Computational and artificial neural network based study of functional SNPs of human LEPR protein associated with reproductive function

Genetic polymorphisms are mostly associated with inherited diseases, detecting and analyzing the biological significance of functional single-nucleotide polymorphisms (SNPs) using wet laboratory experiments is an arduous task hence the computational analysis of putative SNPs is essential before conducting a study on a large population. SNP in the leptin receptor (LEPR) could result in the retention of intracellular signalling due to the structural and functional instability of the receptor causing abnormal reproductive function in human. In this first comprehensive computational analysis of LEPR gene mutation, we have identified and analyzed the functional consequence and structural significance of the SNPs in LEPR using recently developed several computational algorithms. Thirteen deleterious mutations such as W13C, S93G, I232R, Q307H, Y354C, E497A, Q571H, R612H, K656N, T690A, T699M V741M, and L760R were identified in the LEPR gene coding region. Backpropagation algorithm has been developed to forestall the deleterious nature of SNP and to validate the outcome of the tested computational tools. From ConSurf prediction three SNPs (Q571H, R612H, and T699M) were highly conserved on LEPR protein and the most deleterious variant R612H had one hydrogen bond abolished and severely reduced protein stability. Molecular docking suggested that the mutant (R612H) LEPR had lowest binding energy than native LEPR with the ligand molecule. Thus the energetically destructive changeover of ARG to HIS in R612H could possibly affect the LEPR protein structural stability and functional constancy due to interruption in the amino acid interactions and could result in reproductive disorders in human and increases the complication in obstetric and pregnancy outcome.     

Analysis of single nucleotide polymorphisms in three chromosomes of European sea bass Dicentrarchus labrax

Single nucleotide polymorphisms (SNPs) are believed to contain relevant information and have been therefore extensively used as genetic markers in population and conservation genetics, and molecular ecology studies. This study reports on the identification of potential SNPs in a diploid European sea bass Dicentrarchus labrax genome by using reference sequences from three assembled chromosomes and mapping all WGS datasets onto them (3× Sanger, 3× 454 and 20× SOLEXA). A total of 20,779 SNPs were identified over the 1469 gene loci and intergenic space analysed. Within chromosomes the occurrence of SNPs was the lowest in exons and higher in introns and intergenic regions, which may be explained by the fact, that coding regions are under strong selective pressure to maintain their biological function. The ratio of nonsynonymous to synonymous mutations was smaller than one for all the chromosomes, suggesting that most of deleterious nonsynonymous mutations were eliminated by negative selection. SNPs were not uniformly distributed over the chromosomes. Two chromosomes exhibited large regions with extremely low SNP density, which might represent homozygous regions in the diploid genome. The results of this study show how SNP detection can take profit from sequencing a single diploid individual, but also uncover the limits of such an approach. SNPs that have been identified will support marker development for genetic linkage mapping, population genetics and aquaculture related questions in general.     

In silico analysis of structural and functional consequences in p16INK4A by deleterious nsSNPs associated CDKN2A gene in malignant melanoma

In this study, we identified the most deleterious nsSNP in CDKN2A gene through structural and functional properties of its protein (p16INK4A) and investigated its binding affinity with cdk6. Out of 118 SNPs, 14 are nsSNPs in the coding region and 17 SNPs were found in the untranslated region (UTR). FastSNP suggested that 7 SNPs in the 5' UTR might change the protein expression levels. Sixty-four percent of nsSNPs are found to be damaged in PolyPhen server among the 14 nsSNPs investigated. With this effort, we modeled the mutant p16INK4A proteins based on these deleterious nsSNPs, out of which three nsSNPs associated p16INK4A had RMSD values of greater than 3.00 A with native protein. From a comparison of total energy of these three mutant proteins, we identified that the major mutation is from Aspartic acid to Tyrosine at the residue position of 84 of p16INK4A. Further, we compared the binding efficiency of both native and mutant p16INK4A with cdk6. We found that mutant p16INK4A has less binding affinity with cdk6 compared to native type. This is due to ten hydrogen bonds and eight salt bridges which exist between the native type and cdk6, whereas the mutant type makes only nine hydrogen bonds and five salt bridges with cdk6. Based on our investigation, we propose that the SNP with the ID rs11552822 could be the most deleterious nsSNP in CDKN2A gene, causing malignant melanoma, as it was well correlated with experimental studies carried out elsewhere.     

A catalog of neutral and deleterious polymorphism in yeast

The abundance and identity of functional variation segregating in natural populations is paramount to dissecting the molecular basis of quantitative traits as well as human genetic diseases. Genome sequencing of multiple organisms of the same species provides an efficient means of cataloging rearrangements, insertion, or deletion polymorphisms (InDels) and single-nucleotide polymorphisms (SNPs). While inbreeding depression and heterosis imply that a substantial amount of polymorphism is deleterious, distinguishing deleterious from neutral polymorphism remains a significant challenge. To identify deleterious and neutral DNA sequence variation within Saccharomyces cerevisiae, we sequenced the genome of a vineyard and oak tree strain and compared them to a reference genome. Among these three strains, 6% of the genome is variable, mostly attributable to variation in genome content that results from large InDels. Out of the 88,000 polymorphisms identified, 93% are SNPs and a small but significant fraction can be attributed to recent interspecific introgression and ectopic gene conversion. In comparison to the reference genome, there is substantial evidence for functional variation in gene content and structure that results from large InDels, frame-shifts, and polymorphic start and stop codons. Comparison of polymorphism to divergence reveals scant evidence for positive selection but an abundance of evidence for deleterious SNPs. We estimate that 12% of coding and 7% of noncoding SNPs are deleterious. Based on divergence among 11 yeast species, we identified 1,666 nonsynonymous SNPs that disrupt conserved amino acids and 1,863 noncoding SNPs that disrupt conserved noncoding motifs. The deleterious coding SNPs include those known to affect quantitative traits, and a subset of the deleterious noncoding SNPs occurs in the promoters of genes that show allele-specific expression, implying that some cis-regulatory SNPs are deleterious. Our results show that the genome sequences of both closely and distantly related species provide a means of identifying deleterious polymorphisms that disrupt functionally conserved coding and noncoding sequences.     

Computational refinement of functional single nucleotide polymorphisms associated with ATM gene

Background

Understanding and predicting molecular basis of disease is one of the major challenges in modern biology and medicine. SNPs associated with complex disorders can create, destroy, or modify protein coding sites. Single amino acid substitutions in the ATM gene are the most common forms of genetic variations that account for various forms of cancer. However, the extent to which SNPs interferes with the gene regulation and affects cancer susceptibility remains largely unknown.

Principal findings

We analyzed the deleterious nsSNPs associated with ATM gene based on different computational methods. An integrative scoring system and sequence conservation of amino acid residues was adapted for a priori nsSNP analysis of variants associated with cancer. We further extended our approach on SNPs that could potentially influence protein Post Translational Modifications in ATM gene.

Significance

In the lack of adequate prior reports on the possible deleterious effects of nsSNPs, we have systematically analyzed and characterized the functional variants in both coding and non coding region that can alter the expression and function of ATM gene. In silico characterization of nsSNPs affecting ATM gene function can aid in better understanding of genetic differences in disease susceptibility.     

Baldness and the androgen receptor: the AR polyglycine repeat polymorphism does not confer susceptibility to androgenetic alopecia

Androgenetic alopecia, or male pattern baldness, is a complex condition with a strong heritable component. In 2001, we published the first significant evidence of a genetic association between baldness and a synonymous coding SNP (rs6152) in the androgen receptor gene, AR. Recently, this finding was replicated in three independent studies, confirming an important role for AR in the baldness phenotype. In one such replication study, it was claimed that the causative variant underlying the association was likely to be the polyglycine (GGN) repeat polymorphism, one of two apparently functional triplet repeat polymorphisms located in the exon 1 transactivating domain of the gene. Here, we extend our original association finding and present comprehensive evidence from approximately 1,200 fathers and sons drawn from 703 families of the Victorian Family Heart Study, a general population Caucasian cohort, that neither exon 1 triplet repeat polymorphism is causative in this condition. Seventy-eight percent of fathers (531/683) and 30% of sons (157/520) were affected to some degree with AGA. We utilised statistical methods appropriate for the categorical nature of the phenotype and familial structure of the cohort, and determined that whilst SNP rs6152 was strongly associated with baldness (P < 0.0001), the GGN triplet repeat was not (P = 0.13). In the absence of any other known common functional coding variants, we argue that the causative variant is likely to be in the non-coding region, and yet to be identified. The identification of functional non-coding variants surrounding AR may have significance not only for baldness, but also for the many other complex conditions that have thus far been linked to AR.     

Prediction of a highly deleterious mutation E17K in AKT-1 gene: An in silico approach

The AKT1 (v-akt murine thymoma viral oncogene homologue 1) kinase is a member of most frequently activated proliferation and survival signaling pathway in cancer. Recently, hyperactivation of AKT1, due to functional point mutation in the pleckstrin homology (PH) domain of AKT1 gene, has been found to be associated with human colorectal, breast and ovarian cancer. Thus, considering its crucial role in cellular signaling pathway, a functional analysis of missense mutations of AKT1 gene was undertaken in this study. Twenty nine nsSNPs (non-synonymous single nucleotide polymorphism) within coding region of AKT1 gene were selected for our investigation and six SNPs were found to be deleterious by combinatorial predictions of various computational tools. RMSD values were calculated for the mutant models which predicted four substitutions (E17K, E319G, D32E and A255T) to be highly deleterious. The insight of the structural attribute was gained through analysis of, secondary structures, solvent accessibility and intermolecular hydrogen bond analysis which confirmed one missense mutation (E17K) to be highly deleterious nsSNPs. In conclusion, the investigated gene AKT1 has twenty nine SNPs in the coding region and through progressive analysis using different bioinformatics tools one highly deleterious SNP with rs121434592 was profiled. Thus, results of this study can pave a new platform to sort nsSNPs for several important regulatory genes that can be undertaken for the confirmation of their phenotype and their correlation with diseased status in case control studies.     

Exploring the structural and functional effect of pRB by significant nsSNP in the coding region of <Emphasis Type="Italic">RB1</Emphasis> gene causing retinoblastoma

In this study, we identified the most deleterious nsSNP in RB1 gene through structural and functional properties of its protein (pRB) and investigated its binding affinity with E2F-2. Out of 956 SNPs, we investigated 12 nsSNPs in coding region in which three of them (SNPids rs3092895, rs3092903 and rs3092905) are commonly found to be damaged by I-Mutant 2.0, SIFT and PolyPhen programs. With this effort, we modeled the mutant pRB proteins based on these deleterious nsSNPs. From a comparison of total energy, stabilizing residues and RMSD of these three mutant proteins with native pRB protein, we identified that the major mutation is from Glutamic acid to Glycine at the residue position of 746 of pRB. Further, we compared the binding efficiency of both native and mutant pRB (E746G) with E2F-2. We found that mutant pRB has less binding affinity with E2F-2 as compared to native type. This is due to sixteen hydrogen bonding and two salt bridges that exist between native type and E2F-2, whereas mutant type makes only thirteen hydrogen bonds and one salt bridge with E2F-2. Based on our investigation, we propose that the SNP with an id rs3092905 could be the most deleterious nsSNP in RB1 gene causing retinoblastoma.     

Exploring the structural and functional effect of pRB by significant nsSNP in the coding region of RB1 gene causing retinoblastoma

In this study,we identified the most deleterious nsSNP in RB1 gene through structural and functional properties of its protein (pRB) and investigated its binding affinity with E2F-2.Out of 956 SNPs,we investigated 12 nsSNPs in coding region in which three of them (SNPids rs3092895,rs3092903 and rs3092905) are commonly found to be damaged by I-Mutant 2.0,SIFT and PolyPhen programs.With this effort,we modeled the mutant pRB proteins based on these deleterious nsSNPs.From a comparison of total energy,stabilizing residues and RMSD of these three mutant proteins with native pRB protein,we identified that the major mutation is from Glutamic acid to Glycine at the residue position of 746 of pRB.Further,we compared the binding efficiency of both native and mutant pRB (E746G) with E2F-2.We found that mutant pRB has less binding affinity with E2F-2 as compared to native type.This is due to sixteen hydrogen bonding and two salt bridges that exist between native type and E2F-2,whereas mutant type makes only thirteen hydrogen bonds and one salt bridge with E2F-2.Based on our investigation,we propose that the SNP with an id rs3092905 could be the most deleterious nsSNP in RB1 gene causing retinoblastoma.     

Exploration of relationships between production and fertility traits in dairy cattle via association studies of SNPs within candidate genes derived by expression profiling

The objective of this work was to integrate findings from functional genomics studies with genome-wide association studies for fertility and production traits in dairy cattle. Association analyses of production and fertility traits with SNPs located within or close to 170 candidate genes derived from two gene expression studies and from the literature were performed. Data from 2294 Holstein bulls genotyped for 39557 SNPs were used. A total of 111 SNPs were located on chromosomal segments covered by a candidate gene. Allele substitution effects for each SNP were estimated using a mixed model with a fixed effect of marker and a random polygenic effect. Assumed covariance was derived either from marker or from pedigree information. Results from the analysis with the kinship matrix built from marker genotypes were more conservative than from the analysis with the pedigree-derived relationship matrix. From sixteen SNPs with significant effects on both classes of traits, ten provided evidence of an antagonistic relationship between productivity and fertility. However, we found four SNPs with favourable effects on fertility and on yield traits, one SNP with favourable effects on fertility and percentage traits, and one SNP with antagonistic effects on two fertility traits. While most quantitative genetic studies have proven genetic antagonisms between yield and functional traits, improvements in both production and functionality may be possible when focusing on a few relevant SNPs. Investigations combining input from quantitative genetics and functional genomics with association analysis may be applied for the identification of such SNPs.     

The ApoE gene of Alzheimer's disease (AD)

The ApoE gene responsible for the Alzheimer's disease has been examined to identify functional consequences of single-nucleotide polymorphisms (SNPs). Eighty-eight SNPs have been identified in the ApoE gene in which 31 are found to be nonsynonymous, 8 of them are coding synonymous, 33 are found to be in intron, and 3 are in untranslated region. The SNPs found in the untranslated region consisted of two SNPs from 5′ and one SNP from the 3′. Twenty-nine percent of the identified nsSNPs have been reported as damaging. In the analysis of SNPs in the UTR regions, it has been recognized that rs72654467 from 5′ and rs71673244 from 5′ and 3′ are responsible for the alteration in levels of expression. Both native and mutant protein structures were analyzed along with the stabilization residues. It has been concluded that among all SNPs of ApoE, the mutation in rs11542041 (R132S) has the most significant effect on functional variation.     

Structure analysis of deleterious nsSNPs in human PALB2 protein for functional inference

Partner and Localizer of BRCA2 or PALB2 is a typical tumor suppressor protein, that responds to DNA double stranded breaks through homologous recombination repair. Heterozygous mutations in PALB2 are known to contribute to the susceptibility of breast and ovarian cancer. However, there is no comprehensive study characterizing the structural and functional impacts of SNPs located in the PALB2 gene. Therefore, it is of interest to document a comprehensive analysis of coding and non-coding SNPs located at the PALB2 loci using in silico tools. The data for 1455 non-synonymous SNPs (nsSNPs) located in the PALB2 loci were retrieved from the dbSNP database. Comprehensive characterization of the SNPs using a combination of in silico tools such as SIFT, PROVEAN, PolyPhen, PANTHER, PhD-SNP, Pmut, MutPred 2.0 and SNAP-2, identified 28 functionally important SNPs. Among these, 16 nsSNPs were further selected for structural analysis using conservation profile and protein stability. The most deleterious nsSNPs were documented within the WD40 domain of PALB2. A general outline of the structural consequences of each variant was developed using the HOPE project data. These 16 mutant structures were further modelled using SWISS Model and three most damaging mutant models (rs78179744, rs180177123 and rs45525135) were identified. The non-coding SNPs in the 3'' UTR region of the PALB2 gene were analyzed for altered miRNA target sites. The comprehensive characterization of the coding and non-coding SNPs in the PALB2 locus has provided a list of damaging SNPs with potential disease association. Further validation through genetic association study will reveal their clinical significance.     

Investigation of a genome wide association signal for obesity: synthetic association and haplotype analyses at the melanocortin 4 receptor gene locus

Background

Independent genome-wide association studies (GWAS) showed an obesogenic effect of two single nucleotide polymorphisms (SNP; rs12970134 and rs17782313) more than 150 kb downstream of the melanocortin 4 receptor gene (MC4R). It is unclear if the SNPs directly influence MC4R function or expression, or if the SNPs are on a haplotype that predisposes to obesity or includes functionally relevant genetic variation (synthetic association). As both exist, functionally relevant mutations and polymorphisms in the MC4R coding region and a robust association downstream of the gene, MC4R is an ideal model to explore synthetic association.

Methodology/Principal Findings

We analyzed a genomic region (364.9 kb) encompassing the MC4R in GWAS data of 424 obesity trios (extremely obese child/adolescent and both parents). SNP rs12970134 showed the lowest p-value (p = 0.004; relative risk for the obesity effect allele: 1.37); conditional analyses on this SNP revealed that 7 of 78 analyzed SNPs provided independent signals (p≤0.05). These 8 SNPs were used to derive two-marker haplotypes. The three best (according to p-value) haplotype combinations were chosen for confirmation in 363 independent obesity trios. The confirmed obesity effect haplotype includes SNPs 3′ and 5′ of the MC4R. Including MC4R coding variants in a joint model had almost no impact on the effect size estimators expected under synthetic association.

Conclusions/Significance

A haplotype reaching from a region 5′ of the MC4R to a region at least 150 kb from the 3′ end of the gene showed a stronger association to obesity than single SNPs. Synthetic association analyses revealed that MC4R coding variants had almost no impact on the association signal. Carriers of the haplotype should be enriched for relevant mutations outside the MC4R coding region and could thus be used for re-sequencing approaches. Our data also underscore the problems underlying the identification of relevant mutations depicted by GWAS derived SNPs.     

Association of CNR1 and FAAH endocannabinoid gene polymorphisms with anorexia nervosa and bulimia nervosa: evidence for synergistic effects

Endocannabinoids modulate eating behavior; hence, endocannabinoid genes may contribute to the biological vulnerability to eating disorders. The rs1049353 (1359 G/A) single nucleotide polymorphism (SNP) of the gene coding the endocannabinoid CB1 receptor ( CNR1 ) and the rs324420 (cDNA 385C to A) SNP of the gene coding fatty acid amide hydrolase (FAAH), the major degrading enzyme of endocannabinoids, have been suggested to have functional effects on mature proteins. Therefore, we explored the possibility that those SNPs were associated to anorexia nervosa and/or bulimia nervosa. The distributions of the CNR1 1359 G/A SNP and of the FAAH cDNA 385C to A SNP were investigated in 134 patients with anorexia nervosa, 180 patients with bulimia nervosa and 148 normal weight healthy controls. Additive effects of the two SNPs in the genetic susceptibility to anorexia nervosa and bulimia nervosa were also tested. As compared to healthy controls, anorexic and bulimic patients showed significantly higher frequencies of the AG genotype and the A allele of the CNR1 1359 G/A SNP. Similarly, the AC genotype and the A allele of the FAAH cDNA 385C to A SNP were significantly more frequent in anorexic and bulimic individuals. A synergistic effect of the two SNPs was evident in anorexia nervosa but not in bulimia nervosa. Present findings show for the first time that the CNR1 1359 G/A SNP and the FAAH cDNA 385C to A SNP are significantly associated to anorexia nervosa and bulimia nervosa, and demonstrate a synergistic effect of the two SNPs in anorexia nervosa.     

Disease-driven detection of differential inherited SNP modules from SNP network

Detection of the synergetic effects between variants, such as single-nucleotide polymorphisms (SNPs), is crucial for understanding the genetic characters of complex diseases. Here, we proposed a two-step approach to detect differentially inherited SNP modules (synergetic SNP units) from a SNP network. First, SNP-SNP interactions are identified based on prior biological knowledge, such as their adjacency on the chromosome or degree of relatedness between the functional relationships of their genes. These interactions form SNP networks. Second, disease-risk SNP modules (or sub-networks) are prioritised by their differentially inherited properties in IBD (Identity by Descent) profiles of affected and unaffected sibpairs. The search process is driven by the disease information and follows the structure of a SNP network. Simulation studies have indicated that this approach achieves high accuracy and a low false-positive rate in the identification of known disease-susceptible SNPs. Applying this method to an alcoholism dataset, we found that flexible patterns of susceptible SNP combinations do play a role in complex diseases, and some known genes were detected through these risk SNP modules. One example is GRM7, a known alcoholism gene successfully detected by a SNP module comprised of two SNPs, but neither of the two SNPs was significantly associated with the disease in single-locus analysis. These identified genes are also enriched in some pathways associated with alcoholism, including the calcium signalling pathway, axon guidance and neuroactive ligand-receptor interaction. The integration of network biology and genetic analysis provides putative functional bridges between genetic variants and candidate genes or pathways, thereby providing new insight into the aetiology of complex diseases.