̽��ֱ�� of Cambridge - genetic sequencing

̽��ֱ��sequencing of COVID-19

fpjl2 — Fri, 17 Apr 2020 07:20:04 +0000

Labs across the country have converted to the genetic sequencing of coronavirus samples to help track its mutation and spread. ̽��ֱ��initiative, COG-UK, is being led by Cambridge. We spoke to one of the scientists lending their time and expertise.

Genetic study suggests present-day Lebanese descend from biblical Canaanites

fpjl2 — Thu, 27 Jul 2017 16:02:17 +0000

Scientist have sequenced the entire genomes of 4,000-year-old Canaanite individuals who inhabited the Near East region during the Bronze Age, and compared these to other ancient and present-day populations. ̽��ֱ��results, published in the American Journal of Human Genetics, suggest that present-day Lebanese are direct descendants of the ancient Canaanites.

̽��ֱ��Near East is often described as the cradle of civilisation. ̽��ֱ��Bronze Age Canaanites, later known as the Phoenicians, introduced many aspects of society that we know today - they created the first alphabet, established colonies throughout the Mediterranean and were mentioned several times in the Bible.

However, historical records of the Canaanites are limited. They were mentioned in ancient Greek and Egyptian texts, and the Bible which reports widespread destruction of Canaanite settlements and annihilation of the communities. Experts have long debated who the Canaanites were genetically, what happened to them, who their ancestors were and if they had any descendants today.

In the first study of its kind, an international team of scientists have uncovered the genetics of the Canaanite people and a firm link with people living in Lebanon today. ̽��ֱ��team discovered that more than 90 per cent of present-day Lebanese ancestry is likely to be from the Canaanites, with an additional small proportion of ancestry coming from a different Eurasian population.

̽��ֱ��team, including researchers from Cambridge ̽��ֱ��’s Department of Archaeology and Anthropology, and led by the Wellcome Trust Sanger Institute, estimate that new Eurasian people mixed with the Canaanite population about 2,200 to 3,800 years ago at a time when there were many conquests of the region from outside.

̽��ֱ��analysis of ancient DNA also revealed that the Canaanites themselves were a mixture of local people who settled in farming villages during the Neolithic period and eastern migrants who arrived in the area around 5,000 years ago.

"Ancient DNA is becoming an indispensable tool for understanding population movements of the past. This study in particular provides previously inaccessible information about a group of people known only by surviving written accounts and interpretations of archaeological findings,” said Dr. C L Scheib, one of two Cambridge co-authors, along with Dr Toomas Kivisild.

“ ̽��ֱ��fact that we can retrieve whole genomes from conditions not considered ideal for DNA preservation also shows how far the field has advanced technically," she said.

In the study, researchers sequenced whole genomes of five Canaanite individuals who lived 4,000 years ago in a city known as Sidon in present-day Lebanon. Scientists also sequenced the genomes of 99 present-day Lebanese and analysed the genetic relationship between the ancient Canaanites and modern Lebanese.

Dr Marc Haber, first author from the Sanger Institute, said: “It was a pleasant surprise to be able to extract and analyse DNA from 4,000-year-old human remains found in a hot environment, which is not known for preserving DNA well. We overcame this challenge by taking samples from the petrous bone in the skull, which is a very tough bone with a high density of ancient DNA.”

Dr Claude Doumet-Serhal, co-author and Director of the Sidon excavation site in Lebanon, said: “For the first time we have genetic evidence for substantial continuity in the region, from the Bronze Age Canaanite population through to the present day. These results agree with the continuity seen by archaeologists.

“Collaborations between archaeologists and geneticists greatly enrich both fields of study and can answer questions about ancestry in ways that experts in neither field can answer alone.”

Adapted from a Wellcome Trust press release.

Researchers analysed DNA extracted from 4,000-year-old human remains to reveal that more than 90% of Lebanese ancestry is from ancient Canaanite populations.

̽��ֱ��fact that we can retrieve whole genomes from conditions not considered ideal for DNA preservation also shows how far the field has advanced technically

C.L Scheib

Wellcome Genome Campus Public Engagement

Cambridge co-author C.L Scheib conducting ancient bone analysis at the Wellcome Genome Campus.

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. For image use please see separate credits above.

Yes

Ancient DNA reveals 'genetic continuity’ between Stone Age and modern populations in East Asia

fpjl2 — Wed, 01 Feb 2017 19:04:57 +0000

Researchers working on ancient DNA extracted from human remains interred almost 8,000 years ago in a cave in the Russian Far East have found that the genetic makeup of certain modern East Asian populations closely resemble that of their hunter-gatherer ancestors.

̽��ֱ��study, published today in the journal Science Advances, is the first to obtain nuclear genome data from ancient mainland East Asia and compare the results to modern populations.

̽��ֱ��findings indicate that there was no major migratory interruption, or “population turnover”, for well over seven millennia. Consequently, some contemporary ethnic groups share a remarkable genetic similarity to Stone Age hunters that once roamed the same region.

̽��ֱ��high “genetic continuity” in East Asia is in stark contrast to most of Western Europe, where sustained migrations of early farmers from the Levant overwhelmed hunter-gatherer populations. This was followed by a wave of horse riders from Central Asia during the Bronze Age. These events were likely driven by the success of emerging technologies such as agriculture and metallurgy

̽��ֱ��new research shows that, at least for part of East Asia, the story differs – with little genetic disruption in populations since the early Neolithic period.

Despite being separated by a vast expanse of history, this has allowed an exceptional genetic proximity between the Ulchi people of the Amur Basin, near where Russia borders China and North Korea, and the ancient hunter-gatherers laid to rest in a cave close to the Ulchi’s native land.

̽��ֱ��researchers suggest that the sheer scale of East Asia and dramatic variations in its climate may have prevented the sweeping influence of Neolithic agriculture and the accompanying migrations that replaced hunter-gatherers across much of Europe. They note that the Ulchi retained their hunter-fisher-gatherer lifestyle until recent times.

“Genetically speaking, the populations across northern East Asia have changed very little for around eight millennia,” said senior author Andrea Manica from the ̽��ֱ�� of Cambridge, who conducted the work with an international team, including colleagues from Ulsan National Institute of Science and Technology in Korea, and Trinity College Dublin and ̽��ֱ�� College Dublin in Ireland.

“Once we accounted for some local intermingling, the Ulchi and the ancient hunter-gatherers appeared to be almost the same population from a genetic point of view, even though there are thousands of years between them.”

̽��ֱ��new study also provides further support for the ‘dual origin’ theory of modern Japanese populations: that they descend from a combination of hunter-gatherers and agriculturalists that eventually brought wet rice farming from southern China. A similar pattern is also found in neighbouring Koreans, who are genetically very close to Japanese.

However, Manica says that much more DNA data from Neolithic China is required to pinpoint the origin of the agriculturalists involved in this mixture.

̽��ֱ��team from Trinity College Dublin were responsible for extracting DNA from the remains, which were found in a cave known as Devil’s Gate. Situated in a mountainous area close to the far eastern coast of Russia that faces northern Japan, the cave was first excavated by a soviet team in 1973.

Along with hundreds of stone and bone tools, the carbonised wood of a former dwelling, and woven wild grass that is one of the earliest examples of a textile, were the incomplete bodies of five humans.

If ancient DNA can be found in sufficiently preserved remains, sequencing it involves sifting through the contamination of millennia. ̽��ֱ��best samples for analysis from Devil’s Gate were obtained from the skulls of two females: one in her early twenties, the other close to fifty. ̽��ֱ��site itself dates back over 9,000 years, but the two women are estimated to have died around 7,700 years ago.

Researchers were able to glean the most from the middle-aged woman. Her DNA revealed she likely had brown eyes and thick, straight hair. She almost certainly lacked the ability to tolerate lactose, but was unlikely to have suffered from ‘alcohol flush’: the skin reaction to alcohol now common across East Asia.

While the Devil’s Gate samples show high genetic affinity to the Ulchi, fishermen from the same area who speak the Tungusic language, they are also close to other Tungusic-speaking populations in present day China, such as the Oroqen and Hezhen.

“These are ethnic groups with traditional societies and deep roots across eastern Russia and China, whose culture, language and populations are rapidly dwindling,” added lead author Veronika Siska, also from Cambridge.

“Our work suggests that these groups form a strong genetic lineage descending directly from the early Neolithic hunter-gatherers who inhabited the same region thousands of years previously.”

In contrast to Western Europeans, new research finds contemporary East Asians are genetically much closer to the ancient hunter-gatherers that lived in the same region eight thousand years previously.

̽��ֱ��Ulchi and the ancient hunter-gatherers appeared to be almost the same population from a genetic point of view, even though there are thousands of years between them

Andrea Manica

Elizaveta Veselovskaya/Yuriy Chernyavskiy

Right: Exterior of Devil’s Gate, the cave in the Primorye region near the far eastern coast of Russia. Left: One of the skulls found in the Devil’s Gate cave from which ancient DNA used in the study was extracted.

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. For image use please see separate credits above.

Yes

Algorithm for predicting protein pairings could help show how living systems work

sc604 — Tue, 20 Sep 2016 08:00:00 +0000

Researchers have developed an algorithm that aids our understanding of how living systems work, by identifying which proteins within cells will interact with each other, based on their genetic sequences alone.

̽��ֱ��ability to generate huge amounts of data from genetic sequencing has developed rapidly in the past decade, but the trouble for researchers is in being able to apply that sequence data to better understand living systems. ̽��ֱ��new research, published in the journal Proceedings of the National Academy of Sciences, is a significant step forward because biological processes, such as how our bodies turn food into energy, are driven by specific protein-protein interactions.

“We were really surprised that our algorithm was powerful enough to make accurate predictions in the absence of experimentally-derived data,” said study co-author Dr Lucy Colwell, from the ̽��ֱ�� of Cambridge’s Department of Chemistry, who led the study with Ned Wingreen of Princeton ̽��ֱ��. “Being able to predict these interactions will help us understand how proteins fit and work together to complete required tasks – and using an algorithm is much faster and much cheaper than relying on experiments.”

When proteins interact with each other, they stick together to form protein complexes. In her previous research, Colwell found that if the two interacting proteins were known, sequence data could be used to figure out the structure of these complexes. Once the structure of the complexes is known, researchers can then investigate what is happening chemically. However, the question of which proteins interact with each other still required expensive, time-consuming experiments. Each cell often contains multiple versions of the same protein, and it wasn’t possible to predict which version of each protein would interact specifically – instead, experiments involve trying all options to see which ones stick.

In the current paper, the researchers used a mathematical algorithm to sift through the possible interaction partners and identify pairs of proteins that interact with each other. ̽��ֱ��method correctly predicted 93% of protein-protein interactions present in a dataset of more than 40,000 protein sequences for which the pairing is known, without being first provided any examples of correct pairs.

When two proteins stick together, some amino acids on one chain stick to the amino acids on the other chain. ̽��ֱ��boundaries between interacting proteins tend to evolve together over time, causing their sequences to mirror each other.

̽��ֱ��algorithm uses this effect to build a model of the interaction. It first randomly pairs protein versions within each organism – because interacting pairs tend to be more similar in sequence to one another than non-interacting pairs, the algorithm can quickly identify a small set of largely correct pairings from the random starting point.

Using this small set, the algorithm measures whether the amino acid at a particular location in the first protein influences which amino acid occurs at a particular location in the second protein. These dependencies, learned from the data, are incorporated into a model and used to calculate the interaction strengths for each possible protein pair. Low-scoring pairings are eliminated, and the remaining set used to build an updated model.

̽��ֱ��researchers thought that the algorithm would only work accurately if it first ‘learned’ what makes a good protein-protein pair by studying pairs that have been discovered in experiments. This meant that the researchers had to give the algorithm some known protein pairs, or ‘gold standards,’ against which to compare new sequences. ̽��ֱ��team used two well-studied families of proteins, histidine kinases and response regulators, which interact as part of a signaling system in bacteria.

But known examples are often scarce, and there are tens of millions of undiscovered protein-protein interactions in cells. So the team decided to see if they could reduce the amount of training they gave the algorithm. They gradually lowered the number of known histidine kinase-response regulator pairs that they fed into the algorithm, and were surprised to find that the algorithm continued to work. Finally, they ran the algorithm without giving it any such training pairs, and it still predicted new pairs with 93 percent accuracy.

“ ̽��ֱ��fact that we didn't need a set of training data was really surprising,” said Colwell.

̽��ֱ��algorithm was developed using proteins from bacteria, and the researchers are now extending the technique to other organisms. “Reactions in living organisms are driven by specific protein interactions,” said Colwell. “This approach allows us to identify and probe these interactions, an essential step towards building a picture of how living systems work.”

̽��ֱ��research was supported in part by the National Institutes of Health, the National Science Foundation and the European Union.

Reference:
Anne-Florence Bitbol et al. ‘Inferring interaction partners from protein sequences.’ Proceedings of the National Academy of Sciences (2016). DOI: 10.1073/pnas.1606762113

An algorithm which models how proteins inside cells interact with each other will enhance the study of biology, and sheds light on how proteins work together to complete tasks such as turning food into energy.

Being able to predict these interactions will help us understand how proteins fit and work together to complete required tasks.

Lucy Colwell

Interacting proteins

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. For image use please see separate credits above.

Yes

‘Fourth strand’ of European ancestry originated with hunter-gatherers isolated by Ice Age

fpjl2 — Mon, 16 Nov 2015 10:33:13 +0000

̽��ֱ��first sequencing of ancient genomes extracted from human remains that date back to the Late Upper Palaeolithic period over 13,000 years ago has revealed a previously unknown “fourth strand” of ancient European ancestry.

This new lineage stems from populations of hunter-gatherers that split from western hunter-gatherers shortly after the ‘out of Africa’ expansion some 45,000 years ago and went on to settle in the Caucasus region, where southern Russia meets Georgia today.

Here these hunter-gatherers largely remained for millennia, becoming increasingly isolated as the Ice Age culminated in the last ‘Glacial Maximum’ some 25,000 years ago, which they weathered in the relative shelter of the Caucasus mountains until eventual thawing allowed movement and brought them into contact with other populations, likely from further east.

This led to a genetic mixture that resulted in the Yamnaya culture: horse-borne Steppe herders that swept into Western Europe around 5,000 years ago, arguably heralding the start of the Bronze Age and bringing with them metallurgy and animal herding skills, along with the Caucasus hunter-gatherer strand of ancestral DNA – now present in almost all populations from the European continent.

̽��ֱ��research was conducted by an international team led by scientists from Cambridge ̽��ֱ��, Trinity College Dublin and ̽��ֱ�� College Dublin. ̽��ֱ��findings are published today in the journal Nature Communications.

“ ̽��ֱ��question of where the Yamnaya come from has been something of a mystery up to now,” said one of the lead senior authors Dr Andrea Manica, from Cambridge’s Department of Zoology.

“We can now answer that as we’ve found that their genetic make-up is a mix of Eastern European hunter-gatherers and a population from this pocket of Caucasus hunter-gatherers who weathered much of the last Ice Age in apparent isolation. This Caucasus pocket is the fourth major strand of ancient European ancestry, one that we were unaware of until now,” he said

Professor Daniel Bradley, leader of the Trinity team, said: “This is a major new piece in the human ancestry jigsaw, the influence of which is now present within almost all populations from the European continent and many beyond.”

Previously, ancient Eurasian genomes had revealed three ancestral populations that contributed to contemporary Europeans in varying degrees, says Manica.

Following the ‘out of Africa’ expansion, some hunter-gatherer populations migrated north-west, eventually colonising much of Europe from Spain to Hungary, while other populations settled around the eastern Mediterranean and Levant, where they would develop agriculture around 10,000 years ago. These early farmers then expanded into and colonised Europe.

Lastly, at the start of the Bronze Age around 5,000 years ago, there was a wave of migration from central Eurasia into Western Europe – the Yamnaya.

However, the sequencing of ancient DNA recovered from two separate burials in Western Georgia – one over 13,000 years old, the other almost 10,000 years old – has enabled scientists to reveal that the Yamnaya owed half their ancestry to previously unknown and genetically distinct hunter-gatherer sources: the fourth strand.

By reading the DNA, the researchers were able to show that the lineage of this fourth Caucasus hunter-gatherer strand diverged from the western hunter-gatherers just after the expansion of anatomically modern humans into Europe from Africa.

̽��ֱ��Caucasus hunter-gatherer genome showed a continued mixture with the ancestors of the early farmers in the Levant area, which Manica says makes sense given the relative proximity. This ends, however, around 25,000 years ago – just before the time of the last glacial maximum, or peak Ice Age.

At this point, Caucasus hunter-gatherer populations shrink as the genes homogenise, a sign of breeding between those with increasingly similar DNA. This doesn’t change for thousands of years as these populations remain in apparent isolation in the shelter of the mountains – possibly cut off from other major ancestral populations for as long as 15,000 years – until migrations began again as the Glacial Maximum recedes, and the Yamnaya culture ultimately emerges.

“We knew that the Yamnaya had this big genetic component that we couldn’t place, and we can now see it was this ancient lineage hiding in the Caucasus during the last Ice Age,” said Manica.

While the Caucasus hunter-gatherer ancestry would eventually be carried west by the Yamnaya, the researchers found it also had a significant influence further east. A similar population must have migrated into South Asia at some point, says Eppie Jones, a PhD student from Trinity College who is the first author of the paper.

“India is a complete mix of Asian and European genetic components. ̽��ֱ��Caucasus hunter-gatherer ancestry is the best match we’ve found for the European genetic component found right across modern Indian populations,” Jones said. Researchers say this strand of ancestry may have flowed into the region with the bringers of Indo-Aryan languages.

̽��ֱ��widespread nature of the Caucasus hunter-gatherer ancestry following its long isolation makes sense geographically, says Professor Ron Pinhasi, a lead senior author from ̽��ֱ�� College Dublin. “ ̽��ֱ��Caucasus region sits almost at a crossroads of the Eurasian landmass, with arguably the most sensible migration routes both west and east in the vicinity.”

He added: “ ̽��ֱ��sequencing of genomes from this key region will have a major impact on the fields of palaeogeneomics and human evolution in Eurasia, as it bridges a major geographic gap in our knowledge.”

David Lordkipanidze, Director of the Georgian National Museum and co-author of the paper, said: “This is the first sequence from Georgia – I am sure soon we will get more palaeogenetic information from our rich collections of fossils.”

Inset image: the view from the Satsurblia cave in Western Georgia, where a human right temporal bone dating from over 13,000 years ago was discovered. DNA extracted from this bone was used in the new research.

Reference:
E.R. Jones et. al. ‘Upper Palaeolithic genomes reveal deep roots of modern Eurasians.’ Nature Communications (2015). DOI: 10.1038/ncomms9912

Populations of hunter-gatherers weathered Ice Age in apparent isolation in Caucasus mountain region for millennia, later mixing with other ancestral populations, from which emerged the Yamnaya culture that would bring this Caucasus hunter-gatherer lineage to Western Europe.

This Caucasus pocket is the fourth major strand of ancient European ancestry, one that we were unaware of until now

Andrea Manica

Eppie Jones

DNA was extracted from the molar teeth of this skeleton, dating from almost 10,000 years ago and found in the Kotias Klde rockshelter in Western Georgia.

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. For image use please see separate credits above.

Yes

Cambridge partners with India to fight multidrug resistant TB

Anonymous — Fri, 13 Feb 2015 16:30:42 +0000

̽��ֱ��Cambridge-Chennai Centre Partnership on Antimicrobial Resistant Tuberculosis will bring together a multidisciplinary team of international researchers, and will be led by Professor Sharon Peacock and Dr Soumya Swaminathan. ̽��ֱ��team, including Professors Lalita Ramakrishnan, Ken Smith, Tom Blundell and Andres Floto, will focus on developing new diagnostic tools and treatments to address the sharp rise in cases of multidrug resistant tuberculosis (TB).

This will include research into:

the use of emerging sequence-based diagnostics to improve the accuracy of individual patient treatment for drug resistant TB
predicting the impact of genetic mutations on drug resistance based on modelling of bacterial genome data
the development of an in-depth understanding of bacterial genes associated with so-called ‘drug-tolerance’, where the drug’s ability to kill the bacteria gradually weakens
novel approaches to treatment of TB based on enhancing the body’s immune system to enable it to fight infection.

̽��ֱ��partnership will generate a rich and lasting clinical and genomic dataset for studying TB, and the transfer of scientific training and technology will foster future international collaborative projects.

“I am delighted that Cambridge has been given the opportunity to work on a disease of global importance through the development of this partnership,” said Professor Sharon Peacock. “Chennai was the site for many of the early MRC-funded TB treatment trials, and the chance to explore new therapies and diagnostics to improve patient outcome through the use of state-of-the-art technologies represents an exciting opportunity.”

̽��ֱ��funding is part of a landmark collaboration between the MRC and the Government of India DBT. Nearly £3.5million will be invested by the UK, through the MRC and the Newton Fund, a new initiative intended to strengthen research and innovation partnerships between the UK and emerging knowledge economies, with matched funding provided by DBT.

Prof K. VijayRaghavan, Secretary, Department of Biotechnology added: “ ̽��ֱ��Department of Biotechnology, Government of India is delighted to partner with the MRC in creating research centres which will address vexing challenges in medicine through quality science and collaboration. India is committed to working with the best in the world, for India and for the world. We are acutely aware that the fruits of our partnership can mean better lives for the most- needy everywhere and are committed to make the collaboration succeed.”

̽��ֱ�� ̽��ֱ�� of Cambridge has been awarded £2 million from the UK Medical Research Council and the Government of India’s Department for Biotechnology to develop a partnership with the National Institute for Research in Tuberculosis (NIRT) in Chennai.

I am delighted that Cambridge has been given the opportunity to work on a disease of global importance through the development of this partnership

Sharon Peacock

CDC/ Melissa Brower

This illustration depicts a three-dimensional (3D) computer-generated image of a cluster of rod-shaped drug-resistant Mycobacterium tuberculosis bacteria, the pathogen responsible for causing the disease tuberculosis (TB). ̽��ֱ��artistic recreation was base

̽��ֱ��text in this work is licensed under a Creative Commons Licence. If you use this content on your site please link back to this page. For image rights, please see the credits associated with each individual image.

Yes