Literature DB >> 27081555

iJGVD: an integrative Japanese genome variation database based on whole-genome sequencing.

Yumi Yamaguchi-Kabata1, Naoki Nariai2, Yosuke Kawai1, Yukuto Sato1, Kaname Kojima3, Minoru Tateno2, Fumiki Katsuoka1, Jun Yasuda1, Masayuki Yamamoto1, Masao Nagasaki4.   

Abstract

The integrative Japanese Genome Variation Database (iJGVD; http://ijgvd.megabank.tohoku.ac.jp/) provides genomic variation data detected by whole-genome sequencing (WGS) of Japanese individuals. Specifically, the database contains variants detected by WGS of 1,070 individuals who participated in a genome cohort study of the Tohoku Medical Megabank Project. In the first release, iJGVD includes >4,300,000 autosomal single nucleotide variants (SNVs) whose minor allele frequencies are >5.0%.

Entities:  

Year:  2015        PMID: 27081555      PMCID: PMC4785574          DOI: 10.1038/hgv.2015.50

Source DB:  PubMed          Journal:  Hum Genome Var        ISSN: 2054-345X


Since the completion of the Human Genome Project,[1] many studies have focused on the detection and characterization of genomic variants.[2-4] In Japan, a gene-based single nucleotide polymorphism (SNP) discovery project as part of the Japanese Millennium Genome Project reported >190,000 variants and catalogued the SNPs in the JSNP database.[5,6] This catalogue of high-quality SNPs was the foundation that led to the early success of genome-wide association studies in Japan.[7] The International HapMap Project[8-10] has produced genome-wide SNP genotype data for major ethnic groups including the Japanese population, and these data have facilitated genome-wide association studies. Although reports of common variants and their frequencies are accumulating for various populations, it is difficult to avoid ascertainment biases (e.g., well-known SNPs or tag SNPs are disproportionately examined). Many low-frequency variants remain undetected or have unknown frequencies. A catalogue of genomic variants from WGS and estimates of variant frequencies for each population are needed to provide a foundation for genomic medicine. The 1000 Genomes Project (1KGP)[11] involved low-coverage WGS and high-coverage exome sequencing for >1,000 individuals, including 89 Japanese samples, and the data is widely used for genotype imputation. However, the sample sizes for individual populations are insufficient to obtain reliable allele frequencies. Therefore, high-coverage WGS of a larger number of individuals for a target population is desired to construct a variant catalogue with reliable allele frequencies, including rare variants. To make a reference panel of genomic variation for the Japanese population, we sequenced whole genomes of 1,070 cohort participants, and detected genomic variants including SNVs, indels and structural variants.[12] This variant set formed a reference panel for the Japanese population, which we refer to as ‘1KJPN.’ We released the comprehensive catalogue of SNV frequencies for alleles whose frequencies are >5% among the 1,070 individuals. The current release of iJGVD provides allele frequency data for 4,301,546 autosomal SNVs. The set of variants in iJGVD was released from 1KJPN, which was constructed with data from the WGS of 1,070 healthy Japanese individuals in the Tohoku Medical Megabank Project.[12] The 1KJPN subjects were adult individuals (age ⩾20 years) whose Japanese ancestry was confirmed, and close-relatives were excluded (see Supplementary Figure 1 for statistics regarding age and sex). All participants gave written informed consent. In this project, the genomic DNA of 1,070 subjects obtained from peripheral blood samples was subjected to paired-end sequencing using the Illumina HiSeq 2500 platform. All sequencing libraries were constructed based on PCR-free methods.[13] The sequence reads were mapped onto the human reference genome, assembly GRCh37/hg19, with decoy sequences (hs37d5) and an average sequencing coverage of 32.4× for full-length autosomal chromosomes. Variant calling and subsequent filtering were performed by an in-house bioinformatics pipeline.[14,15] The details of methods and quality controls are described in Nagasaki et al.[12] Among the total variants in 1KJPN, autosomal SNVs whose minor allele frequencies were >5% were selected. These SNVs were annotated with their corresponding database SNP (dbSNP) IDs and their effects on gene products were predicted using SnpEff[16]. SNVs were selected if the variants were reported in dbSNP138[3], and the iJGVD release (Version 1.0) included a final sample size of 4,301,546 SNVs. The iJGVD system consists of (i) the relational database and (ii) the web server (Figure 1a). The relational database (using MySQL 5.1.73) for iJGVD includes SNV alleles, genomic positions based on the GRCh37/hg19 coordinates, allele frequencies, the corresponding dbSNP IDs, P values for the Hardy–Weinberg equilibrium test, gene annotations and so on. The web server consists of functions to search SNVs and explore the region surrounding an SNV based on chromosome coordinates. The web server and exploration functions were implemented in PHP 5.3.3 and JBrowse 1.11.5, respectively.
Figure 1

Schema of the systems and graphical user interfaces of iJGVD. (a) Schematic diagram of the iJGVD systems. (b–d) Graphical user interfaces for iJGVD. (b) SNV searches are initiated at the top page by specifying a gene, dbSNP ID, or genomic region. (c) SNV allele frequencies are displayed in a table, and rs671 is shown as an example. (d) A graphical view of the SNV location in the genome browser. iJGVD, integrative Japanese Genome Variation Database ; dbSNP, database single nucleotide polymorphism; SNV, single nucleotide variant.

Among the 4,301,546 SNVs, 1.72% were located in exonic regions (i.e., untranslated regions or coding regions). The minor allele frequency distribution for the SNVs in iJGVD was examined (Table 1). The SNV counts for each frequency class were not uniform, and the sample was enriched for low-frequency SNVs.
Table 1

Number of SNVs in iJGVD by frequency class and functional category

Functional category Frequency class
0.05–0.100.10–0.150.15–0.200.20–0.250.25–0.300.30–0.350.35–0.400.40–0.450.45–0.50
Nonsynonymous3,1142,1131,7261,3931,2481,1811,1701,089995
Synonymous3,2282,1691,8171,5651,4501,4581,3331,2661,268
5′ UTR1,9801,3101,208939866849856831745
3′ UTR7,2154,9584,1353,5553,1283,1852,9232,9482,906
Splice donor site25106459786
Splice acceptor site81171135568
Intron307,422219,990187,246163,319152,763143,780136,719131,543129,083
Others499,044366,535313,854283,193255,771245,457234,201229,951225,074
Total822,036597,096509,999453,979415,234395,924377,214367,642360,085

Abbreviations: iJGVD, integrative Japanese Genome Variation Database ; SNVs, single nucleotide variants; UTR, untranslated region.

We compared the allele frequencies of SNVs in iJGVD with those of SNVs in HapMap3[10] JPT (Japanese from Tokyo) individuals (Figure 2a). The allele frequencies in the two populations were very similar (the correlation coefficient was 0.99). We also tested statistical difference in allele counts between ToMMo 1KJPN and HapMap3 JPT, and found that only a small fraction (0.022%, 226 out of 1,020,909) of SNVs showed P values of <10−8 (see Supplementary Figure 2 for QQ-plots). This fraction of SNVs with small P values was very similar with that for the comparison between NGS data and SNP array data in the JPT population (Figure 2b).
Figure 2

Comparison of SNV allele frequencies in ToMMo 1KJPN with those of HapMap JPT. (a) Non-reference SNV allele frequencies in ToMMo 1KJPN (y axis) are shown with those in HapMap3 JPT individuals (n=86; x axis) for 1,020,909 overlapping SNVs in a two-dimensional scatter plot. (b) Non-reference SNV allele frequencies in 1KGP JPT individuals (n=89) by whole-genome sequencing (y axis) are plotted against those in HapMap3 JPT individuals (n=86; x axis) for 1,061,165 autosomal SNVs. JPT, Japanese from Tokyo; SNV, single nucleotide variant.

SNVs in iJGVD can be searched by specifying the gene symbol, rsSNP ID, or genomic position (Figures 1b and c). Hits are displayed in a table of SNVs with allele frequencies in sequential order based on their genomic coordinates. The table can be downloaded as a text file by clicking ‘Download Table.’ SNVs can also be queried using the genome browser by specifying the chromosome and genomic position. The genome browser (Figure 1d) provides graphical views of the genomic location of SNVs with locations of known genes and other SNVs in dbSNP. We constructed a public database of genomic variants with allele frequencies for the Japanese population. Variant databases for the Japanese population to date have been based on targeted SNP typing[6] or whole-exome sequencing.[17] iJGVD is the first database of genomic variants for Japanese individuals based on high-coverage WGS. A set of variants and the corresponding frequency information from WGS would provide a comprehensive platform for finding disease-causing variants because they can be found in non-coding regions. The allele frequencies of SNVs in iJGVD and in the HapMap3 JPT population are highly correlated (Figure 2b). Furthermore, our database contains allele frequencies for more than three million additional high-quality SNVs that were not genotyped in the HapMap3 project. We recently designed a genotyping chip, ‘Japonica Array’, which was optimized for the Japanese population,[18] and probes for autosomal SNPs on Japonica Array can be seen in iJGVD. We plan to improve the usefulness of iJGVD by adding biological annotations for SNVs and expanding search options using these annotations. Furthermore, information of linkage disequilibrium will be considered for additional data. Although iJGVD contains only SNV information at present, insertions, deletions and other structural variants will be included after quality control processes are implemented. We believe that our open variant data will be useful in medical genomics, especially for comparisons of allele frequencies in iJGVD with those of the patient group for a target disease to identify disease-causing variants. All SNV frequency data in iJGVD are available from the National Bioscience Database Center Human Database (http://humandbs.biosciencedbc.jp/) under accession hum0015.
  17 in total

1.  Patterns of single-nucleotide polymorphisms in candidate genes for blood-pressure homeostasis.

Authors:  M K Halushka; J B Fan; K Bentley; L Hsie; N Shen; A Weder; R Cooper; R Lipshutz; A Chakravarti
Journal:  Nat Genet       Date:  1999-07       Impact factor: 38.330

2.  JSNP: a database of common gene variations in the Japanese population.

Authors:  Mika Hirakawa; Toshihiro Tanaka; Yoichi Hashimoto; Masako Kuroda; Toshihisa Takagi; Yusuke Nakamura
Journal:  Nucleic Acids Res       Date:  2002-01-01       Impact factor: 16.971

3.  Gene-based SNP discovery as part of the Japanese Millennium Genome Project: identification of 190,562 genetic variations in the human genome. Single-nucleotide polymorphism.

Authors:  Hisanori Haga; Ryo Yamada; Yozo Ohnishi; Yusuke Nakamura; Toshihiro Tanaka
Journal:  J Hum Genet       Date:  2002       Impact factor: 3.172

4.  A haplotype map of the human genome.

Authors: 
Journal:  Nature       Date:  2005-10-27       Impact factor: 49.962

5.  Whole-genome patterns of common DNA variation in three human populations.

Authors:  David A Hinds; Laura L Stuve; Geoffrey B Nilsen; Eran Halperin; Eleazar Eskin; Dennis G Ballinger; Kelly A Frazer; David R Cox
Journal:  Science       Date:  2005-02-18       Impact factor: 47.728

6.  An efficient quantitation method of next-generation sequencing libraries by using MiSeq sequencer.

Authors:  Fumiki Katsuoka; Junji Yokozawa; Kaoru Tsuda; Shin Ito; Xiaoqing Pan; Masao Nagasaki; Jun Yasuda; Masayuki Yamamoto
Journal:  Anal Biochem       Date:  2014-08-28       Impact factor: 3.365

7.  Integrating common and rare genetic variation in diverse human populations.

Authors:  David M Altshuler; Richard A Gibbs; Leena Peltonen; David M Altshuler; Richard A Gibbs; Leena Peltonen; Emmanouil Dermitzakis; Stephen F Schaffner; Fuli Yu; Leena Peltonen; Emmanouil Dermitzakis; Penelope E Bonnen; David M Altshuler; Richard A Gibbs; Paul I W de Bakker; Panos Deloukas; Stacey B Gabriel; Rhian Gwilliam; Sarah Hunt; Michael Inouye; Xiaoming Jia; Aarno Palotie; Melissa Parkin; Pamela Whittaker; Fuli Yu; Kyle Chang; Alicia Hawes; Lora R Lewis; Yanru Ren; David Wheeler; Richard A Gibbs; Donna Marie Muzny; Chris Barnes; Katayoon Darvishi; Matthew Hurles; Joshua M Korn; Kati Kristiansson; Charles Lee; Steven A McCarrol; James Nemesh; Emmanouil Dermitzakis; Alon Keinan; Stephen B Montgomery; Samuela Pollack; Alkes L Price; Nicole Soranzo; Penelope E Bonnen; Richard A Gibbs; Claudia Gonzaga-Jauregui; Alon Keinan; Alkes L Price; Fuli Yu; Verneri Anttila; Wendy Brodeur; Mark J Daly; Stephen Leslie; Gil McVean; Loukas Moutsianas; Huy Nguyen; Stephen F Schaffner; Qingrun Zhang; Mohammed J R Ghori; Ralph McGinnis; William McLaren; Samuela Pollack; Alkes L Price; Stephen F Schaffner; Fumihiko Takeuchi; Sharon R Grossman; Ilya Shlyakhter; Elizabeth B Hostetter; Pardis C Sabeti; Clement A Adebamowo; Morris W Foster; Deborah R Gordon; Julio Licinio; Maria Cristina Manca; Patricia A Marshall; Ichiro Matsuda; Duncan Ngare; Vivian Ota Wang; Deepa Reddy; Charles N Rotimi; Charmaine D Royal; Richard R Sharp; Changqing Zeng; Lisa D Brooks; Jean E McEwen
Journal:  Nature       Date:  2010-09-02       Impact factor: 49.962

8.  Functional SNPs in the lymphotoxin-alpha gene that are associated with susceptibility to myocardial infarction.

Authors:  Kouichi Ozaki; Yozo Ohnishi; Aritoshi Iida; Akihiko Sekine; Ryo Yamada; Tatsuhiko Tsunoda; Hiroshi Sato; Hideyuki Sato; Masatsugu Hori; Yusuke Nakamura; Toshihiro Tanaka
Journal:  Nat Genet       Date:  2002-11-11       Impact factor: 38.330

9.  A second generation human haplotype map of over 3.1 million SNPs.

Authors:  Kelly A Frazer; Dennis G Ballinger; David R Cox; David A Hinds; Laura L Stuve; Richard A Gibbs; John W Belmont; Andrew Boudreau; Paul Hardenbol; Suzanne M Leal; Shiran Pasternak; David A Wheeler; Thomas D Willis; Fuli Yu; Huanming Yang; Changqing Zeng; Yang Gao; Haoran Hu; Weitao Hu; Chaohua Li; Wei Lin; Siqi Liu; Hao Pan; Xiaoli Tang; Jian Wang; Wei Wang; Jun Yu; Bo Zhang; Qingrun Zhang; Hongbin Zhao; Hui Zhao; Jun Zhou; Stacey B Gabriel; Rachel Barry; Brendan Blumenstiel; Amy Camargo; Matthew Defelice; Maura Faggart; Mary Goyette; Supriya Gupta; Jamie Moore; Huy Nguyen; Robert C Onofrio; Melissa Parkin; Jessica Roy; Erich Stahl; Ellen Winchester; Liuda Ziaugra; David Altshuler; Yan Shen; Zhijian Yao; Wei Huang; Xun Chu; Yungang He; Li Jin; Yangfan Liu; Yayun Shen; Weiwei Sun; Haifeng Wang; Yi Wang; Ying Wang; Xiaoyan Xiong; Liang Xu; Mary M Y Waye; Stephen K W Tsui; Hong Xue; J Tze-Fei Wong; Luana M Galver; Jian-Bing Fan; Kevin Gunderson; Sarah S Murray; Arnold R Oliphant; Mark S Chee; Alexandre Montpetit; Fanny Chagnon; Vincent Ferretti; Martin Leboeuf; Jean-François Olivier; Michael S Phillips; Stéphanie Roumy; Clémentine Sallée; Andrei Verner; Thomas J Hudson; Pui-Yan Kwok; Dongmei Cai; Daniel C Koboldt; Raymond D Miller; Ludmila Pawlikowska; Patricia Taillon-Miller; Ming Xiao; Lap-Chee Tsui; William Mak; You Qiang Song; Paul K H Tam; Yusuke Nakamura; Takahisa Kawaguchi; Takuya Kitamoto; Takashi Morizono; Atsushi Nagashima; Yozo Ohnishi; Akihiro Sekine; Toshihiro Tanaka; Tatsuhiko Tsunoda; Panos Deloukas; Christine P Bird; Marcos Delgado; Emmanouil T Dermitzakis; Rhian Gwilliam; Sarah Hunt; Jonathan Morrison; Don Powell; Barbara E Stranger; Pamela Whittaker; David R Bentley; Mark J Daly; Paul I W de Bakker; Jeff Barrett; Yves R Chretien; Julian Maller; Steve McCarroll; Nick Patterson; Itsik Pe'er; Alkes Price; Shaun Purcell; Daniel J Richter; Pardis Sabeti; Richa Saxena; Stephen F Schaffner; Pak C Sham; Patrick Varilly; David Altshuler; Lincoln D Stein; Lalitha Krishnan; Albert Vernon Smith; Marcela K Tello-Ruiz; Gudmundur A Thorisson; Aravinda Chakravarti; Peter E Chen; David J Cutler; Carl S Kashuk; Shin Lin; Gonçalo R Abecasis; Weihua Guan; Yun Li; Heather M Munro; Zhaohui Steve Qin; Daryl J Thomas; Gilean McVean; Adam Auton; Leonardo Bottolo; Niall Cardin; Susana Eyheramendy; Colin Freeman; Jonathan Marchini; Simon Myers; Chris Spencer; Matthew Stephens; Peter Donnelly; Lon R Cardon; Geraldine Clarke; David M Evans; Andrew P Morris; Bruce S Weir; Tatsuhiko Tsunoda; James C Mullikin; Stephen T Sherry; Michael Feolo; Andrew Skol; Houcan Zhang; Changqing Zeng; Hui Zhao; Ichiro Matsuda; Yoshimitsu Fukushima; Darryl R Macer; Eiko Suda; Charles N Rotimi; Clement A Adebamowo; Ike Ajayi; Toyin Aniagwu; Patricia A Marshall; Chibuzor Nkwodimmah; Charmaine D M Royal; Mark F Leppert; Missy Dixon; Andy Peiffer; Renzong Qiu; Alastair Kent; Kazuto Kato; Norio Niikawa; Isaac F Adewole; Bartha M Knoppers; Morris W Foster; Ellen Wright Clayton; Jessica Watkin; Richard A Gibbs; John W Belmont; Donna Muzny; Lynne Nazareth; Erica Sodergren; George M Weinstock; David A Wheeler; Imtaz Yakub; Stacey B Gabriel; Robert C Onofrio; Daniel J Richter; Liuda Ziaugra; Bruce W Birren; Mark J Daly; David Altshuler; Richard K Wilson; Lucinda L Fulton; Jane Rogers; John Burton; Nigel P Carter; Christopher M Clee; Mark Griffiths; Matthew C Jones; Kirsten McLay; Robert W Plumb; Mark T Ross; Sarah K Sims; David L Willey; Zhu Chen; Hua Han; Le Kang; Martin Godbout; John C Wallenburg; Paul L'Archevêque; Guy Bellemare; Koji Saeki; Hongguang Wang; Daochang An; Hongbo Fu; Qing Li; Zhen Wang; Renwu Wang; Arthur L Holden; Lisa D Brooks; Jean E McEwen; Mark S Guyer; Vivian Ota Wang; Jane L Peterson; Michael Shi; Jack Spiegel; Lawrence M Sung; Lynn F Zacharia; Francis S Collins; Karen Kennedy; Ruth Jamieson; John Stewart
Journal:  Nature       Date:  2007-10-18       Impact factor: 49.962

10.  An integrated map of genetic variation from 1,092 human genomes.

Authors:  Goncalo R Abecasis; Adam Auton; Lisa D Brooks; Mark A DePristo; Richard M Durbin; Robert E Handsaker; Hyun Min Kang; Gabor T Marth; Gil A McVean
Journal:  Nature       Date:  2012-11-01       Impact factor: 49.962

View more
  48 in total

1.  A 12-kb structural variation in progressive myoclonic epilepsy was newly identified by long-read whole-genome sequencing.

Authors:  Takeshi Mizuguchi; Takeshi Suzuki; Chihiro Abe; Ayako Umemura; Katsushi Tokunaga; Yosuke Kawai; Minoru Nakamura; Masao Nagasaki; Kengo Kinoshita; Yasunobu Okamura; Satoko Miyatake; Noriko Miyake; Naomichi Matsumoto
Journal:  J Hum Genet       Date:  2019-02-13       Impact factor: 3.172

2.  Evaluation of reported pathogenic variants and their frequencies in a Japanese population based on a whole-genome reference panel of 2049 individuals.

Authors:  Yumi Yamaguchi-Kabata; Jun Yasuda; Osamu Tanabe; Yoichi Suzuki; Hiroshi Kawame; Nobuo Fuse; Masao Nagasaki; Yosuke Kawai; Kaname Kojima; Fumiki Katsuoka; Sakae Saito; Inaho Danjoh; Ikuko N Motoike; Riu Yamashita; Seizo Koshiba; Daisuke Saigusa; Gen Tamiya; Shigeo Kure; Nobuo Yaegashi; Yoshio Kawaguchi; Fuji Nagami; Shinichi Kuriyama; Junichi Sugawara; Naoko Minegishi; Atsushi Hozawa; Soichi Ogishima; Hideyasu Kiyomoto; Takako Takai-Igarashi; Kengo Kinoshita; Masayuki Yamamoto
Journal:  J Hum Genet       Date:  2017-12-01       Impact factor: 3.172

3.  HPRT-related hyperuricemia with a novel p.V35M mutation in HPRT1 presenting familial juvenile gout.

Authors:  Eikan Mishima; Takayasu Mori; Yoko Nakajima; Takafumi Toyohara; Koichi Kikuchi; Yoshitsugu Oikawa; Tetsuro Matsuhashi; Yasuhiro Maeda; Takehiro Suzuki; Masataka Kudo; Sadayoshi Ito; Eisei Sohara; Shinichi Uchida; Takaaki Abe
Journal:  CEN Case Rep       Date:  2020-03-03

4.  Rho Guanine Nucleotide Exchange Factor ARHGEF17 Is a Risk Gene for Intracranial Aneurysms.

Authors:  Xinyu Yang; Jiani Li; Yabo Fang; Zhen Zhang; Daqing Jin; Xingdong Chen; Yan Zhao; Mengqi Li; Linchun Huan; Thomas A Kent; Jing-Fei Dong; Rongcai Jiang; Shuyuan Yang; Li Jin; Jianning Zhang; Tao P Zhong; Fuli Yu
Journal:  Circ Genom Precis Med       Date:  2018-07

5.  Distribution of genetic alterations in high-risk early-stage cervical cancer patients treated with postoperative radiation therapy.

Authors:  Naoya Murakami; Yuka Asami; Hiroshi Yoshida; Daisuke Takayanagi; Sou Hirose; Ikumi Kuno; Kazuaki Takahashi; Maiko Matsuda; Yoko Shimada; Shotaro Yamano; Kuniko Sunami; Takayuki Honda; Tomomi Nakahara; Tomoko Watanabe; Kae Okuma; Takafumi Kuroda; Takashi Kohno; Tomoyasu Kato; Kouya Shiraishi; Jun Itami
Journal:  Sci Rep       Date:  2021-05-19       Impact factor: 4.379

6.  Genomic analysis of familial pancreatic cancers and intraductal papillary mucinous neoplasms: A cross-sectional study.

Authors:  Kodai Abe; Minoru Kitago; Kenjiro Kosaki; Mamiko Yamada; Eisuke Iwasaki; Shintaro Kawasaki; Keijiro Mizukami; Yukihide Momozawa; Chikashi Terao; Hiroshi Yagi; Yuta Abe; Yasushi Hasegawa; Shutaro Hori; Masayuki Tanaka; Yutaka Nakano; Yuko Kitagawa
Journal:  Cancer Sci       Date:  2022-03-09       Impact factor: 6.518

7.  A novel COL11A1 missense mutation in siblings with non-ocular Stickler syndrome.

Authors:  Tomohiro Kohmoto; Atsumi Tsuji; Kei-Ichi Morita; Takuya Naruto; Kiyoshi Masuda; Kenichi Kashimada; Keisuke Enomoto; Tomohiro Morio; Hiroyuki Harada; Issei Imoto
Journal:  Hum Genome Var       Date:  2016-04-07

8.  A missense variant in PER2 is associated with delayed sleep-wake phase disorder in a Japanese population.

Authors:  Taku Miyagawa; Akiko Hida; Mihoko Shimada; Chihiro Uehara; Yuri Nishino; Hiroshi Kadotani; Makoto Uchiyama; Takashi Ebisawa; Yuichi Inoue; Yuichi Kamei; Katsushi Tokunaga; Kazuo Mishima; Makoto Honda
Journal:  J Hum Genet       Date:  2019-09-17       Impact factor: 3.172

Review 9.  Thiopurine pharmacogenomics and pregnancy in inflammatory bowel disease.

Authors:  Akira Andoh; Masahiro Kawahara; Takayuki Imai; Goichi Tatsumi; Osamu Inatomi; Yoichi Kakuta
Journal:  J Gastroenterol       Date:  2021-07-21       Impact factor: 7.527

10.  A novel missense mutation of COL5A2 in a patient with Ehlers-Danlos syndrome.

Authors:  Miki Watanabe; Ryuji Nakagawa; Takuya Naruto; Tomohiro Kohmoto; Ken-Ichi Suga; Aya Goji; Shoji Kagami; Kiyoshi Masuda; Issei Imoto
Journal:  Hum Genome Var       Date:  2016-09-15
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.