EXPLoRA-web: linkage analysis of quantitative trait loci using bulk segregant analysis

被引:8
|
作者
Pulido-Tamayo, Sergio [1 ,2 ,3 ,4 ]
Duitama, Jorge [5 ]
Marchal, Kathleen [1 ,2 ,3 ,6 ]
机构
[1] IGent Toren, Dept Informat Technol, Technol Pk 15, B-9052 Ghent, Belgium
[2] UGent, Dept Plant Biotechnol & Bioinformat, Technol Pk 927, B-9052 Ghent, Belgium
[3] Bioinformat Inst Ghent, Technol Pk 927, B-9052 Ghent, Belgium
[4] Katholieke Univ Leuven, Dept Microbial & Mol Syst, Kasteelpk Arenberg 20, B-3001 Leuven, Belgium
[5] Int Ctr Trop Agr CIAT, Agrobiodivers Res Area, Cali 763537, Colombia
[6] Univ Pretoria, Dept Genet, Hatfield Campus, ZA-0028 Pretoria, South Africa
关键词
SEQUENCING REVEALS; IDENTIFICATION; GENES;
D O I
10.1093/nar/gkw298
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Identification of genomic regions associated with a phenotype of interest is a fundamental step toward solving questions in biology and improving industrial research. Bulk segregant analysis (BSA) combined with high-throughput sequencing is a technique to efficiently identify these genomic regions associated with a trait of interest. However, distinguishing true from spuriously linked genomic regions and accurately delineating the genomic positions of these truly linked regions requires the use of complex statistical models currently implemented in software tools that are generally difficult to operate for non-expert users. To facilitate the exploration and analysis of data generated by bulked segregant analysis, we present EXPLoRA-web, a web service wrapped around our previously published algorithm EXPLoRA, which exploits linkage disequilibrium to increase the power and accuracy of quantitative trait loci identification in BSA analysis. EXPLoRA-web provides a user friendly interface that enables easy data upload and parallel processing of different parameter configurations. Results are provided graphically and as BED file and/or text file and the input is expected in widely used formats, enabling straightforward BSA data analysis. The web server is available at http://bioinformatics.intec.ugent.be/explora-web/.
引用
收藏
页码:W142 / W146
页数:5
相关论文
共 50 条
  • [31] Quantitative trait loci analysis and genome-wide comparison for silique related traits in Brassica napus
    Wang, Xiaodong
    Chen, Li
    Wang, Aina
    Wang, Hao
    Tian, Jianhua
    Zhao, Xiaoping
    Chao, Hongbo
    Zhao, Yajun
    Zhao, Weiguo
    Xiang, Jun
    Gan, Jianping
    Li, Maoteng
    BMC PLANT BIOLOGY, 2016, 16
  • [32] Characterization and bulk segregant analysis of 'moon and star' appearance in watermelon
    Liu, Dongming
    Sun, Dongling
    Liang, Jinfang
    Dou, Junling
    Yang, Sen
    Zhu, Huayu
    Hu, Jianbin
    Sun, Shouru
    Yang, Luming
    SCIENTIA HORTICULTURAE, 2021, 285
  • [33] Linkage and mapping of quantitative trait loci associated with angular leaf spot and powdery mildew resistance in common beans
    Bassi, Denis
    Brinez, Boris
    Rosa, Juliana Santa
    Oblessuc, Paula Rodrigues
    de Almeida, Caleo Panhoca
    Nucci, Stella Maris
    Domingos da Silva, Larissa Chariel
    Chiorato, Alisson Fernando
    Vianello, Rosana Pereira
    Aranha Camargo, Luis Eduardo
    Blair, Matthew Wohlgemuth
    Benchimol-Reis, Luciana Lasry
    GENETICS AND MOLECULAR BIOLOGY, 2017, 40 (01) : 109 - 122
  • [34] Construction of the First High-Density Genetic Linkage Map and Analysis of Quantitative Trait Loci for Growth-Related Traits in Sinonovacula constricta
    Niu, Donghong
    Du, Yunchao
    Wang, Ze
    Xie, Shumei
    Nguyen, Haideng
    Dong, Zhiguo
    Shen, Heding
    Li, Jiale
    MARINE BIOTECHNOLOGY, 2017, 19 (05) : 488 - 496
  • [35] Quantitative trait loci analysis for flower-related traits in almond (Prunus dulcis)
    Paizila, Aibibula
    Karci, Harun
    Motalebipour, Elmira Ziya
    Guney, Murat
    Kafkas, Salih
    PLANT BREEDING, 2022, 141 (01) : 119 - 132
  • [36] Quantitative Trait Locus Analysis of Leaf Morphology Indicates Conserved Shape Loci in Grapevine
    Demmings, Elizabeth M.
    Williams, Brigette R.
    Lee, Cheng-Ruei
    Barba, Paola
    Yang, Shanshan
    Hwang, Chin-Feng
    Reisch, Bruce I.
    Chitwood, Daniel H.
    Londo, Jason P.
    FRONTIERS IN PLANT SCIENCE, 2019, 10
  • [37] Co-localization and analysis of miR477b with fiber length quantitative trait loci in cotton
    Song, Jikun
    Liu, Guoyuan
    Jin, Changyin
    Pei, Wenfeng
    Zhang, Bingbing
    Jia, Bing
    Wu, Man
    Ma, Jianjiang
    Liu, Ji
    Zhang, Jinfa
    Yu, Jiwen
    PHYSIOLOGIA PLANTARUM, 2024, 176 (03)
  • [38] Mitochondrial genome-wide analysis of nuclear DNA methylation quantitative trait loci
    Laaksonen, Jaakko
    Mishra, Pashupati P.
    Seppala, Ilkka
    Raitoharju, Emma
    Marttila, Saara
    Mononen, Nina
    Lyytikainen, Leo-Pekka
    Kleber, Marcus E.
    Delgado, Graciela E.
    Lepisto, Maija
    Almusa, Henrikki
    Ellonen, Pekka
    Lorkowski, Stefan
    Maerz, Winfried
    Hutri-Kahonen, Nina
    Raitakari, Olli
    Kahonen, Mika
    Salonen, Jukka T.
    Lehtimaki, Terho
    HUMAN MOLECULAR GENETICS, 2022, 31 (10) : 1720 - 1732
  • [39] Quantitative trait loci analysis of seed oil content and composition of wild and cultivated soybean
    Yao, Yanjie
    You, Qingbo
    Duan, Guozhan
    Ren, Jianjun
    Chu, Shanshan
    Zhao, Junqing
    Li, Xia
    Zhou, Xinan
    Jiao, Yongqing
    BMC PLANT BIOLOGY, 2020, 20 (01)
  • [40] Mapping Quantitative Trait Loci Underlying Function-Valued Traits Using Functional Principal Component Analysis and Multi-Trait Mapping
    Kwak, Il-Youp
    Moore, Candace R.
    Spalding, Edgar P.
    Broman, Karl W.
    G3-GENES GENOMES GENETICS, 2016, 6 (01): : 79 - 86