Category Archives: Genome

The Single Nucleotide Polymorphism Database (dbSNP) of Nucleotide Sequence Variation Adrienne Kitts and Stephen Sherry

Online Mendelian Inheritance in Man (OMIM): A Directory of Human Genes and Genetic Disorders Donna Maglott, Joanna S. Amberger, and Ada Hamosh

The SKY/CGH Database for Spectral Karyotyping and Comparative Genomic Hybridization Data Turid Knutsen, Vasuki Gobu, Rodger Knaus, Thomas Ried, and Karl Sirotkin

Genome Assembly and Annotation Process Paul Kitts

The Reference Sequence (RefSeq) Project Kim D. Pruitt, Tatiana Tatusova, and Donna Maglott

Using the Map Viewer to Explore Genomes Susan M. Dombrowski and Donna Maglott

UniGene: A Unified View of the Transcriptome Joan U. Pontius, Lukas Wagner, and Gregory D. Schuler

Exercises: Using Map Viewer David Wheeler, Kim Pruitt, Donna Maglott, Susan Dombrowski, and Andrei Gabrelian

A challenge facing researchers today is that of piecing together and analyzing the plethora of data currently being generated through the Human Genome Project and scores of smaller projects. NCBI's Web site serves an an integrated, one-stop, genomic information infrastructure for biomedical researchers from around the world so that they may use these data in their research efforts. More...

Reference epigenomic maps and studies on new epigenetic mechanisms and their relevance to human health.

A comprehensive listing of all NIH Roadmap Epigenomics datasets submitted to GEO and SRA.

Homology Map Computed blocks of conserved synteny between mouse and human.

See the rest here:
NCBI Human Genome Resources

Format: Hardcover

This is an excellent overview of current scientific discovery and argument regarding that inheritently common, but innately variable blueprint of 23 pairs of chromosones we all share. Our knowledge of our genes is progressing at a rapid rate, so much so, that by the time I finish writing this sentence, our knowledge of the human genetic code has been updated. If you wish to know what kinds of things are being discovered, this book is a very good place to find it. Matt Ridley devotes each chapter to one of our chromosones-23 in all, and describes some useful dicoveries and speculations regarding each. From such things as the ability to digest lactose, blood groups, cancer suppressors, 'instinct',intelligence, ethics, free will, allergies, aspects of language, ageing, sex, cloning, test tube babies, Mad Cow disease etc, he describes in a clever and clear way the discoveries being made in the field. I would give the book 4 1/2 stars,(but there are no halves in these reviews), as no book is ever perfect, but a point to remember is no understanding of our world, or our genes themselves, is ever perfect either. But we can find pieces to the puzzle, useful and uplifting, and that is what this book is about. Ridleys style is clear and clever, my only quibble is that he displays perhaps just a touch of arrogance, and a subtle air of bias. But give the author his due, an author is entitled to his opinions and leanings, what is important is that he generally makes it clear when he does so. The book is highly recommended for both those familiar with the jargon, and those with enthusiastic minds who wish to learn about it.

Read more:
Genome: The Autobiography of a Species in 23 Chapters

Genome size is the total amount of DNA contained within one copy of a single genome. It is typically measured in terms of mass in picograms (trillionths (1012) of a gram, abbreviated pg) or less frequently in Daltons or as the total number of nucleotide base pairs typically in megabases (millions of base pairs, abbreviated Mb or Mbp). One picogram equals 978 megabases.[1] In diploid organisms, genome size is used interchangeably with the term C-value. An organism's complexity is not directly proportional to its genome size; some single cell organisms have much more DNA than humans (see Junk DNA and C-value enigma).

The term "genome size" is often erroneously attributed to Hinegardner,[2] even in discussions dealing specifically with terminology in this area of research (e.g., Greilhuber, 2005[3]). Notably, Hinegardner[2] used the term only once: in the title. The term actually seems to have first appeared in 1968 when Hinegardner wondered, in the last paragraph of his article, whether "cellular DNA content does, in fact, reflect genome size".[4] In this context, "genome size" was being used in the sense of genotype to mean the number of genes. In a paper submitted only two months later (in February 1969), Wolf et al. (1969)[5] used the term "genome size" throughout and in its present usage; therefore these authors should probably be credited with originating the term in its modern sense. By the early 1970s, "genome size" was in common usage with its present definition, probably as a result of its inclusion in Susumu Ohno's influential book Evolution by Gene Duplication, published in 1970.[6]

The genome sizes of thousands of eukaryotes have been analyzed over the past 50 years, and these data are available in online databases for animals, plants, and fungi (see external links). Nuclear genome size is typically measured in eukaryotes using either densitometric measurements of Feulgen-stained nuclei (previously using specialized densitometers, now more commonly using computerized image analysis[7]) or flow cytometry. In prokaryotes, pulsed field gel electrophoresis and complete genome sequencing are the predominant methods of genome size determination. Nuclear genome sizes are well known to vary enormously among eukaryotic species. In animals they range more than 3,300-fold, and in land plants they differ by a factor of about 1,000.[8][9]Protist genomes have been reported to vary more than 300,000-fold in size, but the high end of this range (Amoeba) has been called into question.[by whom?] In eukaryotes (but not prokaryotes), variation in genome size is not proportional to the number of genes, an observation that was deemed wholly counterintuitive before the discovery of non-coding DNA and which became known as the C-value paradox as a result. However, although there is no longer any paradoxical aspect to the discrepancy between genome size and gene number, this term remains in common usage. For reasons of conceptual clarification, the various puzzles that remain with regard to genome size variation instead have been suggested by one author to more accurately comprise a puzzle or an enigma (the C-value enigma). Genome size correlates with a range of features at the cell and organism levels, including cell size, cell division rate, and, depending on the taxon, body size, metabolic rate, developmental rate, organ complexity, geographical distribution, or extinction risk (for recent reviews, see Bennett and Leitch 2005;[8] Gregory 2005[9]). Based on completely sequenced genome data currently (as of April 2009) available, log-transformed gene number forms a linear correlation with log-transformed genome size in bacteria, archea, viruses, and organelles combined whereas a nonlinear (semi-natural log) correlation in eukaryotes (Hou and Lin 2009 [10]). The nonlinear correlation for eukaryotes, although claim of its existence contrasts the previous view that no correlation exists for this group of organisms, reflects disproportionately fast increasing noncoding DNA in increasingly large eukaryotic genomes. Although sequenced genome data are practically biased toward small genomes, which may compromise the accuracy of the empirically derived correlation, and the ultimate proof of the correlation remains to be obtained by sequencing some of the largest eukaryotic genomes, current data do not seem to rule out a correlation.

Genome reduction, also known as Genome degradation, is the process by which a genome shrinks relative to its ancestor. Genomes fluctuate in size regularly, however, genome size reduction is most significant in bacteria.

The most evolutionary significant cases of genome reduction may be the eukaryotic organelles that are derived from bacteria: the mitochondrion and plastid. These organelles are descended from endosymbionts, which can only survive within the host cell and which the host cell likewise needs for survival. Many mitochondria have less than 20 genes in their entire genome, whereas a free-living bacterium generally has at least 1000 genes. Many genes have been transferred to the host nucleus, while others have simply been lost and their function replaced by host processes.

Other bacteria have become endosymbionts or obligate intracellular pathogens and experienced extensive genome reduction as a result. This process seems to be dominated by genetic drift resulting from small population size, low recombination rates, and high mutation rates, as opposed to selection for smaller genomes.

Some free-living marine bacterioplanktons also shows signs of genome reduction, which are hypothesized to be driven by natural selection.[12][13][14]

Obligate endosymbiotic species are characterized by a complete inability to survive external to their host environment. These species have become a considerable threat to human health, as they are often highly capable of evading human immune systems and manipulating the host environment to acquire nutrients. A common explanation for these keen manipulative abilities is the compact and efficient genomic structure consistently found in obligate endosymbionts. This compact genome structure is the result of massive losses of extraneous DNA - an occurrence that is exclusively associated with the loss of a free-living stage. In fact, as much as 90% of the genetic material can be lost when a species makes the evolutionary transition from a free-living to obligate intracellular lifestyle. Common examples of species with reduced genomes include: Buchnera aphidicola, Rickettsia prowazekii and Mycobacterium leprae. One obligate endosymbiont of leafhoppers, Nasuia deltocephalinicola, has the smallest genome currently known among cellular organisms at 112kb.[15] It is important to note, however, that some obligate intracellular species have positive fitness effects on their hosts. (See also mutualists and parasites.)

The reductive evolution model has been proposed as an effort to define the genomic commonalities seen in all obligate endosymbionts.[16] This model illustrates four general features of reduced genomes and obligate intracellular species:

Based on this model, it is clear that endosymbionts face different adaptive challenges than free-living species.

or simply:

In 1991 Drake proposed a rule: that the mutation rate within a genome and its size were inversely correlated.[18] This rule has been found to be approximately correct for DNA viruses and unicellular organisms. Its basis is unknown.

The small size of RNA viruses has been proposed to be locked into a three part relation between replication fidelity, genome size and genetic complexity. The majority of RNA viruses lack an RNA proofreading facility which limits their replication fidelity and hence the genome size. This has also been described as the Eigen paradox.[19]

An exception to the rule of small genome sizes in RNA viruses is found the Nidoviruses. These viruses appear to have acquired a 3-to-5 exoribonuclease (ExoN) which has allowed for an increase in genome size.[20]

Here is the original post:
Genome size - Wikipedia, the free encyclopedia

About The Music Genome Project

We believe that each individual has a unique relationship with music no one else has tastes exactly like yours. So delivering a great radio experience to each and every listener requires an incredibly broad and deep understanding of music. That's why Pandora is based on the Music Genome Project, the most sophisticated taxonomy of musical information ever collected. It represents over ten years of analysis by our trained team of musicologists, and spans everything from this past Tuesday's new releases all the way back to the Renaissance and Classical music.

Each song in the Music Genome Project is analyzed using up to 450 distinct musical characteristics by a trained music analyst. These attributes capture not only the musical identity of a song, but also the many significant qualities that are relevant to understanding the musical preferences of listeners. The typical music analyst working on the Music Genome Project has a four-year degree in music theory, composition or performance, has passed through a selective screening process and has completed intensive training in the Music Genome's rigorous and precise methodology. To qualify for the work, analysts must have a firm grounding in music theory, including familiarity with a wide range of styles and sounds.

The Music Genome Project's database is built using a methodology that includes the use of precisely defined terminology, a consistent frame of reference, redundant analysis, and ongoing quality control to ensure that data integrity remains reliably high.

The Music Genome Project is updated on a continual basis with the latest releases, emerging artists, and an ever-deepening collection of catalogue titles.

By utilizing the wealth of musicological information stored in the Music Genome Project, Pandora recognizes and responds to each individual's tastes. The result is a much more personalized radio experience - stations that play music you'll love - and nothing else.

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About The Music Genome Project - Pandora Radio

CAREERS @ THE NEW YORK GENOME CENTER

The New York Genome Center (NYGC) is an independent, non-profit organization that leverages the collaborative resources of leading academic medical centers, research universities and commercial organizations. Our vision is to transform medical research and clinical care through the creation of one of the largest genomics facilities in North America; integrating sequencing, bioinformatics and data management, as well as performing cutting-edge genomics research.

Each faculty member of the NYGC leads a laboratory of post doctoral researchers, lab associates and scientific staff. They integrate their genomic expertise with the work that we are doing NYGC, working in collaborative research relationships both inside NYGC and with academic institutions. Our Faculty members hold joint appointments at our Institutional Founding Members while also managing their independent laboratories housed at the NYGC and conducting ground-breaking and collaborative genomic research.

We believe that every team member is crucial as NYGC works towards our mission, be it in a scientific, technical, or administrative position. Our administration team plays a huge role in driving transformative change in biomedical and clinical care. This group includes external affairs, finance, legal, business development, project management, sponsored research and facilities.

We are proud to boast a world-class bioinformatics and computational biology organization to support the cutting edge genomics research and integrated genomics services that we offer at NYGC. Our collaborative bioinformatics team is passionate about understanding and modeling human genetic variation and researching how it can be used to generate clinically actionable results.

This group develops and maintains the tools and infrastructure necessary to support our scientists as they tackle ground-breaking and large-scale data and genomic analysis. They are responsible for initiating and fostering external collaborations with technology partners, as well as ensuring that NYGC is a leader in the effective use of technology.

NYGC is committed to providing the most advanced sequencing an analysis possible. Our facility was designed to accommodate ever-improving technology, and we have more sequencing capacity than any other single institution in the Tri-State area. The Sequencing Operations group is responsible for understanding and interpreting sequencing and primary bioinformatics data, and is central to the transformative work of NYGC.

Our Software Engineers develop cutting edge tools to drive the services at NYGC. This team works closely with bioinformatics, sequencing lab, scientists, program management, and more to develop scientific applications for high-volume data processing, analysis and management.

Learn, grow and become part of the New York Genome Center team for a summer by participating in our 10-week paid internship program. Interns will have the opportunity to contribute towards the cutting-edge science being performed within our facilities. All interns will contribute towards a specific and meaningful project within their group which will culminate in an end-of-summer company presentation, ensuring our interns' professional and personal development. NYGC believes that our interns' summers should be both social and educational, and will offer a variety of lunch & learns, training seminars offered by team members across multiple functions of the organization, and organized social events.

Our Innovation Lab is currently testing several novel technologies with the potential to complement and enhance current technologies. Working with this group provides the opportunity to be on the cutting-edge of new technology and to perform innovative research that will shape the future of our industry.

The New York Genome Center provides equal employment opportunities to all employees and applicants without regard to race, color, religious creed, sex, national origin, ancestry, citizenship status, pregnancy, childbirth, physical disability, mental disability, age, military status or status as a Vietnam-era or special disabled veteran, marital status, registered domestic partner or civil union status, gender (including sex stereotyping and gender identity or expression), medical condition (including, but not limited to, cancer related or HIV/AIDS related), genetic information or sexual orientation in accordance with applicable federal and state laws. In addition, the New York Genome Center complies with applicable state and local laws governing nondiscrimination in employment in every location in which the Company has facilities. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

2016 New York Genome Center. All rights reserved.

Read more here:
New York Genome Center NYGC Careers

A Brief Guide to Genomics DNA, Genes and Genomes

Deoxyribonucleic acid (DNA) is the chemical compound that contains the instructions needed to develop and direct the activities of nearly all living organisms. DNA molecules are made of two twisting, paired strands, often referred to as a double helix

Each DNA strand is made of four chemical units, called nucleotide bases, which comprise the genetic "alphabet." The bases are adenine (A), thymine (T), guanine (G), and cytosine (C). Bases on opposite strands pair specifically: an A always pairs with a T; a C always pairs with a G. The order of the As, Ts, Cs and Gs determines the meaning of the information encoded in that part of the DNA molecule just as the order of letters determines the meaning of a word.

An organism's complete set of DNA is called its genome. Virtually every single cell in the body contains a complete copy of the approximately 3 billion DNA base pairs, or letters, that make up the human genome.

With its four-letter language, DNA contains the information needed to build the entire human body. A gene traditionally refers to the unit of DNA that carries the instructions for making a specific protein or set of proteins. Each of the estimated 20,000 to 25,000 genes in the human genome codes for an average of three proteins.

Located on 23 pairs of chromosomes packed into the nucleus of a human cell, genes direct the production of proteins with the assistance of enzymes and messenger molecules. Specifically, an enzyme copies the information in a gene's DNA into a molecule called messenger ribonucleic acid (mRNA). The mRNA travels out of the nucleus and into the cell's cytoplasm, where the mRNA is read by a tiny molecular machine called a ribosome, and the information is used to link together small molecules called amino acids in the right order to form a specific protein.

Proteins make up body structures like organs and tissue, as well as control chemical reactions and carry signals between cells. If a cell's DNA is mutated, an abnormal protein may be produced, which can disrupt the body's usual processes and lead to a disease such as cancer.

Sequencing simply means determining the exact order of the bases in a strand of DNA. Because bases exist as pairs, and the identity of one of the bases in the pair determines the other member of the pair, researchers do not have to report both bases of the pair.

In the most common type of sequencing used today, called sequencing by synthesis, DNA polymerase (the enzyme in cells that synthesizes DNA) is used to generate a new strand of DNA from a strand of interest. In the sequencing reaction, the enzyme incorporates into the new DNA strand individual nucleotides that have been chemically tagged with a fluorescent label. As this happens, the nucleotide is excited by a light source, and a fluorescent signal is emitted and detected. The signal is different depending on which of the four nucleotides was incorporated. This method can generate 'reads' of 125 nucleotides in a row and billions of reads at a time.

To assemble the sequence of all the bases in a large piece of DNA such as a gene, researchers need to read the sequence of overlapping segments. This allows the longer sequence to be assembled from shorter pieces, somewhat like putting together a linear jigsaw puzzle. In this process, each base has to be read not just once, but at least several times in the overlapping segments to ensure accuracy.

Researchers can use DNA sequencing to search for genetic variations and/or mutations that may play a role in the development or progression of a disease. The disease-causing change may be as small as the substitution, deletion, or addition of a single base pair or as large as a deletion of thousands of bases.

The Human Genome Project, which was led at the National Institutes of Health (NIH) by the National Human Genome Research Institute, produced a very high-quality version of the human genome sequence that is freely available in public databases. That international project was successfully completed in April 2003, under budget and more than two years ahead of schedule.

The sequence is not that of one person, but is a composite derived from several individuals. Therefore, it is a "representative" or generic sequence. To ensure anonymity of the DNA donors, more blood samples (nearly 100) were collected from volunteers than were used, and no names were attached to the samples that were analyzed. Thus, not even the donors knew whether their samples were actually used.

The Human Genome Project was designed to generate a resource that could be used for a broad range of biomedical studies. One such use is to look for the genetic variations that increase risk of specific diseases, such as cancer, or to look for the type of genetic mutations frequently seen in cancerous cells. More research can then be done to fully understand how the genome functions and to discover the genetic basis for health and disease.

Virtually every human ailment has some basis in our genes. Until recently, doctors were able to take the study of genes, or genetics, into consideration only in cases of birth defects and a limited set of other diseases. These were conditions, such as sickle cell anemia, which have very simple, predictable inheritance patterns because each is caused by a change in a single gene.

With the vast trove of data about human DNA generated by the Human Genome Project and other genomic research, scientists and clinicians have more powerful tools to study the role that multiple genetic factors acting together and with the environment play in much more complex diseases. These diseases, such as cancer, diabetes, and cardiovascular disease constitute the majority of health problems in the United States. Genome-based research is already enabling medical researchers to develop improved diagnostics, more effective therapeutic strategies, evidence-based approaches for demonstrating clinical efficacy, and better decision-making tools for patients and providers. Ultimately, it appears inevitable that treatments will be tailored to a patient's particular genomic makeup. Thus, the role of genetics in health care is starting to change profoundly and the first examples of the era of genomic medicine are upon us.

It is important to realize, however, that it often takes considerable time, effort, and funding to move discoveries from the scientific laboratory into the medical clinic. Most new drugs based on genome-based research are estimated to be at least 10 to 15 years away, though recent genome-driven efforts in lipid-lowering therapy have considerably shortened that interval. According to biotechnology experts, it usually takes more than a decade for a company to conduct the kinds of clinical studies needed to receive approval from the Food and Drug Administration.

Screening and diagnostic tests, however, are here. Rapid progress is also being made in the emerging field of pharmacogenomics, which involves using information about a patient's genetic make-up to better tailor drug therapy to their individual needs.

Clearly, genetics remains just one of several factors that contribute to people's risk of developing most common diseases. Diet, lifestyle, and environmental exposures also come into play for many conditions, including many types of cancer. Still, a deeper understanding of genetics will shed light on more than just hereditary risks by revealing the basic components of cells and, ultimately, explaining how all the various elements work together to affect the human body in both health and disease.

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Last Updated: August 27, 2015

Link:
A Brief Guide to Genomics - Genome.gov

Genome Genomu Alternate names

Android Berserker

Genome, the Android Berserker (), is a Human who utilizes the advanced time travel technology of the Dragon Ball Heroes machines, allowing him to become a Bio-Android.[1]

Android Berserker is one of the Android classes in the arcade game Dragon Ball Heroes.

The Android Berserker in his alternate outfit

The Android Berserker is a young Bio-Android whose overall appearance resembles Cell's perfect form; the main differences being he is primarily colored purple instead of green and he has a mouthpiece similar to Imperfect Cell. When in his GM outfit, he seems to be the reverse of this with his body looking like Imperfect Cell's and his face appearing similar to that of Perfect Cell and Frieza's faces. In both outfits, he has the Red Ribbon Army logo on his chest. In his JM outfit, his overall appearance resembles Perfect Cell.

As a Human, Genome looks like a younger version of Super 17.

See the article here:
Genome - Dragon Ball Wiki - Wikia

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What is a genome?

An organisms genome is the total set of DNA it inherits from its parents. The genome includes genes and non-coding DNA sequence as well as epigenetic modifications, such as methylation. The regulated expression of these genetic elements provides the building blocks and instructions through which an organism develops, grows, and interacts with its environment.

The DNA sequence of a genome sequence provides context. By sequencing the genome of Joshua Tree, we will have a global view of the genes and regulatory elements that code for the chemical building blocks of a Joshua tree and control how it grows and responds to its environment. Knowing the genome sequence, we can begin to conduct experiments and analyses that can identify specific regions of that sequence that are important for Joshua trees interactions with pollinating moths and other members of the Mojave desert biological community, and its adaptation to desert climates.

Joshua trees genome is approximately three billion DNA bases in length thats as many characters as there are in more than 2,500 copies of Moby Dick. Current technology doesnt allow us to simply read such a long DNA sequence from one end to the other; instead, DNA sequencing methods collect many smaller snippets of DNA sequence, which we can then assemble into a whole-genome sequence. We will use a hybrid assembly approach for the Joshua tree genome by combining the power of two DNA sequencing technologies. Illumina sequencing can collect large quantities of DNA sequence data, but in small snippets of just a couple hundred DNA bases. The PacBio method reads long continuous stretches of DNA sequence, though it cant collect as much total data as Illumina. Through our collaborators, we have access to PacBio sequencing capacity, and were crowd-funding the collection of Illumina data to complete the assembly. We will incorporate a new optical mapping method from BioNano to help assemble this sequence data into the full genome sequence.

When we have completed genome assembly from Illumina and PacBio sequencing, we will annotate the genome to identify genes and other functional elements. Ultimately we will build a transcriptions atlas of which genome regions play roles in development of different parts of a Joshua tree, and which control the trees growth and responses to its environment. This will provide a foundation to explore form and function within Joshua tree, from questions of how the genome functions as a whole to identifying genes that shape the interaction between Joshua tree and its pollinators.

Link:
Genome Sequencing - joshuatreegenome.org

A major news story over recent years has been the announcement of the genome sequence for humans. In fact, this project reached a symbolic completion point in April 2003. But this human genome work is just part of a much bigger story -- which includes a list of many completed genomes, for microbes, plants and animals. All this genome work is just the beginning; genome information alone does not solve anything in particular; it is a big resource that will make further biological work easier.

Two major news stories of 2003 set the background for this discussion. One is the 50th anniversary of the announcement of the double helical structure of DNA. The other is the announcement of the completed DNA sequence for the human genome. We discussed the development of the DNA structure. A key idea that emerged from this is the complementarity of the two DNA strands. This complementarity immediately suggests how DNA replicates -- by the two strands separating and each serving as a template for a new strand. The resulting "daughter" DNA molecules have one "old" strand and one "new" strand. A physical test of replicated DNA, showing this characteristic, was key in "proving" the basic DNA model. There is much chemical complexity to DNA and much biochemical complexity to how DNA really replicates, but the basic logic of a double stranded structure held together by complementarity still holds.

We then discussed DNA sequencing. We started by looking at some simple DNA sequencing results -- and showed how easy it is to actually read the sequence. Of course, what we looked at is the end step of a lengthy series of steps. We discussed an example of how one might generate the pattern we saw on the sequencing film; our example was not what is actually done, but was a simpler variation to illustrate the logic. The main problem with this basic sequencing procedure is that it works for only about 500 bases. Thus sequencing larger genomes requires some additional work, but it is still based on the same classical procedure that we started with. For large genomes, the process is highly automated, including the use of lasers to read dye-coded bases. Further, tremendous computer capability is needed to keep track of the data from the millions of pieces of DNA that are individually sequenced.

We discussed the gene count for humans. It is rather low -- and also uncertain. It is uncertain because we actually have considerable difficulty recognizing genes simply from DNA sequences, especially for complex organisms. The low gene count is forcing us to emphasize complexities in gene function, such as splicing and editing, that allow more than one protein to be made from a gene. We then discussed applications of genome information, especially of genome differences between individuals. These include applications such as forensic testing and paternity testing, which were developed some time ago. We discussed some drugs which are chosen based on specific genetic characteristics -- either of the individual, or even of the particular cancer. We then discussed more recent work, using gene chips (microarrays), where analysis of many genes allows leukemia (or leprosy) sub-types to be recognized. The specific figure that I showed was from a recent supplement to The Scientist: New Frontiers in Cancer Research, Sept 22, 2003. One topic that came up during general discussion was prions; I now have a page on prions.

The human genome is made of DNA -- as is the genome of almost all organisms. (A few viruses use the closely related chemical, RNA, for their genome; RNA operates by the same basic principles as DNA in this role.) A major milestone in the history of DNA is being celebrated in 2003 (the year this page was started)... It was fifty years ago, April 1953, that Watson & Crick announced that they had determined the structure of DNA -- a structure that in fact "made clear" how it works.

This Fig is from the Glossary of the NIH genome site, http://www.genome.gov/glossary/index.cfm?. Choose deoxyribonucleic acid (DNA). Also see next Fig.

In this Fig, the "replication fork" (the site and apparatus for making new DNA) is moving upward.

This Fig is also from the Glossary of the NIH genome site, http://www.genome.gov/glossary/index.cfm?. Choose DNA replication.

Good overview of DNA, by David Goodsell. This is a "Molecule of the Month" feature at the Protein Data Bank. http://www.rcsb.org/pdb/101/motm.do?momID=23. For more, see http://ndbserver.rutgers.edu/education/index.html. This is from the educational resources of The Nucleic Acid Database Project at Rutgers.

The double helix structure was published by Watson and Crick in 1953 in the journal Nature. 2003 is the 50th anniversary of that landmark, and there are many commemorations. The January 23, 2003, issue of Nature has a big feature on this. It includes an introductory article (Nature 421:310), copies of the original papers on DNA structure, and many articles discussing various aspects of the DNA story. And then there is more in the April 24, 2003, issue. This includes an article (Nature 422:835) by Francis Collins et al on the future of the human genome project. Fig 1 of that article is a fold-out timeline "Landmarks in Genetics and Genomics"; this is available as a pdf file from the Nature web site. At least some of this material could be usefully read or browsed by those with little background in the field.

* Nature is available online at http://www.nature.com/index.html. * The Nature "web focus" Double helix: 50 years of DNA ... http://www.nature.com/nature/dna50/index.html. * A Nature News Special on the DNA Anniversary ... http://www.nature.com/news/specials/dna50/index.html.

Among other web sites that resulted from the commemoration of the DNA anniversary...

The human genome was officially announced in February 2001 by two groups.

The main genome articles are probably too technical for most, but the issues contain many news stories dealing with various aspects of the project.

The Human Genome. A genome site from the Burroughs Wellcome Trust, which supported much of the British part of the genome project. http://genome.wellcome.ac.uk/. Includes a range of information at various levels, including for the general public.

Nature: Human Genome Collection. http://www.nature.com/nature/supplements/collections/humangenome/index.html. Links to all human genome work from Nature journals. Much consists of the technical articles, but there are also news stories and discussions.

Neandertal genome. February 2009 brings the announcement of a genome sequence from a 38,000 year old Neandertal. It is actually fairly rough at this point, but it is a remarkable achievement to get this far. There is little to conclude for now, except that the genome evidence so far provides no evidence for interbreeding between Neandertals and modern man (Homo sapiens).

Genome results are so important and fascinating that rodents have been seen scrutinizing their genome data. http://news.bbc.co.uk/2/hi/science/nature/424076.stm. (My main purpose in giving this link is for the Figure, for fun. But the work described there is an example of moving a gene from one organism to another, and using that as a tool to learn about the characteristics of an organism.)

As noted earlier, the genome is just data. It is not the magic solution to anything in particular. Because the genome data is fairly new, in fact few practical advances can be directly attributed to it. So, much of what I do here is to show how genome info might be used.

Pharmacogenomics and nutrigenomics. Traditional recommendations about proper nutrition and medicine assume that the population is uniform. Data is collected about population averages and this is used to guide medical treatments and nutritional advice. But we are not all the same. In fact, some examples of genetic differences in how we respond to drugs or nutrients have been found, more or less accidentally, in the past. The availability of complete genome information will allow such knowledge to come more rapidly. Briefly, pharmacogenomics is the customization of drug usage depending on an individual's genetic makeup; nutrigenomics is the analogous customization of nutrition information depending on an individual's genetic makeup.

The following two items are major nutrigenomics sites:

* The Center of Excellence for Nutritional Genomics at UC Davis, supported by the NCMHD (National Center for Minority Health and Health Disparities, part of the NIH) : http://nutrigenomics.ucdavis.edu.

* The European Nutrigenomics Organisation (NuGO): http://www.nugo.org/everyone/. In particular, see their page http://www.nugo.org/nip/ for the Nutrigenomics Information Portal, then choose Research. Also, they have an electronic newsletter. You can read it online, or sign up to receive it by email; choose NutriAlerts from the "NuGO sites" menu at the left (of either of those pages).

The two sites above are also listed on my page Further reading: Medical topics, under Web Sites. A specific page of the NuGO site, on Adipose Tissue, is listed for Organic/Biochemistry Internet resources, under Lipids.

The Future of Nutrigenomics - From the Lab to the Dining Room. A brochure for the general public, from the Institute for the Future. March 2005. http://www.iftf.org/node/773.

Cancer. Two articles on work to classify cancers by gene expression patterns. This work has implications for customizing treatment. A Gianella-Borradori et al, Reducing risks, maximizing impact with cancer biomarkers and B A Maher, The makings of a microarray prognosis. The Scientist Mar 15, 2004, pp 8 & 32.

Race. Is "race" a useful criterion for guiding medical treatment? The important point for us here is that genomics is offering new insight into this socially-charged question. At this point, genetic analysis suggests that there are some genes that reflect "geographical origin", but that the variability of human genomes within any "race" is far more than the genetic differences between "races". Of course, this information will be of more practical use as details emerge.

The following New York Times article discusses a clinical trial of a drug that is being targeted to and tested with only one racial group -- with the approval of the FDA. U.S. to Review Heart Drug Intended for One Race, June 2005. http://www.nytimes.com/2005/06/13/business/13cardio.html.

The following two short essays are by scientists discussing the race issue:

Personalized medicine. There are now companies that will take your DNA (and some money) and report back to you your risk for certain diseases. A good idea in principle, but how good is it in practice. Genome pioneer Craig Venter and colleagues have evaluated a couple of these companies, and offer some suggestions. As a general perspective, they think the companies are doing high quality work, technically, but the quality and usefulness of the information is questionable. It is true that your DNA contains information about disease susceptibility, but current knowledge of that is limited -- more limited than the companies want to admit. The paper is: P C Ng et al, An agenda for personalized medicine. Nature 461:724, 10/8/09. The paper seems to be freely available via the web site of the Venter Institute. Go to their page of press releases: http://www.jcvi.org/cms/press/press-releases/. Scroll down to the item for October 7, 2009. Click on its link; it takes you directly to the article at Nature. This probably means that the article is freely available directly from Nature.

Added May 7, 2011. There are many Musings posts in the broad area of personalized medicine. One of the first was: Personalized medicine: Getting your genes checked (10/27/09). It links to several others in the area.

An Introduction to Genomics: The Human Genome and Beyond, and related educational materials on the how and why of sequencing. From the Joint Genome Institute, a US DOE lab in Walnut Creek, CA. http://www.jgi.doe.gov/education/index.html.

Genetics Home Reference, an educational site on genetic diseases in humans; from the National Library of Medicine. http://ghr.nlm.nih.gov.

Book. J D Watson (with A Berry), DNA - The Secret of Life. Knopf, 2003. Watson has played a major role in the DNA story, most famously as co-discoverer of the DNA double helical structure and as the first head of the US Human Genome Project. Here he discusses the history and future of the human genome project. He is a fine writer -- clear, and provocative enough to be fun. This book is for the general public. The science in it is good, and well-explained, with helpful artwork. The history is broadly good. And it is Watson's style to tell you what he thinks about controversial issues; agree or disagree, he makes for lively reading. For two -- very different -- reviews: Lindee, Science 300:432, 4/18/03; Singer, Nature 422:809, 4/24/03. Lindee concludes that "[Watson's] latest promotional brochure is not worth anyone's time." Singer says that the public and even scientists "can learn a great deal from the book, and enjoy doing so." I recommend it -- without endorsing all of his opinions.

Online video. A conversation with Jim Watson. Go to the Caltech theater listings for Science and Technology: http://today.caltech.edu/theater/list?subset=science&story%5fcount=end. Scroll down the list to this item, dated May 5, 2003. The conversation is with David Baltimore, (then) president of Caltech and himself a Nobel prize winner (for his discovery of the enzyme reverse transcriptase, the enzyme that copies RNA into DNA).

Book. B Maddox, Rosalind Franklin - The dark lady of DNA. Harper/Collins, 2002. One of the dark parts of the DNA story is the lack of recognition of the role of Rosalind Franklin, who made the very fine X-ray pictures that Watson & Crick used as part of developing the double-helix structure. This lack of recognition was magnified by Watson's poor treatment of Franklin, especially in his earlier book, The Double Helix. Brenda Maddox's new biography has received wide praise as being fair and accurate; she had access to many materials that were previously unavailable. This is a biography, not a science book -- though you will certainly get a good sense of how the DNA story was developed. Highly recommended, but don't expect to come away declaring winners and losers; it's not that simple, but it is a good story, and it certainly enhances our understanding of an important scientist. (One part of the controversy, to some, is why Franklin did not share in the Nobel prize for the DNA work. It is a sufficient answer to that question that she died a few years before the DNA Nobel, 1962; posthumous Nobels are not allowed. Note that this point does not address the merits of her contributions, but does address one question which often comes to the forefront.)

There is a short essay about Franklin, in the general spirit of the book, online in the Mill Hill collection: K Rittinger & A Pastore, Rosalind Franklin - The dark lady of DNA... http://www.nimr.mrc.ac.uk/mill-hill-essays/rosalind-franklin-the-dark-lady-of-dna. For more about the Mill Hill essays, see the note on the BITN main page, under Web sites.

Coumadin (warfarin) is a widely prescribed medication to reduce blood clotting. The dosage must be carefully controlled, and people vary in how they respond. The FDA has announced a new labeling of coumadin that encourages testing the patient for two known genetic factors that affect the metabolism of the drug. A brief version of the announcement is at http://www.fda.gov/Safety/MedWatch/SafetyInformation/SafetyAlertsforHumanMedicalProducts/ucm152972.htm.

A small trial has been reported showing that such testing is beneficial. So far, all we have is a news story summarizing the key findings. Gene test cuts complications from blood thinner warfarin (3/16/10). http://www.usatoday.com/news/health/2010-03-16-warfarin-gene_N.htm.

Sequencing technology -- and cost. The human genome project cost about $3 billion. Much technology was developed along the way; as the project wrapped up, it was estimated that one could sequence a person's genome for a few million dollars. There is a dream -- and goal -- of sequencing an individual's genome for a thousand dollars. That may still be a way off, but the cost of sequencing has been declining, in large part due to fundamentally new approaches to sequencing. 2009 brings a report of a complete human genome for $50,000. A news story on this: Cost of Decoding a Genome Is Lowered. A Stanford engineer has invented a new technology for decoding DNA and used it to decode his own genome for less than $50,000. August 10, 2009. http://www.nytimes.com/2009/08/11/science/11gene.html.

Using genetic information to assess risk and guide screening. Most genes that affect disease susceptibility have only a small effect. How do we use such information? A paper in the New England Journal of Medicine lays out a model. Although there is probably much to quibble with, the model is clear enough, and may be a useful reference point for discussion. They start with the current UK recommendation that women be screened for breast cancer starting at age 50. Accepting this as the starting point, they note that this is the point at which a woman has a 2.3% chance of breast cancer within the next 10 years. They then argue that by a simple test for some known genetic variants, they can mark some women for screening at age 40 -- because with their genetic makeup that is the age at which they now have a 2.3% risk of breast cancer within 10 years. Similarly, women with other genetic variants have lower risk, and their screening can be delayed. The result is the same use of resources, but more effectively deployed. A news story about this work: Cancer gene test 'for all women', June 26, 2008. Online: http://news.bbc.co.uk/2/hi/health/7475312.stm. The paper is P D P Pharoah et al, Polygenes, Risk Prediction, and Targeted Prevention of Breast Cancer. N Engl J Med 358:2796, 6/26/08. Free online: http://www.nejm.org/doi/full/10.1056/NEJMsa0708739.

Tradeoff. We sometimes dream of finding "the gene" that causes a particular disease -- so we can counteract that gene. But among the complications... It may be that the same gene is good in one way and bad in another. Recent work suggests such a tradeoff may occur between diabetes and prostate cancer. In fact, two genes with this tradeoff have been found. News story: Genetic variants may be 'trading' one illness with another using new genes, Oxford research shows. Online: http://www.timesonline.co.uk/tol/news/science/article3649020.ece.

Genome ethics. Genome work is raising a new set of ethics questions -- especially since there is so much uncertainty what the genome information means at this point. A group of bioethicists has proposed a set of guidelines for doing genome research, published as: T Caulfield et al, Research Ethics Recommendations for Whole-Genome Research: Consensus Statement. PLOS Biology 6, e73, 3/08. The paper is free online: http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0060073.

Ancestry. An interesting subject is tracing human lineages by genetic tests. This is indeed a proper area of study, and has yielded insights into human migrations. It has also entered the popular arena. There are commercial tests that claim to reveal your ancestry. Unfortunately, the quality of this testing is questionable at this point. A "Policy Forum" article about this appeared in Science, and a news story about the work and that article appeared in the UC Berkeley news. The Science article: D A Bolnick et al, Genetics: The science and business of genetic ancestry testing. Science 318:399, 10/19/07. The UC Berkeley news story, featuring co-author Kimberly TallBear: Researchers caution against genetic ancestry testing; October 18, 2007. http://www.berkeley.edu/news/media/releases/2007/10/18_genetictesting.shtml.

Craig Venter is one of the pioneers of genome work. He is also the first person to have his entire DNA -- the diploid chromosome set -- completely sequenced and reported. Importance? Well, for now it is a technical milestone and something of a curiosity. However, as more complete genomes become available -- and as the cost comes down -- the usefulness will increase. For example, they note how he has specific alleles that both favor and disfavor heart disease. At this point, that is too little info to be useful. At some point, with more information, it will be useful. I doubt that many will want to read this in detail, but simply browsing the Introduction and Discussion sections will give the flavor. And it is a historic paper. The paper -- by Venter, about Venter, and from the Venter Institute -- is: S Levy et al, The Diploid Genome Sequence of an Individual Human. PLoS Biol 5(10): e254. 9/4/07. It is open access at http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0050254.

M May, Pharmacogenetics lurches forward. The Scientist 8/2/04, p 26. This article discusses several specific examples of how drugs may affect individuals differently, depending on their genetics. It includes the recent genetic analysis of why Iressa works for some patients and not others.

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