@article {116, title = {Copy number variants~and fixed duplications among 198 rhesus macaques (Macaca mulatta).}, journal = {PLoS Genet}, volume = {16}, year = {2020}, month = {2020 05}, pages = {e1008742}, abstract = {

The rhesus macaque is an abundant species of Old World monkeys and a valuable model organism for biomedical research due to its close phylogenetic relationship to humans. Copy number variation is one of the main sources of genomic diversity within and between species and a widely recognized cause of inter-individual differences in disease risk. However, copy number differences among rhesus macaques and between the human and macaque genomes, as well as the relevance of this diversity to research involving this nonhuman primate, remain understudied. Here we present a high-resolution map of sequence copy number for the rhesus macaque genome constructed from a dataset of 198 individuals. Our results show that about one-eighth of the rhesus macaque reference genome is composed of recently duplicated regions, either copy number variable regions or fixed duplications. Comparison with human genomic copy number maps based on previously published data shows that, despite overall similarities in the genome-wide distribution of these regions, there are specific differences at the chromosome level. Some of these create differences in the copy number profile between human disease genes and their rhesus macaque orthologs. Our results highlight the importance of addressing the number of copies of target genes in the design of experiments and cautions against human-centered assumptions in research conducted with model organisms. Overall, we present a genome-wide copy number map from a large sample of rhesus macaque individuals representing an important novel contribution concerning the evolution of copy number in primate genomes.

}, keywords = {Animals, Chromosome Mapping, DNA Copy Number Variations, Female, Gene Duplication, Genetics, Population, Genome, High-Throughput Nucleotide Sequencing, Humans, Macaca mulatta, Male, Open Reading Frames, Phylogeny, Sequence Analysis, DNA, Species Specificity}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1008742}, author = {Bras{\'o}-Vives, Marina and Povolotskaya, Inna S and Hartas{\'a}nchez, Diego A and Farr{\'e}, Xavier and Fernandez-Callejo, Marcos and Raveendran, Muthuswamy and Harris, R Alan and Rosene, Douglas L and Lorente-Galdos, Belen and Navarro, Arcadi and Marques-Bonet, Tomas and Rogers, Jeffrey and Juan, David} } @article {112, 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 = {

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.

}, 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} } @article {91, title = {Rapid, Paralog-Sensitive CNV Analysis of 2457 Human Genomes Using QuicK-mer2.}, journal = {Genes (Basel)}, volume = {11}, year = {2020}, month = {2020 01 29}, abstract = {

Gene duplication is a major mechanism for the evolution of gene novelty, and copy-number variation makes a major contribution to inter-individual genetic diversity. However, most approaches for studying copy-number variation rely upon uniquely mapping reads to a genome reference and are unable to distinguish among duplicated sequences. Specialized approaches to interrogate specific paralogs are comparatively slow and have a high degree of computational complexity, limiting their effective application to emerging population-scale data sets. We present QuicK-mer2, a self-contained, mapping-free approach that enables the rapid construction of paralog-specific copy-number maps from short-read sequence data. This approach is based on the tabulation of unique k-mer sequences from short-read data sets, and is able to analyze a 20X coverage human genome in approximately 20 min. We applied our approach to newly released sequence data from the 1000 Genomes Project, constructed paralog-specific copy-number maps from 2457 unrelated individuals, and uncovered copy-number variation of paralogous genes. We identify nine genes where none of the analyzed samples have a copy number of two, 92 genes where the majority of samples have a copy number other than two, and describe rare copy number variation effecting multiple genes at the APOBEC3 locus.

}, keywords = {Algorithms, Computational Biology, DNA Copy Number Variations, Evolution, Molecular, Gene Duplication, Genome, Human, Humans, Sequence Analysis, DNA}, issn = {2073-4425}, doi = {10.3390/genes11020141}, author = {Shen, Feichen and Kidd, Jeffrey M} }