A High-Performance Database Management System for Managing and Analyzing Large-Scale SNP Data in Plant Genotyping and Breeding Applications

被引:2
|
作者
Zhao, Yikun [1 ]
Jiang, Bin [1 ]
Huo, Yongxue [1 ]
Yi, Hongmei [1 ]
Tian, Hongli [1 ]
Wu, Haotian [1 ]
Wang, Rui [1 ]
Zhao, Jiuran [1 ]
Wang, Fengge [1 ]
机构
[1] Beijing Acad Agr & Forest Sci BAAFS, Maize Res Ctr, Beijing Key Lab Maize DNA Fingerprinting & Mol Br, Beijing 100097, Peoples R China
来源
AGRICULTURE-BASEL | 2021年 / 11卷 / 11期
基金
国家重点研发计划;
关键词
SNP; SNP array; KASP; database; DNA fingerprint; algorithms; genotyping; DNA; DIVERSITY; SEQUENCE; BARCODE;
D O I
10.3390/agriculture11111027
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
A DNA fingerprint database is an efficient, stable, and automated tool for plant molecular research that can provide comprehensive technical support for multiple fields of study, such as pan-genome analysis and crop breeding. However, constructing a DNA fingerprint database for plants requires significant resources for data output, storage, analysis, and quality control. Large amounts of heterogeneous data must be processed efficiently and accurately. Thus, we developed plant SNP database management system (PSNPdms) using an open-source web server and free software that is compatible with single nucleotide polymorphism (SNP), insertion-deletion (InDel) markers, Kompetitive Allele Specific PCR (KASP), SNP array platforms, and 23 species. It fully integrates with the KASP platform and allows for graphical presentation and modification of KASP data. The system has a simple, efficient, and versatile laboratory personnel management structure that adapts to complex and changing experimental needs with a simple workflow process. PSNPdms internally provides effective support for data quality control through multiple dimensions, such as the standardized experimental design, standard reference samples, fingerprint statistical selection algorithm, and raw data correlation queries. In addition, we developed a fingerprint-merging algorithm to solve the problem of merging fingerprints of mixed samples and single samples in plant detection, providing unique standard fingerprints of each plant species for construction of a standard DNA fingerprint database. Different laboratories can use the system to generate fingerprint packages for data interaction and sharing. In addition, we integrated genetic analysis into the system to enable drawing and downloading of dendrograms. PSNPdms has been widely used by 23 institutions and has proven to be a stable and effective system for sharing data and performing genetic analysis. Interested researchers are required to adapt and further develop the system.
引用
收藏
页数:21
相关论文
共 50 条
  • [31] Guest Editorial: Large-scale Data Management for Mobile Applications
    Thierry Delot
    Sandra Geisler
    Sergio Ilarri
    Christoph Quix
    Distributed and Parallel Databases, 2016, 34 : 1 - 2
  • [32] Guest Editorial: Large-scale Data Management for Mobile Applications
    Delot, Thierry
    Geisler, Sandra
    Ilarri, Sergio
    Quix, Christoph
    DISTRIBUTED AND PARALLEL DATABASES, 2016, 34 (01) : 1 - 2
  • [33] A Bioinspired, Reusable, Paper-Based System for High-Performance Large-Scale Evaporation
    Liu, Yanming
    Yu, Shengtao
    Feng, Rui
    Bernard, Antoine
    Liu, Yang
    Zhang, Yao
    Duan, Haoze
    Shang, Wen
    Tao, Peng
    Song, Chengyi
    Deng, Tao
    ADVANCED MATERIALS, 2015, 27 (17) : 2768 - +
  • [34] A high-performance distributed file system for large-scale concurrent HD video streams
    Duan, Hancong
    Zhan, Wenhan
    Min, Geyong
    Guo, Hui
    Luo, Shengmei
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2015, 27 (13): : 3510 - 3522
  • [35] High-performance Negative Database for Massive Data Management System of The Mingantu Spectral Radioheliograph
    Shi, Congming
    Wang, Feng
    Deng, Hui
    Liu, Yingbo
    Liu, Cuiyin
    Wei, Shoulin
    PUBLICATIONS OF THE ASTRONOMICAL SOCIETY OF THE PACIFIC, 2017, 129 (978)
  • [36] LARGE-SCALE HIGH-PERFORMANCE VIBRATION TABLE FACILITIES AT NUPEC
    OHMORI, T
    OHNO, T
    KUSU, Y
    JOURNAL OF THE ATOMIC ENERGY SOCIETY OF JAPAN, 1983, 25 (02): : 92 - 96
  • [37] High-performance computing for large-scale analysis, optimization, and control
    Adeli, Hojjat, 1600, ASCE, Reston, VA, United States (13):
  • [38] A large-scale study of failures in high-performance computing systems
    Schroeder, Bianca
    Gibson, Garth A.
    DSN 2006 INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS, PROCEEDINGS, 2006, : 249 - 258
  • [39] A High-Performance Accelerator for Large-Scale Convolutional Neural Networks
    Sun, Fan
    Wang, Chao
    Gong, Lei
    Xu, Chongchong
    Zhang, Yiwei
    Lu, Yuntao
    Li, Xi
    Zhou, Xuehai
    2017 15TH IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED PROCESSING WITH APPLICATIONS AND 2017 16TH IEEE INTERNATIONAL CONFERENCE ON UBIQUITOUS COMPUTING AND COMMUNICATIONS (ISPA/IUCC 2017), 2017, : 622 - 629
  • [40] High-Performance Large-Scale Image Recognition Without Normalization
    Brock, Andrew
    De, Soham
    Smith, Samuel L.
    Simonyan, Karen
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139, 2021, 139