Investigating the genomic basis of discrete phenotypes using a Pool‐Seq‐only approach: New insights into the genetics underlying colour variation in diverse taxa

Neethiraj, Ramprasad; Hornett, Emily A.; Hill, Jason; Wheat, Christopher W.

doi:10.1111/mec.14205

Cited by 29 publications

(32 citation statements)

References 51 publications

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“…Pooling samples before library preparations, also called "poolseq", can be used for projects with hundreds of samples and if tracing back individual samples is not relevant for the research question at hand (Himmelbach et al, 2014;Anand et al, 2016). This strategy is useful for the identification of variable regions between populations, especially when population sampling must be higher than what the budget allows for sequencing as individual libraries (Neethiraj et al, 2017). Because with this method it is possible to sample many individuals within a population, there is more information for detecting rare variants across the population.…”

Section: Amplificationmentioning

confidence: 99%

A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project

et al. 2020

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High-throughput DNA sequencing techniques enable time-and cost-effective sequencing of large portions of the genome. Instead of sequencing and annotating whole genomes, many phylogenetic studies focus sequencing effort on large sets of pre-selected loci, which further reduces costs and bioinformatic challenges while increasing coverage. One common approach that enriches loci before sequencing is often referred to as target sequence capture. This technique has been shown to be applicable to phylogenetic studies of greatly varying evolutionary depth. Moreover, it has proven to produce powerful, large multi-locus DNA sequence datasets suitable for phylogenetic analyses. However, target capture requires careful considerations, which may greatly affect the success of experiments. Here we provide a simple flowchart for designing phylogenomic target capture experiments. We discuss necessary decisions from the identification of target loci to the final bioinformatic processing of sequence data. We outline challenges and solutions related to the taxonomic scope, sample quality, and available genomic resources of target capture projects. We hope this review will serve as a useful roadmap for designing and carrying out successful phylogenetic target capture studies.

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Section: Amplificationmentioning

confidence: 99%

A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project

et al. 2020

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“…As an alternative to using reference genomes of closely related species or for situations when no such reference is available, we here apply a newly developed exon mining via Pool‐seq approach to acquire a draft genome assembly both for the focal species and for single nucleotide polymorphism (SNP) frequency estimation. The approach leverages the power of Pool‐seq to subsample the genome to obtain high‐resolution genomic insights quickly and at a reasonable cost (Neethiraj, Hornett, Hill, & Wheat, ). This pipeline has been utilized for elucidating the genomics underlying phenotypic differences between populations of several butterfly species (Keehnen, Hill, Nylin, & Wheat, ; Pruisscher, Nylin, Gotthard, & Wheat, ; Woronik & Wheat, ).…”

Section: Introductionmentioning

confidence: 99%

“…Pool‐seq data from populations are mapped against the final gene‐models‐only genome assembly which contains both protein‐coding and noncoding sequences, for estimation of population diversity and differentiation (akin to mapping RNA‐seq data against a de novo transcriptome of the same data). This method (Neethiraj et al, ) has similarities with that of Therkildsen and Palumbi () who mapped Pool‐seq reads to a reference transcriptome. In our case, we generate a transcriptome from published RNA‐seq data and use it to scaffold and annotate a draft genome assembly from Pool‐seq data.…”

Section: Introductionmentioning

confidence: 99%

Exploring a Pool‐seq‐only approach for gaining population genomic insights in nonmodel species

Kurland

Wheat

Celorio‐Mancera

et al. 2019

Ecology and Evolution

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Developing genomic insights is challenging in nonmodel species for which resources are often scarce and prohibitively costly. Here, we explore the potential of a recently established approach using Pool‐seq data to generate a de novo genome assembly for mining exons, upon which Pool‐seq data are used to estimate population divergence and diversity. We do this for two pairs of sympatric populations of brown trout (Salmo trutta): one naturally sympatric set of populations and another pair of populations introduced to a common environment. We validate our approach by comparing the results to those from markers previously used to describe the populations (allozymes and individual‐based single nucleotide polymorphisms [SNPs]) and from mapping the Pool‐seq data to a reference genome of the closely related Atlantic salmon (Salmo salar). We find that genomic differentiation (FST) between the two introduced populations exceeds that of the naturally sympatric populations (FST = 0.13 and 0.03 between the introduced and the naturally sympatric populations, respectively), in concordance with estimates from the previously used SNPs. The same level of population divergence is found for the two genome assemblies, but estimates of average nucleotide diversity differ (trueπ¯ ≈ 0.002 and trueπ¯ ≈ 0.001 when mapping to S. trutta and S. salar, respectively), although the relationships between population values are largely consistent. This discrepancy might be attributed to biases when mapping to a haploid condensed assembly made of highly fragmented read data compared to using a high‐quality reference assembly from a divergent species. We conclude that the Pool‐seq‐only approach can be suitable for detecting and quantifying genome‐wide population differentiation, and for comparing genomic diversity in populations of nonmodel species where reference genomes are lacking.

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“…As this genome lacks an annotation, we generated a draft annotation using spaln v2.1.2 (Gotoh, ; Iwata & Gotoh, ), which is a high‐performance protein to genome alignment program that is exon boundary aware, and the Danaus plexippus protein set DPOGS2 (Zhan & Reppert, ). In addition, the MESPA pipeline (Neethiraj, Hornett, Hill, & Wheat, ), which uses spaln to construct gene models from highly fragmented genome assemblies, was used to identify the immune genes. A set of 225 immune proteins were used for annotation, with the majority ( N = 205) of these being the canonical set of immune genes identified in Bombyx mori (Lepidoptera, Bombycidae; Tanaka et al., ), and an additional 20 candidate genes being antimicrobial peptides identified in the closely related species Pieris rapae (Lepidoptera, Pieridae; C. Wheat unpublished data).…”

Section: Methodsmentioning

confidence: 99%

Microevolutionary selection dynamics acting on immune genes of the green‐veined white butterfly, Pieris napi

et al. 2018

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Insects rely on their innate immune system to successfully mediate complex interactions with their microbiota, as well as the microbes present in the environment. Previous work has shown that components of the canonical immune gene repertoire evolve rapidly and have evolutionary characteristics originating from interactions with fast-evolving microorganisms. Although these interactions are likely to vary among populations, there is a poor understanding of the microevolutionary dynamics of immune genes, especially in non-Dipteran insects. Here, we use the full set of canonical insect immune genes to investigate microevolutionary dynamics acting on these genes between and among populations by comparing three allopatric populations of the green-veined white butterfly, Pieris napi (Linné; Lepidoptera, Pieridae). Immune genes showed increased genetic diversity compared to genes from the rest of the genome and various functional categories exhibited different types of signatures of selection, at different evolutionary scales, presenting a complex pattern of selection dynamics. Signatures of balancing selection were identified in 10 genes, and 17 genes appear to be under positive selection. Genes involved with the cellular arm of the immune response as well as the Toll pathway appear to be enriched among our outlier loci, regardless of functional category. This suggests that the targets of selection might focus upon an entire pathway, rather than functional subsets across pathways. Our microevolutionary results are similar to previously observed macroevolutionary patterns from diverse taxa, suggesting that either the immune system is robust to dramatic differences in life history and microbial communities, or that diverse microbes exert similar selection pressures.

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Investigating the genomic basis of discrete phenotypes using a Pool‐Seq‐only approach: New insights into the genetics underlying colour variation in diverse taxa

Cited by 29 publications

References 51 publications

A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project

A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project

Exploring a Pool‐seq‐only approach for gaining population genomic insights in nonmodel species

Microevolutionary selection dynamics acting on immune genes of the green‐veined white butterfly, Pieris napi

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