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Introduction: The COVID-19 pandemic represented one of the most significant challenges to researchers and healthcare providers. Several factors determine the disease severity, whereas none alone can explain the tremendous variability. The Single nucleotide variants (SNVs) in angiotensin-converting enzyme-2 (ACE2) and transmembrane serine protease type-2 (TMPRSS2) genes affect the virus entry and are considered possible risk factors for COVID-19. Methods: We compiled a panel of gene variants from both genes and used insilico analysis to predict their significance. We performed biological validation to assess their capacity to alter the ACE2 interaction with the virus spike protein. Subsequently, we conducted a retrospective comparative genome analysis on those variants in the Emirati patients with different disease severity (total of 96) along with 69 healthy control subjects. Results: Our results showed that the Emirati population lacks the variants that were previously reported as associated with disease severity, whereas a new variant in ACE2 "Chr X:g.15584534" was associated with disease severity specifically among female patients. In-silico analysis revealed that the new variant can determine the ACE2 gene transcription. Several cytokines (GM-CSF and IL-6) and chemokines (MCP-1/CCL2, IL-8/CXCL8, and IP-10/CXCL10) were markedly increased in COVID-19 patients with a significant correlation with disease severity. The newly reported genetic variant of ACE2 showed a positive correlation with CD40L, IL-1β, IL-2, IL-15, and IL-17A in COVID-19 patients. Conclusion: Whereas COVID-19 represents now a past pandemic, our study underscores the importance of genetic factors specific to a population, which can influence both the susceptibility to viral infections and the level of severity; subsequently expected required preparedness in different areas of the world. [ABSTRACT FROM AUTHOR]

Introduction: Frailty is the most common medical condition affecting the aging population, and its prevalence increases in the population aged 65 or more. Frailty is commonly diagnosed using the frailty index (FI) or frailty phenotype (FP) assessments. Observational studies have indicated the association of frailty with Alzheimer's disease (AD). However, the shared genetic and biological mechanism of these comorbidity has not been studied. Methods: To assess the genetic relationship between AD and frailty, we examined it at single nucleotide polymorphism (SNP), gene, and pathway levels. Results: Overall, 16 genome-wide significant loci (15 unique loci) (pmeta-analysis < 5 × 10-8) and 22 genes (21 unique genes) were identified between AD and frailty using cross-trait meta-analysis. The 8 shared loci implicated 11 genes: CLRN1-AS1, CRHR1, FERMT2, GRK4, LINC01929, LRFN2, MADD, RP11-368P15.1, RP11-166N6.2, RNA5SP459, and ZNF652 between AD and FI, and 8 shared loci between AD and FFS implicated 11 genes: AFF3, C1QTNF4, CLEC16A, FAM180B, FBXL19, GRK4, LINC01104, MAD1L1, RGS12, ZDHHC5, and ZNF521. The loci 4p16.3 (GRK4) was identified in both meta-analyses. The colocalization analysis supported the results of our meta-analysis in these loci. The gene-based analysis revealed 80 genes between AD and frailty, and 4 genes were initially identified in our meta-analyses: C1QTNF4, CRHR1, MAD1L1, and RGS12. The pathway analysis showed enrichment for lipoprotein particle plasma, amyloid fibril formation, protein kinase regulator, and tau protein binding. Conclusion: Overall, our results provide new insights into the genetics of AD and frailty, suggesting the existence of non-causal shared genetic mechanisms between these conditions. [ABSTRACT FROM AUTHOR]

IntroductionThe COVID-19 pandemic represented one of the most significant challenges to researchers and healthcare providers. Several factors determine the disease severity, whereas none alone can explain the tremendous variability. The Single nucleotide variants (SNVs) in angiotensin-converting enzyme-2 (ACE2) and transmembrane serine protease type-2 (TMPRSS2) genes affect the virus entry and are considered possible risk factors for COVID-19.MethodsWe compiled a panel of gene variants from both genes and used in-silico analysis to predict their significance. We performed biological validation to assess their capacity to alter the ACE2 interaction with the virus spike protein. Subsequently, we conducted a retrospective comparative genome analysis on those variants in the Emirati patients with different disease severity (total of 96) along with 69 healthy control subjects.ResultsOur results showed that the Emirati population lacks the variants that were previously reported as associated with disease severity, whereas a new variant in ACE2 “Chr X:g.15584534” was associated with disease severity specifically among female patients. In-silico analysis revealed that the new variant can determine the ACE2 gene transcription. Several cytokines (GM-CSF and IL-6) and chemokines (MCP-1/CCL2, IL-8/CXCL8, and IP-10/CXCL10) were markedly increased in COVID-19 patients with a significant correlation with disease severity. The newly reported genetic variant of ACE2 showed a positive correlation with CD40L, IL-1β, IL-2, IL-15, and IL-17A in COVID-19 patients.ConclusionWhereas COVID-19 represents now a past pandemic, our study underscores the importance of genetic factors specific to a population, which can influence both the susceptibility to viral infections and the level of severity; subsequently expected required preparedness in different areas of the world.

Introduction: The knowledge of the aetiology of Behçet disease (BD), an immune-mediated vasculitis, is limited. HLA-B, mainly HLA-B51, and HLA-A molecules are associated with disease, but the ultimate cause of this association remains obscure. There is evidence that NK cells participate in the etiopathology of BD. NK cells have activator and inhibitor surface receptors, like the KIR and the NKG2 families. Classical HLA-class I molecules (A, B and C) are keys in the activity control of the NK because they are KIR ligands. Most NKG2 receptors bind HLA-E, which presents only nonapeptides derived from the signal peptide of other class-I molecules. Objective: This study investigates the contribution of the pair HLA-E and ligand, nonapeptide derived from the 3-11 sequence of the signal peptides of class I classical molecules, to the susceptibility to BD. Methods: We analyzed the frequency of the HLA-derivated nonapeptide forms in 466 BD patients and 444 controls and an HLA-E functional dimorphism in a subgroup of patients and controls. Results: In B51 negative patients, the frequency of VMAPRTLLL was lower (70.4% versus 80.0% in controls; P=0.006, Pc=0.04, OR=0.60, 95%CI 0.41-0.86), and the frequency of VMAPRTLVL was higher (81.6% versus 71.4% in controls; P=0.004, Pc=0.03, OR=1.78, 95%CI 1.20-2.63). In homozygosity, VMAPRTLLL is protective, and VMAPRTLVL confers risk. The heterozygous condition is neutral. There were no significant differences in the distribution of the HLA-E dimorphism. Discussion: Our results explain the association of BD with diverse HLA-A molecules, reinforce the hypothesis of the involvement of the NK cells in the disease and do not suggest a significant contribution of the HLA-E polymorphism to disease susceptibility. [ABSTRACT FROM AUTHOR]

IntroductionThe knowledge of the aetiology of Behçet disease (BD), an immune-mediated vasculitis, is limited. HLA-B, mainly HLA-B51, and HLA-A molecules are associated with disease, but the ultimate cause of this association remains obscure. There is evidence that NK cells participate in the etiopathology of BD. NK cells have activator and inhibitor surface receptors, like the KIR and the NKG2 families. Classical HLA-class I molecules (A, B and C) are keys in the activity control of the NK because they are KIR ligands. Most NKG2 receptors bind HLA-E, which presents only nonapeptides derived from the signal peptide of other class-I molecules.ObjectiveThis study investigates the contribution of the pair HLA-E and ligand, nonapeptide derived from the 3-11 sequence of the signal peptides of class I classical molecules, to the susceptibility to BD.MethodsWe analyzed the frequency of the HLA-derivated nonapeptide forms in 466 BD patients and 444 controls and an HLA-E functional dimorphism in a subgroup of patients and controls. Results: In B51 negative patients, the frequency of VMAPRTLLL was lower (70.4% versus 80.0% in controls; P=0.006, Pc=0.04, OR=0.60, 95%CI 0.41-0.86), and the frequency of VMAPRTLVL was higher (81.6% versus 71.4% in controls; P=0.004, Pc=0.03, OR=1.78, 95%CI 1.20-2.63). In homozygosity, VMAPRTLLL is protective, and VMAPRTLVL confers risk. The heterozygous condition is neutral. There were no significant differences in the distribution of the HLA-E dimorphism.DiscussionOur results explain the association of BD with diverse HLA-A molecules, reinforce the hypothesis of the involvement of the NK cells in the disease and do not suggest a significant contribution of the HLA-E polymorphism to disease susceptibility.

Coevolution at the gene level, as reflected by correlated events of gene loss or gain, can be revealed by phylogenetic profile analysis. The optimal method and metric for comparing phylogenetic profiles, especially in eukaryotic genomes, are not yet established. Here, we describe a procedure suitable for large-scale analysis, which can reveal coevolution based on the assessment of the statistical significance of correlated presence/absence transitions between gene pairs. This metric can identify coevolution in profiles with low overall similarities and is not affected by similarities lacking coevolutionary information. We applied the procedure to a large collection of 60,912 orthologous gene groups (orthogroups) in 1,264 eukaryotic genomes extracted from OrthoDB. We found significant cotransition scores for 7,825 orthogroups associated in 2,401 coevolving modules linking known and unknown genes in protein complexes and biological pathways. To demonstrate the ability of the method to predict hidden gene associations, we validated through experiments the involvement of vertebrate malate synthase-like genes in the conversion of (S)-ureidoglycolate into glyoxylate and urea, the last step of purine catabolism. This identification explains the presence of glyoxylate cycle genes in metazoa and suggests an anaplerotic role of purine degradation in early eukaryotes. [ABSTRACT FROM AUTHOR]

Claudin-14 protein plays an essential role in regulating calcium ions in the kidney and ear. Two phenotypes, hearing loss and kidney stones, were reportedly associated with variations in the CLDN14 gene. This study aimed to understand CLDN14 mutations’ contribution to hearing loss and renal stone formation in a Pakistani cohort. We analyzed CLDN14 sequence variations in 100 patients, along with healthy individuals, to assess whether specific polymorphisms were associated with the disease. Also, we performed an in silico analysis using a mutation database and protein annotation. The rs219779’s genotype CT (p = 0.0020) and rs219780’s genotype AG (p = 0.0012) were significantly associated with kidney stones. We also found that a novel haplotype, “TA” associated with kidney stone formation, has moderate linkage disequilibrium. The TA haplotype was significantly correlated with a kidney stone risk formation of 3.76-fold (OR (CI 95%) = 3.76 (1.83–7.72)) and p = 0.0016 compared to other haplotypes. In silico analysis revealed that mutations associated with hearing loss were not correlated with renal stone formation but affected claudin-14 protein stability. We structurally mapped a novel TA haplotype of CLDN14 that, based on our analysis, likely contributes to the pathogenesis of renal stones.

Objective: To investigate causal associations between blood-based inflammatory markers and female infertility using Mendelian randomization (MR)., Design: Mendelian randomization using genome-wide association study data., Setting: Publicly available genome-wide association study data., Patient(s): Large female-only cohorts of European ancestry., Intervention(s): Blood-based inflammatory markers (C-reactive protein, interleukins, monocyte chemoattractant protein-1, tumor necrosis factor-α, interferon-γ)., Main Outcomes Measure(s): Anovulatory infertility (1,054 cases and 117,098 controls); female infertility of other/unspecified origin (5,667 cases and 117,098 controls); and medical treatment for female infertility (2,706 cases and 120,873 controls). Total causal effects were assessed using univariable two-sample methods including inverse variance weighted (IVW) as the primary analysis, as well as other secondary analyses (MR-Egger, weighted median, etc.), with relevant quality assessments., Result(s): Interleukin-8 demonstrated a positive association with anovulatory infertility via IVW (odds ratio, 95% confidence interval; 1.51, 1.04-2.21) and weighted median (1.64, 1.05-2.57) methods. Monocyte chemoattractant protein-1 was associated with anovulatory infertility via MR-Egger (2.06, 1.13-3.77). Inverse associations were found for interleukins-12 and -18 via IVW, with higher interleukin-12 being associated with lower medical treatment for female infertility (0.75, 0.59-0.94), whereas higher interleukin-18 was associated with lower female infertility of other/unspecified origin (0.90, 0.83-0.97)., Conclusion(s): This is the first study to examine causal relationships between inflammation and female infertility using MR. Monocyte chemoattractant protein-1 and interleukin-8 are implicated in anovulatory infertility; however, only the relationship with interleukin-8 was evident in the primary analysis. Interleukins-12 and -18 demonstrated inverse associations with infertility outcomes. Further research is needed to uncover the mechanistic functions of these markers to confirm causality and examine their therapeutic potential for female infertility., Competing Interests: Declaration of Interests S.A. has nothing to disclose. H.T. reports funding from National Health and Medical Research Council Australia (2009326 and 1171592); and President Elect International Society Endocrinology, outside the submitted work. J.E. has nothing to disclose. K.D.S. has nothing to disclose. A.M. reports funding from National Health and Medical Research Council of Australia (fellowship for salary funding) for the submitted work., (Copyright © 2024 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.)

El Niño events, the warm phase of the El Niño Southern Oscillation, facilitate the movement of warm surface waters eastwards across the Pacific Ocean. Marine organisms transported by these waters can act as biological corridors for water-borne bacteria with attachment abilities. El Niño events have been hypothesized as driving the recent emergence of Vibrio parahaemolyticus (Vp) variants, marine bacterium causing gastroenteritis, in South America, but the lack of a robust methodological framework limited any further exploration. Here, we introduce two new analysis approaches to explore Vp dynamics in South America, which will be central to uncovering Vp dynamics in the future. Distributed non-linear lag models found that strong El Niño events increase the relative probability of Vp detection in Peru, with a 3-4-month lag time. Machine learning found that the presence of a specific gene ( vopZ ) involved in attachment to plankton in a pandemic Vp clone in South America was temporally associated with strong El Niño events, offering a possible strategy for survival over long-range dispersal, such as that offered by El Niño events. Robust surveillance of marine pathogens and methodological development are necessary to produce resolute conclusions on the effect of El Niño events on water-borne diseases.

Translesion synthesis (TLS) is a cell signaling pathway that facilitates the tolerance of replication stress. Increased TLS activity, the particularly elevated expression of TLS polymerases, has been linked to resistance to cancer chemotherapeutics and significantly altered patient outcomes. Building upon current knowledge, we found that the expression of one of these TLS polymerases (POLI) is associated with significant differences in cervical and pancreatic cancer survival. These data led us to hypothesize that POLI expression is associated with cancer survival more broadly. However, when cancers were grouped cancer type, POLI expression did not have a significant prognostic value. We presented a binary cancer random forest classifier using 396 genes that influence the prognostic characteristics of POLI in cervical and pancreatic cancer selected via graphical least absolute shrinkage and selection operator. The classifier was then used to cluster patients with bladder, breast, colorectal, head and neck, liver, lung, ovary, melanoma, stomach, and uterus cancer when high POLI expression was associated with worsened survival (Group I) or with improved survival (Group II). This approach allowed us to identify cancers where POLI expression is a significant prognostic factor for survival (p = 0.028 in Group I and p = 0.0059 in Group II). Multiple independent validation approaches, including the gene ontology enrichment analysis and visualization tool and network visualization support the classification scheme. The functions of the selected genes involving mitochondrial translational elongation, Wnt signaling pathway, and tumor necrosis factor-mediated signaling pathway support their association with TLS and replication stress. Our multidisciplinary approach provides a novel way of identifying tumors where increased TLS polymerase expression is associated with significant differences in cancer survival. [ABSTRACT FROM AUTHOR]

The recent development of a high throughput single-cell RNA sequence devises the opportunity to study entire transcriptomes in the smallest detail. It also leads to the characterization of molecules and subtypes of a cell. Cancer epigenetics induced not only from individual molecules but also from the dysfunction of the system and the coupling effect of genes. While rapid advances are being made in the development of tools for single-cell RNA-seq data analysis, few slants are noticed in the potential advantages of single-cell network construction. Here, we used network perturbation theory with significant analysis to develop a cell-specific network that provides an insight into gene–gene association based on molecular expressions in a single-cell resolution. Besides, using this method, we can characterize each cell by inspecting how genes are connected and can identify the hub genes using network degree theory. Pathway & Gene enrichment analysis of the identified cell-specific high network degree genes supported the effectiveness of this method. This method could be beneficial for personalized drug design and even therapeutics. [ABSTRACT FROM AUTHOR]

Several studies have previously assessed the association between interleukin (IL)-10 gene polymorphisms and the risk of asthma, leading to conflicting results. To resolve the incongruent outcomes yielded from different single studies, we conducted the most up-to-date meta-analysis of the IL-10 gene rs1800896, rs1800871, and rs1800872 single-nucleotide polymorphisms (SNPs) and susceptibility to asthma. A systematic literature search performed until April 2020, and the pooled odds ratio (OR) and their corresponding 95% confidence interval (CI) were calculated to determine the association strength. Thirty articles comprising 5678 asthmatic patients and 6079 controls met the inclusion criteria. No significant association was found between rs1800872 SNP and susceptibility to asthma across all genetic models in the overall and subgroup analyses. The rs1800871 SNP had only significant association with a decreased risk of asthma in Europeans (OR 0.66, CI 0.53–0.82, P < 0.001). However, rs1800896 SNP was significantly associated with a decreased risk of asthma by dominant (OR 0.67, CI 0.50–0.90, P < 0.001) and heterozygote (OR 0.66, CI 0.49–0.88, P < 0.001) models in the overall analysis. Subgroup analyses indicated significant association of rs1800896 SNP by dominant (OR 0.45, CI 0.28–0.72, P < 0.001) and heterozygote (OR 0.43, CI 0.26–0.70, P < 0.001) models in the African population. The IL-10 rs1800896 SNP confers protection against the risk of asthma, especially in Africans. Additionally, rs1800871 SNP has a protective role against asthma in Europeans. [ABSTRACT FROM AUTHOR]

Abstract Background C4 photosynthesis is a key domain of plant research with outcomes ranging from crop quality improvement, biofuel production and efficient use of water and nutrients. A metabolic network model of C4 “lab organism” Setaria viridis with extensive gene-reaction associations can accelerate target identification for desired metabolic manipulations and thereafter in vivo validation. Moreover, metabolic reconstructions have also been shown to be a significant tool to investigate fundamental metabolic traits. Results A mass and charge balance genome-scale metabolic model of Setaria viridis was constructed, which was tested to be able to produce all major biomass components in phototrophic and heterotrophic conditions. Our model predicted an important role of the utilization of NH 4+ $_{4}^{+}$ and NO 3− $_{3}^{-}$ ratio in balancing charges in plants. A multi-tissue extension of the model representing C4 photosynthesis was able to utilize NADP-ME subtype of C4 carbon fixation for the production of lignocellulosic biomass in stem, providing a tool for identifying gene associations for cellulose, hemi-cellulose and lignin biosynthesis that could be potential target for improved lignocellulosic biomass production. Besides metabolic engineering, our modeling results uncovered a previously unrecognized role of the 3-PGA/triosephosphate shuttle in proton balancing. Conclusions A mass and charge balance model of Setaria viridis, a model C4 plant, provides the possibility of system-level investigation to identify metabolic characteristics based on stoichiometric constraints. This study demonstrated the use of metabolic modeling in identifying genes associated with the synthesis of particular biomass components, and elucidating new role of previously known metabolic processes.

Several studies have evaluated the association between killer-cell immunoglobulin-like receptors (KIR) genes and susceptibility risk to tuberculosis (TB) infection. Nonetheless, their outcomes have not been conclusive and consistent. Here we implemented a systematic review and meta-analysis of KIR genes association to susceptibility risk of pulmonary TB (PTB) infection to attain a clear understanding of the involvement of these genes in susceptibility to PTB infection. A systematic search was conducted in the MEDLINE/PubMed and Scopus databases to find case-control studies published before November 2020. Pooled odds ratio (OR) and 95% confidence interval (95% CI) were calculated to determine the association between KIR genes and risk of PTB infection. After comprehensive searching and implementing the inclusion and exclusion criteria, 10 case-control studies were included in the meta-analysis. Four KIR genes were found to have significant positive association with PTB susceptibility risk of infection, including 2DL3 (OR = 1.454, 95% CI = 1.157–1.827; P = 0.001), 2DS1 (OR = 1.481, 95% CI = 1.334–1.837; P < 0.001), 2DS4 (OR = 1.782, 95% CI = 1.273–2.495; P = 0.001) and 3DL1 (OR = 1.726, 95% CI = 1.277–2.333; P < 0.001). However, the results showed that the remaining KIR genes (2DS2-4, 2DL1, 2, 4, 3DL1-2) and two pseudogenes (2DP1 and 3DP1) did not have significant associations with risk of PTB infection. This meta-analysis provides reliable evidence that the KIR genes 2DL3, 2DS1, 2DS4, and 3DL1 may be associated with an increased risk of PTB infection. [ABSTRACT FROM AUTHOR]

Abstract Background Gene Ontology (GO) is a useful resource of controlled vocabulary that provides information about annotated genes. Based on such resource, finding the biological function is useful for biologists to come up with different hypotheses and help further investigations of an experiment. The biological function for desired genes and gene associations is picked up from a randomly chosen list or through the analysis of differential gene expression. Many tools have been developed to utilize GO knowledge and cluster genes according to relevant biological functions. The retrieved GO terms include both specific and non-specific terms, which is not user-friendly in terms of data analysis. Thus one approach is still missing, which allows navigating through different levels of GO hierarchy manually. Result We developed a tool, GOTrapper, which allows moving up or down to the very bottom of the GO hierarchy. This is performed manually by the user, based on an assigned threshold. This tool grabs the shared terms by the desired set of input genes of Homo sapiens. Here, two inputs are possible. “Within” is to find associated terms within one gene list, and “Between” is to find associated terms between two lists. The tool also provides the option to return the terms with the pre-selected evidence codes. Conclusion GOTrapper is a user-friendly Java tool that helps the user move up and down the ontology tree, which leads to new hypotheses and devising new association of the input genes. It also allows returning terms of associated genes based on selected evidence codes. This tool can be accessed and is freely available at https://github.com/BioGeneTools/GOTrapper.

To facilitate smoking genetics research we determined whether a screen of mutagenized zebrafish for nicotine preference could predict loci affecting smoking behaviour. From 30 screened F3 sibling groups, where each was derived from an individual ethyl-nitrosurea mutagenized F0 fish, two showed increased or decreased nicotine preference. Out of 25 inactivating mutations carried by the F3 fish, one in the slit3 gene segregated with increased nicotine preference in heterozygous individuals. Focussed SNP analysis of the human SLIT3 locus in cohorts from UK (n=863) and Finland (n=1715) identified two variants associated with cigarette consumption and likelihood of cessation. Characterisation of slit3 mutant larvae and adult fish revealed decreased sensitivity to the dopaminergic and serotonergic antagonist amisulpride, known to affect startle reflex that is correlated with addiction in humans, and increased htr1aa mRNA expression in mutant larvae. No effect on neuronal pathfinding was detected. These findings reveal a role for SLIT3 in development of pathways affecting responses to nicotine in zebrafish and smoking in humans.

Short interspersed nuclear elements (SINEs) are non-autonomous retrotransposons that are highly abundant, but not well annotated, in plant genomes. In this study, we identified 41,573 copies of SINEs in seven citrus genomes, including 11,275 full-length copies. The citrus SINEs were distributed among 12 families, with an average full-length rate of 0.27, and were dispersed throughout the chromosomes, preferentially in AT-rich areas. Approximately 18.4% of citrus SINEs were found in close proximity (≤1 kb upstream) to genes, indicating a significant enrichment of SINEs in promoter regions. Citrus SINEs promote gene and genome evolution by offering exons as well as splice sites and start and stop codons, creating novel genes and forming tandem and dispersed repeat structures. Comparative analysis of unique homologous SINE-containing loci (HSCLs) revealed chromosome rearrangements in sweet orange, pummelo, and mandarin, suggesting that unique HSCLs might be valuable for understanding chromosomal abnormalities. This study of SINEs provides us with new perspectives and new avenues by which to understand the evolution of citrus genes and genomes. [ABSTRACT FROM AUTHOR]

Background: C4 photosynthesis is a key domain of plant research with outcomes ranging from crop quality improvement, biofuel production and efficient use of water and nutrients. A metabolic network model of C4 "lab organism" Setaria viridis with extensive gene-reaction associations can accelerate target identification for desired metabolic manipulations and thereafter in vivo validation. Moreover, metabolic reconstructions have also been shown to be a significant tool to investigate fundamental metabolic traits. Results: A mass and charge balance genome-scale metabolic model of Setaria viridis was constructed, which was tested to be able to produce all major biomass components in phototrophic and heterotrophic conditions. Our model predicted an important role of the utilization of NH 4 + and NO 3 − ratio in balancing charges in plants. A multi-tissue extension of the model representing C4 photosynthesis was able to utilize NADP-ME subtype of C4 carbon fixation for the production of lignocellulosic biomass in stem, providing a tool for identifying gene associations for cellulose, hemi-cellulose and lignin biosynthesis that could be potential target for improved lignocellulosic biomass production. Besides metabolic engineering, our modeling results uncovered a previously unrecognized role of the 3-PGA/triosephosphate shuttle in proton balancing. Conclusions: A mass and charge balance model of Setaria viridis, a model C4 plant, provides the possibility of system-level investigation to identify metabolic characteristics based on stoichiometric constraints. This study demonstrated the use of metabolic modeling in identifying genes associated with the synthesis of particular biomass components, and elucidating new role of previously known metabolic processes. [ABSTRACT FROM AUTHOR]

This article introduces a novel method for selecting main effects and a set of reparameterized effects called conditional main effects (CMEs), which capture the conditional effect of a factor at a fixed level of another factor. CMEs represent interpretable, domain-specific phenomena for a wide range of applications in engineering, social sciences, and genomics. The key challenge is in incorporating the implicit grouped structure of CMEs within the variable selection procedure itself. We propose a new method, cmenet, which employs two principles called CME coupling and CME reduction to effectively navigate the selection algorithm. Simulation studies demonstrate the improved CME selection performance of cmenet over more generic selection methods. Applied to a gene association study on fly wing shape, cmenet not only yields more parsimonious models and improved predictive performance over standard two-factor interaction analysis methods, but also reveals important insights on gene activation behavior, which can be used to guide further experiments. Efficient implementations of our algorithms are available in the R package cmenet in CRAN. Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

Background: Gene Ontology (GO) is a useful resource of controlled vocabulary that provides information about annotated genes. Based on such resource, finding the biological function is useful for biologists to come up with different hypotheses and help further investigations of an experiment. The biological function for desired genes and gene associations is picked up from a randomly chosen list or through the analysis of differential gene expression. Many tools have been developed to utilize GO knowledge and cluster genes according to relevant biological functions. The retrieved GO terms include both specific and non-specific terms, which is not user-friendly in terms of data analysis. Thus one approach is still missing, which allows navigating through different levels of GO hierarchy manually. Result: We developed a tool, GOTrapper, which allows moving up or down to the very bottom of the GO hierarchy. This is performed manually by the user, based on an assigned threshold. This tool grabs the shared terms by the desired set of input genes of Homo sapiens. Here, two inputs are possible. "Within" is to find associated terms within one gene list, and "Between" is to find associated terms between two lists. The tool also provides the option to return the terms with the pre-selected evidence codes. Conclusion: GOTrapper is a user-friendly Java tool that helps the user move up and down the ontology tree, which leads to new hypotheses and devising new association of the input genes. It also allows returning terms of associated genes based on selected evidence codes. This tool can be accessed and is freely available at https://github.com/BioGeneTools/GOTrapper. [ABSTRACT FROM AUTHOR]

Summary: The aim of this research was to evaluate the polymorphisms of selected genes and to find their potential effect on the occurrence of osteochondrosis in Polish Warmbloods (sport horse breeds). The study was conducted on a group of 198 horses subjected to official performance tests. Investigated joints—fetlock, hock and stifle—were X‐rayed twice, once before and again at the end of the tests (first and second examination), and on this basis the degree of disease was evaluated. Based on the results of previous research, 13 candidate genes potentially associated with the occurrence of osteochondrosis were selected and, among them, 32 polymorphisms were tested. Seven SNPs located in the MATN1,CPVL,HYAL1,XIRP2,FRZB,COL5A2 and IGF1 genes were found to be associated with occurrence of osteochondrotic lesions in different joints. These intragenic polymorphisms seem to provide valuable information about the genetic basis of osteochondrosis in sport horse breeds. [ABSTRACT FROM AUTHOR]

Background: The development, evolution and rupture of intracranial aneurysms are in part related to genetic factors. The role of collagen type-I a2 genetic polymorphisms has not been clarified yet. Material and methods: A meta-analysis was realized by means of a genotype model-fitting process (allele contrast, recessive, dominant, additive and co-dominant), and a model-free approach using the generalized odds ratio. The latter was assessed in association to the degree of dominance (h-index). Results: No statistically significant association was documented between EX28 G>C collagen type-I a2 variant and intracranial aneurysms (generalized odds ratio = 1.23, 95% confidence interval = 0.57, 2.63). Significant associations between INT46 T>G collagen type I a2 variant and intracranial aneurysms were documented in three models, the dominant [0.52 (0.38, 069)], the co-dominant [0.50 (0.32, 0.78)] and the allele contrast models [0.63 (0.49, 0.82)]. The generalized odds ratio was estimated to be as high as 1.94 (1.23, 3.06). The degree of dominance (h-index = −1.54) indicated that the TG genotype was characterized by lower risk of developing intracranial aneurysms compared to the TT genotype. Conclusions: The available literature data demonstrated that there is no association of collagen type-(2a) and intracranial aneurysms, through EX28 G>C (rs42524) polymorphism according to the model-fitting process and the model-free approach. Regarding the INT46 T>G (rs2621215) polymorphisms, the latter models indicated that there could be a protective effect of the G-allele against the development of intracranial aneurysms. However, the majority of studies are from East Asia, therefore the results are applicable primarily to that patient population. [ABSTRACT FROM AUTHOR]

Aquagenic keratoderma has been described as a transient condition affecting predominantly young females and defined clinically by the appearance of palmar hyper-wrinkling accentuated after immersion in water. We present two new cases with aquagenic palmoplantar acrokeratoderma - a child and a young male. A significant clinical improvement was achieved after topical treatment with aluminum salts. Aquagenic palmar keratoderma may be a clue to cystic fibrosis in adolescents and young adults. We developed a new hypothesis on its pathogenesis.

Prolificacy data of Romanov sheep breed were retrieved from Sekhra Station (Jordan) through five parities. The data were used for studying the effect of Fecundity (FecB), Growth Differentiation Factor 9 (GDF9) and Prolactin genes on the prolificacy of Romanov ewes. GDF9, FecB and Prolactin genes genotypes were investigated in Romanov ewes by using the PCRRFLP technique. The Mixed Model of SAS software was used for analyzing the data. The different gene genotypes and the parity were inserted in the Model as fixed effects while the dams were inserted as Random. Fecundity gene was observed to be monomorphic, the wild type genotype of Fecundity gene was found in the Romanov ewes. Prolactin and GDF9 genes were observed to be polymorphic in Romanov. The results revealed non-significant differences in the prolificacy of the ewes that carry AA and BB of Prolactin gene genotypes. The GDF9 gene genotypes showed significant (P≤0.0001) differences in prolificacy. The homozygous MM genotype ewes produced 0.792 more lambs born per lambing than the heterozygous NM genotype. Selection based on GDF9 mutation may help in improving the prolificacy of Romanov sheep. [ABSTRACT FROM AUTHOR]