BaitsTools: Software for hybridization capture bait design

Campana, Michael G.

doi:10.1111/1755-0998.12721

Cited by 24 publications

(24 citation statements)

References 20 publications

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“…In contrast to our pipeline, MarkerMiner ( Chamala et al, 2015 ) outputs SCG sequences, but not bait sequences. MarkerMiner may, however, be combined with other tools such as BaitFisher ( Mayer et al, 2016 ) or BaitsTools ( Campana, 2017 ). BaitFisher has been developed to obtain an optimal set of baits by minimizing the number of baits (by reducing redundancy of baits without gaps or ambiguous nucleotides) while maximizing the number of targeted nucleotide sequences.…”

Section: Resultsmentioning

confidence: 99%

“…The disadvantage of BaitFisher is that it does not tolerate any gaps nor ambiguity codes in the start position of a putative bait, rendering it susceptible to low-quality samples. BaitsTools ( Campana, 2017 ) can use various forms of input data (e.g., alignments, sequence lists, RADseq loci) and allows quality checks on obtained bait sequences to be performed, but it does not include any tools to modify or generate input data (e.g., removal of putative contaminants, extracting exons from transcriptome data).…”

Section: Resultsmentioning

confidence: 99%

“…Both tools provide an automated, user-friendly and web-supported workflow for discovery of LCN loci from transcriptome data. Campana (2017) developed BaitsTools, which automates bait design from various sources (e.g., alignments, unaligned sequences, and RADseq loci) and quality checking of thus obtained baits. Disadvantages of these approaches include reliance on whole or draft genome sequences ( de Sousa et al, 2014 ; Weitemier et al, 2014 ) or settings that bias against less conserved loci, i.e., strictly reciprocal blast searches in MarkerMiner ( Chamala et al, 2015 ) and the highly reduced bait-to-target distances in BaitFisher ( Mayer et al, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

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Marker Development for Phylogenomics: The Case of Orobanchaceae, a Plant Family with Contrasting Nutritional Modes

Hao

Pan

et al. 2017

Front. Plant Sci.

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Phylogenomic approaches, employing next-generation sequencing (NGS) techniques, have revolutionized systematic and evolutionary biology. Target enrichment is an efficient and cost-effective method in phylogenomics and is becoming increasingly popular. Depending on availability and quality of reference data as well as on biological features of the study system, (semi-)automated identification of suitable markers will require specific bioinformatic pipelines. Here, we established a highly flexible bioinformatic pipeline, BaitsFinder, to identify putative orthologous single copy genes (SCGs) and to construct bait sequences in a single workflow. Additionally, this pipeline has been constructed to be able to cope with challenging data sets, such as the nutritionally heterogeneous plant family Orobanchaceae. To this end, we used transcriptome data of differing quality available for four Orobanchaceae species and, as reference, SCG data from monkeyflower (Erythranthe guttata, syn. Mimulus g.; 1,915 genes) and tomato (Solanum lycopersicum; 391 genes). Depending on whether gaps were permitted in initial blast searches of the four Orobanchaceae species against the reference, our pipeline identified 1,307 and 981 SCGs with average length of 994 bp and 775 bp, respectively. Automated bait sequence construction (using 2× tiling) resulted in 38,170 and 21,856 bait sequences, respectively. In comparison to the recently published MarkerMiner 1.0 pipeline BaitsFinder identified about 1.6 times as many SCGs (of at least 900 bp length). Skipping steps specific to analyses of Orobanchaceae, BaitsFinder was successfully used in a group of non-parasitic plants (three Asteraceae species and, as reference, SCG data from Arabidopsis thaliana based on previously compiled SCGs). Thus, BaitsFinder is expected to be broadly applicable in groups, where only transcriptomes or partial genome data of differing quality are available.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Marker Development for Phylogenomics: The Case of Orobanchaceae, a Plant Family with Contrasting Nutritional Modes

Hao

Pan

et al. 2017

Front. Plant Sci.

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“…These short RNA baits are used in a hybridisation reaction to bind to DNA fragments matching the target loci, which are then captured and PCR-amplified for sequencing. The increasing availability of genomic resources held in public repositories, combined with pipelines to identify low-or-single-copy genes based on these resources, have enabled bait kit design for a wide range of plant groups (Kadlec et al, 2017;Campana et al, 2018;Chafin et al, 2018;Vatanaprast et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

New targets acquired: improving locus recovery from the Angiosperms353 probe set

McLay

Birch

Gunn

et al. 2020

Preprint

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Universal target enrichment kits maximise utility across wide evolutionary breadth while minimising the number of baits required to create a cost-efficient kit. Locus assembly requires a target reference, but the taxonomic breadth of the kit means that target references files can be phylogenetically sparse. The Angiosperms353 kit has been successfully used to capture loci throughout angiosperms but includes sequence information from 6−18 taxa per locus. Consequently, reads sequenced from on-target DNA molecules may fail to map to references, resulting in fewer on-target reads for assembly, reducing locus recovery. We expanded the Angiosperms353 target file, incorporating sequences from 566 transcriptomes to produce a mega353 target file, with each gene represented by 17−373 taxa. This mega353 file is a drop-in replacement for the original Angiosperms353 file in HybPiper analyses. We provide tools to subsample the file based on user-selected taxon groups, and to incorporate other transcriptome or protein-coding gene datasets. Compared to the default Angiosperms353 file, the mega353 file increased the percentage of on-target reads by an average of 31%, increased loci recovery at 75% length by 61.9%, and increased the total length of the concatenated loci by 30%. The mega353 file and associated scripts are available at: https://github.com/chrisjackson−pellicle/NewTargets

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“…Selecting target markers and designing baits that are effective across a wide range of species is the first major challenge when applying the gene capture method. Many considerations are taken into baits design, such as uniqueness and conservativeness of markers, length and complexity of markers, and genetic distance between baits and target sequences (Bi et al, 2012;Campana, 2017;Faircloth, 2017;Faircloth et al, 2012;Gilbert et al, 2015;Hugall et al, 2016;Lemmon et al, 2012;Li et al, 2013;Mayer et al, 2016). However, all these measures are usually taken a priori, and few studies have been done to refine baits design after gene capture to improve the baits set for future experiments (but see Branstetter, Longino, Ward, & Faircloth, 2017).…”

mentioning

confidence: 99%

Gene markers for exon capture and phylogenomics in ray‐finned fishes

Jiang

Yuan

Zheng

et al. 2019

Ecology and Evolution

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Gene capture coupled with the next‐generation sequencing has become one of the preferred methods of subsampling genomes for phylogenomic studies. Many exon markers have been developed in plants, sharks, frogs, reptiles, fishes, and others, but no universal exon markers have been tested in ray‐finned fishes. Here, we identified a suite of “single‐copy” protein‐coding sequence (CDS) markers through comparing eight fish genomes, and tested them empirically in 83 species (33 families and nine orders or higher clades: Acipenseriformes, Lepisosteiformes, Elopomorpha, Osteoglossomorpha, Clupeiformes, Cypriniformes, Gobiaria, Carangaria, and Eupercaria; sensu Betancur et al. 2013). Sorting the markers according to their completeness and phylogenetic decisiveness in taxa tested resulted in a selection of 4,434 markers, which were proven to be useful in reconstructing phylogenies of the ray‐finned fishes at different taxonomic levels. We also proposed a strategy of refining baits (probes) design a posteriori based on empirical data. The markers that we have developed may greatly enrich the batteries of exon markers for phylogenomic study in ray‐finned fishes.

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BaitsTools: Software for hybridization capture bait design

Cited by 24 publications

References 20 publications

Marker Development for Phylogenomics: The Case of Orobanchaceae, a Plant Family with Contrasting Nutritional Modes

Marker Development for Phylogenomics: The Case of Orobanchaceae, a Plant Family with Contrasting Nutritional Modes

New targets acquired: improving locus recovery from the Angiosperms353 probe set

Gene markers for exon capture and phylogenomics in ray‐finned fishes

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