Drosophila remains a popular model for investigating the mechanisms of steroid action in eukaryotes. The ecdysone receptor EcR can effectively bind ecdysone-response elements with or without the presence of a hormone. For years, EcR enhancers were thought to respond to ecdysone via recruiting coactivator complexes, which replace corepressors and stimulate transcription. However, the exact mechanism of transcription activation by ecdysone remains unclear. Here, we present experimental data on 11 various coregulators at ecdysone-responsive loci of Drosophila S2 cells. We describe the regulatory elements where coregulators reside within these loci and assess changes in their binding levels following 20-hydroxyecdysone treatment. In the current study, we detected the presence of some coregulators at the TSSs (active and inactive) and boundaries marked with CP190 rather than enhancers of the ecdysone-responsive loci where EcR binds. We observed minor changes in the coregulators’ binding level. Most were present at inducible loci before and after 20-hydroxyecdysone treatment. Our findings suggest that: (1) coregulators can activate a particular TSS operating from some distal region ; (2) coregulators are not recruited after 20-hydroxyecdysone treatment to the responsive loci; rather, their functional activity changes (shown as an increase in H3K27 acetylation marks generated by CBP/p300/Nejire acetyltransferase). Taken together, our findings imply that the 20-hydroxyecdysone signal enhances the functional activity of coregulators rather than promoting their binding to regulatory regions during the ecdysone response.Ecdysone signaling in  Drosophila 20-hydroxyecdysone (further referred to as ecdysone) hormone have been a subject of interest to many researchers. Ecdysone signaling is the best described and simplest system of steroid action; therefore, it is an ideal experimental model.For many years, mechanisms of transcriptional activation by the Drosophila salivary glands corroborated the presence of the ecdysone receptor (EcR) in the nucleus, even in the absence of ecdysone ,3510,35]EcR peaks (EcR-bound enhancers) demonstrated an increase in the CBP/p300/Nejire binding level, but it did not exceed two times B. ConverCompared with EcR peaks, STARR-Seq peaks demonstrated a substantial increase in the binding levels of FLAG-EcR and CBP/p300/Nejire after 20-hydroxyecdysone treatment . The nateip74ef locus confirms our conclusions from analyzing the averaged plots . Interestingly, the highest Rpb3 peak inside the eip74ef loci was located at the TSS of the transcript, which was not induced by 20-hydroxyecdysone. Moreover, the uninduced eip74ef promoter also had EcR and CBP/p300/Nejire peaks proximal to TSS. The only difference between the chromatin context of the surrounding uninducible TSS and the inducible one was a lower level of H3K27Ac modification.A close examination of the ChIP-Seq tracks at the individual ed plots C,D. The dhr3 and hr4 genes by 20-hydroxyecdysone treatment in S2 cells [Previously, we reported the functional significance of chromatin remodelers for adequately inducing S2 cells . HoweverS2 cells . SignifiDespite detecting the presence of Brm and CHD1 at the TSSs of ecdysone-inducible genes in significant amounts, we did not observe a substantial increase in their binding level after a 1 h 20-hydroxyecdysone treatment of S2 cells A. EcR-boeip74ef locus had a better colocalization of Brm and CHD1 with TSSs than EcR-bound peaks/enhancers  within 86 loci induced in S2 cells by 20-hydroxyecdysone (To demonstrate that the ecdysone .eip74ef).Our findings show the presence of Brm, CHD1, and KisL remodelers within ecdysone-responsive loci in S2 cells before and after hormone treatment. The binding levels of the remodelers demonstrate only minor changes upon 20-hydroxyecdysone induction. The highest amounts of remodelers were present at the TSSs (Brm and CHD1), EcR-bound enhancers (KisL), and CP190-rich boundaries (CHD1). Significant remodeler enrichment was demonstrated by the TSSs of silent and uninducible transcripts , we observed mild changes in binding levels after 20-hydroxyecdysone treatment. Nevertheless, we admit that these minor changes may carry functional significance. In the case of the ecdysone response, mild changes in the coregulators’ binding levels affect several enhancers that form the clusters controlling the transcriptional status of individual ecdysone-dependent genes, as described previously . SynchroDrosophila loci. In this case, exposure to ecdysone may disrupt this interaction by removing CtBP and, consequently, stimulate CBP/p300/Nejire acetyltransferase activity. An alternative possibility is the simultaneous binding of inactive ecdysone-responsive loci by enzymes with opposing activities regarding H3K27Ac modification, namely, CBP/p300/Nejire acetyltransferase and Rpd3/HDAC1 deacetylase (a previously described repressor of ecdysone-inducible genes) [Drosophila modifier [It is worth noting that we detected a substantial increase in H3K27Ac modification at the EcR-bound enhancers upon induction with 20-hydroxyecdysone. Considering that CBP/p300/Nejire is stably present at the EcR-bound enhancers, this finding suggests CBP/p300/Nejire recruitment in a functionally inactive state (or “paused state”). Our data suggest that an increase in the ecdysone titer can stimulate CBP/p300/Nejire activity on regulatory elements of the genome. For now, we have considered three ways of implementing this. First, it is known that human CtBP can directly interact with p300 and inhibit its acetyltransferase activity ,48. We be genes) ,50. In te genes) ) or covamodifier ,53.Chromatin binding by coregulators in a functionally inactive state has found indirect confirmation in studies that split chromatin into various functional subtypes (chromatin colors). The first studies aimed at dividing genome regions into functional subtypes and relied more on the state of histones and their modifications than on the presence of particular coregulatory proteins . This apDrosophila Schneider cell line 2 (S2) cells were maintained at 25 °C in ecdysone-free Schneider’s insect medium  containing 10% FBS . The treatment of S2 cells with 20-hydroxyecdysone (20E)  was performed at a final concentration of 0.3 μM, as was described previously [eviously . Our appDrosophila genome assembly dm6 using HISAT2 [Drosophila genome and was provided as a grey transparent area at the averaged plots.The chromatin immunoprecipitation (ChIP) and ChIP-MNase seq were performed and analyzed exactly as previously described ,35,57. Cg HISAT2  and filtg HISAT2 . BigWig g HISAT2 . The finDrosophila cells after 1 h of treatment with 20-hydroxyecdysone was selected using previously described RNA-Seq data (GEO Series GSE156847) [Drosophila cells. Next, we selected only transcripts whose genomic loci have EcR peaks in S2 untreated cells (FLAG-EcR ChIP-Seq and FLAG-EcR peaks were previously reported by our group) [A set of primary transcripts induced in S2 E156847) ,11. Firsr group) . The resDrosophila S2 cells with our list of 86 loci that are primarily respondent to ecdysone  and genomic loci of 86 transcripts induced by 20-hydroxyecdysone. We included +/−5 kb regions encompassing the loci but excluded all TSS regions   were obtained with coordinates of the hsp70 gene induced by heat shock [Rabbit polyclonal antibodies against Rpb3 (1–275 aa), Brm (1513–1646 aa), CBP/p300/Nejire 125–310 aa), KisL (1150–1314 aa), CHD1 (1420–1651 aa), DART1 (1–100 aa), dSet1 (1–103 aa), lid/Kdm5 (1–165 aa), Gcn5 (349–813 aa), Spt5 (917–1117 aa), PAF1 (1–234 aa), and cdk8 (293–394 aa) were obtained and described previously in our lab  aa, KisL. All antat shock . Antibod


Phospholipase A and acyltransferase (PLAAT) 4 is a class II tumor suppressor with phospholipid metabolizing abilities. It was characterized in late 2000s, and has since been referred to as ‘tazarotene-induced gene 3’ (TIG3) or ‘retinoic acid receptor responder 3’ (RARRES3) as a key downstream effector of retinoic acid signaling. Two decades of research have revealed the complexity of its function and regulatory roles in suppressing tumorigenesis. However, more recent findings have also identified PLAAT4 as a key anti-microbial effector enzyme acting downstream of interferon regulatory factor 1 (IRF1) and interferons (IFNs), favoring protection from virus and parasite infections. Unveiling the molecular mechanisms underlying its action may thus open new therapeutic avenues for the treatment of both cancer and infectious diseases. Herein, we aim to summarize a brief history of PLAAT4 discovery, its transcriptional regulation, and the potential mechanisms in tumor prevention and anti-pathogen defense, and discuss potential future directions of PLAAT4 research toward the development of therapeutic approaches targeting this enzyme with pleiotropic functions. Vitamin A (retinol), an essential fat-soluble nutrient widely present in the diet, is vital for human health and embryonic development , 2. The TIG3, also referred to as RA receptor responder 3 (RARRES3), retinoid-inducible gene 1 (RIG1) or H-Ras-like suppressor 4 (HRASLS4), was first identified in 1998 from tazarotene-stimulated primary human keratinocytes –13. NotaSince its discovery, over two decades of research have unveiled the molecular mechanisms underlying PLAAT4-mediated restriction of tumor development and progression. More recently, the anti-pathogen properties of PLAAT4 have come to light, expanding its focus from cancer biology to anti-pathogen defense mechanisms , 17. In In early studies, PLAAT4 was shown to share significant homology with another class II tumor suppressor − H-REV 107 (most well known as PLA2G16/HRASLS3/PLAAT3 among other names) , 19. Thein vitro Ca2+-independent phospholipase A1/2 and acyltransferase activities, and are thus capable of catalyzing several reactions in phospholipid metabolism (2+-dependent N-acyltransferase (Ca-NAT)  family, the representative member of vertebrate NlpC/P60 protein superfamily . Given ttabolism , 23, 24.(Ca-NAT) –28. ThesThe catalytic activity of PLAAT4 depends on a 134 amino-acid hydrophilic region at the N-terminus. It shares several common features with LRAT as well as all other PLAATs, among which a highly conserved ‘NCEHFV’ motif is particularly prominent, with the conserved cysteine being identified as the active site catalytic nucleophile . AccordiPLAAT4 has a 30 amino-acid hydrophobic transmembrane domain following the N-terminal catalytic domain , 33. DesApart from the membrane system, PLAAT4 also distributes at the centrosome in skin cancer cells, leading to pericentrosomal organelle accumulation which in turn drives cancer cell apoptosis . A 24-amPLAAT4 gene is expressed ubiquitously in human cells, implying a tissue-wide protective role of its product. In addition, PLAAT4 transcription is readily induced by retinoic acids and its natural and synthetic analogues, DNA-damaging stimuli, as well as interferons (IFNs), the secreted cytokines that orchestrate the induction of IFN-stimulated genes (ISGs) to establish an anti-pathogen state (discussed below)  , 41, 42.ogenesis Figure 2PLAAT4 promoter contains the binding sites for transcription factors that constitutively activate PLAAT4 transcription to exert a protective role at the basal level  is also present at low basal levels in the nucleus where it manifests anti-oncogenic and anti-pathogen activities through maintaining optimal constitutive expression of hundreds of target genes, including PLAAT4 , the hexanucleotide units with a core ‘GAAA’ sequence which are recognized specifically by the N-terminal DNA-binding domains from all IRF family members  is among the most frequently mutated genes in cancer, and the majority of tumor-derived mutations occurs in the region encoding DNA binding domain of p53 . This does not necessarily suggest that p53 plays a dominant role in driving PLAAT4 transcription. In fact, PLAAT4 is abundantly expressed in T antigen-transformed cell lines in which p53 function is inactivated. Hence, while both IRF1 and p53 are key regulators of PLAAT4 transcription, p53 likely activates a much broader anti-tumor transcriptional spectrum than IRF1.It has long been noted that at the heart of tumorigenesis and progression lies genetic mutations disrupting the harmonious checks and balances of normal cellular growth and development. In this context, n of p53 . This reB5, etc. –54. Likes region . Consistf tumors , 56–58. elopment . Rather,PLAAT4 is markedly induced by RA and its analogues, the biological effects of which are transduced through RA receptors (RARs) and retinoid X receptors (RXRs) as RAR-RXR heterodimers (via binding to a series of RA response elements (RAREs) that typically consist of hexameric direct repeats of (A/G)G(T/G)TCA with either a two (DR2) or five (DR5) nucleotide spacer  (Expression of rodimers –63. Theye spacer –67. In at point) , 41. Intt point) , 68.PLAAT4 transcript and its protein product in human hepatoma HepG2 cells is robustly stimulated by DNA-damaging agents including 5-fluorouracil and UV irradiation , it should be noted that p53 plays an absolutely dominant role in activating PLAAT4 transcription in HepG2 cells treated with DNA damage agents  that depend mainly on the specific binding of IFN-stimulated gene factor 3 (ISGF3) heterotrimeric complex and STAT1 homodimer  to IFN-stimulated response element (ISRE) and gamma-activated sequence (GAS), respectively  in HtTA cervical cancer cells ) tissues than in ER-, PR- and ER/PR-negative tissues, hence providing a biomarker to identify a subgroup of patients with higher susceptibility to lung metastasis  that is involved in the development of various types of tumors, preventing MTDH from activating the cytoplasm-nuclear translocation of β-Catenin, whereby leading to suppression of the metastasis of colorectal cancer (a.k.a. L-PGDS), a member of the lipocalin superfamily that has been shown to be involved in the tumorigenesis of solid tumors , a notoriously stealthy picornavirus causing acute hepatitis in humans   . The antgonidii) . Thus, iIt is currently unknown the detailed mechanisms underlying anti-pathogen activity of PLAAT4. Nevertheless, the catalytic activity of PLAAT4 mediates induction of p70 S6 kinase phosphorylation at Thr389 and subsequent phosphorylation of mechanistic/mammalian target of rapamycin (mTOR) at Ser2448 that inactivates mTOR activity to phosphorylate 4E-BP1 in immortalized human hepatocytes . The funPicornaviridae family, it distinguishes itself from other mammalian picornaviruses in the capsid structure, genome organization and replication cycle , it is rarely mutated or deleted , 160. ThPLAAT4 exhibits a time- and concentration-dependent expression pattern in response to ATRA, similar to IFNs that also play functional roles in anti-cancer immunity  and anti-pathogen (IFNs and IRF1) functions, thereby reinforcing both stress response and immunity. Given the numerous interacting proteins identified with PLAAT4, it could serve as a potential multiplex switch, fine-tuning key pathways to ensure an adequate response, or otherwise triggering signaling processes that favor apoptotic cell death.PLAAT4 transcription program is activated? What signals stimulate translocation of the membrane-localized PLAAT4 to other subcellular sites (e.g. centrosome) to transduce functional signals? What are the specific functions of endoplasmic reticulum-localized PLAAT4? Whether PLAAT4 regulates mTOR-dependent and independent autophagy and/or apoptosis in pathogen-infected cells? Understanding a comprehensive picture of PLAAT4 would open new avenues of PLAAT4 regulome that could impact biological events other than protection against cancers and pathogens. In addition to PLAAT4 itself, it would be important to clarify how its metabolite NAPE and changes in the host lipidome regulate the protein-protein interactions. It also remains to be determined whether PLAAT family proteins with similar biochemical features play redundant roles in protection from both invading pathogens and tumorigenesis. This is particularly important in understanding what cellular mechanisms may compensate for the lack of PLAAT4 orthologs in rodents.Since it has just begun to appreciate the roles for PLAAT4 in the restriction of tumors and pathogen infections, several important gaps have remained in terms of mechanistic understanding of its function. For example, are there any other contexts where a In summary, PLAAT4 research, while still in its infancy, has just begun to be emerged as an important field with relevance to host immunity to infection and disease progression. Although more investigations are required to answer above questions, further understanding of the molecular details of the PLAAT4 action would contribute to the development of more effective therapeutic approaches to treat tumors and pathogen infections.All authors contributed to conception of the topic. HF and J-YZ wrote the original paper and prepared the figures. DY provided intellectual input and wrote the paper. X-KY, R-ZL, L-XW and WG provided intellectual input. All authors contributed to the article and approved the submitted version.


Single nucleotide polymorphisms (SNPs) are the most common type of variation in the human genome. The vast majority of SNPs identified in the human genome do not have any effect on the phenotype; however, some can lead to changes in the function of a gene or the level of its expression. Most SNPs associated with certain traits or pathologies are mapped to regulatory regions of the genome and affect gene expression by changing transcription factor binding sites. In recent decades, substantial effort has been invested in searching for such regulatory SNPs (rSNPs) and understanding the mechanisms by which they lead to phenotypic differences, primarily to individual differences in susceptibility to diseases and in sensitivity to drugs. The development of the NGS (next-generation sequencing) technology has contributed not only to the identification of a huge number of SNPs and to the search for their association  with certain diseases or phenotypic manifestations, but also to the development of more productive approaches to their functional annotation. It should be noted that the presence of an association does not allow one to identify a functional, truly disease-associated DNA sequence variant among multiple marker SNPs that are detected due to linkage disequilibrium. Moreover, determination of associations of genetic variants with a disease does not provide information about the functionality of these variants, which is necessary to elucidate the molecular mechanisms of the development of pathology and to design effective methods for its treatment and prevention. In this regard, the functional analysis of SNPs annotated in the GWAS catalog, both at the genome-wide level and at the level of individual SNPs, became especially relevant in recent years. A genome-wide search for potential rSNPs is possible without any prior knowledge of their association with a trait. Thus, mapping expression quantitative trait loci (eQTLs) makes it possible to identify an SNP for which – among transcriptomes of homozygotes and heterozygotes for its various alleles – there are differences in the expression level of certain genes, which can be located at various distances from the SNP. To predict rSNPs, approaches based on searches for allele-specific events in RNA-seq, ChIP-seq, DNase-seq, ATAC-seq, MPRA, and other data are also used. Nonetheless, for a more complete functional annotation of such rSNPs, it is necessary to establish their association with a trait, in particular, with a predisposition to a certain pathology or sensitivity to drugs. Thus, approaches to finding SNPs important for the development of a trait can be categorized into two groups: (1) starting from data on an association of SNPs with a certain trait, (2) starting from the determination of allele-specific changes at the molecular level (in a transcriptome or regulome). Only comprehensive use of strategically different approaches can considerably enrich our knowledge about the role of genetic determinants in the molecular mechanisms of trait formation, including predisposition to multifactorial diseases. One of the main tasks of human genetics is to clarify themechanisms by which genome variations lead to phenotypicdifferences, primarily to individual differences in susceptibilityto diseases and in sensitivity to drugs. Single-nucleotidepolymorphisms (SNPs) are the most common type of genomevariation . Currently, due to the developmentof next-generation sequencing (NGS) technologies, morethan 950 million SNPs of the human genome are registeredin database dbSNP (https://www.ncbi.nlm.nih.gov/projects/SNP/snp_summary.cgi) ; furthermore,rare SNPs with a frequency  ofless than 1 % constitute more than 90 % of the total numberof SNPs. It seems unlikely that the vast majority of identifiedvariations can be important for the phenotype, but some ofthem certainly form the genetic basis of phenotypic traits,including predisposition to various diseases. In recent decades,major efforts have been applied to the search for such SNPs.The most popular approach (which started back in the1980s) to the identification of trait-related SNPs has been thedetermination of associations with diseases for SNPs foundin candidate genes , and in this context, only SNPs affecting the proteincodingpart of a gene have been investigated .Somewhat later, there has been some interest in elucidatingthe functionalityof variants located in noncoding regions ofgenes, i. e., in determining an effect of such variants on a certainmolecular phenotype. In particular, it has been shown thatsuch SNPs affect transcription factor-binding sites (TFBSs),thereby leading to changes in the expression of the respectivegenes . Nonetheless, these fewfunctional studies have remained almost invisible against thebackdrop of a huge wave of research aimed at identifying associations.The productivity of detection of disease-associated SNPsincreased dramatically with the advent of the genome-wideassociation study (GWAS) technology in the mid-2000s, which is based on an unbiased – not based on anyideas about the formation of a trait – principle of a genomewidesearch for SNPs associated with the trait . To date, more than 72 thousandassociations of genetic variants with traits have been foundby GWASs ,thus allowing to find many new genes and systems of genesassociated with predisposition to various diseases .Nevertheless, GWAS technology does not provide any informationabout the functionality of the detected variants,thereby making it very difficult to elucidate the molecularmechanisms underlying the development of a pathologyand hence to develop effective methods for its treatment andprevention. Additionally, based on results of GWASs, it isalmost impossible to distinguish a truly disease-associatedvariant from the many marker variants that are detected due tolinkage disequilibrium . It is also known that most SNPs identifiedby GWASs are located in the noncoding part of the genomeand, as a rule, in its regulatory regions  ; these data implyan influence of such SNPs on the binding of transcription factors(TFs) and on gene expression. Thus, a need for researchon functional interpretation of data from GWASs – both at the level of individual potentially regulatory SNPs (rSNPs)and at the level of all such variants collectively – has becomeobvious. In addition, because the GWAS technology greatlyunderestimates the actual number of associations owing tothe required strict thresholds in statistical processing , investigators have recognized the need to developGWAS-unrelated large-scale function-based approaches tothe search for rSNPs .timing of emergence  is analysis ofexpression quantitative trait loci (eQTLs) . Thisanalysis, by means of transcriptome data , determinesfor each SNP a difference in the level of expression of individualgenes among homozygotes and heterozygotes fordifferent alleles of this SNP . Somewhat later, techniques were devisedfor finding allele-specific events both in data from RNA-seq   and in data from ChIP-seq,DNase-seq, and ATAC-seq   . Massivefunction-based approaches also include massively parallelreporter assay (MPRA), SNP-seq, and SNP-SELEX .At the beginning of this review, using the latest studies asexamples, we examine rSNPs that are (i) associated with thedevelopment of pathologies according to results of GWASsand are (ii) characterized in detail in terms of their influenceon an interaction with a TF and on the expression of nearbyor distant genes. Next, the review describes the application offunctional genomics methods to interpretation of data fromGWASs and to the search for new regulatory variants withoutGWASs. In the course of the presentation, strengths and weaknessesof these approaches are shown, as is the importanceof comprehensive use of GWASs and functional genomicsmethods to reveal the role of SNPs in molecular aberrationsunderlying the development of a pathology.A wide range of experimental methods are utilized to functionallystudy individual possible rSNPs. At initial stages,classical methods are usually used: analysis of DNA-proberetardationin a gel by nuclear extract proteins  and a reporter assay , which allow a researcher to detect aninfluence of an SNP on the binding of some TF or on reportergene expression, respectively . To identify the TFs the binding sites of which areaffected by nucleotide substitution, scientists perform EMSAusing appropriate antibodies or purified TFs , chromatin immunoprecipitation with detection of alleleasymmetry in a PCR product (ChIP-AS-qPCR) , and mass-spectrometric analysis of proteins isolatedfrom complexes with oligonucleotides containing minor alleles.An impact of a nucleotide substitution in the identifiedTFBSs on their potential target genes is confirmed by experimentswith downregulation or artificial upregulation ofgenes of the corresponding TFs or by studying the effect ofpoint mutations introduced into the TFBS using CRISPR/Cas9 technology . Lately, an increasingly popularapproach in this field of research on SNPs has also been thedetermination of allelic imbalance of the expression for SNPslocated in transcribed regions of genes. Nonetheless, it is worthnoting that such an SNP can be either an rSNP proper  or a marker SNP in a linkagegroup with an rSNP located in a nontranscribed region .Various combinations of these techniques are employed inmodern research, as illustrated by the examples below.A textbook example of a well-studied rSNP is rs36115365(G/C), which is situated at a locus associated with varioustypes of cancer according to data from GWASs (chr5p15.33:region 2). At this locus, a correlation analysis has revealednine SNPs  associated withpancreatic cancer, testicular germ cell tumor, lung cancer, andmelanoma. To screen all nine SNPs for regulatory activity,EMSA and reporter assay were performed by means of eighthuman cell lines . The use of several celllines is a common practice in such studies  and is aimed at the highest possiblecoverage of events of interaction of TFs with their bindingsites; the reason is substantial differences in the sets of TFs expressedin different cell types . The screeninganalyses identified only SNP rs36115365 as potentiallyregulatory, and its C allele showed both much better binding toa certain protein in the EMSA and greater activation of reportergene expression as compared to the G allele .rs36115365 is located ~18 kilobase pairs (kbp) upstreamof the start of the TERT gene (encoding reverse transcriptaseof the telomerase complex) and approximately 5 kbpdownstream of the end of the CLPTM1L gene. Accordingto the results of ChIP-seq (chromatin immunoprecipitationfollowed by sequencing of DNA from the precipitates) fromproject ENCODE , this SNP’s locationoverlaps with many TFBSs, and this region is enriched withactive chromatin histone marks, which is typical for enhancerregions. Inactivation of this region by small-interfering-RNAmediatedtranscriptional silencing results in downregulation of only the TERT gene. To identifythe TF the binding site of which changes as a consequenceof the substitution of G with C, the binding of proteins fromnuclear extracts to oligonucleotides containing minor alleleswas implemented, followed by mass-spectrometric analysis ofthe bound proteins. After an analysis of the obtained peptides,four TF candidates that prefer the C allele were proposed:ZNF148, VEZF1/ZNF161, ZNF281, and ZNF740. In EMSAinvolving specific antibodies to these TFs, only ZNF148 wasconfirmed, which was subsequently verified by means ofthe purified ZNF148 protein in an experiment. A small-interfering-RNA-mediated knockdown of ZNF148 gave a de-finitiveanswer because it reduced TERT expression and telomeraseactivity and shortened telomere length. Thus, theC allele corrects the binding site of ZNF148, enhances theexpression of TERT and, as a consequence, increases the riskof carcinogenesis .According to GWASs, rs174575 (C/G) correlates with anelevated risk of colorectal cancer . ThisSNP is located in the first intron of the delta-6-desaturasegene (FADS2) at a distance of +41.5 kbp from its transcriptionstart site and at a distance of –178.8 kbp from the transcriptionstart site of the gene of long noncoding RNA AP002754.2.The rs174575 region in chromatin is enriched with histonemodifications characteristic of active regulatory regions, and judging by DNaseseqdata (identification of sites of hypersensitivity to DNase I)and findings of ATAC-seq (assay for transposase-accessiblechromatin), corresponds to open chromatin (ENCODE). Thehypothesis of a regulatory role of rs174575 is supported byeQTL analysis data, which show an association of the G allelewith overexpression of FADS2 and AP002754.2.Computer analysis of DNA motifs using Web services Cistrome and JASPAR has revealed that in the case of rs174575, the replacement ofG with C damages the binding site of TF E2F1, and the dataof ChIP-seq from ENCODE, obtained on colorectal cancerLoVo cells, indicate that E2F1 is mapped to the location ofthis SNP. A cross-competitive EMSA has confirmed betterbinding of a certain nuclear extract protein to the G allele,and that this protein is E2F1 has been demonstrated by ChIPqPCRwith appropriate antibodies. For instance, in cell lineswith different genotypes – HCT116 (CG), SNU-C1 (CG), andHT115 (CC) – a stronger binding of E2F1 is observed in cellscarrying the G allele. A study involving reporter constructs hasalso confirmed a higher enhancer activity of a DNA fragmentcontaining the G allele .Direct contact between the region containing rs174575 andpromoters of FADS2 and AP002754.2 has been detected by thechromosome conformation capture (3C) method, and it turnedout that the interaction was much more pronounced in cell linescarrying the G allele. Further experiments indicated that overexpressionof AP002754.2 sharply raises the level of FADS2expression in HCT116 and LoVo cells, and a knockdown ofAP002754.2 by microRNA causes a decrease in the expressionof this gene, indicating a stimulatory role of AP002754.2 inthe regulation of the FADS2 gene. On the other hand, overexpressionof FADS2 or AP002754.2 significantly increasesthe proliferation rate of HCT116 and LoVo cells, whereas aknockdown of FADS2 or AP002754.2 significantly reducesit. It has also been shown that overexpression of FADS2 andAP002754.2 accelerates tumor growth in in vivo experimentsin mice. It is known that the product of the FADS2 gene is a keyenzyme in the biosynthesis of polyunsaturated fatty acids,including arachidonic acid, which in turn is a precursor ofprostaglandin E2 (PGE2), which promotes tumor growth andmetastasis. Thus, rs174575 acts as an allele-specific enhancerthat stimulates the transcription of FADS2 and AP002754.2,leading to an elevated risk of colorectal cancer in the case ofthe G allele .According to GWASs, rs4903064 (T/C) is associated withrenal cell carcinoma, the most common type of kidney cancer. rs4903064 is located in the third intronof the DPF3 gene, which encodes a protein of the BAF subfamilyof the SWI/SNF chromatin-remodeling complex. Thepredominance of the C allele of rs4903064 in tumor tissuesamples from patients with clear-cell renal carcinoma hasbeen demonstrated, in contrast to both normal kidney tissuesand tumor tissue from individuals with papillary renal cellcarcinoma and individuals with chromophobe renal cell carcinoma.In this context, a measurement of the ratio of alleles inDPF3 pre-mRNA in patients with clear-cell renal carcinomaheterozygous for rs4903064 has confirmed a skew toward theC allele .According to ATAC-seq data obtained on primary renalcancer cells, rs4903064 is located in an open chromatinregion, in a putative enhancer. Given that the substitution ofT with C (rs4903064) creates a potential binding site for TFHIF, a reporter analysis has been performed on HeLa andMCF-7 cell lines, showing that an increase in reporter geneexpression takes place only in the case of the C allele andonly when cells are treated with a specific stabilizer of HIF:dimethyloxalylglycine. Knockouts of various isoforms ofHIF have revealed that the increase in reporter activity uponstimulation with dimethyloxalylglycine depends on HIF-1α.By means of ChIP-qPCR in primary renal tubular cells withdifferent genotypes of rs4903064 , enhancedbinding of HIF-1α and HIF-1β to risk allele C has been confirmed.To elucidate the role of overexpression of DPF3 inthe development of clear-cell renal carcinoma, a knockout ofDPF3 has been performed in cells of proximal renal tubulesusing CRISPR/Cas9 technology. It was demonstrated in thatreport that cells with defective expression of DPF3 grow moreslowly than control clones of the corresponding cells, suggestingthat increased expression of DPF3 in proximal tubule cellsstimulates proliferation .rs17114036 (T/C) is associated with coronary heart diseaseand ischemic stroke according to GWASs . This SNP is located in the 5th intron of the PLPP3gene, encoding phospholipid phosphatase 3, which inhibitsinflammation of endothelium and contributes to the integrityof its monolayer.Experiments with ATAC-seq and ChIP-seq (H3K27ac andH3K4me2)performed on human aortic endothelial cells(HAECs) have identified the region containing rs17114036 asa potential enhancer. The enhancer activity of this region wasconfirmed by reporter analysis, whereas protective allele C  significantly increased the activity ofluciferase upon transfection of vector constructs into HAECs.A deletion of a 66-bp region containing rs17114036 by meansof CRISPR/Cas9 significantly reduced the expression ofPLPP3 as compared to the unedited genome and enhanced thepermeability of the monolayer of edited HAECs. As a result ofmodeling hemodynamic processes, an increase in the activityof the studied enhancer  in HAECs wasshown with an 18-hour “atheroprotective” flow as comparedto an “atherogenic” flow, while no effect of the T allele wasfound. It turned out that the substitution of the T nucleotidewith C creates a binding site (CACC) for the KLF2 protein,as confirmed by ChIP-AS-qPCR analysis in HAECs heterozygousfor rs17114036. Cotransfection experiments with aplasmid causing overexpression of KLF2 also showed higherluciferase activity in the case of the tested enhancer carryingthe C allele .rs4407214 (T/G) is associated with estrogen receptor-negativebreast cancer. In the HMEC cell line, an analysis of ChIP-seqdata from the ENCODE project regarding locations of marksof active chromatin  has helped to find in the rs4407214 region a regulatorylocus in intron 1 of the WDR43 gene .By EMSA, the researchers showed ASB of nuclear proteinsfrom MCF10A and CAL-51 cells to DNA probes mimickingthe region of this SNP’s location in the genome. Reporter geneexpression under the control of the identified regulatory regionon the same cell lines was also found to be allele-dependent.Bioinformatic analysis was then performed using theJASPARdatabase and available ChIP-seq data for this regionfrom the ENCODE project to identify the TFs the bindingsitesof which are altered by the G-to-T substitution (rs4407214).As a result, USF1 was identified as such a TF. A competitiveEMSA with nuclear proteins isolated from CAL-51 andMCF10A cells confirmed the ASB of USF1 in the case ofthe G allele. It was also demonstrated that CRISPR/Cas9-mediated removal of the presumed regulatory region containingrs4407214 results in underexpression of PLB1 (phospholipaseB1), which is located at a distance of ~400 kbp fromWDR43.Because results of GWASs tend to associate a trait (disease)with multiple loci , mostof which in turn contain many often coinherited SNPs , it is very difficult tochoose among them the potential rSNPs involved in a disease’spathogenesis. To date, several effective experimental solutionsto this problem have been developed. First of all, these arescaled up versions of the approaches utilized to investigateindividual rSNPs: a reporter assay (MPRA) and methods forstudying protein–nucleic acid interactions  .In particular, MPRA has been successfully used to find therSNPs that play a key role in the genetic predisposition tolupus erythematosus . According to GWASfindings, 3,073 SNPs in 91 loci are associated with this disease.Those researchers constructed a barcoded library containing12,396 170-bp oligonucleotides containing in the middle allknown variants of these 3,073 SNPs; these oligos were insertedupstream of a minimal promoter placed before the eGFP gene.An influence of a minor allele on enhancer activity of insertsfor 51 SNPs from 27 loci was demonstrated in the GM12878cell line. The small number of identified rSNPs can most likelybe explained by transfection of only one cell line; if severalcell lines had been tested, the number of rSNPs would havebeen much larger due to expansion of the set of TFs involvedin the study. Similarly, in MPRA, 30 out of 832 SNPs (associatedwith melanoma risk according to GWASs) showeda significant difference in the impact of minor alleles on reportergene expression in the UACC903 melanoma cell line. For one of these 30 SNPs (rs398206),which is located in intron 1 of the MX2 gene, the differencewas the largest. It turned out that risk allele A of rs398206significantly enhances the binding of TF YY1 in vitro (inEMSA) and in vivo (according to ChIP-AS-qPCR), therebyupregulating MX2 and thus contributing to the initiation ofmelanoma . Other examples can be foundin refs .By methodically similar Reel-seq and SNP-seq, which arebased on a comparative analysis of the binding of a TF tooligonucleotides containing minor alleles, 521 potential rSNPshave been selected out of 4,316 SNPs correlating with breastcancer according to GWASs  as well as403 possible rSNPs out of 903 SNPs associated with prostatecancer . The largest study involving theapproach from this research group was published in 2021. The approach was named SNP-SELEX. Toimplement it, those authors used a library of 383,544 40-bpoligonucleotides containing in the middle all possible allelesof 95,886 SNPs. SNPs were chosen based on either their associationwith type 2 diabetes mellitus in GWASs or localizationwithin a 500-kbp window containing a variant associatedwith this pathology. By means of 270 recombinant TFs, thoseauthors conducted a multiplex analysis of their binding tothe oligonucleotides and identified 11,079 SNPs having anappreciable allele effect on binding to at least one TF.For mass interpretation of the results of GWASs, functionalgenomics data from available databases are also widely used,such as data on genome-wide profiles (ChIP-seq) of TFs’ binding and of histone modifications , on open-chromatin genome-wide profiles (ATACseq), on three-dimensional chromatincontacts , and on locations of enhancerand superenhancer regions  as well as data from eQTL analysis.For example, 8,005 SNPs – either directly associated byGWASs with major depressive disorder or present in the samelinkage group – have been mapped to ChIP-seq peaks obtainedfrom a brain tissue or cells of neuronal origin by means ofantibodies to 34 various TFs . After that,a search was performed for binding sites of the correspondingTFs in the regions of the SNPs using a database containing7,699 position weight matrices ,and it was revealed that 34 SNPs disrupt the binding sites of15 TFs. A reporter assay confirmed the effect of an allele ongene expression for 29 SNPs. One of them, rs3101339, provedto be located at a potential binding site of TF REST in thepromoter region of the NEGR1 gene, whereas the substitutionof A with C considerably damaged the structure of this site,as evidenced by a decrease in reporter gene expression underthe control of an insert carrying the C allele. The influence ofrs3101339 on NEGR1 gene expression in vivo was confirmedby elimination of an appropriate DNA fragment via CRISPRCas9genomic editing. Since the product of NEGR1 playsan important part in the maintenance of required density ofdendritic spines, its underexpression when A is replaced by Cmay substantially contribute to the development of a depressivestate .Data on genome-wide profiles of active-chromatin histonemarks are also turning out to be very informative for thefunctional interpretation of GWAS results. For example, toanalyze many SNPs correlating with epithelial ovarian cancer,they have been mapped in the region of ChIP-seq peaks forH3K27Ac; these peaks were obtained by the researchers ina study on 26 tissue samples of this type of cancer . Then, using the motifbreakR tool , among the mapped SNPs, 469 SNPs were selected inwhich the nucleotide substitution substantially altered a bindingsite of some TF. The most frequent was the change in thesequence of the binding site of TF REST, for which there aredata on its tumor-suppressive and oncogenic functions . Besides, the use of ChIP-seq datasets on varioushistone modifications from relevant databases in combinationwith data and tools from a database of potential regulatoryvariants (rVarBase)  has made it possible todetect in superenhancers 286 and 366 possible rSNPs associatedwith type 2 diabetes mellitus  andcoronary heart disease , respectively, thatalter the predicted TFBSs.Modern massive function-based approaches to the identificationof potential rSNPs are mainly based on the registrationof an effect of a nucleotide substitution on some molecularphenotype. This may be (i) determination (in transcriptomes)of a difference in the expression level of individual genesamong homozygotes and heterozygotes for different alleles ofeach SNP , (ii) identification of SNPs showingasymmetry of enrichment within transcriptome data (RNAseq:ASE events) or within epigenomic data , or (iii) determinationof an influence of an allele on reporter gene expressionby MPRA.The term “eQTL” either means that there is a correlationbetween a variant (eVariant) and the expression level ofa certain gene(s) (eGene[s]) or refers directly to an SNP the alleles of which show sucha correlation; the term is used much more frequently in thelatter sense . Transcriptomic data obtainedusingeither microarrays  or RNA-seq  are suitablefor finding eQTLs. These data are quite sufficient for thedetection of eQTLs located in transcribed regions , whereas the identification of their entire set alsorequires genome sequencing data . In contrast to GWASs, which requirebiological samples from many thousands of individuals , several hundred participants are sufficient foreQTL analysis . Nonetheless, just as in GWASs, in eQTLanalyses, the problem of distinguishing an SNP that is indeedrelevant to the formation of a trait – among marker variantsdetected through linkage disequilibrium – is still relevant .The largest-scale project on obtaining transcriptomic dataand identifying eQTLs is international consortium GTEx,within which RNA-seq data on 15,201 postmortem samplesof 49 tissues collected from 838 donors have been collected,allowing to identify 4,278,636 eQTLs associated with changesin the expression of 18,262 and 5,006 genes encoding proteinsand long intergenic noncoding RNAs, respectively .There are other datasets of eQTLs, including those obtainednot on postmortem but on biopsy materials . For example, in a study by Stolzeet al., in an analysis of transcriptomes (RNA-seq) of the aorticendothelium of 157 donors, the investigators identifiedthousands of eQTLs not registered in the GTEx Consortiumdata . Fairfax et al. have employed CD14+monocytes  treated in vitrowith either interferon gamma  orbacterial cell wall lipopolysaccharide (LPS) . CD14+ monocytes from414 people served as controls there. Through microarrayRNA profiling and genotyping, 609,704 SNPs  were examined and 21,516 eQTLs weredetected, 24.6 % of which manifested themselves in controlcells, 21.6 % of which manifested themselves after 2 h oftreatment with LPS, and 25.4 and 28.3 % after 24 h treatmentwith LPS and IFN-γ, respectively. The results of this workpoint to an important role of genomic variants in the natureof transcriptomic response to a drug . Inconclusion, it should be noted that any dataset of transcriptomicdata obtained from hundreds or more individuals can beused to search for eQTLs, as, for example, has been done byus  with the help of data from RNAseqanalysis of postmortem brain samples from 96 individuals.At present, quantitative expression trait loci analysis ismainly utilized to identify groups of genes participating intrait formation . Additionally, its results are often used to prioritizeGWAS-identified SNPs for their subsequent rigorous experimentalinvestigation. An example is rs13239597, which islocated in the TNPO3 gene promoter and associated with lupuserythematosus and multiple sclerosis according to GWASs.eQTL analysis of transcriptomes of lymphoblastoid cell linesderived from 373 individuals has not revealed any impact ofrs13239597 on TNPO3 expression but uncovered a significantassociation of the A allele of this SNP with overexpression ofthe IRF5 gene [which is located 118 kbp away ], in agreement with findings of the GTEx Consortium. Next, an analysis of availableHi-C data showed that IRF5 is one of 12 genes that are indirect contact with the rs13239597 region. A computationalanalysis of motifs that potentially change affinity for a TF asa result of a nucleotide substitution  hasrevealed four such TFs: EVI1, ERF, GATA1, and TAL1. ByChIP-AS-qPCR, it has been demonstrated that EVI1 bindsmuch better to the rs13239597 region in the case of the A alleleas compared to the C allele . Similarexamples can also be found in refs .The development of next-generation-sequencing-based methodsof transcriptomic analysis (RNA-seq) and epigenomicanalysis  has opened upa unique opportunity for quantifying a difference in the enrichmentof two alleles  of each heterozygouspolymorphic site of a diploid organism within the respectivedataset . An important feature of these approaches to theidentification of potential rSNPs – in contrast to eQTL analysis – is that allele-asymmetric events are recordedfor each individual and the backgrounds are identical. Thisarrangement enables researchers to obtain reliable data whenstudying a very small number of individuals, down to one. An increase in sample size is requiredonly for involving in the analysis a larger number of SNPs thatare in a heterozygous state. For instance, calculations showthat data from 20 individuals theoretically allow to determineASE or ASB events for 65–70 % of SNPs that have a populationfrequency of ≥5 % .For this reason, possibilities of pharmacogenetic and pharmacogenomicprojects become much more abundant. Themost striking example of such a project is a simultaneousanalysis of allele-specific effects of 50 substances  in primary cultures offive cell types ,each of which is represented by cell samples fromthree individuals . An analysisof the resultant transcriptomic data helped to identify morethan 300 SNPs, an imbalance in the enrichment of the allelesof which within transcriptomes emerged or increasedsignificantly in response to treatment with one or anotherdrug. Via the same approach, inducer -dependent ASE events have been identified in19 immuneresponse genes by an analysis of transcriptomesof blood mononuclear cells from eight individuals  as well as 561 ASE events responsive to treatmentof CD4+ T cells  withimmobilized anti-CD3/CD28 antibodies . These results open up a new – unrelated to anya priori hypothesis – way to elucidate mechanisms of individualsensitivity to drugsThe largest dataset of ASE events at present, containing431 million such events, is derived from data on RNA-seq andwhole-genome sequencing from the GTEx Consortium  and is published in a paper by Castel et al. . This dataset can serve as a source formass discovery of rSNPs, for example, in a comparison withdata from GWASs or from eQTL analysis. It is worth notingthat in the absence of whole-genome sequencing data, relevantinformation can be acquired by more sophisticated methodsof bioinformatic search for allele-specific events directly inRNA-seq data .ChIP-seq experiments based on antibodies to various TFsmake it possible to directly register events of allele-asymmetricinteraction of these proteins with their binding sitesin the case of a heterozygous state of SNPs at these sites.In a pioneering work in the laboratory of Claus Wadelius,they analyzed all the then-available data from the ENCODEproject on binding profiles of TFs in cell lines GM12878(B cells), H1-hESC, K562, and SK-N-SH, thereby revealing9,962 SNPs featuring an allelic imbalance in the binding ofa TF (ASB) . By the same approach,3,713 SNPs have been found showing an allelic imbalancein the binding of TFs in HepG2 and HeLa-S3 cells; testing39 of them in a luciferase reporter system has confirmed theeffect of an allele on reporter gene expression for 27 SNPs. A detailed analysis of one of them,rs953413, indicates that the A allele disrupts the binding siteof TF FOXA, resulting in reduced binding of not only thisTF but also of TF HNF4α cooperatively interacting with it,thereby ultimately leading to underexpression of ELOVL2and possibly serving as a factor in the pathogenesis of non-alcoholicfatty liver disease .Because allele-asymmetric alterations in profiles of histonemodifications and of open chromatin can reflect SNP-inducedchanges in the binding of TFs , these dataare also widely utilized to find ASB events. For instance, Mauranoet al.  have examined 493 openchromatinprofiles (DNase-seq) obtained in various celllines, where 64,599 SNPs with ASB have been found. Theirbioinformatic analysis using position weight matrices for2,203 motifs of TFBSs from different sources indicates thatmost of the identified SNPs can affect the binding of TFsand hence the accessibility of the respective DNA regionsto DNase I . A newer technique fordetecting open chromatin, ATAC-seq, is based on the abilityof a hyperactive mutant of Tn5 transposase to detect openDNA regions in chromatin  and isalso used to search for ASB events. In particular, it has beenemployed to identify 53 rSNPs in breast cancer MCF-7 cellsand 125 rSNPs in a line of human mesenchymal stem cells(MSCs); in total, 30 % of the rSNPs found in MCF-7 cells and43 % of those found in MSCs have been identified as eQTLsin GTEx data, indicating their influence on gene expression. Examples of use of data from ChIP-seq(involving antibodies to histone marks) for registering ASBevents can be found in refs .The combination of searches for ASE events and ASBevents can be considered the most productive approach toidentifying rSNPs. For example, in our work , at first, ASB events were identified in ChIP-seqdata from the ENCODE project for histone modificationsH3K27ac, H3K4me1, H3K4me2, H3K4me3, and H3K27me3as well as for 456 TFs and their associated proteins in humancell lines K562, MCF-7, and HCT-116. Then, by means ofRNA-seq data obtained from the same cell lines, SNPs (rSNPs)that are associated with changes in gene expression levels wereidentified. According to GWASs, out of 1,633 rSNPs found inthis way, 27 have shown associations with cancers , and 14, with cognitive disorders . Another 30 rSNPs have been implicated in colorectalcancer with the help of data from the International Cancer GenomeConsortium (ICGC) . Genotypingof patients with colorectal cancer and healthy individuals forsix of these SNPs has revealed an association of rs590352,rs4796672, and rs2072580 with this disease . A correlation with breast cancer has been found forrs2072580 . Later, the same approachhas allowed to identify 14,266 rSNPs during the processingof data obtained in a study by Reyes-Palomares et al.  on H3K4me3 histone marker profiling(ChIP-seq) and RNA-seq data on pulmonary-artery epithelialsamples from 19 individuals .Research into the effect of polymorphic-site alleles on reportergene expression via simultaneous transfection of hundredsand thousands of barcoded plasmid constructs into eukaryoticcells with subsequent transcriptome sequencing is also aninformativeapproach to finding rSNPs . The largest-scalestudy based on this approach has been conducted in the laboratoryof Bas van Steensel . Usinga promoterless plasmid and fragmented genomes (fragmentlength 150–500 bp) of four individuals belonging to differentethnic groups, two barcoded libraries were constructedfor each individual, where inserts were expected to play therole of a promoter. At the same time, on the basis of data ontranscription initiation in enhancer regions , those authors expectedto detect not only promoters but also enhancers. The use ofDNA from humans of genetically distant ethnic groups allowedthose investigators to hope for an analysis of the largestpossible number of polymorphic sites that are homozygousfor different alleles in at least two of those people.After transfection of K562 and HepG2 cells with the resultinglibraries, 19 and 14 thousand potential rSNPs, respectively,were found, most of which did not overlap, once again indicatingtissue specificity of the supragenomic (protein) regulatorymachine. The identified SNPs showed significant enrichmentwithin regulatory regions of the genome. In this case, theenrichment (approximately 15-fold) was three times higherin promoter regions than in enhancer regions (approximately5-fold); this outcome is obviously due to the design of thereporter constructs. For several rSNPs, by mass-spectrometricanalysis of proteins interacting with oligonucleotides containingminor alleles, those authors were able to identify TFs thebinding sites of which are altered by a nucleotide substitution.In particular, the A allele of rs623853 was found to disruptthe binding of TFs of the ELF family, whereas the C allele ofrs554591 weakens the binding of ZNF787 while enhancingthe binding of KLF and SP .Programs – of coordinated switching on, switching off, andchanges of the expression of various genes – that underlie(1) ontogenesis events, (2) the existence of many types ofdifferentiated cells, and (3) the abilities of cells to respond tovarious factors of the external and internal environment areimplemented by the regulatory part of the genome of multicellularorganisms. The information encoded in the regulatoryregions is converted into a desired pattern of gene expressionprimarily via the binding of TFs to specific sequences in theregulatory regions . Accordingto present-day concepts, the SNPs located in regulatoryregions of genes, affecting binding sites of TFs, and changingthe level of gene expression play a central part in the variationof phenotypic traits, including predisposition/resistanceto multifactorial diseases . In this regard, thereis a strong interest both in functional interpretation of SNPshavingan association with various diseases (primarily accordingto GWAS data) and in the development of massivefunction-based approaches to the discovery of rSNPs. Interpretationof data from GWASs is carried out either at the levelof individual SNPs or for all SNPs collectively by a varietyof functional genomics techniques . Meanwhile, thesame methods of functional genomics are used for personalsearches for rSNPs, but at the same time, it is necessary tosolve the inverse problem: determining a relation between thefound rSNPs and a trait (disease). The most popular solutionto this problem is to compare the obtained data with availableinformation from GWASs . On the other hand, inthis way, usually only 1.5–3.0 % of found rSNPs are implicatedin various traits . In this regard, it seems very promising to takeadvantage of results of eQTL analysis, enabling an investigatorto determine an influence of many specific rSNPs on theexpression of fairly large groups of genes, the subsequentanalysis of which by modern functional annotation tools  allows to get an idea about a possible affected trait.To sum up, there are two approaches – based on oppositeprinciples – to finding SNPs that are important for the developmentof a trait (pathology): on the one hand, starting from dataon an association of an SNP with some trait, and on the otherhand, starting from determination of allele-specific changes atthe molecular level (in the transcriptome or regulome). 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