@article {895,
	title = {Optimized sample selection for cost-efficient long-read population sequencing.},
	journal = {Genome Res},
	volume = {31},
	year = {2021},
	month = {2021 May},
	pages = {910-918},
	abstract = {<p>An increasingly important scenario in population genetics is when a large cohort has been genotyped using a low-resolution approach (e.g., microarrays, exome capture, short-read WGS), from which a few individuals are resequenced using a more comprehensive approach, especially long-read sequencing. The subset of individuals selected should ensure that the captured genetic diversity is fully representative and includes variants across all subpopulations. For example, human variation has historically focused on individuals with European ancestry, but this represents a small fraction of the overall diversity. Addressing this, SVCollector identifies the optimal subset of individuals for resequencing by analyzing population-level VCF files from low-resolution genotyping studies. It then computes a ranked list of samples that maximizes the total number of variants present within a subset of a given size. To solve this optimization problem, SVCollector implements a fast, greedy heuristic and an exact algorithm using integer linear programming. We apply SVCollector on simulated data, 2504 human genomes from the 1000 Genomes Project, and 3024 genomes from the 3000 Rice Genomes Project and show the rankings it computes are more representative than alternative naive strategies. When selecting an optimal subset of 100 samples in these cohorts, SVCollector identifies individuals from every subpopulation, whereas naive methods yield an unbalanced selection. Finally, we show the number of variants present in cohorts selected using this approach follows a power-law distribution that is naturally related to the population genetic concept of the allele frequency spectrum, allowing us to estimate the diversity present with increasing numbers of samples.</p>},
	issn = {1549-5469},
	doi = {10.1101/gr.264879.120},
	author = {Ranallo-Benavidez, T Rhyker and Lemmon, Zachary and Soyk, Sebastian and Aganezov, Sergey and Salerno, William J and McCoy, Rajiv C and Lippman, Zachary B and Schatz, Michael C and Sedlazeck, Fritz J}
}
@article {843,
	title = {Major Impacts of Widespread Structural Variation on Gene Expression and Crop Improvement in Tomato.},
	journal = {Cell},
	volume = {182},
	year = {2020},
	month = {2020 07 09},
	pages = {145-161.e23},
	abstract = {<p>Structural variants (SVs) underlie important crop improvement and domestication traits. However, resolving the extent, diversity, and quantitative impact of SVs has been challenging. We used long-read nanopore sequencing to capture 238,490 SVs in 100 diverse tomato lines. This panSV genome, along with 14 new reference assemblies, revealed large-scale intermixing of diverse genotypes, as well as thousands of SVs intersecting genes and cis-regulatory regions. Hundreds of SV-gene pairs exhibit subtle and significant expression changes, which could broadly influence quantitative trait variation. By combining quantitative genetics with genome editing, we show how multiple SVs that changed gene dosage and expression levels modified fruit flavor, size, and production. In the last example, higher order epistasis among four SVs affecting three related transcription factors allowed introduction of an important harvesting trait in modern tomato. Our findings highlight the underexplored role of SVs in genotype-to-phenotype relationships and their widespread importance and utility in crop improvement.</p>},
	keywords = {Alleles, Crops, Agricultural, Cytochrome P-450 Enzyme System, Ecotype, Epistasis, Genetic, Fruit, Gene Duplication, Gene Expression Regulation, Plant, Genome, Plant, Genomic Structural Variation, Genotype, Inbreeding, Lycopersicon esculentum, Molecular Sequence Annotation, Phenotype, Plant Breeding, Quantitative Trait Loci},
	issn = {1097-4172},
	doi = {10.1016/j.cell.2020.05.021},
	author = {Alonge, Michael and Wang, Xingang and Benoit, Matthias and Soyk, Sebastian and Pereira, Lara and Zhang, Lei and Suresh, Hamsini and Ramakrishnan, Srividya and Maumus, Florian and Ciren, Danielle and Levy, Yuval and Harel, Tom Hai and Shalev-Schlosser, Gili and Amsellem, Ziva and Razifard, Hamid and Caicedo, Ana L and Tieman, Denise M and Klee, Harry and Kirsche, Melanie and Aganezov, Sergey and Ranallo-Benavidez, T Rhyker and Lemmon, Zachary H and Kim, Jennifer and Robitaille, Gina and Kramer, Melissa and Goodwin, Sara and McCombie, W Richard and Hutton, Samuel and Van Eck, Joyce and Gillis, Jesse and Eshed, Yuval and Sedlazeck, Fritz J and van der Knaap, Esther and Schatz, Michael C and Lippman, Zachary B}
}
