The morphologic variability seen in the domestic dog, Canis lupus familiaris, is unique among mammals. Selective pressures imposed by humans have divided dogs into almost 400 separate breeds. Selection has also led to the development of approximately 450 hereditary diseases, many of which are limited to specific breeds. Over half of these diseases present with similar clinical characteristics to those of many human hereditary diseases, making the dog an ideal model for study of the genetic bases of such diseases. Many diseases do not have candidate genes or have too many candidates to characterize. This is exacerbated in complex diseases that are caused by several genes. Whole-genome scans can provide insight into diseases by identifying marker(s) that co-segregate with a disease phenotype. The Minimal Screening Set - 2 (MSS-2) is the most recent set of microsatellites suitable for whole-genome screens. The first objective of this work was to streamline genomic screens in order to efficiently analyze large numbers of animals. To this end, chromosome-specific microsatellite panels were developed for the MSS-2. Canine hip dysplasia (CHD) is the most common orthopedic disease of the dog. CHD primarily affects medium and large breed dogs, but is found in almost every breed. The major objective of this work was to use linkage analysis to identify chromosomal regions that contain genes that are involved in CHD. Two populations were screened using the MSS-2. The first was a small family of Boykin Spaniels, though no markers were statistically significant in a whole-genome screen. An outcrossed pedigree of Greyhound/Labrador Retrievers was created for quantitative trait loci (QTL) mapping of CHD. The informativeness of markers in the F2 and backcrossed generations were calculated to show the utility of using such a population. Other factors that affect the power of this pedigree to identify QTL were also highlighted. Chromosomes that were identified in a previous screen as harboring putative QTLs were examined using the chromosome-specific panels to further define and confirm the regions of interest. Although no markers reached statistical significance, several areas of interest were identified.

No description available.

This PhD dissertation is focused on short tandemly repeated nucleotide patterns which occur extremely often across DNA sequences, called microsatellites. The main characteristic of microsatellites, and probably the reason why they are so abundant across genomes, is the extremely high frequency of specific replication errors occurring within their sequences, which usually cause addition or deletion of one or more complete tandem repeat units. Due to these errors, frequent fluctuations in the number of repetitive units can be observed among cellular and organismal generations. The molecular mechanisms as well as the consequences of these microsatellite mutations, both, on a generational as well as on an evolutionary scale, have sparked debate and controversy among the scientific community. Furthermore, the bioinformatic approaches used to study microsatellites and the ways microsatellites are referred to in the general literature are often not rigurous, leading to misinterpretations and inconsistencies among studies. As an introduction to this complex topic, in Chapter I I present a review of the knowledge accumulated on microsatellites during the past two decades. A major part of this chapter has been published in the Encyclopedia of Life Sciences in a Chapter about microsatellite evolution (see Publication 1 in Appendix II). The ongoing controversy about the rates and patterns of microsatellite mutation was evident to me since before starting this PhD thesis. However, the subtler problems inherent to the computational analyses of microsatellites within genomes only became apparent when retrieving information on microsatellite distribution and abundance for the design of comparative genomic analyses. There are numerous publications analyzing the microsatellite content of genomes but, in most cases, the results presented can neither be reliably compared nor reproduced, mainly due to the lack of details on the microsatellite search process (particularly the program’s algorithm and the search parameters used) and because the results are expressed in terms that are relative to the search process (i.e. measures based on the absolute number of microsatellites). Therefore, in Chapter II I present a critical review of all available software tools designed to scan DNA sequences for microsatellites. My aim in undertaking this review was to assess the comparability of search results among microsatellite programs, and to identify the programs most suitable for the generation of microsatellite datasets for a thorough and reproducible comparative analysis of microsatellite content among genomic sequences. Using sequence data where the number and types of microsatellites were empirical know I compared the ability of 19 programs to accurately identify and report microsatellites. I then chose the two programs which, based on the algorithm and its parameters as well as the output informativity, offered the information most suitable for biological interpretation, while also reflecting as close as possible the microsatellite content of the test files. From the analysis of microsatellite search results generated by the various programs available, it became apparent that the program’s search parameters, which are specified by the user in order to define the microsatellite characteristics to the program, influence dramatically the resulting datasets. This is especially true for programs suited to allow imperfections within tandem repeats, because imperfect repetitions can not be defined accurately as is the case for perfect ones, and because several different algorithms have been proposed to address this problem. The detection of approximate microsatellites is, however, essential for the study of microsatellite evolution and for comparative analyses based on microsatellites. It is now well accepted that small deviations from perfect tandem repeat structure are common within microsatellites and larger repeats, and a number of different algorithms have been developed to confront the challenge of finding and registering microsatellites with all expectable kinds of imperfection. However, biologists have still to apply these tools to their full potential. In biological analyses single tandem repeat hits are consistently interpreted as isolated and independent repeats. This interpretation also depends on the search strategy used to report the microsatellites in DNA sequences and, therefore, I was particularly interested in the capacity of repeat finding programs to report imperfect microsatellites allowing interpretations that are useful in a biological sense. After analzying a series of tandem repeat finding programs I optimized my microsatellite searches to yield the best possible datasets for assessing and comparing the degree of imperfection of microsatellites among different genomes (Chapter III) During the program comparisons performed in Chapter II, I show that the most critical search parameter influencing microsatellite search results is the minimum length threshold. Biologically speaking, there is no consensus with respect to the minimum length, beyond which a short tandem repeat is expected to become prone to microsatellite-like mutations. Usually, a single absolute value of ~12 nucleotides is assigned irrespective of motif length.. In other cases thresholds are assigned in terms of number of repeat units (i.e. 3 to 5 repeats or more), which are better applied individually for each motif. The variation in these thresholds is considerable and not always justifiable. In addition, any current minimum length measures are likely naïve because it is clear that different microsatellite motifs undergo replication slippage at different length thresholds. Therefore, in Chapter III, I apply two probabilistic models to predict the minimum length at which microsatellites of varying motif types become overrepresented in different genomes based on the individual oligonucleotide frequency data of these genomes. Finally, after a range of optimizations and critical analyses, I performed a preliminary analysis of microsatellite abundance among 24 high quality complete eukaryotic genomes, including also 8 prokaryotic and 5 archaeal genomes for contrast. The availability of the methodologies and the microsatellite datasets generated in this project will allow informed formulation of questions for more specific genome research, either about microsatellites, or about other genomic features microsatellites could influence. These datasets are what I would have needed at the beginning of my PhD to support my experimental design, and are essential for the adequate data interpretation of microsatellite data in the context of the major evolutionary units; chromosomes and genomes.

Carthamus (Asteraceae) contains both crop species (C. tinctorius, safflower) and weedy species, increasing the need for a better understanding of the genus. Despite previous studies, many outstanding questions remain regarding the phylogenetic relationships of safflower, especially with regards to the weedy species. Investigation of the relationships in Carthamus was done using sequence data. The closest relative to C. tinctorius was studied using microsatellite data. Microsatellite data was also utilized to track the introgression of C. oxyacanthus DNA into the C. tinctorius genome in an interspecific cross. Sequence data supports the division of the genus into two sections, Carthamus and Atractylis. Both sequence and microsatellite data reveal that most traditionally recognized species are not monophyletic. Microsatellite data indicates that C. palaestinus is the closest relative of cultivated safflower. Microsatellites also indicate that C. oxyacanthus DNA is able to move into the C. tinctorius genome, showing potential for breeding programs and raising concerns for potential transgenic crops. / Plant Biology

Abstract The genetic structure at different spatial scales and growing habitats was studied on Silene tatarica, using AFLP and microsatellite markers. S. tatarica is a rare perennial plant occurring along riverbanks and shores of two annually flooding rivers in Finland. Regional scale analysis based on AFLP fragment analysis showed that at Oulanka River population structure represented mostly classical metapopulation model. In general, colonization-extinction processes had an important role, dispersal between subpopulations was limited and genetic differentiation was independent of geographic location. The same subpopulations were partly used to study spatial genetic structuring within subpopulations. Spatial autocorrelation revealed clear spatial genetic structure in each subpopulation. Paternity analysis in an isolated subpopulation showed small amounts of inbreeding, restricted seed dispersal and pollen flow through the subpopulation. Factors affecting the creation and maintenance of spatial genetic structure within subpopulation were most likely colonization events and restricted seed dispersal. The impact of river regulation on the genetic structure of populations was studied by comparing results from Oulanka River to the results obtained from second main growing area, Kitinen River. Oulanka River is a natural river system, whereas Kitinen is a regulated river. The overall regional scale studies did not indicate major differences between river systems. There were some clear population genetic differences between rivers but there were no clear evidence that those would have been caused by river regulation. More likely differences were related to the marginal location of Kitinen population at the edge of the distribution range. Studies indicated that regardless of the species rarity in Finland, active management measures are not currently needed in either S. tatarica growing area. Species specific microsatellite loci were isolated to complement AFLP studies. During the microsatellite isolation, an interesting amplification pattern was detected and studied further. It was suggested that there were repetitive areas within genome containing microsatellites resulting in unusual amplification. The most likely explanation for this phenomenon would be transposable elements containing proto-microsatellite areas. The microsatellites isolated could have evolved mostly from those proto-microsatellites.

Flamingo species generate tremendous interest whether they are small captive groups or wild populations numbering in the thousands. Genetic pedigrees are invaluable for maintaining maximum genetic diversity in captive, as well as wild, populations. However, presently there is a general lack of genetic data for flamingo populations. Microsatellites are loci composed of 2-6 base pair tandem repeats, scattered throughout higher eukaryotic genomes, often exhibiting high levels of polymorphism and heterozygosity. These loci are thus important genetic markers for identity, parentage and population studies. Here, six microsatellite loci were isolated from a microsatellite-enriched Caribbean flamingo partial genomic library. Two are compound complex repeats and four are perfect trinucleotide repeats. Each locus was amplified from Caribbean, African greater, Chilean and lesser flamingo genomic DNAs. Heterozygosity frequencies were calculated for Caribbean (range 0.12-0.90) and African greater flamingos (range 0.23-0.94) loci. All six microsatellite loci were found to be in Hardy-Weinberg equilibrium and linkage disequilibrium analyses did not suggest linkage for any pair of two greater flamingo subspecies (African and Caribbean) loci. At least five of the loci also exhibit polymorphism in Chilean and lesser flamingos, but due to small sample numbers, relevant allele/heterozygosity frequency calculations could not be estimated. Nucleotide sequence comparisons of the amplicons derived from the four flamingo groups reveal a high level of sequence conservation at all loci. Although small sample numbers again limit the data for lesser flamingos and to some degree for the Chilean birds, the sequences of the two greater flamingo subspecies were identical and the number of nonconserved nucleotides appears to be higher for lesser/greater comparisons than for Chilean/greater comparisons. This is consistent with Chilean flamingos being a different species within the same genus as the greater flamingos, while lesser flamingos belong to a separate genus. Parentage analyses on suggested African greater flamingo family groups from Disney's Animal Kingdom's collection were performed using microsatellite data. Results confirmed many suggested family groups but in other cases one or more of the suggested parents were clearly excluded. The six microsatellite loci isolated provide a new population management tool useful for both wild and captive flamingo populations.

Deep water corals are an understudied yet biologically important and fragile ecosystem under threat from recent increasing temperatures and high carbon dioxide emissions. Using 454 sequencing, we develop 14 new microsatellite markers for the deep water coral Eguchipsammia fistula, collected from the Red Sea but found in deep water coral ecosystems globally. We tested these microsatellite primers on 26 samples of this coral collected from a single population. Results show that these corals are highly clonal within this population stemming from a high level of asexual reproduction. Mitochondrial studies back up microsatellite findings of high levels of genetic similarity. CO1, ND1 and ATP6 mitochondrial sequences of E. fistula and 11 other coral species were used to build phylogenetic trees which grouped E. fistula with shallow water coral Porites rather than deep sea L. Petusa.

No description available.

<p> In the past two decades or so. microsatellites have become a very widely used genetic tool in many disciplines of biology. Their major downfalL however. is that they often need to be isolated de novo before they can be applied to molecular studies. Traditional shotgun cloning can be successfuL but it is often overly costly and time consuming. Compounding this downfall, isolating microsatellites from some taxa has been shown to be difficult. For example. on average only 0.46% of all clones screened using avian genomes will yield positive clones. This is thought to be a result of a smaller avian genome, a requirement for flight. Several alternative methods have been developed for isolating microsatellites, but the choice as to which isolation method to use is often arbitrary. To address this. four species of birds. the smooth-billed ani (Crotophaga ani). herring gull (Larus argentatus), yellow-bellied elaenia (Elaenia flavogaster), and pukeko (Porphyria porphyria), representing four different orders were used to compare two alternative isolation methods. Enrichment via selective hybridization versus cloning with Lambda Zap phage vector were compared in terms of monetary requirements (total startup cost as well as per isolation attempt cost). and time requirements (total time from start to finish and hands-on experimentation time). No significant difference was detected in terms of number of polymorphic microsatellite loci isolated by each method (p = 0.57), with enrichment yielding more for the anis and elaenias, Lambda Zap yielding more for herring gulls. and both methods isolating equal numbers for pukekos. Nor was any difference found between the methods for dollars spent per sequence with repeat (SWR) using the startup cost (p = 0.30). Enrichment. however. proved to be significantly more effective in terms of dollars per SWR isolated using the per use cost (p = 0.004) as well as hands-on minutes per SWR (p = 0.01) and total minutes per SWR (p < 0.01 ). Based on these tindings. selective hybridization is the better choice for microsatellite isolation. </p> / Thesis / Master of Science (MSc)

Ip Toi Yan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 81-105). / Abstracts in English and Chinese. / CONTENTS --- p.i-iii / ACKNOWLEDGEMENT --- p.iv / ABSTRACT --- p.v-vi / Chapter Chapter One --- INTRODUCTION --- p.1-2 / Chapter Chapter Two --- LITERATURE REVIEW --- p.3-37 / Chapter 2.1 --- Epidemiology and Etiology of Cervical and Endometrial Cancers --- p.3-4 / Chapter 2.1.1 --- Epidemiology and Etiology of Cervical cancer --- p.4 / Chapter 2.1.1.1 --- Incidence and Mortality --- p.4-6 / Chapter 2.1.1.2 --- Etiology --- p.6-8 / Chapter 2.1.2 --- Epidemiology and Etiology of Endometrial Cancer --- p.9 / Chapter 2.1.2.1 --- Incidence and Mortality --- p.9-11 / Chapter 2.1.2.2 --- Rick Factors --- p.11-14 / Chapter 2.2 --- Pathology of Cervical and Endometrial Cancers --- p.14 / Chapter 2.2.1 --- Pathology of Cervical Cancer --- p.14-15 / Chapter 2.2.1.1 --- Macroscopic Appearance --- p.15 / Chapter 2.2.1.2 --- Histology --- p.15-18 / Chapter 2.2.2 --- Staging of Cervical Cancer --- p.19-21 / Chapter 2.2.3 --- Pathology of Endometrial Cancer --- p.21 / Chapter 2.2.3.1 --- Macroscopic Appearance --- p.22 / Chapter 2.2.3.2 --- Histology --- p.22-24 / Chapter 2.2.4 --- Staging of Endometrial Cancer --- p.24-25 / Chapter 2.2 --- Introduction to Microsatellite Instability (MI) --- p.25 / Chapter 2.3.1 --- DNA structure --- p.25-27 / Chapter 2.3.2 --- Microsatellite --- p.27-28 / Chapter 2.3.3 --- Mismatch Repair (MMR) --- p.28-29 / Chapter 2.3.4 --- Microsatellite Instability (MI) --- p.30-33 / Chapter 2.3.5 --- Microsatellite Instability in various cancers --- p.33-37 / Chapter Chapter Three --- MATERIALS AND METHODS --- p.38-50 / Chapter 3.1 --- Materials --- p.38 / Chapter 3.1.1 --- Patients and Specimens --- p.38-39 / Chapter 3.1.2 --- Chemicals and Reagents --- p.39 / Chapter 3.1.2.1 --- Chemicals --- p.39-40 / Chapter 3.1.2.2 --- Solution --- p.40-41 / Chapter 3.1.2.3 --- Microsatellite Markers --- p.42 / Chapter 3.1.3 --- Major Equipment --- p.43 / Chapter 3.2 --- Methodology --- p.43 / Chapter 3.2.1 --- DNA Extraction --- p.43-45 / Chapter 3.2.2 --- DNA Amplification --- p.45 / Chapter 3.2.2.1 --- End-labeling of Primer --- p.45 / Chapter 3.2.2.2 --- Polymerase Chain Reaction (PCR) --- p.46 / Chapter 3.2.3 --- Electrophoresis of PCR Products and Autoradiography --- p.46-49 / Chapter 3.2.4 --- Determination Of Microsatellite Instability (MI) --- p.49 / Chapter 3.3 --- Statistical Analyses --- p.50 / Chapter Chapter Four --- Result --- p.51-66 / Chapter 4.1 --- Microsatellite Instability in Cervical Cancer --- p.51 / Chapter 4.1.1 --- Prevalence of MI in Cervical Cancer --- p.51 -54 / Chapter 4.1.2 --- MI and Age in Cervical Cancer --- p.55 / Chapter 4.1.3 --- MI and Histological Type in Cervical Cancer --- p.55-56 / Chapter 4.1.4 --- MI and Histologic Grades in Cervical Cancer --- p.56-57 / Chapter 4.1.5 --- MI and Clinical stage in Cervical Cancer --- p.57-58 / Chapter 4.1.6 --- MI and Clinical Status in Cervical Cancer --- p.58-59 / Chapter 4.2 --- Microsatellite Instability in Endometrial Cancer --- p.59 / Chapter 4.2.1 --- Prevalence of MI in Endometrial Cancer --- p.59-62 / Chapter 4.2.2 --- MI and Age Groups in Endometrial Cancer --- p.63 / Chapter 4.2.3 --- MI and Histological Type in Endometrial Cancer --- p.63-64 / Chapter 4.2.4 --- MI and Histologic Grades in Endometrial Cancer --- p.64-65 / Chapter 4.2.5 --- MI and Clinical stage of Endometrial Cancer --- p.65 / Chapter 4.2.6 --- MI and Clinical Status in Endometrial Cancer --- p.66 / Chapter Chapter Five --- Discussion --- p.67-77 / Chapter 5.1 --- MI detection --- p.67-71 / Chapter 5.2 --- MI of Cervical Cancer --- p.71 -74 / Chapter 5.3 --- MI of Endometrial Cancer --- p.74-77 / Chapter Chapter Six --- Conclusions --- p.78-80 / Reference --- p.81-112 / Appendix --- p.113-114