Penalized regression methods are becoming increasingly popular in genome-wide association studies (GWAS) for identifying genetic markers associated with disease. However, standard penalized methods such as the LASSO do not take into account the possible linkage disequilibrium between adjacent markers. We propose a novel penalized approach for GWAS using a dense set of single nucleotide polymorphisms (SNPs). The proposed method uses the minimax concave penalty (MCP) for marker selection and incorporates linkage disequilibrium (LD) information by penalizing the difference of the genetic effects at adjacent SNPs with high correlation. A coordinate descent algorithm is derived to implement the proposed method. This algorithm is efficient and stable in dealing with a large number of SNPs. A multi-split method is used to calculate the p-values of the selected SNPs for assessing their significance. We refer to the proposed penalty function as the smoothed MCP (SMCP) and the proposed approach as the SMCP method. Performance of the proposed SMCP method and its comparison with a LASSO approach are evaluated through simulation studies, which demonstrate that the proposed method is more accurate in selecting associated SNPs. Its applicability to real data is illustrated using data from a GWAS on rheumatoid arthritis. Based on the idea of SMCP, we propose a new penalized method for group variable selection in GWAS with respect to the correlation between adjacent groups. The proposed method uses the group LASSO for encouraging group sparsity and a quadratic difference for adjacent group smoothing. We call it smoothed group LASSO, or SGL for short. Canonical correlations between two adjacent groups of SNPS are used as the weights in the quadratic difference penalty. Principal components are used to reduced dimensionality locally within groups. We derive a group coordinate descent algorithm for computing the solution path of the SGL. Simulation studies are used to evaluate the finite sample performance of the SGL and group LASSO. We also demonstrate its applicability on rheumatoid arthritis data.

This work discusses the field of genealogy, different types of records and data in them. The thesis describes the topic of comparison of data and record linkage. It further it also discusses the design and implementation of the resulting system. The developed system connects people from parish records to larger pedigrees. These are then stored in the form of a graph database. The success of the interconnection of records was tested on the provided data sets.

Quinoa is an important, highly nutritional grain crop in the Andean region of South America. DNA markers and linkage maps are important tools for the improvement of underdeveloped crops such as quinoa. The objectives of this study were to (i) develop a new set of SSR markers to augment the number of SSR markers available in quinoa, and (ii) construct a new genetic linkage map of quinoa based on SSRs using multiple recombinant-inbred line (RIL) populations. Here we report the development of 216 new polymorphic SSR markers from libraries enriched for GA, CAA, and AAT repeats, as well as 6 SSR markers developed from BAC-end sequences (BES-SSRs). Heterozygosity (H) values of the SSR markers ranged from 0.12 to 0.90, with an average value of 0.56. These new SSR and BES-SSR markers were analyzed on two RIL mapping populations (designated Population 1 and Population 40), each obtained by crossing Altiplano and coastal ecotypes of quinoa. Additional markers, including AFLPs, two 11S seed storage protein loci, a SNP, and the nucleolar organizing region (NOR), were also analyzed on one or both populations. Linkage maps were constructed for both populations. The Population 1 map contains 275 markers, including 200 SSR and 70 AFLP markers, as well as five additional markers. The map consists of 41 linkage groups (LGs) covering 913 cM. The Population 40 map contains 68 markers, including 62 SSR and six BES-SSR markers, and consists of 20 LGs covering 353 cM. Thirty-nine anchor markers common between both maps were used to combine 15 Population 1 LGs with 13 Population 40 LGs. The resulting integrated map consists of 13 LGs containing 140 SSR, 48 AFLP, four BES-SSR, one SNP, and one NOR marker spanning a total of 606 cM. A high level of segregation distortion was observed in both populations, indicating possible chromosomal regions associated with gametophytic factors or QTLs conferring a selective advantage under the particular growing conditions. As these maps are based primarily on easily-transferable SSR markers, they are particularly suitable for applications in the underdeveloped Andean regions where quinoa is grown.

Objectives: We sought to identify a novel gene for dilated cardiomyopathy (DCM). Background: DCM is a heritable, genetically heterogeneous disorder that remains idiopathic in the majority of patients. Familial cases provide an opportunity to discover unsuspected molecular bases of DCM, enabling pre-clinical risk detection. Methods: Two large families with autosomal-dominant DCM were studied. Genome-wide linkage analysis was used to identify a disease locus, followed by fine mapping and positional candidate gene sequencing. Mutation scanning was then performed in 278 unrelated subjects with idiopathic DCM, prospectively identified at the Mayo Clinic. Results: Overlapping loci for DCM were independently mapped to chromosome 10q25-q26. Deoxyribonucleic acid sequencing of affected individuals in each family revealed distinct heterozygous missense mutations in exon 9 of RBM20, encoding ribonucleic acid (RNA) binding motif protein 20. Comprehensive coding sequence analyses identified missense mutations clustered within this same exon in 6 additional DCM families. Mutations segregated with DCM (peak composite logarithm of the odds score >11.49), were absent in 480 control samples, and altered residues within a highly conserved arginine/serine (RS)-rich region. Expression of RBM20 messenger RNA was confirmed in human heart tissue. Conclusions: Our findings establish RBM20 as a DCM gene and reveal a mutation hotspot in the RS domain. RBM20 is preferentially expressed in the heart and encodes motifs prototypical of spliceosome proteins that regulate alternative pre-messenger RNA splicing, thus implicating a functionally distinct gene in human cardiomyopathy. RBM20 mutations are associated with young age at diagnosis, end-stage heart failure, and high mortality.

Barley is one of the world's most important food and feed crops. It is adapted to a wide range of environments. According to Harlan and Martini (1936) barley is grown from north of the Artic Circle to the sands of the Sahara, and from the slopes of Mt. Everest to the lower delta of the Nile. Considerable progress has been made in its improvement through plant breeding. Barley is one of the best cultivated crop plants for use in genetic studies. It is a diploid plant from the family Gramineae with seven pairs of chromosomes. The cultivated species are interfertile and have a large number of readily distinguishable genetic characters. Approximately 370 characters are recognized (Nilan, 1964). Many of Barley's genes have been mapped and assigned to one of the seven chromosomes. Linkage groups in barley have been designated in a number of ways. A Roman numeral was used extensively in the earlier studies to identify each linkage group. More recently an Arabic number system has been used. This system was adopted by the Fourth Annual Barley Research Worker's Conference and will be followed in this study. The study involves 24 contrasting factors and was undertaken to determine the location of certain genes already reported in specific linkage groups and, if possible, to assign several previously unassigned genes to linkage groups. Of the 24 factor pairs studied, six have not yet been assigned to a chromosome. The inheritance and linkage associations of these unassigned genes receive major emphasis in this study.

Twenty-two barley crosses (Hordeum sp.) were studied in the F2 generation to determine the inheritance of the following contrasting characters: (N,n),(E,e),(Tr, tr), (Li,li),(Gp,gp),(K,k),(Z,z), (Gl,gl), (Gs, gs),(B,b),(Trd,trd),(O,o),(R,r),(Rb,rb), and Ge, ge). The three factors for glossyness, (gl), (gs), and (ge), were studied in relation to the other factors and each other to determine possible linkage relationships. (gl) was found to be linked with (k) and 16 percent recombination and to (z) with 13 percent recombination. (gs) appeared to be linked with (gp) in two crosses, with a third cross showing independence. No other linkage relationships were found.

Record linkage is the process of combining information about a single individual from two or more records. Probabilistic record linkage gives weights to each field that is compared. The decision of whether the records should be linked is then determined by the sum of the weights, or “Score”, over all fields compared. Using methods similar to the simple versus simple most powerful test, an optimal record linkage decision rule can be established to minimize the number of unlinked records when the probability of false positive and false negative errors are specified. The weights needed for probabilistic record linkage necessitate linking a “training” subset of records for the computations. This is not practical in many settings, as hand matching requires a considerable time investment. In 1989, Matthew A. Jaro demonstrated how the Expectation-Maximization, or EM, algorithm could be used to compute the needed weights when fields have Binomial matching possibilities. This project applies this method of using the EM algorithm to calculate weights for head-of-household records from the 1910 and 1920 Censuses for Ascension Parish of Louisiana and Church and County Records from Perquimans County, North Carolina. This project also expands the Jaro's EM algorithm to a Multinomial framework. The performance of the EM algorithm for calculating weights will be assessed by comparing the computed weights to weights computed by clerical matching. Simulations will also be conducted to investigate the sensitivity of the algorithm to the total number of record pairs, the number of fields with missing entries, the starting values of estimated probabilities, and the convergence epsilon value.

<p> It was known, prior to this study, that there is a factor, or factors, in the centromere-proximal region of Neurospora sitophila which affect recombination near the centromere whether it is in Neurospora sitophila or transferred to Neurospora crassa. A location of this factor, or factors, was performed using tetrad and prototroph analysis. Further mapping of linkage group I of Neurospora crassa was undertaken when the Neurospora sitophila centromere-proximal region was present.</p> / Thesis / Master of Science (MSc)

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