Solanum tuberosum and thale cress Arabidopsis thaliana genomes for the CTCT sequence. The motif was found, on average, 3.6 and 4.3 times per promoter  in these two species, respectively; however, the CTCT sequences were not randomly distributed in the promoter regions but were preferentially located near the transcription initiation site and were closely packed. The closer these CTCT sequences to the transcription initiation site, the smaller distance between them in both plants. One can assume that genes with many CTCT motifs in their promoter regions can be potentially regulated by MFs. To check this assumption, we tested the influence of MFs on gene expression in a transgenic potato with three promoters  containing from 3 to 12 CTCT sequences and starting expression of β-glucuronidase as a reported gene. The potatoes were exposed to a 50 Hz 60–70 A/m MF for 30 min and the reporter gene activity was measured for up to 24 h. Although other factors induced the reporter gene activity, the MF did not. It implies the CTCT motif does not mediate in response to MF in the tested plant promoters.It was proposed that magnetic fields (MFs) can influence gene transcription via CTCT motif located in human HSP70 promoter. To check the universality of this mechanism, we estimated the potential role of this motif on plant gene transcription in response to MFs using both bioinformatics and experimental studies. We searched potential promoter sequences (1000 bp upstream) in the potato  During the life cycle organisms are continually exposed to various external stimuli, which requires adequate responses to maintain homeostasis; this process is often called a stress response. The stress factors cause changes in gene expression resulting in adaptive responses at the proteome (synthesis of relevant proteins) or metabolome levels  .One of such factors could be extremely low-frequency magnetic fields (ELF-MFs), which influence living organisms are supported by the increasing number of evidences. However, the failure to produce repeatable effects  has madeSolanum tuberosum and Arabidopsis thaliana were analyzed in silico. Subsequently, this hypothesis was experimentally evaluated using three promoters that contained CTCT motifs. We selected 16R, 20R and 5UGT promoters, which are involved in flavonoid biosynthesis regulation and responses to free radical stress. The free radicals influence the regulation of genes related to the flavonoid biosynthetic pathway, such as glucose transferase  obtained from Saatzucht Fritz Lange KG , three promoters were used: 20R (EMBL/GenBank database acc. no. AY518222), 5UGT (EMBL/GenBank database acc. no. AY033489), and 16R (EMBL/GenBank database acc. no. AY070220). Each promoter regulated transcription of the reporter gene uidA (coding for β-glucuronidase). For plants transformation binary vector pBI101  and Agrobacterium tumefaciens strain C58C1 were used. Plants were grown in tissue culture under 16-h light (23 mmol/s/m2) – 8-h dark regime in MS medium . After the transfer, the membrane was sequentially incubated with a blocking buffer (5% dry milk) and then with antibodies directed against the GT protein (1:500 dilution). Alkaline phosphatase-conjugated goat anti-rabbit IgG served as the second antibody and was used at the dilution of 1:1500.An assessment of the GT protein level was conducted by means of western blot analysis using the rabbit anti-GT IgG and Pooled samples from at least three samples were used for the total RNA extraction. cDNA was synthesized from 5 μg of the total RNA using High Capacity cDNA reverse transcription kit . cDNA was added to 5 μl of SYBR Green PCR mix  and 0.5 μl of each primer (0.5 μm) in triplicate. Polymerase chain reaction (PCR) was carried out with the use of specific primers for glycosyltransferase gene . Amplification and detection were performed using LightCycler 2.0 instrument and lightcycler software version 4.0 .Plant material was exposed to 50 Hz 76–88 μT (60–70 A/m) MF for 30 min in the air-conditioned room with the temperature of 19°C. Taking into account the air flow and the layout of exposition with the minimum distance from the plant of several centimeters there was no significant effect of temperature on the experimental results with the applied MF.The EMF exposure system was composed of two Helmholtz coils with the inside diameter of 400 mm, external diameter of 462 mm, and 40-mm width with 216 mm spacing. Each of the Helmholtz coils was made of copper wire (2.15 mm in diameter) coiled for 223 winding turns. Both coils were positioned vertically to ensure that the magnetic flux was generated in the horizontal plane. The output of the autotransformer  connected to the electric energy supply was an electric source for a sinusoidal 50-Hz alternating current  in the experiment. The difference of the potential applied to the coils could be regulated. The amplitude of the current intensity was controlled by the ammeter . MF strength in the center of the Helmholtz coils can be calculated from the formula derived from Biot–Savart’s law:I – value of currentwhere: r – radius of coilsN – number of winding turns.Higher harmonic waves in the current were monitored during the experiments  and did not exceed 2%. Magnetic induction was measured with EPRI – Emdex II meter  and with Holaday HI-3627 meter  for traceability. MF strength was kept in our experiments within the range of 60–70 A/m.Supplementary Figure S1). During the exposure, the leaves were put on Petri dish (35 mm × 10 mm) positioned in the geometrical center of Helmholtz coils. Additionally, for transgenic plants with 16R promoter, the whole plants in jars were subjected to exposition.Exposure was carried out on potato leaves with 25 mm long and 15 mm width. Orientation of leaf’s stem was parallel to the force lines of MF generated in the exposure system . Then, the replacement of alternated current with its root mean square (RMS) value allows for determination of the equivalent strength of MF.t-test and confidence intervals (CIs) were calculated using Excel  to assess statistical significance of the obtained results. p-values less than 0.05 were considered statistically significant.S. tuberosum and 31,036 A. thaliana potential promoter sequences, which were defined as regions of 1000 nucleotides upstream of the transcription initiation site of protein-coding nuclear genes; we excluded sequences with unidentified nucleotides in this study. The scanned promoter sequences and gene annotations were obtained from S. tuberosum Group Phureja DM1-3 516R44 (CIP801092) genome annotation v3.4 (Arabidopsis Information Resource (TAIR) database, release 9 , 60 A/m is the upper limit intensity for unlimited exposure of humans to 50-Hz MFs. The nCTCTn motif may be responsible for the regulation of gene expression in response to 50-Hz MFs in animal cells . TherefoS. tuberosum, the subject of the experimental studies in this paper, and a popular model plant organism, A. thaliana. The genome of S. tuberosum has the total length of ∼800 Mb that is arranged into 12 chromosomes . They constituted more than 18% (7573) in S. tuberosum and 16% (4977) in A. thaliana of cases. More than 15% of the promoters  included four potential EMRE sequences, whereas 10 or more motifs were present in 783 S. tuberosum and 1449 and A. thaliana promoter regions . The motifs were absent from only 2195 and 1103 promoter regions, respectively.To analyze the frequency and distribution of the potential EMRE motif within gene promoters in plants, we included two plant representatives, omosomes , whereasomosomes . We searFigure 2). Almost 6.5% and 9% of these sequences  were found in less than 50 nucleotides from the transcription start site, whereas more than 12% and 15% of these sequences  were present in 100 nucleotides upstream of the site, respectively. The contribution of these motifs decreases rapidly at 150 bp from the start transcription site .Detailed analyses revealed that CTCT sequences were not randomly distributed in the promoter regions, but rather located close to the transcription initiation site . The average distance between these motifs is 162 and 146 bp for S. tuberosum and A. thaliana, whereas between these motifs randomly distributed across the promoters much larger, i.e., 271 and 226 bp, respectively. In 36,165 and 40,610 cases (33 and 39%) in S. tuberosum and A. thaliana, the distance was less than 50 nucleotides, whereas in 3582 and 4757 cases (3.3 and 4.5%), respectively, the sequences were adjacent to each other. If we randomized position of these motifs within their promoter regions, only 0.11% and 0.15% of distances between these motifs were shorter than 50 bp for S. tuberosum and A. thaliana, and none sequences were adjacent. About 19% and 23% distances up to 20 bp were found for the Solanum and Arabidopsis genomes, whereas 0.04% and 0.01% for the corresponding randomized data . Interestingly, the densely packed CTCT motifs accumulated close to the site of transcription initiation. A clear positive but non-linear relationship can be observed between the distance of potential EMRE sequences and the distance of these sequences from the transcription initiation site ; the closer the motifs to the transcription initiation site, the smaller distances between these motifs in the studied plants.In addition to that, the analysis of distances between potential EMRE sequences that were found in promoter regions indicated that many of these sequences are closely packed  repeat-containing proteins, which are expressed in mitochondria and plastids. In these organelles, the PPR repeat-containing proteins bind organellar transcripts and influence their expression by RNA editing, turnover, processing, or translation (The top genes with the largest (>20) number of potential EMRE motifs found in their promoters are listed in nslation ; consequS. tuberosum genes with the large numbers of potential EMRE motifs are those that code for stress-responsive alpha-beta barrel domain protein and heat-shock protein 70T-2 (Table 1). In fact, human HSP70 promoters containing these motifs respond to MFs (Table 3). More than half of the HSP70 genes have more observed motifs than expected. In the case of A. thaliana promoters for HSP70 genes, all contained at least one this motif and almost 90% of them had more observed these motifs than expected (Table 4).Interestingly, among the d to MFs , 1999; sTo look for the elements that could modulate transcription in response to ELF-MF, we further analyzed the sequences of three potato promoters, namely 16R, 20R, and 5UGT. These promoters are well-studied and validated expression models in plants .Within the 16R promoter (972 nucleotides in length), the transcription initiation site is located 89 nucleotides upstream of the translation initiation site. This promoter region contains a typical CCAAT box, located at position -147, but lacks a typical TATA box. Among many others, the following putative transcription factor binding sites were found in this promoter: ARF (Auxin Response Factor), light-regulated element GATA, I-box, GT1, elicitor responsive element (ElRE) regulated upon response to infection (TTGACC), and a frequent motif, AATAGAAAA, present in promoters of genes regulated by sucrose levels. Three CTCT motifs were found, which could potentially regulate gene expression after exposure to MFs.Figure 5).Sucrose and plant hormones  regulated the expression of GUS under control of the 16R promoter . The fasThe 20R promoter (1239 nucleotides in length) contains a number of motifs that potentially respond to light, amylase boxes, and sequences regulated by ABA and cold . Fewer sFigure 6). Additionally, to exclude impact of mechanical stress an experiment was performed on 14-days whole potato plants . In the leaves of plants exposed to EMF, no statistically significant increase in GUS activity was observed 6 h after the exposition. The activity decreased in the following time-points and was similar to the control.Different factors were tested using this promoter: ABA, ethylene, auxin, salicylic acid, pathogen infections, metals , salt, glycol, light, wounding, low temperature, and sucrose. Auxin, ethylene, salicylic acid, pathogen infection, and sucrose did not affect GUS activity ; howeverS. sogarandinum. Within its entire sequence, several motifs were found upstream of the translation start site that are potentially recognized by transcription factors and involved in the regulation of responses to UV light, ABA, light, sucrose, and potentially MF because five CTCT motifs were identified. Using heterologous expression in S. tuberosum, the 5UGT promoter was induced by UV light, cold, light, ABA, and salt (NaCl). The effect of cooling and light, as well as ABA and cold, were synergistic. The 5UGT promoter’s activity was inhibited by sugar concentrations above 2% . This result was also confirmed in S. sogarandinum by mRNA (qPCR) and protein (Western Blot) quantification .The glucosyltransferase promoter (1625 nucleotides in length) was isolated from the wild potato above 2% . The 5UGhsp70 and c-myc promoters regulate expression in response to MF exposure for 30 min at 60 Hz and 8 μT . This could partially explain previous failures to obtain repeatable effects  are adjoining. The organization of these motifs in clusters may suggest some regulation of gene expression, involving the cooperative binding of transcription factors to DNA. Moreover, it cannot be excluded that some of the neighboring stretches of CTCT were generated by CT dinucleotide repeat expansion, e.g., by DNA polymerase slippage mutations. The distribution of CTCT sequences may be also influenced by genome rearrangements and amplifications mediated by transposable elements (Tables 1 and 2).Although our searches revealed that the CTCT motifs are widely distributed in the studied plant genomes, the conserved test verifying their presence by chance in promoter regions based on their general nucleotide composition showed only 12 and 4 significant cases for elements , becausen/(TC)n. These elements are a target for specific protein complexes, replacing nucleosomes to create a local chromatin environment, which enables a variety of regulatory responses esponses . GAGA elesponses . Althougal genes , such moal genes . Becausehsp70 genes . Other genes  may be also considered MF-sensitive because their promoters contain a significant number of CTCT motifs (Tables 1 and 2).The transcriptional activation by GAGA factors and the presence of GAGA elements in promoter regions were also reported for 70 genes . Interes70 genes , 1999. OS. tuberosum; however, in the studied experimental conditions, there was no significant regulatory effect of the 50-Hz MF in the range of 60–70 A/m on the expression of 14-3-3 protein gene promoters (16R and 20R) or the glucose 5UGT transferase promoter. Besides the assumption that the EMRE does exist but plants do not respond to MFs because of inappropriate parameters used in the experiments, there are several other possible explanations. One of them is that the CTCT sequences that might act as EMREs should be separated by specific distances. It is also possible that the presence of other motifs and interactions between various transcription factors are necessary for ELF-MF perception, which is very common in many regulators of gene expression. In addition to other uncontrolled parameters that lead to cell line-dependent construct expression, there are clear experimental differences between animal . Indeed, in plant cells, the production of proteins on once-produced mRNA template may be constant for at least 6 h, resulting in steady accumulation of a reporter protein. Once produced and accumulated, the reporter protein, such as GUS, is relatively stable and may be detected for several hours after translation. Consequently, even very short transcriptional activation should be visible in our experimental conditions except for very weak activation, resulting in signal lower than background.It would be worthwhile to reproduce an easy experimental system to study the impact of MFs on living organisms, including plants. Therefore, in addition to the statistical evaluation of plant promoters, we tested the impact of MFs on stress-related promoters in n animal  and plann animal  cells. IThe presented results did not confirm the hypothesis that CTCT motifs are EMREs in the studied plant promoters, which seemed promising because they contain CTCT motifs and are known to response to stress conditions. Although we observed no significant response to MF in the plant model, it cannot be excluded that other promoters or motifs can fulfill such function. Moreover, the response can be realized by a complex regulatory network that escapes the simple promoter studies. The response could be initiated by a subset of genes whose promoters can have some MF-specific motifs. Products of these genes could further serve as transcription factors for many other genes whose promoters may not have such specific motifs. These genes may not give positive response to MF if other set of regulated genes are not sufficiently expressed. This complicated network regulation of gene expression requires a separate approach to particular cases and selection of the promoters to GUS/GFP studies without additional knowledge would be misleading. On the other hand, widespread criticism of the original paper about the presence of EMREs, suggests that such elements do not exists in plants. Therefore, the analysis of promoter regions at the specific genes requires a special and separate consideration.MŁ, DS: study concept and design, data acquisition, statistical analysis, analysis and interpretation, manuscript drafting, editing and revision, manuscript final version approval, PM: data acquisition, statistical and bioinformatic analyses, analysis and interpretation of results, manuscript drafting, editing and revision, manuscript final version approval, AA-S: data acquisition, analysis and interpretation, manuscript final version approval, KK: data acquisition, analysis, and interpretation.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The hierarchical organization of chromatin is known to associate with diverse cellular functions; however, the precise mechanisms and the 3D structure remain to be determined. With recent advances in high-throughput next generation sequencing (NGS) techniques, genome-wide profiling of chromatin structures is made possible. Here, we provide a comprehensive overview of NGS-based methods for profiling “higher-order” and “primary-order” chromatin structures from both experimental and computational aspects. Experimental requirements and considerations specific for each method were highlighted. For computational analysis, we summarized a common analysis strategy for both levels of chromatin assessment, focusing on the characteristic computing steps and the tools. The recently developed single-cell level techniques based on Hi-C and ATAC-seq present great potential to reveal cell-to-cell variability in chromosome architecture. A brief discussion on these methods in terms of experimental and data analysis features is included. We also touch upon the biological relevance of chromatin organization and how the combination with other techniques uncovers the underlying mechanisms. We conclude with a summary and our prospects on necessary improvements of currently available methods in order to advance understanding of chromatin hierarchy. Our review brings together the analyses of both higher- and primary-order chromatin structures, and serves as a roadmap when choosing appropriate experimental and computational methods for assessing chromatin hierarchy. An interphase chromosome is formed by a tightly coiled 250 nm chromatid. Microscopic imaging has demonstrated that each chromosome may be confined to genomic compartments . Within On the other hand, the primary-order chromatin refers to the unpacked chromatin fiber where 11-nm coils of nucleosomes are exposed. The nucleosome is the fundamental unit of chromatin. Each nucleosome comprises 147 bp of DNA wound 1.65 times around core histones ,74. ChroGene expression and biological functions intimately rely on the interactions between regions (higher-order structure) and the accessibility of chromatin (primary-order structure), which are mediated by protein complexes and epigenetic modifications ,79,88. TThis review aims to give a broad overview of NGS-based methods for “higher-order” and “primary-order” chromatin assessment from both experimental and computational aspects. We discuss the characteristics and requirements of each sequencing method together with the computing strategies and bioinformatics tools.1.11.1.1in situ hybridization (FISH) have provided evidence of chromosomal territories and compartments, organization of TADs and non-random organization of genomic loci within the nuclear periphery [Microscopy-based imaging tools have been used to observe the higher-order structure of chromatin and its dynamics for over a century . At a reeriphery ,104.in vivo contacts, chromatin fragmentation by restriction enzyme digestion and proximity ligation of the digested ends. The restriction enzyme selection depends on the size of target loci; for 3C, frequently cutting enzymes give rise to smaller fragments and hence are more suitable for identifying smaller loci. As a guideline, 4-bp cutters (i.e. frequent cutters) are used when studying small loci sized below 10–20 kb, whereas 6-bp cutters are for loci larger than 20 kb. Ligation junctions are detected in conventional 3C libraries via PCR followed by gel electrophoresis. In combination with next-generation sequencing, the physical interactions of chromatin can be detected with a higher resolution and greater sensitivity [Over the past decade, a variety of chromosome conformation capture (3C)-based methods have allowed the detection of higher-order structures of chromatin in unprecedented detail. The conventional 3C method determines the physical interactions of chromatin between two genomic regions (one vs. one) ,84,102. sitivity ,56.cis)- and inter (trans)-chromosomal interactions. Circular chromosome conformation capture (4C) uses restriction digestion, followed by inverse PCR, to identify multiple loci interacting with one particular genomic site, referred to as the “bait” or “viewpoint”  [cis) or long-range (far-cis or trans) contact sites depends on experimental setups. Analyses resulted from 4-bp cutter enzymes have been shown to have low reproducibility of 4C signals between replicates, particularly in far-cis and trans interactions; however, 4-bp cutters are effective in identifying cis interacting loci in the vicinity (<10 kb) of the viewpoint [in situ ligation that occurs inside the nuclei instead of “in solution,” thereby decreasing the probability of false inter-chromosomal fusions [More recent 3C-based technologies, such as 4C, 5C, and Hi-C, incorporate next generation sequencing and thereby are capable of providing quantitative measurements for intra  ,93. The vs. all) . Furtheriewpoint ,99. In ciewpoint ,73,75. F fusions .Chromosome conformation capture carbon copy (5C) is employed to study all contacts within a particular region (many vs. many), based on highly multiplexed ligation-mediated amplification (LMA) . This teHi-C generates contact maps among all parts of the genome  . A bioti1.1.2The advancement of 3C-based technologies and rapid accumulation of data challenge the computational analysis and interpretation. Here, we describe the key features of 3C-based data analysis, with key steps outlined in 1.1.2.1Raw reads are pre-processed by filtering out PCR duplicates and potential artifact reads reduces false-positive signals. Sequencing adaptors can also be removed prior to alignment. There are two types of alignment strategies, the full-read approach and chimeric alignment. The full read alignment method employs standard alignment software such as Bowtie2  or the B1.1.2.2In 3C analysis, the signal-to-noise ratio decreases with increased distance between two target loci. To overcome this limitation, binning is employed in more advanced 3C-based techniques. A bin is a fixed, non-overlapping genomic span into which reads are grouped to increase the signal of the interaction frequency. Smaller bins usually are used for more frequent intra-chromosomal interactions, and larger bins are for less frequent inter-chromosomal interactions . As a ge1.1.2.3Several biases arise as a result of the experimental steps. The goal of normalization is to reduce such biases. Normalization also enables the direct comparison of data from different replicates and conditions on a common scale. There are two general approaches for bias correction: explicit and implicit normalization. Explicit models take into account of known bias factors. In Hi-C experiments as an example, several systematic biases influence the Hi-C read counts, including the distance between restriction enzyme cut sites, the GC content of trimmed ligation junction and uniqueness of sequence reads . In orde1.1.2.4The most popular and intuitive algorithms for identifying intra-chromosomal interactions, known as TADs, include the directionality index (DI)  and the Most TAD calling tools have the options for both DI and ID for TAD calling. For example, TADtool (as a Python package) enables the direct export of TADs called using a set of parameters for both directionality and insulation indices . Other TMost research in this area has focused on the interactions within individual chromosomes, and those between different chromosomes have received less attention. A major challenge is the identification of reliable and reproducible inter-chromosomal contacts; for example, false inter-chromosomal fragments could result from random ligations and in which case the contact profile shows an enrichment of inter-chromosomal interactions and a depletion of intra-chromosomal ones . As the Hi-C dataset analysis requires powerful computers with high computing capacity as numerous interactions between all loci are examined. Although standard computers equipped with high-performance specs are usually sufficient for standard Hi-C analysis, some software packages require specialized hardware. For instance, HiCCUPS requires a general-purpose graphics processing unit (GPU) due to the large number of pixels (trillions) in a kilobase-resolution Hi-C map . In some1.1.2.5Chromatin interactions can be visualized as a heatmap in which the x- and y-axes represent loci in genomic order, and each pixel is the number of observed interactions between them. Plotting contact probabilities versus genomic distance typically reveals an inverse relationship between these two parameters. Hi-C data can be visualized using Juicebox , my5C 7 and 3D g1.2The spatial organization of the genome, and thus, cellular functions are also regulated at the primary scale. Chromatin compaction is determined by nucleosome density. Genomic regions with dense nucleosomes are more tightly packed , whereas nucleosome-depleted regions are more accessible  for interactions with regulators and are therefore regarded as the primary locations of regulatory elements. Currently, NGS enables genome-wide investigations of chromatin accessibility ,86,97. I1.2.1Currently, the most widely used methods for assessing primary-order chromatin state include MNase-seq, DNase-seq, FAIRE-seq and ATAC-seq . For MNaIn contrast, DNase-seq was developed to identify open chromatin regions based on the notion that accessible regions of the genome show hypersensitivity to DNase I endonuclease . Upon enFAIRE -seq ,92 is a ATAC (assay of transposase-accessible chromatin)-seq identifies open and closed chromatin. The Tn5 transposase cleaves DNA fragments from open chromatin regions. After cleavage, Tn5 inserts adaptor sequences into integrated sites, eliminating additional ligation steps prior to sequencing. In addition to a simplified sample processing procedure, ATAC-seq generally requires two to four orders of magnitude fewer tissues/cells see . Most AT6–107 cells [For both animals and plants, 500–50,000 fresh cells are adequate, as opposed to MNase-seq or DNase-seq which requires at least 1007 cells ,62. The 07 cells ,51.https://www.encodeproject.org/about/experiment-guidelines).For all above methods, at least two biological replicates are necessary to ensure the reproducibility. Based on the ENCODE Experiment Guidelines, the replicates must be independently derived from the same cell/tissue type/state. To be considered as reproducible data, the following criteria should be met: a) the number of mapped reads and the length of target lists from replicates should be within a factor of two of each other, and either b) 80% of the top 40% fraction of the target lists of the two replicates should overlap and same for the reciprocal, or c) there must be >75% of targets in common when all available reads of both replicates are compared  represent transcription factor binding sites. ATAC-seq data containing specifically mapped fragments below 38 bp are removed, as 38 bp is the minimal distance between neighboring transposition sites generated by the Tn5 transposase [1.2.2.2http://broadinstitute.github.io/picard/). The size distribution of inserts in a successfully prepared library depicts an array spanning five to six nucleosomal units. In addition to examining read abundance at the locations of certain genetic features, the visualization of read abundance across the entire genome provides a general read density profile. Publicly available genome browsers, such as Integrative Genomics Viewer (IGV)  have been demonstrated to be accessible chromatin locations. Hence, DNase-, FAIRE- and ATAC-seq data are expected to show an overall increase in abundance at these locations, whereas a decrease at TSSs is expected for MNase-seq data. For ATAC-seq specifically, an additional size distribution plot of inserts  can be generated using Picard tools  or open chromatin regions . In some cases, transcription factor binding sites can also be identified when small fragments (25–50 bp) are included in the sequencing library. For better clarity, specific analysis features and tools for each method are discussed individually below.1.2.2.4For MNase-seq data, sequenced in single-end mode, the 5′ end of the mapped sequence for the forward or reverse strand represents the nucleosome border, and the midpoint or full nucleosome length can be identified by shifting the ends 73 bp  employs 1.2.2.5For DNase-seq data analyses, algorithms such as F-seq  and Hots1.2.2.6Paired-end sequencing is performed for ATAC-seq. Paired-end 50-cycle reads generally provide accurate alignments, and approximately 50 million mapped reads are sufficient for human samples . The reahttps://github.com/blikzen/atac-seq).The MACS2 peak caller is a popular tool for ATAC-seq peak calling, as it can detect both narrow and broad peaks and considers the false discovery rate and noise. Similar to MACS2, ZINBA calls both broad and narrow regions of enrichment across a range of signal-to-noise ratios. Additionally, ZINBA accounts for factors that co-vary with the background or experimental signal. Hotspot can detect regions of enrichment of variable sizes and performs automatic normalization for large regions with elevated read levels, reflecting features such as high copy numbers. F-Seq is a Java package that continuously estimates the read density and identifies regions of higher density and was used to identify broad accessible regions in the ENCODE project. In contrast, HOMER was employed to call localized narrow peaks as HOMER was originally developed to identify short (8–12 bp) motifs for ChIP-seq analysis. An R module called “atac-seq” which implements the ATAC-seq pipeline of ENCODE, including F-seq, HOMER, and MACS2, with data visualization was recently made available , combine ultrathin cryosectioning with laser microdissection and DNA sequencing to capture three-dimensional proximities between genomic loci without the ligation step . Based oSimilarly, the profiling of chromatin accessibility often requires a large population of cells. The chromatin landscapes of each cell type are lost when only the average profile is assessed. Hence, the need for epigenetic investigation within complex and heterogeneous tissues drives the development of accessibility profiling techniques at single-cell resolution ,22,82.An investigation of open chromatin regions in single cells has been demonstrated based on a modified DNase I protocol . Using t1.4The higher-order organization of chromatin has implications in major cellular functions . For exa1.5in situ hybridization (FISH) and electron microscopy (EM) can be combined with 3C-based technologies to overcome their limitations in terms of resolution and scale [in situ. Moreover, a recently developed method called NicE-seq (nicking enzyme assisted sequencing) has been demonstrated for its capacity to identify open chromatin regions, and this technique's potential to visualize open chromatin when coupled with fluorescent-labeled dNTPs has been proposed [Other high-throughput technologies have been combined with chromatin conformation capture methods for validating chromatin interactions and examining their biological relevance. Chromatin interaction analysis based on paired-end tag (ChIA-PET) sequencing combines ChIP with chromatin conformation capturing techniques, potentially facilitating the identification of chromatin contacts with sites bound by a protein of interest . Imagingnd scale . Imagingnd scale  developeproposed .cis-regulatory elements responsible for cell differentiation were identified [trans-regulatory elements that induce or suppress cell-to-cell heterogeneity [Integrating chromatin accessibility data obtained from ATAC-seq and other techniques with RNA-seq and ChIP-seq enables researchers to elucidate associations of chromatin states with gene expression and regulation. For example, by correlating the accessibility map generated using ATAC-seq with RNA-seq data, candidate entified . Likewisogeneity . In anotogeneity . These i2Cellular functions are often a consequence of the coordinated action of the chromatin hierarchy. Integrating chromatin studies of higher-order and primary-order structures sheds light on the potential link between these two levels of chromatin structures. For example, it has been demonstrated that genomes from bacteria to mammals segregate into domains wherein segments of DNA preferentially interact, and this preference is associated with epigenetic signatures of the primary chromatin structure. This link between primary-order chromatin accessibility and higher-order chromatin compartmentation was also reported in a single-cell level chromatin profiling of mammalian cells using scATAC-seq . ClearlySeveral limitations challenge the assessment of the higher-order chromatin hierarchy. First, experimental steps including crosslinking, chromatin fragmentation, biotin labeling and ligation introduce biases that complicate the interpretation of detected interactions. Moreover, long-range chromatin interactions and the principles of chromatin dynamics require more accurate, sensitive and reproducible methods. Some of these issues can be addressed by integrating data from multiple biological replicates because higher reproducibility indicates higher reliability and/or stability of the detected interactions. Binning is a critical step that increases the signal of the interaction frequency. Furthermore, most multicellular organism are diploid but the current pipelines for chromatin conformation prediction consider the genome as haploid. To address the issue, single-nucleotide polymorphisms (SNPs) and insertion deletion polymorphisms (Indels) can serve as markers separating sister chromatids; these markers can be incorporated into the computational pipeline to increase the accuracy of chromatin conformation.For primary order structure analyses, future opportunities and challenges include the incorporation of chromatin interactions and accessibility profiles with genetic and epigenetic features to elucidate the intricate regulatory network. Such analyses should also include the association of chromatin interactions and accessibility with allele specificity for functionally relevant SNPs. Combining the results from genome-wide accessibility profiles with quantitative trait locus studies can aid the identification of disease phenotypes. These challenges highlight the need for robust computational tools tailored specifically towards an integrative approach. Furthermore, as single-cell analysis contributes to the clarification of relationships between gene expression and epigenetics, we foresee that this technique will provide new insights into the role of chromatin accessibility in physiological heterogeneity related to cell differentiation, development, health and disease. However, low sequencing coverage is a major issue for single-cell-level techniques which therefore require advancement in sequencing techniques.TADTopology associating domains3CChromosome conformation capture4CCircular chromosome conformation capture5CChromosome conformation capture carbon copyLMAligation-mediated amplificationDIDirectionality indexIDInsulation indexMNase-seqmicrococcal nuclease sequencingFAIREformaldehyde-assisted isolation of regulatory elementsATAC-seqassay of transposase-accessible chromatin sequencingDHSDNase I hypersensitive siteChIA-PETchromatin immunoprecipitation with paired-end tag sequencingFISHin situ hybridizationfluorescence EMElectron microscopySNPsingle-nucleotide polymorphismIndelinsertion deletion polymorphismAll authors contributed to the conception and writing of this manuscript.The authors declare no conflicts of interest.


Pichia pastoris (syn. Komagataella spp.) include overexpression of homologous and heterologous genes, and deletion of host genes. For metabolic and cell engineering purposes the simultaneous overexpression of more than one gene would often be required. Very recently, Golden Gate based libraries were adapted to optimize single expression cassettes for recombinant proteins in P. pastoris. However, an efficient toolbox allowing the overexpression of multiple genes at once was not available for P. pastoris.State-of-the-art strain engineering techniques for the host PiCS system, we provide a flexible modular system for advanced strain engineering in P. pastoris based on Golden Gate cloning. For this purpose, we established a wide variety of standardized genetic parts .With the GoldenPGAP), while all transcription terminators and genome integration loci led to equally high expression strength. These modular genetic parts can be readily combined in versatile order, as exemplified for the simultaneous expression of Cas9 and one or more guide-RNA expression units. Importantly, for constructing multigene constructs (vectors with more than two expression units) it is not only essential to balance the expression of the individual genes, but also to avoid repetitive homologous sequences which were otherwise shown to trigger “loop-out” of vector DNA from the P. pastoris genome.All genetic parts were characterized based on their expression strength measured by eGFP as reporter in up to four production-relevant conditions. The promoters, which are either constitutive or regulatable, cover a broad range of expression strengths in their active conditions  contains supplementary material, which is available to authorized users. Pichia pastoris (syn. Komagataella spp.) is frequently applied for the production of heterologous proteins, most of which are efficiently secreted [P. pastoris such as promoters, signal peptides, selection markers, Flp-frt/Cre-lox recombination and CRISPR/Cas9 have been reviewed recently [P. pastoris is distinguished by its methylotrophy, its Crabtree-negative metabolism, its growth to very high cell densities, the low number and concentration of secreted host cell proteins [The yeast secreted . It is asecreted , pharmacsecreted  and as asecreted . New genrecently . Compareproteins  and the proteins . Genomicproteins .P. pastoris, different highly efficient promoter systems were established  as well as strong constitutive promoters from highly expressed genes  are frequently applied [For recombinant protein production in l et al. ) and appl et al. . The metmethanol , 11. MUT applied . Neverth applied , Delic e applied ). On the applied ). Both oBsaI and BpiI are used which yield four base pair overhangs outside of their recognition sequence. These overhangs can be freely designed and are termed fusion sites (Fs). These fusion sites enable base pair precise assembly of genetic parts such as promoters, coding sequences (CDS) and transcription terminators. By using simultaneous restriction and ligation in efficient one-pot cloning reactions, rapid assembly of multiple DNA fragments is achieved [Today, advanced synthetic biology tools are applied in all fields of microbiology. New cloning methods such as Gateway®, Gibson Assembly and Golden Gate cloning, together with genome editing techniques like CRISPR/Cas9 and TALEN (transcription activator-like effector nucleases), enable efficient and highly specific cell engineering and thereby revolutionized the whole field . Golden achieved .P. pastoris, which were tested for the production of reporter proteins by the assembly of standardized parts such as promoters, ribosome binding sites, secretion signals and terminators in a fast and efficient way. These studies aimed to optimize a single transcription unit for the production of one heterologous protein of interest . Vogl et al. [P. pastoris and could show a strong effect of the inserted promoters when overexpressing the carotenoid pathway . Our study extends the versatile Golden Gate technique for all applications in P. pastoris where the simultaneous integration of multiple DNA products is required  and aims beyond the mere assembly of single expression cassettes for the heterologous protein of interest.Recently, Obst et al.  and Schrl et al.  used GibPiCS (Golden Gate derived P. pastoris cloning system) vector toolkit. GoldenPiCS is part of a universal system termed GoldenMOCS, standing for Golden Gate-derived Multiple Organism Cloning System [PiCS designed for use in P. pastoris and the characterization of its individual genetic parts using eGFP (enhanced green fluorescence protein) as a reporter. Vectors of these systems were deposited at Addgene as GoldenPiCS kit (#1000000133).For this purpose, we adapted the Golden Gate based modular cloning (MoClo) introduced by Weber et al. , to creag System . The GolPiCS, our Golden Gate-derived P. pastoris cloning system, consists of three hierarchical backbone (BB) levels for flexible generation of overexpression plasmids containing multiple transcription units (up to eight per plasmid), four different selection markers and five loci either for targeted genome integration or episomal plasmid maintenance . Contrary to other cloning techniques, Golden Gate Assembly avoids the need for excessive sequencing, because BB2 and BB3 constructs are assembled by ligation instead of overlap-extension PCR (only BB1 inserts require sequencing after assembly). Correct ligation is assured by defined fusion sites  or related expression vectors, which harbor only one transcription unit . High clonal variation prompted us to analyze gene copy numbers (GCN) of integrated genes and we found that individual transcription units were lost. Similar results have been obtained with PGAP or PAOX1 based multicopy vectors [PGAP and ScCYC1tt sequences) resulted in recombination events  during transformation.Initially, we started with Golden Gate vectors carrying up to four transcription units with the same promoter and transcription terminator  is changed to ‘C’ (AAAACACC). While PGAP variants with ‘A’, ‘T’ and ‘C’ at position ‘-1’ performed similarly, the variant with ‘G’ resulted in a lower eGFP level . The Kozak consensus sequence of P. pastoris was analyzed and found to be similar to that of S. cerevisiae, which is rich in ‘A’ and poor in ‘G’ bases  and a slightly increased expression of eGFP was found  as present in batch cultivation, limiting glucose  and methanol feed , the latter two representing conditions as encountered during fed batch cultivation. PGAP was used as reference to evaluate the expression strength of the promoters. PTEF2, PGPM1, PRPP1B, PPDC1, PPOR1, PADH2, PFBA1–1, PRPL2A, PLAT1, PPFK300 and PMDH3 were confirmed to have a constitutive regulation with a range of eGFP expression of 2–192% of PGAP in all tested conditions , glycerol (PGUT1) and methanol  were well repressed (0% of PGAP) and induced (to 18–160% of PGAP) in the repressed and induced conditions, respectively , appearPGAP_eGFP_ScCYC1tt in different positions of the vector as readout, resulted in complete vector integration for more than 97% of all P. pastoris transformants, although we observed a slight efficiency decrease with increasing distance from the selection marker . To further increase our repertoire for strain engineering purposes, Golden Gate constructs containing a single eGFP transcription unit (PGAP_eGFP_ScCYC1tt) targeted to different integration loci  were analyzed. The eGFP levels were similar with all tested constructs expressing from different genomic loci in P. pastoris  and single guide RNA (sgRNA) on one single episomal plasmid and test them for their efficiency to perform InDel mutations in P. pastoris  and the SUP4 terminator from S. cerevisiae [hcas9 controlled by PScTEF and ScCYC1tt, but we could not obtain InDel mutations in P. pastoris. Next, we tried the strong RNAPII promoter PGAP and flanking self-splicing hammerhead  and hepatitis delta virus  ribozyme sequences for correct processing of the sgRNA [P. pastoris, we exchanged the ScCYC1tt terminator of the sgRNA transcription unit for the P. pastoris-derived transcription terminator RPS25Att to avoid repetitive sequences. Regarding the expression of hcas9, we obtained similarly high efficiencies with different promoters, however, growth was weaker with PScTEF1 while it was almost unaffected when using PLAT1 or PPFK300. Targeting efficiency was mostly dependent on the applied sgRNA sequence, as we found large differences for several examples: At least two different sgRNAs designed by CHOP CHOP [sgRNAs each targeting AOX1 and DAS2, which are non-essential on glucose, resulted in largely different efficiencies of 38% vs. 100% and 0% vs. 100%, respectively. Therefore, we recommend to test at least two different sgRNAs for each target sequence.Efficient genome editing by the CRISPR/Cas9 system was shown in many organisms including pastoris . Howeverris Fig. . The asson locus . Initialrevisiae , and hcahe sgRNA  and obsehe sgRNA . To reduHOP CHOP  were tesPiCS to assemble several expression cassettes on one vector and to rapidly create new variants by exchanging parts like promoters, terminators or expression sequences. The GoldenPiCS based vectors for the described CRISP/Cas9 approach are available as separate kit at Addgene  This allowed rapid optimization of a CRISPR/Cas9-BB3 for efficient InDel mutations in P. pastoris within a short time.With this example we demonstrate the suitability of GoldenP. pastoris has been shown to improve bottlenecks of protein synthesis, folding and secretion [P. pastoris [P. pastoris and fine-tuned by using a set of MUT-related promoters and terminators constructed by Gibson assembly [PiCS, a Golden Gate based modular cloning system for genetic engineering of P. pastoris. Both systems facilitate the assembly of multiple transcription units with the possibility to fine-tune the expression of each target individually. In our opinion, Golden Gate cloning has crucial advantages such as its low price, broad flexibility and high efficiency. These advantages have inspired several research groups to apply Golden Gate cloning for their purposes. So far, Golden Gate based screening in P. pastoris was dedicated to design and optimize the expression of a single recombinant gene for its production in P. pastoris by high throughput testing of different promoters and secretion signals [PiCS system is aimed to facilitate cell engineering by allowing the overexpression of multiple genes e.g. redox partners or metabolic enzymes that act in a common pathway. Therefore, our system allows for the assembly of up to eight expression units on one plasmid with the ability to use different characterized promoters and terminators for each expression unit. The latter was proven to be essential to obtain stable transformants. The toolbox described by Obst et al. [PiCS system is not primarily aimed for the expression screening of the heterologous protein itself , but dedicated to combinatorial cell engineering strategies or the expression of whole metabolic pathways. We have thus added an example on the assembly of CRISPR/Cas9 vectors with 2 expression cassettes, where the issue of stability with repeated sequences (and its solution with the promoter library) is illustrated, as well as the advantage of fast assembly of elements. Aside from the development of the GoldenPiCS toolkit, we have invested effort to assay promoter and terminator strength in different conditions, to validate the effect of the ‘-1’ position in front of the start codon and to present data for the ‘loop-out’ effect in P. pastoris transformants. Importantly, we found that repetitive sequences on the expression vector lead to unwanted recombination events and therefore must be avoided.Advanced synthetic biology tools revolutionized genetic engineering and are applied for many different organisms today. Strain engineering of ecretion , 6. Recepastoris , as werepastoris . For sucassembly , 33. At  signals , 19. In t et al.  is basedP. pastoris: GoldenPiCS consists of 20 P. pastoris promoters, 10 terminators , 4 integration loci  and one locus for episomal plasmid maintenance, as well as 4 resistance marker cassettes . With the currently available set of fusion sites, assembly of up to eight expression units per plasmid is possible. All of these are available through Addgene  and allow high throughput assembly of multigene constructs for cell and metabolic engineering purposes.Overall, we present the hierarchical multi-organism modular cloning system (GoldenMOCS) and provide several modules and plasmids for Escherichia coli DH10B (Invitrogen) was used for plasmid amplification. Promoter and terminator studies were done in P. pastoris (Komagataella phaffii) CBS7435(MutS), obtained from Helmut Schwab, Graz University of Technology, Austria. P. pastoris clones were screened in 24- deep well plates  using appropriate media (complex YP media or synthetic M2 screening media) [P. pastoris by electroporation  according to [PiCS module sequences and backbones are listed in Additional file Primer design and in silico cloning was performed using the CLC Main Workbench Version 7.7.3. GoldenP. pastoris . The system is generally comprised of three backbone (BB) levels. BB1 constructs harbor the three basic modules , BB2 constructs are used to assemble transcription units (promoter + CDS + terminator) and BB3 are used to further combine multiple transcription units  which cut outside of their recognition site and enables scarless cloning, assembly of multiple DNA fragments and efficient one-pot cloning reactions . Therefore, internal BsaI and BpiI restriction sites must be removed from all modules by introducing point mutations, respecting the codon usage of the host organism .BsaI and BpiI, which yield four base pair overhangs outside of their recognition sequence. These overhangs - termed fusion sites (Fs) - can be freely designed and are used to systematically assemble modules in the GoldenMOCS.Golden Gate cloning applies the two type IIs restriction endonucleases PiCS include basic modules , resistance cassettes, integration sites, and linkers  to prevent transcriptional read-through from the resistance gene). The following nomenclature is used for basic modules: PXXXn or pXXXn for promoters, YYYn for coding sequences and ZZZntt for terminators. Modules from other organisms are indicated by the initials of the species name, e.g. ‘Sc’ for S. cerevisiae.Modules of the GoldenE. coli, a resistance cassette  and pSTBlue-1 , respectively (with kanamycin/ampicillin resistance). All recipient backbones are comprised of an origin of replication for BsaI sites and two appropriate fusion sites: Fs1-Fs2 to integrate into recipient BB1_12 (for promotor modules), Fs2-Fs3 to integrate into BB1_23 (for CDS modules) and Fs3-Fs4 to integrate into BB1_34 (for terminator modules). Multiple fragments (e.g. to introduce mutations or to create fusion genes) can be assembled in the BB1 assembly reaction by appropriate fusion site design. All inserts which were assembled into BB1 need to be checked by sequencing.The three basic modules promoter, CDS and terminator are assembled into BB1 using primers with Single transcription units  are assembled into a recipient BB2 using the fusion sites Fs1, Fs2, Fs3 and Fs4. Depending on the intended position of the transcription unit in BB3, the appropriate BB2 is used: BB2_AB with FsA-FsB for the first, BB2_BC with FsB-FsC for the second position, etc.BpiI restriction sites and fusion sites Fs1-Fs4 (e.g. BB3aN_14) can be done.Multiple transcription units are assembled into a recipient BB3 using fusion sites appropriate for the number of transcription units (e.g. A-C for two transcription units). For overexpression of a single transcription unit, direct cloning from BB1 into a special BB3, equipped with a BB2 linker with BpiI Golden Gate Assembly reaction with the following modules: linker, resistance cassette, integration locus and Ori modules - including appropriate flanking fusion sites . In order to create recipient BB3 for direct cloning with BB1, the linker with fusion sites FsA-FsB can be replaced using a BsaI reaction with BB2_AB – thereby introducing the BB2 linker with BpiI restriction sites and fusion sites Fs1-Fs4. Amplification and sequencing primers are included in Additional file De novo assembly of BB3 plasmids can be done using a BB3 plasmids for CRISPR/Cas9-mediated genome editing were assembled as usual recipient BB3, consisting of resistance cassette, Ori, CEN/ARS locus and a linker containing fusion sites FsA-FsC for integration of two transcription units , 40 U T4 Ligase (0.1 μL), 2 μL CutSmart™ Buffer , 2 μL ATP  and 40 nM dilutions of PCR fragments and/or carrier and recipient backbone were diluted in 20 μL total volume and incubated as follows: 8 to 50 cycles (depending on insert number) of each 2 min at 37 °C and 16 °C, followed by 10 min at 37 °C, 30 min at 55 °C and 10 min at 80 °C .One μL P. pastoris transformants were cultivated at 25 °C on a rotary shaker at 280 rpm. Screening conditions were designed to represent bioreactor cultivation phases  and methanol feed (“M”), representing fed batch conditions, were measured at an OD600 of about 10 and growth rates around 0.04 h−1 and μMAX-MeOH (up to 0.1 h−1), respectively. Growth rates and biomass increase can roughly be calculated from the substrate yield coefficient, which is YX/S ~ 0.5 for μ > 0.05 h−1 on glucose [X/S ~ 0.6 on glycerol [X/S ~ 0.4) and methanol culture lag phases are prolonged [For evaluation of promoter and terminator function (screening),  glucose  and YX/Sglycerol , while irolonged .P. pastoris wild type cells) and related to expression under the control of PGAP. Indel mutation screenings with CRISPR/Cas9-BB3’s were done in a CBS7435(MutS) strain stably expressing eGFP under control of the PGAP promoter (integration in the native PGAP locus). Disruption frequency of eGFP (InDel mutations) was analysed by flow cytometry and verified by sequencing of individual clones.Analysis of eGFP levels in screenings and corresponding calculations were done as described before , 41. BriAOX1 and DAS1 at two different positions each. CRISPR/Cas9-BB3s plasmids harboring the Cas9/sgRNA transcription units were transformed into electro-competent P. pastoris by electroporation  according to [Targeting efficiency of the modular CRISPR/Cas9 system on native sequences was evaluated by disruption of the coding sequences of Additional file 1:Table S1. Gene copy numbers of four GOIs in three engineered Pichia pastoris strains after three consecutive batch cultivations. Table S2.P. pastoris deep-well screening conditions. Table S3. Selection markers. Table S4. sgRNA sequences for CRISPR/Cas9 and verification primers for InDel mutations. (PDF 277 kb)File contains additional Tables S1-S3. Additional file 2:PiCS modules and plasmids. Modules and plasmids are listed with corresponding cloning- and fusion sites and full sequences. DNA orientation is 5’to 3′. All plasmids are available at Addgene. (XLSX 33 kb)Golden


Here we describe a sensitive and novel method of identifying endogenous DNA–DNA interactions. Capture of Associated Targets on CHromatin (CATCH) uses efficient capture and enrichment of specific genomic loci of interest through hybridization and subsequent purification via complementary biotinylated oligonucleotide. The CATCH assay requires no enzymatic digestion or ligation, requires little starting material, provides high-quality data, has excellent reproducibility and is completed in less than 24 h. Efficacy is demonstrated through capture of three disparate loci, which demonstrate unique subsets of long-distance chromatin interactions enriched for both enhancer marks and oestrogen receptor-binding sites. In each experiment, CATCH-seq peaks representing long-distance chromatin interactions were centred near the TSS of genes, and, critically, the genes identified as physically interacting are shown to be transcriptionally coexpressed. These interactions could potentially create transcriptional hubs for the regulation of gene expression programmes. Chromatin architecture is a key regulator of transcriptional processes, however current methods to investigate it have technical limitations. Here, the authors describe a novel chromatin capture technique, CATCH, which can be used to identify and characterize complex genomic interaction networks. Chromatin architecture is a key regulator of many aspects of cell biology, including gene transcription, DNA repair processes, DNA replication and long-term processes such as X-chromosome inactivationTranscriptional enhancer regions are hubs of transcription factor binding, and are thought to underlie a significant portion of the tissue-specific expression of many gene targets56The current benchmark assay for detecting long-distance chromatin interactions is Chromatin Conformation Capture (3C)To overcome the current technological limitations that constrain the field of DNA–DNA interaction research, we have developed a streamlined, novel protocol named Capture of Associated Targets on CHromatin (CATCH). Similar to traditional 3C, CATCH relies on chemical crosslinking to capture naturally occurring nucleic acid–protein interactions. However, CATCH relies on an unbiased sonication approach to shear DNA, similar to ChIP assays. A genomic locus of interest is enriched through hybridization and subsequent purification using a complementary biotinylated oligonucleotide. Owing to the use of formaldehyde crosslinking, this purifies both the targeted DNA sequence and any interacting nucleic-acid segments. Finally, following de-crosslinking, the resulting DNA sample is subjected to PCR or sequencing to identify interacting fragments. The CATCH assay has significant and extensive list of advantages over 3C-derived technologies, which is considered at length in the discussion section below.SIAH2 gene, which had been previously analysed using chromatin interaction analysis by paired-end tag sequencing (ChIA-PET). SIAH2 (3q25.1) is an E3 ubiquitin ligase whose upregulation correlates with ER activation and has been linked to poor outcome in breast cancer patients14SIAH2 gene transcriptional control is poorly understood: the only confirmed genomic loop within SIAH2 occurs between an intronic oestrogen response element (ERE) and downstream ERESIAH2 regulation, as well as attempt to recapitulate the previously demonstrated looping events around SIAH2, we perform next-generation sequencing after CATCH of the SIAH2 downstream enhancer. In addition, we demonstrate the reproducibility of CATCH using distinct pulldowns near the SIAH2, EIF4A1 and MYC genes. These experiments also show that CATCH-seq peaks are overwhelmingly found overlapping with enhancers (H3K4me1 and H3K27ac enriched) and oestrogen receptor (ER)-binding sites. Finally, these experiments reveal unique subsets of physically interacting gene promoters that are shown to be transcriptionally coexpressed over thousands of data sets using the SEEK search systemIn the present study, we test the effectiveness of CATCH by interrogating a downstream enhancer of the human SIAH2 gene that had previously been shown to interact with a region downstream of the geneB. The human SIAH2 gene consists of two exons and a single intron located on the minus strand of chromosome 3; EREB is located within the intron, ∼6.8 kilobases from the SIAH2 promoter. Because unsheared DNA or over-fixed samples could provide false-positive results, random genomic loci were also tested for interactions within SIAH2. The tested target or random loci ranged in distance between 1.1 and 19 kilobases from EREB  demonstrated that the oligo-targeted downstream ERE (pull down region) was highly enriched when compared with any other genomic site  experiments confirmed that ERα binding was nearly undetectable at the promoter, nor was it responsive to E2 . Those data are represented in graphical form  was demonstrated here in MCF-7 cells, as it was by Fullwood et al. (SIAH2 (distance: 103 kb) was also positively demonstrated, despite its interaction signal appearing ∼2 kb from the previously identified ERα-binding site  was also shown to occur as previously identified  this overlap increased to over 80% . Previous studies produced data, suggesting that the promoter region of the human  control . Interes control . Analysiover 80% . By contrichment . In addieriments .MYC gene was interrogated in a similar manner  and the SIAH2 intron  and promoter , suggesting that oestradiol treatment was not responsible for completely rearranging genomic structure  in the presence of oestradiol  was employed. SEEK determines gene expression correlation by weighting available gene expression data sets based on input genes of interestIn order to test the hypothesis that a single enhancer is capable of interacting with, and altering the transcription of, multiple gene targets on the same chromosome, the SEEK algorithm  could only identify an average of nine genes in common with the CATCH-seq experiment  specific to each CATCH-seq experiment; each SEEK list was then sorted based on the highest coexpression value. The top 100 coexpressed genes from the pull-down chromosome of interest for each CATCH-seq experiment were denoted by the SEEK list. A flowchart describing the processing of each data set can be found in periment , right. periment , left. Sion list . Similart random , as the t random .SIAH2 (SIAH2 CATCH-seq experiment. The majority of genes predicted to be coexpressed were identified in both the vehicle- (93%) and oestradiol-treated (74%) conditions  spacer that eliminated steric hindrance between the biotin moiety and the target DNA–protein complexes, allowing full accessibility to the streptavidin magnetic beads. It was also determined that a desthiobiotin moiety could be used in place of biotin, allowing for a gentler elution from the beads with the addition of excess biotin as shown previouslyB and the ERE downstream of the SIAH2 geneSIAH2 and multiple enhancers and promoters spanning the entirety of chromosome 3; this finding also held true for loci on chromosomes 8 and 17. While the data presented here support the idea that gene promoters are being physically linked, the biochemical data paint a slightly different picture. Traditionally, gene promoters are thought to span ∼5 kbp upstream of a genes TSS, however our CATCH-seq data suggest that the average chromatin-looping interaction involving the TSS region of genes occurs between 50 and 200 bp downstream of the TSS. These findings could be significant for future research projects interested in the specific nature of chromatin architecture and the potential DNA motifs that may coordinate such interactions.In this study, we demonstrated that CATCH could not only recapitulate previous findings, but was also able to detect previously unreported long-distance chromatin interactions. Earlier ChIP-3C studies demonstrated an interaction between the intronic EREThe idea that multiple promoters could be involved in a single ‘hub' of chromatin interaction is not novel, but has little experimental evidence to date. The data presented here strongly support the hypothesis that single enhancers can regulate a host of genes, even at linear distances of multiple millions of base pairs. While the exact mechanism by which these transcriptional hubs may function is yet unknown, our data demonstrate that subsets of genes, spanning entire chromosomes, can physically associate with the same enhancer, and that a highly significant portion of those genes are coexpressed within the cell. In relation to these transcriptionally associated DNA–DNA interactions, the CTCF protein has been implicated in mediating such looping10 of the CATCH P value (for SEEK gene prediction) was plotted on the y axis against the number of CATCH genes identified in the analysis on the x axis. Several interesting points arose from these analyses. First, the approximate resolution of CATCH's transcriptional coexpression-predictive power (as measured by SEEK list prediction) increases with decreasing SEEK gene depth. This effectively suggests that CATCH is more reliable at predicting the most significant SEEK genes, as might be expected with such complex biology. Second, while each CATCH experiment has slightly different effective resolution, they all trend similarly; on average, the effective resolution of CATCH falls between identifying ∼100–200 genes. This, to a degree, attempts to measure the resolution of the assay, not in base-pair like ChIP, but in number of identified genes, making CATCH a technique that functions very well in predicting large cohorts of transcriptionally coexpressed genes, but less reliably for single locus–locus contacts. Attempting to identify fewer genes than the effective resolution of CATCH may not result in the identification of statistically significant coexpressed genes, as it may be influenced by noise and the variations inherent to the complex nature of this biology. Interpretations of single-gene locus–probe interaction should be used with caution. Nonetheless, by summarizing interactions to hundreds of identified genes, this analysis illustrates the collective effect of interactions in mediating gene coexpression.The limitations of the CATCH assay are apparent, not from a base-pairs-of-resolution standpoint like ChIP, but seem to be more attached to the number of CATCH interactions needed to begin to statistically identify subsets of interacting genes. This point is illustrated in In summary, these studies describe and validate a novel next-generation technique for the detection of DNA–DNA interaction called CATCH. Importantly, this technique has demonstrated the ability to detect previously undetectable long-distance chromatin interactions, suggesting that genome-quaternary structure may be much more complex than initially believed, and that it could play a significant role in the expression of entire gene programmes. This revelation would be highly significant in the areas of epigenetics, disease therapy and genome biology.6 cells per sample) were fixed for 6 min at room temperature with a final concentration of 1% formaldehyde  at ∼50% culture confluency. Crosslinking was quenched for 10 min at room temperature by the addition of Tris-HCl pH 8.0 to a final concentration of ∼0.125 M. Next, the cells were harvested via scraping in 1 ml of PBS into a 1.5 ml Eppendorf tube, and then spun at 250g for 8 min . The supernatant was aspirated and the cells were resuspended in 500 μl of cold Nuclear Isolation Buffer supplemented with a protease inhibitor cocktail . The samples were dounce-homogenized 20 times with a tight-fitting pestle and centrifuged again for 10 min at 750g to pellet nuclei. The supernatant was aspirated and the nuclear pellets were resuspended in 100 μl of CATCH buffer supplemented with protease inhibitor cocktail. The samples were sonicated for two cycles  of 8 min each in a Diagenode BioRuptor sonication device, and the cellular debris was pelleted by centrifugation at 24,000g for 15 min at 4 °C. Sonication efficiency was then assessed on a 1.5% (w/v) agarose gel. Genomic DNA fragments should largely fall between 100 and 500 bp. Next, the sheared chromatin sample was incubated at 58 °C for 5 min to unmask biotin on endogenous proteins. Then, 10 μl of pre-equilibrated (in CATCH buffer) streptavidin magnetic beads (Thermo Scientific) were added to each sample. The samples were incubated for 1 h at room temperature while gently rotating. Next, the magnetic beads were extracted and the supernatant was transferred to a clean PCR tube. To each sample, specific biotinylated oligonucleotide probe (Integrated DNA Technologies) was added to a final concentration of ∼300 nM. The probe was then hybridized by incubating the samples as follows: 25 °C for 2 min, 81 °C for 4 min (denaturation), 72–42 °C decreasing gradient (12 s per degree), 42 °C for 30 min (hybridization), followed by storage of the sample at 25 °C. It is important to note that, during testing, denaturation temperatures below 75 °C or above 85 °C were detrimental to oligonucleotide annealing or long-range interaction detection, respectfully; impact on interaction detection at 81 °C was undetectable. The hybridized sample was then transferred to a new 1.5 ml Eppendorf tube and any unhybridized biotinylated oligo was removed with an Illustra Sephacryl (S-400HR) spin column, according to the manufacturer's instruction. The cleared product was again transferred to a new 1.5 ml Eppendorf containing 300 μl of nuclease-free H2O. Next, 25 μl of pre-equilibrated (in CATCH buffer) streptavidin magnetic beads were added to each sample. The samples were incubated at room temperature for 1 h while gently rotating. The beads from each sample were then immobilized on a magnetic stand and washed five times in CATCH buffer at 42 °C while shaking at 1,000 r.p.m. in a thermomixer. The beads were then resuspended in 150 μl of de-crosslinking buffer supplemented with 5 μl of 20 mg ml−1 Proteinase K. The sample was incubated at 55 °C for 30 min to while shaking at 1,000 r.p.m. on a thermomixer, followed by incubation at 65 °C overnight on the same thermomixer. Finally, the sample was incubated at 100 °C for 60 s to destroy any remaining biotin–streptavidin binding and elute the DNA from the magnetic beads. The supernatant was immediately transferred to a new 1.5 ml Eppendorf tube. The DNA was then purified using phenol–chloroform–isoamyl alcohol, and then precipitated in 100% ethanol using glycogen (Thermo Scientific) as a carrier. The DNA was pelleted by spinning at 24,000g for 25 min at room temperature, and resuspended in TE buffer. A complete user protocol is available in the This is an original protocol. What follows is an abbreviated version; the full detailed user version is available below, including all buffer recipes. MCF-7 or T-47D cells  heat-inactivated fetal bovine serum and 100 U ml−l penicillin–streptomycin. Cells were housed at 37 °C in 5% CO2 for a maximum of 12 passages after being purchased directly from the ATCC. The cells used in MCF-7 (American Type Culture Collection (ATCC); HTB-22) and T-47D  cells were maintained in phenol red-free RPMI 1640 with http://zlab.bu.edu/clover/) programmeSIAH2 gene ±100 kb. The resulting potential binding sites were then cross-referenced to previously identified ER-binding sites within MCF-7 cellsUsing the freely available CLOVER (g for 15 min at 4 °C. Sonication efficiency was then assessed on a 1.5% (w/v) agarose gel. Genomic DNA fragments largely fell between 100 and 700 bp. Next, the sheared chromatin sample was diluted to 1 ml in ChIP Dilution Buffer  supplemented with protease inhibitors. Here 10% of total volume was taken as input. Then, 2 μg of anti-ERα  or rabbit IgG antibody was added to each sample, and the samples were rotated overnight at 4 °C. Next, magnetic protein-G Dynabeads (Invitrogen) were washed once in PBS supplemented with 5% BSA and resuspended in ChIP dilution buffer. Then, 30 μl of the pre-washed beads were added to each sample, and the samples were rotated at 4 °C for 2 h. The beads were then washed consecutively in ChIP Wash Buffer I , ChIP Wash Buffer II , ChIP Wash Buffer III  and TE buffer. The beads were then resuspended in 100 μl freshly made ChIP elution buffer (200 μl of 10% SDS and 0.168 g of NaHCO3 in 2 ml of H2O). Next, the samples were incubated at 65 °C for 15 min to elute the complex from the beads. That process was repeated and the eluates were combined. Finally, 8 μl of 5.0 M NaCl was added to each sample (including input samples) and they were incubated overnight at 65 °C. Samples were incubated with RNase and Proteinase K before processing with the QIAquick PCR purification kit (Qiagen) according to the manufacterer's instructions. PCR primers for individual ChIP experiments are detailed in Cells were fixed with 1% formaldehyde for 10 min at room temperature. Reaction was quenched with glycine, and cells were centrifuged to pellet and resuspended in ChIP lysis buffer  supplemented with protease inhibitors. The cell slurry was incubated for 10 min on ice and then sonicated for three cycles  of 7 min each in a Diagenode BioRuptor sonication device, and the cellular debris was pelleted by centrifugation at 24,000For DNA (10 μl) from CATCH final elution was immediately (without freezing) put through the second-strand synthesis protocol using NEBNext Module #E6111S according to the manufacturer's instructions. Nucleic-acid-binding beads were AMPure XP #A63881, purchased from Agencourt. Next, the DNA template was made into a sequencing library using the KAPA Biosystems library kit #KK8232 following the manufacturer's instruction. The KAPA kit was critical as it produces a library with fewer ‘bead swap' steps, allowing you to retain a better DNA template yield, and thus makes a library from less starting material. A complete user protocol is available in the http://seek.princeton.edu/, and is a web application stemming from research carried out at the Princeton UniversitySIAH2 was not used as a ‘seed' gene, despite being identified in the associated CATCH experiment, wherein the downstream enhancer of SIAH2 was captured). Using those guidelines, the three gene promoters nearest the CATCH capture site were chosen as input to determine the list of coexpressed genes via SEEK. Complete details can be found in P value was determined using a t distribution. Only genes from the specific pull-down chromosome were used in this calculation. This was also considered optimal, as we were testing the viability of CATCH to predict gene coexpression, not the inverse. A flowchart detailing the steps of this analysis can be found in The SEEK algorithm can be found here CATCH-seq data sets: Each CATCH-seq experiment was performed alongside an unfixed control experiment using an identical capture oligo. The raw data underwent FASTQ Groomer processing before being aligned to the hg19 build of the chromsome of interest using Bowtie 2. First, an unfixed control pulldown  using the same biotinylated oligonucleotide is normalized from the experimental pull-down data by aligning unfixed control reads (.bam) and ‘subtracting' from the experimental reads, directly, to remove any background signal using the bamCompare function in Galaxy deepTools2. The data were then subsetted by individual chromosome  in R, and then by signal threshold . The identification of that threshold determined the signal strength at which CATCH peaks were defined as peaks; with the threshold determined, those CATCH peaks that satisfied the signal strength threshold in the BIGWIG of respective pulldown were next called. Next, gene promoters that had peaks within 2 k of their promoters were then annotated and considered as interactions with the pull-down locus. The top 500 (highest peaks) genes were then assessed to determine the three closest CATCH-identified genes to the pulldown. These three genes were used as the ‘seed' for creating the SEEK list, which is described above. In the case of P value at which CATCH's ability to predict SEEK gene coexpression became nonsignificant. Enhancers: to determine the location of enhancers, ChIP-seq data from both H3K4me1 and H3K27ac were used. Peaks were called using the MACS  function of Galaxy, and peak locations of at least 1 bp overlap between H3K4me1 and H3K27ac signal were identified. The combined distance of the two peaks was merged into a single peak, denoted an Enhancer, and made into a BED file for further use. ER binding: locations of ER binding were determined as above, instead using ERα ChIP-seq data and without combining any other data sets. CTCF binding: locations of CTCF binding were from CTCF-binding data from T47D cells (GEO accession: GSM803348). CATCH-seq gene identification: to ensure that only the most significant CATCH-seq peaks were used for analysis, gene promoters with peaks within 2 kb of their TSS were identified. If multiple peaks occurred near a TSS, only the most robust peak was considered. Then, the 500 genes with the strongest CATCH-seq signal peaks were identified for use in subsequent analyses. CATCH–enhancer adjacency/overlap: CATCH-seq signal strength (peak height) ranging from 100 to 500 was analysed. CATCH peaks were determined by filtering based on the strength of the signal in BIGWIG files of the respective pulldown. Any CATCH-seq peak within 2 kb of an enhancer region (as defined above) was considered to be adjacent or overlapping, thus achieving our criteria for being considered an overlap in these analyses. TSS density plot: the plot(density(x)) function in R was used to plot CATCH-seq signal strength at locations within 2 kb up- and downstream of every TSS on a chromosome . That signal density plot was used to determine the average location of signal ‘peaks' near gene TSS. All R scripts are available in the online All R-codes are available upon request. All data analyses were performed using R version 3.2.2 within RStudio. Codes for all analyses are available upon request; however, the method will be covered briefly here. ERα ChIP-seq BED file data from MCF-7 cells  were obtGSM803348. The data that support the findings of this study are available on request from the corresponding author . The novel sequencing data from this study are available at the Gene Expression Omnibus (GEO), under accession code GSE85762. All original protocols related to CATCH and CATCH-seq library generation are also available upon request.Previously published CTCF-binding data from T47D cells are available at the GEO under accession code How to cite this article: Bourgo, R. J. et al. Capture of associated targets on chromatin links long-distance chromatin looping to transcriptional coordination. Nat. Commun. 7:12893 doi: 10.1038/ncomms12893 (2016).Supplementary Figures 1-10, Supplementary Tables 1-5 and Supplementary MethodsSupplementary R codes for analyzing CATCH data. The two files included here are basic R code for finding CATCH peaks near enhancers with experiments using single, or multiple replicates, respectively. The codes also contain portions to output graphs of the distribution of average distance of peaks from promoters, as well as potential overlap with BED files, such as those resulting from ChIP experiments. The code provided herein allows all analysis done in the manuscript, as detailed in the Methods section.


Sargassum fusiforme, has previously been shown to alleviate oxidative damage during the aging process in mice, but whether SFPS could extend the lifespan of an organism was not demonstrated. Furthermore, the precise component within SFPS that is responsible for the antioxidant activity and the underlying mechanism of such activity was also not resolved. In this study, SP2, a fucoidan derived from SFPS, was shown to exhibit strong antioxidant activity as measured by in vitro radical-scavenging assays. SP2 also improved the survival rate of D. melanogaster subjected to oxidative stress. The flies that were fed with a diet containing SP2 from the time of eclosion displayed significant enhancement in lifespan and reduced accumulation of triglyceride at the old-age stage. In addition, SP2 markedly improved the activities of the antioxidant enzymes, superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px) and reduced the contents of the malondialdehyde (MDA) and oxidized glutathione (GSSG) in old flies. Furthermore, SP2 also upregulated the expression levels of the nuclear factor-erythroid-2-like 2 (nfe2l2 or nrf2) and its downstream target genes, accompanied by a dramatic reduction in the expression of kelch-like ECH-associated protein 1  in old flies. Additional support linking the crucial role of the Nrf2/ARE pathway to the antioxidant effect of SP2 was the relatively high survival rate under heat stress for D. melanogaster individuals receiving SP2 supplement, an effect that was abolished by the inclusion of inhibitors specific for the Nrf2/ARE pathway. Collectively, the results indicated that SP2, a S. fusiforme fucoidan, could promote longevity in D. melanogaster by enhancing the Nrf2-mediated antioxidant signaling pathway during the aging process.Damage accumulated in the genome and macromolecules is largely attributed to increased oxidative damage and a lack of damage repair in a cell, and this can eventually trigger the process of aging. Alleviating the extent of oxidative damage is therefore considered as a potential way to promote longevity. SFPS, a heteropolysaccharide extracted from the brown alga  Aging is a time-dependent and gradual decline in the physiological function of an organism, which ultimately results in diseases and death. It is now well accepted that the cause of aging and the factors that promote aging are related to genes, oxidative stress, signaling pathways, and energy metabolism –3. Althonef2l2, the gene encoding Nrf2, has even been proposed to act as a longevity gene  × 100%, where A0 is the absorbance of the DPPH alone, A1 is the absorbance of DPPH+polysaccharide, and A2 is the absorbance of the polysaccharide only.The effect of SP2 on free radical-scavenging activity was evaluated by measuring the level of DPPH-scavenging activity using a DPPH-scavenging assay kit purchased from Nanjing Jiancheng Incorporation . Polysaccharide solution was prepared by dissolving the polysaccharide powder in distilled water as previously described . Next, t3 in a volume ratio of 10 : 1 : 1, while ABTS radical was prepared by mixing the ABTS solution (7 mmol/L) with potassium persulfate (2.45 mmol/L).FRAP and ABTS assays were performed using assay kits purchased from Nanjing Jiancheng Incorporation  but with an additional control consisting of the sample only to account for the absorbance due entirely to the polysaccharide . FRAP reg, the supernatant was used for MDA, CAT, and SOD assays performed with assay kits purchased from Nanjing Jiancheng Incorporation . The principles of the assay kits were based on previously described methods [Twenty-five flies from each group were randomly collected at a specific time and then homogenized as one sample. After centrifugation at 3000 ×  methods , 27.qRT-PCR analysis using the AffinityScript qPCR cDNA synthesis kit. The primers for the target genes were designed based on the sequences retrieved from FlyBase (http://flybase.org). The sequences of the primers are listed in ΔΔCt method with reference to that of the rp49 gene and then normalized to the corresponding control group.Total RNA was extracted from whole flies using the TRIzol reagent. Fifteen flies per sample and three samples per group were taken for total RNA extraction. The total RNA extracted from each sample was then subjected to P < 0.05 level.The data were expressed as mean ± SD of, at least, three separate experiments. Statistical analyses were carried out by two-way ANOVA and Fisher's LSD multiple comparison tests by SPSS 17.0. Differences among groups were considered statistically significant at the S. fusiforme heteropolysaccharide, possesses antioxidant activity and shown that it can significantly alleviate aging-related stresses [in vitro and in vivo methods. SP2 displayed the highest antioxidant activity as shown by radical- and ion-scavenging activities , while sulfate radical, which is a unique modification of fucoidan, accounted for about 15.3% . SP2 alsin vitro antioxidant activity assay and the in vivo oxidative stress resistance assay both demonstrated the remarkable antioxidant capacity of SP2. However, the question as to whether SP2 could promote longevity under normal condition needed to be addressed. First, the flies were reared, from the time of eclosion, on media supplemented with different concentrations of SP2. The result revealed a significant increase in lifespan for the flies receiving SP2 supplement  and its classical inhibitor keap1 in the flies of different ages were measured. The results revealed a remarkable upregulation of the cncC, and dramatic downregulation of keap1 mRNA levels in the old flies that had been given moderate (MSP) and high (HSP) concentrations of SP2 supplement  is one of the most important antioxidant pathways that counteract oxidative stress and damage. Nrf2 is conserved in metazoan, and in  in mice , 24. Whe Figures . The tra Figures . CollectcncC gene and its representative downstream target genes, ho, cat, and gclc, in flies that were given just SP2 supplement were significantly upregulated compared with the control (no SP2 supplement) but declined relative to the control when the flies received both SP2 plus luteolin or ATRA  occurred, which further promoted stress resistance and longevity (Figures Aging is also a process of time-dependent decline in function, with cumulative damage in biomacromolecules and downregulation of cellular defense and damage repair. This is reminiscent of the expression pattern of Nrf2, a crucial stress regulator in the aging process, which is downregulated in aging organisms , 39, alt Figures . Convers Figures . AlthougNrf2 gene induces hyperkeratosis in the esophagus and forestomach, leading to postnatal lethality [However, it must be stressed that the ectopic expression of Nrf2 in an organism can adversely affect its development . For exaethality . It is aethality , 48. TheS. fusiform fucoidan, the fucoidans from other algae have also been shown to enhance the Nrf2/ARE signaling, which can ameliorate liver injury and neurodegenerative diseases [α-L-fucopyranosyl but also contains sulfated galactofucans, glucuronic acid, glucose, or xylose at different locations and to different extents [An increasing number of studies suggest that polysaccharides from other sources such as mushroom, hemp seed, and okra can also upregulate the Nrf2/ARE signaling thus ameliorating oxidative damages, aging, diabetes, and other aging-related diseases –51. In adiseases , 53. Howdiseases , 55. How extents . RelativD. melanogaster, but confirmation of this aspect, including the elucidation of the relationship between microbiota composition and the structure of the SP2, will be a subject of further investigation.Polysaccharides administered via diets would not be directly absorbed by the small intestine , 57, 58,in vitro antioxidant screening and in vivo antioxidant resistance assay. Based on this method, SP2, a fucoidan extracted from the S. fusiforme heteropolysaccharide SFPS, was shown to have longevity-promoting activity. SP2 significantly activated the Nrf2/ARE signaling pathway, hence slowing down the decline in antioxidant defense capacity of D. melanogaster and increased its lifespan. This study has provided direct evidence of a longevity-promoting polysaccharide and revealed the worthiness of further research into SP2 as a health supplement.We have optimized an effective method for screening the antiaging property of polysaccharides by integrating