Genomic Analysis of Wild Tomato Introgressions Determining Metabolism- and Yield-Associated Traits

With the aim of determining the genetic basis of metabolic regulation in tomato fruit, we constructed a detailed physical map of genomic regions spanning previously described metabolic quantitative trait loci of a Solanum pennellii introgression line population. Two genomic libraries from S. pennellii were screened with 104 colocated markers from five selected genomic regions, and a total of 614 bacterial artificial chromosome (BAC)/cosmids were identified as seed clones. Integration of sequence data with the genetic and physical maps of Solanum lycopersicum facilitated the anchoring of 374 of these BAC/cosmid clones. The analysis of this information resulted in a genome-wide map of a nondomesticated plant species and covers 10% of the physical distance of the selected regions corresponding to approximately 1% of the wild tomato genome. Comparative analyses revealed that S. pennellii and domesticated tomato genomes can be considered as largely colinear. A total of 1,238,705 bp from both BAC/cosmid ends and nine large insert clones were sequenced, annotated, and functionally categorized. The sequence data allowed the evaluation of the level of polymorphism between the wild and cultivated tomato species. An exhaustive microsynteny analysis allowed us to estimate the divergence date of S. pennellii and S. lycopersicum at 2.7 million years ago. The combined results serve as a reference for comparative studies both at the macrosyntenic and microsyntenic levels. They also provide a valuable tool for fine-mapping of quantitative trait loci in tomato. Furthermore, they will contribute to a deeper understanding of the regulatory factors underpinning metabolism and hence defining crop chemical composition.

Microallelotyping defines novel regions of loss of heterozygosity in uterine leiomyomas

Uterine leiomyomas are extremely common, benign, smooth muscle tumors that represent a significant public health problem. Although there have been few molecular studies of uterine leiomyomas, most of them have reported a very low frequency of loss of heterozygosity (LOH) in different regions of the genome. The detection of LOH has been used to identify genomic regions that harbor tumor suppressor genes and to characterize different tumor types. We have used a set of 15 microsatellite polymorphism markers to examine the frequency of allele loss in a panel of 64 human uterine leiomyomas matched to normal DNAs. The markers were chosen from regions involved in losses identified by comparative genomic hybridization in a subset of uterine leiomyomas described in a previous report. DNA from tumors and normal tissue was amplified by the polymerase chain reaction and subsequently analyzed using an ABI Prism 377 DNA automated sequencer. The frequency of LOH observed was low, except for the markers D15S87 (15q26.3), D7S493 (7p15.3), and D7S517 (7p22.2). No changes in microsatellite size were detected in our samples. These results provide useful clues for identifying putative tumor suppressor genes associated with a subset of uterine leiomyomas. (C) 2004 Wiley-Liss, Inc.

Comparative cytogenetic mapping of Sox2 and Sox14 in cichlid fishes and inferences on the genomic organization of both genes in vertebrates

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genomic divergence of zebu and taurine cattle identified through high-density SNP genotyping

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Prediction of genomic-enabled breeding values and genome-wide association study for feedlot average daily weight gain in Nelore cattle

Pós-graduação em Genética e Melhoramento Animal - FCAV

Genomic profiling of human penile carcinoma predicts worse prognosis and survival

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genomic gains in prostatic carcinoma and proliferative inflammatory atrophy in dogs

The dog can spontaneously develop prostate cancer and consequently can be used as an experimental model for prostatic diseases associated with aging, including benign prostate hyperplasia (BPH) and prostate carcinoma (PCa). DNA copy number variations (CNVs) have been used to identify genes associated with cancer development and progression. DNA microarray based comparative genomic hybridization (aCGH) is a technique that allows to identify copy number of thousands of genes throughout the genome. aCGH was used to identify genomic regions with significantly different DNA copy number in three benign prostatic hyperplasia (BPH), four proliferative inflammatory atrophy (PIA), and 14 canine prostate carcinoma (PCa). Five histologically normal prostate tissue were used as reference. Genomic DNA was extracted from formalin fixed and paraffin embedded samples and CNVs data was evaluated in Canine Genome CGH Microarray 4x44K (G2519F, Design ID021193, Agilent). Data analysis was performed using Genomic Workbench Standard Edition 5.0.14 (Agilent). PCa showed higher number of altered genes related to canonical diseases process, cellular functions and molecular pathways as well as greater inter-relationship between genes, compared with PIA and BPH. In conclusion, PCa showed a more complex genotype, being losses the most frequent genomic changes. Some discrepancies between genomic alterations in human and canine carcinomas may indicate the different clinical behavior of these tumors in these two species. In addition, it was observed was an ascending pattern of genomic complexity in BPH, PIA and CA consistent with a model of multistep tumor progression.

Evolutionary forces shaping genomic islands of population differentiation in humans

Background Levels of differentiation among populations depend both on demographic and selective factors: genetic drift and local adaptation increase population differentiation, which is eroded by gene flow and balancing selection. We describe here the genomic distribution and the properties of genomic regions with unusually high and low levels of population differentiation in humans to assess the influence of selective and neutral processes on human genetic structure. Methods Individual SNPs of the Human Genome Diversity Panel (HGDP) showing significantly high or low levels of population differentiation were detected under a hierarchical-island model (HIM). A Hidden Markov Model allowed us to detect genomic regions or islands of high or low population differentiation. Results Under the HIM, only 1.5% of all SNPs are significant at the 1% level, but their genomic spatial distribution is significantly non-random. We find evidence that local adaptation shaped high-differentiation islands, as they are enriched for non-synonymous SNPs and overlap with previously identified candidate regions for positive selection. Moreover there is a negative relationship between the size of islands and recombination rate, which is stronger for islands overlapping with genes. Gene ontology analysis supports the role of diet as a major selective pressure in those highly differentiated islands. Low-differentiation islands are also enriched for non-synonymous SNPs, and contain an overly high proportion of genes belonging to the 'Oncogenesis' biological process. Conclusions Even though selection seems to be acting in shaping islands of high population differentiation, neutral demographic processes might have promoted the appearance of some genomic islands since i) as much as 20% of islands are in non-genic regions ii) these non-genic islands are on average two times shorter than genic islands, suggesting a more rapid erosion by recombination, and iii) most loci are strongly differentiated between Africans and non-Africans, a result consistent with known human demographic history.

Comparison of identity by descent and identity by state for detecting genetic regions under selection in a sorghum pedigree breeding program

Seventy sorghum inbred lines which formed part of the Queensland Department of Primary Industries (QDPI) sorghum breeding program were screened with 104 previously mapped RFLP markers. The lines were related by pedigree and consisted of ancestral source lines, intermediate lines and recent releases from the program. We compared the effect of defining marker alleles using either identity by state (IBS) or identity by descent (IBD) on our capacity to trace markers through the pedigree and detect evidence of selection for particular alleles. Allelic identities defined using IBD were much more sensitive for detecting non-Mendelian segregation in this pedigree. Only one marker allele showed significant evidence of selection when IBS was used compared with ten regions with particular allelic identities when IBD was used. Regions under selection were compared with the location of QTLs for agronomic traits known to be under selection in the breeding program. Only two of the ten regions were associated with known QTLs that matched with knowledge of the agronomic characteristics of the ancestral lines. Some of the other regions were hypothesised to be associated with genes for particular traits based on the properties of the ancestral source lines.

Towards the prediction of mutations in genomic sequences

Bio-systems are inherently complex information processing systems. Furthermore, physiological complexities of biological systems limit the formation of a hypothesis in terms of behavior and the ability to test hypothesis. More importantly the identification and classification of mutation in patients are centric topics in today's cancer research. Next generation sequencing (NGS) technologies can provide genome-wide coverage at a single nucleotide resolution and at reasonable speed and cost. The unprecedented molecular characterization provided by NGS offers the potential for an individualized approach to treatment. These advances in cancer genomics have enabled scientists to interrogate cancer-specific genomic variants and compare them with the normal variants in the same patient. Analysis of this data provides a catalog of somatic variants, present in tumor genome but not in the normal tissue DNA. In this dissertation, we present a new computational framework to the problem of predicting the number of mutations on a chromosome for a certain patient, which is a fundamental problem in clinical and research fields. We begin this dissertation with the development of a framework system that is capable of utilizing published data from a longitudinal study of patients with acute myeloid leukemia (AML), who's DNA from both normal as well as malignant tissues was subjected to NGS analysis at various points in time. By processing the sequencing data at the time of cancer diagnosis using the components of our framework, we tested it by predicting the genomic regions to be mutated at the time of relapse and, later, by comparing our results with the actual regions that showed mutations (discovered at relapse time). We demonstrate that this coupling of the algorithm pipeline can drastically improve the predictive abilities of searching a reliable molecular signature. Arguably, the most important result of our research is its superior performance to other methods like Radial Basis Function Network, Sequential Minimal Optimization, and Gaussian Process. In the final part of this dissertation, we present a detailed significance, stability and statistical analysis of our model. A performance comparison of the results are presented. This work clearly lays a good foundation for future research for other types of cancer.^

Flexible strategies for association analysis with genomic phenotypes

Thesis (Ph.D.)--University of Washington, 2016-08

Genomic structure and marker-derived gene networks for growth and meat quality traits of brazilian nelore beef cattle.

Nelore is the major beef cattle breed in Brazil with more than 130 million heads. Genome-wide association studies (GWAS) are often used to associate markers and genomic regions to growth and meat quality traits that can be used to assist selection programs. An alternative methodology to traditional GWAS that involves the construction of gene network interactions, derived from results of several GWAS is the AWM (Association Weight Matrices)/PCIT (Partial Correlation and Information Theory). With the aim of evaluating the genetic architecture of Brazilian Nelore cattle, we used high-density SNP genotyping data (~770,000 SNP) from 780 Nelore animals comprising 34 half-sibling families derived from highly disseminated and unrelated sires from across Brazil. The AWM/PCIT methodology was employed to evaluate the genes that participate in a series of eight phenotypes related to growth and meat quality obtained from this Nelore sample.

Recombination hotspots and host susceptibility modulate the adaptive value of recombination during maize streak virus evolution

Background Maize streak virus -strain A (MSV-A; Genus Mastrevirus, Family Geminiviridae), the maize-adapted strain of MSV that causes maize streak disease throughout sub-Saharan Africa, probably arose between 100 and 200 years ago via homologous recombination between two MSV strains adapted to wild grasses. MSV recombination experiments and analyses of natural MSV recombination patterns have revealed that this recombination event entailed the exchange of the movement protein - coat protein gene cassette, bounded by the two genomic regions most prone to recombination in mastrevirus genomes; the first surrounding the virion-strand origin of replication, and the second around the interface between the coat protein gene and the short intergenic region. Therefore, aside from the likely adaptive advantages presented by a modular exchange of this cassette, these specific breakpoints may have been largely predetermined by the underlying mechanisms of mastrevirus recombination. To investigate this hypothesis, we constructed artificial, low-fitness, reciprocal chimaeric MSV genomes using alternating genomic segments from two MSV strains; a grass-adapted MSV-B, and a maize-adapted MSV-A. Between them, each pair of reciprocal chimaeric genomes represented all of the genetic material required to reconstruct - via recombination - the highly maize-adapted MSV-A genotype, MSV-MatA. We then co-infected a selection of differentially MSV-resistant maize genotypes with pairs of reciprocal chimaeras to determine the efficiency with which recombination would give rise to high-fitness progeny genomes resembling MSV-MatA. Results Recombinants resembling MSV-MatA invariably arose in all of our experiments. However, the accuracy and efficiency with which the MSV-MatA genotype was recovered across all replicates of each experiment depended on the MSV susceptibility of the maize genotypes used and the precise positions - in relation to known recombination hotspots - of the breakpoints required to re-create MSV-MatA. Although the MSV-sensitive maize genotype gave rise to the greatest variety of recombinants, the measured fitness of each of these recombinants correlated with their similarity to MSV-MatA. Conclusions The mechanistic predispositions of different MSV genomic regions to recombination can strongly influence the accessibility of high-fitness MSV recombinants. The frequency with which the fittest recombinant MSV genomes arise also correlates directly with the escalating selection pressures imposed by increasingly MSV-resistant maize hosts.

Prediction of multilocus identity-by-descent

Previous studies have enabled exact prediction of probabilities of identity-by-descent (IBD) in randommating populations for a few loci (up to four or so), with extension to more using approximate regression methods. Here we present a precise predictor of multiple-locus IBD using simple formulas based on exact results for two loci. In particular, the probability of non-IBD X ABC at each of ordered loci A, B, and C can be well approximated by XABC = XABXBC/XB and generalizes to X123. . .k = X12X23. . .Xk-1,k/ Xk-2, where X is the probability of non-IBD at each locus. Predictions from this chain rule are very precise with population bottlenecks and migration, but are rather poorer in the presence of mutation. From these coefficients, the probabilities of multilocus IBD and non-IBD can also be computed for genomic regions as functions of population size, time, and map distances. An approximate but simple recurrence formula is also developed, which generally is less accurate than the chain rule but is more robust with mutation. Used together with the chain rule it leads to explicit equations for non-IBD in a region. The results can be applied to detection of quantitative trait loci (QTL) by computing the probability of IBD at candidate loci in terms of identity-by-state at neighboring markers.

Studies on the pathophysiology and genetic basis of migraine

Migraine is a neurological disorder that affects the central nervous system causing painful attacks of headache. A genetic vulnerability and exposure to environmental triggers can influence the migraine phenotype. Migraine interferes in many facets of people’s daily life including employment commitments and their ability to look after their families resulting in a reduced quality of life. Identification of the biological processes that underlie this relatively common affliction has been difficult because migraine does not have any clearly identifiable pathology or structural lesion detectable by current medical technology. Theories to explain the symptoms of migraine have focused on the physiological mechanisms involved in the various phases of headache and include the vascular and neurogenic theories. In relation to migraine pathophysiology the trigeminovascular system and cortical spreading depression have also been implicated with supporting evidence from imaging studies and animal models. The objective of current research is to better understand the pathways and mechanisms involved in causing pain and headache to be able to target interventions. The genetic component of migraine has been teased apart using linkage studies and both candidate gene and genome-wide association studies, in family and case-control cohorts. Genomic regions that increase individual risk to migraine have been identified in neurological, vascular and hormonal pathways. This review discusses knowledge of the pathophysiology and genetic basis of migraine with the latest scientific evidence from genetic studies.