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Introduction Cancers may be treated by selective targeting of the genes vital for their survival. A number of attempts have led to discovery of several genes essential for surviving of tumor cells of different types. In this work, we tried to analyze genes that were previously predicted to be essential for melanoma surviving. Here we present the results of transient siRNA-mediated knockdown of the four of such genes, namely, UNC45A, STK11IP, RHPN2 and ZNFX1, in melanoma cell line A375, then assayed the cells for their viability, proliferation and ability to migrate in vitro. In our study, the knockdown of the genes predicted as essential for melanoma survival does not lead to statistically significant changes in cell viability. On the other hand, for each of the studied genes, mobility assays showed that the knockdown of each of the target genes accelerates the speed of cells migrating. Possible explanation for such counterintuitive results may include insufficiency of the predicting computational models or the necessity of a multiplex knockdown of the genes. Aims To examine the hypothesis of essentiality of hypomutated genes for melanoma surviving we have performed knockdown of several genes in melanoma cell line and analyzed cell viability and their ability to migrate. Methods Knockdown was performed by siRNAs transfected by Metafectene PRO. The levels of mRNAs before and after knockdown were evaluated by RT-qPCR analysis. Cell viability and proliferation were assessed by MTT assay. Cell migration was assessed by wound healing assay. Results The knockdown of the genes predicted as essential for melanoma survival does not lead to statistically significant changes in cell viability. On the other hand, for each of the studied genes, mobility assays showed that the knockdown of each of the target genes accelerates the speed of cells migrating. Conclusion Our results do not confirm initial hypothesis that the genes predicted essential for melanoma survival as a matter of fact support the survival of melanoma cells.

Background Head-to-head comparison of BeadChip and WGS/WES genotyping techniques for their precision is far from straightforward. A tool for validation of high-throughput genotyping calls such as Sanger sequencing is neither scalable nor practical for large-scale DNA processing. Here we report a cross-validation analysis of genotyping calls obtained via Illumina GSA BeadChip and WGS (Illumina HiSeq X Ten) techniques. Results When compared to each other, the average precision and accuracy of BeadChip and WGS genotyping techniques exceeded 0.991 and 0.997, respectively. The average fraction of discordant variants for both platforms was found to be 0.639%. A sliding window approach was utilized to explore genomic regions not exceeding 500 bp encompassing a maximal amount of discordant variants for further validation by Sanger sequencing. Notably, 12 variants out of 26 located within eight identified regions were consistently discordant in related calls made by WGS and BeadChip. When Sanger sequenced, a total of 16 of these genotypes were successfully resolved, indicating that a precision of WGS and BeadChip genotyping for this genotype subset was at 0.81 and 0.5, respectively, with accuracy values of 0.87 and 0.61. Conclusions We conclude that WGS genotype calling exhibits higher overall precision within the selected variety of discordantly genotyped variants, though the amount of validated variants remained insufficient.

Despite the acceptance of NextGen sequencing as a diagnostic modality suitable for probands and carriers of Mendelian diseases, its efficiency in identifying causal mutations is limited by both technical aspects of variant call algorithms and by imperfect, consensus-based criteria for assessing the pathogenicity of the findings. Here we describe the medical history of the family with a child born with Fanconi anemia. In this case, typical diagnostic routines were complicated by unusual combination of mutations. PALB2 variant NM_024675.3:c.172_175delTTGT (p.Gln60Argfs) in maternal sample, previously classified as a definitely pathogenic frameshift mutation, was in compound heterozygous state with PALB2 NM_024675.3:c.3114-16_3114-11del (p.Asn1039Glyfs*7), which led to validated PALB2 exon 11 skipping event in paternal locus. Findings enabled the development of the PGТ and successful selection of two mutation-free embryos. We show that even in absence of definitive exome findings, clinician-guided research inquiries into the structure and function of the suspected loci allow definitive diagnosis. Described case provides an example of a crucial input of an investigational workflow in genetic prognosis and successful PGT.

ObjectivesDeciphering the genetic relationships between major depressive disorder (MDD) and atopic diseases (asthma, hay fever, and eczema) may facilitate understanding of their biological mechanisms as well as the development of novel treatment regimens. Here we tested the genetic correlation between MDD and atopic diseases by linkage disequilibrium score regression.MethodsA polygenic overlap analysis was performed to estimate shared genetic variations between the two diseases. Causal relationships between MDD and atopic diseases were investigated using two-sample bidirectional Mendelian randomization analysis. Genomic loci shared between MDD and atopic diseases were identified using cross-trait meta-analysis. Putative functional genes were evaluated by fine-mapping of transcriptome-wide associations.ResultsThe polygenic analysis revealed approximately 15.8 thousand variants causally influencing MDD and 0.9 thousand variants influencing atopic diseases. Among these variants, approximately 0.8 thousand were shared between the two diseases. Mendelian randomization analysis indicates that genetic liability to MDD has a causal effect on atopic diseases (b = 0.22, p = 1.76 × 10-6), while genetic liability to atopic diseases confers a weak causal effect on MDD (b = 0.05, p = 7.57 × 10-3). Cross-trait meta-analyses of MDD and atopic diseases identified 18 shared genomic loci. Both fine-mapping of transcriptome-wide associations and analysis of existing literature suggest the estrogen receptor β-encoding gene ESR2 as one of the potential risk factors for both MDD and atopic diseases.ConclusionOur findings reveal shared genetic liability and causal links between MDD and atopic diseases, which shed light on the phenotypic relationship between MDD and atopic diseases.

Major psychiatric traits are genetically inter-correlated with one another, but it not well known which genes play pleiotropic effects across different traits. We curated and compared genes identified from large-scale genome-wide association studies for seven psychiatric traits, including depression, bipolar disorder, schizophrenia, autism spectrum disorder, attention-deficit/hyperactivity disorder, anxiety and neuroticism. We then explored biological functions of the top pleiotropic genes. A total of 243 cross-trait genes were identified for the seven traits. Except for autism spectrum disorder, there was significant enrichment of overlapped genes across these psychiatric traits. Chromosome 5q14.3, 11q23.2, and 7p22.3 are the three genomic regions conferring highest pleiotropic effects for these psychiatric traits. The long non-coding gene LINC00461 showed the highest pleiotropic effects on five psychiatric traits. In silico and functional studies with mice support the vital role of LINC00461 in neurodevelopment. In sum, our study provides insights into the shared genetic liability among major psychiatric traits.

Deciphering the genetic relationships between major depressive disorder (MDD) and insomnia may facilitate understanding biological mechanisms as well as inform more effective treatment regimens for these conditions. Here, we attempted to investigate mechanisms underlying relationships between MDD and insomnia in the context of shared genetic variations. Shared genetic variation was evaluated by polygenic analysis. In two-sample bidirectional Mendelian randomization (MR) analysis, causal relationships between MDD and insomnia were investigated; the list of shared genomic loci was identified using cross-trait meta-analysis. Putatively causal genes for the two diseases were prioritized by fine-mapping of transcriptome-wide associations. Polygenic analysis identified 15.1 thousand variants as causally influencing MDD, and 10.8 thousand variants as influencing insomnia. Among these variants, 8.5 thousand were shared between the two diseases. MR analysis suggests that genetic liability to MDD and to insomnia have mutual causal effects [MDD on insomnia with odds ratio (OR) = 1.25 and insomnia on MDD with OR = 2.23]. Cross-trait meta-analyses identified 89 genomic loci as being shared between MDD and insomnia, with some of them being prioritized as causal in subsequent fine-mapping of transcriptome-wide association signals. Analysis highlights possible role of endogenous production of nitric oxide in the brain, and the gonadotropic secretion in the pituitary as possibly physiological connectors of MDD and insomnia. Here, we show a substantial shared genetic liability and mutual causal links between MDD and insomnia. Presented findings provide novel insight into phenotypic relationship between these two interconnected conditions.

We investigated the relationship between neuroticism and 16 mental and 18 physical traits using summary results of genome-wide association studies for these traits. LD score regression was used to investigate genetic correlations between neuroticism and the 34 health outcomes. Mendelian randomization was performed to investigate mutual causal relationships between neuroticism and the 34 health outcomes. Neuroticism genetically correlates with a majority of health-related traits and confers causal effects on 12 mental traits (major depressive disorder (MDD), insomnia, subjective well-being (SWB, negatively), schizophrenia, attention-deficit/hyperactivity disorder, alcohol dependence, loneliness, anorexia nervosa, anxiety disorder, bipolar disorder, obsessive-compulsive disorder, and psychiatric disorders) and two physical diseases (cardiovascular disease and hypertensive disease). Conversely, MDD, SWB, and insomnia have a causal effect on neuroticism. We highlighted key genes contributing to the causal associations between neuroticism and MDD, including RBFOX1, RERE, SOX5, and TCF4, and those contributing to the causal associations between neuroticism and cardiovascular diseases, including MAD1L1, ARNTL, RERE, and SOX6. The present study indicates that genetic variation mediates the causal influences of neuroticism on mental health and cardiovascular diseases.

Background: Schizophrenia (SZ) is a severe chronic mental disorder with complex genetic mechanisms. Brain-derived neurotrophic factor (BDNF) is one of promising candidate genes for SZ, and rs6265 is a non-synonymous single nucleotide polymorphism (SNP) in BDNF.Methods: In this study, we performed a case-control association study of rs6265 in a cohort of Han Chinese population from eastern China, including 1,407 SZ patients and 1,136 healthy controls; and carried out a cis-mQTL (Methylation Quantitative Trait Loci) analysis for BDNF rs6265.Results: We found a positive association of rs6265 with SZ (P = 0.037), with the minor allele (A) of rs6265 conferring a protecting effect for SZ (OR = 0.89). Furthermore, cis-mQTL analysis indicates that rs6265 is associated with several methylation loci surrounding BDNF.Conclusions: Together, our findings provide further evidence to support the involvement of BDNF gene in the genesis of SZ.

Background Major depressive disorder (MDD) and posttraumatic stress disorder (PTSD) are highly comorbid and exhibit strong correlations with one another. We aimed to investigate mechanisms of underlying relationships between PTSD and three kinds of depressive phenotypes, namely, MDD, depressed affect (DAF), and depression (DEP, including both MDD and the broad definition of depression). Methods Genetic correlations between PTSD and the depressive phenotypes were tested using linkage disequilibrium score regression. Polygenic overlap analysis was used to estimate shared and trait-specific causal variants across a pair of traits. Causal relationships between PTSD and the depressive phenotypes were investigated using Mendelian randomization. Shared genomic loci between PTSD and MDD were identified using cross-trait meta-analysis. Results Genetic correlations of PTSD with the depressive phenotypes were in the range of 0.71~0.80. The estimated numbers of causal variants were 14,565, 12,965, 10,565, and 4,986 for MDD, DEP, DAF, and PTSD, respectively. In each case, causal variants contributing to PTSD were completely or largely covered by causal variants defining each of the depressive phenotypes. Mendelian randomization analysis indicates that the genetically determined depressive phenotypes confer a causal effect on PTSD (b = 0.21~0.31). Notably, genetically determined PTSD confers a causal effect on DEP (b = 0.14) and DAF (b = 0.15), but not MDD. Cross-trait meta-analysis of MDD and PTSD identifies 47 genomic loci, including 29 loci shared between PTSD and MDD. Conclusion Evidence from shared genetics suggests that PTSD is a subtype of MDD. This study provides support to the efforts in reducing diagnostic heterogeneity in psychiatric nosology. Funding The National Key Research and Development Program of China (2018YFC1314300) and the National Natural Science Foundation of China (81471364 and 81971255).

Both Major depressive disorder (MDD) and insomnia are two common mental disorders. However, the inherent and comprehensive genetic factors causing the links between MDD and insomnia are unclear yet. Here, based on GWAS results for each disorder, we used linkage disequilibrium (LD) score regression analysis and a multi-single nucleotide polymorphism (SNP) Mendelian randomization (MR) analysis to test the genetic relationships between these two diseases. Genetic correlation analyses indicated that MDD has a significant genetic correlation with insomnia (correlation ratio = 0.40 ± 0.03, P = 1.12 × 10−52). Mendelian randomization analysis indicated that liability to MDD confers a causal effect on insomnia (bxy = 0.16 ± 0.02, P = 1.11 × 10−18), while liability to insomnia confers a causal effect on MDD (bxy = 0.57 ± 0.07, P = 1.17 × 10−14). We found that the transcription factor 4 (TCF4) gene may contribute to the mutual influences between MDD and insomnia. These results provide insights into the relationships between MDD and insomnia and may have implications for policy, planning, and provision of services.

Preeclampsia (PE) confers a significant risk for subsequent diagnosis with autism spectrum disorder (ASD), with the mechanisms underlying this observation being largely unknown. To identify molecular networks affected by both PE and ASD, we conducted a large-scale literature data mining and a gene set enrichment analysis (GSEA), followed by an expression mega-analysis in 13 independently profiled ASD datasets. Sets of genes implicated in ASD and in PE significantly overlap (156 common genes; p = 3.14E−67), with many biological pathways shared (94 pathways; p < 1.00E−21). A set of PE-driven molecular triggers possibly contributing to worsening the risk of subsequent ASD was identified, possibly representing a regulatory shift toward greater vulnerability to the development of ASD. Mega-analysis of expression highlighted RPS4Y1, an inhibitor of STAT3 that is expressed in a sexually dimorphic manner, as a contributor to both PE and ASD, which should be evaluated as a possible contributor to male predominance in ASD. A set of PE-driven molecular triggers may shift the developing brain toward a greater risk of ASD. One of these triggers, chromosome Y encoded gene RPS4Y1, an inhibitor of STAT3 signaling, warrants evaluation as a possible contributor to male predominance in ASD.

In Iran, esophageal cancer is the fourth common cancers in women and sixth common cancers in men. Here we evaluated the importance of familial risk factors and the role of genetic predisposition in Esophageal Squamous Cell Carcinoma (ESCC) using Whole-Exome Sequencing (WES). Germline damaging mutations were identified in WES data from 9 probands of 9 unrelated ESCC pedigrees. Mutations were confirmed with Sanger sequencing and evaluated amplification-refractory mutation system-Polymerase Chain Reaction (ARMS-PCR) in 50 non-related ethnically matched samples and in complete genomics database. Sixteen candidate variants were detected in ESCC 9 probands. Four of these 16 variants were rare damaging mutations including novel mutations in KCNJ12/KCNJ18, and GPRIN2 genes. This WES study in Iranian patients with ESCC, provides insight into the identification of novel germline mutations in familial ESCC. Our data suggest an association between specific mutations and increased risk of ESCC.

Background Cystic fibrosis (CF) is one of the most common life-threatening genetic disorders. Around 2000 variants in the CFTR gene have been identified, with some proportion known to be pathogenic and 300 disease-causing mutations have been characterized in detail by CFTR2 database, which complicates its analysis with conventional methods. Methods We conducted next-generation sequencing (NGS) in a cohort of 89 adult patients negative for p.Phe508del homozygosity. Complete clinical and demographic information were available for 84 patients. Results By combining MLPA with NGS, we identified disease-causing alleles in all the CF patients. Importantly, in 10% of cases, standard bioinformatics pipelines were inefficient in identifying causative mutations. Class IV-V mutations were observed in 38 (45%) cases, predominantly ones with pancreatic sufficient CF disease; rest of the patients had Class I-III mutations. Diabetes was seen only in patients homozygous for class I-III mutations. We found that 12% of the patients were heterozygous for more than two pathogenic CFTR mutations. Two patients were observed with p.[Arg1070Gln, Ser466*] complex allele which was associated with milder pulmonary obstructions (FVC 107 and 109% versus 67%, CI 95%: 63-72%; FEV 90 and 111% versus 47%, CI 95%: 37-48%). For the first time p.[Phe508del, Leu467Phe] complex allele was reported, observed in four patients (5%). Conclusion NGS can be a more information-gaining technology compared to standard methods. Combined with its equivalent diagnostic performance, it can therefore be implemented in the clinical practice, although careful validation is still required. Electronic supplementary material The online version of this article (10.1186/s12920-018-0328-z) contains supplementary material, which is available to authorized users.

Background The history of human populations occupying the plains and mountain ridges separating Europe from Asia has been eventful, as these natural obstacles were crossed westward by multiple waves of Turkic and Uralic-speaking migrants as well as eastward by Europeans. Unfortunately, the material records of history of this region are not dense enough to reconstruct details of population history. These considerations stimulate growing interest to obtain a genetic picture of the demographic history of migrations and admixture in Northern Eurasia. Results We genotyped and analyzed 1076 individuals from 30 populations with geographical coverage spanning from Baltic Sea to Baikal Lake. Our dense sampling allowed us to describe in detail the population structure, provide insight into genomic history of numerous European and Asian populations, and significantly increase quantity of genetic data available for modern populations in region of North Eurasia. Our study doubles the amount of genome-wide profiles available for this region. We detected unusually high amount of shared identical-by-descent (IBD) genomic segments between several Siberian populations, such as Khanty and Ket, providing evidence of genetic relatedness across vast geographic distances and between speakers of different language families. Additionally, we observed excessive IBD sharing between Khanty and Bashkir, a group of Turkic speakers from Southern Urals region. While adding some weight to the “Finno-Ugric” origin of Bashkir, our studies highlighted that the Bashkir genepool lacks the main “core”, being a multi-layered amalgamation of Turkic, Ugric, Finnish and Indo-European contributions, which points at intricacy of genetic interface between Turkic and Uralic populations. Comparison of the genetic structure of Siberian ethnicities and the geography of the region they inhabit point at existence of the “Great Siberian Vortex” directing genetic exchanges in populations across the Siberian part of Asia. Slavic speakers of Eastern Europe are, in general, very similar in their genetic composition. Ukrainians, Belarusians and Russians have almost identical proportions of Caucasus and Northern European components and have virtually no Asian influence. We capitalized on wide geographic span of our sampling to address intriguing question about the place of origin of Russian Starovers, an enigmatic Eastern Orthodox Old Believers religious group relocated to Siberia in seventeenth century. A comparative reAdmix analysis, complemented by IBD sharing, placed their roots in the region of the Northern European Plain, occupied by North Russians and Finno-Ugric Komi and Karelian people. Russians from Novosibirsk and Russian Starover exhibit ancestral proportions close to that of European Eastern Slavs, however, they also include between five to 10 % of Central Siberian ancestry, not present at this level in their European counterparts. Conclusions Our project has patched the hole in the genetic map of Eurasia: we demonstrated complexity of genetic structure of Northern Eurasians, existence of East-West and North-South genetic gradients, and assessed different inputs of ancient populations into modern populations. Electronic supplementary material The online version of this article (10.1186/s12863-017-0578-3) contains supplementary material, which is available to authorized users.

Gene set analysis (GSA) has become the common methodology for analyzing transcriptomics data. However, self-contained GSA techniques are rarely, if ever, used for proteomics data analysis. Here we present a self-contained proteome level GSA of four consensus molecular subtypes (CMSs) previously established by transcriptome dissection of colon carcinoma specimens. Despite notable difference in structure of proteomics and transcriptomics data, many pathway-wide characteristic features of CMSs found at the mRNA level were reproduced at the protein level. In particular, CMS1 features show heavy involvement of immune system as well as the pathways related to mismatch repair, DNA replication and functioning of proteasome, while CMS4 tumors upregulate complement pathway and proteins participating in epithelial-to-mesenchymal transition (EMT). In addition, protein level GSA yielded a set of novel observations visible at the proteome, but not at the transcriptome level, including possible involvement of major histocompatibility complex II (MHC-II) antigens in the known immunogenicity of CMS1 and a connection between cholesterol trafficking and the regulation of Integrin-linked kinase (ILK) in CMS3. Overall, this study proves utility of self-contained GSA approaches as a critical tool for analyzing proteomics data in general and dissecting protein-level molecular portraits of human tumors in particular. publishedVersion

The term ‘ancient DNA’ (aDNA) is coming of age, with over 1,200 hits in the PubMed database, beginning in the early 1980s with the studies of ‘molecular paleontology’. Rooted in cloning and limited sequencing of DNA from ancient remains during the pre-PCR era, the field has made incredible progress since the introduction of PCR and next-generation sequencing. Over the last decade, aDNA analysis ushered in a new era in genomics and became the method of choice for reconstructing the history of organisms, their biogeography, and migration routes, with applications in evolutionary biology, population genetics, archaeogenetics, paleo-epidemiology, and many other areas. This change was brought by development of new strategies for coping with the challenges in studying aDNA due to damage and fragmentation, scarce samples, significant historical gaps, and limited applicability of population genetics methods. In this review, we describe the state-of-the-art achievements in aDNA studies, with particular focus on human evolution and demographic history. We present the current experimental and theoretical procedures for handling and analysing highly degraded aDNA. We also review the challenges in the rapidly growing field of ancient epigenomics. Advancement of aDNA tools and methods signifies a new era in population genetics and evolutionary medicine research.

The lux-operon of the psychrophilic bioluminescent bacterium Aliivibrio logei is regulated by quorum sensing (QS). The key components of this system are LuxI, which catalyses synthesis of the autoinducer (AI), and LuxR, which activates transcription of the entire lux-operon. The lux-operon of A. logei contains two copies of the luxR gene: luxR1 and luxR2. In the present study, lux-operon sequence analysis from 16 strains of A. logei, isolated from cold habitats of the White, Baltic, Okhotsk and Bering seas, was carried out. Phylogenetic analysis showed that all isolated strains of A. logei have both copies of luxR genes which are homologous to luxR genes of the related Aliivibrio salmonicida. Evaluation of LuxR1 and LuxR2 activity showed that LuxR2 remains active at significantly lower concentrations of AI (10− 9 M) than LuxR1, which is active only at high AI concentrations (10− 6 M). As the QS response is already prominent at AI concentrations as low as 10− 8 to 10− 9 M, we conclude that LuxR2 is the main activator of the lux-operon of A. logei. The thermolabilities of LuxR1 and LuxR2 are similar and exceed that of LuxR of the mesophilic bacterium Aliivibrio fischeri. In contrast to LuxR2, LuxR1 is not a substrate of Lon protease and does not require the chaperonin GroEL/ES for its folding. This study expands our current understanding of QS regulation in A. logei as it implies differential regulation by LuxR1 and LuxR2 proteins.

Genotyping of cell-free DNA (cfDNA) in plasma samples has the potential to allow for a noninvasive assessment of tumor biology, avoiding the inherent shortcomings of tissue biopsy. Next generation sequencing (NGS), a leading technology for liquid biopsy analysis, continues to be hurdled with several major issues with cfDNA samples, including low cfDNA concentration and high fragmentation. In this study, by employing Ion Torrent PGM semiconductor technology, we performed a comparison between two multi-biomarker amplicon-based NGS panels characterized by a substantial difference in average amplicon length. In course of the analysis of the peripheral blood from 13 diagnostic non-small cell lung cancer patients, equivalence of two panels, in terms of overall diagnostic sensitivity and specificity was shown. A pairwise comparison of the allele frequencies for the same somatic variants obtained from the pairs of panel-specific amplicons, demonstrated an identical analytical sensitivity in range of 140 to 170 bp amplicons in size. Further regression analysis between amplicon length and its coverage, illustrated that NGS sequencing of plasma cfDNA equally tolerates amplicons with lengths in the range of 120 to 170 bp. To increase the sensitivity of mutation detection in cfDNA, we performed a computational analysis of the features associated with genome-wide nucleosome maps, evident from the data on the prevalence of cfDNA fragments of certain sizes and their fragmentation patterns. By leveraging the support vector machine-based machine learning approach, we showed that a combination of nucleosome map associated features with GC content, results in the increased accuracy of prediction of high inter-sample sequencing coverage variation (areas under the receiver operating curve: 0.75, 95% CI: 0.750-0.752 vs. 0.65, 95% CI: 0.63-0.67). Thus, nucleosome-guided fragmentation should be utilized as a guide to design amplicon-based NGS panels for the genotyping of cfDNA samples.

Certain types of DNA damage are known to accumulate with age. Here we present the quantitative data describing the extent of the spontaneous DNA damage in 144 SHK mice of various ages. In each animal, we assessed double strand breaks, single strand breaks and alkali-labile sites, as well as amounts of oxidized purines, oxidized pyrimidines and misincorporated uracils. In addition, overall levels of genome DNA methylation were evaluated. The amounts of oxidized pyrimidines were correlated with age in males only, while the amounts of double strand breaks (DSB) in DNA samples were correlated with age in females only (R=0.26; p0.035). No age-related accumulation of single-strand breaks (SSB) was observed. The hypomethylation of DNA was significant in aging females, but not in aging males. Various types of DNA damage were correlated to each other. In attempt to develop more stable indicator of age-dependent alterations in DNA, the DNA Damage Level Differential (DDLD) indices was developed for comet assaying of peripheral blood leukocytes. As expected, DDLD index was shown to be better correlated with age than any single quantitative measure reflecting certain type of DNA damage. A variability of effectiveness of various kinds of DNA repair in individual animals was larger than expected. This conclusion may have a substantial impact on subsequent studies of the mutagens and other kinds of environmental stressors in animal populations. Nor DDLD neither individual quantitative measures of DNA damage were capable of prediction post-sampling survival time.

Computational analysis of promoters is hindered by the complexity of their architecture. In less studied genomes with complex organization, false positive promoter predictions are common. Accurate identification of transcription start sites and core promoter regions remains an unsolved problem. In this paper, we present a comprehensive analysis of genomic features associated with promoters and show that probabilistic integrative algorithms-driven models allow accurate classification of DNA sequence into “promoters” and “non-promoters” even in absence of the full-length cDNA sequences. These models may be built upon the maps of the distributions of sequence polymorphisms, RNA sequencing reads on genomic DNA, methylated nucleotides, transcription factor binding sites, as well as relative frequencies of nucleotides and their combinations. Positional clustering of binding sites shows that the cells of Oryza sativa utilize three distinct classes of transcription factors: those that bind preferentially to the [-500,0] region (188 “promoter-specific” transcription factors), those that bind preferentially to the [0,500] region (282 “5′ UTR-specific” TFs), and 207 of the “promiscuous” transcription factors with little or no location preference with respect to TSS. For the most informative motifs, their positional preferences are conserved between dicots and monocots.

Background With 15,949 markers, the low-density Infinium QC Array-24 BeadChip enables linkage analysis, HLA haplotyping, fingerprinting, ethnicity determination, mitochondrial genome variations, blood groups and pharmacogenomics. It represents an attractive independent QC option for NGS-based diagnostic laboratories, and provides cost-efficient means for determining gender, ethnic ancestry, and sample kinships, that are important for data interpretation of NGS-based genetic tests. Methods We evaluated accuracy and reproducibility of Infinium QC genotyping calls by comparing them with genotyping data of the same samples from other genotyping platforms, whole genome/exome sequencing. Accuracy and robustness of determining gender, provenance, and kinships were assessed. Results Concordance of genotype calls between Infinium QC and other platforms was above 99%. Here we show that the chip’s ancestry informative markers are sufficient for ethnicity determination at continental and sometimes subcontinental levels, with assignment accuracy varying with the coverage for a particular region and ethnic groups. Mean accuracies of provenance prediction at a regional level were varied from 81% for Asia, to 89% for Americas, 86% for Africa, 97% for Oceania, 98% for Europe, and 100% for India. Mean accuracy of ethnicity assignment predictions was 63%. Pairwise concordances of AFR samples with the samples from any other super populations were the lowest (0.39–0.43), while the concordances within the same population were relatively high (0.55–0.61). For all populations except African, cross-population comparisons were similar in their concordance ranges to the range of within-population concordances (0.54–0.57). Gender determination was correct in all tested cases. Conclusions Our results indicate that the Infinium QC Array-24 chip is suitable for cost-efficient, independent QC assaying in the settings of an NGS-based molecular diagnostic laboratory; hence, we recommend its integration into the standard laboratory workflow. Low-density chips can provide sample-specific measures for variant call accuracy, prevent sample mix-ups, validate self-reported ethnicities, and detect consanguineous cases. Integration of low-density chips into QC procedures aids proper interpretation of candidate sequence variants. To enhance utility of this low-density chip, we recommend expansion of ADME and mitochondrial markers. Inexpensive Infinium-like low-density human chips have a potential to become a “Swiss army knife” among genotyping assays suitable for many applications requiring high-throughput assays. Electronic supplementary material The online version of this article (10.1186/s12920-017-0297-7) contains supplementary material, which is available to authorized users.

Esophageal squamous cell carcinoma is one of the deadliest of all the cancers. Its metastatic properties portend poor prognosis and high rate of recurrence. A more advanced method to identify new molecular biomarkers predicting disease prognosis can be whole exome sequencing. Here, we report the most effective genetic variants of the Notch signaling pathway in esophageal squamous cell carcinoma susceptibility by whole exome sequencing. We analyzed nine probands in unrelated familial esophageal squamous cell carcinoma pedigrees to identify candidate genes. Genomic DNA was extracted and whole exome sequencing performed to generate information about genetic variants in the coding regions. Bioinformatics software applications were utilized to exploit statistical algorithms to demonstrate protein structure and variants conservation. Polymorphic regions were excluded by false-positive investigations. Gene–gene interactions were analyzed for Notch signaling pathway candidates. We identified novel and damaging variants of the Notch signaling pathway through extensive pathway-oriented filtering and functional predictions, which led to the study of 27 candidate novel mutations in all nine patients. Detection of the trinucleotide repeat containing 6B gene mutation (a slice site alteration) in five of the nine probands, but not in any of the healthy samples, suggested that it may be a susceptibility factor for familial esophageal squamous cell carcinoma. Noticeably, 8 of 27 novel candidate gene mutations (e.g. epidermal growth factor, signal transducer and activator of transcription 3, MET) act in a cascade leading to cell survival and proliferation. Our results suggest that the trinucleotide repeat containing 6B mutation may be a candidate predisposing gene in esophageal squamous cell carcinoma. In addition, some of the Notch signaling pathway genetic mutations may act as key contributors to esophageal squamous cell carcinoma.

The generation of true random and pseudorandom control sequences is an important problem of computational biology. Available random sequence generators differ in underlying probabilistic models that often remain undisclosed to users. Random sequences produced by differing probabilistic models substantially differ in their outputs commonly used as baselines for evaluations of the motif frequencies. Moreover, modern bioinformatics studies often require generation of matching control transcriptome with emulated partitions into ORFs, 5- and 3-UTRs, as well as the proportion of non-coding RNAs within model transcriptome rather than relatively simple continuous control sequences. Here we describe novel random sequence generating tool RANDTRAN that accounts for the length distribution of 5′ and 3′ non-translated regions in given transcriptome and the partition-specific di- and trinucleotide compositions in translated and non-translated regions. RANDRAN presents matching control transcriptomes in ready-to-use UCSC genome browser-compatible input files. These features may be useful for generating of control sequence sets for common types of computational analysis of various sequence motifs within various sets of RNA. RANDTRAN is available for free download at http://www.generesearch.ru/images/Randtran.rar

As the use of next-generation sequencing (NGS) for the Mendelian diseases diagnosis is expanding, the performance of this method has to be improved in order to achieve higher quality. Typically, performance measures are considered to be designed in the context of each application and, therefore, account for a spectrum of clinically relevant variants. We present EphaGen, a new computational methodology for bioinformatics quality control (QC). Given a single NGS dataset in BAM format and a pre-compiled VCF-file of targeted clinically relevant variants it associates this dataset with a single arbiter parameter. Intrinsically, EphaGen estimates the probability to miss any variant from the defined spectrum within a particular NGS dataset. Such performance measure virtually resembles the diagnostic sensitivity of given NGS dataset. Here we present case studies of the use of EphaGen in context of BRCA1/2 and CFTR sequencing in a series of 14 runs across 43 blood samples and 504 publically available NGS datasets. EphaGen is superior to conventional bioinformatics metrics such as coverage depth and coverage uniformity. We recommend using this software as a QC step in NGS studies in the clinical context. Availability: https://github.com/m4merg/EphaGen or https://hub.docker.com/r/m4merg/ephagen.

The KCTD family includes tetramerization (T1) domain containing proteins with diverse biological effects. We identified a novel member of the KCTD family, BTBD10. A comprehensive analysis of protein-protein interactions (PPIs) allowed us to put forth a number of testable hypotheses concerning the biological functions for individual KCTD proteins. In particular, we predict that KCTD20 participates in the AKT-mTOR-p70 S6k signaling cascade, KCTD5 plays a role in cytokinesis in a NEK6 and ch-TOG-dependent manner, KCTD10 regulates the RhoA/RhoB pathway. Developmental regulator KCTD15 represses AP-2α and contributes to energy homeostasis by suppressing early adipogenesis. TNFAIP1-like KCTD proteins may participate in post-replication DNA repair through PCNA ubiquitination. KCTD12 may suppress the proliferation of gastrointestinal cells through interference with GABAb signaling. KCTD9 deserves experimental attention as the only eukaryotic protein with a DNA-like pentapeptide repeat domain. The value of manual curation of PPIs and analysis of existing high-throughput data should not be underestimated.

Background Visceral obesity and metabolic syndrome are commonly associated with non-alcoholic fatty liver disease (NAFLD). The progression of steatosis to NASH depends on a number of metabolic and patient-related factors. The mechanisms of genetic predisposition towards the development of NASH and related fibrosis remain unclear. In this study, our aim was to utilize mitotyping and identify mitochondrial haplotypes that may be associated with NAFLD. Methods We examined mitochondrial haplotypes along with patatin-like phospholipase domain containing 3 (PNPLA3) rs738409 genotype to determine their association with NAFLD phenotypes. Whole blood samples were obtained from 341 patients (BMI > 35) undergoing weight reduction surgery after written consent. Liver biopsies were centrally reviewed by a single pathologist based on predetermined pathologic protocol (41.9 % Non-NASH NAFLD, 30.4 % NASH, 27.5 % controls). A 1,122 bp of the mitochondrial control loop was sequenced for each sample and classified into haplogroups. Results The presence of haplogroup L exhibits protection against the development of NASH and pericellular fibrosis. The alleles of PNPLA3 locus showed differential distribution in cohorts with NAFLD, NASH and pericellular fibrosis. Heterozygosity at this locus is independently associated with higher risk of having NASH and pericellular fibrosis. Conclusion Mitochondrial genetics play an important role in NASH probably by modulation of oxidative stress and the efficiency of oxidative phosphorylation. Electronic supplementary material The online version of this article (doi:10.1186/s12881-016-0324-0) contains supplementary material, which is available to authorized users.

A selection of papers prepared by participants of 7th Young Scientists School SBB’15 is presented in three Supplementary Issues to the journals of BMC series, namely, BMC Genomics, BMC Genetics and BMC Microbiology. SBB’15 took place June 22nd-25th in Novosibirsk, Russia (http://conf.nsc.ru/sbb2015). The series of Young Scientists Schools in Systems Biology and Bioinformatics (SBB) started several years ago, in 2008, as educational workshop associated with the large international conference series on bioinformatics known as BGRS\SB (Bioinformatics of Genome Regulation and Structure\Systems Biology) (http://conf.bionet.nsc.ru/bgrssb2016). After its inauguration year of 1998, BGRS/SBB held biannually at the Institute of Cytology and Genetics SB RAS in Novosibirsk. In a recent decade, it became a prime meeting venue for biologists, computer scientists, physicists, mathematicians and biochemists working in an interdisciplinary field of systems biology and computer genomics. Being the largest system biology meeting series in Russia, BGRS\SB-14 attracted participants from 27 countries. In the past BioMedCentral had published series of special issues based on best materials presented at the conference in BMC Genomics (http://www.biomedcentral.com/bmcgenomics/supplements/15/S12), BMC Evolutionary Biology (http://www.biomedcentral.com/bmcevolbiol/supplements/15/S1), BMC Genetics (http://www.biomedcentral.com/bmcgenet/supplements/16/S1) and BMC Systems biology (http://www.biomedcentral.com/bmcsystbiol/supplements/9/S2). In addition, the protein structure related studies presented by BGRS/SBB participants were collated as special issues in Journal of Bioinformatics and Computational Biology (http://www.worldscientific.com/toc/jbcb/4113/01; http://www.worldscientific.com/toc/jbcb/11/01). [1] In addition, the SBB School series has its own history to be proud of. The first generation of its participants already matured enough to substantially advance in the field. A majority of the participants graduated with PhDs, and now are contributing to the school as the lecturers and to a number of world universities as professors. For some students, the conference became instrumental in obtaining their post-doc or first independent position in academic world. In many cases, the informal atmosphere of the school helped to spark a collaboration that later led to publications in leading journals or the dramatic changes in their science career. The Program Committee of the conference and SBB Schools series includes data analysis, bioinformatics and computational biology professionals from different countries. For the last decade, the SBB conference was co-chaired by Academician Prof. Nikolay A. Kolchanov of the Institute of Cytology and Genetics SB RAS, Russia and Prof. Dr. Ralf Hofestadt of Bielefeld University, Germany. System biology and bioinformatics are rapidly developing and wide fields of science knowledge. For Young Scientists Schools, every year is different as it comprises the topics for the trainings that are the hottest at the time of the event. In 2015, the SBB School concentrated on the modern genomics and an analysis of high-throughput sequencing data. The materials presented in the current special issue provide examples of seamless integration of experimental studies performed in the lab and the computer-assisted inquiries into in the complex patterns of the organization and the functioning of biologic systems at the molecular, cell, tissue, organ, and body levels. The scientific topics discussed in 2015 were presented at the following sections: Next generation sequencing (NGS) and data analysis Evolutionary bioinformatics Systems biology and gene network modeling In SBB’15 Supplements to BMC journals Genomics, we collected the best studies presented at the conference. Due to the general breadth of the field of Systems Biology and Bioinformatic, the manuscripts were accepted into three separate tracks, thus forming three Supplementary Issues, BMC Genomics, BMC Genetics and BMC Microbiology. Below we will describe contents of these issues.

Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in complex diseases like obesity and gastritis. However, variations in amount of starting material, enzymatic efficiency and presence of amplification inhibitors can lead to quantification errors. Hence, the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Human gastric tissue has been the least investigated for stability of reference gene expression. In this study, three popular algorithms, GeNorm, NormFinder and BestKeeper were used to evaluate the reference gene stability. Conclusion: HPRT1 and GAPDH are the best performing pair of reference genes for qRT-PCR profiling experiments involving non-malignant gastric tissue samples.

Non-alcoholic fatty liver disease (NAFLD) is a hepatic manifestation of metabolic syndrome and major cause of chronic liver disease in developed countries. Its prevalence is increasing in parallel with the prevalence of obesity and other components of the metabolic syndrome. As the liver is central to the clearance and catabolism of circulating advanced glycosylation end-products (AGEs), AGEs and their cognate receptors-RAGE (receptor for AGEs) system might be involved in NAFLD in obese patients. To examine this, we investigated four common polymorphisms of RAGE gene: 1704G/T (rs184003), G82S (rs2070600), -374T/A (rs1800624) and -429T/C (rs1800625) in 340 obese patients with metabolic syndrome. and protein levels of AGE and RAGE. This is the first study to describe association of 4 common polymorphisms with non-alcoholic steatohepatitis (NASH) as well as to examine protein levels of RAGE and AGE. Univariate analysis showed patients carrying the rs1800624 heterozygote genotype (AT) exhibited 2.36-fold increased risk of NASH (odds ratio (OR) = 2.36; 95% confidence interval (95% CI): 1.35-4.19) after adjusting for confounders. The minor allele -374 A has been shown to suppress the expression of RAGE protein. The protein levels of esRAGE, total sRAGE and AGE protein levels did not correlate with each other in obese patients with no liver disease, indicative of RAGE signaling playing an independent role in liver injury. In obese patients with non-NASH NAFLD and NASH respectively, esRAGE protein showed strong positive correlation with total sRAGE protein. Further, haplotype analysis of the 4 SNPs, indicated that haplotype G-A-T-G was significantly associated with 2-fold increased risk for NASH (OR = 2.08; 95% CI: 1.21-3.5; P = 0.006) after adjusting for confounders. In conclusion, the presented data indicate that the G-A-T-G haplotype containing minor allele at position -374 A and major allele at position -429T, 1704G, and G82S G could be regarded as a marker for NASH.

Melanin is a common pigment in animals. In humans, melanin is produced in melanocytes, in retinal pigment epithelium (RPE) cells, in the inner ear, and in the central nervous system. Previously, we noted that human adipose tissue expresses several melanogenesis-related genes. In the current study, we confirmed the expression of melanogenesis-related mRNAs and proteins in human adipose tissue using real-time polymerase chain reaction and immunohistochemical staining. TYR mRNA signals were also detected by in situ hybridization in visceral adipocytes. The presence of melanin in human adipose tissue was revealed both by Fontana-Masson staining and by permanganate degradation of melanin coupled with liquid chromatography/ultraviolet/mass spectrometry determination of the pyrrole-2,3,5-tricarboxylic acid (PTCA) derivative of melanin. We also compared melanogenic activities in adipose tissues and in other human tissues using the L-[U-14C] tyrosine assay. A marked heterogeneity in the melanogenic activities of individual adipose tissue extracts was noted. We hypothesize that the ectopic synthesis of melanin in obese adipose may serve as a compensatory mechanism that uses its anti-inflammatory and its oxidative damage-absorbing properties. In conclusion, our study demonstrates for the first time that the melanin biosynthesis pathway is functional in adipose tissue.—Randhawa, M., Huff, T., Valencia, J. C., Younossi, Z., Chandhoke, V., Hearing, V. J., Baranova, A. Evidence for the ectopic synthesis of melanin in human adipose tissue.

Subcutaneous and visceral adipose compartments act, not only as fatty acid depots, but also as active endocrine organs that undergo hyperplastic changes and significantly enhance their function in obesity. Adipokines and other proteins secreted by both adipocytes and stromal cells play a central role in peripheral insulin resistance and the metabolic syndrome (MS). Minor alleles of the adipokine genes substantially contribute to MS. The most important consequence of MS is low-level systemic inflammation supported by adiposespecific synthesis of proinflammatory soluble molecules. Proinflammatory signals are secreted into the bloodstream and spread to peripheral tissues that express their receptors. The signals provided by adipose tissue stimulate the development of secondary complications of MS, including cardiovascular disorders (CVDs) and nonalcoholic fatty liver disease. The review describes the physiological effects of adiponectin, leptin, resistin, visfatin, and apelin and the influence of the minor alleles of the adipokine genes on the development of the secondary complications of MS.