Functional Bias and Spatial Organization of Genes in Mutational Hot and Cold Regions in the Human Genome

The neutral mutation rate is known to vary widely along human chromosomes, leading to mutational hot and cold regions. We provide evidence that categories of functionally-related genes reside preferentially in mutationally hot or cold regions, the size of which we have measured. Genes in hot regions are biased toward extra-cellular communication (surface receptors, cell adhesion, immune response, etc.) while those in cold regions are biased toward essential cellular processes (gene regulation, RNA processing, protein modification, etc.). From a selective perspective, this organization of genes could minimize the mutational load on genes that need to be conserved and allow fast evolution for genes that must frequently adapt. We also analyze the effect of gene duplication and chromosomal recombination, which contribute significantly to these biases for certain categories of hot genes. Overall, our results show that genes are located non-randomly with respect to hot and cold regions, offering the possibility that selection acts at the level of gene location in the human genome.Comment: 17 pages, 6 figures, 2 tables. accepted to PLOS Biology, Feb. 2004 issu

Deterministic and cascadable conditional phase gate for photonic qubits

Previous analyses of conditional \phi-phase gates for photonic qubits that treat cross-phase modulation (XPM) in a causal, multimode, quantum field setting suggest that a large (~\pi rad) nonlinear phase shift is always accompanied by fidelity-degrading noise [J. H. Shapiro, Phys. Rev. A 73, 062305 (2006); J. Gea-Banacloche, Phys. Rev. A 81, 043823 (2010)]. Using an atomic V-system to model an XPM medium, we present a conditional phase gate that, for sufficiently small nonzero \phi, has high fidelity. The gate is made cascadable by using using a special measurement, principal mode projection, to exploit the quantum Zeno effect and preclude the accumulation of fidelity-degrading departures from the principal-mode Hilbert space when both control and target photons illuminate the gate

Qudit-Basis Universal Quantum Computation using χ(2)\chi^{(2)} Interactions

We prove that universal quantum computation can be realized---using only linear optics and $\chi^{(2)}$ (three-wave mixing) interactions---in any $(n+1)$-dimensional qudit basis of the $n$-pump-photon subspace. First, we exhibit a strictly universal gate set for the qubit basis in the one-pump-photon subspace. Next, we demonstrate qutrit-basis universality by proving that $\chi^{(2)}$ Hamiltonians and photon-number operators generate the full $\mathfrak{u}(3)$ Lie algebra in the two-pump-photon subspace, and showing how the qutrit controlled-$Z$ gate can be implemented with only linear optics and $\chi^{(2)}$ interactions. We then use proof by induction to obtain our general qudit result. Our induction proof relies on coherent photon injection/subtraction, a technique enabled by $\chi^{(2)}$ interaction between the encoding modes and ancillary modes. Finally, we show that coherent photon injection is more than a conceptual tool in that it offers a route to preparing high-photon-number Fock states from single-photon Fock states.Comment: 9 pages, 3 figure

Weak preservation of local neutral substitution rates across mammalian genomes

<p>Abstract</p> <p>Background</p> <p>The rate at which neutral (non-functional) bases undergo substitution is highly dependent on their location within a genome. However, it is not clear how fast these location-dependent rates change, or to what extent the substitution rate <it>patterns </it>are conserved between lineages. To address this question, which is critical not only for understanding the substitution process but also for evaluating phylogenetic footprinting algorithms, we examine ancestral repeats: a predominantly neutral dataset with a significantly higher genomic density than other datasets commonly used to study substitution rate variation. Using this repeat data, we measure the extent to which orthologous ancestral repeat sequences exhibit similar substitution patterns in separate mammalian lineages, allowing us to ascertain how well local substitution rates have been preserved across species.</p> <p>Results</p> <p>We calculated substitution rates for each ancestral repeat in each of three independent mammalian lineages (primate – from human/macaque alignments, rodent – from mouse/rat alignments, and laurasiatheria – from dog/cow alignments). We then measured the correlation of local substitution rates among these lineages. Overall we found the correlations between lineages to be statistically significant, but too weak to have much predictive power (<it>r</it>²<<it>5%</it>). These correlations were found to be primarily driven by regional effects at the scale of several hundred kb or larger. A few repeat classes (e.g. 7SK, Charlie8, and MER121) also exhibited stronger conservation of rate patterns, likely due to the effect of repeat-specific purifying selection. These classes should be excluded when estimating local neutral substitution rates.</p> <p>Conclusion</p> <p>Although local neutral substitution rates have some correlations among mammalian species, these correlations have little predictive power on the scale of individual repeats. This indicates that local substitution rates have changed significantly among the lineages we have studied, and are likely to have changed even more for more diverged lineages. The correlations that do persist are too weak to be responsible for many of the highly conserved elements found by phylogenetic footprinting algorithms, leading us to conclude that such elements must be conserved due to selective forces.</p

CodingMotif: exact determination of overrepresented nucleotide motifs in coding sequences

<p>Abstract</p> <p>Background</p> <p>It has been increasingly appreciated that coding sequences harbor regulatory sequence motifs in addition to encoding for protein. These sequence motifs are expected to be overrepresented in nucleotide sequences bound by a common protein or small RNA. However, detecting overrepresented motifs has been difficult because of interference by constraints at the protein level. Sampling-based approaches to solve this problem based on codon-shuffling have been limited to exploring only an infinitesimal fraction of the sequence space and by their use of parametric approximations.</p> <p>Results</p> <p>We present a novel <it>O</it>(<it>N</it>(log <it>N</it>)²)-time algorithm, CodingMotif, to identify nucleotide-level motifs of unusual copy number in protein-coding regions. Using a new dynamic programming algorithm we are able to exhaustively calculate the distribution of the number of occurrences of a motif over all possible coding sequences that encode the same amino acid sequence, given a background model for codon usage and dinucleotide biases. Our method takes advantage of the sparseness of loci where a given motif can occur, greatly speeding up the required convolution calculations. Knowledge of the distribution allows one to assess the exact non-parametric p-value of whether a given motif is over- or under- represented. We demonstrate that our method identifies known functional motifs more accurately than sampling and parametric-based approaches in a variety of coding datasets of various size, including ChIP-seq data for the transcription factors NRSF and GABP.</p> <p>Conclusions</p> <p>CodingMotif provides a theoretically and empirically-demonstrated advance for the detection of motifs overrepresented in coding sequences. We expect CodingMotif to be useful for identifying motifs in functional genomic datasets such as DNA-protein binding, RNA-protein binding, or microRNA-RNA binding within coding regions. A software implementation is available at <url>http://bioinformatics.bc.edu/chuanglab/codingmotif.tar</url></p

Measuring the prevalence of regional mutation rates: an analysis of silent substitutions in mammals, fungi, and insects

BackgroundThe patterns of mutation vary both within and across genomes. It has been shown for a few mammals that mutation rates vary within the genome, while for unknown reasons, the sensu stricto yeasts have uniform rates instead. The generality of these observations has been unknown. Here we examine silent site substitutions in a more expansive set (20 mammals, 27 fungi, 4 insects) to determine why some genomes demonstrate this mosaic distribution and why others are uniform.ResultsWe applied several intragene and intergene correlation tests to measure regional substitution patterns. Assuming that silent sites are a reasonable approximation to neutrally mutating sequence, our results show that all multicellular eukaryotes exhibit mutational heterogeneity. In striking contrast, all fungi are mutationally uniform - with the exception of three Candida species: C. albicans, C. dubliniensis, and C. tropicalis. We speculate that aspects of replication timing may be responsible for distinguishing these species. Our analysis also reveals classes of genes whose silent sites behave anomalously with respect to the mutational background in many species, indicating prevalent selective pressures. Genes associated with nucleotide binding or gene regulation have consistently low silent substitution rates in every mammalian species, as well as multiple fungi. On the other hand, receptor genes repeatedly exhibit high silent substitution rates, suggesting they have been influenced by diversifying selection.ConclusionOur findings provide a framework for understanding the regional mutational properties of eukaryotes, revealing a sharp difference between fungi and multicellular species. They also elucidate common selective pressures acting on eukaryotic silent sites, with frequent evidence for both purifying and diversifying selection

Distribution-based measures of tumor heterogeneity are sensitive to mutation calling and lack strong clinical predictive power.

Mutant allele frequency distributions in cancer samples have been used to estimate intratumoral heterogeneity and its implications for patient survival. However, mutation calls are sensitive to the calling algorithm. It remains unknown whether the relationship of heterogeneity and clinical outcome is robust to these variations. To resolve this question, we studied the robustness of allele frequency distributions to the mutation callers MuTect, SomaticSniper, and VarScan in 4722 cancer samples from The Cancer Genome Atlas. We observed discrepancies among the results, particularly a pronounced difference between allele frequency distributions called by VarScan and SomaticSniper. Survival analysis showed little robust predictive power for heterogeneity as measured by Mutant-Allele Tumor Heterogeneity (MATH) score, with the exception of uterine corpus endometrial carcinoma. However, we found that variations in mutant allele frequencies were mediated by variations in copy number. Our results indicate that the clinical predictions associated with MATH score are primarily caused by copy number aberrations that alter mutant allele frequencies. Finally, we present a mathematical model of linear tumor evolution demonstrating why MATH score is insufficient for distinguishing different scenarios of tumor growth. Our findings elucidate the importance of allele frequency distributions as a measure for tumor heterogeneity and their prognostic role

Defects in translation-dependent quality control pathways lead to convergent molecular and neurodevelopmental pathology.

Translation-dependent quality control pathways such as no-go decay (NGD), non-stop decay (NSD), and nonsense-mediated decay (NMD) govern protein synthesis and proteostasis by resolving non-translating ribosomes and preventing the production of potentially toxic peptides derived from faulty and aberrant mRNAs. However, how translation is altered and the in vivo defects that arise in the absence of these pathways are poorly understood. Here, we show that the NGD/NSD factors Pelo and Hbs1l are critical in mice for cerebellar neurogenesis but expendable for survival of these neurons after development. Analysis of mutant mouse embryonic fibroblasts revealed translational pauses, alteration of signaling pathways, and translational reprogramming. Similar effects on signaling pathways, including mTOR activation, the translatome and mouse cerebellar development were observed upon deletion of the NMD factor Upf2. Our data reveal that these quality control pathways that function to mitigate errors at distinct steps in translation can evoke similar cellular responses