Regulation of nitric oxide production in hypothyroidism

Hypothyroidism is a common endocrine disorder that predominantly occurs in females. It is associated with an increased risk of cardiovascular diseases (CVD), but the molecular mechanism is not known. Disturbance in lipid metabolism, the regulation of oxidative stress, and inflammation characterize the progression of subclinical hypothyroidism. The initiation and progression of endothelial dysfunction also exhibit these changes, which is the initial step in developing CVD. Animal and human studies highlight the critical role of nitric oxide (NO) as a reliable biomarker for cardiovascular risk in subclinical and clinical hypothyroidism. In this review, we summarize the recent literature findings associated with NO production by the thyroid hormones in both physiological and pathophysiological conditions. We also discuss the levothyroxine treatment effect on serum NO levels in hypothyroid patients. © 2020 The Author

Reptile enamel matrix proteins: Selection, divergence, and functional constraint

The three major enamel matrix proteins (EMPs): amelogenin (AMEL), ameloblastin (AMBN), and enamelin (ENAM), are intrinsically linked to tooth development in tetrapods. However, reptiles and mammals exhibit significant differences in dental patterning and development, potentially affecting how EMPs evolve in each group. In most reptiles, teeth are replaced continuously throughout life, while mammals have reduced replacement to only one or two generations. Reptiles also form structurally simple, aprismatic enamel while mammalian enamel is composed of highly organized hydroxyapatite prisms. These differences, combined with reported low sequence homology in reptiles, led us to predict that reptiles may experience lower selection pressure on their EMPs as compared with mammals. However, we found that like mammals, reptile EMPs are under moderate purifying selection, with some differences evident between AMEL, AMBN, and ENAM. We also demonstrate that sequence homology in reptile EMPs is closely associated with divergence times, with more recently diverged lineages exhibiting high homology, along with strong phylogenetic signal. Lastly, despite sequence divergence, none of the reptile species in our study exhibited mutations consistent with diseases that cause degeneration of enamel (e.g. amelogenesis imperfecta). Despite short tooth retention time and simplicity in enamel structure, reptile EMPs still exhibit purifying selection required to form durable enamel.We calculated the percent identity between amino acid sequences of ameloblastin from various reptile groups. Crocodilians exhibit the highest sequence identity, while identity across squamates was substantially lower. Upon closer examination of the individual squamate clades, however, we found that identity values are actually much higher in snakes, with much of the variation existing between the various lizard infraorders.HIGHLIGHTSReptile enamel matrix proteins are under moderate purifying selection despite polyphyodonty and simple enamel structure.Sequence identity in reptile enamel matrix proteins exhibit correlation with divergence times in spite of differences in substitution rates.Reptile amelogenin operates under a distinct selection regime compared with ameloblastin and enamelin.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150577/1/jezb22857.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150577/2/jezb22857-sup-0001-Supplementary_file.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150577/3/jezb22857-sup-0007-Supplementary_file_S8-DAMBE-Saturation.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150577/4/jezb22857-sup-0002-Supplementary_file_S1-SpeciesTable.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150577/5/jezb22857-sup-0003-Supplementary_file_S2_Alignments.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150577/6/jezb22857-sup-0008-Supplementary_File_S9.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150577/7/jezb22857-sup-0005-Supplementary_file_S6.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150577/8/jezb22857_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150577/9/jezb22857-sup-0009-Supplementary_file_Reptiles.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150577/10/jezb22857-sup-0006-Supplementary_file_S7-DIVERGE.pd

Comparative genomics study reveals Red Sea Bacillus with characteristics associated with potential microbial cell factories (MCFs)

© 2019, The Author(s). Recent advancements in the use of microbial cells for scalable production of industrial enzymes encourage exploring new environments for efficient microbial cell factories (MCFs). Here, through a comparison study, ten newly sequenced Bacillus species, isolated from the Rabigh Harbor Lagoon on the Red Sea shoreline, were evaluated for their potential use as MCFs. Phylogenetic analysis of 40 representative genomes with phylogenetic relevance, including the ten Red Sea species, showed that the Red Sea species come from several colonization events and are not the result of a single colonization followed by speciation. Moreover, clustering reactions in reconstruct metabolic networks of these Bacillus species revealed that three metabolic clades do not fit the phylogenetic tree, a sign of convergent evolution of the metabolism of these species in response to special environmental adaptation. We further showed Red Sea strains Bacillus paralicheniformis (Bac48) and B. halosaccharovorans (Bac94) had twice as much secreted proteins than the model strain B. subtilis 168. Also, Bac94 was enriched with genes associated with the Tat and Sec protein secretion system and Bac48 has a hybrid PKS/NRPS cluster that is part of a horizontally transferred genomic region. These properties collectively hint towards the potential use of Red Sea Bacillus as efficient protein secreting microbial hosts, and that this characteristic of these strains may be a consequence of the unique ecological features of the isolation environment

Evidence for Pervasive Adaptive Protein Evolution in Wild Mice

The relative contributions of neutral and adaptive substitutions to molecular evolution has been one of the most controversial issues in evolutionary biology for more than 40 years. The analysis of within-species nucleotide polymorphism and between-species divergence data supports a widespread role for adaptive protein evolution in certain taxa. For example, estimates of the proportion of adaptive amino acid substitutions (alpha) are 50% or more in enteric bacteria and Drosophila. In contrast, recent estimates of alpha for hominids have been at most 13%. Here, we estimate alpha for protein sequences of murid rodents based on nucleotide polymorphism data from multiple genes in a population of the house mouse subspecies Mus musculus castaneus, which inhabits the ancestral range of the Mus species complex and nucleotide divergence between M. m. castaneus and M. famulus or the rat. We estimate that 57% of amino acid substitutions in murids have been driven by positive selection. Hominids, therefore, are exceptional in having low apparent levels of adaptive protein evolution. The high frequency of adaptive amino acid substitutions in wild mice is consistent with their large effective population size, leading to effective natural selection at the molecular level. Effective natural selection also manifests itself as a paucity of effectively neutral nonsynonymous mutations in M. m. castaneus compared to humans

Detecting Linkage between a Trait and a Marker in a Random Mating Population without Pedigree Record

Modern linkage-based approaches employing extended pedigrees are becoming powerful tools for localizing complex quantitative trait loci. For these linkage mapping methods, it is necessary to reconstruct extended pedigrees which include living individuals, using extensive pedigree records. Unfortunately, such records are not always easy to obtain and application of the linkage-based approaches has been restricted. Within a finite population under random mating, latent inbreeding rather than non-random inbreeding by consanguineous marriages is expected to occur and is attributable to coalescence in a finite population. Interestingly, it has been revealed that significant random inbreeding exists even in general human populations. Random inbreeding should be used to detect the hidden coancestry between individuals for a particular chromosomal position and it could also have application in linkage mapping methods. Here we present a novel method, named finite population based linkage mapping (FPL) method, to detect linkage between a quantitative trait and a marker via random inbreeding in a finite population without pedigree records. We show how to estimate coancestry for a chromosomal position between individuals by using multipoint Bayesian estimation. Subsequently, we describe the FPL method for detecting linkage via interval mapping method using a nonparametric test. We show that the FPL method does work via simulated data. For a random sample from a finite population, the FPL method is more powerful than a standard pedigree-based linkage mapping method with using genotypes of all parents of the sample. In addition, the FPL method was demonstrated by actual microsatellite genotype data of 750 Japanese individuals that are unrelated according to pedigree records to map a known Psoriasis susceptible locus. For samples without pedigree records, it was suggested that the FPL method require limited number of individuals, therefore would be better than other methods using thousands of individuals

Personalized Pathway Enrichment Map of Putative Cancer Genes from Next Generation Sequencing Data

BACKGROUND: Pathway analysis of a set of genes represents an important area in large-scale omic data analysis. However, the application of traditional pathway enrichment methods to next-generation sequencing (NGS) data is prone to several potential biases, including genomic/genetic factors (e.g., the particular disease and gene length) and environmental factors (e.g., personal life-style and frequency and dosage of exposure to mutagens). Therefore, novel methods are urgently needed for these new data types, especially for individual-specific genome data. METHODOLOGY: In this study, we proposed a novel method for the pathway analysis of NGS mutation data by explicitly taking into account the gene-wise mutation rate. We estimated the gene-wise mutation rate based on the individual-specific background mutation rate along with the gene length. Taking the mutation rate as a weight for each gene, our weighted resampling strategy builds the null distribution for each pathway while matching the gene length patterns. The empirical P value obtained then provides an adjusted statistical evaluation. PRINCIPAL FINDINGS/CONCLUSIONS: We demonstrated our weighted resampling method to a lung adenocarcinomas dataset and a glioblastoma dataset, and compared it to other widely applied methods. By explicitly adjusting gene-length, the weighted resampling method performs as well as the standard methods for significant pathways with strong evidence. Importantly, our method could effectively reject many marginally significant pathways detected by standard methods, including several long-gene-based, cancer-unrelated pathways. We further demonstrated that by reducing such biases, pathway crosstalk for each individual and pathway co-mutation map across multiple individuals can be objectively explored and evaluated. This method performs pathway analysis in a sample-centered fashion, and provides an alternative way for accurate analysis of cancer-personalized genomes. It can be extended to other types of genomic data (genotyping and methylation) that have similar bias problems

Optimized ancestral state reconstruction using Sankoff parsimony

<p>Abstract</p> <p>Background</p> <p>Parsimony methods are widely used in molecular evolution to estimate the most plausible phylogeny for a set of characters. Sankoff parsimony determines the minimum number of changes required in a given phylogeny when a cost is associated to transitions between character states. Although optimizations exist to reduce the computations in the number of taxa, the original algorithm takes time <it>O</it>(<it>n</it>²) in the number of states, making it impractical for large values of <it>n</it>.</p> <p>Results</p> <p>In this study we introduce an optimization of Sankoff parsimony for the reconstruction of ancestral states when ultrametric or additive cost matrices are used. We analyzed its performance for randomly generated matrices, Jukes-Cantor and Kimura's two-parameter models of DNA evolution, and in the reconstruction of elongation factor-1<it>α </it>and ancestral metabolic states of a group of eukaryotes, showing that in all cases the execution time is significantly less than with the original implementation.</p> <p>Conclusion</p> <p>The algorithms here presented provide a fast computation of Sankoff parsimony for a given phylogeny. Problems where the number of states is large, such as reconstruction of ancestral metabolism, are particularly adequate for this optimization. Since we are reducing the computations required to calculate the parsimony cost of a single tree, our method can be combined with optimizations in the number of taxa that aim at finding the most parsimonious tree.</p

A Strong Deletion Bias in Nonallelic Gene Conversion

Gene conversion is the unidirectional transfer of genetic information between orthologous (allelic) or paralogous (nonallelic) genomic segments. Though a number of studies have examined nucleotide replacements, little is known about length difference mutations produced by gene conversion. Here, we investigate insertions and deletions produced by nonallelic gene conversion in 338 Drosophila and 10,149 primate paralogs. Using a direct phylogenetic approach, we identify 179 insertions and 614 deletions in Drosophila paralogs, and 132 insertions and 455 deletions in primate paralogs. Thus, nonallelic gene conversion is strongly deletion-biased in both lineages, with almost 3.5 times as many conversion-induced deletions as insertions. In primates, the deletion bias is considerably stronger for long indels and, in both lineages, the per-site rate of gene conversion is orders of magnitudes higher than that of ordinary mutation. Due to this high rate, deletion-biased nonallelic gene conversion plays a key role in genome size evolution, leading to the cooperative shrinkage and eventual disappearance of selectively neutral paralogs

Distribution and Effects of Nonsense Polymorphisms in Human Genes

BACKGROUND: A great amount of data has been accumulated on genetic variations in the human genome, but we still do not know much about how the genetic variations affect gene function. In particular, little is known about the distribution of nonsense polymorphisms in human genes despite their drastic effects on gene products. METHODOLOGY/PRINCIPAL FINDINGS: To detect polymorphisms affecting gene function, we analyzed all publicly available polymorphisms in a database for single nucleotide polymorphisms (dbSNP build 125) located in the exons of 36,712 known and predicted protein-coding genes that were defined in an annotation project of all human genes and transcripts (H-InvDB ver3.8). We found a total of 252,555 single nucleotide polymorphisms (SNPs) and 8,479 insertion and deletions in the representative transcripts in these genes. The SNPs located in ORFs include 40,484 synonymous and 53,754 nonsynonymous SNPs, and 1,258 SNPs that were predicted to be nonsense SNPs or read-through SNPs. We estimated the density of nonsense SNPs to be 0.85x10(-3) per site, which is lower than that of nonsynonymous SNPs (2.1x10(-3) per site). On average, nonsense SNPs were located 250 codons upstream of the original termination codon, with the substitution occurring most frequently at the first codon position. Of the nonsense SNPs, 581 were predicted to cause nonsense-mediated decay (NMD) of transcripts that would prevent translation. We found that nonsense SNPs causing NMD were more common in genes involving kinase activity and transport. The remaining 602 nonsense SNPs are predicted to produce truncated polypeptides, with an average truncation of 75 amino acids. In addition, 110 read-through SNPs at termination codons were detected. CONCLUSION/SIGNIFICANCE: Our comprehensive exploration of nonsense polymorphisms showed that nonsense SNPs exist at a lower density than nonsynonymous SNPs, suggesting that nonsense mutations have more severe effects than amino acid changes. The correspondence of nonsense SNPs to known pathological variants suggests that phenotypic effects of nonsense SNPs have been reported for only a small fraction of nonsense SNPs, and that nonsense SNPs causing NMD are more likely to be involved in phenotypic variations. These nonsense SNPs may include pathological variants that have not yet been reported. These data are available from Transcript View of H-InvDB and VarySysDB (http://h-invitational.jp/varygene/)

Towards BioDBcore: a community-defined information specification for biological databases

The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological database