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This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made., The Solar Occultation (SO) channel of the Nadir and Occultation for Mars Discovery (NOMAD) instrument scans the Martian atmosphere since 21 April 2018. In this work, we present a subset of the NOMAD SO data measured at the mesosphere. We focused on a spectral range that started to be recorded in Martian year (MY) 35. A total of 968 vertical profiles of carbon dioxide density and temperature covering MY 35 and the beginning of MY 36 were investigated until 135° of solar longitude. We compared 47 profiles with co-located profiles of the Mars Climate Sounder onboard the Mars Reconnaissance Orbiter. Most profiles show a good agreement as SO temperatures are only 1.8 K higher, but some biases lead to an average absolute difference of 7.4°K. The SO data set is also compared with simulations from the Global Environmental Multiscale-Mars general circulation model. Both data sets are in good agreement except for the presence of a cold layer in the winter hemisphere and a warm layer at dawn in the Northern hemisphere for solar longitudes between 240° and 360°. Five profiles contain temperatures lower than the limit for CO2 condensation. Strong warm layers were found in 13.5% of the profiles. They are present mainly at dawn and in the winter hemisphere, while the Northern dusks appear featureless. The data set mainly covers high latitudes around 60° and we derived some non-migrating tides. In the Southern winter hemisphere, we derived apparent zonal wavenumber-1 (WN-1) and WN-3 tidal components with a maximum amplitude of 10% and 5% at 63 km, respectively. © 2023. The Authors., The NOMAD experiment is led by the Royal Belgian Institute for Space Aeronomy (IASB-BIRA), assisted by Co-PI teams from Spain (IAA-CSIC), Italy (INAF-IAPS), and the United Kingdom (Open University). This project acknowledges funding by the Belgian Science Policy Office (BELSPO), with financial and contractual coordination by the ESA Prodex Office (PEA 4000103401 and 4000121493), the Spanish Ministry of Science and Innovation (MCIU), and European funds under Grants PGC2018-101836-B-I00 and ESP2017-87143-R (MINECO/FEDER), as well as by UK Space Agency through Grants ST/V002295/1, ST/V005332/1, and ST/S00145X/1 and Italian Space Agency through Grant 2018-2-HH.0. This work was supported by the Belgian Fonds de la Recherche Scientifique—FNRS under Grant 30442502 (ET_HOME). This project received funding from the European Union's Horizon 2020 research and innovation program under Grant 101004052 (RoadMap project). The IAA/CSIC team acknowledges financial support from the State Agency for Research of the Spanish MCIU through the “Center of Excellence Severo Ochoa” award for the Instituto de Astrofísica de Andalucía (SEV-2017-0709) and funding by Grant PGC2018-101836-B-100 (MCIU/AEI/FEDER, EU). G. Villanueva is supported by the National Aeronautics and Space Administration., With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made., The Solar Occultation (SO) channel of the Nadir and Occultation for Mars Discovery (NOMAD) instrument has been scanning the Martian atmosphere for almost 2 Martian years. In this work, we present a subset of the NOMAD SO data measured at the mesosphere at the terminator. From the data set, we investigated 968 vertical profiles of carbon dioxide density and temperature covering the Martian Year (MY) 35 as well as MY 36 up to a solar longitude (Ls) of 135° and altitudes around 60–100 km. While carbon dioxide density profiles are directly retrieved from the spectral signature in the spectra, temperature profiles are more challenging to retrieve as unlike density profiles, temperature profiles can present some spurious features if the regularization is not correctly managed. Comparing seven regularization methods, we found that the expected error estimation method provides the best regularization parameters. The vertical resolution of the profiles is on average 1.6 km. Numerous warm layers and cold pockets appear in this data set. The warm layers are found in the Northern hemisphere at dawn and dusk as well as in the Southern hemisphere at dawn. Strong warm layers are present in more than 13.5% of the profiles. The Southern hemisphere at dusk does not present any warm layer between Ls 50° and 150°. The height and latitudinal distribution of those warm layers were similar in MY 35 and MY 36 during the first half of the year (Ls = 0°–135°). © 2023. The Authors., The NOMAD experiment is led by the Royal Belgian Institute for Space Aeronomy (IASB-BIRA), assisted by Co-PI teams from Spain (IAA-CSIC), Italy (INAF-IAPS), and the United Kingdom (Open University). This project acknowledges funding by the Belgian Science Policy Office (BELSPO), with the financial and contractual coordination by the ESA Prodex Office (PEA 4000103401 and 4000121493), by the Spanish Ministry of Science and Innovation (MCIU), and by European funds under Grants PGC2018-101836-B-I00 and ESP2017-87143-R (MINECO/FEDER), as well as by UK Space Agency through Grants ST/V002295/1, ST/V005332/1, and ST/S00145X/1 and Italian Space Agency through Grant 2018-2-HH.0. This work was supported by the Belgian Fonds de la Recherche Scientifique—FNRS under Grant 30442502 (ET_HOME). This project has received funding from the European Union's Horizon 2020 research and innovation program under Grant 101004052 (RoadMap project). The IAA/CSIC team acknowledges financial support from the State Agency for Research of the Spanish MCIU through the “Center of Excellence Severo Ochoa” award for the Instituto de Astrofísica de Andalucía (SEV-2017-0709) and funding by Grant PGC2018-101836-B-100 (MCIU/AEI/FEDER, EU). G. Villanueva was supported by the National Aeronautics and Space Administration., With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).

Comparisons between machine learning and optimal transport-based approaches in classifying images are made in underwater orbital angular momentum (OAM) communications. A model is derived that justifies optimal transport for use in attenuated water environments. OAM pattern demultiplexing is performed using optimal transport and deep neural networks and compared to each other. Additionally, some of the complications introduced by signal attenuation are highlighted. The Radon cumulative distribution transform (R-CDT) is applied to OAM patterns to transform them to a linear subspace. The original OAM images and the R-CDT transformed patterns are used in several classification algorithms, and results are compared. The selected classification algorithms are the nearest subspace algorithm, a shallow convolutional neural network (CNN), and a deep neural network. It is shown that the R-CDT transformed images are more accurate than the original OAM images in pattern classification. Also, the nearest subspace algorithm performs better than the selected CNNs in OAM pattern classification in underwater environments.

Detection of gene fusions is important for discovery of cancer drivers and clinical oncology testing, but existing software tools for fusion detection usually take hours to run and may fail to find lowly expressed fusions. To overcome these limitations, we developed the Fuzzion2 program, which uses pattern matching to detect known gene fusions in unmapped paired-read RNA-Seq data. Given a set of patterns representing fusion transcript breakpoints, Fuzzion2 finds every read pair matching any of the patterns. Both exact and inexact (fuzzy) matches are detected; the fuzzy matching tolerates variations caused by sequencing errors, SNVs, and indels. By employing a novel index of frequency minimizers, Fuzzion2 needs only minutes to process a sample. We have also developed pipelines to produce patterns for Fuzzion2, from fusion contig sequences, from genomic breakpoints in DNA and RNA, and from fusion protein sequences. To evaluate its applicability in clinical testing, we ran Fuzzion2 on ~2,000 RNA-seq samples profiled by the St. Jude clinical genomics program and confirmed its sensitivity in identifying lowly expressed fusions, such as KIAA1549-BRAF in low-grade glioma, which are frequently missed by commonly used fusion detection programs. Notably, Fuzzion2 detected a subclonal BCR-ABL1 fusion expressed at 1% and 6% of the wild-type BCR and ABL1 transcription level, respectively, in a B-lineage ALL sample that also has an IGH-CRLF fusion. Processing RNA-seq data from BCR-ABL1 cell lines, K562 with p210 fusion and OP1 with p190 fusion, diluted at 1:10, 1:100, and 1:1000 showed that Fuzzion2 can detect the fusion at 1:10-1:100 dilution, achieving a sensitivity 10 times greater than that of other fusion detection programs. We also evaluated the performance of Fuzzion2 for large-scale data mining in a study to compare the prevalence of gene fusions in pediatric versus adult cancers. We assembled a set of 15,474 patterns representing 5,480 fusions identified in the Pediatric Cancer Genome Project, NCI TARGET, clinical sequencing, and the COSMIC database. Fuzzion2 was deployed to the NCI Cancer Genomics Cloud and analyzed 9,464 TCGA RNA-seq samples from adult solid and brain tumors. Processing took an average of 6 minutes at a cost of only US$0.16 per sample. Among the 105 recurrent fusions identified in pediatric cancers, only 11 were also found in adult cancers. These shared fusions can be classified into two categories: 1) gene fusions present in cancers that occur in both children and young adults, e.g., synovial sarcoma, papillary thyroid cancer, and fibrolamellar hepatocellular carcinoma; and 2) kinase fusions involving ABL1, NTRK, and FGFR. Our experience with Fuzzion2 demonstrates that it is a powerful tool for time-critical clinical application and large-scale data mining. It is publicly available at https://github.com/stjude/fuzzion2. Citation Format: Stephen V. Rice, Michael N. Edmonson, Liqing Tian, Michael Rusch, David A. Wheeler, Jennifer L. Neary, Scott Newman, Lu Wang, Patrick R. Blackburn, Michael Macias, Andrew Thrasher, Jian Wang, Mark R. Wilkinson, Xin Zhou, Jinghui Zhang. Fuzzion2: Fast, sensitive detection of known gene fusions by fuzzy pattern matching for clinical testing and large-scale data mining [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4092.

Abrupt increases of sensory input (onsets) likely reflect the occurrence of novel events or objects in the environment, potentially requiring immediate behavioral responses. Accordingly, onsets elicit a transient and widespread modulation of ongoing electrocortical activity: the Vertex Potential (VP), which is likely related to the optimisation of rapid behavioral responses. In contrast, the functional significance of the brain response elicited by abrupt decreases of sensory input (offsets) is more elusive, and a detailed comparison of onset and offset VPs is lacking. In four experiments conducted on 44 humans, we observed that onset and offset VPs share several phenomenological and functional properties: they (1) have highly similar scalp topographies across time, (2) are both largely comprised of supramodal neural activity, (3) are both highly sensitive to surprise and (4) co-occur with similar modulations of ongoing motor output. These results demonstrate that the onset and offset VPs largely reflect the activity of a common supramodal brain network, likely consequent to the activation of the extralemniscal sensory system which runs in parallel with core sensory pathways. The transient activation of this system has clear implications in optimizing the behavioral responses to surprising environmental changes.

Turbulence and attenuation are signal degrading factors that can severely hinder free-space and underwater OAM optical pattern demultiplexing. A variety of state-of-the-art convolutional neural network architectures are explored to identify which, if any, provide optimal performance under these non-ideal environmental conditions. Hyperparameter searches are performed on the architectures to ensure that near-ideal settings are used for training. Architectures are compared in various scenarios and the best performing, with their settings, are provided. We show that from the current state-of-the-art architectures, DenseNet outperforms all others when memory is not a constraint. When memory footprint is a factor, ShuffleNet is shown to performed the best.

Signal attenuation, resulting in low signal to noise ratio (SNR), in underwater optical communications (UWOC) is a problem that degrades classification performance. We develop and contrast several novel ways to create machine learning (ML) and optimal transport-based attenuation models and insert these models in a convolutional neural network (CNN) classification training pipeline. We show that including these ML-based attenuation models in the CNN classifier training, significantly improves classification performance.

Methyl-DNA immunoprecipitation is used in combination with next generation sequencing (MeDIP-seq) as a genome-wide approach to enrich for and analyze methylated DNA. Fragmented DNA containing methylated cytosines is purified from genomic samples via an antibody to 5-methylcytosine (5mC), then sequenced and analyzed in order to detect peaks of differential methylation across the genomic landscape. Introduced more than a decade ago, MeDIP enrichment is considered a useful, repeatable, and affordable approach for methylation research. As next generation sequencing has become increasingly accessible and affordable, deep sequencing of the enriched DNA has replaced the initial use of microarrays. At this time, researchers consider MeDIP-seq a viable protocol to answer most questions about DNA methylation, providing single-base resolution is not required. Many well-established downstream analysis tools are also available, making MeDIP-seq a consistently popular option. As we continue to engage with highly complex methylomes, which may vary tremendously by cell-type, timepoint, and environment, we must focus on proper study design, larger cohorts, and judicious deployment of experimental controls in order to pull meaningful signals from background noise.

We pursued our ground-based seasonal monitoring of hydrogen peroxide on Mars using thermal imaging spectroscopy, with two observations of the planet near opposition, in May 2016 (solar longitude Ls = 148.5°, diameter = 17 arcsec) and July 2018 (Ls = 209°, diameter = 23 arcsec). Data were recorded in the 1232–1242 cm−1 range (8.1 μm) with the Texas Echelon Cross Echelle Spectrograph (TEXES) mounted at the 3 m Infrared Telescope Facility (IRTF) at the Mauna Kea Observatories. As in the case of our previous analyses, maps of H2O2 were obtained using line depth ratios of weak transitions of H2O2 divided by a weak CO2 line. The H2O2 map of April 2016 shows a strong dichotomy between the northern and southern hemispheres, with a mean volume mixing ratio of 45 ppbv on the north side and less than 10 ppbv on the south side; this dichotomy was expected by the photochemical models developed in the LMD Mars Global Climate Model (LMD-MGCM) and with the recently developed Global Environmental Multiscale (GEM) model. The second measurement (July 2018) was taken in the middle of the MY 34 global dust storm. H2O2 was not detected with a disk-integrated 2σ upper limit of 10 ppbv, while both the LMD-MGCM and the LEM models predicted a value above 20 ppbv (also observed by TEXES in 2003) in the absence of dust storm. This depletion is probably the result of the high dust content in the atmosphere at the time of our observations, which led to a decrease in the water vapor column density, as observed by the PFS during the global dust storm. GCM simulations using the GEM model show that the H2O depletion leads to a drop in H2O2, due to the lack of HO2 radicals. Our result brings a new constraint on the photochemistry of H2O2 in the presence of a high dust content. In parallel, we reprocessed the whole TEXES dataset of H2O2 measurements using the latest version of the GEISA database (GEISA 2015). We recently found that there is a significant difference in the H2O2 line strengths between the 2003 and 2015 versions of GEISA. Therefore, all H2O2 volume mixing ratios up to 2014 from TEXES measurements must be reduced by a factor of 1.75. As a consequence, in four cases (Ls around 80°, 100°, 150°, and 209°) the H2O2 abundances show contradictory values between different Martian years. At Ls = 209° the cause seems to be the increased dust content associated with the global dust storm. The inter-annual variability in the three other cases remains unexplained at this time.

Major gains have been made in recent years in object recognition due to advances in deep convolutional neural networks. One struggle with deep learning is identifying an optimal network architecture for a given problem. Often different configurations are tried until one is identified that gives acceptable results. This paper proposes an asynchronous learning algorithm that finds an optimal network configuration by automatically adjusting network hyperparameters.

Major gains have been made in recent years in object recognition due to advances in deep neural networks. One struggle with deep learning, however, revolves around the fact that currently it is unknown what network architecture is best for a given problem. Consequently, different configurations are tried until one is identified that gives acceptable results. This paper proposes an asynchronous reinforcement learning algorithm that finds an optimal network configuration by automatically adjusting parameters for a given problem. It is shown that asynchronous reinforcement learning is able to converge on an optimal solution for the MNIST data set.

Background We recently assessed blood-based miRNA expression profiles for association with age in a cohort of 895 Mexican Americans. Of 2,747 miRNAs that were tested (including SNP-derived and novel miRNAs in addition to those reported in miRBase 21), we identified significant associations for 46 known miRNAs (p Methods We conducted in vivo studies to test for correlations between blood and brain miR-34a-5p expression across seven brain regions in four baboons. Then, to investigate the consequences of increased miRNA expression on gene expression, we transfected four neuronal and glial cell lines (CHP-212, HCN-2, SVG-P12 and A172) with a miR-34a-5p mimic. We performed functional annotation of genes that were at least 2-fold up- or down-regulated in each of the cell lines using DAVID. Results Our in vivo studies using baboons as a model organism show moderate to strong correlation of miR-34a-5p expression across blood and amygdala (r=0.69), dorsal anterior cingulate cortex (r=0.95), hypothalamus (r=0.77), lateral orbitofrontal cortex (r=0.81) and medial orbitofrontal cortex (0.56), further strengthening its potential role in neuropsychiatric disease. Our in vitro studies identified several functional categories and gene ontologies that were consistent across two or more cell lines, including phosphoprotein, alternative splicing, protein binding and cell cycle. Discussion Through a combination of in vivo, in vitro and in silico studies, we strengthen the argument for miR-34a-5p as an important player in neuropsychiatric research. Our findings suggest important downstream consequences of induced overexpression of miR-34a-5p. We are currently trying to develop a novel unbiased in vitro method to detect miRNA-mRNA binding interactions that would be broadly applicable to any cell type using miR-34a-5p as a model.

Background Given the inaccessibility of brain tissue for large cohort-based and longitudinal studies, analysis of peripheral blood as a surrogate tissue has become a mainstay within the neuropsychiatric field for analysis of gene and miRNA expression and DNA methylation. Although the importance of peripheral biomarkers as diagnostic and prognostic indicators is well recognized, translation of findings into meaningful pathology is more difficult to achieve. Lack of validation of peripheral biomarkers in brain tissue may be confounded by smaller sample sizes, investigation of inappropriate brain regions, or post-mortem complications. Methods To shed some light on the utility of blood-based biomarkers to inform upon pathology of disease, we investigated correlations between miRNA expression levels in blood and brain tissue from 14 cortical and subcortical regions within two groups of baboons (n=4, n=6; 7 brain regions each). To better understand how blood-brain correlations might relate to human biology and disease, we investigated a subset of 212 miRNAs whose peripheral blood expression was at least moderately correlated (r≥0.5) with 50% or more of the brain regions examined in a family-based cohort of Mexican Americans (n=896) for whom we have extensive neurocognitive and neuroanatomical phenotypes as well as peripheral blood miRNA profiles. We tested 145 human peripheral blood-expressed miRNAs for association against 34 cortical and 10 subcortical structures (using magnetic resonance imaging data), and 24 neurocognitive phenotypes. Due to high inter-relatedness and potentially unknown correlations across many of the phenotypes assessed, we corrected only for the number of miRNAs tested, setting the significance threshold at p Results The overall correlation (r) of miRNA expression profiles between blood and 14 different brain regions in baboons ranged from 0.62–0.66. We identified 444 miRNAs that were expressed in 90% of all samples analyzed and of these, 212 showed at least moderate correlation (r≥0.5) between blood and 50% or more of the brain regions examined. Within this subset of baboon-defined correlated miRNAs, we identified 145 that were also expressed in at least 90% of our human cohort and tested these for association with neurological traits. We identified 34 significant associations between miRNAs and neurological traits. Of these, one of the most interesting findings was association of peripheral miR-144-3p expression with amygdala (p=8.50×10-5) and hippocampus (p=5.86×10-5) volumes, as well as thickness of the fusiform gyrus (p=1.98×10-5). In our baboon study, peripheral expression of this miRNA was highly correlated with expression in the amygdala (r=1.00) and hippocampus (r=0.66), expression was not measured in the fusiform gyrus. Discussion Prior studies have shown that overexpression of miR-144-3p in the basolateral amygdala of mice rescued impaired fear extinction, and also that expression of miR-144-3p is increased in the hippocampus of rats following chronic treatment of both lithium and valproate mood stabilizers. Our studies highlight the utility of using peripheral blood as a surrogate tissue for miRNA profiling and indicate that disease associations identified using peripheral blood may point toward pathological processes within the brain, particularly for miRNAs whose expression is correlated between blood and brain.

Although DNA methylation is now recognized as an important mediator of complex diseases, the extent to which the genetic basis of such diseases is accounted for by DNA methylation is unknown. In the setting of large, extended families representing a minority, high-risk population of the USA, we aimed to characterize the role of epigenome-wide DNA methylation in type 2 diabetes (T2D). Using Illumina HumanMethylation450 BeadChip arrays, we tested for association of DNA methylation at 446 356 sites with age, sex and phenotypic traits related to T2D in 850 pedigreed Mexican-American individuals. Robust statistical analyses showed that (i) 15% of the methylome is significantly heritable, with a median heritability of 0.14; (ii) DNA methylation at 14% of CpG sites is associated with nearby sequence variants; (iii) 22% and 3% of the autosomal CpG sites are associated with age and sex, respectively; (iv) 53 CpG sites were significantly associated with liability to T2D, fasting blood glucose and insulin resistance; (v) DNA methylation levels at five CpG sites, mapping to three well-characterized genes (TXNIP, ABCG1 and SAMD12) independently explained 7.8% of the heritability of T2D (vi) methylation at these five sites was unlikely to be influenced by neighboring DNA sequence variation. Our study has identified novel epigenetic indicators of T2D risk in Mexican Americans who have increased risk for this disease. These results provide new insights into potential treatment targets of T2D.

Both environmental and genetic factors contribute to schizophrenia; however, the exact etiology of this disorder is not known. Animal models are utilized to better understand the mechanisms associated with neuropsychiatric diseases, including schizophrenia. One of these involves gestational administration of methylazoxymethanol acetate (MAM) to induce a developmental disruption, which in turn produces a schizophrenia-like phenotype in post-pubertal rats. The mechanisms by which MAM produces this phenotype are not clear; however, we now demonstrate that MAM induces differential DNA methylation, which may be heritable. Here we demonstrate that a subset of both second (F2) and third (F3) filial generations of MAM-treated rats displays a schizophrenia-like phenotype and hypermethylation of the transcription factor, Sp5. Specifically, ventral tegmental area of dopamine neuron activity was examined using electrophysiology as a correlate for the dopamine hyperfunction thought to underlie psychosis in patients. Interestingly, only a subset of F2 and F3 MAM rats exhibited increases in dopamine neuron population activity, indicating that this may be a unique model with a susceptibility to develop a schizophrenia-like phenotype. An increase in dopamine system function in rodent models has been previously associated with decreases in hippocampal GABAergic transmission. In line with these observations, we found a significant correlation between hippocampal parvalbumin expression and dopamine neuron activity in F2 rats. These data therefore provide evidence that offspring born from MAM-treated rats possess a susceptibility to develop aspects of a schizophrenia-like phenotype and may provide a useful tool to investigate gene–environment interactions.

We conducted a comparative study of multiplexed affinity enrichment sequence methodologies (MBD-seq and MeDIP-seq) in a rodent model of schizophrenia, induced by in utero methylazoxymethanol acetate (MAM) exposure. We also examined related gene expression changes using a pooled sample approach. MBD-seq and MeDIP-seq identified 769 and 1771 differentially methylated regions (DMRs) between F2 offspring of MAM-exposed rats and saline control rats, respectively. The assays showed good concordance, with ~ 56% of MBD-seq-detected DMRs being identified by or proximal to MeDIP-seq DMRs. There was no significant overlap between DMRs and differentially expressed genes, suggesting that DNA methylation regulatory effects may act upon more distal genes, or are too subtle to detect using our approach. Methylation and gene expression gene ontology enrichment analyses identified biological processes important to schizophrenia pathophysiology, including neuron differentiation, prepulse inhibition, amphetamine response, and glutamatergic synaptic transmission regulation, reinforcing the utility of the MAM rodent model for schizophrenia research.

Background There is growing interest in the hypertriglyceridemic waist (HTGW) phenotype, defined as high waist circumference (≥95 cm in males and ≥80 cm in females) combined with high serum triglyceride concentration (≥2.0 mmol/L in males and ≥1.5 mmol/L in females) as a marker of type 2 diabetes (T2D) and cardiovascular disease. However, the prevalence of this phenotype in high-risk populations, its association with T2D, and the genetic or epigenetic influences on HTGW are not well explored. Using data from large, extended families of Mexican Americans (a high-risk minority population in the USA) we aimed to: (1) estimate the prevalence of this phenotype, (2) test its association with T2D and related traits, and (3) dissect out the genetic and epigenetic associations with this phenotype using genome-wide and epigenome-wide studies, respectively. Results Data for this study was from 850 Mexican American participants (representing 39 families) recruited under the ongoing San Antonio Family Heart Study, 26 % of these individuals had HTGW. This phenotype was significantly heritable (h2r = 0.52, p = 1.1 × 10−5) and independently associated with T2D as well as fasting glucose levels and insulin resistance. We conducted genome-wide association analyses using 759,809 single nucleotide polymorphisms (SNPs) and epigenome-wide association analyses using 457,331 CpG sites. There was no evidence of any SNP associated with HTGW at the genome-wide level but two CpG sites (cg00574958 and cg17058475) in CPT1A and one CpG site (cg06500161) in ABCG1 were significantly associated with HTGW and remained significant after adjusting for the closely related components of metabolic syndrome. CPT1A holds a cardinal position in the metabolism of long-chain fatty acids while ABCG1 plays a role in triglyceride metabolism. Conclusions Our results reemphasize the value of HTGW as a marker of T2D. This phenotype shows association with DNA methylation within CPT1A and ABCG1, genes involved in fatty acid and triglyceride metabolism. Our results underscore the importance of epigenetics in a clinically informative phenotype. Electronic supplementary material The online version of this article (doi:10.1186/s13148-016-0173-x) contains supplementary material, which is available to authorized users.

Microarray technology has generated enormous amounts of high-dimensional gene expression data, providing a unique platform for exploring gene regulatory networks. However, the curse of dimensionality plagues effort to analyze these high throughput data. Linear Discriminant Analysis (LDA) and Biased Discriminant Analysis (BDA) are two popular techniques for dimension reduction, which pay attention to different roles of the positive and negative samples in finding discriminating subspace. However, the drawbacks of these two methods are obvious: LDA has limited efficiency in classifying sample data from subclasses with different distributions, and BDA does not account for the underlying distribution of negative samples. In this paper, we propose a novel dimension reduction technique for microarray analysis: Adaptive Discriminant Analysis (ADA), which effectively exploits favorable attributes of both BDA and LDA and avoids their unfavorable ones. ADA can find a good discriminative subspace with adaptation to different sample distributions. It not only alleviates the problem of high dimensionality, but also enhances the classification performance in the subspace with naïve Bayes classifier. To learn the best model fitting the real scenario, boosted Adaptive Discriminant Analysis is further proposed. Extensive experiments on the yeast cell cycle regulation data set, and the expression data of the red blood cell cycle in malaria parasite Plasmodium falciparum demonstrate the superior performance of ADA and boosted ADA. We also present some putative genes of specific functional classes predicted by boosted ADA. Their potential functionality is confirmed by independent predictions based on Gene Ontology, demonstrating that ADA and boosted ADA are effective dimension reduction methods for microarray-based classification.

The steadily increasing number of prokaryotic genomes has accelerated the study of genome evolution; in particular, the availability of sets of genomes from closely related bacteria has made exploration of questions surrounding the evolution of pathogenesis tractable. Here we present the results of a detailed comparison of the genomes of Yersinia pseudotuberculosis IP32593 and three strains of Yersinia pestis (CO92, KIM10, and 91001). There appear to be between 241 and 275 multigene families in these organisms. There are 2,568 genes that are identical in the three Y. pestis strains, but differ from the Y. pseudotuberculosis strain. The changes found in some of these families, such as the kinases, proteases, and transporters, are illustrative of how the evolutionary jump from the free-living enteropathogen Y. pseudotuberculosis to the obligate host-borne blood pathogen Y. pestis was achieved. We discuss the composition of some of the most important families and discuss the observed divergence between Y. pseudotuberculosis and Y. pestis homologs. J. Exp. Zool. (Mol. Dev. Evol.) 306B, 2006. © 2006 Wiley-Liss, Inc.

We report on the use of a portable instrument for microbial detection in the Mojave Desert soil and the potential for its use on Mars. The instrument is based on native fluorescence and employs four excitation wavelengths combined with four emission wavelengths. A soil dilution series in which known numbers of Bacillus subtilis spores were added to soil was used to determine the sensitivity of the instrument. We found that the fluorescence of the biological and organic components of the desert soil samples studied can be as strong as the fluorescence of the mineral component of these soils. Using the calibration derived from B. subtilis spores, we estimated that microbial content at our primary sampling site was 10(7) bacteria per gram of soil, a level confirmed by phospholipid fatty acid analysis. At a nearby site, but in a slightly different geological setting, we tested the instrument's ability to map out microbial concentrations in situ. Over a ∼50 m diameter circle, soil microbial concentrations determined with the B. subtilis calibration indicate that the concentrations of microorganisms detected varies from 10(4) to 10(7) cells per gram of soil. We conclude that fluorescence is a promising method for detecting soil microbes in noncontact applications in extreme environments on Earth and may have applications on future missions to Mars.

Background The steadily increasing number of prokaryotic genomes has accelerated the study of genome evolution; in particular, the availability of sets of genomes from closely related bacteria has facilitated the exploration of the mechanisms underlying genome plasticity. The family Vibrionaceae is found in the Gammaproteobacteria and is abundant in aquatic environments. Taxa from the family Vibrionaceae are diversified in their life styles; some species are free living, others are symbiotic, and others are human pathogens. This diversity makes this family a useful set of model organisms for studying bacterial evolution. This evolution is driven by several forces, among them gene duplication and lateral gene transfer, which are believed to provide raw material for functional redundancy and novelty. The resultant gene copy increase in one genome is then detected as lineage-specific expansion (LSE). Results Here we present the results of a detailed comparison of the genomes of eleven Vibrionaceae strains that have distinct life styles and distinct phenotypes. The core genome shared by all eleven strains is composed of 1,882 genes, which make up about 31%–50% of the genome repertoire. We further investigated the distribution and features of genes that have been specifically expanded in one unique lineage of the eleven strains. Abundant duplicate genes have been identified in the eleven Vibrionaceae strains, with 1–11% of the whole genomes composed lineage specific radiations. These LSEs occurred in two distinct patterns: the first type yields one or more copies of a single gene; we call this a single gene expansion. The second pattern has a high evolutionary impact, as the expansion involves two or more gene copies in a block, with the duplicated block located next to the original block (a contiguous block expansion) or at some distance from the original block (a discontiguous block expansion). We showed that LSEs involve genes that are tied to defense and pathogenesis mechanisms as well as in the fundamental life cycle of Vibrionaceae species. Conclusion Our results provide evidence of genome plasticity and rapid evolution within the family Vibrionaceae. The comparisons point to sources of genomic variation and candidates for lineage-specific adaptations of each Vibrionaceae pathogen or nonpathogen strain. Such lineage specific expansions could reveal components in bacterial systems that, by their enhanced genetic variability, can be tied to responses to environmental challenges, interesting phenotypes, or adaptive pathogenic responses to host challenges.

This study compares the predicted metabolic capabilities of seven sequenced bacterial strains within the family Vibrionaceae, with emphasis on the possible biosynthetic pathways encoded by their genomes. The goal is to elucidate whether the high diversity among Vibrionaceae in terms of environment and pathogenicity is reflected in their suite of available metabolic processes. The data set included the genomes of two Vibrio cholerae, two Vibrio vulnificus, two Aliivibrio fischeri, and one Vibrio parahaemolyticus species. Possible metabolic pathways available to these strains were deduced using the Pathway Tools software, and the results (for biosynthetic pathways) were hand-corrected using the NCBI database, MetaCyc, KEGG, and BlastP.

We examined the metabolic capabilities of eight Escherichia coli strains in order to identify variations among these strains which might account for their alternate mechanisms of infection or levels of virulence. Our data set included two non-pathogenic strains, two diarrheagenic strains and four extra-intestinal pathogenic strains. The metabolic pathway complements of these strains were deduced using the Pathway Tools software. The results were hand-corrected using the NCBI database, EcoCyc, and tBLASTn. After curation, only 20 differences were discerned among the strains, but a few of these differences are intriguing. Two of the pathways are involved in the biosynthesis of lipopolysaccharides, which are known virulence determinants. Further research is needed to test the implications of our findings, but this study has identified possible metabolic variations that may prove significant for understanding the pathogenicity of different E. coli strains.

Pathway-genome databases were constructed for three Yersinia pestis strains and a single Yersinia pseudotuberculosis strain in order to compare their predicted metabolic pathways. Y. pestis, the causative agent of bubonic plague, is 100% host-associated while Y. pseudotuberculosis is a free-living aquatic organism which is believed to be ancestral to Y. pestis. A total of 326 pathways were identified between the four Yersinia strains, with each strain containing 269-294 pathways. Intra-speciflc and inter-specific differences in predicted metabolic capabilities are reported here, and efforts to curate the databases continue.

Microarray technology offers a high-throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small sample size in microarray data calls for effective computational methods. In this article, we propose a novel hybrid dimension reduction technique for classification that combines principal component analysis (PCA) and linear discriminant analysis (LDA)-hybrid PCA and LDA analysis. This technique effectively solves the singular scatter matrix problem caused by small training samples and increases the effective dimension of the projected subspace. It offers more flexibility and a richer set of alternatives to LDA and PCA in the parametric space. In addition, we propose a boosted hybrid discriminant analysis (HDA), using the AdaBoost algorithm which provides a unified and stable solution to find close to the optimal PCA-LDA prediction result and also reduces computational complexity. Extensive experiments on the yeast cell cycle regulation data set show the superior performance of the hybrid analysis, as we explain.