Structure-based inference of molecular functions of proteins of unknown function from Berkeley Structural Genomics Center

Shin, Dong Hae,Hou, Jingtong,Chandonia, John-Marc,Das, Debanu,Choi, In-Geol,Kim, Rosalind,Kim, Sung-Hou 이화여자대학교 약학연구소 2008 藥學硏究論文集 Vol.- No.18

Advances in sequence genomics have resulted in an accumulation of a huge number of protein sequences derived from genome sequences. However, the functions of a large portion of them cannot be inferred based on the current methods of sequence homology detection to proteins of known functions. Three-dimensional structure can have an important impact in providing inference of molecular function (physical and chemical function) of a protein of unknown function. Structural genomics centers worldwide have been determining many 3-D structures of the proteins of unknown functions, and possible molecular functions of them have been inferred based on their structures. Combined with bioinformatics and enzymatic assay tools, the successful acceleration of the process of protein structure determination through high throughput pipelines enables the rapid functional annotation of a large fraction of hypothetical proteins. We present a brief summary of the process we used at the Berkeley Structural Genomics Center to infer molecular functions of proteins of unknown function.

Structural Analysis of Hypothetical Proteins from <i>Helicobacter pylori</i> : An Approach to Estimate Functions of Unknown or Hypothetical Proteins

Park, Sung Jean,Son, Woo Sung,Lee, Bong-Jin Molecular Diversity Preservation International (MD 2012 INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES Vol.13 No.6

<P><I>Helicobacter pylori</I> (<I>H. pylori</I>) have a unique ability to survive in extreme acidic environments and to colonize the gastric mucosa. It can cause diverse gastric diseases such as peptic ulcers, chronic gastritis, mucosa-associated lymphoid tissue (MALT) lymphoma, gastric cancer, <I>etc</I>. Based on genomic research of <I>H. pylori</I>, over 1600 genes have been functionally identified so far. However, <I>H. pylori</I> possess some genes that are uncharacterized since: (i) the gene sequences are quite new; (ii) the function of genes have not been characterized in any other bacterial systems; and (iii) sometimes, the protein that is classified into a known protein based on the sequence homology shows some functional ambiguity, which raises questions about the function of the protein produced in <I>H. pylori</I>. Thus, there are still a lot of genes to be biologically or biochemically characterized to understand the whole picture of gene functions in the bacteria. In this regard, knowledge on the 3D structure of a protein, especially unknown or hypothetical protein, is frequently useful to elucidate the structure-function relationship of the uncharacterized gene product. That is, a structural comparison with known proteins provides valuable information to help predict the cellular functions of hypothetical proteins. Here, we show the 3D structures of some hypothetical proteins determined by NMR spectroscopy and X-ray crystallography as a part of the structural genomics of <I>H. pylori</I>. In addition, we show some successful approaches of elucidating the function of unknown proteins based on their structural information.</P>

Beamline Automation of RIKEN Structural Genomics Beamlines

Ida, Koh,Yamamoto, Masaki,Kumasaka, Takashi,Ueno, Go,Kanda, Hiroyuki,Miyano, Masashi,Ishikawa, Tetsuya Korean Society of Photoscience 2002 Journal of Photosciences Vol.9 No.2

RIKEN Structural Genomics Beamlines have been constructed for the crystallographic analysis in the structural genomics research at synchrotron radiation facility SPring-8. Synchrotron radiation accelerates the crystallographic analysis of protein structure. The target of the research and development is focused on the automatic beamline operation to maximize beamline efficiency. We are developing the sample management system, which is composed of the sample auto-changer and the database system, for high-throughput data collection. The sample management system and the beamline operating system make it possible to execute automatic data collection without any operators. The beamlines will be ready for user operation in autumn 2002. The concept of automatic beamline operation and the present status of RIKEN Structural Genomics Beamlines will be presented.

A comparative, BAC end sequence enabled map of the genome of the American mink (Neovison vison)

Bernhard F. Benkel,Amanda Smith,Knud Christensen,Razvan Anistoroaei,Ye Zhang,Christoph W. Sensen,Hossain Farid,Lyn Paterson,Ronald M. Teather 한국유전학회 2012 Genes & Genomics Vol.34 No.1

In this report we present the results of the analysis of approximately 2.7 Mb of genomic information for the American mink (Neovison vison) derived through BAC end sequencing. Our study, which encompasses approximately 1/1000th of the mink genome, suggests that simple sequence repeats (SSRs) are less common in the mink than in the human genome, whereas the average GC content of the mink genome is slightly higher than that of its human counterpart. The 2.7 Mb mink genomic dataset also contained 2,416 repeat elements (retroids and DNA transposons) occupying almost 31% of the sequence space. Among repeat elements, LINEs were over-represented and endogenous viruses (aka LTRs) under-represented in comparison to the human genome. Finally, we present a virtual map of the mink genome constructed with reference to the human and canine genome assemblies using a comparative genomics approach and incorporating over 200 mink BESs with unique hits to the human genome.

Detection of genome-wide structural variations in the Shanghai Holstein cattle population using next-generation sequencing

Dengying Liu,Zhenliang Chen,Zhe Zhang,Hao Sun,Peipei Ma,Kai Zhu,Guanglei Liu,Qishan Wang,Yuchun Pan 아세아·태평양축산학회 2019 Animal Bioscience Vol.32 No.3

Objective: The Shanghai Holstein cattle breed is susceptible to severe mastitis and other diseases due to the hot weather and long-term humidity in Shanghai, which is the main distribution centre for providing Holstein semen to various farms throughout China. Our objective was to determine the genetic mechanisms influencing economically important traits, especially diseases that have huge impact on the yield and quality of milk as well as reproduction. Methods: In our study, we detected the structural variations of 1,092 Shanghai Holstein cows by using next-generation sequencing. We used the DELLY software to identify deletions and insertions, cn.MOPS to identify copy-number variants (CNVs). Furthermore, we annotated these structural variations using different bioinformatics tools, such as gene ontology, cattle quantitative trait locus (QTL) database and ingenuity pathway analysis (IPA). Results: The average number of high-quality reads was 3,046,279. After filtering, a total of 16,831 deletions, 12,735 insertions and 490 CNVs were identified. The annotation results showed that these mapped genes were significantly enriched for specific biological functions, such as disease and reproduction. In addition, the enrichment results based on the cattle QTL database showed that the number of variants related to milk and reproduction was higher than the number of variants related to other traits. IPA core analysis found that the structural variations were related to reproduction, lipid metabolism, and inflammation. According to the functional analysis, structural variations were important factors affecting the variation of different traits in Shanghai Holstein cattle. Our results provide meaningful information about structural variations, which may be useful in future assessments of the associations between variations and important phenotypes in Shanghai Holstein cattle. Conclusion: Structural variations identified in this study were extremely different from those of previous studies. Many structural variations were found to be associated with mastitis and reproductive system diseases; these results are in accordance with the characteristics of the environment that Shanghai Holstein cattle experience.

HisCoM-GGI: Software for Hierarchical Structural Component Analysis of Gene-Gene Interactions

Choi, Sungkyoung,Lee, Sungyoung,Park, Taesung Korea Genome Organization 2018 Genomics & informatics Vol.16 No.4

Gene-gene interaction (GGI) analysis is known to play an important role in explaining missing heritability. Many previous studies have already proposed software to analyze GGI, but most methods focus on a binary phenotype in a case-control design. In this study, we developed "Hierarchical structural CoMponent analysis of Gene-Gene Interactions" (HisCoM-GGI) software for GGI analysis with a continuous phenotype. The HisCoM-GGI method considers hierarchical structural relationships between genes and single nucleotide polymorphisms (SNPs), enabling both gene-level and SNP-level interaction analysis in a single model. Furthermore, this software accepts various types of genomic data and supports data management and multithreading to improve the efficiency of genome-wide association study data analysis. We expect that HisCoM-GGI software will provide advanced accessibility to researchers in genetic interaction studies and a more effective way to understand biological mechanisms of complex diseases.

Application of Structural Equation Models to Genome-wide Association Analysis

김지영,남궁정현,이승묵,박태성 한국유전체학회 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.

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.

HisCoM-PCA: software for hierarchical structural component analysis for pathway analysis based using principal component analysis

Jiang, Nan,Lee, Sungyoung,Park, Taesung Korea Genome Organization 2020 Genomics & informatics Vol.18 No.1

In genome-wide association studies, pathway-based analysis has been widely performed to enhance interpretation of single-nucleotide polymorphism association results. We proposed a novel method of hierarchical structural component model (HisCoM) for pathway analysis of common variants (HisCoM for pathway analysis of common variants [HisCoM-PCA]) which was used to identify pathways associated with traits. HisCoM-PCA is based on principal component analysis (PCA) for dimensional reduction of single nucleotide polymorphisms in each gene, and the HisCoM for pathway analysis. In this study, we developed a HisCoM-PCA software for the hierarchical pathway analysis of common variants. HisCoM-PCA software has several features. Various principle component scores selection criteria in PCA step can be specified by users who want to summarize common variants at each gene-level by different threshold values. In addition, multiple public pathway databases and customized pathway information can be used to perform pathway analysis. We expect that HisCoM-PCA software will be useful for users to perform powerful pathway analysis.

Dissecting the genetic structure of Korean population using genome-wide SNP arrays

김영진,진한준 한국유전학회 2013 Genes & Genomics Vol.35 No.3

Genome-wide SNP arrays have generated unprecedented quantities of data allow the detection of human evolutionary history and dense genome-wide data also enable the identification of distance ancestry among individuals or ethnic groups. To explain wider aspects of the genetic structure of Koreans and the East Asian population,we analyzed 79 individuals from the Korean HapMap project at 555,352 common single-nucleotide polymorphism loci, and compared this data with the worldwide population groups with the 53 ethnic groups from Human Genome Diversity Panel (HGDP-CEPH). Population differentiation (FST), Principal Component Analyses, STRUCTURE and ADMIXTURE are examined. In general, all the individual samples studies here were classified into subset of ethnic groups according to their geographical origins. Korean HapMap individuals were grouped together with East Asian populations from HGDP panel. Recently, a sub-population structure within Korean population has been reported. Our result, however,revealed the genetic homogeneity of Korean population. The ADMIXTURE analysis showed that, overall the Korean populations derive 79 % of their genomic ancestry from southern Asia and have relatively little northern Asian ancestry (21 %). The present work, therefore, provide the evidence that the male-biased southern-to-northern migration influenced not only for the genetic make up of the Y chromosome in the Korean population but also, its autosomal composition.