January 23, 2019

Good Morning,

I'm always hesitant to trust AI. I've seen plenty of movies that have informed me to keep an eye on AI. So when it was revealed that an AI-powered genomic analysis revealed an unknown human ancestor, naturally, I was skeptical. But check out the story below and see what you think about this new discovery.

Learn about this and more interesting stories from the scientific community in today's issue.

Until Next Time,
Erin

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*-- AI-powered genomic analysis reveals unknown human ancestor --*

Using a combination of deep learning algorithms and advanced statistical techniques, researchers identified an unknown human ancestor hiding in the modern human genome.

According to the new genomic analysis, a hybrid species produced by Neanderthals and Denisovans bred with Out of Africa modern humans in Asia some 40,000 years ago.

The discovery, detailed this week in the journal Nature Communications, marks the first time scientists have used deep learning algorithms to analyze human evolution.

The statistical analysis suggests hybrid hominids may have regularly interbred with modern humans.

"About 80,000 years ago, the so-called Out of Africa occurred, when part of the human population, which already consisted of modern humans, abandoned the African continent and migrated to other continents, giving rise to all the current populations," Jaume Bertranpetit, principal investigator at the Institute of Evolutionary Biology, said in a news release.

"We know that from that time onwards, modern humans cross bred with Neanderthals in all the continents, except Africa, and with the Denisovans in Oceania and probably in Southeast Asia, although the evidence of cross-breeding with a third extinct species had not been confirmed with any certainty," Bertranpetit said.

Scientists have previously theorized that a third species accounts for the origins of genomic fragments belonging to modern humans.

Deep learning algorithms mimic the mammalian nervous system, using a combination of artificial neurons to analyze data and detect patterns important to the performance of a specific task.

"We have used this property to get the algorithm to learn to predict human demographics using genomes obtained through hundreds of thousands of simulations," said Oscar Lao, principal investigator at the National Genomic Analysis Center in Barcelona. "Whenever we run a simulation we are traveling along a possible path in the history of humankind. Of all simulations, deep learning allows us to observe what makes the ancestral puzzle fit together."

Last summer, paleontologists recovered the remains of a hybrid hominid -- the offspring of a Neanderthal mother and a Denisovan father. The latest findings seem to confirm the fossil's identification.

"Our theory coincides with the hybrid specimen discovered recently in Denisova, although as yet we cannot rule out other possibilities," said Mayukh Mondal, researcher at the University of Tartu.

*-- Geneticists accidentally engineer mice with especially short, long tails --*

Scientists have happened upon the genetic pathway that controls tail developmental in mice.

The pathway was discovered accidentally by two separate research groups, both investigating genes related to physiological development.

"We were trying to make mouse models of Lin28-driven cancer, but we were surprised to find that these mice had super long tails," researcher George Daley, dean at Harvard Medical School, said in a news release. "They had more vertebrae."

Daley and his colleagues were studying the Lin28/let-7 pathway, a series of genes that regulates developmental timing. The path has been linked with several cancers.

Researchers in Portugal found Gdf11, a gene that controls embryonic development of the tail in mice, finding during lab tests that Gfd11 mutations caused mice to grow shorter, thicker tails.

"They also contained a fully grown neural tube inside, as opposed to a normal tail that is essentially made of vertebrae," said Moises Mallo, researcher at the Instituto Gulbenkian de Ciência in Portugal.

Both teams of scientists inadvertently showcased the primary role the gene Lin28 plays in tail development.

"We were able to pinpoint the Lin28 and Hox13 genes as key regulators of tail development downstream from Gdf11," Mallo said.

Both Lin28 and Hox13 control the deployment of somites, blocks of cells that transform into specialized cell types, forming dermis, skeletal muscle, cartilage, tendons and vertebrae.

"From my perspective, one of the most important findings of our work is that a group of multipotent cells that build both the somites and the spinal cord are regulated by fundamentally different genetic networks and have different cell competences at two consecutive stages of development," Mallo said. "This finding goes beyond the trunk to tail transition, possibly acquiring relevance in pathological processes like the initiation of metastasis."

The discoveries of both teams -- detailed in two separate papers in the journal Developmental Cell -- could also offer scientists new insights into the evolution of tailed species.

"Anterior-posterior axis elongation is an important feature in bilateral animals, and natural selection has created a variety of tail lengths to suit different evolutionary pressures," said Harvard researcher Daisy Robinton. "Until now, little was known about how length is controlled and how the manipulation of genetics can impact morphogenesis."

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