The genome of the Australian zebra finch, published today (April 1) in Nature, sets a framework that could provide insights into how humans learn language and new ways of studying speech disorders.

Researchers who collaborated on the finch genome found a much higher proportion of the bird's DNA is actively engaged by the act of singing songs.

“The system for singing has much more complexity than we imagined,” said co-author Erich Jarvis, Ph.D., Duke professor of neurobiology and a Howard Hughes Medical Institute Investigator.

More genes involved

“In the part of the brain that controls learning how to sing, about 5 per cent of the genes are regulated by the action of singing. I thought there might be 100 genes, but our laboratory found that there are at least 800 regulated genes turning off and on, and there may be many more.”

The effect

Jarvis was the first to discover that singing altered genetic activity in songbirds. He said: “we were also able for the first time to use the genome sequence to infer the regulatory regions that turn genes on and off and the way in which they may interact.”

The new work may help scientists understand how humans learn language. It also could help identify the genetic and molecular origins of speech disorders, including those related to autism, stroke, stuttering and Parkinson's Disease, the researchers say. The findings could also have an impact on research into deafness and language learning after the critical learning period, according to a Duke University press release.

“Overall, the genome will help researchers worldwide learn about the genes responsible for developing neural circuits for critical periods of learning, study the effect of hormones on brain and behaviour, and provide further information for a model of sex-related brain differences,” Jarvis said. “During juvenile development, the female song-learning brain regions and ability atrophy.”

Jarvis noted that sequencing additional genomes, like the parrot genome his lab is working on with the Warren laboratory, would contribute valuable information about spoken language.

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