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Eun Yong Kang

Publications and source records attributed to Eun Yong Kang.

3 recordsLinked to original sources

Distant regulatory effects of genetic variation in multiple human tissues

Understanding the genetics of gene regulation provides information on the cellular mechanisms through which genetic variation influences complex traits. Expression quantitative trait loci, or eQTLs, are enriched for polymorphisms that have been found to be associated with disease risk. While most analyses of human data has focused on regulation of expression by nearby variants (cis-eQTLs), distal or trans-eQTLs may have broader effects on the transcriptome and important phenotypic consequences, necessitating a comprehensive study of the effects of genetic variants on distal gene transcription levels. In this work, we identify trans-eQTLs in the Genotype Tissue Expression (GTEx) project data1, consisting of 449 individuals with RNA-sequencing data across 44 tissue types. We find 81 genes with a trans-eQTL in at least one tissue, and we demonstrate that trans-eQTLs are more likely than cis-eQTLs to have effects specific to a single tissue. We evaluate the genomic and functional properties of trans-eQTL variants, identifying strong enrichment in enhancer elements and Piwi-interacting RNA clusters. Finally, we describe three tissue-specific regulatory loci underlying relevant disease associations: 9q22 in thyroid that has a role in thyroid cancer, 5q31 in skeletal muscle, and a previously reported master regulator near KLF14 in adipose. These analyses provide a comprehensive characterization of trans-eQTLs across human tissues, which contribute to an improved understanding of the tissue-specific cellular mechanisms of regulatory genetic variation.

Genomics

The genetic basis of host choice and resting behavior in the major African malaria vector, Anopheles arabiensis

Malaria transmission is dependent on the propensity of Anopheles mosquitoes to bitehumans (anthropophily) instead of other dead end hosts. Recent increases in the usage of Long Lasting Insecticide Treated Nets (LLINs) in Africa have been associated with reductions in highly anthropophilic vectors such as Anopheles gambiae s.s.,leaving less anthropophilic species such as Anopheles arabiensis as the most prominent remaining source of transmission in many settings. An.arabiensis is more of a generalist in terms of its host choice and resting behavior, which may be due to phenotypic plasticity and/or segregating allelic variation. To investigate the potential genetic basis of host choice and resting behavior in An. arabiensis we performed a genome-wide association study on host choice (human-or cattle-fed) and resting position (collected indoors or outdoors) in the Kilombero Valley, Tanzania. This represents the first genomic/molecular analysis of host choice and resting behavior in a malaria vector. We identified a total of 4,820,851 SNPs, which were used to conduct the first genome-wide estimates of 'SNP heritability' for host choice and resting behavior in this species. A genetic component was detected for host choice (human vs cow fed; permuted P = 0.002), but there was no evidence of a genetic component for resting behavior (indoors versus outside; permuted P = 0.465). A principal component analysis (PCA) segregated individuals based on genomic variation into three groups which are characterized by differences at the 2Rb and/or 3Ra paracentromeric chromosome inversions. There was a non-random distribution of cattle-fed mosquitoes between the PCA clusters, suggesting that alleles linked to the 2Rb and/or 3Ra inversions may influence host choice. Using a novel inversion genotyping assay, we detected a significant enrichment of the standard arrangement (non-inverted) of 3Ra among cattle-fed mosquitoes (N=129) versus all non-cattle-fed individuals (N=234; 2, p=0.007). Thus, tracking the frequency of the 3Ra in An. arabiensis populations is important, especially in relation to the emergence of behavioral avoidance(e.g. shifting toward cattle-feeding) in some populations. A better understanding of the genetic basis for host choice in An. arabiensis may also open avenues for novel vector control strategies based on introducing genes for zoophily into wild mosquito populations.\n\nAuthor summaryMalaria transmission is driven by the propensity for mosquito vectors to bite people, whilst its control depends on the tendency of mosquitoes to bite and rest in places where they will come into contact with insecticides. In many parts of Africa, Anopheles arabiensis is now the only remaining vec 63 tor in areas where coverage with Long Lasting Insecticide Treated Nets is high. We sought to assess the potential for An. arabiensis to adapt its behavior to avoid control measures by investigating the genetic basis for its host choice and resting behavior. Blood fed An. arabiensis were collected resting indoors and outdoors in the Kilombero Valley, Tanzania. We sequenced a total of 48 genomes representing 4 phenotypes (human or cow fed, resting in or outdoors) and tested for a genetic basis for each phenotype. Genomic analysis followed up by application of a novel molecular karyotyping assay revealed a relationship between An. arabiensis that fed on cattle and the standard arrangement of the 3Ra inversion. This indicates that the host choice behavior of An. arabiensis has has a substantial genetic component. Validation with controlled host preference assays comparing individuals with the standard and inverted arrangement of 3Ra is still needed.

Genetics

An Ancestry Based Approach for Detecting Interactions

IBackgroundEpistasis and gene-environment interactions are known to contribute significantly to variation of complex phenotypes in model organisms. However, their identification in human association studies remains challenging for myriad reasons. In the case of epistatic interactions, the large number of potential interacting sets of genes presents computational, multiple hypothesis correction, and other statistical power issues. In the case of gene-environment interactions, the lack of consistently measured environmental covariates in most disease studies precludes searching for interactions and creates difficulties for replicating studies.\n\nResultsIn this work, we develop a new statistical approach to address these issues that leverages genetic ancestry in admixed populations. We applied our method to gene expression and methylation data from African American and Latino admixed individuals respectively, identifying nine interactions that were significant at p < 5x10-8, we show that two of the interactions in methylation data replicate, and the remaining six are significantly enriched for low p-values (p < 1.8x10-6).\n\nConclusionWe show that genetic ancestry can be a useful proxy for unknown and unmeasured covariates in the search for interaction effects. These results have important implications for our understanding of the genetic architecture of complex traits.

Genetics