Genomic Perspective Research Articles

Population genomics of a thermophilic cyanobacterium revealed divergence at subspecies level and possible adaptation genes

BackgroundCyanobacteria are diverse phototrophic microbes with ecological importance and potential for biotechnology applications. One species of thermophilic cyanobacteria, Thermosynechococcus taiwanensis, has been studied for biomass pyrolysis, estrogen degradation, and the production of bioethanol, monosaccharide, and phycocyanin. To better understand the diversity and evolution of this species, we sampled across different regions in Taiwan for strain isolation and genomic analysis.ResultsA total of 27 novel strains were isolated from nine of the 12 hot springs sampled and subjected to whole genome sequencing. Including strains studied previously, our genomic analyses encompassed 32 strains from 11 hot springs. Genome sizes among these strains ranged from 2.64 to 2.70 Mb, with an average of 2.66 Mb. Annotation revealed between 2465 and 2576 protein-coding genes per genome, averaging 2537 genes. Core-genome phylogeny, gene flow estimates, and overall gene content divergence consistently supported the within-species divergence into two major populations. While isolation by distance partially explained the within-population divergence, the factors driving divergence between populations remain unclear. Nevertheless, this species likely has a closed pan-genome comprising approximately 3030 genes, with our sampling providing sufficient coverage of its genomic diversity. To investigate the divergence and potential adaptations, we identified genomic regions with significantly lower nucleotide diversity, indicating loci that may have undergone selective sweeps within each population. We identified 149 and 289 genes within these regions in populations A and B, respectively. Only 16 genes were common to both populations, suggesting that selective sweeps primarily targeted different genes in the two populations. Key genes related to functions such as photosynthesis, motility, and ion transport were highlighted.ConclusionsThis work provides a population genomics perspective on a hot spring cyanobacterial species in Taiwan. Beyond advancing our understanding of microbial genomics and evolution, the strains collected and genome sequences generated in this work provide valuable materials for future development and utilization of biological resources.

From the genome's perspective: Bearing somatic retrotransposition to leverage the regulatory potential of L1 RNAs.

Transposable elements (TEs) are mobile genomic elements constituting a big fraction of eukaryotic genomes. They ignite an evolutionary arms race with host genomes, which in turn evolve strategies to restrict their activity. Despite being tightly repressed, TEs display precisely regulated expression patterns during specific stages of mammalian development, suggesting potential benefits for the host. Among TEs, the long interspersed nuclear element (LINE-1 or L1) has been found to be active in neurons. This activity prompted extensive research into its possible role in cognition. So far, no specific cause-effect relationship between L1 retrotransposition and brain functions has been conclusively identified. Nevertheless, accumulating evidence suggests that interactions between L1 RNAs and RNA/DNA binding proteins encode specific messages that cells utilize to activate or repress entire transcriptional programs. We summarize recent findings highlighting the activity of L1 RNAs at the non-coding level during early embryonic and brain development. We propose a hypothesis suggesting a mutualistic relationship between L1 mRNAs and the host cell. In this scenario, cells tolerate a certain rate of retrotransposition to leverage the regulatory effects of L1s as non-coding RNAs on potentiating their mitotic potential. In turn, L1s benefit from the cell's proliferative state to increase their chance to mobilize.

Exploring the mediating role of immune cells in the pathogenesis of IgA nephropathy through the inflammatory axis of gut microbiota from a genomic perspective.

IgA nephropathy (IgAN) is a chronic glomerular disease characterized by the deposition of IgA antibodies in the kidney's mesangium. Its pathogenesis involves genetic, immune, and environmental factors, particularly within the mucosal immune system and gut microbiota. Immune cells play a central role in mediating these processes, which this study investigates using Mendelian Randomization (MR) to explore causal relationships among gut microbiota, inflammatory markers, blood cells, and immune cells in IgAN pathogenesis. We conducted a two-sample MR analysis using Genome-Wide Association Study (GWAS) summary data to assess the causal effects of gut microbiota, inflammatory markers, and blood cell traits on IgAN. Data sources included the FinnGen dataset for IgAN and relevant GWAS datasets for immune traits, blood cells, and inflammatory markers. Inverse variance weighting (IVW) was the primary MR method, supported by sensitivity analyses. We particularly examined the mediation effect of immune cells on these exposures' influence on IgAN. Significant associations were found between several factors and IgAN. Gut microbiota traits, such as Firmicutes E and Sporomusales, increased IgAN risk, while Citrobacter A and Herbinix reduced it. Inflammatory markers, including Interleukin-10 and Fibroblast Growth Factor 23, promoted IgAN onset. Blood cell traits like red blood cell perturbation response increased risk, while monocyte perturbation response was protective. Immune traits played a key mediating role, with Transitional %B cells reducing IgAN risk and CD28- CD25 + + CD8br %T cells increasing it. This study highlights the pivotal mediating role of immune cells in the interactions between gut microbiota, inflammatory markers, and IgAN risk. These findings identify potential biomarkers and therapeutic targets, providing new insights into the immune mechanisms underlying IgAN and opportunities for intervention.

Clinical, genomic, and proteomic perspectives in the analysis of comorbid conditions in type 2 diabetes mellitus: a retrospective study.

Type-2 Diabetes Mellitus (T2DM) affects millions globally, with escalating rates. It often leads to undiagnosed complications and commonly coexists with other health conditions. This study investigates two types of prevalent comorbidities related to T2DM-the circulatory system (DCM1) and digestive system diseases (DCM2)-using clinical, genomic and proteomic datasets. The aim is to identify new biomarkers by applying existing machine learning (ML) based techniques for early detection, prognosis and diagnosis of these comorbidities. Here, we report a cross-sectional retrospective analysis from a T2DM dataset of T2DM associated concordant comorbidities (diseases with shared pathophysiology and management) from the Diastrat cohort (a T2DM cohort) recruited at the Northern Ireland Centre for Stratified Medicine (NICSM), in Northern Ireland. In the clinical data analysis, we identified that lipidemia was shown to negatively correlate with depression in the DCM1 group while positively correlate with depression in the DCM2 group. In genomic analysis, we identified statistically significant variants rs9844730 in procollagen-lysine (PLOD2), rs73590361 in beta-1,4-N-acetyl- galactosaminyl-transferase (B4GALNT3) and rs964680 in A kinase (PRKA) anchor protein 14 (AKAP14) which appear to differentiate DCM1 and DCM2 groups. In proteomic analysis, we identified 4 statistically significant proteins: natriuretic peptides B (BNP), pro-adrenomedullin (ADM), natriuretic peptides B (NT-proBNP) and discoidin (DCBLD2) that can differentiate DCM1 and DCM2 groups and have built robust ML model using clinical, genomic, and proteomic markers (0.83 receiver operative characteristics curve area, 84% positive predictive value and 83% negative predictive value and a classification accuracy of 83%) for prediction of DCM1 and DCM2 groups. Our study successfully identifies novel clinical, genomic, and proteomic biomarkers that differentiate between circulatory and digestive system comorbidities in Type-2 Diabetes Mellitus patients. The machine learning model we developed demonstrates strong predictive capabilities, providing a promising tool for the early detection, prognosis, and diagnosis of these T2DM-associated comorbidities. These findings have the potential to enhance personalized management strategies for patients with T2DM, ultimately improving clinical outcomes. Further research is needed to validate these biomarkers and integrate them into clinical practice.

Genomic perspectives on foodborne illness

Whole-genome sequencing of bacterial pathogens is used by public health agencies to link cases of food poisoning caused by the same source of contamination. The vast majority of these appear to be sporadic cases associated with small contamination episodes and do not trigger investigations. A "contamination episode" refers to one or more contamination events from a single source over a period of time. We examine clusters of sequenced clinical isolates of Salmonella, Escherichia coli, Campylobacter, and Listeria that differ by only a small number of mutations (SNPs) to identify features of the underlying contamination episodes. These analyses provide additional evidence that the youngest age groups have greater susceptibility to infection by Salmonella, E. coli, and Campylobacter than older age groups. This age bias is weaker for the common Salmonella serovar Enteritidis than Salmonella in general. A large fraction of the contamination episodes causing sickness appear to have a long duration. For example, 50% of the Salmonella cases are in clusters that persist for almost 3 y. For all four pathogen species, the majority of the cases were part of genetic clusters with illnesses in multiple states and likely to be caused by contaminated commercially distributed foods. Salmonella infections in infants under 3 mo are predominantly acquired from the same contaminated food, pet food, or environmental sources as older individuals, rather than infant formula contaminated during production.

Genomic and transcriptomic perspectives on the origin and evolution of NUMTs in Orthoptera

Nuclear mitochondrial pseudogenes (NUMTs) result from the transfer of mitochondrial DNA (mtDNA) to the nuclear genome. NUMTs, as “frozen” snapshots of mitochondria, can provide insights into diversification patterns. In this study, we analyzed the origins and insertion frequency of NUMTs using genome assembly data from ten species in Orthoptera. We found divergences between NUMTs and contemporary mtDNA in Orthoptera ranging from 0 % to 23.78 %. The results showed that the number of NUMT insertions was significantly positively correlated with the content of transposable elements in the genome. We found that 39.09 %-68.65 % of the NUMTs flanking regions (2,000 bp) contained retrotransposons, and more NUMTs originated from mitochondrial rDNA regions. Based on the analysis of the mitochondrial transcriptome, we found a potential mechanism of NUMT integration: mitochondrial transcripts are reverse transcribed into double-stranded DNA and then integrated into the genome. The probability of this mechanism occurring accounts for 0.30 %-1.02 % of total mitochondrial nuclear transfer events. Finally, based on the phylogenetic tree constructed using NUMTs and contemporary mtDNA, we provide insights into ancient evolutionary events such as species-specific “autaponumts” and “synaponumts” shared among different species, as well as post-integration duplication events.

The effects of Pseudomonas strains isolated from Achnatherum inebrians on plant growth: A genomic perspective.

Achnatherum inebrians is a perennial grass widely distributed in northwest China. Nearly all wild A. inebrians plants are infected by Epichloë endophytes. In this study, bacteria from the phyllosphere were isolated from leaves of both endophyte-free and endophyte-infected A. inebrians and sequenced for identification. Pseudomonas, comprising 48.12% of the culturable bacterial communities, was the most dominant bacterial genus. Thirty-four strains from 12 Pseudomonas species were used to inoculate A. inebrians seeds and plants. Results indicated that Epichloë significantly increased the diversity and richness index of the phyllosphere. Pseudomonas Sp1, Sp3, Sp5 and Sp7 had a significantly positive effect on plant growth and photosynthesis, whereas Sp10, Sp11 and Sp12 had a significantly negative effect. Whole-genome and pan-genome analysis suggested that the variability in the effects of Pseudomonas on A. inebrians was related to differences in genome composition and genomic islands.

Immune Subtypes and Characteristics of Endometrial Cancer Based on Immunogenes.

The aim of this study was to explore the immune subtypes of endometrial cancer (EC) and its characteristics by immunogenes from the perspective of multidimensional genomics (multi-omics). Immune subtypes were carried out using an unsupervised non-negative matrix factorization clustering (NMF) method and their characteristics were analysed. Key genes were identified using random forest analysis. A predictive model for immune subtypes and their clinical prognosis were constructed. The relationship between immune subtypes and molecular subtypes was investigated. Two immune subtypes C1 and C2 were available. C2 patients were younger, less graded, had significantly higher immune cell infiltration, immune checkpoint expression, tumor neoantigens, tumor mutation load than C1 (P<005). S100A9, CD3D, CD3E, HLA-DRB1 and IL2RB were the key genes with significant survival outcomes. S100A9 expression was lower in C2 than C1, and IL2RB, HLA-DRB1, CD3E and CD3D expression was higher than C1 (P<0.05). The predictive accuracy of five key genes for immune subtypes was good, with a Receiver operating characteristic of 0.941. The incidence of TP53abn type in C2 was significantly lower than that of C1, and the incidence of POLE type was significantly higher than that of C1 (P<0.0001). EC can be divided into two immune subtypes based on immunogenes. Low expression of S100A9 and high expression of IL2RB, HLA-DRB1, CD3E, and CD3D suggest sensitivity to immunotherapy and a good prognosis.

3D genome contributes to MHC-II neoantigen prediction.

Reliable and ultra-fast DNA and RNA sequencing have been achieved with the emergence of high-throughput sequencing technology. When combining the results of DNA and RNA sequencing for tumor cells of cancer patients, neoantigens that potentially stimulate the immune response of either CD4+ or CD8+ T cells can be identified. However, due to the abundance of somatic mutations and the high polymorphic nature of human leukocyte antigen (HLA) it is challenging to accurately predict the neoantigens. Moreover, comparing to HLA-I presented peptides, the HLA-II presented peptides are more variable in length, making the prediction of HLA-II loaded neoantigens even harder. A number of computational approaches have been proposed to address this issue but none of them considers the DNA origin of the neoantigens from the perspective of 3D genome. Here we investigate the DNA origins of the immune-positive and non-negative HLA-II neoantigens in the context of 3D genome and discovered that the chromatin 3D architecture plays an important role in more effective HLA-II neoantigen prediction. We believe that the 3D genome information will help to increase the precision of HLA-II neoantigen discovery and eventually benefit precision and personalized medicine in cancer immunotherapy.

Maternal effects and its importance in the genetic evaluations of preweaning live weight traits of beef cattle. A review.

Maternal effects in cattle genetics are defined as the causal influence of the phenotype or maternal genotype on the offspring's phenotype by effects occurring when the genetic and environmental characteristics of the mother influence the phenotype of the offspring beyond the direct inheritance of genes. Its relevance has been strongly described in genetic models focused on the genetic improvement of preweaning traits in cow-calf beef cattle production systems. Here, basic concepts and the importance of maternal effects when using linear and animal model procedures for genetic evaluations of growth and live-weight traits in beef cattle are reviewed and discussed. A brief history of estimation methods from classical studies to recent studies used for the development of animal models for studying maternal effects is also provided. Some important biometric concepts for maternal effect estimation are described, and the antagonism between direct genetic effects and maternal effects, its biological basis, and sources of error in the estimation of direct genetic and maternal covariance are discussed. Finally, some genomic perspectives are presented.

Uncovering the genomic diversity of the wild forage crop Setaria sphacelata

AbstractGrasses are considered one of the most important angiosperm groups in economic terms. The Setaria sphacelata complex is an intriguing species with considerable variation in genome size (GS). It is currently being explored from a genomic perspective especially because of its great adaptability under winter periods. Repetitive DNA sequences are known to contribute significantly to GS diversity, which in turn can play a role in impacting the ecology and evolution of a species. This study is aimed to characterize the GS and repetitive elements of different germplasm accessions of S. sphacelata. We analyzed 540 plants from 70 accessions collected worldwide. Flow cytometry was used for GS estimation, together with chromosome counting, fluorescent in situ hybridization (FISH), and bioinformatic analysis. Most (i.e., 80%) accessions were tetraploids (2n = 4x = 36) with GS ranging from 3.0 to 3.7 pg/2C. Additionally, a low number of diploids (2n = 2x = 18; ∼1.6 to 2 pg/2C), pentaploids (2n = 5x = 45: ∼4 pg/2C), hexaploids (2n = 6x = 54; ∼4.4 pg/2C), and octoploids (2n = 8x = 72; ∼6 pg/2C,) were detected. The greatest variation was found in accessions from South Africa. RepeatExplorer2 showed that 39% and 43% of the genomes of two diploid accessions comprised repetitive sequences, with Ty3/gypsy retrotransposons being the most abundant repeats. However, variation in the percentage of two Ty3/gypsy sublineages, Athila and Ogre, suggests different process of amplification and deletion of repeats during the evolution of the species complex. In contrast, FISH revealed some satellite repeats with a conserved localized distribution in pericentromeric regions between accessions. Although differences in the distribution of the FISH signals over the chromosomes were observed between the different ploidy levels, the data suggest that increases in the ploidy level were associated with the occurrence of hybridization and DNA loss.

A review of model evaluation metrics for machine learning in genetics and genomics.

Machine learning (ML) has shown great promise in genetics and genomics where large and complex datasets have the potential to provide insight into many aspects of disease risk, pathogenesis of genetic disorders, and prediction of health and wellbeing. However, with this possibility there is a responsibility to exercise caution against biases and inflation of results that can have harmful unintended impacts. Therefore, researchers must understand the metrics used to evaluate ML models which can influence the critical interpretation of results. In this review we provide an overview of ML metrics for clustering, classification, and regression and highlight the advantages and disadvantages of each. We also detail common pitfalls that occur during model evaluation. Finally, we provide examples of how researchers can assess and utilise the results of ML models, specifically from a genomics perspective.

Exploring Levansucrase Operon Regulating Levan-Type Fructooligosaccharides (L-FOSs) Production in Priestia koreensis HL12.

Levan biopolymer and levan-type fructooligosaccharides (L-FOSs) are β-2,6-linked fructans that have been used as non-digestible dietary fiber and prebiotic oligosaccharides in food and cosmeceutical applications. In this study, we explore the operon responsible for levan and L-FOSs production in Priestia koreensis HL12. Presented is the first genomic perspective on sucrose utilization and the levan biosynthesis pathway in this bacterium. Regarding sequence annotation, the putative levansucrase operon responsible for β-2,6-linked fructan was identified in the genome of strain HL12, and comprises sacB levansucrase gene belonging to GH68, located adjacent to levB endo-levanase gene, which belongs to GH32. Importantly, sugars related with the levan biosynthesis pathway are proposed to be transported via 3 types of transportation systems, including multiple ABCSugar and glucose/H+ transporters, as well as glucose- and fructose-specific PTS systems. Based on product profile analysis, the HL12 strain exhibited high efficiency in levan production from high sucrose concentration (300 g/l), achieving the highest yield of 127 g/l (equivalent to 55% conversion based on sucrose consumption), together with short-chain L-FOSs (DP3-5) and long-chain L-FOSs with respective size larger than DP6 after 48 h incubation. These findings highlight the potential of P. koreensis HL12 as a whole-cell biocatalyst for producing levan and L-FOSs, and underscore its novelty in converting sugars into high-value-added products for diverse commercial and industrial applications.

Divergent Evolution in Bilateral Prostate Cancer: a Case Study.

Multifocal prostate cancer is a prevalent phenomenon, with most cases remaining uncharacterized from a genomic perspective. A patient presented with bilateral prostate cancer. On systematic biopsy, two indistinguishable clinicopathologic lesions were detected. Whole-genome sequencing displayed somatically unrelated tumours with distinct driver CNA regions, suggesting independent origins of the two tumors. We demonstrated that similar clinicopathologic multifocal tumours, which might be interpreted as clonal disease, can in fact represent independent cancers. Genetic prognostics can prevent mischaracterization of multifocal disease to enable optimal patient management.

Exploring the Genetic Landscape of Vitiligo in the Pura Raza Español Horse: A Genomic Perspective.

Vitiligo is a depigmentation autoimmune disorder characterized by the progressive loss of melanocytes leading to the appearance of patchy depigmentation of the skin. The presence of vitiligo in horses is greater in those with grey coats. The aim of this study was therefore to perform a genome-wide association study (GWAS) to identify genomic regions and putative candidate loci associated with vitiligo depigmentation and susceptibility in the Pura Raza Español population. For this purpose, we performed a wssGBLUP (weighted single step genomic best linear unbiased prediction) using data from a total of 2359 animals genotyped with Affymetrix Axiom™ Equine 670 K and 1346 with Equine GeneSeek Genomic Profiler™ (GGP) Array V5. A total of 60,136 SNPs (single nucleotide polymorphisms) present on the 32 chromosomes from the consensus dataset after quality control were employed for the analysis. Vitiligo-like depigmentation was phenotyped by visual inspection of the different affected areas (eyes, mouth, nostrils) and was classified into nine categories with three degrees of severity (absent, slight, and severe). We identified one significant genomic region for vitiligo around the eyes, eight significant genomic regions for vitiligo around the mouth, and seven significant genomic regions for vitiligo around the nostrils, which explained the highest percentage of variance. These significant genomic regions contained candidate genes related to melanocytes, skin, immune system, tumour suppression, metastasis, and cutaneous carcinoma. These findings enable us to implement selective breeding strategies to decrease the incidence of vitiligo and to elucidate the genetic architecture underlying vitiligo in horses as well as the molecular mechanisms involved in the disease's development. However, further studies are needed to better understand this skin disorder in horses.

A study on factors influencing delayed sputum conversion in newly diagnosed pulmonary tuberculosis based on bacteriology and genomics

Conversion of sputum from positive to negative is one of the indicators to evaluate the efficacy of anti-tuberculosis treatment (ATT). We investigate the factors associated with delayed sputum conversion after 2 or 5 months of ATT from the perspectives of bacteriology and genomics. A retrospective study of sputum conversion in sputum positive 1782 pulmonary tuberculosis (PTB) was conducted from 2021 to 2022 in Beijing, China. We also designed a case-matched study including 24 pairs of delayed-sputum-conversion patients (DSCPs) and timely-sputum-conversion patients (TSCPs), and collect clinical isolates from DSCPs before and after ATT and initial isolates of TSCPs who successfully achieved sputum conversion to negative after 2 months of ATT. A total of 75 strains were conducted drug sensitivity testing (DST) of 13 anti-TB drugs and whole-genome sequencing (WGS) to analyze the risk factors of delayed conversion and the dynamics changes of drug resistance and genomics of Mycobacterium tuberculosis (MTB) during ATT. We found TSCPs have better treatment outcomes and whose initial isolates show lower levels of drug resistance. Clinical isolates of DSCPs showed dynamically changing of resistance phenotypes and intra-host heterogeneity. Single nucleotide polymorphism (SNP) profiles showed large differences between groups. The study provided insight into the bacteriological and genomic variation of delayed sputum conversion. It would be helpful for early indication of sputum conversion and guidance on ATT.

Clinical and Genomic Perspective of SARS CoV-2 Infection in Liver Disease Patients: A Single-Centre Retrospective Study.

The limited literature on the clinical course of COVID-19 among patients with underlying liver disease (LD) is available from India. The present study aimed to evaluate the clinical and mutational profile of SARS-CoV-2 among LD cases. This was a retrospective study including admitted LD cases in whom SARS-CoV-2 RT-PCR testing was performed. Complete demographic and clinical details were retrieved from Hospital Information System. Detailed mutational analysis was performed by comparing LD COVID-19 positive study group, i.e. LD-CoV(+) with COVID-19 positive outpatients without any underlying LD as control, i.e. NLD-CoV(+). Out of 232 enrolled LD cases, 137 (59.1%) were LD-CoV(+). LD cases with existing co-morbidities were affected more (P = 0.002) and had 2.29 times (OR 2.29, CI 95%, 1.25-4.29) higher odds of succumbing to COVID-19 (P = 0.006). On multivariate regression analysis, ascites (P = 0.05), severe COVID-19 pneumonia (P = 0.046), and an increased levels of bilirubin (P = 0.005) and alkaline phosphatase (P = 0.003) were found to be associated with adverse outcome in LD-CoV(+).On mutational analysis, we found certain differences between LD- and NLD-CoV(+) infected with Delta [LD- and NLD-CoV (+ /D)] and Omicron [LD- and NLD-CoV(+/O)]. More mutations were shared between LD- and NLD-CoV(+/O) compared to LD- and NLD-CoV(+/D). There were differences in prevalence of indel mutations specific to LD-CoV ( +) for both Delta and Omicron. Moreover, we also reported an interesting genic bias between LD- and NLD-CoV( +) in harbouring deleterious/tolerated mutations. To conclude, LD cases with comorbidities were affected more and had higher odds of mortality due to COVID-19. The definite difference between LD- and NLD-CoV(+) groups with respect to frequency of harboured mutations and an inherent genic bias between them is of noteworthy importance.

Legal Aspects of Food Security from the Perspective of Genetics and Genomics

The current state of the legal support of food security in Russia is examined from the perspective of genetics and genomics. From a comparison of conventional and legal ideas about food security, priorities are identified and foundational principles analyzed. In contrast to earlier periods, the topic of food independence as a component of food security has received higher priority in more recent legal acts. As part of a balanced approach to prohibitions, permissions, and the imposition of controls in food security in the Russian Federation, the development of national genetic and genomic technologies should be taken into account. Future prospects for the development of food security legislation in the Russian Federation are considered. A proposition to legally formalize the principles of state policy at the level of the federal law is presented.

Whole genome sequencing and analysis of Bacillus sp. TTMP2, a tetramethylpyrazine-producing bacterium.

Tetramethylpyrazine has been extensively studied as an anticancer substance and a flavor substance in the fields of medicine and food industry. A strain with high tetramethylpyrazine production was screened from the fermented grains of Danquan winery. Genome sequencing can reveal the potential roles of bacteria by thoroughly examining the connection between genes and phenotypes from a genomic perspective. In this study, whole genome of this strain was sequenced and analyzed. This paper summarized the genomic characteristics of strain TTMP2 and analyzed genes related to the synthesis of tetramethylpyrazine. Bacillus sp. TTMP2 has a complete metabolic pathway for acetoin and tetramethylpyrazine metabolism. Gene function was analyzed by COG annotation, GO annotation, KEGG annotation and functional annotations for lipoproteins, carbohydrate-active enzymes, and pathogen-host interactions. Phylogenetic analysis indicated that Bacillus velezensis had the high homology with Bacillus sp. TTMP2. Genomes of 16 Bacillus species cover all genes of Bacillus, suggesting that genus Bacillus has an open pan-genome and can survive in diverse environments. The analysis of genome sequencing data from Bacillus sp. TTMP2 showed that its metabolic characteristics could be deeply understood, indicating that this bacterium had a particular role in tetramethylpyrazine synthesis.

Estimation of genetic variation in vitiligo associated genes: Population genomics perspective

BackgroundVitiligo is an auto-immune progressive depigmentation disorder of the skin due to loss of melanocytes. Genetic risk is one of the important factors for development of vitiligo. Preponderance of vitiligo in certain ethnicities is known which can be analysed by understanding the distribution of allele frequencies across normal populations. Earlier GWAS identified 108 risk alleles for vitiligo in Europeans and East Asians. In this study, 64 of these risk alleles were used for analysing their enrichment and depletion across populations (1000 Genomes Project and IndiGen) with reference to 1000 Genomes dataset. Genetic risk scores were calculated and Fisher’s exact test was performed to understand statistical significance of their variation in each population with respect to 1000 Genomes dataset as reference. In addition to SNPs reported in GWAS, significant variation in allele frequencies of 1079 vitiligo-related genes were also analysed. Two-tailed Chi-square test and Bonferroni’s multiple adjustment values along with fixation index (≥ 0.5) and minimum allele frequency (≥ 0.05) were calculated and used to prioritise the variants based on pairwise comparison across populations.ResultsRisk alleles rs1043101 and rs10768122 belong to 3 prime UTR of glutamate receptor gene SLC1A2 are found to be highly enriched in the South Asian population when compared with the ‘global normal’ population. Intron variant rs4766578 (ATXN2) was found to be deleted in SAS, EAS and AFR and enriched in EUR and AMR1. This risk allele is found to be under positive selection in SAS, AMR1 and EUR. From the ancillary vitiligo gene list, nonsynonymous variant rs16891982 was found to be enriched in the European and the Admixed American populations and depleted in all others. rs2279238 and rs11039155 belonging to the LXR-α gene involved in regulation of metalloproteinase 2 and 9 (melanocyte precursors) were found to be associated with vitiligo in the North Indian population (in earlier study).ConclusionThe differential enrichment/depletion profile of the risk alleles provides insight into the underlying inter-population variations. This would provide clues towards prioritisation of SNPs associated with vitiligo thereby elucidating its preponderance in different ethnic groups.