Genetics Society of America
GSA connects you to the field through a range of scholarly and community publications: our peer-reviewed journals offer two distinct platforms for communicating high-quality original research; our blog brings perspective to your research and career; and our newsletters keep you up to date with the latest opportunities and news from your community.
GENETICS publishes high-quality genetics and genomics research that expands scientific boundaries—we’ve been building the field since 1916. With its broad readership, rich history, and responsive editors, GENETICS brings the latest in publishing innovations to the communities it serves. We invite you to submit your research and discover the fast turnaround times and helpful review process for yourself.
Get your useful data out into the world by publishing in G3: Genes|Genomes|Genetics. G3 publishes high quality foundational research, particularly studies that generate useful genetic information, such as mutant screens, single gene studies, genome maps, genome sequence data, GWAS and QTL studies, software, data resources, and new methods. The Editorial Board of G3 believes that rapid dissemination of such data lays the foundation for many important insights.
We treat authors as colleagues, not adversaries. Your time is important—and so is your research. Peer editors oversee the review process and give you clear guidance on how to address any reviewer comments; our helpful editorial staff keep the process moving and on time. We make it easy to submit: no formatting requirements on initial submission. Our dedicated editors work hard to keep time to first decision at around a month. And because we’re agile and community-driven, we’ve long been at the forefront of publishing innovations.
The GSA Journals are committed to helping authors get their work in front a wide audience. Our Promotional Toolkit for Authors contains pointers to help you promote your GENETICS or G3: Genes|Genomes|Genetics paper, including how GSA and Oxford University Press can help.
The review experience has been the single most useful and pleasant of my career. The reviews were constructive and fair, the editor provided exceptionally clear guidance, and turn-around on the revision was lightning fast.
Genes to Genomes, the GSA blog, features news from the GSA community, highlights from the GSA journals, and posts from staff and guest authors about careers, professional development, science policy, publishing, education, outreach, equity and inclusion, and the intersections of science, art, and culture. Propose a guest post yourself and start a conversation!
In March 2016, GENETICS launched WormBook, a comprehensive compendium of review articles presenting the current state of knowledge in C. elegans research. WormBook articles span the breadth of the biology, genetics, genomics, and evolutionary biology of C. elegans. Find historical WormBook articles published as the online companion to WormBase here. This page contains the full list of all historical and GSA-published WormBook articles, organized by section.
Researchers show that the key to helping crops withstand shifting conditions may lie in balancing speed with flexibility.
AbstractPlastics are highly stable materials with widespread applications, but their resistance to degradation poses a significant environmental challenge, often resulting in accumulation in landfills or pollution in the form of microplastics. Biodegradation using insect larvae has recently emerged as a promising strategy to address this issue, though the molecular basis of plastic degradation in these organisms remains poorly understood due to limited genomic resources. In this study, we present a complete genome of the lesser...
AbstractSimulation-based inference methods are increasingly being used in population genetics due to their flexibility and ability to be applied in settings where likelihood-based methods are intractable. Perhaps the best known such method is Approximate Bayesian Computation (ABC); however, its popularity is offset by its shortcomings which include computational expense and an unfortunate inability to efficiently fit models to high-dimensional summaries of the data. An alternative approach that solves these issues is supervised machine learning (ML);...
