Prediction and Structural Comparison of Deleterious Coding Nonsynonymous Single Nucleotide Polymorphisms (nsSNPs) in Human LEP Gene Associated with Obesity

Rapid discrimination between deleterious and benign missense mutations in the CAGI 6 experiment

We describe the machine learning tool that we applied in the CAGI 6 experiment to predict whether single residue mutations in proteins are deleterious or benign. This tool was trained using only single sequences, i.e., without multiple sequence alignments or structural information. Instead, we used global characterizations of the protein sequence. Training and testing data for human gene mutations was obtained from ClinVar (ncbi.nlm.nih.gov/pub/ClinVar/), and for non-human gene mutations from Uniprot (www.uniprot.org). Testing was done on post-training data from ClinVar. This testing yielded high AUC and Matthews correlation coefficient (MCC) for well trained examples but low generalizability. For genes with either sparse or unbalanced training data, the prediction accuracy is poor. The resulting prediction server is available online at http://www.mamiris.com/Shoni.cagi6.

Exploring the rare variants associated with Type 2 Diabetes Mellitus in Indian population and its disease-drug association studies: an in-silico approach

The diversified eating habits and religious culture of Indian population may be one of the reasons they largely contribute to the global diabetes burden. In the present investigation, an in-silico approach was carried out to explore hub genes in the Indian population with Type 2 Diabetes Mellitus (T2DM) that are scantily reported in the GWAS catalogue and probable potential anti-diabetic drugs from plants. This computational approach unwrapped LEP (leptin) as the hub gene among 170 genes analyzed with 14 non-synonymous single nucleotide polymorphisms (nsSNPs) with MAF < 0.01. The mutation of the LEP gene leads to a decrease in leptin concentration, which increases the risk of obesity and T2DM. According to the DUET webserver, 11 of 14 mutations examined were found to destabilize the LEP protein. Among 14, four barely reported LEP variants rs781301976 (I45N), rs776443424 (S52F), rs200915360 (D76Y), and rs1191666811 (D162N) were unzipped to be associated with T2DM, which may be the probable potential drug targets. The virtual screening revealed Vescalagin as having the highest binding energy among 336 natural compounds. Molecular docking of Vescalagin depicted higher binding energy (-9.0 kcal/mol) against mutated LEP [rs200915360 (D76Y)] compared to wild (-8.9 kcal/mol) and LEP-Metformin complexes. The trajectory analysis of MD simulations revealed that Vescalagin was more effective than Metformin in stabilizing the system. The present study suggests that the associations of the investigated nsSNPs in LEP [rs200915360 (D76Y)] and others can be key factors in the predominant role of T2DM morbidity in the Indian population that can be used as potential markers and drug targets for T2DM therapeutics.Communicated by Ramaswamy H. Sarma.

Investigating the Influence of ANTXR2 Gene Mutations on Protective Antigen Binding for Heightened Anthrax Resistance

Bacillus anthracis is the bacterium responsible for causing the zoonotic disease called anthrax. The disease presents itself in different forms like gastrointestinal, inhalation, and cutaneous. Bacterial spores are tremendously adaptable, can persist for extended periods and occasionally endanger human health. The Anthrax Toxin Receptor-2 (ANTXR2) gene acts as membrane receptor and facilitates the entry of the anthrax toxin into host cells. Additionally, mutations in the ANTXR2 gene have been linked to various autoimmune diseases, including Hyaline Fibromatosis Syndrome (HFS), Ankylosing Spondylitis (AS), Juvenile Hyaline Fibromatosis (JHF), and Infantile Systemic Hyalinosis (ISH). This study delves into the genetic landscape of ANTXR2, aiming to comprehend its associations with diverse disorders, elucidate the impacts of its mutations, and pinpoint minimal non-pathogenic mutations capable of reducing the binding affinity of the ANTXR2 gene with the protective antigen. Recognizing the pivotal role of single-nucleotide polymorphisms (SNPs) in shaping genetic diversity, we conducted computational analyses to discern highly deleterious and tolerated non-synonymous SNPs (nsSNPs) in the ANTXR2 gene. The Mutpred2 server determined that the Arg465Trp alteration in the ANTXR2 gene leads to altered DNA binding (p = 0.22) with a probability of a deleterious mutation of 0.808; notably, among the identified deleterious SNPs, rs368288611 (Arg465Trp) stands out due to its significant impact on altering the DNA-binding ability of ANTXR2. We propose these SNPs as potential candidates for hypertension linked to the ANTXR2 gene, which is implicated in blood pressure regulation. Noteworthy among the tolerated substitutions is rs200536829 (Ala33Ser), recognized as less pathogenic; this highlights its potential as a valuable biomarker, potentially reducing side effects on the host while also reducing binding with the protective antigen protein. Investigating these SNPs holds the potential to correlate with several autoimmune disorders and mitigate the impact of anthrax disease in humans.

Discovering Deleterious Single Nucleotide Polymorphisms of Human AKT1 Oncogene: An In Silico Study

BACKGROUND

AKT1 is a serine/threonine kinase necessary for the mediation of apoptosis, angiogenesis, metabolism, and cell proliferation in both normal and cancerous cells. The mutations in the AKT1 gene have been associated with different types of cancer. Further, the AKT1 gene mutations are also reported to be associated with other diseases such as Proteus syndrome and Cowden syndromes. Hence, this study aims to identify the deleterious AKT1 missense SNPs and predict their effect on the function and structure of the AKT1 protein using various computational tools.

METHODS

Extensive in silico approaches were applied to identify deleterious SNPs of the human AKT1 gene and assessment of their impact on the function and structure of the AKT1 protein. The association of these highly deleterious missense SNPs with different forms of cancers was also analyzed. The in silico approach can help in reducing the cost and time required to identify SNPs associated with diseases.

RESULTS

In this study, 12 highly deleterious SNPs were identified which could affect the structure and function of the AKT1 protein. Out of the 12, four SNPs-namely, G157R, G159V, G336D, and H265Y-were predicted to be located at highly conserved residues. G157R could affect the ligand binding to the AKT1 protein. Another highly deleterious SNP, R273Q, was predicted to be associated with liver cancer.

CONCLUSIONS

This study can be useful for pharmacogenomics, molecular diagnosis of diseases, and developing inhibitors of the AKT1 oncogene.

Computational refinement identifies functional destructive single nucleotide polymorphisms associated with human retinoid X receptor gene

Alterations in the nuclear retinoid X receptor (RXRs) signalling have been implicated in neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, stroke, multiple sclerosis and glaucoma. Single nucleotide polymorphisms (SNPs) are the main cause underlying single nucleic acid variations which in turn determine heterogeneity within various populations. These genetic polymorphisms have been suggested to associate with various degenerative disorders in population-wide analysis. This bioinformatics study was designed to investigate, search, retrieve and identify deleterious SNPs which may affect the structure and function of various RXR isoforms through a computational and molecular modelling approach. Amongst the 1,813 retrieved SNPs several were found to be deleterious with rs140464195_G139R, rs368400425_R358W and rs368586400_L383F RXRα mutant variants being the most detrimental ones causing changes in the interatomic interactions and decreasing the flexibility of the mutant proteins. Molecular genetics analysis identified seven missense mutations in RXRα/β/γ isoforms. Two novel mutations SNP IDs (rs1588299621 and rs1057519958) were identified in RXRα isoform. We used several in silico prediction tools such as SIFT, PolyPhen, I-Mutant, Protein Variation Effect Analyzer (PROVEAN), PANTHER, SNP&Go, PhD-SNP and SNPeffect to predict pathogenicity and protein stability associated with RXR mutations. The structural assessment by DynaMut tool revealed that hydrogen bonds were affected along with hydrophobic and carbonyl interactions resulting in reduced flexibility at the mutated residue positions but ultimately stabilizing the molecule as a whole. Summarizing, analysis of the missense mutations in RXR isoforms showed a mix of conclusive and inconclusive genotype-phenotype correlations suggesting the use of sophisticated computational analysis tools for studying RXR variants.Communicated by Ramaswamy H. Sarma.

Screening of Pathogenic Missense Single Nucleotide Variants From LHPP Gene Associated With the Hepatocellular Carcinoma: An In silico Approach

LHPP gene encodes a phospholysine phosphohistidine inorganic pyrophosphate phosphatase, which functions as a tumor-suppressor protein. The tumor suppression by this protein has been confirmed in various cancers, including hepatocellular carcinoma (HCC). LHPP downregulation promotes cell growth and proliferation by modulating the PI3K/AKT signaling pathway. This study identifies potentially deleterious missense single nucleotide variants (SNVs) associated with the LHPP gene using multiple computational tools based on different algorithms. A total of 4 destabilizing mutants are identified as L22P, I212T, G227R, and G236R, from the conserved region of the phosphatase. The 3-dimensional (3D) modeling and structural comparison of variants with the native protein reveals significant structural and conformational variations after mutations, suggesting disruption in the function of phospholysine phosphohistidine inorganic pyrophosphate phosphatase. The identified mutations might, therefore, participate in the cause of HCC.

A Simulation Analysis and Screening of Deleterious Nonsynonymous Single Nucleotide Polymorphisms (nsSNPs) in Sheep LEP Gene

Leptin is a polypeptide hormone produced in the adipose tissue and governs many processes in the body. Recently, polymorphisms in the LEP gene revealed a significant change in body weight regulation, energy balance, food intake, and reproductive hormone secretion. This study considers its crucial role in the regulation of the economically important traits of sheep. Several computational tools, including SIFT, Predict SNP2, SNAP2, and PROVEAN, have been used to screen out the deleterious nsSNPs. Following the screening of 11 nsSNPs in the sheep genome, 5 nsSNPs, T86M (C → T), D98N (G → A), N136T (A → C), R142Q (G → A), and P157Q (C → A), were predicted to have a significant deleterious effect on the LEP protein function, leading to phenotypic difference. The analysis of proteins’ stability change due to amino acid substitution using the I-stable, SDM, and DynaMut consistently confirmed that three nsSNPs (T86M (C → T), D98N (G → A), and P157Q (C → A)) increased protein stability. It is suggested that these three nsSNPs may enhance the evolvability of LEP protein, which is vital for the evolutionary adaptation of sheep. Our findings demonstrate that the five nsSNPs reported in this study might be responsible for sheep’s structural and functional modifications of LEP protein. This is the first comprehensive report on the sheep LEP gene. It narrow downs the candidate nsSNPs for in vitro experiments to facilitate the development of reliable molecular markers for associated traits.

The investigation of nonsynonymous SNPs of human SLC6A4 gene associated with depression: An in silico approach

Genetic polymorphism of the SLC6A4 gene is associated with several behavioral disorders, including depression. Since studying the total nonsynonymous single nucleotide polymorphisms (nsSNPs) of the SLC6A4 gene at the population level is a difficult task, we aim to utilize in silico approach to detect the most deleterious nsSNPs of the SLC6A4 gene. In our study, 7 computational tools were used in the initial stage, including SIFT, Polyphen-2, PROVEAN, SNAP2, PhD-SNP, PANTHER, and SNPs&GO to find out the most damaging nsSNPs. In the second phase, we performed structural, functional, and stability analysis of SLC6A4 protein by popular computation tools, including I-Mutant 2.0 and MutPred2. Also, the ConSurf server was utilized to find the conserved region of the SLC6A4 protein to determine the relationship between these conserved regions with high-risk nsSNPs. Based on these analyses, 5 high-risk mutations of the SLC6A4 protein were selected. Then, we carried out comparative modeling by using the Robetta server and aligned the mutant protein model with the native protein structure. Later, we performed the post-translational modification and functional domain analysis of the SLC6A4 protein. This study concludes that Arginine → Tryptophan at position 79 and Arginine → Cysteine at position 104 are the two significant mutations in SLC6A4 protein which might play an essential role in causing diseases. Future studies should take these high-risk nsSNPs (rs1221448303, rs200953188) into consideration while exploring diseases related to the SLC6A4 gene. Besides, our research is the first-ever comprehensive in silico investigation of the SLC6A4 gene. Thus, the findings of this study could be beneficial for developing precision medicines against diseases caused by SLC6A4 malfunction. Furthermore, extensive wet-lab research and experiments on various model organisms might be helpful to investigate the precise role of these damaging nsSNPs of the SLC6A4 gene.

IRLnc: a novel functional noncoding RNA contributes to intramuscular fat deposition

Background

Intramuscular fat (IMF) is associated with meat quality and insulin resistance in animals. Research on genetic mechanism of IMF decomposition has positive meaning to pork quality and diseases such as obesity and type 2 diabetes treatment. In this study, an IMF trait segregation population was used to perform RNA sequencing and to analyze the joint or independent effects of genes and long intergenic non-coding RNAs (lincRNAs) on IMF.

Results

A total of 26 genes including six lincRNA genes show significantly different expression between high- and low-IMF pigs. Interesting, one lincRNA gene, named IMF related lincRNA (IRLnc) not only has a 292-bp conserved region in 100 vertebrates but also has conserved up and down stream genes (< 10 kb) in pig and humans. Real-time quantitative polymerase chain reaction (RT-qPCR) validation study indicated that nuclear receptor subfamily 4 group A member 3 (NR4A3) which located at the downstream of IRLnc has similar expression pattern with IRLnc. RNAi-mediated loss of function screens identified that IRLnc silencing could inhibit both of the RNA and protein expression of NR4A3. And the in-situ hybridization co-expression experiment indicates that IRLnc may directly binding to NR4A3. As the NR4A3 could regulate the catecholamine catabolism, which could affect insulin sensitivity, we inferred that IRLnc influence IMF decomposition by regulating the expression of NR4A3.

Conclusions

In conclusion, a novel functional noncoding variation named IRLnc has been found contribute to IMF by regulating the expression of NR4A3. These findings suggest novel mechanistic approach for treatment of insulin resistance in human beings and meat quality improvement in animal.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07349-5.

The Study of the Response of Fat Metabolism to Long-Term Energy Stress Based on Serum, Fatty Acid and Transcriptome Profiles in Yaks

Simple Summary

The serum, fatty acid and transcriptome profiles in the subcutaneous fat of yaks were measured to explore the effect of long-term energy stress (ES) on fat metabolism during the cold season. The study indicated that under long-term ES during the cold season, the amount of fat in yaks was less, and fat mobilization was one of the main ways by which energy was obtained in yaks. Yaks regulated fat metabolism in subcutaneous fat primarily through adenosine 5′-monophosphate-activated protein kinase (AMPK) signaling. Glucose (GLU) intake, fat catabolism, fatty acid synthesis and fatty acid oxidation in the subcutaneous fat of yaks were all inhibited, which resulted in the fat mobilization of yaks slowing as much as possible under long-term ES. In addition, the energy expenditures in fat cells were inhibited by regulating phosphatidylinositol 3’ -kinase (PI3K)-serine/threonine-protein kinase (Akt) andmammalian target of rapamycin (mTOR) signaling, and the limited energy obtained from GLU and fat was consumed by muscle and organs as much as possible. These factors led to an energy balance in yaks under long-term ES. The fat stored in yaks can be expended for as long as possible, and yaks can survive for as long as necessary under long-term ES.

Abstract

Long-term energy stress (ES) during the cold season is a serious problem for the breeding of yaks. In this paper, the response of fat metabolism in yaks to long-term ES during the cold season was studied. Gas chromatography (GC) analysis showed that the percentage of saturated fatty acids (SFAs) in the subcutaneous fat of the yaks in the ES group was 42.7%, which was less than the 56.6% in the CO group (p < 0.01) and the percentage of polyunsaturated unsaturated fatty acids (PUFAs) in the subcutaneous fat of the yaks in the ES group was 38.3%, which was more than the 26.0% in the CO group (p < 0.01). The serum analysis showed that fatty acid oxidation in yaks was increased under long-term ES. In the subcutaneous fat of yaks under long-term ES, the gene expression levels of glycerol-3-phosphate acyltransferase 4 (GPAT4), hormone-sensitive lipase (HSL), patatin-like phospholipase domain-containing protein 2 (PNPLA2), acyl-CoA dehydrogenase (ACAD), acyl-coenzyme A thioesterase 8 (ACOT8), facilitated glucose transporter (GLUT4), 3-oxoacyl-[acyl-carrier-protein] synthase (OXSM), oestradiol 17-beta-dehydrogenase 8 (HSD17B8) and malonate-Co-A ligase ACSF3 (ACSF3) were downregulated (q < 0.05), whereas the gene expression levels of aquaporin-7 (AQP7), long-chain-fatty-acid-CoA ligase (ACSL), elongation of very long chain fatty acids protein (ELOVL) and fatty acid desaturase 1 (FADS1) were upregulated (q < 0.05), indicating the inhibition of fat catabolism, fat anabolism, fatty acid oxidation, glucose (GLU) intake and SFA synthesis and the promotion of glycerinum (GLY) transportation and PUFA synthesis. Additional findings showed that the gene expression levels of leptin (LEP), adenosine 5′-monophosphate-activated protein kinase (AMPK) and phosphatidylinositol 3-kinase (PI3K) were upregulated (q < 0.05), whereas the gene expression levels of malonyl-CoA decarboxylase (MCD), sterol regulatory element-binding protein 1 (SREBF1), mammalian target of rapamycin (mTOR) and serine/threonine-protein kinase (AKT) were downregulated (q < 0.05), indicating that fat metabolism in the subcutaneous fat of yaks under ES was mainly regulated by AMPK signaling and mTOR and PI3K-AKT signaling were also involved. Energy consumption was inhibited in the subcutaneous fat itself. This study can provide a theoretical basis for the healthy breeding and genetic breeding of yaks.