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Next‐generation sequencing (NGS) has emerged as an affordable and reproducible means to query tumors for somatic genetic anomalies. To help interpret somatic NGS data, many institutions have created a molecular tumor board to analyze the results of NGS and make recommendations. This article evaluates the utility of cognitive computing systems to analyze data for clinical decision‐making., Background. Using next‐generation sequencing (NGS) to guide cancer therapy has created challenges in analyzing and reporting large volumes of genomic data to patients and caregivers. Specifically, providing current, accurate information on newly approved therapies and open clinical trials requires considerable manual curation performed mainly by human “molecular tumor boards” (MTBs). The purpose of this study was to determine the utility of cognitive computing as performed by Watson for Genomics (WfG) compared with a human MTB. Materials and Methods. One thousand eighteen patient cases that previously underwent targeted exon sequencing at the University of North Carolina (UNC) and subsequent analysis by the UNCseq informatics pipeline and the UNC MTB between November 7, 2011, and May 12, 2015, were analyzed with WfG, a cognitive computing technology for genomic analysis. Results. Using a WfG‐curated actionable gene list, we identified additional genomic events of potential significance (not discovered by traditional MTB curation) in 323 (32%) patients. The majority of these additional genomic events were considered actionable based upon their ability to qualify patients for biomarker‐selected clinical trials. Indeed, the opening of a relevant clinical trial within 1 month prior to WfG analysis provided the rationale for identification of a new actionable event in nearly a quarter of the 323 patients. This automated analysis took

Background Prompted by the revolution in high-throughput sequencing and its potential impact for treating cancer patients, we initiated a clinical research study to compare the ability of different sequencing assays and analysis methods to analyze glioblastoma tumors and generate real-time potential treatment options for physicians. Methods A consortium of seven institutions in New York City enrolled 30 patients with glioblastoma and performed tumor whole genome sequencing (WGS) and RNA sequencing (RNA-seq; collectively WGS/RNA-seq); 20 of these patients were also analyzed with independent targeted panel sequencing. We also compared results of expert manual annotations with those from an automated annotation system, Watson Genomic Analysis (WGA), to assess the reliability and time required to identify potentially relevant pharmacologic interventions. Results WGS/RNAseq identified more potentially actionable clinical results than targeted panels in 90% of cases, with an average of 16-fold more unique potentially actionable variants identified per individual; 84 clinically actionable calls were made using WGS/RNA-seq that were not identified by panels. Expert annotation and WGA had good agreement on identifying variants [mean sensitivity = 0.71, SD = 0.18 and positive predictive value (PPV) = 0.80, SD = 0.20] and drug targets when the same variants were called (mean sensitivity = 0.74, SD = 0.34 and PPV = 0.79, SD = 0.23) across patients. Clinicians used the information to modify their treatment plan 10% of the time. Conclusion These results present the first comprehensive comparison of technical and machine augmented analysis of targeted panel and WGS/RNA-seq to identify potential cancer treatments.

Multiple questions relating to contributions of cultural and demographical factors in the process of human geographical dispersal remain largely unanswered. India, a land of early human settlement and the resulting diversity is a good place to look for some of the answers. In this study, we explored the genetic structure of India using a diverse panel of 78 males genotyped using the GenoChip. Their genome-wide single-nucleotide polymorphism (SNP) diversity was examined in the context of various covariates that influence Indian gene pool. Admixture analysis of genome-wide SNP data showed high proportion of the Southwest Asian component in all of the Indian samples. Hierarchical clustering based on admixture proportions revealed seven distinct clusters correlating to geographical and linguistic affiliations. Convex hull overlay of Y-chromosomal haplogroups on the genome-wide SNP principal component analysis brought out distinct non-overlapping polygons of F*-M89, H*-M69, L1-M27, O2a-M95 and O3a3c1-M117, suggesting a male-mediated migration and expansion of the Indian gene pool. Lack of similar correlation with mitochondrial DNA clades indicated a shared genetic ancestry of females. We suggest that ancient male-mediated migratory events and settlement in various regional niches led to the present day scenario and peopling of India.

Metabotropic glutamate receptors (mGluRs) constitute an important family of the G-protein coupled receptors. Due to their widespread distribution in the central nervous system (CNS), these receptors are attractive candidates for understanding the molecular basis of various cognitive processes as well as for designing inhibitors for relevant psychiatric and neurological disorders. Despite many studies on drugs targeting the mGluR receptors to date, the molecular level details on the ligand binding dynamics still remain unclear. In this study, we performed in silico experiments for mGluR1 with 29 different ligands including known synthetic agonists and antagonists as well as natural amino acids. The ligand-receptor binding affinities were estimated by the use of atomistic simulations combined with the mathematically rigorous, Free Energy Perturbation (FEP) method, which successfully recognized the native agonist l-glutamate among the highly favorable binders, and also accurately distinguished antagonists from agonists. Comparative contact analysis also revealed the binding mode differences between natural and non-natural amino acid-based ligands. Several factors potentially affecting the ligand binding affinity and specificity were identified including net charges, dipole moments, and the presence of aromatic rings. On the basis of these findings, linear response models (LRMs) were built for different sets of ligands that showed high correlations (R(2) > 0.95) to the corresponding FEP binding affinities. These results identify some key factors that determine ligand-mGluR1 binding and could be used for future inhibitor designs and support a role for in silico modeling for understanding receptor ligand interactions.

Following publication of the original article [1], it was reported that the given name of the fourteenth author was incorrectly published. The incorrect and the correct names are given below.

Objective:To analyze a glioblastoma tumor specimen with 3 different platforms and compare potentially actionable calls from each.Methods:Tumor DNA was analyzed by a commercial targeted panel. In addition, tumor-normal DNA was analyzed by whole-genome sequencing (WGS) and tumor RNA was analyzed by RNA sequencing (RNA-seq). The WGS and RNA-seq data were analyzed by a team of bioinformaticians and cancer oncologists, and separately by IBM Watson Genomic Analytics (WGA), an automated system for prioritizing somatic variants and identifying drugs.Results:More variants were identified by WGS/RNA analysis than by targeted panels. WGA completed a comparable analysis in a fraction of the time required by the human analysts.Conclusions:The development of an effective human-machine interface in the analysis of deep cancer genomic datasets may provide potentially clinically actionable calls for individual patients in a more timely and efficient manner than currently possible.ClinicalTrials.gov identifier:NCT02725684.

Motivation: Analyses and algorithmic predictions based on high-throughput data are essential for the success of systems biology in academic and industrial settings. Organizations, such as companies and academic consortia, conduct large multi-year scientific studies that entail the collection and analysis of thousands of individual experiments, often over many physical sites and with internal and outsourced components. To extract maximum value, the interested parties need to verify the accuracy and reproducibility of data and methods before the initiation of such large multi-year studies. However, systematic and well-established verification procedures do not exist for automated collection and analysis workflows in systems biology which could lead to inaccurate conclusions. Results: We present here, a review of the current state of systems biology verification and a detailed methodology to address its shortcomings. This methodology named ‘Industrial Methodology for Process Verification in Research’ or IMPROVER, consists on evaluating a research program by dividing a workflow into smaller building blocks that are individually verified. The verification of each building block can be done internally by members of the research program or externally by ‘crowd-sourcing’ to an interested community. www.sbvimprover.com Implementation: This methodology could become the preferred choice to verify systems biology research workflows that are becoming increasingly complex and sophisticated in industrial and academic settings. Contact: gustavo@us.ibm.com

Lebanon is an eastern Mediterranean country inhabited by approximately four million people with a wide variety of ethnicities and religions, including Muslim, Christian, and Druze. In the present study, 926 Lebanese men were typed with Y-chromosomal SNP and STR markers, and unusually, male genetic variation within Lebanon was found to be more strongly structured by religious affiliation than by geography. We therefore tested the hypothesis that migrations within historical times could have contributed to this situation. Y-haplogroup J*(xJ2) was more frequent in the putative Muslim source region (the Arabian Peninsula) than in Lebanon, and it was also more frequent in Lebanese Muslims than in Lebanese non-Muslims. Conversely, haplogroup R1b was more frequent in the putative Christian source region (western Europe) than in Lebanon and was also more frequent in Lebanese Christians than in Lebanese non-Christians. The most common R1b STR-haplotype in Lebanese Christians was otherwise highly specific for western Europe and was unlikely to have reached its current frequency in Lebanese Christians without admixture. We therefore suggest that the Islamic expansion from the Arabian Peninsula beginning in the seventh century CE introduced lineages typical of this area into those who subsequently became Lebanese Muslims, whereas the Crusader activity in the 11(th)-13(th) centuries CE introduced western European lineages into Lebanese Christians.

We have performed molecular dynamics simulations for a total duration of more than 10 µs (with most molecular trajectories being 1 µs in duration) to study, the effect of a single mutation on hen lysozyme protein stability and denaturing, using an IBM Blue Gene/L™ supercomputer. One goal of this study was to assess the use of certain force fields to reproduce experimental results of protein unfolding using thermal denaturing techniques. A second and more important goal was to gain microscopic insights into the mechanism of protein misfolding using both thermal and chemical denaturing techniques. We found that the thermal denaturing results were robust and reproducible with various force fields. The chemical denaturing results explained why the single amino-acid mutation on residue Trp62 causes the disruption of long-range interactions in the tertiary structure. Simulation results revealed that the Trp62 residue was the key to a cooperative long-range interaction within the wild-type protein. Specifically, Trp62 acts as a bridge between two neighboring basic residues through a π-type H-bond or π-cation interaction to form an Arg-Trp-Arg "sandwich-like" structure. Our findings support the general conclusions of the experiment and provide an interesting molecular depiction of the disruption of the long-range interactions.

Biomolecular simulations enabled by massively parallel supercomputers such as BlueGene/L promise to bridge the gap between the currently accessible simulation time scale and the experimental time scale for many important protein folding processes. In this study, molecular dynamics simulations were carried out for both the wild-type and the mutant hen lysozyme (TRP62GLY) to study the single mutation effect on lysozyme stability and misfolding. Our thermal denaturing simulations at 400-500 K with both the OPLSAA and the CHARMM force fields show that the mutant structure is indeed much less stable than the wild-type, which is consistent with the recent urea denaturing experiment (Dobson et al. Science 2002, 295, 1719-1722; Nature 2003, 424, 783-788). Detailed results also reveal that the single mutation TRP62GLY first induces the loss of native contacts in the beta-domain region of the lysozyme protein at high temperatures, and then the unfolding process spreads into the alpha-domain region through Helix C. Even though the OPLSAA force field in general shows a more stable protein structure than does the CHARMM force field at high temperatures, the two force fields examined here display qualitatively similar results for the misfolding process, indicating that the thermal denaturing of the single mutation is robust and reproducible with various modern force fields.

The structural characteristics of a mucin glycopeptide motif derived from the N-terminal fragment STTAV of the cell surface glycoprotein CD43 have been investigated by NMR. In this study, a series of molecules prepared by total synthesis were examined, consisting of the peptide itself, three glycopeptides having clustered sites of alpha-O-glycosylation on the serine and threonine side chains with the Tn, TF, and STF carbohydrate antigens, respectively, and one with the beta-O-linked TF antigen. Additionally, a glycopeptide having the sequence SSSAVAV, triglycosylated with the Le(y) epitope, was investigated. NMR data for the tri-STF-STTAV glycopeptide were used to solve the structure of this construct through restrained molecular dynamics calculations. The calculations revealed a defined conformation for the glycopeptide core rooted in the interaction of the peptide and the first N-acetylgalactosamine residue. The similarity of the NMR data for each of the alpha-O-linked glycopeptides demonstrates that this structure persists for each construct and that the mode of attachment of the first sugar and the peptide is paramount in establishing the organization of the core. The core provides a common framework on which a variety of glycans may be displayed. Remarkably, while there is a profound organizational effect on the peptide backbone with the alpha-linked glycans, attachment via a beta-linkage has little apparent consequence.

In December 1999, IBM announced the start of a five-year effort to build a massively parallel computer, to be applied to the study of biomolecular phenomena such as protein folding. The project has two main goals: to advance our understanding of the mechanisms behind protein folding via large-scale simulation, and to explore novel ideas in massively parallel machine architecture and software. This project should enable biomolecular simulations that are orders of magnitude larger than current technology permits. Major areas of investigation include: how to most effectively utilize this novel platform to meet our scientific goals, how to make such massively parallel machines more usable, and how to achieve performance targets, with reasonable cost, through novel machine architectures. This paper provides an overview of the Blue Gene project at IBM Research. It includes some of the plans that have been made, the intended goals, and the anticipated challenges regarding the scientific work, the software application, and the hardware design.

We introduce a method to fabricate solid-state nanopores at sub-20 nm diameter in membranes with embedded metal electrodes across a 200 mm wafer with CMOS compatible semiconductor processes. Multi-layer (metal-dielectric) structures embedded in membranes were demonstrated with high uniformity (± 0.5 nm) across the wafer. Arrays of nanopores were fabricated with average size of 18 ± 2 nm in diameter using a Reactive Ion Etching (RIE) method in lieu of TEM drilling. Shorts between the membrane-embedded metals were occasionally created after pore formation, but the RIE based pores had a much better yield (99%) of unshorted electrodes compared to TEM drilled pores (

We report sub-20 nm sacrificial nanochannels that enable stretching and translocating single DNA molecules. Sacrificial silicon nano-structures were etched with XeF2 to form nanochannels. Translocations of linearized DNA single molecules were imaged by fluorescence microscopy. Our method offers a manufacturable wafer-scale approach for CMOS-compatible bio-chip platform.

ArunKumar, GaneshPrasad et al.--The Genographic Consortium, Previous studies that pooled Indian populations from a wide variety of geographical locations, have obtained contradictory conclusions about the processes of the establishment of the Varna caste system and its genetic impact on the origins and demographic histories of Indian populations. To further investigate these questions we took advantage that both Y chromosome and caste designation are paternally inherited, and genotyped 1,680 Y chromosomes representing 12 tribal and 19 non-tribal (caste) endogamous populations from the predominantly Dravidian-speaking Tamil Nadu state in the southernmost part of India. Tribes and castes were both characterized by an overwhelming proportion of putatively Indian autochthonous Y-chromosomal haplogroups (H-M69, F-M89, R1a1-M17, L1-M27, R2-M124, and C5-M356; 81% combined) with a shared genetic heritage dating back to the late Pleistocene (10-30 Kya), suggesting that more recent Holocene migrations from western Eurasia contributed, The study is supported by “The Genographic Project” funded by The National Geographic Society, IBM and Waitt Family Foundation. CTS was supported by The Wellcome Trust (Grant number 098051).

Y-chromosome Haplogroup O is the dominant lineage of East Asians, comprising more than a quarter of all males on the world; however, its internal phylogeny remains insufficiently investigated. In this study, we determined the phylogenetic position of recently defined markers (L127, KL1, KL2, P164, and PK4) in the background of Haplogroup O. In the revised tree, subgroup O3a-M324 is divided into two main subclades, O3a1-L127 and O3a2-P201, covering about 20 and 35% of Han Chinese people, respectively. The marker P164 is corrected from a downstream site of M7 to upstream of M134 and parallel to M7 and M159. The marker PK4 is also relocated from downstream of M88 to upstream of M95, separating the former O2(*) into two parts. This revision evidently improved the resolving power of Y-chromosome phylogeny in East Asia.

Autores: Haber, Marc et al., Cultural expansions, including of religions, frequently leave genetic traces of differentiation and in-migration. These expansions may be driven by complex doctrinal differentiation, together with major population migrations and gene flow. The aim of this study was to explore the genetic signature of the establishment of religious communities in a region where some of the most influential religions originated, using the Y chromosome as an informative male-lineage marker. A total of 3139 samples were analyzed, including 647 Lebanese and Iranian samples newly genotyped for 28 binary markers and 19 short tandem repeats on the non-recombinant segment of the Y chromosome. Genetic organization was identified by geography and religion across Lebanon in the context of surrounding populations important in the expansions of the major sects of Lebanon, including Italy, Turkey, the Balkans, Syria, and Iran by employing principal component analysis, multidimensional scaling, and AMOVA. Timing of population differentiations was estimated using BATWING, in comparison with dates of historical religious events to determine if these differentiations could be caused by religious conversion, or rather, whether religious conversion was facilitated within already differentiated populations. Our analysis shows that the great religions in Lebanon were adopted within already distinguishable communities. Once religious affiliations were established, subsequent genetic signatures of the older differentiations were reinforced. Post-establishment differentiations are most plausibly explained by migrations of peoples seeking refuge to avoid the turmoil of major historical events.

The single mutation effect on the binding affinity of H3N2 viral protein hemagglutinin (HA) with the monoclonical antibody fragment (Fab) is studied in this paper using the free energy perturbation (FEP) simulations. An all-atom protein model with explicit solvents is used to perform an aggregate of several microsecond FEP molecular dynamics simulations. A recent experiment shows that a single mutation in H3N2 HA, T131I, increases the antibody-antigen dissociation constant Kd by a factor of approximately 4000 (equivalent to a binding affinity decrease of approximately 5 kcal/mol), thus introducing an escape of the antibody (Ab) neutralization. Our FEP result confirms this experimental finding by estimating the HA-Ab binding affinity decrease of 5.2 +/- 0.9 kcal/mol but with a somewhat different molecular mechanism from the experimental findings. Detailed analysis reveals that this large binding affinity decrease in the T131I mutant is mainly due to the displacement of two bridge water molecules otherwise present in the wild-type HA/Ab interface. The decomposition of the binding free energy supports this observation, as the major contribution to the binding affinity is from the electrostatic interactions. In addition, we find that the loss of the binding affinity is also related to the large conformational distortion of one loop (loop 155-161) in the unbound state of the mutant. We then simulate all other possible mutations for this specific mutation site T131, and predict a few more mutations with even larger decreases in the binding affinity (i.e., better candidates for antibody neutralization), such as T131W, T131Y, and T131F. As for further validation, we have also modeled another mutation, S157L, with experimental binding affinity available (Kd increasing approximately 500 times), and found a binding affinity decrease of 4.1 +/- 1.0 kcal/mol, which is again in excellent agreement with experiment. These large scale simulations might provide new insights into the detailed physical interaction, possible future escape mutation, and antibody-antigen coevolution relationship between influenza virus and human antibodies.

The mitochondrial DNA hypervariable segment I (HVS-I) is widely used in studies of human evolutionary genetics, and therefore accurate estimates of mutation rates among nucleotide sites in this region are essential. We have developed a novel maximum-likelihood methodology for estimating site-specific mutation rates from partial phylogenetic information, such as haplogroup association. The resulting estimation problem is a generalized linear model, with a nonstandard link function. We develop inference and bias correction tools for our estimates and a hypothesis-testing approach for site independence. We demonstrate our methodology using 16,609 HVS-I samples from the Genographic Project. Our results suggest that mutation rates among nucleotide sites in HVS-I are highly variable. The 16,400–16,500 region exhibits significantly lower rates compared to other regions, suggesting potential functional constraints. Several loci identified in the literature as possible termination-associated sequences (TAS) do not yield statistically slower rates than the rest of HVS-I, casting doubt on their functional importance. Our tests do not reject the null hypothesis of independent mutation rates among nucleotide sites, supporting the use of site-independence assumption for analyzing HVS-I. Potential extensions of our methodology include its application to estimation of mutation rates in other genetic regions, like Y chromosome short tandem repeats.

The distributions of residue hydrophobicity for individual domains as well as for the aggregates of domains on a single chain have been found to exhibit well-defined second-order hydrophobic moment profiles. This indicates that most of the domains do fold into a stable entity with a core composed predominantly of hydrophobic residues as well as a prevalence of hydrophobic residues at the interface between domains. A simple scoring function based upon the relative hydrophobic moment dipole orientations shows that 80% of the dipoles of adjacent domains point to each other, highlighting hydrophobic residue prevalence at the domain interfaces.

We propose a mechanism, based on a ≥10-μs molecular dynamics simulation, for the surprising misfolding of hen egg-white lysozyme caused by a single mutation (W62G). Our simulations of the wild-type and mutant lysozymes in 8 M urea solution at biological temperature (with both pH 2 and 7) reveal that the mutant structure is much less stable than that of the wild type, with the mutant showing larger fluctuations and less native-like contacts. Analysis of local contacts reveals that the Trp-62 residue is the key to a cooperative long-range interaction within the wild type, where it acts like a bridge between two neighboring basic residues. Thus, a native-like cluster or nucleation site can form near these residues in the wild type but not in the mutant. The time evolution of the secondary structure also exhibits a quicker loss of the β-sheets in the mutant than in the wild type, whereas some of the α-helices persist during the entire simulation in both the wild type and the mutant in 8 M urea (even though the tertiary structures are basically all gone). These findings, while supporting the general conclusions of a recent experimental study by Dobson and coworkers [Klein-Seetharam J, Oikama M, Grimshaw SB, Wirmer J, Duchardt E, Ueda T, Imoto T, Smith LJ, Dobson CM, Schwalbe H (2002) Science 295:1719–1722], provide a detailed but different molecular picture of the misfolding mechanism.

The history of human migratory events can be inferred from observed variations in DNA sequences. Such studies on non-recombinant mtDNA and Y-chromosome show that present day humans outside Africa originated from one or more migrations of small groups of individuals between 30K-70K YBP. Coalescence theory reveals that, any collection of non-recombinant DNA sequences can be traced back to a common ancestor. Mutations fixed by genetic drift act as markers on the timeline from the common ancestor to the present and can be used to infer migration and founder events that occurred in ancestral populations. However, most mutations seen in the data today are relatively recent and do not carry useful information about deep ancestry. The only ones that can be used reliably are those that can be shown to robustly distinguish large clusters of individuals and thus qualify as true representatives of population events in the past. In this talk, we present results from the analysis of 1737 complete mtDNA sequences from public databases to infer such a robust set of mutations that reveal the haplogroup phylogeny. Using principal component analysis we identify the samples in L, M and N clades and with unsupervised consensus ensemble clustering we infer the substructure in these clades. Traditional methods are inadequate to handle data of this size and complexity. The substructure is inferred using a new algorithm that mitigates the usual problems of sample size bias within haplogroups as well as the sampling bias across haplogroups. First, we cluster the data in each of the M, N, L clades separately into k=2,3,4,... kmax groups using an agreement matrix derived from multiple clustering techniques and bootstrap sampling. Repeated training/test splits of the samples identify robust clusters and patterns of SNPs which can assign haplogroup labels with a reliability greater than 90%. Even though the clustering at each k is done independently, the clusters split in a way that suggests that the data is revealing population events; a cluster at level k has k–2 clusters which are identical with those at level k–1 plus two more that obtain from a split of one of the clusters at level k–1. The clustering is repeated with equal number of samples from the first level clusters. The sequence in which the clusters now split defines a binary network which reveals population events unbiased by sample size. We root the network using an out-group and, assuming a molecular clock, identify an internal node in the bifurcation process which is equidistant from the leaves. This rooting removes the bias across haplogroups which would otherwise influence the order in which the clusters emerge. Our analysis shows that the African clades L0/L1, L2 and L3 have the greatest heterogeneity of SNPs, in agreement with their ancient ancestry. It also suggests that the M, N clades originated from a common ancestor of L3 in two separate migrations. The first migration gave rise to the M haplogroup, whose descendents currently populate South-East Asia and Australia. The second migration resulted in the N haplogroup, accounting for the current populations in China, Japan, Europe, Central Asia and North and South America. We reveal and robustly label many branches of the mtDNA tree, improving current results significantly. We find that for our choice of robust SNPs, the genetic distances between the NA and NRB haplogroups is smaller compared to that between B and J/T/H/V/U. The detailed N migratory sub-tree is rooted so that the T, J and U haplogroups are on one side of the root and the F, V/H, I, X, R5, B, N9, A and W are on the other. We also find a detailed structure for the M tree consistent with prior literature and we infer additional branches for the MD haplogroup. Finally we provide detailed SNP patterns for each haplogroup identified by our clustering. Our patterns can be used to infer a haplogroup assignment with reliability greater than 90%.

A nanofluidic channel, with a pair of perpendicularly aligned nanoelectrodes, is proposed to electrically control the motion of DNA molecules. Using all-atom molecular dynamics simulations, we studied electrostatic responses of a charged DNA molecule in the nanochannel and investigated optimized operating conditions for controlling the DNA molecule. When the transversal electric field was periodically turned on and off, the DNA molecule was correspondingly immobilized on and released from the channel surface. Under simultaneously applied longitudinal biasing and transversal trapping electric fields, the DNA molecule moved forward in a 'ratchet'-like fashion. It is expected that achieving the controlled motion of DNA in the channel can advance studies and applications of a nanochannel-based sensor for analyzing DNA (e.g., DNA sequencing).

We present an efficient algorithm to systematically and automatically identify patterns in protein sequence families. The procedure is based on the Splash deterministic pattern discovery algorithm and on a framework to assess the statistical significance of patterns. We demonstrate its application to the fully automated discovery of patterns in 974 PROSITE families (the complete subset of PROSITE families which are defined by patterns and contain DR records). Splash generates patterns with better specificity and undiminished sensitivity, or vice versa, in 28% of the families; identical statistics were obtained in 48% of the families, worse statistics in 15%, and mixed behavior in the remaining 9%. In about 75% of the cases, Splash patterns identify sequence sites that overlap more than 50% with the corresponding PROSITE pattern. The procedure is sufficiently rapid to enable its use for daily curation of existing motif and profile databases. Third, our results show that the statistical significance of discovered patterns correlates well with their biological significance. The trypsin subfamily of serine proteases is used to illustrate this method's ability to exhaustively discover all motifs in a family that are statistically and biologically significant. Finally, we discuss applications of sequence patterns to multiple sequence alignment and the training of more sensitive score-based motif models, akin to the procedure used by PSI-BLAST. All results are available at httpl//www.research.ibm.com/spat/.

Outbreaks of influenza cause considerable public health concerns and pose a potential threat of a global pandemic. In this paper, we describe some of our recent work on modeling of influenza virus with an IBM Blue Gene® supercomputer. The goal is to predict which mutations [on the viral glycoprotein hemagglutinin (HA)] are likely to occur in the next flu season, which mutations might escape antibody (Ab) neutralization, and which mutations might cause its receptor binding specificity to switch (e.g., from avian to human). We have analyzed more than 4,000 influenza A/H3N2 HA sequences from 1968 to 2010 to model the evolutionary path using a weighted mutual information method, which allows us to build a site transition network to predict antigenic drifts. We then used large-scale free energy perturbation calculations to study the mutation-induced effects on the antigen-Ab and antigen-receptor bindings. For example, we found that a single mutation T131I on H3N2 HA can decrease the HA-Ab binding affinity by 5.2 ± 0.9 kcal/mol, in excellent agreement with recent experimental results. We also found that a double mutation, i.e., V135S and A138S, could potentially switch the H5N1 HA binding specificity from avian to human, thus allowing the virus to gain a foothold in the human population. Detailed analyses also reveal a molecular picture of the influenza virus Ab and receptor binding mechanisms.

PROSITE is a method for protein classification which relies on a database of biologically significant sites and patterns in protein sequences. Most patterns in PROSITE have been gathered by a a labor intensive combination of experimental characterization of functional residues and sequence alignment. In this paper we present a new and efficient supervised learning procedure, based on the Splash deterministic pattern discovery algorithm and on a framework to assess the statistical significance of patterns. We demonstrate its application to the fully automatic discovery of patterns in 974 PROSITE families. For these families, Splash generates patterns with better specificity and/or sensitivity in 28%, identical statistics in 48%, and worse statistics in 15% of the cases; for the remaining families, patterns exhibited mixed behavior. Second, we have characterized the amount of overlap, on the sequences, between newly discovered patterns and those in PROSITE. In about 75% of the cases, Splash patterns identify sequence sites that overlap more than 50% with those reported in PROSITE. Of the 272 patterns which perform strictly better than the corresponding PROSITE pattern, 178 show more than 70% overlap with the PROSITE pattern. Third, our results suggest that the statistical significance of discovered patterns correlates well with their biological significance. Finally, we use the trypsin subfamily of serine proteases to illustrate the use of this method to exhaustively discover all motifs in a family that are statistically and biologically significant. The complete analysis is sufficiently rapid, taking less than a day for all PROSITE families, to enable the use this methodology for routine curation of existing motif and profile databases.

Behar, Doron M. et al.-- The Genographic Consortium, Different lines of evidence point to the resettlement of much of western and central Europe by populations from the Franco-Cantabrian region during the Late Glacial and Postglacial periods. In this context, the study of the genetic diversity of contemporary Basques, a population located at the epicenter of the Franco-Cantabrian region, is particularly useful because they speak a non-Indo-European language that is considered to be a linguistic isolate. In contrast with genome-wide analysis and Y chromosome data, where the problem of poor time estimates remains, a new timescale has been established for the human mtDNA and makes this genome the most informative marker for studying European prehistory. Here, we aim to increase knowledge of the origins of the Basque people and, more generally, of the role of the Franco-Cantabrian refuge in the postglacial repopulation of Europe. We thus characterize the maternal ancestry of 908 Basque and non-Basque individuals from the Basque Country and immediate adjacent regions and, by sequencing 420 complete mtDNA genomes, we focused on haplogroup H. We identified six mtDNA haplogroups, H1j1, H1t1, H2a5a1, H1av1, H3c2a, and H1e1a1, which are autochthonous to the Franco-Cantabrian region and, more specifically, to Basque-speaking populations. We detected signals of the expansion of these haplogroups at ∼4,000 years before present (YBP) and estimated their separation from the pan-European gene pool at ∼8,000 YBP, antedating the Indo-European arrival to the region. Our results clearly support the hypothesis of a partial genetic continuity of contemporary Basques with the preceding Paleolithic/Mesolithic settlers of their homeland., This work was supported by the Institut Pasteur, National Geographic, and the Histoire des populations et variation linguistique dans les Pyrénées de l'Ouest project, which received funding from the Conseil Régional d'Aquitaine, the Conseil Général des Pyrénées-Atlantiques, the Conseil des Elus du Pays-Basque, and the Centre National de la Recherche Scientifique interdisciplinary program Origine de l'Homme, des Langues et du Langage. This study also benefited from the support of Department of Hematology, Centre Hospitalier de la Côte Basque, in Bayonne, and Association Sang 64.