Category Archives: Human Genetics

The Wellcome Trust Centre has deployed a high-performance computing cluster based on Fujitsu blades, Mellanox InfiniBand and DataDirect Networks storage systems to support statistical genetics research.

Designed in conjunction with OCF, a provider of high-performance computing (HPC), data management, big data storage and analytics, the cluster enables researchers to run statistical analysis on the human genome.

The hardware powers applications that analyse small genetic differences across a population of 1,000 people.

Fujitsu BX900 blade with Intel Ivy Bridge CPUs are used in the cluster, giving performance 2.6 times better than its predecessor, built in 2011.

It boasts 1,728 cores of processing power, up from the 912 of its forerunner, with 16GB of 1866MHz memory per core compared with a maximum of 8GB per core on the older cluster of the Wellcome Trust Centre for Human Genetics (WTCHG).

Robert Esnouf, head of the research computing core at WTCHG, said: If you are interested in a certain disease, you can partition the genome and analyse the genetic difference between those individuals who have a medical condition like diabetes and those that do not.

Processing power limits the number of people whose DNA makeup can be analysed statistically. But the more DNA that is analysed, the greater the accuracy of the statistical analysis.

Typically, a single human genome requires 30TB. Esnouf said that processing the DNA data of a thousand individuals requires a lot of I/O remapping.

He added: An individual may have thousands of different genetic variations. The more people you can get, the more chance you have of finding low-frequency genetic differences.

The new cluster works alongside a second production cluster; both clusters share a Mellanox FDR InfiniBand network that links the compute nodes to a DDN GridScaler SFA12K storage system whose controllers can read block data at 20Gbps. According to WTCHG this speed is essential for keeping the cluster at maximum utilisation and consistently fed with genomic data.

Follow this link:
Wellcome Trust builds 1,728-core grid for DNA analysis

In the battle against ovarian cancer, UNC School of Medicine researchers have created the first mouse model of the worst form of the disease and found a potential route to better treatments and much-needed diagnostic screens.

Led by Terry Magnuson, PhD, the Sarah Graham Kenan Professor and chair of the department of genetics, a team of UNC genetics researchers discovered how two genes interact to trigger cancer and then spur on its development.

"It's an extremely aggressive model of the disease, which is how this form of ovarian cancer presents in women," said Magnuson, who is also a member of the UNC Lineberger Comprehensive Cancer Center. Not all mouse models of human diseases provide accurate depictions of the human condition. Magnuson's mouse model, though, is based on genetic mutations found in human cancer samples.

Mutations in two genes -ARID1A and PIK3CA -- were previously unknown to cause cancer. "When ARID1A is less active than normal and PIK3CA is overactive," Magnuson said, "the result is ovarian clear cell carcinoma 100 percent of the time in our model."

The research also showed that a drug called BKM120, which suppresses PI3 kinases, directly inhibited tumor growth and significantly prolonged the lives of mice. The drug is currently being tested in human clinical trials for other forms of cancer.

The work, published in the journal Nature Communications, was spearheaded by Ron Chandler, PhD, a postdoctoral fellow in Magnuson's lab. Chandler had been studying the ARID1A gene -- which normally functions as a tumor suppressor in people -- when results from cancer genome sequencing projects showed that the ARID1A gene was highly mutated in several types of tumors, including ovarian clear cell carcinoma. Chandler began researching the gene's precise function in that disease and found that deleting it in mice did not cause tumor formation or tumor growth.

"We found that the mice needed an additional mutation in the PIK3CA gene, which acts like a catalyst of a cellular pathway important for cell growth," Chandler said. Proper cell cycle regulation is crucial for normal cell growth. When it goes awry, cells can turn cancerous.

"Our research shows why we see mutations of both ARID1A and PIK3CA in various cancers, such as endometrial and gastric cancers," Chandler said. "Too little expression of ARID1A and too much expression of PIK3CA is the perfect storm; the mice always get ovarian clear cell carcinoma. This pair of genes is really important for tumorigenesis."

Magnuson's team also found that ARID1A and PIC3CA mutations led to the overproduction of Interleukin-6, or IL-6, which is a cytokine -- a kind of protein crucial for cell signaling that triggers inflammation. "We don't know if inflammation causes ovarian clear cell carcinoma, but we do know it's important for tumor cell growth," Chandler said.

Magnuson added, "We think that IL-6 contributes to ovarian clear cell carcinoma and could lead to death. You really don't want this cytokine circulating in your body."

Read the rest here:
Researchers pinpoint two genes that trigger severest form of ovarian cancer

The evolution of human culture is often compared to biological evolution, and its easy to see why: both involve variation across a population, transmission of units from one generation to the next, and factors that ensure the survival of some variants and the death of others. However, sometimes this comparison fails. Culture, for instance, can be transmitted horizontally between members of the same generation, but genes cant.

Little is known about whether human demographic history generates patterns in linguistic data that are similar to those found in genetic data, write the authors of a recent paper in PNAS. Both linguistic and geneticdata can be used to draw conclusions about human history, but it's vital to understand how the forces affecting them differ in order to be sure that the conclusions we're drawing are accurate.

By conducting a large-scale analysis on global genetic and linguistic data, the researchers found that languages sometimes behave in ways very unlike genetics. For instance, isolated languages have more, not less, diversity, and languages don't retain the echo of a migration out of Africaunlike our genomes.

To conduct the analysis, the researchers focused on phonemes, which are the smallest linguistic units of sound that can distinguish meaning. For instance, English uses p and b to distinguish between the words pat and bat, which meansp and b act as phonemes. Other languages may not use these particular sounds to distinguish wordsor they may make finer distinctions, basing meaning differences on subtle changes like whether or not a puff of air follows the p.

Every language has a certain number of phonemes, and these phoneme inventories differ in size from language to language. The researchers compared information on global phoneme inventories with data on global genetics and geographic location in order to isolate how phonemic and genetic units track each other.

Some of their results were intuitive. They found that populations with greater geographical distance between them also had larger genetic and phonemic differences. Languages that come from the same family (like French and Italian) could be expected to have similar phoneme inventories, but the finding held true even for geographically close but historically unrelated languages.

However, some of their results were not quite as intuitive. When populations migrate, genetic diversity goes down, because thegroup thatmoves takes alongonly a portion of the gene pool of their originalpopulation. Isolated groups of people, who have no opportunity to mingle with other groups, therefore have limited genetic diversity. Language, on the other hand, shows the opposite pattern: languages with lots of close neighbors seem to be influenced by these neighbors, leading to less phonemic diversity over time. Isolated languages, on the other hand, change over the generations to become more diverse.

The most surprising finding was that, unlike genetic data, the human migration out of Africa has not left traces on modern linguistic data. This contradicts previous work in the field suggesting that, as with genetics, language diversity declines with distance from Africa, as a result of populations breaking off and moving farther away. The authors of the newpaper suggest that language changes faster than genetics, and it's less determined by the size and characteristics of a migrating population, leading to markedly different patterns in phonemic and genetic data.

This is a very interesting and important addition to the field, not only because it uses such a large database and introduces (relatively) new methods to the field, but also because of its findings, says Dr. Dan Dediu, who researches linguistics and genetics at the Max Planck Institute for Psycholinguistics in Nijmegen, The Netherlands.If its main finding survives replication with other databases and methods, then its a very powerful confirmation of the idea that demographic processes are one of the main driving forces behind both linguistic and genetic diversity."

It also highlights the fact that language and genes have different properties, especially when it comes to small, isolated communities and contact between populations, he adds.

Read the rest here:
Modern languages show no trace of our African origins

Researchers to showcase groundbreaking work in: Cellular decision-making, human accelerated regions, medical research and lineage barcodes

The Allen Distinguished Investigator program supports high-risk, high-reward ideas in science. Award recipients typically receive nearly $1 million or more for three years of research. Without the ADI program, many of these innovative research projects would go unfunded.

Monday, February 9th, Allen Distinguished Investigator awardees will gather in La Jolla, California at the Scripps Seaside Forum for an all-day symposium. It's a unique opportunity to hear how these researchers are breaking new ground and making an impact on science today and in the future.

Presentations will feature various key award focus areas.

Cellular Decision-Making:

Thierry Emonet, Yale University; Thomas Shimizu, FOM Institute for Atomic and Molecular Physics; Steven Zucker, Yale University: Crowd Computing with Bacteria: Balancing Phenotypic Diversity and Coordinated Behavior.

Hana El-Samad, University of California, San Francisco: Untangling the Wires: An Integrated Framework for Probing Signal Encoding and Decoding in Cellular Circuits.

Jeff Gore, Massachusetts Institute of Technology: Microbial Studies of Cellular Decision-making: Game Theory and the Evolutionary Origins of Cooperation.

Suckjoon Jun, University of California, San Diego: Cell-Size Control and its Evolution at the Single-Cell Level.

Human Accelerated Regions:

Link:
Inaugural Allen Distinguished Investigator Life Science Symposium

There's a good reason why wolves became human companions long before domestic breeding turned them into everything from Great Danes to poodles, scientists in Vienna say.

They wanted to be our friends because underneath that furry hide they were a lot like us.

For several years, researchers at Vienna's University of Veterinary Medicine have been studying wolves that have been raised in captivity just like domesticated dogs, to see how they differ from the canine pets that are in so many of our homes. They have even established the Clever Dog Lab and the Wolf Science Center.

In a study published in the journal Frontiers in Psychology, researchers Friederike Range and Zsofia Viranyi offer their "Canine Cooperation Hypothesis."

According to the hypothesis, ancient wolves already possessed at least three social skills that made them suitable for human companionship: They were tolerant, attentive and cooperative.

Just like dogs.

And they were very social, running in packs, just like humans.

In the latest in a series of experiments, the researchers found that wolves can learn if a human has food, where it is stashed, and even if the human is just fooling.

If the human hid it behind a shed, the wolf went right to it, apparently because it had observed the human's actions. Dogs that participated in the same experiment were more likely to sniff their way to the food, not relying as much on their powers of observation.

Getty Images

See the original post:
Why Wolves Became Dogs

Oldowan choppers dating to 1.7 million years ago, from Melka Kunture, Ethiopia.

Its widely understood that human genetics can influence culture, but increasingly, the idea that culture can also affect genetics is gaining ground. The theory of gene-culture coevolution suggests that the cultural practices we adopt change the costs and benefits of having certain genes, explains Catharine Cross, a researcher at the University of St Andrews. A gene that is advantageous under one cultural practice is not necessarily advantageous under another.

For example, yam cultivation in West Africa led to deforestation and an increase in standing water, which creates a breeding ground for mosquitoes and malaria. This meant that yam farmers with a particular genetic resistance to malaria were more likely to survive than farmers with susceptibility to malaria. Yam farmers in the region have been found to have a higher incidence of this genetic trait than nearby groupseven speakers of the same languagewho farm other crops.

A recent study published in Nature Communications has suggested that stone tool-making practices among the ancestors of modern humans may have put evolutionary pressure on individuals who werent very good at communicating, helping to select for the genes that would become involved in language.The study found that the use of verbal teaching, compared to learning by imitation, significantly improved the quality and speed production of stone tools. This suggests that individuals with gestural or verbal communication skills could have learned to make tools faster and better, giving them an advantage over individuals who could only imitate.

The researchers tested the difference in performance by using transmission chains, a method similar to the childrens game of telephone. The person who starts a chain passes on information to the next person, who then passes that information along, all the way down the chain. This can provide insight into how information changes when it is passed through generations of people.

In this case, the information being passed down the chain was the technique of creating Oldowan stone tools. These were the first stone tools to appear in the fossil record, approximately 2.5 million years ago, and were the predominant technology for approximately 700,000 years until more advanced Acheulean stone tools started to appear.

The first person in each chain was an experimenter skilled in the Oldowan method of hammering sharp flakes of flint off a central core. This person could pass information down the transmission chain in one of five ways. The first method, pure imitation, involved the teacher simply making the tools while the first participant watched, with no interaction.Three of the five transmission methods involved some sort of interaction: basic teaching, which allowed the teacher to slow their movements down or shape the participants grip; gestural teaching, which added in gestures; or verbal teaching, which allowed normal speech.Finally, the fifth method allowed the participant no contact at all with the teacherrather, they had to work out how to make the tools just by looking at examples produced by the teacher.

After a short learning period, the participant was required to pass on their new skills to the next participant in the chain using the same transmission method. Participants were paid more if they and their pupils produced more, higher-quality tools, so there was a strong motivation to learn and teach well. Each learning condition had six transmission chains, with 184 participants overall.

The results indicated that learning through teaching, rather than reverse engineering or imitation, had a marked influence on the results. Participants who experienced active instruction from their teachers produced more, better quality flakes at a higher speed, with fewer mistakes. Unsurprisingly, verbal instruction produced the best results, followed by gestural instruction and then basic teaching.

The results are important, write the researchers, because they help us to understand the language could have played inhuman ancestors during the period when Oldowan tools were in use. Its unlikely that Oldowan tools would have remained unchanged for 700,000 years if language had already emerged, they write. Thissuggests that imitation, which doesn't transmit information as efficiently, helped to maintain this long period of stasis. However, it also seems that individuals with better communicative abilities may have had better success at tool-making, contributing to the pressures that led to the evolution of language, and more advanced Acheulean tools.

Visit link:
Tool-making may have made language genes more useful

Introduction to Human Genetics- for medical students
This video lecture includes the definition of human genetics, its different branches, history, common terminologies, principle of human genetics, definition ...

By: Janak Lecture Series

Visit link:
Introduction to Human Genetics- for medical students - Video

In a significant finding, an international team of scientists has discovered five genetic variants that influence the size of structures within the human brain.

They evaluated genetic data from seven subcortical brain regions and intracranial volume from MRI scans.

This is the largest analysis of brain structure and genetics ever done.

"Through a large-scale, international data sharing and data-analysis-sharing effort, we were able to actually successfully identify genetic effects on the hippocampus, putamen and other brain regions that no one had ever successfully identified genetics effects on before," said Jessica Turner, associate professor of psychology and neuroscience at Georgia State University.

Their goal was to determine how common genetic variants affect the structure of these seven subcortical brain regions, which are associated with memory, movement, learning and motivation.

Changes in these brain areas can lead to abnormal behaviour and predisposition to disease.

Previous research showed that the brain's structure was strongly shaped by genetic influences. Identifying genetic variants could provide insight into the causes for variation in human brain development and help to determine how dysfunction in the brain occurs.

"Those are brain regions that we know are involved in various psychiatric and neurodegenerative disorders. In trying to figure out the genetics that make them either larger or smaller, it could have great benefits for understanding mechanisms of these disorders," Turner concluded.

Their findings were published in the journal Nature.

Read this article:
Top Stories

Science has helped us understand how blue eyes or baldness as well as other inherited traits both harmless and harmful can run in a family. In the past few decades, largely due to the Human Genome Project and other scientific endeavors, knowledge has exploded in the field of human genetics.

Genetic services available in New Jersey include direct clinical care services as well as activities such as screening programs and laboratory services, educational activities and birth defects surveillance. The State of New Jersey partially funds a network of Genetic Centers [see the list at bottom of page] that provide testing, diagnosis, and ongoing management and comprehensive care of genetic conditions. Physicians specially trained in medical genetics, along with genetic counselors, nurses, social workers and other medical specialists provide comprehensive care to patients with genetic concerns.

Services may include some or all of the following: a review of your family and medical history; physical examination; laboratory testing; genetic counseling/education; and management or referral to other specialists experienced in treating or managing rare disorders. These services can provide information on certain disorders that you or your child may have inherited, how genetic conditions may be passed from one generation to another in a family, and what the risks are that certain conditions will affect you, your present or future pregnancies, or other members of your family.

Genetic counseling translates the science of genetics into practical information. Anyone who has unanswered questions about diseases or traits in their family should consider genetic counseling. People who might be especially interested are:

Resources:

American College of Medical Genetics (ACMG) http://www.acmg.net

Genetic Alliance http://www.geneticalliance.org/

Genetics Home Reference http://ghr.nlm.nih.gov/

Human Genetics Association of New Jersey (HGANJ) http://www.hganj.org

National Newborn Screening & Genetic Resource Center (NNSGRC) http://genes-r-us.uthscsa.edu/

Continued here:
NJDOH - New Born Screening & Genetic Services

ATLANTA--Five genetic variants that influence the size of structures within the human brain have been discovered by an international team that included a Georgia State University researcher.

Their findings were reported this week in the journal Nature.

In the study led by Drs. Sarah Medland, Margie Wright, Nick Martin and Paul Thompson of the QIMR Berghofer Medical Research Institute in Australia, nearly 300 researchers analyzed genetic data and magnetic resonance imaging (MRI) scans from 30,717 individuals from around the world. They evaluated genetic data from seven subcortical brain regions (nucleus accumbens, caudate, putamen, pallidum, amygdala, hippocampus and thalamus) and intracranial volume from MRI scans.

This is the largest analysis of brain structure and genetics ever done, said Dr. Jessica Turner, associate professor of psychology and neuroscience at Georgia State, who organized some of the teams collecting and evaluating data from participants with schizophrenia.

The goal was to determine how common genetic variants affect the structure of these seven subcortical brain regions, which are associated with memory, movement, learning and motivation. Changes in these brain areas can lead to abnormal behavior and predisposition to disease.

Previous research has shown the brain's structure is strongly shaped by genetic influences. Identifying genetic variants could provide insight into the causes for variation in human brain development and help to determine how dysfunction in the brain occurs.

"The team looked at several million base pairs or locations on the human genome," Turner said. "Through a large-scale, international data sharing and data-analysis-sharing effort, we were able to actually successfully identify genetic effects on the hippocampus, putamen and other brain regions that no one had ever successfully identified genetics effects on before."

The researchers discovered five new genetic variants that influenced the volumes of the putamen and caudate nucleus. They also found stronger evidence for three locations in the genome that influence the size of the hippocampus and intracranial areas of the brain. The strongest genetic effects were observed for the putamen.

"Those are brain regions," Turner said, "that we know are involved in various psychiatric and neurodegenerative disorders. In trying to figure out the genetics that make them either larger or smaller, it could have great benefits for understanding mechanisms of these disorders."

###

See the original post here:
Researchers discover genetic links to size of brain structures