G3-Genes Genomes Genetics
基因,基因组学和遗传学
ISSN: 2160-1836
自引率: 6.4%
发文量: 345
被引量: 6487
影响因子: 3.538
通过率: 暂无数据
出版周期: 月刊
审稿周期: 1.43
审稿费用: 0
版面费用: 暂无数据
年文章数: 345
国人发稿量: 8

期刊描述简介:

G3: Genes, Genomes, Genetics provides a forum for the publication of high‐quality foundational research, particularly research that generates useful genetic and genomic information such as genome maps, single gene studies, genome‐wide association and QTL studies, as well as genome reports, mutant screens, and advances in methods and technology. The Editorial Board of G3 believes that rapid dissemination of these data is the necessary foundation for analysis that leads to mechanistic insights. G3, published by the Genetics Society of America, meets the critical and growing need of the genetics community for rapid review and publication of important results in all areas of genetics. G3 offers the opportunity to publish the puzzling finding or to present unpublished results that may not have been submitted for review and publication due to a perceived lack of a potential high-impact finding. As part of our mission to serve our communities, we've published thematic collections, including Genomic Prediction, Multiparental Populations, Genetics of Immunity, and Genetics of Sex. G3 has earned the DOAJ Seal, which is a mark of certification for open access journals, awarded by the Directory of Open Access Journals to journals that achieve a high level of openness, adhering to Best Practices and high publishing standards. More than just a publisher, the Genetics Society of America is mission-driven and places a high priority on responding to community needs. GENETICS and G3 have long been committed to supporting resources that serve scientists. We were the first journals to partner with Cold Spring Harbor Laboratories to enable seamless deposits of manuscripts from our submission systems straight into the preprint server bioRxiv, as well as from bioRxiv to GENETICS and G3, and we have accepted submissions posted for preprint servers since 2012. Articles feature links to model organism databases like SGD, FlyBase, and WormBase. We have also partnered with Overleaf to provide custom templates for authors who use LaTex, saving them time at submission. The annotation tool Remarq is available on both the GENETICS and G3 websites and allows for collaborative commenting and article sharing. Our latest collaboration with Figshare ensures that supplemental material and data files are permanently associated with an article—and that authors aren’t limited by file type or size when providing data that support their work. Early online publication means that research investigations are freely accessible and in PubMed within days of acceptance – which eliminates delays in discovering the latest science.

最新论文
  • De novo genome assembly of the tobacco hornworm moth (Manduca sexta).

    The tobacco hornworm, Manduca sexta, is a lepidopteran insect that is used extensively as a model system for studying insect biology, development, neuroscience, and immunity. However, current studies rely on the highly fragmented reference genome Msex_1.0, which was created using now-outdated technologies and is hindered by a variety of deficiencies and inaccuracies. We present a new reference genome for M. sexta, JHU_Msex_v1.0, applying a combination of modern technologies in a de novo assembly to increase continuity, accuracy, and completeness. The assembly is 470 Mb and is ∼20× more continuous than the original assembly, with scaffold N50 > 14 Mb. We annotated the assembly by lifting over existing annotations and supplementing with additional supporting RNA-based data for a total of 25,256 genes. The new reference assembly is accessible in annotated form for public use. We demonstrate that improved continuity of the M. sexta genome improves resequencing studies and benefits future research on M. sexta as a model organism.

    被引量:17 发表:2021

  • Using Sequence Variants in Linkage Disequilibrium with Causative Mutations to Improve Across-Breed Prediction in Dairy Cattle: A Simulation Study.

    Sequence data are expected to increase the reliability of genomic prediction by containing causative mutations directly, especially in cases where low linkage disequilibrium between markers and causative mutations limits prediction reliability, such as across-breed prediction in dairy cattle. In practice, the causative mutations are unknown, and prediction with only variants in perfect linkage disequilibrium with the causative mutations is not realistic, leading to a reduced reliability compared to knowing the causative variants. Our objective was to use sequence data to investigate the potential benefits of sequence data for the prediction of genomic relationships, and consequently reliability of genomic breeding values. We used sequence data from five dairy cattle breeds, and a larger number of imputed sequences for two of the five breeds. We focused on the influence of linkage disequilibrium between markers and causative mutations, and assumed that a fraction of the causative mutations was shared across breeds and had the same effect across breeds. By comparing the loss in reliability of different scenarios, varying the distance between markers and causative mutations, using either all genome wide markers from commercial SNP chips, or only the markers closest to the causative mutations, we demonstrate the importance of using only variants very close to the causative mutations, especially for across-breed prediction. Rare variants improved prediction only if they were very close to rare causative mutations, and all causative mutations were rare. Our results show that sequence data can potentially improve genomic prediction, but careful selection of markers is essential.

    被引量:28 发表:1970

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