Biological molecules are composed of discrete units, called domains. The study of the identity and organization of these domains can reveal the correspondence between individual units in different molecules, and the history of domains themselves, which may guide our understanding of the evolutionary history of individual molecules. Currently, the study of domain organization in protein sequences is a mature field; however, the studies of domain organization in other types of biological sequences and protein structures are still in their infancy. There is currently no general framework and specific tools for the identification of domains or for the discovery of the domain organization. Existing tools do not explicitly define what a domain is. In some cases, existing tools (e.g., multiple sequence alignment tools) ignore domain organizations entirely, or represent only a limited subset of domain organization. As a result, the mosaic structures of biological data are left undetected, and we demonstrate that the prevalence of mosaic arrangements is under- appreciated. This dissertation considers shortcomings of current technologies and develops a generic framework for the discovery and analysis of domain organizations in any types of sequential data. We apply this framework in several biological contexts. First we develop the A-Bruijn Aligner (ABA), which represents a multiple sequence alignment (MSA) as a graph that automatically reveals the domain structures. Second, we develop a repeat domain graph approach that decomposes a repeat family library into repeat domains, which is the first method for the comprehensive identification of repeat domains in large genomes. Third, we extend the A-Bruijn graph approach to an exploration of the mosaic arrangements in protein structures. Finally, we propose a new method for structure comparison based on a simplified representation of protein structures using the local curvatures along their generalized backbones

Objective: To investigate gut microbial composition in Latino infants in relation to breastfeeding, obesity, and antibiotic exposure.Method: We analyzed the gut microbiome in 6-month-old Latino infants from an ongoing urban mother-child cohort. Alpha and beta diversity were assessed in relation to infants early dietary exposure and anthropometrics including obesity.Results: Infants exclusively breastfed at 4 to 6 weeks had lower alpha diversity and less bacterial abundance compared with those who did not. Breastfeeding status at 4 to 6 weeks and 6 months of age accounted for differences in alpha and beta diversity. Infants who were obese at 6 months of age had higher levels of alpha diversity compared with non-obese infants.Conclusions: Early exclusive breastfeeding and obesity impacts microbial diversity by 6 months of age in Latino infants, a group at high risk for future obesity.

Background

Most existing formulations of protein structure comparison are based on detailed atomic level descriptions of protein structures and bypass potential insights that arise from a higher-level abstraction.

Results

We propose a structure comparison approach based on a simplified representation of proteins that describes its three-dimensional path by local curvature along the generalized backbone of the polypeptide. We have implemented a dynamic programming procedure that aligns curvatures of proteins by optimizing a defined sum turning angle deviation measure.

Conclusion

Although our procedure does not directly optimize global structural similarity as measured by RMSD, our benchmarking results indicate that it can surprisingly well recover the structural similarity defined by structure classification databases and traditional structure alignment programs. In addition, our program can recognize similarities between structures with extensive conformation changes that are beyond the ability of traditional structure alignment programs. We demonstrate the applications of procedure to several contexts of structure comparison. An implementation of our procedure, CURVE, is available as a public webserver.

A variety of age-related differences in the innate and adaptive immune systems have been proposed to contribute to the increased susceptibility to infection of human neonates and older adults. The emergence of RNA sequencing (RNA-seq) provides an opportunity to obtain an unbiased, comprehensive, and quantitative view of gene expression differences in defined cell types from different age groups. An examination of ex vivo human monocyte responses to lipopolysaccharide stimulation or Listeria monocytogenes infection by RNA-seq revealed extensive similarities between neonates, young adults, and older adults, with an unexpectedly small number of genes exhibiting statistically significant age-dependent differences. By examining the differentially induced genes in the context of transcription factor binding motifs and RNA-seq data sets from mutant mouse strains, a previously described deficiency in interferon response factor-3 activity could be implicated in most of the differences between newborns and young adults. Contrary to these observations, older adults exhibited elevated expression of inflammatory genes at baseline, yet the responses following stimulation correlated more closely with those observed in younger adults. Notably, major differences in the expression of constitutively expressed genes were not observed, suggesting that the age-related differences are driven by environmental influences rather than cell-autonomous differences in monocyte development.

Carotid intima-media thickness (cIMT) is a subclinical measure of atherosclerosis with mounting evidence that higher cIMT confers an increased risk of cardiovascular disease. The ryanodine receptor 3 gene (RYR3) has previously been linked to increased cIMT; however, the causal variants have not yet been localized. Therefore, we sequenced 339,480 bp encompassing 104 exons and 2 kb flanking region of the RYR3 gene in 96 HIV-positive white men from the extremes of the distribution of common cIMT from the Fat Redistribution and Metabolic Changes in HIV infection study (FRAM). We identified 2710 confirmed variants (2414 single-nucleotide polymorphisms (SNPs) and 296 insertion/deletions (indels)), with a mean count of 736 SNPs (ranging from 528 to 1032) and 170 indels (ranging from 128 to 214) distributed in each individual. There were 39 variants in the exons and 15 of these were non-synonymous, of which with only 4 were common variants and the remaining 11 were rare variants, one was a novel SNP. We confirmed that the common variant rs2229116 was significantly associated with cIMT in this design (P<7.9 × 10(-9)), and observed seven other significantly associated SNPs (P<10(-8)). These variants including the private non-synonymous SNPs need to be followed up in a larger sample size and also tested with clinical atherosclerotic outcomes.

Background

Fibrates are commonly prescribed for hypertriglyceridemia, but they also lower LDL cholesterol and increase HDL cholesterol. Large interindividual variations in lipid response suggest that some patients may benefit more than others and genetic studies could help identify such patients.

Methods

We carried out the first genome-wide association study of lipid response to fenofibrate using data from two well-characterized clinical trials: the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Study and the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Study. Genome-wide association study data from both studies were imputed to the 1000 Genomes CEU reference panel (phase 1). Lipid response was modeled as the log ratio of the post-treatment lipid level to the pretreatment level. Linear mixed models (GOLDN, N=813 from 173 families) and linear regression models (ACCORD, N=781) adjusted for pretreatment lipid level, demographic variables, clinical covariates, and ancestry were used to evaluate the association of genetic markers with lipid response. Among Caucasians, the results were combined using inverse-variance weighted fixed-effects meta-analyses. The main findings from the meta-analyses were examined in other ethnic groups from the HyperTG study (N=267 Hispanics) and ACCORD (N=83 Hispanics, 138 African Americans).

Results

A known lipid locus harboring the pre-B-cell leukemia homeobox 4 (PBX4) gene on chromosome 19 is important for LDL cholesterol response to fenofibrate (smallest P=1.5×10). The main results replicated with nominal statistical significance in Hispanics from ACCORD (P<0.05).

Conclusion

Future research should evaluate the usefulness of this locus to refine clinical strategies for lipid-lowering treatments.

Background

Genome-wide association studies have identified loci influencing circulating lipid concentrations in humans; further information on novel contributing genes, pathways, and biology may be gained through studies of epigenetic modifications.

Methods and results

To identify epigenetic changes associated with lipid concentrations, we assayed genome-wide DNA methylation at cytosine-guanine dinucleotides (CpGs) in whole blood from 2306 individuals from 2 population-based cohorts, with replication of findings in 2025 additional individuals. We identified 193 CpGs associated with lipid levels in the discovery stage (P<1.08E-07) and replicated 33 (at Bonferroni-corrected P<0.05), including 25 novel CpGs not previously associated with lipids. Genes at lipid-associated CpGs were enriched in lipid and amino acid metabolism processes. A differentially methylated locus associated with triglycerides and high-density lipoprotein cholesterol (HDL-C; cg27243685; P=8.1E-26 and 9.3E-19) was associated with cis-expression of a reverse cholesterol transporter (ABCG1; P=7.2E-28) and incident cardiovascular disease events (hazard ratio per SD increment, 1.38; 95% confidence interval, 1.15-1.66; P=0.0007). We found significant cis-methylation quantitative trait loci at 64% of the 193 CpGs with an enrichment of signals from genome-wide association studies of lipid levels (P_TC=0.004, P_HDL-C=0.008 and P_{triglycerides}=0.00003) and coronary heart disease (P=0.0007). For example, genome-wide significant variants associated with low-density lipoprotein cholesterol and coronary heart disease at APOB were cis-methylation quantitative trait loci for a low-density lipoprotein cholesterol-related differentially methylated locus.

Conclusions

We report novel associations of DNA methylation with lipid levels, describe epigenetic mechanisms related to previous genome-wide association studies discoveries, and provide evidence implicating epigenetic regulation of reverse cholesterol transport in blood in relation to occurrence of cardiovascular disease events.

We evaluated interactions of SNP-by-ACE-I/ARB and SNP-by-TD on serum potassium (K+) among users of antihypertensive treatments (anti-HTN). Our study included seven European-ancestry (EA) (N = 4835) and four African-ancestry (AA) cohorts (N = 2016). We performed race-stratified, fixed-effect, inverse-variance-weighted meta-analyses of 2.5 million SNP-by-drug interaction estimates; race-combined meta-analysis; and trans-ethnic fine-mapping. Among EAs, we identified 11 significant SNPs (P < 5 × 10^-8) for SNP-ACE-I/ARB interactions on serum K+ that were located between NR2F1-AS1 and ARRDC3-AS1 on chromosome 5 (top SNP rs6878413 P = 1.7 × 10^-8; ratio of serum K+ in ACE-I/ARB exposed compared to unexposed is 1.0476, 1.0280, 1.0088 for the TT, AT, and AA genotypes, respectively). Trans-ethnic fine mapping identified the same group of SNPs on chromosome 5 as genome-wide significant for the ACE-I/ARB analysis. In conclusion, SNP-by-ACE-I /ARB interaction analyses uncovered loci that, if replicated, could have future implications for the prevention of arrhythmias due to anti-HTN treatment-related hyperkalemia. Before these loci can be identified as clinically relevant, future validation studies of equal or greater size in comparison to our discovery effort are needed.

The genetic sequence variation of people from the Indian subcontinent who comprise one-quarter of the world's population, is not well described. We carried out whole genome sequencing of 168 South Asians, along with whole-exome sequencing of 147 South Asians to provide deeper characterisation of coding regions. We identify 12,962,155 autosomal sequence variants, including 2,946,861 new SNPs and 312,738 novel indels. This catalogue of SNPs and indels amongst South Asians provides the first comprehensive map of genetic variation in this major human population, and reveals evidence for selective pressures on genes involved in skin biology, metabolism, infection and immunity. Our results will accelerate the search for the genetic variants underlying susceptibility to disorders such as type-2 diabetes and cardiovascular disease which are highly prevalent amongst South Asians.