Genome sequencing and population genomics in non-model organisms.
By H. Ellegren. Trends in Ecology & Evolution, 2014
669 citations recorded by the source corpus.
Subfields: Genetics, Molecular Biology, Plant Science
View Paper: https://www.semanticscholar.org/paper/ac0ec1e2ceb7a686f7472e412914a141c47262ce
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Citations in the corpus
- Applications of next-generation sequencing to the study of biological invasions (2015, background): “Excellent reviews are available on de novo genome assembly (Baker, 2012) and use of genome sequencing in non-model organisms (Ellegren, 2014).”
- Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions (2016, positive): “…Tif fi n and Ross-Ibarra 2014), genetic-environment association methods (Rellstab et al. 2015), genomic resource development (Stapley et al. 2010; Ellegren 2014; Bragg et al. 2015; Manel et al. 2016), signatures of selection (Vitti et al. 2013), and mapping variation underlying adaptive…”
- What is Speciation Genomics? The roles of ecology, gene flow, and genomic architecture in the formation of species (2018, methodology): “…of interest, estimate parameters to describe the demographic aspects of speciation history with unprecedented resolution (Ellegren et al., 2012; Ellegren, 2014; Fan & Meyer, 2014; Gaither et al., 2015; Malinsky et al., 2015; Gante et al., 2016; Kang et al., 2016; Schmitz et al., 2016; Toews et…”
- A framework for incorporating evolutionary genomics into biodiversity conservation and management (2015, background): “Economical sample preparation strategies reviewed in [51-53] now enable high-throughput genomics studies even with-”
- Third generation sequencing: technology and its potential impact on evolutionary biodiversity research (2016, background): “Likewise, affordable genome sequencing for non-model organisms helped to transform the field of population genetics to population genomics (Ellegren, 2014).”
- OptM: estimating the optimal number of migration edges on population trees using Treemix (2021, background): “…[notably for single-nucleotide polymorphisms (SNPs)] have made the generation of genome-wide allele frequency data for multiple populations increasingly tractable [1], thus limiting studies of demographic history primarily to the statistical models and computational capabilities available.”