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The Bermuda Principles for DNA sequence data sharing are an enduring legacy of the Human Genome Project (HGP). They were adopted by the HGP at a strategy meeting in Bermuda in February of 1996 and implemented in formal policies by early 1998, mandating daily release of HGP-funded DNA sequences into the public domain. The idea of daily sharing, we argue, emanated directly from strategies for large, goal-directed molecular biology projects first tested within the \"community\" of C. elegans researchers, and were introduced and defended for the HGP by the nematode biologists John Sulston and Robert Waterston. In the C. elegans community, and subsequently in the HGP, daily sharing served the pragmatic goals of quality control and project coordination. Yet in the HGP human genome, we also argue, the Bermuda Principles addressed concerns about gene patents impeding scientific advancement, and were aspirational and flexible in implementation and justification. They endured as an archetype for how rapid data sharing could be realized and rationalized, and permitted adaptation to the needs of various scientific communities. Yet in addition to the support of Sulston and Waterston, their adoption also depended on the clout of administrators at the US National Institutes of Health (NIH) and the UK nonprofit charity the Wellcome Trust, which together funded 90% of the HGP human sequencing effort. The other nations wishing to remain in the HGP consortium had to accommodate to the Bermuda Principles, requiring exceptions from incompatible existing or pending data access policies for publicly funded research in Germany, Japan, and France. We begin this story in 1963, with the biologist Sydney Brenner's proposal for a nematode research program at the Laboratory of Molecular Biology (LMB) at the University of Cambridge. We continue through 2003, with the completion of the HGP human reference genome, and conclude with observations about policy and the historiography of molecular biology.

In the next generation sequencing techniques millions of short reads are produced from a genomic sequence at a single run. The chances of low read coverage to some regions of the sequence are very high. The reads are short and very large in number. Due to erroneous base calling, there could be errors in the reads. As a consequence, sequence assemblers often fail to sequence an entire DNA molecule and instead output a set of overlapping segments that together represent a consensus region of the DNA. This set of overlapping segments are collectively called contigs in the literature. The final step of the sequencing process, called scaffolding, is to assemble the contigs into a correct order. Scaffolding techniques typically exploit additional information such as mate-pairs, pair-ends, or optical restriction maps. In this paper we introduce a series of novel algorithms for scaffolding that exploit optical restriction maps (ORMs). Simulation results show that our algorithms are indeed reliable, scalable, and efficient compared to the best known algorithms in the literature.

The goal of the Human Genome Project (HGP) is to determine a complete and high-quality sequence of the human genome. China, as one of the six member states, takes a region between 3pter and D3S3397 of the human chromosome 3 as its share of this historic project, referred as “Beijing Region”. The complete sequence of this region comprises of 17.4 megabasepairs (Mb) with an average GC content of 42% and an average recombination rate of 2.14 cM/Mb. Within Beijing Region, 122 known and 20 novel genes are identified, as well as 42607 single nucleotide polymorphisms (SNPs). Comprehensive analyses also reveal: (i) gene density and GC-content of Beijing Region are in agreement with human cytogenetic maps, i.e. G-minus bands are GC-rich and of a high gene density, whereas G-plus bands are GC-poor and of a relatively low gene density; (ii) the average recombination rate within Beijing Region is relatively high compared with other regions of chromosome 3, with the highest recombination rate of 6.06 cM/Mb in the subtelomeric area; (iii) it is most likely that a large gene, associated with the mammary gland, may reside in the 1.1 Mb gene-poor area near the telomere; (iv) many disease-related genes are genetically mapped to Beijing Region, including those associated with cancers and metabolic syndromes. All make Beijing Region an important target for in-depth molecular investigations with a purpose of medical applications.

This chapter highlights the unique nature of the information obtained by genetic testing, the need to maintain confidentiality and privacy, and ensure fair use of the genetic information of an individual. While genetic testing can be useful for early diagnosis of genetic diseases and is of immense value to drug developers, it can potentially be misused by employers and insurance companies to deny services. Understanding issues of genetic discrimination has been the objective of studies on the ethical, legal and social implication of genomic information. Mechanisms to prevent discrimination on the basis of genetic information include international advocacy and policies on human rights as well as national laws, including several that specifically address the issue.

This chapter contains sections titled: The Current Conundrum The Objects of Our Study The Legal Framework So Far Special Challenges of DNA Property and Parts Autonomy, Individuality, and Personhood Economics and the Marketplace for Genes Ethics and Method An Outline for the Investigation The Challenge Ahead

This chapter contains sections titled: The Basics of Genetic Science Genetics and Medical Sociology The Legacy of Eugenics Genetics in the Clinic The Genetic Construction of Disease Living with our Genotype Expectations and the Commodification of Genetic Knowledge: The Biopharmaceutical and Genomics Industry Conclusions: Reflections on Geneticization References

[...]numerous genome wide linkage studies have frustratingly failed to find clear and replicable evidence for the location of the genes responsible for these traits. [...]it appears that common variants of most genes can be characterised by a small number of SNP haplotypes, facilitating candidate gene association studies.