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VEGF gene has been reported to be related with many diseases and recurrent pregnancy loss in various studies. Concerning the role of VEGF polymorphisms in pregnancy losses, generally mothers genotypes have been analyzed. To evaluate the association between VEGF A +405G/C (rs2010963), -460T/C (rs833061), +936C/T (rs3025039) and - 2578A/C (rs699947) polymorphisms and spontaneous abortion, we studied the genotypes of spontaneously aborted fetuses, their mothers and healthy controls. 23 spontaneously aborted fetal materials, 22 mothers who had these abortions and 86 healthy controls were included in this study. rs2010963, rs833061, rs3025039 and rs699947 polymorphisms were analyzed by Real Time PCR technique after genomic DNA isolation from all subjects. The frequencies of VEGF A rs2010963 GG genotype and rs2010963 G allele were higher in fetuses compared both with mothers and healthy controls. VEGF A rs3025039 TT genotype and rs3025039 T allele frequencies were higher in fetuses comparing with mothers. VEGF A rs833061 CT and TT genotypes frequencies were higher in fetuses comparing with mothers. We ascertained that VEGF A rs2010963, rs833061 and rs3025039 are the risk factors for spontaneous abortion in fetal genotypes comparing with their mothers and healthy controls.
We report the first genetic characterization of wildtype measles viruses from Uganda. Thirty-six virus isolates from outbreaks in 6 districts were analyzed from 2000 to 2002. Analyses of sequences of the nucleoprotein (N) and hemagglutinin (H) genes showed that the Ugandan isolates were all closely related, and phylogenetic analysis indicated that these viruses were members of a unique group within clade D. Sequences of the Ugandan viruses were not closely related to any of the World Health Organization reference sequences representing the 22 currently recognized genotypes. The minimum nucleotide divergence between the Ugandan viruses and the most closely related reference strain, genotype D2, was 3.1% for the N gene and 2.6% for the H gene. Therefore, Ugandan viruses should be considered a new, proposed genotype (d10). This new sequence information will expand the utility of molecular epidemiologic techniques for describing measles transmission patterns in eastern Africa.
This study described the structural characterization of Pakistani HCV NS3 GT3a in parallel with genotypes 1a and 1b NS3. We investigated the role of amino acids and their interaction patterns in different HCV genotypes by crystallographic modeling. Different softwares were used to study the interaction pattern, for example, CLCBIO sequence viewer, MODELLER, NMRCLUST, ERRAT score, and MODELLER. Sixty models were produced and clustered into groups and the best model of PK-NCVI/Pk3a NS3 was selected and studied further to check the variability with other HCV NS3 genotypes. This study will help in future to understand the structural architecture of HCV genome variability and to further define the conserved targets for antiviral agents.
F2 and recombinant inbred lines (RILs) populations are very commonly used in plant genetic mapping studies. Although genome-wide genetic markers like single nucleotide polymorphisms (SNPs) can be readily identified by a wide array of methods, accurate genotype calling remains challenging, especially for heterozygous loci and missing data due to low sequencing coverage per individual. Therefore, we developed Genotype-Corrector, a program that corrects genotype calls and imputes missing data to improve the accuracy of genetic mapping. Genotype-Corrector can be applied in a wide variety of genetic mapping studies that are based on low coverage whole genome sequencing (WGS) or Genotyping-by-Sequencing (GBS) related techniques. Our results show that Genotype-Corrector achieves high accuracy when applied to both synthetic and real genotype data. Compared with using raw or only imputed genotype calls, the linkage groups built by corrected genotype data show much less noise and significant distortions can be corrected. Additionally, Genotype-Corrector compares favorably to the popular imputation software LinkImpute and Beagle in both F2 and RIL populations. Genotype-Corrector is publicly available on GitHub at https://github.com/freemao/Genotype-Corrector .
The genetic correlation between purebred (PB) and crossbred (CB) performances ([Formula: see text]) partially determines the response in CB when selection is on PB performance in the parental lines. An earlier study has derived expressions for an upper and lower bound of [Formula: see text], using the variance components of the parental purebred lines, including e.g. the additive genetic variance in the sire line for the trait expressed in one of the dam lines. How to estimate these variance components is not obvious, because animals from one parental line do not have phenotypes for the trait expressed in the other line. Thus, the aim of this study was to propose and compare three methods for approximating the required variance components. The first two methods are based on (co)variances of genomic estimated breeding values (GEBV) in the line of interest, either accounting for shrinkage (VCGEBV-S) or not (VCGEBV). The third method uses restricted maximum likelihood (REML) estimates directly from univariate and bivariate analyses (VCREML) by ignoring that the variance components should refer to the line of interest, rather than to the line in which the trait is expressed. We validated these methods by comparing the resulting predicted bounds of [Formula: see text] with the [Formula: see text] estimated from PB and CB data for five traits in a three-way cross in pigs.
This study aimed to investigate the genetic evolution of the H9N2 avian influenza virus (AIV). Whole genome phylogenetic trees were constructed based on 306 H9N2 avian influenza strains collected in China from 2014 to 2019. The results showed that eight gene sequences were clustered separately according to their dominant clades, and a total of 10 genotypes were identified (seven of which were novel types). Among them, G57 genotype was confirmed as the most prevalent genotype with a frequency of 94%. In China, the G57 genotype of H9N2 first emerged in 2007, and then became the most common genotype in 2013. Therefore, the nucleotide substitution rates of G57 genotype in HA and NA genes collected from 2007 to 2019 were estimated, and the positive selection pressure sites in the same data set were measured. Taking 2013 as the boundary, the time period was divided into two periods: 2007-2012 and 2013-2019. From 2007 to 2012, multiple genotypes coexisted and could bear the pressures from both nature and environment; while G57 genotype was still in the adaptation stage, subjected to less selection pressure and in the process of slow evolution. However, from 2013 to 2019, G57 became the dominant genotype, and most of the external pressure reacted on it. Moreover, G57 genotype showed better adaptability than other genotypes. From 2013 to 2019, the nucleotide substitution rates of the HA gene were increased, and the positive selection pressures on HA and NA genes were stronger compared to those from 2007 to 2012. To sum up, the absolutely dominant G57 genotype exhibited a relatively constant genotype frequency and experienced adaptive evolution and natural selection simultaneously during the monitoring period. Therefore, urgent attention and diligent surveillance of H9N2 avian influenza virus are becoming increasingly important.
Several methods have been proposed to impute genotypes at untyped markers using observed genotypes and genetic data from a reference panel. We used the Genetic Analysis Workshop 16 rheumatoid arthritis case-control dataset to compare the performance of four of these imputation methods: IMPUTE, MACH, PLINK, and fastPHASE. We compared the methods' imputation error rates and performance of association tests using the imputed data, in the context of imputing completely untyped markers as well as imputing missing genotypes to combine two datasets genotyped at different sets of markers. As expected, all methods performed better for single-nucleotide polymorphisms (SNPs) in high linkage disequilibrium with genotyped SNPs. However, MACH and IMPUTE generated lower imputation error rates than fastPHASE and PLINK. Association tests based on allele "dosage" from MACH and tests based on the posterior probabilities from IMPUTE provided results closest to those based on complete data. However, in both situations, none of the imputation-based tests provide the same level of evidence of association as the complete data at SNPs strongly associated with disease.
Hepatitis delta virus (HDV) coinfection will additionally aggravate the hepatitis B virus (HBV) burden in the coming decades, with an increase in HBV-related liver diseases. Between 2018 and 2019, a total of 205 HBV patients clinically characterized as chronic hepatitis B (CHB; n = 115), liver cirrhosis (LC; n = 21), and hepatocellular carcinoma (HCC; n = 69) were recruited. HBV surface antigen (HBsAg), antibodies against surface antigens (anti-HBs), and core antigens (anti-HBc) were determined by ELISA. The presence of hepatitis B viral DNA and hepatitis delta RNA was determined. Distinct HBV and HDV genotypes were phylogenetically reconstructed and vaccine escape mutations in the "a" determinant region of HBV were elucidated. All HBV patients were HbsAg positive, with 99% (n = 204) and 7% (n = 15) of them being positive for anti-HBc and anti-HBs, respectively. Anti-HBs positivity was higher among HCC (15%; n = 9) compared to CHB patients. The HBV-B genotype was predominant (65%; n = 134), followed by HBV-C (31%; n = 64), HBV-D, and HBV-G (3%; n = 7). HCC was observed frequently among young individuals with HBV-C genotypes. A low frequency (2%; n = 4) of vaccine escape mutations was observed. HBV-HDV coinfection was observed in 16% (n = 33) of patients with the predominant occurrence of the HDV-1 genotype. A significant association of genotypes with alanine aminotransferase (ALT) and aspartate aminotransferase (AST) enzyme levels was observed in HBV monoinfections. The prevalence of the HDV-1 genotype is high in Vietnam. No correlation was observed between HDV-HBV coinfections and disease progression when compared to HBV monoinfections.
Rhizobia are ecologically important, facultative plant-symbiotic microbes. In nature, there is a large variability in the association of rhizobial strains and host plants of the same species. Here, we evaluated whether plant and rhizobial genotypes influence the initial transcriptional response of rhizobium following perception of a host plant. RNA sequencing of the model rhizobium Sinorhizobium meliloti exposed to root exudates or luteolin (an inducer of nod genes, involved in the early steps of symbiotic interaction) was performed on a combination of three S. meliloti strains and three alfalfa varieties as host plants. The response to root exudates involved hundreds of changes in the rhizobium transcriptome. Of the differentially expressed genes, 35% were influenced by the strain genotype, 16% were influenced by the plant genotype, and 29% were influenced by strain-by-host plant genotype interactions. We also examined the response of a hybrid S. meliloti strain in which the symbiotic megaplasmid (∼20% of the genome) was mobilized between two of the above-mentioned strains. Dozens of genes were upregulated in the hybrid strain, indicative of nonadditive variation in the transcriptome. In conclusion, this study demonstrated that transcriptional responses of rhizobia upon perception of legumes are influenced by the genotypes of both symbiotic partners and their interaction, suggesting a wide spectrum of genetic determinants involved in the phenotypic variation of plant-rhizobium symbiosis.IMPORTANCE A sustainable way for meeting the need of an increased global food demand should be based on a holobiont perspective, viewing crop plants as intimately associated with their microbiome, which helps improve plant nutrition, tolerance to pests, and adverse climate conditions. However, the genetic repertoire needed for efficient association with plants by the microbial symbionts is still poorly understood. The rhizobia are an exemplary model of facultative plant symbiotic microbes. Here, we evaluated whether genotype-by-genotype interactions could be identified in the initial transcriptional response of rhizobium perception of a host plant. We performed an RNA sequencing study to analyze the transcriptomes of different rhizobial strains elicited by root exudates of three alfalfa varieties as a proxy of an early step of the symbiotic interaction. The results indicated strain- and plant variety-dependent variability in the observed transcriptional changes, providing fundamentally novel insights into the genetic basis of rhizobium-plant interactions. Our results provide genetic insights and perspective to aid in the exploitation of natural rhizobium variation for improvement of legume growth in agricultural ecosystems.
Pharmacogenomics (PGx) research holds the promise for detecting association between genetic variants and drug responses in randomized clinical trials, but it is limited by small populations and thus has low power to detect signals. It is critical to increase the power of PGx genome-wide association studies (GWAS) with small sample sizes so that variant-drug-response association discoveries are not limited to common variants with extremely large effect.
Most current genotype imputation methods are model-based and computationally intensive, taking days to impute one chromosome pair on 1000 people. We describe an efficient genotype imputation method based on matrix completion. Our matrix completion method is implemented in MATLAB and tested on real data from HapMap 3, simulated pedigree data, and simulated low-coverage sequencing data derived from the 1000 Genomes Project. Compared with leading imputation programs, the matrix completion algorithm embodied in our program MENDEL-IMPUTE achieves comparable imputation accuracy while reducing run times significantly. Implementation in a lower-level language such as Fortran or C is apt to further improve computational efficiency.
Genotype imputation for single nucleotide polymorphisms (SNPs) has been shown to be a powerful means to include genetic markers in exploratory genetic association studies without having to genotype them, and is becoming a standard procedure. A number of different software programs are available. In our experience, user-friendliness is often the deciding factor in the choice of software to solve a particular task. We therefore evaluated the usability of three publicly available imputation programs: BEAGLE, IMPUTE and MACH. We found all three programs to perform well with HapMap reference data, with little effort needed for data preparation and subsequent association analysis. Each of them has different strengths and weaknesses, however, and none is optimal for all situations.
Recent increase in the detection of unusual G1P[8], G3P[8], G8P[8], and G9P[4] Rotavirus A (RVA) strains bearing the DS-1-like constellation of the non-G, non-P genes (hereafter referred to as the genotype 2 backbone) requires better understanding of their evolutionary relationship. However, within a genotype, there is lack of a consensus lineage designation framework and a set of common sequences that can serve as references. Phylogenetic analyses were carried out on over 8,500 RVA genotype 2 genes systematically retrieved from the rotavirus database within the NCBI Virus Variation Resource. In line with previous designations, using pairwise comparison of cogent nucleotide sequences and stringent bootstrap support, reference lineages were defined. This study proposes a lineage framework and provides a dataset ranging from 34 to 145 sequences for each genotype 2 gene for orderly lineage designation of global genotype 2 genes of RVAs detected in human and animals. The framework identified five to 31 lineages depending on the gene. The least number of lineages (five to seven) were observed in genotypes A2 (NSP1), T2 (NSP3) and H2 (NSP5) which are limited to human RVA whereas the most number of lineages (31) was observed in genotype E2 (NSP4). Sharing of the same lineage constellations of the genotype 2 backbone genes between recently-emerging, unusual G1P[8], G3P[8], G8P[8] and G9P[4] reassortants and many contemporary G2P[4] strains provided strong support to the hypothesis that unusual genotype 2 strains originated primarily from reassortment events in the recent past involving contemporary G2P[4] strains as one parent and ordinary genotype 1 strains or animal RVA strains as the other. The lineage framework with selected reference sequences will help researchers to identify the lineage to which a given genotype 2 strain belongs, and trace the evolutionary history of common and unusual genotype 2 strains in circulation.
Sedentary behavior (SB) expression and its underlying causal factors have been progressively studied, as it is a major determinant of decreased health quality. In the present study we applied Genotype x Age (GxAge) and Genotype x Sex (GxSex) interaction methods to determine if the phenotypic expression of different SB traits is influenced by an interaction between genetic architecture and both age and sex. A total of 1345 subjects, comprising 249 fathers, 327 mothers, 334 sons and 325 daughters, from 339 families of The Portuguese Healthy Family Study were included in the analysis. SB traits were assessed by means of a 3-d physical activity recall, the Baecke and IPAQ questionnaires. GxAge and GxSex interactions were analyzed using SOLAR 4.0 software. Sedentary behaviour heritability estimates were not always statistically significant (p>0.05) and ranged from 3% to 27%. The GxSex and GxAge interaction models were significantly better than the single polygenic models for TV (min/day), EEsed (kcal/day), personal computer (PC) usage and physical activty (PA) tertiles. The GxAge model is also significantly better than the polygenic model for Sed (min/day). For EEsed, PA tertiles, PC and Sed, the GxAge interaction was significant because the genetic correlation between SB environments was significantly different from 1. Further, PC and Sed variance heterogeneity among distinct ages were observed. The GxSex interaction was significant for EEsed due to genetic variance heterogeneity between genders and for PC due to a genetic correlation less than 1 across both sexes. Our results suggest that SB expression may be influenced by the interactions between genotype with both sex and age. Further, different sedentary behaviors seem to have distinct genetic architectures and are differentially affected by age and sex.
Wolbachia pipientis is a widespread, obligatory intracellular and maternally inherited bacterium, that induces a wide range of reproductive alterations to its hosts. Cytoplasmic Incompatibility (CI) is causing embryonic lethality, the most common of them. Despite that Wolbachia-borne sterility has been proposed as an environmental friendly pest control method (Incompatible Insect Technique, IIT) since 1970s, the fact that Wolbachia modifies important fitness components of its hosts sets severe barriers to IIT implementation. Mass rearing of Mediterranean fruit fly, Ceratitis capitata (medfly), is highly optimized given that this pest is a model species regarding the implementation of another sterility based pest control method, the Sterile Insect Technique (SIT). We used the medfly-Wolbachia symbiotic association, as a model system, to study the effect of two different Wolbachia strains, on the life history traits of 2 C. capitata lines with different genomic background.
The dynamics of coevolution between hosts and parasites are influenced by their genetic interactions. Highly specific interactions, where the outcome of an infection depends on the precise combination of host and parasite genotypes (G × G interactions), have the potential to maintain genetic variation by inducing negative frequency-dependent selection. The importance of this effect also rests on whether such interactions are consistent across different environments or modified by environmental variation (G × G × E interaction). In the black bean aphid, Aphis fabae, resistance to its parasitoid Lysiphlebus fabarum is largely determined by the possession of a heritable bacterial endosymbiont, Hamiltonella defensa, with strong G × G interactions between H. defensa and L. fabarum. A key environmental factor in this system is the host plant on which the aphid feeds. Here, we exposed genetically identical aphids harbouring three different strains of H. defensa to three asexual genotypes of L. fabarum and measured parasitism success on three common host plants of A. fabae, namely Vicia faba, Chenopodium album and Beta vulgaris. As expected, we observed the pervasive G × G interaction between H. defensa and L. fabarum, but despite strong main effects of the host plants on average rates of parasitism, this interaction was not altered significantly by the host plant environment (no G × G × E interaction). The symbiont-conferred specificity of resistance is thus likely to mediate the coevolution of A. fabae and L. fabarum, even when played out across diverse host plants of the aphid.
Genome-wide association studies have revealed an association between several loci in the nicotinic acetylcholine receptor gene cluster CHRNA5-A3-B4 and daily cigarette consumption. Recent studies have sought to refine this phenotype, and have shown that a locus within this cluster, marked primarily by rs1051730 and rs16969968, is also associated with levels of cotinine, the primary metabolite of nicotine. This association remains after adjustment for self-reported smoking, which suggests that even amongst people who smoke the same number of cigarettes there is still genetically-influenced variation in nicotine consumption. This is likely to be due to differences in smoking topography, that is, how a cigarette is smoked (e.g., volume of smoke inhaled per puff, number of puffs taken per cigarette). The aim of this study is to determine potential mediation of the relationship between the rs1051730 locus and cotinine levels by smoking topography.
Host genotype can influence the composition of the commensal bacterial community in some organisms. Composition, however, is only one parameter describing a microbial community. Here, we test whether a second parameter-abundance of bacteria-is a heritable trait by quantifying the presence of four commensal bacterial strains within 36 gnotobiotic inbred lines of Drosophila melanogaster. We find that D. melanogaster genotype exerts a significant effect on microbial levels within the fly. When introduced as monocultures into axenic flies, three of the four bacterial strains were reliably detected within the fly. The amounts of these different strains are strongly correlated, suggesting that the host regulates commensal bacteria through general, not bacteria-specific, means. While the correlation does not appear to be driven by simple variation in overall gut dimensions, a genetic association study suggests that variation in commensal bacterial load may largely be attributed to physical aspects of host cell growth and development.
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