Transposable Elements and Genome Size Variations in Plants

Lee, Sung-Il,Kim, Nam-Soo Korea Genome Organization 2014 Genomics & informatics Vol.12 No.3

Although the number of protein-coding genes is not highly variable between plant taxa, the DNA content in their genomes is highly variable, by as much as 2,056-fold from a 1C amount of 0.0648 pg to 132.5 pg. The mean 1C-value in plants is 2.4 pg, and genome size expansion/contraction is lineage-specific in plant taxonomy. Transposable element fractions in plant genomes are also variable, as low as ~3% in small genomes and as high as ~85% in large genomes, indicating that genome size is a linear function of transposable element content. Of the 2 classes of transposable elements, the dynamics of class 1 long terminal repeat (LTR) retrotransposons is a major contributor to the 1C value differences among plants. The activity of LTR retrotransposons is under the control of epigenetic suppressing mechanisms. Also, genome-purging mechanisms have been adopted to counter-balance the genome size amplification. With a wealth of information on whole-genome sequences in plant genomes, it was revealed that several genome-purging mechanisms have been employed, depending on plant taxa. Two genera, Lilium and Fritillaria, are known to have large genomes in angiosperms. There were twice times of concerted genome size evolutions in the family Liliaceae during the divergence of the current genera in Liliaceae. In addition to the LTR retrotransposons, non-LTR retrotransposons and satellite DNAs contributed to the huge genomes in the two genera by possible failure of genome counter-balancing mechanisms.

Whole-genome sequence analysis through online web interfaces: a review

Gunasekara, A.W.A.C.W.R.,Rajapaksha, L.G.T.G.,Tung, T.L. Korea Genome Organization 2022 Genomics & informatics Vol.20 No.1

The recent development of whole-genome sequencing technologies paved the way for understanding the genomes of microorganisms. Every whole-genome sequencing (WGS) project requires a considerable cost and a massive effort to address the questions at hand. The final step of WGS is data analysis. The analysis of whole-genome sequence is dependent on highly sophisticated bioinformatics tools that the research personal have to buy. However, many laboratories and research institutions do not have the bioinformatics capabilities to analyze the genomic data and therefore, are unable to take maximum advantage of whole-genome sequencing. In this aspect, this study provides a guide for research personals on a set of bioinformatics tools available online that can be used to analyze whole-genome sequence data of bacterial genomes. The web interfaces described here have many advantages and, in most cases exempting the need for costly analysis tools and intensive computing resources.

Comparison of Erythrocyte Traits Among European, Japanese and Korean

Kwon, Ji-Sun,Kim, Sang-Soo Korea Genome Organization 2010 Genomics & informatics Vol.8 No.3

Erythrocyte traits are heritable and indirect indicators of blood diseases caused by erythrocyte, but their genetic factors are largely unknown. So we performed genome-wide association study in 8,842 Korean individuals to identify genetic factors influencing erythrocyte traits. We identified 40 associations for three erythrocyte traits at genome-wide significance levels (p < $1{\times}10^{-6}$). We compared these associated loci with those reported in genome-wide association studies of European and Japanese. Our findings include previously identified loci(HBS1L-MYB, TMPRSS6, USP49 and CCND3) in other studies and novel associations (MRDS1/OFCC1, CSDE1, NRAS and 8 other loci). For example, SNP rs4895440 of HBS1L-MYB intergenic region on chromosome 6q23.3 is one of the most associations influencing erythrocyte traits (p=$8.33{\times}10^{-27}$).

Application of Structural Equation Models to Genome-wide Association Analysis

Kim, Ji-Young,Namkung, Jung-Hyun,Lee, Seung-Mook,Park, Tae-Sung Korea Genome Organization 2010 Genomics & informatics Vol.8 No.3

Genome-wise association studies (GWASs) have become popular approaches to identify genetic variants associated with human biological traits. In this study, we applied Structural Equation Models (SEMs) in order to model complex relationships between genetic networks and traits as risk factors. SEMs allow us to achieve a better understanding of biological mechanisms through identifying greater numbers of genes and pathways that are associated with a set of traits and the relationship among them. For efficient SEM analysis for GWASs, we developed a procedure, comprised of four stages. In the first stage, we conducted single-SNP analysis using regression models, where age, sex, and recruited area were included as adjusting covariates. In the second stage, Fisher's combination test was conducted for each gene to detect significant genes using p-values obtained from the single-SNP analysis. In the third stage, Fisher's exact test was adopted to determine which biological pathways were enriched with significant SNPs. Finally, based on a pathway that was associated with the four traits in common, a SEM was fit to model a causal relationship among the genetic factors and traits. We applied our SEM model to GWAS data with four central obesity related traits: suprailiac and subscapular measures for upper body fat, BMI, and hypertension. Study subjects were collected from two Korean cohort regions. After quality control, 327,872 SNPs for 8842 individuals were included in the analysis. After comparing two SEMs, we concluded that suprailiac and subscapular measures may indirectly affect hypertension susceptibility by influencing BMI. In conclusion, our analysis demonstrates that SEMs provide a better understanding of biological mechanisms by identifying greater numbers of genes and pathways.

Computational Analysis of Neighboring Genes on Arabidopsis thaliana Chromosomes 4 and 5: Their Genomic Association as Functional Subunits

Goh, Sung-Ho,Kim, Tae-Hyung,Kim, Jee-Hyub,Nam, DouGu,Choi, Doil,Hur, Cheol-Goo Korea Genome Organization 2003 Genomics & informatics Vol.1 No.1

The genes related to specific events or pathways in bacteria are frequently localized proximate to the genome of their neighbors, as with the structures known as operon, but eukaryotic genes seem to be independent of their neighbors, and are dispersed randomly throughout genomes. Although cases are rare, the findings from structures similar to prokaryotic operons in the nematode genome, and the clustering of housekeeping genes on human genome, lead us to assess the genomic association of genes as functional subunits. We evaluated the genomic association of neighboring genes on chromosomes 4 and 5 of Arabidopsis thaliana with and without respectively consideration of the scaffold/matrix­attached regions (S/MAR) loci. The observed number of functionally identical bigrams and trig rams were significantly higher than expected, and these results were verified statistically by calculating p-values for weighted random distributions. The observed frequency of functionally identical big rams and trig rams were much higher in chromosome 4 than in chromosome 5, but the frequencies with, and without, consideration of the S/MAR in each chromosome were similar. In this study, a genomic association among functionally related neighboring genes in Arabidopsis thaliana was suggested.

New Approach to the Analysis of Palindromic Structure in Genome Sequences

Kim, Seok-Won,Lee, Yong-Seok,Choi, Sang-Haeng,Chae, Sung-Hwa,Kim, Dae-Won,Park, Hong-Seog Korea Genome Organization 2006 Genomics & informatics Vol.4 No.4

PABAP (Palindrome Analysis by BLAST Program) is an analysis system that identifies palindromic sequences from a large genome sequence up to several megabases long. It uses NCBI BLAST as a searching engine, and data processing such as alignment filtration and detection of inverted repeats which satisfy user-defined parameters is performed by manipulating data after populating into a MySQL database. PABAP outperforms publicly available palindrome search program in that it can detect large palindrome with internal spacer at a faster speed from bacterial genomes. It is a standalone application and is freely available for noncommercial users.

Cloning of Notl-linked DNA Detected by Restriction Landmark Genomic Scanning of Human Genome

Kim Jeong-Hwan,Lee Kyung-Tae,Kim Hyung-Chul,Yang Jin-Ok,Hahn Yoon-Soo,Kim Sang-Soo,Kim Seon-Young,Yoo Hyang-Sook,Kim Yong-Sung Korea Genome Organization 2006 Genomics & informatics Vol.4 No.1

Epigenetic alterations are common features of human solid tumors, though global DNA methylation has been difficult to assess. Restriction Landmark Genomic Scanning (RLGS) is one of technology to examine epigenetic alterations at several thousand Notl sites of promoter regions in tumor genome. To assess sequence information for Notl sequences in RLGS gel, we cloned 1,161 unique Notl-linked clones, compromising about 60% of the spots in the soluble region of RLGS profile, and performed BLAT searches on the UCSC genome server, May 2004 Freeze. 1,023 (88%) unique sequences were matched to the CpG islands of human genome showing a large bias of RLGS toward identifying potential genes or CpG islands. The cloned Notl-loci had a high frequency (71%) of occurrence within CpG islands near the 5' ends of known genes rather than within CpG islands near the 3' ends or intragenic regions, making RLGS a potent tool for the identification of gene-associated methylation events. By mixing RLGS gels with all Notl-linked clones, we addressed 151 Notl sequences onto a standard RLGS gel and compared them with previous reports from several types of tumors. We hope our sequence information will be useful to identify novel epigenetic targets in any types of tumor genome.

Lack of Replication of Genetic Association with Body Mass Index Detected by Genome-wide Association Study

Lee, Hae-In,Kim, Jae-Jung,Park, Tae-Sung,Kim, Kyung-A,Lee, Jong-Eun,Cho, Yoon-Shin,Lee, Jong-Young,Han, Bok-Ghee,Lee, Jong-Keuk Korea Genome Organization 2011 Genomics & informatics Vol.9 No.2

Obesity provokes many serious human diseases, including various cardiovascular diseases and diabetes. Body mass index (BMI) is a highly heritable trait that is broadly used to diagnose obesity. To identify genetic loci associated with obesity in Asians, we conducted a genome-wide association study (GWAS) of a population of Korean adults (n=6,742, age 40~60 years) and detected six BMI risk loci (TNR, FAM124B, RGS12, NFE2L3, MC4R and FTO) having p< $1{\times}10^{-5}$. However, in the replication study, only melanocortin 4 receptor gene (MC4R) (rs9946888, p=$4.58{\times}10^{-7}$) was replicated with marginal significance (p<0.05) in the second cohort (n=5,102, age 40~60 years). This study indicates that each locus associated with BMI has very weak genetic effect.

Identification of Causal and/or Rare Genetic Variants for Complex Traits by Targeted Resequencing in Population-based Cohorts

Kim, Yun-Kyoung,Hong, Chang-Bum,Cho, Yoon-Shin Korea Genome Organization 2010 Genomics & informatics Vol.8 No.3

Genome-wide association studies (GWASs) have greatly contributed to the identification of common variants responsible for numerous complex traits. There are, however, unavoidable limitations in detecting causal and/or rare variants for traits in this approach, which depends on an LD-based tagging SNP microarray chip. In an effort to detect potential casual and/or rare variants for complex traits, such as type 2 diabetes (T2D) and triglycerides (TGs), we conducted a targeted resequencing of loci identified by the Korea Association REsource (KARE) GWAS. The target regions for resequencing comprised whole exons, exon-intron boundaries, and regulatory regions of genes that appeared within 1 Mb of the GWA signal boundary. From 124 individuals selected in population-based cohorts, a total of 0.7 Mb target regions were captured by the NimbleGen sequence capture 385K array. Subsequent sequencing, carried out by the Roche 454 Genome Sequencer FLX, generated about 110,000 sequence reads per individual. Mapping of sequence reads to the human reference genome was performed using the SSAHA2 program. An average of 62.2% of total reads was mapped to targets with an average 22X-fold coverage. A total of 5,983 SNPs (average 846 SNPs per individual) were called and annotated by GATK software, with 96.5% accuracy that was estimated by comparison with Affymetrix 5.0 genotyped data in identical individuals. About 51% of total SNPs were singletons that can be considered possible rare variants in the population. Among SNPs that appeared in exons, which occupies about 20% of total SNPs, 304 nonsynonymous singletons were tested with Polyphen to predict the protein damage caused by mutation. In total, we were able to detect 9 and 6 potentially functional rare SNPs for T2D and triglycerides, respectively, evoking a further step of replication genotyping in independent populations to prove their bona fide relevance to traits.

Joint Identification of Multiple Genetic Variants of Obesity in a Korean Genome-wide Association Study

Oh, So-Hee,Cho, Seo-Ae,Park, Tae-Sung Korea Genome Organization 2010 Genomics & informatics Vol.8 No.3

In recent years, genome-wide association (GWA) studies have successfully led to many discoveries of genetic variants affecting common complex traits, including height, blood pressure, and diabetes. Although GWA studies have made much progress in finding single nucleotide polymorphisms (SNPs) associated with many complex traits, such SNPs have been shown to explain only a very small proportion of the underlying genetic variance of complex traits. This is partly due to that fact that most current GWA studies have relied on single-marker approaches that identify single genetic factors individually and have limitations in considering the joint effects of multiple genetic factors on complex traits. Joint identification of multiple genetic factors would be more powerful and provide a better prediction of complex traits, since it utilizes combined information across variants. Recently, a new statistical method for joint identification of genetic variants for common complex traits via the elastic-net regularization method was proposed. In this study, we applied this joint identification approach to a large-scale GWA dataset (i.e., 8842 samples and 327,872 SNPs) in order to identify genetic variants of obesity for the Korean population. In addition, in order to test for the biological significance of the jointly identified SNPs, gene ontology and pathway enrichment analyses were further conducted.