101 research outputs found
Discovering rare variants from populations to families
Thesis advisor: Gabor T. MarthPartitioning an individual's phenotype into genetic and environmental components has been a major goal of genetics since the early 20th century. Formally, the proportion of phenotypic variance attributable to genetic variation in the population is known as heritability. Genome wide association studies have explained a modest percentage of variability of complex traits by genotyping common variants. Currently, there is great interest in what role rare variants play in explaining the missing heritability of complex traits. Advances of next generation sequencing and genomic enrichment technologies over the past several years have made it feasible to re-sequence large numbers of individuals, enabling the discovery of the full spectrum of genetic variation segregating in the human population, including rare variants. The four projects that comprise my dissertation all revolve around the discovery of rare variants from next generation sequencing datasets. In my first project, I analyzed data from the exon sequencing pilot of the 1000 Genomes Project, where I discovered variants from exome capture sequencing experiments in a worldwide sample of nearly 700 individuals. My results show that the allele frequency spectrum of the dataset has an excess of rare variants. My next project demonstrated the applicability of using whole-genome amplified DNA (WGA) in capture sequencing. WGA is a method that amplifies DNA from nanogram starting amounts of template. In two separate capture experiments I compared the concordance of call sets, both at the site and genotype level, of variant calls derived from WGA and genomic DNA. WGA derived calls have excellent concordance metrics, both at the site and genotypic level, suggesting that WGA DNA can be used in lieu of genomic DNA. The results of this study have ramifications for medical sequencing experiments, where DNA stocks are a finite quantity and re-collecting samples maybe too expensive or not possible. My third project kept its focus on capture sequencing, but in a different context. Here, I analyzed sequencing data from Mendelian exome study of non-sensorineural hearing loss (NSHL). A subset of 6 individuals (5 affected, 1 unaffected) from a family of European descent were whole exome sequenced in an attempt to uncover the causative mutation responsible for the loss of hearing phenotype in the family. Previous linkage analysis uncovered a linkage region on chr12, but no mutations in previous candidate genes were found, suggesting a novel mutation segregates in the family. Using a discrete filtering approach with a minor allele frequency cutoff, I uncovered a putative causative non-synonymous mutation in a gene that encodes a transmembrane protein. The variant perfectly segregates with the phenotype in the family and is enriched in frequency in an unrelated cohort of individuals. Finally, for my last project I implemented a variant calling method for family sequencing datasets, named Pgmsnp, which incorporates Mendelian relationships of family members using a Bayesian network inference algorithm. My method has similar detection sensitivities compared to other pedigree aware callers, and increases power of detection for non-founder individuals.Thesis (PhD) — Boston College, 2013.Submitted to: Boston College. Graduate School of Arts and Sciences.Discipline: Biology
Analysis of concordance of different haplotype block partitioning algorithms
BACKGROUND: Different classes of haplotype block algorithms exist and the ideal dataset to assess their performance would be to comprehensively re-sequence a large genomic region in a large population. Such data sets are expensive to collect. Alternatively, we performed coalescent simulations to generate haplotypes with a high marker density and compared block partitioning results from diversity based, LD based, and information theoretic algorithms under different values of SNP density and allele frequency. RESULTS: We simulated 1000 haplotypes using the standard coalescent for three world populations – European, African American, and East Asian – and applied three classes of block partitioning algorithms – diversity based, LD based, and information theoretic. We assessed algorithm differences in number, size, and coverage of blocks inferred under different conditions of SNP density, allele frequency, and sample size. Each algorithm inferred blocks differing in number, size, and coverage under different density and allele frequency conditions. Different partitions had few if any matching block boundaries. However they still overlapped and a high percentage of total chromosomal region was common to all methods. This percentage was generally higher with a higher density of SNPs and when rarer markers were included. CONCLUSION: A gold standard definition of a haplotype block is difficult to achieve, but collecting haplotypes covered with a high density of SNPs, partitioning them with a variety of block algorithms, and identifying regions common to all methods may be the best way to identify genomic regions that harbor SNP variants that cause disease
Methanol Extract of Euchelus asper
Marine molluscs are widely distributed throughout the world and many bioactive compounds exhibiting antiviral, antitumor, antileukemic, and antibacterial activity have been reported worldwide. The present study was designed to investigate the beneficial effect of methanol extract of Euchelus asper (EAME) on estrogen deficiency induced osteoporosis in ovariectomised mice model. Forty-two female Swiss albino mice were randomly assigned into Sham operated (Sham) group and six ovariectomised (OVX) subgroups such as OVX with vehicle (OVX); OVX with estradiol (2 mg/kg/day); OVX with EAME of graded doses (25, 50, 100, and 200 mg/kg/day). Bone turnover markers like serum alkaline phosphatase (ALP), serum acid phosphatase (ACP), serum calcium, and histological investigations of tibia and uterus were analysed. Metaphyseal DNA content of the femur bone was also studied. Antiosteoclastogenic activity of EAME was examined. Administration of EAME was able to reduce the increased bone turnover markers in the ovariectomised mice. Histomorphometric analysis revealed an increase in bone trabeculation and restoration of trabecular separation by EAME treatment. Metaphyseal DNA content of the femur of the OVX mice was increased by EAME administration. EAME also showed a potent antiosteoclastogenic behaviour. Thus, the present study reveals that EAME was able to successfully reduce the estrogen deficiency induced bone loss
The Alfredo Namitete Agroecology Credit System:A New Business Model That Supports Small-Scale Lending
A major obstruction in the development of sustainable agriculture is the weakness of the financial and banking sectors in supporting smallholder farming. While farmers need to invest in their farms, they struggle to find credit schemes adapted to their specific needs. This study explores the literature on a range of credit systems applied in different geographical and historical contexts to analyse the underlying drivers of their successes or otherwise. In light of this review, the study investigates a farmers’ association, Alfredo Namitete (AN), in Mozambique, offering a range of agroecology credit modalities. It is then assessed as to whether a new business model initiated with seed funding could be self-managed by the association itself and lead to greater autonomy. The AN pilot tested three schemes between 2015 and 2019. Based on the findings, i.e., better production, increased revenue and greater self-determination, the study combines elements for a new business model for small-scale lending. It concludes that to be effective, a credit scheme needs to meet several conditions simultaneously: believe in the genuine will to repay, abolish the lender–borrower distance, ensure a role for women in decision making, add a savings mechanism, combine individual and collective investments and, finally, reserve funds for solidarity and climate issues
Association of TMTC2 with human nonsyndromic sensorineural hearing loss
IMPORTANCE: Sensorineural hearing loss (SNHL) is commonly caused by conditions that affect cochlear structures or the auditory nerve, and the genes identified as causing SNHL to date only explain a fraction of the overall genetic risk for this debilitating disorder. It is likely that other genes and mutations also cause SNHL. OBJECTIVE: To identify a candidate gene that causes bilateral, symmetric, progressive SNHL in a large multigeneration family of Northern European descent. DESIGN, SETTING, AND PARTICIPANTS: In this prospective genotype and phenotype study performed from January 1, 2006, through April 1, 2016, a 6-generation family of Northern European descent with 19 individuals having reported early-onset hearing loss suggestive of an autosomal dominant inheritance were studied at a tertiary academic medical center. In addition, 179 unrelated adult individuals with SNHL and 186 adult individuals reporting nondeafness were examined. MAIN OUTCOMES AND MEASURES: Sensorineural hearing loss. RESULTS: Nine family members (5 women [55.6%]) provided clinical audiometric and medical records that documented hearing loss. The hearing loss is characterized as bilateral, symmetric, progressive SNHL that reached severe to profound loss in childhood. Audiometric configurations demonstrated a characteristic dip at 1000 to 2000 Hz. All affected family members wear hearing aids or have undergone cochlear implantation. Exome sequencing and linkage and association analyses identified a fully penetrant sequence variant (rs35725509) on chromosome 12q21 (logarithm of odds, 3.3) in the TMTC2 gene region that segregates with SNHL in this family. This gene explains the SNHL occurrence in this family. The variant is also associated with SNHL in a cohort of 363 unrelated individuals (179 patients with confirmed SNHL and 184 controls, P = 7 x 10-4). CONCLUSIONS AND RELEVANCE: A previously uncharacterized gene, TMTC2, has been identified as a candidate for causing progressive SNHL in humans. This finding identifies a novel locus that causes autosomal dominant SNHL and therefore a more detailed understanding of the genetic basis of SNHL. Because TMTC2 has not been previously reported to regulate auditory function, the discovery reveals a potentially new, uncharacterized mechanism of hearing loss
Assessing the Evolutionary Impact of Amino Acid Mutations in the Human Genome
Quantifying the distribution of fitness effects among newly arising mutations in the human genome is key to resolving important debates in medical and evolutionary genetics. Here, we present a method for inferring this distribution using Single Nucleotide Polymorphism (SNP) data from a population with non-stationary demographic history (such as that of modern humans). Application of our method to 47,576 coding SNPs found by direct resequencing of 11,404 protein coding-genes in 35 individuals (20 European Americans and 15 African Americans) allows us to assess the relative contribution of demographic and selective effects to patterning amino acid variation in the human genome. We find evidence of an ancient population expansion in the sample with African ancestry and a relatively recent bottleneck in the sample with European ancestry. After accounting for these demographic effects, we find strong evidence for great variability in the selective effects of new amino acid replacing mutations. In both populations, the patterns of variation are consistent with a leptokurtic distribution of selection coefficients (e.g., gamma or log-normal) peaked near neutrality. Specifically, we predict 27–29% of amino acid changing (nonsynonymous) mutations are neutral or nearly neutral (|s|<0.01%), 30–42% are moderately deleterious (0.01%<|s|<1%), and nearly all the remainder are highly deleterious or lethal (|s|>1%). Our results are consistent with 10–20% of amino acid differences between humans and chimpanzees having been fixed by positive selection with the remainder of differences being neutral or nearly neutral. Our analysis also predicts that many of the alleles identified via whole-genome association mapping may be selectively neutral or (formerly) positively selected, implying that deleterious genetic variation affecting disease phenotype may be missed by this widely used approach for mapping genes underlying complex traits
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Novel synthesised flavone derivatives provide significant insight into the structural features required for enhanced anti-proliferative activity
With many cancers showing resistance to current chemotherapies, the search for novel anti-cancer agents is attracting considerable attention. Natural flavonoids have been identified as useful leads in such programmes. However, since an in-depth understanding of the structural requirements for optimum activity is generally lacking, further research is required before the full potential of flavonoids as anti-proliferative agents can be realised. Herein a broad library of 76 methoxy and hydroxy flavones, and their 4-thio analogues, was constructed and their structure-activity relationships for anti-proliferative activity against the breast cancer cell lines MCF-7 (ER+ve), MCF-7/DX (ER+ve, anthracycline resistant) and MDA-MB-231 (ER-ve) were probed. Within this library, 42 compounds were novel, and all compounds were afforded in good yields and > 95% purity. The most promising lead compounds, specifically the novel hydroxy 4-thioflavones 15f and 16f, were further evaluated for their anti-proliferative activities against a broader range of cancer cell lines by the National Cancer Institute (NCI), USA and displayed significant growth inhibition profiles (e.g Compound-15f: MCF-7 (GI50 = 0.18 μM), T-47D (GI50 = 0.03 μM) and MDA-MB-468 (GI50 = 0.47 μM) and compound-16f: MCF-7 (GI50 = 1.46 μM), T-47D (GI50 = 1.27 μM) and MDA-MB-231 (GI50 = 1.81 μM). Overall, 15f and 16f exhibited 7-46 fold greater anti-proliferative potency than the natural flavone chrysin (2d). A systematic structure-activity relationship study against the breast cancer cell lines highlighted that free hydroxyl groups and the B-ring phenyl groups were essential for enhanced anti-proliferative activities. Substitution of the 4-C=O functionality with a 4-C=S functionality, and incorporation of electron withdrawing groups at C4’ of the B-ring phenyl, also enhanced activity. Molecular docking and mechanistic studies suggest that the anti-proliferative effects of flavones 15f and 16f are mediated via ER-independent cleavage of PARP and downregulation of GSK-3β for MCF-7 and MCF-7/DX cell lines. For the MDA-MB-231 cell line, restoration of the wild-type p53 DNA binding activity of mutant p53 tumour suppressor gene was indicated
The functional spectrum of low-frequency coding variation
Background
Rare coding variants constitute an important class of human genetic variation, but are underrepresented in current databases that are based on small population samples. Recent studies show that variants altering amino acid sequence and protein function are enriched at low variant allele frequency, 2 to 5%, but because of insufficient sample size it is not clear if the same trend holds for rare variants below 1% allele frequency.
Results
The 1000 Genomes Exon Pilot Project has collected deep-coverage exon-capture data in roughly 1,000 human genes, for nearly 700 samples. Although medical whole-exome projects are currently afoot, this is still the deepest reported sampling of a large number of human genes with next-generation technologies. According to the goals of the 1000 Genomes Project, we created effective informatics pipelines to process and analyze the data, and discovered 12,758 exonic SNPs, 70% of them novel, and 74% below 1% allele frequency in the seven population samples we examined. Our analysis confirms that coding variants below 1% allele frequency show increased population-specificity and are enriched for functional variants.
Conclusions
This study represents a large step toward detecting and interpreting low frequency coding variation, clearly lays out technical steps for effective analysis of DNA capture data, and articulates functional and population properties of this important class of genetic variatio
Global haplotype partitioning for maximal associated SNP pairs
<p>Abstract</p> <p>Background</p> <p>Global partitioning based on pairwise associations of SNPs has not previously been used to define haplotype blocks within genomes. Here, we define an association index based on LD between SNP pairs. We use the Fisher's exact test to assess the statistical significance of the LD estimator. By this test, each SNP pair is characterized as associated, independent, or not-statistically-significant. We set limits on the maximum acceptable proportion of independent pairs within all blocks and search for the partitioning with maximal proportion of associated SNP pairs. Essentially, this model is reduced to a constrained optimization problem, the solution of which is obtained by iterating a dynamic programming algorithm.</p> <p>Results</p> <p>In comparison with other methods, our algorithm reports blocks of larger average size. Nevertheless, the haplotype diversity within the blocks is captured by a small number of tagSNPs. Resampling HapMap haplotypes under a block-based model of recombination showed that our algorithm is robust in reproducing the same partitioning for recombinant samples. Our algorithm performed better than previously reported models in a case-control association study aimed at mapping a single locus trait, based on simulation results that were evaluated by a block-based statistical test. Compared to methods of haplotype block partitioning, we performed best on detection of recombination hotspots.</p> <p>Conclusion</p> <p>Our proposed method divides chromosomes into the regions within which allelic associations of SNP pairs are maximized. This approach presents a native design for dimension reduction in genome-wide association studies. Our results show that the pairwise allelic association of SNPs can describe various features of genomic variation, in particular recombination hotspots.</p
Evolutionary Processes Acting on Candidate cis-Regulatory Regions in Humans Inferred from Patterns of Polymorphism and Divergence
Analysis of polymorphism and divergence in the non-coding portion of the human genome yields crucial information about factors driving the evolution of gene regulation. Candidate cis-regulatory regions spanning more than 15,000 genes in 15 African Americans and 20 European Americans were re-sequenced and aligned to the chimpanzee genome in order to identify potentially functional polymorphism and to characterize and quantify departures from neutral evolution. Distortions of the site frequency spectra suggest a general pattern of selective constraint on conserved non-coding sites in the flanking regions of genes (CNCs). Moreover, there is an excess of fixed differences that cannot be explained by a Gamma model of deleterious fitness effects, suggesting the presence of positive selection on CNCs. Extensions of the McDonald-Kreitman test identified candidate cis-regulatory regions with high probabilities of positive and negative selection near many known human genes, the biological characteristics of which exhibit genome-wide trends that differ from patterns observed in protein-coding regions. Notably, there is a higher probability of positive selection in candidate cis-regulatory regions near genes expressed in the fetal brain, suggesting that a larger portion of adaptive regulatory changes has occurred in genes expressed during brain development. Overall we find that natural selection has played an important role in the evolution of candidate cis-regulatory regions throughout hominid evolution
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