Genetic analysis of foot-and-mouth disease virus serotype A of Indian origin and detection of positive selection and recombination in leader protease- and capsid-coding regions

The leader protease (L-pro) and capsid-coding sequences (P1) constitute approximately 3 kb of the foot-and-mouth disease virus (FMDV). We studied the phylogenetic relationship of 46 FMDV serotype A isolates of Indian origin collected during the period 1968-2005 and also eight vaccine strains using the neighbour-joining tree and Bayesian tree methods. The viruses were categorized under three major groups - Asian, Euro-South American and European. The Indian isolates formed a distinct genetic group among the Asian isolates. The Indian isolates were further classified into different genetic subgroups (<5% divergence). Post-1995 isolates were divided into two subgroups while a few isolates which originated in the year 2005 from Andhra Pradesh formed a separate group. These isolates were closely related to the isolates of the 1970s. The FMDV isolates seem to undergo reverse mutation or onvergent evolution wherein sequences identical to the ancestors are present in the isolates in circulation. The eight vaccine strains included in the study were not related to each other and belonged to different genetic groups. Recombination was detected in the L-pro region in one isolate (A IND 20/82) and in the VP1 coding 1D region in another isolate (A RAJ 21/96). Positive selection was identified at aa positions 23 in the L-pro (P<0.05; 0.046*) and at aa 171 in the capsid protein VP1 (P<0.01; 0.003**).

A consensus genetic map of sorghum that integrates multiple component maps and high-throughput Diversity Array Technology (DArT) markers

Background: Sorghum genome mapping based on DNA markers began in the early 1990s and numerous genetic linkage maps of sorghum have been published in the last decade, based initially on RFLP markers with more recent maps including AFLPs and SSRs and very recently, Diversity Array Technology (DArT) markers. It is essential to integrate the rapidly growing body of genetic linkage data produced through DArT with the multiple genetic linkage maps for sorghum generated through other marker technologies. Here, we report on the colinearity of six independent sorghum component maps and on the integration of these component maps into a single reference resource that contains commonly utilized SSRs, AFLPs, and high-throughput DArT markers. Results: The six component maps were constructed using the MultiPoint software. The lengths of the resulting maps varied between 910 and 1528 cM. The order of the 498 markers that segregated in more than one population was highly consistent between the six individual mapping data sets. The framework consensus map was constructed using a "Neighbours" approach and contained 251 integrated bridge markers on the 10 sorghum chromosomes spanning 1355.4 cM with an average density of one marker every 5.4 cM, and were used for the projection of the remaining markers. In total, the sorghum consensus map consisted of a total of 1997 markers mapped to 2029 unique loci ( 1190 DArT loci and 839 other loci) spanning 1603.5 cM and with an average marker density of 1 marker/0.79 cM. In addition, 35 multicopy markers were identified. On average, each chromosome on the consensus map contained 203 markers of which 58.6% were DArT markers. Non-random patterns of DNA marker distribution were observed, with some clear marker-dense regions and some marker-rare regions. Conclusion: The final consensus map has allowed us to map a larger number of markers than possible in any individual map, to obtain a more complete coverage of the sorghum genome and to fill a number of gaps on individual maps. In addition to overall general consistency of marker order across individual component maps, good agreement in overall distances between common marker pairs across the component maps used in this study was determined, using a difference ratio calculation. The obtained consensus map can be used as a reference resource for genetic studies in different genetic backgrounds, in addition to providing a framework for transferring genetic information between different marker technologies and for integrating DArT markers with other genomic resources. DArT markers represent an affordable, high throughput marker system with great utility in molecular breeding programs, especially in crops such as sorghum where SNP arrays are not publicly available.

Estimation in a multiplicative mixed model involving a genetic relationship matrix.

Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

Statistical analysis of the associations of hereditary factors with the risk of Type 1 diabetes and Diabetic Nephropathy based on the familial data collected through ascertaiment from population-based registers

In genetic epidemiology, population-based disease registries are commonly used to collect genotype or other risk factor information concerning affected subjects and their relatives. This work presents two new approaches for the statistical inference of ascertained data: a conditional and full likelihood approaches for the disease with variable age at onset phenotype using familial data obtained from population-based registry of incident cases. The aim is to obtain statistically reliable estimates of the general population parameters. The statistical analysis of familial data with variable age at onset becomes more complicated when some of the study subjects are non-susceptible, that is to say these subjects never get the disease. A statistical model for a variable age at onset with long-term survivors is proposed for studies of familial aggregation, using latent variable approach, as well as for prospective studies of genetic association studies with candidate genes. In addition, we explore the possibility of a genetic explanation of the observed increase in the incidence of Type 1 diabetes (T1D) in Finland in recent decades and the hypothesis of non-Mendelian transmission of T1D associated genes. Both classical and Bayesian statistical inference were used in the modelling and estimation. Despite the fact that this work contains five studies with different statistical models, they all concern data obtained from nationwide registries of T1D and genetics of T1D. In the analyses of T1D data, non-Mendelian transmission of T1D susceptibility alleles was not observed. In addition, non-Mendelian transmission of T1D susceptibility genes did not make a plausible explanation for the increase in T1D incidence in Finland. Instead, the Human Leucocyte Antigen associations with T1D were confirmed in the population-based analysis, which combines T1D registry information, reference sample of healthy subjects and birth cohort information of the Finnish population. Finally, a substantial familial variation in the susceptibility of T1D nephropathy was observed. The presented studies show the benefits of sophisticated statistical modelling to explore risk factors for complex diseases.

Genetic basis of hereditary colorectal cancers: Hereditary nonpolyposis colorectal cancer and Familial adenomatous polyposis

Hereditary nonpolyposis colorectal cancer (HNPCC) and familial adenomatous polyposis (FAP) are characterized by a high risk and early onset of colorectal cancer (CRC). HNPCC is due to a germline mutation in one of the following MMR genes: MLH1, MSH2, MSH6 and PMS2. A majority of FAP and attenuated FAP (AFAP) cases are due to germline mutations of APC, causing the development of multiple colorectal polyps. To date, over 450 MMR gene mutations and over 800 APC mutations have been identified. Most of these mutations lead to a truncated protein, easily detected by conventional mutation detection methods. However, in about 30% of HNPCC and FAP, and about 90% of AFAP families, mutations remain unknown. We aimed to clarify the genetic basis and genotype-phenotype correlation of mutation negative HNPCC and FAP/AFAP families by advanced mutation detection methods designed to detect large genomic rearrangements, mRNA and protein expression alterations, promoter mutations, phenotype linked haplotypes, and tumoral loss of heterozygosity. We also aimed to estimate the frequency of HNPCC in Uruguayan CRC patients. Our expression based analysis of mutation negative HNPCC divided these families into two categories: 1) 42% of families linked to the MMR genes with a phenotype resembling that of mutation positive, and 2) 58% of families likely to be associated with other susceptibility genes. Unbalanced mRNA expression of MLH1 was observed in two families. Further studies revealed that a MLH1 nonsense mutation, R100X was associated with aberrant splicing of exons not related to the mutation and an MLH1 deletion (AGAA) at nucleotide 210 was associated with multiple exon skipping, without an overall increase in the frequency of splice events. APC mutation negative FAP/AFAP families were divided into four groups according to the genetic basis of their predisposition. Four (14%) families displayed a constitutional deletion of APC with profuse polyposis, early age of onset and frequent extracolonic manifestations. Aberrant mRNA expression of one allele was observed in seven (24%) families with later onset and less frequent extracolonic manifestations. In 15 (52%) families the involvement of APC could neither be confirmed nor excluded. In three (10%) of the families a germline mutation was detected in genes other than APC: AXIN2 in one family, and MYH in two families. The families with undefined genetic basis and especially those with AXIN2 or MYH mutations frequently displayed AFAP or atypical polyposis. Of the Uruguayan CRC patients, 2.6% (12/461) fulfilled the diagnostic criteria for HNPCC and 5.6% (26/461) were associated with increased risk of cancer. Unexpectedly low frequency of molecularly defined HNPCC cases may suggest a different genetic profile in the Uruguayan population and the involvement of novel susceptibility genes. Accurate genetic and clinical characterization of families with hereditary colorectal cancers, and the definition of the genetic basis of "mutation negative" families in particular, facilitate proper clinical management of such families.

ssSNPer: identifying statistically similar SNPs to aid interpretation of genetic association studies

ssSNPer is a novel user-friendly web interface that provides easy determination of the number and location of untested HapMap SNPs, in the region surrounding a tested HapMap SNP, which are statistically similar and would thus produce comparable and perhaps more significant association results. Identification of ssSNPs can have crucial implications for the interpretation of the initial association results and the design of follow-up studies. AVAILABILITY: http://fraser.qimr.edu.au/general/daleN/ssSNPer/

Pheo-type: A diagnostic gene-expression assay for the classification of pheochromocytoma and paraganglioma

Context: Pheochromocytomas and paragangliomas (PPGLs) are heritable neoplasms that can be classified into gene-expression subtypes corresponding to their underlying specific genetic drivers. Objective: This study aimed to develop a diagnostic and research tool (Pheo-type) capable of classifying PPGL tumors into gene-expression subtypes that could be used to guide and interpret genetic testing, determine surveillance programs, and aid in elucidation of PPGL biology. Design: A compendium of published microarray data representing 205 PPGL tumors was used for the selection of subtype-specific genes that were then translated to the Nanostring gene-expression platform. A support vector machine was trained on the microarray dataset and then tested on an independent Nanostring dataset representing 38 familial and sporadic cases of PPGL of known genotype (RET, NF1, TMEM127, MAX, HRAS, VHL, and SDHx). Different classifier models involving between three and six subtypes were compared for their discrimination potential. Results: A gene set of 46 genes and six endogenous controls was selected representing six known PPGL subtypes; RTK1–3 (RET, NF1, TMEM127, and HRAS), MAX-like, VHL, and SDHx. Of 38 test cases, 34 (90%) were correctly predicted to six subtypes based on the known genotype to gene-expression subtype association. Removal of the RTK2 subtype from training, characterized by an admixture of tumor and normal adrenal cortex, improved the classification accuracy (35/38). Consolidation of RTK and pseudohypoxic PPGL subtypes to four- and then three-class architectures improved the classification accuracy for clinical application. Conclusions: The Pheo-type gene-expression assay is a reliable method for predicting PPGL genotype using routine diagnostic tumor samples.

On the basin-scale detection and attribution of human-induced climate change in monsoon precipitation and streamflow

Detecting and quantifying the presence of human-induced climate change in regional hydrology is important for studying the impacts of such changes on the water resources systems as well as for reliable future projections and policy making for adaptation. In this article a formal fingerprint-based detection and attribution analysis has been attempted to study the changes in the observed monsoon precipitation and streamflow in the rain-fed Mahanadi River Basin in India, considering the variability across different climate models. This is achieved through the use of observations, several climate model runs, a principal component analysis and regression based statistical downscaling technique, and a Genetic Programming based rainfall-runoff model. It is found that the decreases in observed hydrological variables across the second half of the 20th century lie outside the range that is expected from natural internal variability of climate alone at 95% statistical confidence level, for most of the climate models considered. For several climate models, such changes are consistent with those expected from anthropogenic emissions of greenhouse gases. However, unequivocal attribution to human-induced climate change cannot be claimed across all the climate models and uncertainties in our detection procedure, arising out of various sources including the use of models, cannot be ruled out. Changes in solar irradiance and volcanic activities are considered as other plausible natural external causes of climate change. Time evolution of the anthropogenic climate change ``signal'' in the hydrological observations, above the natural internal climate variability ``noise'' shows that the detection of the signal is achieved earlier in streamflow as compared to precipitation for most of the climate models, suggesting larger impacts of human-induced climate change on streamflow than precipitation at the river basin scale.

Joint modeling of lithosphere and mantle dynamics: Evaluation of constraints from global tomography models

With the advances in technology, seismological theory, and data acquisition, a number of high-resolution seismic tomography models have been published. However, discrepancies between tomography models often arise from different theoretical treatments of seismic wave propagation, different inversion strategies, and different data sets. Using a fixed velocity-to-density scaling and a fixed radial viscosity profile, we compute global mantle flow models associated with the different tomography models and test the impact of these for explaining surface geophysical observations (geoid, dynamic topography, stress, and strain rates). We use the joint modeling of lithosphere and mantle dynamics approach of Ghosh and Holt (2012) to compute the full lithosphere stresses, except that we use HC for the mantle circulation model, which accounts for the primary flow-coupling features associated with density-driven mantle flow. Our results show that the seismic tomography models of S40RTS and SAW642AN provide a better match with surface observables on a global scale than other models tested. Both of these tomography models have important similarities, including upwellings located in Pacific, Eastern Africa, Iceland, and mid-ocean ridges in the Atlantic and Indian Ocean and downwelling flows mainly located beneath the Andes, the Middle East, and central and Southeast Asia.

Ancient DNA from Hunter-Gatherer and Farmer Groups from Northern Spain Supports a Random Dispersion Model for the Neolithic Expansion into Europe

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Single cell proteomics microchip to profile immune function, with applications in stem cell biology, translational disease mechanism study and clinical therapeutics monitoring

In response to infection or tissue dysfunction, immune cells develop into highly heterogeneous repertoires with diverse functions. Capturing the full spectrum of these functions requires analysis of large numbers of effector molecules from single cells. However, currently only 3-5 functional proteins can be measured from single cells. We developed a single cell functional proteomics approach that integrates a microchip platform with multiplex cell purification. This approach can quantitate 20 proteins from >5,000 phenotypically pure single cells simultaneously. With a 1-million fold miniaturization, the system can detect down to ~100 molecules and requires only ~104 cells. Single cell functional proteomic analysis finds broad applications in basic, translational and clinical studies. In the three studies conducted, it yielded critical insights for understanding clinical cancer immunotherapy, inflammatory bowel disease (IBD) mechanism and hematopoietic stem cell (HSC) biology.

To study phenotypically defined cell populations, single cell barcode microchips were coupled with upstream multiplex cell purification based on up to 11 parameters. Statistical algorithms were developed to process and model the high dimensional readouts. This analysis evaluates rare cells and is versatile for various cells and proteins. (1) We conducted an immune monitoring study of a phase 2 cancer cellular immunotherapy clinical trial that used T-cell receptor (TCR) transgenic T cells as major therapeutics to treat metastatic melanoma. We evaluated the functional proteome of 4 antigen-specific, phenotypically defined T cell populations from peripheral blood of 3 patients across 8 time points. (2) Natural killer (NK) cells can play a protective role in chronic inflammation and their surface receptor – killer immunoglobulin-like receptor (KIR) – has been identified as a risk factor of IBD. We compared the functional behavior of NK cells that had differential KIR expressions. These NK cells were retrieved from the blood of 12 patients with different genetic backgrounds. (3) HSCs are the progenitors of immune cells and are thought to have no immediate functional capacity against pathogen. However, recent studies identified expression of Toll-like receptors (TLRs) on HSCs. We studied the functional capacity of HSCs upon TLR activation. The comparison of HSCs from wild-type mice against those from genetics knock-out mouse models elucidates the responding signaling pathway.

In all three cases, we observed profound functional heterogeneity within phenotypically defined cells. Polyfunctional cells that conduct multiple functions also produce those proteins in large amounts. They dominate the immune response. In the cancer immunotherapy, the strong cytotoxic and antitumor functions from transgenic TCR T cells contributed to a ~30% tumor reduction immediately after the therapy. However, this infused immune response disappeared within 2-3 weeks. Later on, some patients gained a second antitumor response, consisted of the emergence of endogenous antitumor cytotoxic T cells and their production of multiple antitumor functions. These patients showed more effective long-term tumor control. In the IBD mechanism study, we noticed that, compared with others, NK cells expressing KIR2DL3 receptor secreted a large array of effector proteins, such as TNF-α, CCLs and CXCLs. The functions from these cells regulated disease-contributing cells and protected host tissues. Their existence correlated with IBD disease susceptibility. In the HSC study, the HSCs exhibited functional capacity by producing TNF-α, IL-6 and GM-CSF. TLR stimulation activated the NF-κB signaling in HSCs. Single cell functional proteome contains rich information that is independent from the genome and transcriptome. In all three cases, functional proteomic evaluation uncovered critical biological insights that would not be resolved otherwise. The integrated single cell functional proteomic analysis constructed a detail kinetic picture of the immune response that took place during the clinical cancer immunotherapy. It revealed concrete functional evidence that connected genetics to IBD disease susceptibility. Further, it provided predictors that correlated with clinical responses and pathogenic outcomes.

Calibrating Analytical Models for Semilocal Strings

In this work we calibrate two different analytic models of semilocal strings by constraining the values of their free parameters. In order to do so, we use data obtained from the largest and most accurate field theory simulations of semilocal strings to date, and compare several key properties with the predictions of the models. As this is still work in progress, we present some preliminary results together with descriptions of the methodology we are using in the characterisation of semilocal string networks.

接收函数方法与中国及邻区上地幔间断面的研究

The receiver function method applied in researching the discontinuities in upper mantle was systematically studied in this paper. Using the theoretical receiver functions, the characteristics of P410S and P660S phases were analyzed, and the influencing factors for detection of these phases were discussed. The stability of receiver function was studied, and a new computational method of receiver function, RFSSMS (Receiver Function of Stack and Smooth of Multi seismic-records at a Single station), was put forward. We built initial reference velocity model for the media beneath each of 18 seismic stations respectively; then estimated the buried depths of 410-km and 660-km discontinuities(simply marked as '410' and '660') under the stations by using the arrive time differences of P410S and P660S with P. We developed a new receiver function inversion method -PGARFI (Peeling-Genetic Algorithm of Receiver Function Inversion), to obtain the whole crust and upper mantle velocity structure and the depths of discontinuities beneath a station. The major works and results could be summarized as follows: (1) By analysis of the theoretical receiver functions with different velocity models and different ray parameters, we obtain the knowledge: The amplitudes of P410S and P660S phases are decreasing with the increasing of epicentral distance A , and the arrival time differences of these phases with P are shorter as A is longer. The multiple refracted and/or reflected waves yielded on Moho and the discontinuities in the crust interfere the identification of P410S. If existing LVZ under the lithosphere, some multiple waves caused by LVZ will interfere the identification of P410S. The multiple waves produced by discontinuity lied near 120km depth will mix with P410s phase in some range of epicentral distance; and the multiple waves concerned with the discontinuity lied near 210km depth will interfere the identification of P660S. The epicentral distance for P4i0s identification is limited, the upper limit is 80° . The identification of P660S is not restricted by the epicenter distance obviously. The identification of P410S and P6gos in the theoretical receiver functions is interfered weakly from the seismic wave attenuation caused by the media absorption if the Q value in a reasonable range. (2) The stability of receiver function was studied by using synthetic seismograms with different kind of noise. The results show that on the condition of high signal-noise-ratio of seismic records, the high frequency background noise and the low frequency microseism noise do not influence the calculating result of receiver function. But the media "scattering noise" influence the stability of receiver function. When the scattering effect reach some level, the identification of P4iOs and P66os is difficult in single receiver function which is yielded from only one seismic record. We provided a new method to calculate receiver function, that is, with a group of earthquake records, stacking the R and Z components respectively in the frequency domain, and weighted smooth the stacked Z component, then compute the complex spectrum ratio of R to Z. This method can improve the stability of receiver function and protrude the P4i0s and P66os in the receiver function curves. (3) 263 receiver functions were provided from 1364 three component broadband seismograms recorded at 18 stations in China and adjacent areas for the tele-earthquakes. The observed arrival time differences of P410S and P660S with P were obtained in these receiver functions. The initial velocity model for every station was built according to the prior research results. The buried depths of '410' and '660' under a station were acquired by the way of adjusting the depths of these two discontinuities in the initial velocity model until the theoretical arrival time differences of P410S and P660S with P well conformed to the observed. The results show an obvious lateral heterogeneity of buried depths of ' 410' and (660' . The depth of '410' is shallower beneath BJI, XAN, LZH and ENH, but deeper under QIZ and CHTO, and the average is 403km . The average depth of '660' is 663km, deeper under MDJ and MAJO, but shallower under QIZ and HYB. (4) For inversing the whole crust and upper mantle velocity structure, a new inversion method -PGARFI (Peeling-Genetic Algorithm of Receiver Function Inversion) has- been developed here. The media beneath a station is divided into segments, then the velocity structure is inversed from receiver function from surface to deep successively. Using PGARFI, the multi reflection / refraction phases of shallower discontinuities are isolated from the first order refraction transform phase of deep discontinuity. The genetic algorithm with floating-point coding was used hi the inversion of every segment, and arithmetical crossover and non-uniform mutation technologies were employed in the genetic optimization. 10 independent inversions are completed for every segment, and 50 most excellent velocity models are selected according to the priority of fitness from all models produced in the inversion process. The final velocity structure of every segment is obtained from the weighted average of these 50 models. Before inversion, a wide range of velocity variation with depth and depth range of the main discontinuities are given according to priori knowledge. PGARFI was verified with numerical test and applied in the inversion of the velocity structure beneath HIA station down to 700km depth.

A survey of fingerprint classification Part I: taxonomies on feature extraction methods and learning models

This paper reviews the fingerprint classification literature looking at the problem from a double perspective. We first deal with feature extraction methods, including the different models considered for singular point detection and for orientation map extraction. Then, we focus on the different learning models considered to build the classifiers used to label new fingerprints. Taxonomies and classifications for the feature extraction, singular point detection, orientation extraction and learning methods are presented. A critical view of the existing literature have led us to present a discussion on the existing methods and their drawbacks such as difficulty in their reimplementation, lack of details or major differences in their evaluations procedures. On this account, an experimental analysis of the most relevant methods is carried out in the second part of this paper, and a new method based on their combination is presented.

Impairments of hippocampal synaptic plasticity induced by aggregated beta-amyloid (25-35) are dependent on stimulation-protocol and genetic background

The aggregation of beta-amyloid to plaques in the brain is one of the hallmarks of Alzheimer disease (AD). Numerous studies have tried to elucidate to what degree amyloid peptides play a role in the neurodegenerative developments seen in AD. While most studies report an effect of amyloid on neural activity and cognitive abilities of rodents, there have been many inconsistencies in the results. This study investigated to what degree the different genetic backgrounds affect the outcome of beta-amyloid fragment (25-35) on synaptic plasticity in vivo in the rat hippocampus. Two strains, Wistar and Lister hooded rats, were tested. In addition, the effects of a strong (600 stimuli) and a weak stimulation protocol (100 stimuli) on impairments of LTP were analysed. Furthermore, since the state of amyloid aggregation appears to play a role in the induction of toxic processes, it was tested by dual polarisation interferometry to what degree and at what speed beta-amyloid (25-35) can aggregate in vitro. It was found that 100 nmol beta-amyloid (25-35) injected icv did impair LTP in Wistar rats when using the weak but not the strong stimulation protocol (P <0.001). One-hundred nano mole of the reverse sequence amyloid (35-25) had no effect. LTP in Lister Hooded rats was not impaired by amyloid at any stimulation protocol. The aggregation studies showed that amyloid (25-35) aggregated within hours, while amyloid (35-25) did not. These results show that the genetic background and the stimulation protocol are important variables that greatly influence the experimental outcome. The fact that amyloid (25-35) aggregated quickly and showed neurophysiological effects, while amyloid (35-25) did not aggregate and did not show any effects indicates that the state of aggregation plays an important role in the physiological effects.