate locations or properties. We propose a Bayesian hierarchical approach which is particularly appropriate for identifying sparse linear clusters. We show that the sparse cluster in SNP genotyping datasets can be successfully identified after a careful specification of the prior distributions.

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The SLC30A2 zinc transporter has been investigated due to its important role in zinc secretion into human milk. SLC30A2 is expressed in mammary epithelial cells, and the presence of genetic variations in this transporter could cause low zinc transport into the milk, leading to Transient Neonatal Zinc Deficiency (TNZD) in newborns. Through bioinformatics analysis 22 SNPs were identified. Therefore, we aim to identify the functional changes caused by 4 SNPs. By subcloning the SLC30A2 open reading frames into the Gateway expression plasmid tagged with red and green fluorescent proteins (mCherry, tGFP). Four SNPs were introduced by mutagenesis and tagged with mCherry. We transfected individual plasmids into mammary epithelial cells (HC11) and observed cellular targeting using epifluorescent imaging. The most common variants located to secreting endosomes and membrane in HC11 cells. Incorrect targeting of SLC30A2 causes mislocalization. It may be possible to identify mothers carrying risk genotypes for infant zinc deficiency.

Motivation: RNA-Sequence or RNA-Seq experiments produce millions of discrete DNA sequence reads, as a measure of gene expression levels. It enable researchers to investigate complex aspects of the genomic studies. These include but not limited to identi cation of di erentially expressed (DE) genes in two or more treatment conditions and detection of novel transcripts. One of the common assumptions of RNA-Seq data is that, all gene counts follow an overdispersed Poisson or negative binomial (NB) distribution which is sometimes misleading because some genes may have stable transcription levels with no overdispersion. Thus, a more realistic assumption in RNA-Seq data is to consider two sets of genes: overdispersed and non-overdispersed. Method: We propose a new two step integrated approach to detect di erentially expressed (DE) genes in RNA-Seq data using standard Poisson model for non-overdispersed genes and NB model for overdispersed genes. This is an integrated approach because this method can be combined with any other NB based methods for detecting DE genes. Results: We evaluate the proposed approach using two simulated and two real RNA-Seq data sets. We compare the performance of our proposed method combined with the four popular R-software packages edgeR, DESeq, sSeq, and NBPSeq with their default settings. For both the simulated and real data sets, integrated approaches perform better or at least equally well compared to the regular methods embedded in these R-packages. / Access to thesis permanently restricted to Ball State community only.

Pattern of Linkage Disequilibrium (LD) is a major factor largely determining the power of association mapping studies. Along with nucleotide diversities and DNA polymorphism, knowledge of patterns of LD along the genome needs to be to known to effectively design association mapping studies. In this study, patterns of nucleotide diversity, population structure, LD was estimated in Norway spruce (Picea abies). The data used for this were 23 nuclear loci sequenced in around 90 individuals originating from natural populations of Norway spruce throughout the current distribution range in Sweden and Finland. The observed levels of nucleotide diversity are variable among loci varying between 0.002 and 0.008 if measured by average pairwise nucleotide diversity. Despite the samples stretching large part of Finland and Sweden there were no evidence for strong population structure. As in earlier studies LD decays fast with distance and the average pattern of the squared correlation of allele frequencies drops to less than 0.2 within 100bp. In order to put the data in perspective previously generated data sets were re-analyzed and compared to the inferred results.

The SLC30A2 zinc transporter has been investigated due to its important role in zinc secretion into human milk. SLC30A2 is expressed in mammary epithelial cells, and the presence of genetic variations in this transporter could cause low zinc transport into the milk, leading to Transient Neonatal Zinc Deficiency (TNZD) in newborns. Through bioinformatics analysis 22 SNPs were identified. Therefore, we aim to identify the functional changes caused by 4 SNPs. By subcloning the SLC30A2 open reading frames into the Gateway expression plasmid tagged with red and green fluorescent proteins (mCherry, tGFP). Four SNPs were introduced by mutagenesis and tagged with mCherry. We transfected individual plasmids into mammary epithelial cells (HC11) and observed cellular targeting using epifluorescent imaging. The most common variants located to secreting endosomes and membrane in HC11 cells. Incorrect targeting of SLC30A2 causes mislocalization. It may be possible to identify mothers carrying risk genotypes for infant zinc deficiency.

C. cinereus, any two of which are sufficient to promote B-regulated development following cell fusion. The isolation of the B42 locus is described along with the DNA sequence analysis that identified nine B mating type genes within a 27kb B42 -specific DNA sequence. Six of the genes, with small transcripts of 800-900nt, encode the mating pheromone precursors and the other three, with 1.9 to 2-5kb transcripts, encode the transmembrane pheromone receptors. The genes are arranged in three groups, designated group 1, 2 and 3, each consisting of one receptor gene and two pheromone genes. B42 and B6 share the same alleles of the group 1 genes, but not those of groups 2 and 3. This was demonstrated by DNAsequence analysis and Southern blot analysis. None of the group 1 genes from B42 were able to activate B -regulated development in a B6 host when introduced by transformation but with one exception, all genes from group 2 and group 3 were able to do so. This analysis led to the recognition that the three genes in any one group are held together in an allele-specific DNA sequence and that Southern blot analysis and transformation can be used to identify shared alleles in uncloned loci. Extensive Southern analyses using cloned genes to probe genomic DNAs from strains having other B mating specificites showed that different B loci may share identical alleles of two groups of genes. Mating partners thus require different alleles of only one group of genes to generate a compatible B mating interaction. Transformation analyses with the same cloned genes confirmed the conclusions derived from the hybridisation data. Multiple B mating specificities thus appear to be derived from three groups of multiallelic and functionally redundant genes. A tenth gene located within the B42- specific DNA sequence encodes a putative transporter protein belonging to the major facilitator superfamily (MFS). In other genomic backgrounds this gene lies in homologous flanking sequences and its presence within the B42 locus is unlikely to be related to mating type function.