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

Abstract

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/.

Exploring DNA variant segregation types in pooled genome sequencing enables effective mapping of weeping trait in Malus

“…To facilitate data analysis, several analytical software packages have been developed, such as SHOREmap ( Schneeberger et al , 2009 ; Sun and Schneeberger, 2015 ), CloudMap ( Minevich et al , 2012 ), SNPtrack ( Leshchiner et al , 2012 ), MegaMapper ( Obholzer et al , 2012 ), MMAPPR ( Hill et al , 2013 ), EXPLoRA and EXPLoRA-Web ( Duitama et al , 2014 ; Pulido-Tamayo et al , 2016 ), and GIPS ( Hu et al , 2016 ). These packages are helpful tools for pooled genome sequencing data analysis for many model species from which they were developed.…”

Indel‐seq: a fast‐forward genetics approach for identification of trait‐associated putative candidate genomic regions and its application in pigeonpea (Cajanus cajan)

“…To control the EXPLoRA‐web models, three different parameters were utilized for identification of QTLs (i) α = 5; β = 1 (high sensitivity) (ii) α = 10; β = 1 (the middle ground between sensitivity and specificity) and (iii) α=30; β=1 (high specificity). The α/β ratio determines the shape of the β distribution in the models, which reflects the probability for the phenotype‐linked states (Pulido‐Tamayo et al ., ).…”

Easymap: A User-Friendly Software Package for Rapid Mapping-by-Sequencing of Point Mutations and Large Insertions

“…Mapping-by-sequencing approaches for the identification of causal mutations are much faster than previous methods but can be hampered by the lack of computing resources and/or accessible software. Currently available programs for mapping-by-sequencing data analysis suffer from one or several of the following issues: they require the purchase of licenses ( Smith, 2015 ); they require a certain level of bioinformatics skills to use ( Abe et al, 2012 ; Fekih et al, 2013 ; Jiang et al, 2015 ; Sun and Schneeberger, 2015 ; Ecovoiu et al, 2016 ; Wachsman et al, 2017 ; see also https://sourceforge.net/projects/mimodd/ ); they only do a part of the computing tasks required for a mapping-by-sequencing experiment ( Li et al, 2009 ; Langmead and Salzberg, 2012 ; Hill et al, 2013 ); they are designed for a specific type of mutation or mapping strategy ( Gonzalez et al, 2013 ; Ewing, 2015 ; Hénaff et al, 2015 ; Solaimanpour et al, 2015 ; Sun and Schneeberger, 2015 ; Wachsman et al, 2017 ; Klein et al, 2018 ; Javorka et al, 2019 ); they are hosted at a public server but usage is limited ( Gonzalez et al, 2013 ; Afgan et al, 2018 ); or they can no longer be accessed or used ( Minevich et al, 2012 ; Pulido-Tamayo et al, 2016 ).…”