Researchers at the University of Missouri studied the all-female Amazon molly to understand how it avoids genetic decline from asexual reproduction. The molly reproduces by cloning yet has persisted far longer than models predicted; scientists first confirmed an asexual vertebrate in 1932 and today there are about 100 such vertebrate species.
Wes Warren and Edward Ricemeyer spent more than a decade investigating the fish. In 2018 Warren mapped the molly’s full genome and expected to find accumulated genetic damage, but the DNA looked healthy. They suggested gene conversion — a process in which one gene copy overwrites another — could be repairing harmful mutations.
Using newer long-read sequencing, the team compared the molly’s DNA to the genomes of its two parental species and found the parental genome sets were mutating at different rates. The researchers concluded that gene conversion occurs at an apparently optimal rate and helps keep the species genetically healthy, with possible applications in breeding and medical research.
Difficult words
- asexual — reproduction without combining two parents' genes
- clone — produce an identical genetic copy of organismcloning
- genome — the complete set of an organism's DNAgenomes
- gene conversion — one gene copy overwrites another gene copy
- mutation — a change in the DNA sequencemutations
- vertebrate — an animal with a backbone or spine
- sequencing — the process of reading DNA letters in orderlong-read sequencing
- optimal — best or most effective under certain conditions
Tip: hover, focus or tap highlighted words in the article to see quick definitions while you read or listen.
Discussion questions
- Do you think gene conversion ideas from this study could help animal breeding? Why or why not?
- How might finding healthy DNA in asexual species change ideas about cloning?
- Would you support using these research findings in medical research? Give one reason.
Related articles
AI models encode real-world plausibility
Researchers at Brown University tested whether modern AI language models can tell if events are common, unlikely, impossible or nonsensical. They used mechanistic interpretability and found internal patterns that match human judgments in several open-source models.
