Tag: genetic analysis

Categories : Diseases, Syndromes and ConditionsTags :

Oil Exploration Software Reveals why Cystic Fibrosis Drugs Fail

On By ModernMedia
Photo by WORKSITE Ltd. on Unsplash

Scientists have harnessed a computational approach usually used in oil exploration to search for cures for rare genetic diseases such cystic fibrosis. By using the method to analyse the spatial relationships between different variants of a protein, instead of the relationships between test wells across an oil field, the researchers can obtain valuable information on how disease affects a protein’s underlying shape and how drugs can restore that shape to normal.

The new method, detailed in the journal Structure, runs with just a few gene sequences collected from people with disease. Then, it determines how the structure of each corresponding variant protein is associated with its function, and how this functional structure can affect pathology and be repaired by therapeutics. To test the techniques, the researchers showed why existing drugs for cystic fibrosis fall short of curing the disease.

“This is an important step forward for treating rare diseases,” said senior author William Balch, PhD, professor of Molecular Medicine at Scripps Research. “The fact that we can get so much information from a few gene sequences is really unprecedented.”

Studies on inherited diseases often rely on the precise three-dimensional shape of a protein affected by disease. But genetic diseases can be caused by thousands of gene variants, some of which destabilise or change the protein shape in ways that make isolating the protein for further investigation much more difficult than usual.

Prof Balch, with Scripps Research senior staff scientist Chao Wang and staff scientist Frédéric Anglés, instead wanted to use natural variation to their advantage. So the group developed a method called variation-capture (VarC) mapping to analyse the natural array of gene sequences which exist in the human population and determine the mechanism by which they each changed a protein’s structure to cause disease.

Among other statistical tools, Prof Balch’s group integrated the methods that oil companies use to draw inferences about the location of an oil reservoir using only a small number of test wells. With only a few gene sequences, this let the researchers determine the most likely structural mechanisms driving function for each variant leading to disease, as well as model how drugs impacted those structural functions.

In the case of cystic fibrosis, disease is caused by genetic variants in the cystic fibrosis transmembrane conductance regulator (CFTR), leading to a buildup of mucus in the lungs. More than 2000 variants of the CFTR gene have been identified, and many of these variants were known to have very different effects on the CFTR protein, but it has been difficult to compare and contrast these variants to guide how patients with different variants should be treated differently in the clinic.

“When you want to treat patients, you really have to appreciate that different therapeutics might target different variants in completely different ways, and that’s why our approach that looks at many different variants all at once is so powerful,” explained Wang. “Our approach not only reveals how these variants contribute to each patient’s biology, but also connects them in a way that each variant can inform how to manage the others.”

The researchers input about 60 genetic variants found in the cystic fibrosis population into their VarC program. The analysis captured how each amino acid residue talks to every other residue to generate function, and revealed that most of the cystic fibrosis patients had the same net effect on the protein: an unstable inner core.

When the program modelled how existing cystic fibrosis drugs impacted the structures, the researchers discovered that, despite the drugs’ effect on CFTR structure, none of them effectively stabilised the protein’s hidden inner core. This was like how the location of an oil reservoir in a complex landscape can be revealed by test wells.

Now that the researchers better understand the structural deficiencies in CFTR in cystic fibrosis patients, they say that the job of developing an effective drug to fix it is much easier. Potential compounds can be modelled in advance of lab experiments for their effect on the inner core of the CFTR protein.

“In most drug discovery, you throw thousands of compounds at a protein and see which ones change it, often without fully understanding the mechanism,” said Prof Balch. “To fix a thing, you must first understand the problem.”

Already, his team is applying the method to other rare genetic diseases, as well as pursuing new drugs to treat cystic fibrosis.

Source: Scripps Research Institute

Categories : General Interest GeneticsTags :

Chief Sitting Bull’s DNA Matched to Living Descendant

On By ModernMedia
By Orlando Scott Goff – Heritage Auctions, Public Domain, https://commons.wikimedia.org/w/index.php?curid=27530348

A team of researchers led by the University of Cambridge has proven a man’s claim to be the great-grandson of legendary Native American leader Sitting Bull has been confirmed using DNA extracted from Sitting Bull’s scalp lock. This is the first time ancient DNA has been used to confirm a familial relationship between living and historical individuals.

The researchers used a new method to analyse family lineages using ancient DNA fragments, which searches for ‘autosomal DNA’ in the genetic fragments extracted from a body sample. Since half of our autosomal DNA is inherited from the father and half from the mother, this means genetic matches can be checked regardless of whether an ancestor is on the father or mother’s side of the family.

Autosomal DNA from Lakota Sioux leader Sitting Bull’s scalp lock was compared to DNA samples from Ernie Lapointe and other Lakota Sioux. The resulting match confirms that Lapointe is Sitting Bull’s great-grandson, and his closest living descendant.

“Autosomal DNA is our non-gender-specific DNA. We managed to locate sufficient amounts of autosomal DNA in Sitting Bull’s hair sample, and compare it to the DNA sample from Ernie Lapointe and other Lakota Sioux – and were delighted to find that it matched,” said senior author of the study, Professor Eske Willerslev in the University of Cambridge’s Department of Zoology and Lundbeck Foundation GeoGenetics Centre, who also developed the new DNA analysis technique.

Lapointe said: “over the years, many people have tried to question the relationship that I and my sisters have to Sitting Bull.”

Lapointe believes that Sitting Bull’s bones currently lie at a site in Mobridge, South Dakota, in a place that has no significant connection to Sitting Bull and the culture he represented. He also has concerns about the care of the gravesite. There are two official burial sites for Sitting Bull – at Fort Yates, North Dakota and Mobridge – and both receive visitors.

Lapointe, with the help of the DNA evidence confirming his heritage, now hopes to rebury the great Native American leader’s bones in a more appropriate location.

The new technique can be used when very limited genetic data are available, as was the case in this study. This could be used to match up long-dead historical figures and their living descendants.

The technique could also be used on old human DNA that might previously have been considered too degraded to analyse – for example in forensic investigations.

“In principle, you could investigate whoever you want – from outlaws like Jesse James to the Russian tsar’s family, the Romanovs. If there is access to old DNA – typically extracted from bones, hair or teeth, they can be examined in the same way,” said Willerslev, who is a Fellow of St John’s College, Cambridge.

It took the scientists 14 years to find a way of extracting useable DNA from the 5-6cm piece of Sitting Bull’s hair, which was extremely degraded, having been stored for over a century at room temperature in a museum before it was returned to Lapointe and his sisters in 2007.

In traditional DNA analysis, which searches for a genetic match between specific DNA in the Y chromosome passed down the male line, or, in females, specific DNA in the mitochondria passed from a mother to her offspring. Neither are particularly reliable, and in this case neither could be used as Lapointe claimed to be related to Sitting Bull on his mother’s side.

Tatanka-Iyotanka, better known as the Native American leader and military leader Sitting Bull (1831–1890), led 1,500 Lakota warriors at the Battle of the Little Bighorn in 1876 and wiped out US General Custer and five companies of soldiers.

“Sitting Bull has always been my hero, ever since I was a boy. I admire his courage and his drive. That’s why I almost choked on my coffee when I read in a magazine in 2007 that the Smithsonian Museum had decided to return Sitting Bull’s hair to Ernie Lapointe and his three sisters, in accordance with new US legislation on the repatriation of museum objects,” said Willerslev.

He added: “I wrote to Lapointe and explained that I specialised in the analysis of ancient DNA, and that I was an admirer of Sitting Bull, and I would consider it a great honour if I could be allowed to compare the DNA of Ernie and his sisters with the DNA of the Native American leader’s hair when it was returned to them.”

Until this study, the familial relationship between LaPointe and Sitting Bull was based on birth and death certificates, a family tree, and a review of historical records. This new genetic analysis lends further credence to his claims. Before the remain can be reburied, they will have to be analysed in the same to ensure a genetic match to Sitting Bull.

Before the remains from the Mobridge burial site can be reburied elsewhere, they will have to be analysed in a similar way to the hair sample to ensure a genetic match to Sitting Bull. 

Source: Cambridge University