Every human has about 100 novel mutations that are absent in the genomes of his/her parents. This intense influx of mutations degrades information that is stored in the DNA sequences and, at the same time, provides an opportunity for creation of new genetic messages. Currently, over one hundred million mutations have been characterized in the public databases. The dynamics of mutation have been investigated for decades in both experiments and sophisticated mathematical models, yet our understanding of genome evolution is still ambiguous. In this project, we computationally processed eighty million human mutations to get clear answers to basic questions about DNA evolution. Specifically, how is the non-randomness in nucleotide composition in vast genomic regions maintained? What biological forces preserve sequence non-randomness from being degraded by novel mutations? Our goal was to uncover peculiarities in dynamics of G+C nucleotide content and evaluate the equilibrium of GC-percentage in the human genome. We found that novel mutations that convert G:C pairs into A:T pairs are 1.39 times more frequent than opposite mutations that change A:T → G:C. This effect is more striking if we take into account the fact that the total number of G:C pairs (42%) is significantly less than the number of A:T pairs (58%). Hence, calculating per nucleotide pair, the mutations of G:C → A:T is 1.93 times more frequent than A:T → G:C mutations. Such bias should create fewer and fewer G:C pairs in the genomes from generation to generation, until it reaches equilibrium at 34% of GC-composition. However, the GC-percentage of the human genome is stable at 42%. There are two possible biological processes that may be responsible for preserving GC-composition from degradation: i) natural selection or ii) biased gene conversion. However, estimated parameters for both processes are unable to explain the maintenance of CG-percentage. We re-evaluated the biased gene conversion parameters and rates that might explain GC-composition. The vast majority of our genome is represented by intergenic regions and introns. The effects of mutations inside these two noncoding regions are practically impossible to evaluate. We generally cannot classify these mutations as increasing or decreasing fitness, or measure their effects. In contrast, the effects of some of the mutations in protein-coding regions, that occupy only 1.2% of the human genome, may be quantifiable. Learning to measure the ratio of synonymous to non-synonymous mutations in coding regions was profoundly important, and revealed important rules in population genetics. Human Genomes have about 5% of regions with extreme nucleotide compositions. These include chromosomal segments with A+T-rich, G+C-rich, purine-rich (pyrimidine-rich), G+T-rich (A+C-rich) and alternating purine/pyrimidine sequences (that may form Z-DNA structures). We called such sequence patterns, exhibiting profound biases in nucleotide composition, Genomic MRI (Mid-Range Inhomogeneity). Genomic-MRI regions may form special DNA structures (e.g. H-DNA, Z-DNA) and are non-randomly distributed along the genome. At least some of them have known biological roles. The best understood are the G+C-rich sequences that organize CG-islands in promoters of many genes, and are the targets of DNA methylation. Genomic MRI-regions allow us to quantify the effect of mutations inside them, because mutations may decrease or increase the nucleotide bias in these regions. For example, A→C, A→G, T→C, and T→G mutations increase GC-composition in G+C-rich sequences, G→A, G→T, C→A, and C→T decrease the GC-composition, while A→T, T→A, G→C, and C→G are neutral to G+C-richness. In this project, we examined how mutations change genomic-MRI regions, and explore the biological forces that maintain these genomic-MRI structures during evolution despite the constant mutational pressure to equilibrium and randomness. We found that the point mutations in MRI preferentially degrade the nucleotide inhomogeneity, decreasing the biases in their nucleotide composition. The level of mutational degradation by novel SNPs was observed to be highest for G+C-rich MRIs and least for the A+T-rich MRIs. Older SNPs (those broadly widespread across populations) showed a decrease in the level of degradation compared to the Novel SNPs. Furthermore, we found that re-evaluation of Biased Gene Conversion parameters could explain how the GC content is preserved despite the bias in mutations.

There is growing enthusiasm in the scientific community about the prospect of mapping and sequencing the human genome, a monumental project that will have far-reaching consequences for medicine, biology, technology, and other fields. But how will such an effort be organized and funded? How will we develop the new technologies that are needed? What new legal, social, and ethical questions will be raised? Mapping and Sequencing the Human Genome is a blueprint for this proposed project. The authors offer a highly readable explanation of the technical aspects of genetic mapping and sequencing, and they recommend specific interim and long-range research goals, organizational strategies, and funding levels. They also outline some of the legal and social questions that might arise and urge their early consideration by policymakers.

Cis-regulatory DNA encodes the circuitry that enables cell development and differentiation. Cis-regulatory DNA is densely populated by recogntition sequences for transcription factors and the cooperative binding TFs to these sequences determines cell-fate and function by the precise transcriptional regulation of their cognate genes. As such, a mechanistic understanding of gene regulation hinges on our ability to quantify transcription factor occupancy. To map transcription factor occupancy with in the human genome, I took part in the development of digital genomic footprinting -- a technique leveraging the endonuclease DNase I that enables the unbiased and simultaneous detection of transcription factor occupancy genome-wide. We applied digital genomic footprinting to 41 diverse cell- and tissue-types to comprehensively map the human cis-regulatory lexicon. We show that this small genomic compartment contains an expansive repertoire of conserved recognition sequences for DNA-binding proteins and that nuclease patterns within these sequences mirror nucleotide-level evolutionary conservation and track the crystallographic topography of protein-DNA interfaces. We also show that both genetic and epigenetic variants affecting chromatin states are concentrated within footprints. Finally, we describe a large collection of novel regulatory factor recognition motifs that are highly conserved in both sequence and function, and exhibit cell-selective occupancy patterns that closely parallel major regulators of development, differentiation and pluripotency. These results provide for the first time an exhaustive map of TF occupancy within the human genome. The architecture of individual cis-regulatory sites is critical for their function. While digital genomic footprinting provides rich information about the occupancy of TFs within individual cis-regulatory elements, it is currently not possible to resolve the genome-wide relationship of transcription factors (TFs) and nucleosomes. To address this deficiency, I developed an extension to digital genomic footprinting that couples the detection of individual TF footprints to nucleosome occupancy. We find that TF occupancy is the major determinant of the positioning of cis-regulatory proximal nucleosomes, and that the positioning and occupancy of promoter-associated nucloeosomes is related to transcriptional start sites selection and output. The approach we describe provides a new view on the structure of cis-regulatory chromatin. In the second part of this thesis, I used a comparative genomics approach to study the evolution of cis-regulatory DNA and protein occupancy. To do this, I mapped DNase I hypersensitive sites (DHSs) in 45 mouse cell types and primary tissues, and systematically compared these with human DHS maps from orthologous cell and tissue compartments. While I uncovered a small set of core regulatory sequences that encode a developmental program, the vast majority of cis-egulatory DNA is rapidly evolving independently in mouse and human. Overall, I find that the activity of cis-regulatory DNA is directly linked to the the composition of TF recognition sequences within and that the aggregate recognition sequence space for each transcription factor within accessible regulatory DNA of orthologous mouse and human cell types has been strictly conserved. These results demonstrate the remarkable plasticity of the mammalian cis egulatory program and that TF occupancy is driven by an evolutionary inflexible trans-environment rather than conservation of individual regulatory elements. Taken together, this thesis provides a framework to understand the organization and evolution of global TF occupancy within the mammalian genome.

Humanity's physical design flaws have long been apparent--we get hemorrhoids and impacted wisdom teeth, for instance--but do the imperfections extend down to the level of our genes? Inside the Human Genome is the first book to examine the philosophical question of why, from the perspectives of biochemistry and molecular genetics, flaws exist in the biological world. Distinguished evolutionary geneticist John Avise offers a panoramic yet penetrating exploration of the many gross deficiencies in human DNA--ranging from mutational defects to built-in design faults--while at the same time offering a comprehensive treatment of recent findings about the human genome. The author shows that the overwhelming scientific evidence for genomic imperfection provides a compelling counterargument to intelligent design. He also develops a case that theologians should welcome rather than disavow these discoveries. The evolutionary sciences can help mainstream religions escape the shackles of Intelligent Design, and thereby return religion to its rightful realm--not as the secular interpreter of the biological minutiae of our physical existence, but rather as a respectable philosophical counselor on grander matters of ultimate concern.

Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis. Sequence - Evolution - Function should help bridge the "digital divide" between biologists and computer scientists, allowing biologists to better grasp the peculiarities of the emerging field of Genome Biology and to learn how to benefit from the enormous amount of sequence data available in the public databases. The book is non-technical with respect to the computer methods for genome analysis and discusses these methods from the user's viewpoint, without addressing mathematical and algorithmic details. Prior practical familiarity with the basic methods for sequence analysis is a major advantage, but a reader without such experience will be able to use the book as an introduction to these methods. This book is perfect for introductory level courses in computational methods for comparative and functional genomics.

Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.