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Looking for study/genome data for HIV in different organs

Looking for study/genome data for HIV in different organs



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I am looking for a research study or data base that has HIV genome data available in fasta or similar format. Specifically I need genome data of HIV taken from different organs in the same subject. I am interested in studying the way HIV diversifies and changes to infect different organs and in comparing the process across different patients.

If you are familiar with such a study, or if you have general pointers as to where I may find similar data, I would appreciate it very much. I have done a few hours of searching on NCBI GeneBank, but have had no luck.

Thanks!


This website comes to my mind

https://www.hiv.lanl.gov/content/index

It is a HIV databases containing HIV sequence data and related immunologic information


Model organism

A model organism (often shortened to model) is a non-human species that is extensively studied to understand particular biological phenomena, with the expectation that discoveries made in the model organism will provide insight into the workings of other organisms. [1] [2] Model organisms are widely used to research human disease when human experimentation would be unfeasible or unethical. [3] This strategy is made possible by the common descent of all living organisms, and the conservation of metabolic and developmental pathways and genetic material over the course of evolution. [4]

Studying model organisms can be informative, but care must be taken when generalizing from one organism to another. [5] [ page needed ]

In researching human disease, model organisms allow for better understanding the disease process without the added risk of harming an actual human. The species chosen will usually meet a determined taxonomic equivalency [ clarification needed ] to humans, so as to react to disease or its treatment in a way that resembles human physiology as needed. Although biological activity in a model organism does not ensure an effect in humans, many drugs, treatments and cures for human diseases are developed in part with the guidance of animal models. [6] [7] There are three main types of disease models: homologous, isomorphic and predictive. Homologous animals have the same causes, symptoms and treatment options as would humans who have the same disease. Isomorphic animals share the same symptoms and treatments. Predictive models are similar to a particular human disease in only a couple of aspects, but are useful in isolating and making predictions about mechanisms of a set of disease features. [8]


The 1000 Genomes Project more than doubles catalog of human genetic variation

Genetic variation explains part of why people look different and vary in their risk for diseases. The goal of the 1000 Genomes Project is to identify and compile variants in the human genome that occur at a frequency of at least 1 in 50 people. Although most of these genetic variants cause little if any effect, some contribute to disease, and others are beneficial. An example of a beneficial difference is a rare genetic variant that blocks the human immunodeficiency virus from infecting white blood cells and, thus, protects people exposed to HIV who carry this variant. "

The 1000 Genomes Project is a large, international effort aiming to characterize human genetic variation, including people from many different populations," said Eric D. Green, M.D., Ph.D., NHGRI director. "The newly published findings provide deeper insights about the presence and pattern of variants in different people's genomes, which is critical information for studying the genomic basis of human disease."

The expanded catalog allows medical researchers to locate genetic differences contributing to rare and common diseases more precisely. Identifying the genetic underpinnings of disease will help lead to new diagnostic tests and, in some cases, treatments.

"I view this project as a Lewis and Clark expedition to the interior of the human genome," said Stephen Sherry, Ph.D., chief of the Reference Collections Section, Information Engineering Branch at the National Center for Biotechnology Information (NCBI), part of the National Library of Medicine. "We knew the outlines and contours (of the genome). Now, we're trying to document all the fine details such as the rivers and tributaries."

So far, project researchers have sequenced the genomes of 1,092 people from 14 populations in Europe, East Asia, sub-Saharan Africa and the Americas. Ultimately, they will study more than 2,500 individuals from 26 populations.

All of the participants consented to inclusion, in an open online database, of sequence data derived from their anonymous DNA samples. Each part of these genomes were read (or sequenced) an average of six times, which provides accurate information about common genetic variants but misses many rare variants.

To identify rare variants in the exome, the part of the genome that codes for proteins, the researchers sequenced the exons of 15,000 genes in each genome an average of 80 times. The study discovered 99.8 percent of exome variants with a frequency of at least 1 percent and 99.3 percent of variants elsewhere in the genome with a frequency of at least 1 percent.

Phase one of the 1000 Genomes Project, the subject of the Nature paper, has produced a massive amount of genomic data. Simply recording the raw information takes some 180 terabytes of hard-drive space, enough to fill more than 40,000 DVDs. All of the information is freely available on the Internet through public databases such as ones at the National Center for Biotechnology Information at the U.S. National Library of Medicine in Bethesda, Md., and the European Bioinformatics Institute in Hinxton, England. Data from the project have been available to researchers since 2008. The massive dataset became available in the cloud this year via Amazon Web Services (AWS). Cloud access enables users to analyze large amounts of the data much more quickly, as it eliminates the time-consuming download of data and because users can run their analyses over many servers at once. Researchers pay only for the additional AWS resources they need to further process or analyze the data.

"With this project, we have succeeded in making sure that information about our shared genetic heritage, and the common DNA variants we carry, are freely available for researchers to use to benefit patients around the world," said David Altshuler, M.D., Ph.D., an endocrinologist at Massachusetts General Hospital who directs the Broad Institute's Program in Medical and Population Genetics, and who co-leads the 1000 Genomes Project. "Moreover, the tools and methods that this project has helped foster are being used now in disease-oriented genetics research and will be used increasingly in clinical care."

All the genetic information for making an organism resides in the DNA, which is a set of long molecules made of units called bases. Each base is a chemical unit abbreviated A, C, G or T. For this paper, the researchers identified 38 million single-nucleotide polymorphisms, or SNPs (pronounced "snips"), which are DNA variants that occur when a particular basein the genome sequence differs among people.

These variants are the most common genetic differences among people. Each SNP is like a landmark, reflecting a specific position in the genome where the DNA spelling differs by one letter among people.

They also identified variants in the linear structure of the DNA, including 1.4 million short indels (insertions or deletions of DNA as small as a single base or as large as 50 bases) and 14,000 large deletions of DNA.

SNPs and structural variants can help explain an individual's susceptibility to disease, response to drugs, or reaction to environmental factors such as air pollution or stress. Other studies have found an elevated rate of indels in diseases such as autism and schizophrenia, although it's not yet clear how they affect those diseases.

"Project researchers discovered that each person carries a handful of rare variants that would currently be recognized as disease-causing and a few hundred more rare variants that are likely to have a detrimental effect on how genes work," said Gilean McVean, Ph.D., professor of statistical genetics at the University of Oxford in England and co-leader of the 1000 Genomes Project Analysis Group. "It's fortunate that most of us usually carry only one copy of these variants since two copies might lead to disease."

Another large NHGRI-funded effort, the ENCODE Project, recently published a series of papers showing that large parts of the human genome outside of protein-coding regions affect gene regulation. The patterns of variation in these regions that the 1000 Genomes Project found provide additional evidence about the functionality of these regions.

Data analysis is a vital part of the project, and about 260 analysts participated in analyzing the data reported in the recent Nature publication. They mapped and assembled the raw DNA sequence data relative to the reference human genome sequence. They then analyzed the aligned sequences to locate SNPs and structural variants. SNPs are relatively easy to find structural variants (such as insertions, deletions and copy number differences) are much harder to find. A number of research groups are working to establish how to go from the raw sequence data to identifying structural variants.

Many research groups contributed to the generation of genome sequence data for this project, including NHGRI's large-scale sequencing centers: the Human Genome Sequencing Center at the Baylor College of Medicine, Houston The Broad Institute of MIT and Harvard University in Cambridge, Mass., and The Genome Institute at the Washington University School of Medicine in St. Louis. Other groups included the Wellcome Trust Sanger Institute in Hinxton, England BGI Shenzhen in Shenzhen, China the Max Planck Institute for Molecular Genetics in Berlin and Illumina, Inc., in San Diego.

The 1000 Genomes Project eliminates time-consuming steps for researchers trying to find genetic variants that affect a disease. Genome-wide association studies aim to find regions of the genome that contain DNA variants relevant to a disease. They use technologies that provide information about hundreds of thousands to a couple of million SNPs in each studied genome they can combine these data with 1000 Genomes Project data on tens of millions of variants to find regions affecting the disease more precisely. The 1000 Genomes Project data then can be used to greatly enhance such studies by providing more detailed information about known variants. Instead of sequencing the genomes of all the people in a study - still an expensive prospect for thousands of people - researchers can use the 1000 Genomes Project data to find most of the variants in those regions that are associated with the disease.

"Once researchers find genes and variants of interest associated with disease by using the 1000 Genomes Project data, they have to return to basic biology to study them one at a time, to establish which genes and variants are causal for the disease and not just along for the ride," said Lisa D. Brooks, Ph.D., program director of the Genetic Variation Program in NHGRI's Division of Genome Sciences. "The 1000 Genomes Project data accelerate their ability to close in on those genes and variants."

Planning for the $120 million project began in 2007. In 2010, researchers published data on three pilot studies. The 2012 data set will be followed by the last addition to the catalog in 2013.


Looking for study/genome data for HIV in different organs - Biology

NIAID conducts and supports clinical trials evaluating therapies and vaccine candidates against severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), the virus that causes COVID-19.

The NIAID Strategic Plan for COVID-19 Research details the institute’s priorities for controlling and ultimately ending the spread of the novel coronavirus (SARS-CoV-2) and the disease it causes (COVID-19).

NIAID's cloud-based, secure data platform enables sharing of anonymous patient-level clinical data to help generate new knowledge to treat and prevent infectious diseases such as COVID-19.

NIAID’s research program to develop safe and effective antivirals to combat SARS-CoV-2 will also build sustainable platforms for targeted drug discovery and development of antivirals against viruses with pandemic potential.


Evaluation of Patients With Immune Function Abnormalities

This study will evaluate patients with abnormal immune function that results in recurrent or unusual infections or chronic inflammation.

Natural History of Intestinal Inflammation in People With Primary Immune Dysregulations

To learn more about when and why IBD may develop in some people with primary immune dysregulation.

Patients Treated for Chronic Granulomatous Disease (CGD) Since 1995

This study will determine the long term medical condition and daily functioning of participants with CGD after a transplant and if possible, compare these results to participants who do not undergo a transplant.

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To see if RFA is a safe and effective treatment for CGD-related liver abscesses.

Study of Gene Therapy Using a Lentiviral Vector to Treat X-linked Chronic Granulomatous Disease

This study is a prospective non-controlled, non-randomized Phase I/II clinical trial to assess the safety, feasibility and efficacy of cellular gene therapy in patients with chronic granulomatous disease.

Use of G-CSF to Obtain Blood Cell Precursors

This protocol is designed to study the techniques needed to develop gene therapy or other treatments for certain inherited immune system diseases.


Looking for study/genome data for HIV in different organs - Biology

A new genome-wide association study published today in Nature Genetics begins to uncover the basis of genetic variations in eight blood measurements and the impact those variants can have on common human diseases. Blood measurements, including the number and volume of cells in the blood, are routinely used to diagnose a wide range of disorders, including anaemia, infection and blood cell cancers.

An international team of scientists measured haemoglobin concentration, the count and volume of red and white cells and the sticky cells that prevent bleeding - platelets, in over 14,000 individuals from the UK and Germany. They uncovered 22 regions of the human genome implicated in the development of these blood cells. Of the 22 regions, 15 had not previously been identified.

The study represents the first genome-wide association of blood measurements to be completed in cohorts with large sample sizes.

"This study has been made possible by a great collaboration of scientists from the UK and Germany, and the contribution of clinical colleagues working in the field of heart disease, diabetes and coeliac disease in the UK, Germany and the United States," explains Dr Nicole Soranzo, group leader at the Wellcome Trust Sanger Institute and co-lead of the HaemGen consortium. "This unique collaboration has allowed us to discover novel genetic determinants of blood cell parameters, providing important insights into novel biological mechanisms underlying the formation of blood cells by the blood stem cells and their role in disease.

"This study highlights the importance of studying large collections of samples from healthy individuals where many different traits are measured."

The team compared regions of the human genome implicated in blood cell development with regions associated with risk of heart disease. By looking at the genetic data of 10,000 people with disease with that of 10,000 apparently healthy people, they found that one of the genetic variants associated with platelet counts also causes an increased risk of heart disease. The new variant was found in a region of the genome already known to influence the risk of hypertension, coeliac disease and diabetes in children and young adults, or so-called type 1 diabetes.

Further analysis showed that these genetic risk factors are uniquely found in individuals of European origin. By comparing human data with genetic data from chimpanzees, the team were able to conclude that the genetic variant was the result of a selection event favouring variants that increase the risk of heart disease, coeliac disease and type 1 diabetes in European populations 3,400 years ago. The authors suggest that the risk factors were positively selected for because they gave carriers an increased protection against infection.

"The study of blood traits is challenging because of the difficulty of teasing apart biological processes underlying the origin of blood cells," explains Dr Christian Gieger, Head of the Genetic Epidemiology research unit at the Helmholtz Zentrum and co-lead of the HaemGen consortium. "Until now, few genome-wide association studies have looked beyond single traits. But, through a systematic analysis of correlated traits we can begin to discover such shared genetic variants, forming the basis for understanding how these processes interact to influence health and disease.

"Using these techniques, we can now begin to understand the complex genetic basis of a whole variety of human diseases."

Scientists at the Wellcome Trust Sanger Institute, UK and the Helmholtz Zentrum Munich, Germany initiated the European HaemGen consortium, which encompasses groups from the UK (TwinsUK-KCL, NHS Blood and Transplant (NHSBT), University of Cambridge and University of Leicester) and Germany (Study of Health in Pomerania (SHIP) in Greifswald, the KORA study in the region of Augsburg and GerMIFS (University of Lbeck and Regensburg)). The HaemGen consortium aims to identify genetic loci contributing to variation in blood measurements and uncovers the potential correlation of these loci with disease phenotypes.

"We have uncovered a novel variant linking platelet counts with heart attacks," explains Nicole Soranzo. "Further characterisation of the regions uncovered in this study has the potential to improve our understanding of how blood cell development is linked with human diseases, including blood cell cancers."


Looking for study/genome data for HIV in different organs - Biology



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The HIV Life Cycle

In order for viruses to reproduce, they must infect cells in the body. Viruses are not technically alive: They are like a brain without a body. So in order to make more copies of itself, a virus must hijack our cells and use them to make new viruses. But how does that happen?

Your body constantly makes new skin and blood cells, and each cell often makes new proteins in order to stay alive and reproduce. Viruses hide their own DNA in the DNA of the cell. So when the cell tries to make its own proteins, it accidentally makes new viruses as well.

HIV can infect many types of cells in the body, but it mostly infects cells in the immune system. Once infected, a cell can produce hundreds of new copies of HIV.

Several kinds of immune cells have proteins on their surface, called CD4 receptors. HIV searches for these because the CD4 protein helps the virus bind to the cell. The main target for HIV is a white blood cell called a T4 lymphocyte, or &ldquoT helper cell&rdquo. The T4 cell is responsible for warning your immune system that there are invaders present.

Once HIV binds to an immune cell, it hides its DNA inside the cell&rsquos DNA: This turns the cell into a sort of HIV factory so it can make many more copies of itself. Let&rsquos look at the life cycle step by step.

Step 1: Binding

The outside of HIV has an outer shell (envelope) of proteins, fats and sugars. Inside, it carries its genes and special enzymes.

Proteins on the outside of HIV (also called receptors) are strongly attracted to and connect to the CD4+ receptors on a T4 cell. When HIV binds to a CD4+ receptor, other proteins on the cell&rsquos surface get activated, allowing HIV to fuse to and enter the cell.

Entry into the cell can be blocked by a class of HIV meds called entry inhibitors.

Step 2: Reverse Transcription

HIV&rsquos genes are RNA while the genes inside human cells are DNA. So, in order for the virus to infect the cell, a process called &ldquoreverse transcription&rdquo makes a DNA copy of the HIV&rsquos RNA. This is done with one of HIV&rsquos enzymes called reverse transcriptase. The new HIV DNA is also called &ldquoproviral DNA.&rdquo

Reverse transcription can be blocked by one class of HIV meds called nucleoside reverse transcriptase inhibitors (NRTIs) and another class called non-nucleoside reverse transcriptase inhibitors (NNRTIs).

Step 3: Integration

The new HIV DNA is then carried into the cell&rsquos nucleus (center), where the cell&rsquos DNA is kept. At this point, another HIV enzyme called integrase hides the HIV DNA into the cell&rsquos DNA. Then, when the cell tries to make new proteins for itself, it accidentally makes new HIV.

Integration can be blocked by a class of HIV meds called integrase inhibitors.

Step 4: Transcription

Once the HIV DNA is inside the cell&rsquos nucleus, it directs the cell to produce new HIV. Special enzymes will eventually create new genetic material called messenger RNA or mRNA. (Think of this new RNA as instructions for making new HIV.)

Transcription can be blocked by antisense antivirals or transcription inhibitors. However, these classes of drugs are in the earliest stage of research and are not FDA approved.

Step 5: Translation

Since mRNA carries instructions for making new viral proteins, each section of the mRNA relates to making a different part of HIV. So, as the full strand of mRNA is processed, it gets transformed or &ldquotranslated&rdquo into all the viral proteins needed to make a new virus.

Step 6: Viral Assembly and Maturation

The final step begins with the assembly of new virus. First, the long strings of proteins translated from the mRNA are then cut up into smaller proteins by the HIV enzyme called protease. These proteins become different parts of HIV, such as structural pieces (capsid, matrix, etc.) or enzymes (integrase, protease, etc.).

Next, once all the new viral proteins get assembled, they enter through and bud off the host cell to create a new virus. The new HIV then takes some time to mature, which can go on to infect new cells.

Viral assembly can be blocked by a class of HIV meds called protease inhibitors (PIs). Maturation may be blocked using maturation inhibitors, although none are yet FDA approved.

Glossary of Cell Terms

DNA: DNA is like the &ldquoblueprint&rdquo for building living cells.

Enzymes: Enzymes are like the workers of a cell. They build new proteins, transport materials around the cell, and carry out other important cellular functions.

RNA: RNA is like the construction boss. Cells use RNA to tell enzymes how to build a specific part of a cell. To make a new protein, enzymes will copy a specific part of the DNA into a piece of RNA. This RNA is then used by other enzymes to build a new protein or enzyme.

Proteins: The building blocks that are used to make living things.

Nucleus: A small package inside the cell where the genetic material is kept.


Study finds novel genetic patterns that make us rethink biology and individuality

Professor of Genetics Scott Williams, PhD, of the Institute for Quantitative Biomedical Sciences (iQBS) at Dartmouth's Geisel School of Medicine, has made two novel discoveries: first, a person can have several DNA mutations in parts of their body, with their original DNA in the rest—resulting in several different genotypes in one individual—and second, some of the same genetic mutations occur in unrelated people. We think of each person's DNA as unique, so if an individual can have more than one genotype, this may alter our very concept of what it means to be a human, and impact how we think about using forensic or criminal DNA analysis, paternity testing, prenatal testing, or genetic screening for breast cancer risk, for example. Williams' surprising results indicate that genetic mutations do not always happen purely at random, as scientists have previously thought. His work, done in collaboration with Professor of Genetics Jason Moore, PhD, and colleagues at Vanderbilt University, was published in PLOS Genetics journal on November 7, 2013. 1

Genetic mutations can occur in the cells that are passed on from parent to child and may cause birth defects. Other genetic mutations occur after an egg is fertilized, throughout childhood or adult life, after people are exposed to sunlight, radiation, carcinogenic chemicals, viruses, or other items that can damage DNA. These later or "somatic" mutations do not affect sperm or egg cells, so they are not inherited from parents or passed down to children. Somatic mutations can cause cancer or other diseases, but do not always do so. However, if the mutated cell continues to divide, the person can develop tissue, or a part thereof, with a different DNA sequence from the rest of his or her body.

"We are in reality diverse beings in that a single person is genetically not a single entity—to be philosophical in ways I do not yet understand—what does it mean to be a person if we are variable within?" says Williams, the study's senior author, and founding Director of the Center for Integrative Biomedical Sciences in iQBS. "What makes you a person? Is it your memory? Your genes?" He continues, "We have always thought, 'your genome is your genome.' The data suggest that it is not completely true."

In the past, it was always thought that each person contains only one DNA sequence (genetic constitution). Only recently, with the computational power of advanced genetic analysis tools that examine all the genes in one individual, have scientists been able to systematically look for this somatic variation. "This study is an example of the type of biomedical research project that is made possible by bringing together interdisciplinary teams of scientists with expertise in the biological, computational and statistical sciences." says Jason Moore, Director of the iQBS, who is also Associate Director for Bioinformatics at the Cancer Center, Third Century Professor, and Professor of Community and Family Medicine at Geisel.

Having multiple genotypes from mutations within one's own body is somewhat analogous to chimerism, a condition in which one person has cells inside his or her body that originated from another person (i.e., following an organ or blood donation or sometimes a mother and child—or twins—exchange DNA during pregnancy. Also, occasionally a person finds out that, prior to birth, he or she had a twin who did not survive, whose genetic material is still contained within their own body). 2 Chimerism has resulted in some famous DNA cases: one in which a mother had genetic testing that "proved" that she was unrelated to two of her three biological sons. 3

Williams says that, although this was a small study, "there is a lot more going on than we thought, and the results are, in some ways, astoundingly weird."

Because somatic changes are thought to happen at random, scientists do not expect unrelated people to exhibit the same mutations. Williams and colleagues analyzed the same 10 tissue samples in two unrelated people. They found several identical mutations, and detected these repeated mutations only in kidney, liver and skeletal body tissues. Their research examined "mitochondrial DNA" (mtDNA)—a part of DNA that is only inherited from the mother. 4 Technically all women would share mtDNA from one common female ancestor, but mutations have resulted in differences. The importance of Williams' finding is that these tissue-specific, recurrent, common mutations in mtDNA among unrelated study subjects—only detected in three body tissues—are "not likely being developed and maintained through purely random processes," according to Williams. They indicate "a completely different model …. a decidedly non-random process that results in particular mutations, but only in specific tissues."

If our human DNA changes, or mutates, in patterns, rather than randomly if such mutations "match" among unrelated people or if genetic changes happen only in part of the body of one individual, what does this mean for our understanding of what it means to be human? How may it impact our medical care, cancer screening, or treatment of disease? We don't yet know, but ongoing research may help reveal the answers.

Christopher Amos, PhD, Director of the Center for Genomic Medicine and Associate Director for Population Sciences at the Cancer Center, says, "This paper identifies mutations that develop in multiple tissues, and provides novel insights that are relevant to aging. Mutations are noticed in several tissues in common across individuals, and the aging process is the most likely contributor. The theory would be that selected mutations confer a selective advantage to mitochondria, and these accumulate as we age." Amos, who is also a Professor of Community and Family Medicine at Geisel, says, "To confirm whether aging is to blame, we would need to study tissues from multiple individuals at different ages." Williams concurs, saying, "Clearly these do accumulate with age, but how and why is unknown—and needs to be determined."

As more and better data become available from high-throughput genetic analyses and high-powered computers, researchers are identifying an increasing number of medical conditions that result from somatic mutations, including neurological, hematological, and immune-related disorders. Williams and colleagues are conducting further research to examine how diseases, other than cancer or even benign conditions, may result from somatic changes. 5 Williams, Moore and Amos will employ iQBS's Discovery supercomputer for next-generation sequencing to process subjects' DNA data. 6 Future analyses will include large, whole-genome sequencing of the data for the two individuals studied in the current report.

Williams explains, "We know that cancer is caused by mutations that cause a tumor. But in this work, we chose to study mutations in people without any cancer. Knowing how we accumulate mutations may make it easier to separate genetic signals that may cause cancer from those that accumulate normally without affecting disease. It may also allow us to see that many changes that we thought caused cancer do not in many situations, if we find the same mutations in normal tissues."

Just as our bodies' immune systems have evolved to fight disease, interestingly, they can also stave off the effects of some genetic mutations. Williams states that, "Most genetic changes don't cause disease, and if they did, we'd be in big trouble. Fortunately, it appears our systems filter a lot of that out."

Mark Israel, MD, Director of Norris Cotton Cancer Center and Professor of Pediatrics and Genetics at Geisel, says, "The fact that somatic mutation occurs in mitochondrial DNA apparently non-randomly provides a new working hypothesis for the rest of the genome. If this non-randomness is general, it may affect cancer risks in ways we could not have previously predicted. This can have real impact in understanding and changing disease susceptibility."

2 Strain L, Dean JC, Hamilton MP, Bonthron D. A true hermaphrodite chimera resulting from embryo amalgamation after in vitro fertilization. N Engl J Med 1998(338):166-9/

3 Norton AT and Zehner O. Project MUSE: Today's Research, Tomorrow's Inspiration. www.academia.edu/202539/Which_ &hellip d_Trans-Subjectivity.

4 The Bradshaw Foundation [online learning resource with main areas of focus on archaeology, anthropology and genetic research]: Mitochondrial DNA: The EVE Gene. www.bradshawfoundation.com/journey/eve.htm.

5 Li, Chun and Williams, Scott M. Human somatic variation: It's not just for cancer anymore. Current Genetic Medicine Reporter (In Press).


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