Gene therapy targets sickle-cell disease – Nature

Image credit: Steve Babuljak/UCSF

Gene therapy might offer a cure for sickle-cell disease, and clinical trials are already under way. The approach is promising because just a single gene needs correcting: the one for the β-globin subunit of haemoglobin, the body’s oxygen ferry. But Elliott Vichinsky is concerned that the same problems that make current sickle-cell care ineffective will also plague this gene-therapy treatment. He estimates that at least 30% of his adult patients with sickle-cell disease die from preventable causes. As his patients attest, sickle-cell care is often inadequate for reasons that have little to do with scientific advancement and lots to do with economics and racism.


The automatic-design tools that are changing synthetic biology – Nature

Illustration by The Project Twins

Computerized genetic-design tools automate the process by which researchers design complex genetic circuits that can program cells — especially bacteria and yeast — to carry out specific actions, such as activating a particular enzyme or churning out a certain protein. Synthetic biologists have used single-celled organisms in this way to produce drugs, biological sensors that include cells or antibodies, enzymes for use in industry, and more.

Blockchains Won’t Fix the Problem with Genomics – NeoLife

Illustration by Igor Bastidas

This is shaping up to be the year of DNA for cryptocurrency. One startup after another is offering to pay you in bitcoin-like tokens for sharing your genetic data.

But it’s hard to see how using blockchains and cryptocurrencies will substantially increase demand for genome sequencing. That’s a vexing problem because too few genomes have been sequenced and analyzed to generate as many meaningful insights as scientists had hoped.

Read the full story in NeoLife.

How to build a human cell atlas – Nature

photo by Casey Atkins for Nature

Aviv Regev likes to work at the edge of what is possible. In 2011, the computational biologist was collaborating with molecular geneticist Joshua Levin to test a handful of methods for sequencing RNA. The scientists were aiming to push the technologies to the brink of failure and see which performed the best. They processed samples with degraded RNA or vanishingly small amounts of the molecule. Eventually, Levin pointed out that they were sequencing less RNA than appears in a single cell.

To Regev, that sounded like an opportunity. The cell is the basic unit of life and she had long been looking for ways to explore how complex networks of genes operate in individual cells, how those networks can differ and, ultimately, how diverse cell populations work together. The answers to such questions would reveal, in essence, how complex organisms such as humans are built.

Read the full story in Nature.

New method taps family trees for clues about conditions – Spectrum

Genetic puzzle: A new approach for finding risk variants considers data from multiple generations of a family. Hero Images/Getty Images

Asking participants in genetic databases about their family’s medical history can help researchers uncover genetic variants tied to uncommon conditions. Because people share 50 percent of their DNA with each of their parents, siblings and children, the DNA of the participants holds clues to the conditions of these relatives.

Read the full story in Spectrum.

Tasmanian devils show signs of resistance to devastating facial cancer – Nature

Jason Reed/Reuters

A contagious facial cancer that is almost always fatal has cut a wide swathe through the population of Tasmanian devils since 1996. The disease has reduced the devil population by 80%, and researchers have predicted that the cancer will drive the animals to extinction within decades. But a study published on 30 August in Nature Communications offers hope. Researchers have found that Tasmanian devils have developed some genetic resistance to the disease in just four to six generations.

Spiking genomic databases with misinformation could protect patient privacy – Nature


Large genomic databases are indispensable for scientists looking for genetic variations associated with diseases. But they come with privacy risks for people who contribute their DNA. To address those concerns, a system developed by Bonnie Berger and Sean Simmons, computer scientists at MIT, masks the donor’s identity by adding a small amount of noise, or random variation, to the results it returns on a user’s query.