Targeted Modulation of Chicken Genes In Vitro Using CRISPRa and CRISPRi Toolkit

Engineering of clustered regularly interspaced short palindromic repeats (CRISPR) and the CRISPR-associated protein 9 (Cas9) system has enabled versatile applications of CRISPR beyond targeted DNA cleavage. Combination of nuclease-deactivated Cas9 (dCas9) and transcriptional effector domains allows activation (CRISPRa) or repression (CRISPRi) of target loci. To demonstrate the effectiveness of the CRISPR-mediated transcriptional regulation in chickens, three CRISPRa (VP64, VPR, and p300) and three CRISPRi (dCas9, dCas9-KRAB, and dCas9-KRAB-MeCP2) systems were tested in chicken DF-1 cells. By introducing guide RNAs (gRNAs) targeting near the transcription start site (TSS) of each gene in CRISPRa and CRISPRi effector domain-expressing chicken DF-1 cell lines, significant gene upregulation was induced in dCas9-VPR and dCas9-VP64 cells, while significant downregulation was observed with dCas9 and dCas9-KRAB. We further investigated the effect of gRNA positions across TSS and discovered that the location of gRNA is an important factor for targeted gene regulation. RNA sequencing analysis of IRF7 CRISPRa and CRISPRi- DF-1 cells revealed the specificity of CRISPRa and CRISPRi-based targeted transcriptional regulation with minimal off-target effects. These findings suggest that the CRISPRa and CRISPRi toolkits are an effective and adaptable platform for studying the chicken genome by targeted transcriptional modulation.


Introduction
Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9), which was first discovered in the bacterial immunity system [1], is a powerful tool for genome editing in living organisms [2,3]. This technology requires two components for DNA double-strand breaks (DSBs) on the target locus: a guide RNA (gRNA) and the Cas9 nuclease that induces the cleavage by binding a gRNA to complementary regions in the genome and subsequent endonuclease activity.
Not only was Cas9 designed for gene knockout by inducing DSBs, but it was repurposed to allow for gene regulation rather than genome editing by utilizing catalytically inactive Cas9 lacking endonuclease activity (dCas9) and fusing effector proteins [4][5][6][7][8][9]. The CRISPR/dCas9-mediated gene activation (CRISPRa) system enhances endogenous gene expression with dCas9-mediated recruitment of activator domains by targeting the transcription start site (TSS) or enhancers [10,11]. The fusion of dCas9 and activator domains such as VP64 [12], VPR (containing VP64, Nuclear Factor p65, and Epstein-Barr virus R transactivator (Rta) domains) [10,13], p300 histone acetyltransferase [14,15], SunTag and the synergistic activation mediator (SAM) system allowed for the activation of the expression of coding and noncoding target loci ablation of DNA sequences [16,17]. The CRISPR/dCas9mediated gene interference (CRISPRi) system can utilize gRNAs for repression of singular or multiple genes by blocking transcription elongation or initiation [18]. Transcription repression via the CRISPRi system is reversible, as the dCas9-repression domain blocks transcription of the gene, rather than editing the genetic information [4]. A construct with the

Validation of CRISPRa and CRISPRi Cell Line
To confirm the expression of CRISPRa and CRISPRi components in the cell lines, total RNA from each cell line was isolated using Direct-Zol RNA Mini or Microprep kit (ZymoResearch, Irvine, CA, USA) and reverse-transcribed using High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher-Scientific) [37]. Then, the cDNAs of each cell line were amplified with the CRISPRi and CRISPRa component-specific primers by polymerase chain reaction (RT-PCR). All reactions were performed under the same conditions using DreamTaq Green DNA Polymerase (Thermo Fisher-Scientific) according to the manufacturer's instructions. The cycling conditions were as follows: 95 • C for 1 min, 34 cycles of 95 • C for 30 s, 60 • C for 30 s, 72 • C for 1 min, followed by a melting cycle. The primers used in the PCR were listed in Table S1.
To validate the targeted gene insertion of CRISPRa vectors, the genomic DNA of the cell lines was extracted by using Quick Extract DNA Extraction Solution (Lucigen, Middleton, WI, USA) according to the manufacturer's instructions. Then, the genomic DNAs were analyzed by PCR using knock-in-specific primers (Table S1). The amplicons were cloned into the pGEM-T-easy vector (Promega, Madison, WI, USA) and sequenced using T7 primer. The sequences were then compared against reference sequences using SnapGene (GSL Biotech, LLC, San Diego, CA, USA).

Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR)
Total RNA was used to synthesize cDNA by using High-Capacity cDNA Reverse Transcription Kit (Thermo Fisher-Scientific). For qPCR, the PowerUp SYBR Green Master Mix and protocol (Thermo Fisher-Scientific) was used. For each reaction, 2 µL of cDNA and 1 µL of each forward and reverse primers were used for a 20 µL qPCR reaction. Cycling conditions were as follows: 50 • C for 2 min, 95 • C for 2 min, 40 cycles of 95 • C for 15 s and 60 • C for 1 min, followed by a melting cycle. Each gene expression level was normalized to the housekeeping gene GAPDH expression using the ∆∆Ct method [41]. All qPCR was performed using at least 3 biological replicates, and a significant difference compared to mock control was evaluated by t-test.

Bulk RNA Sequencing and Data Analysis
A total of 8 cDNA libraries (2 replicates each) were prepared with NEBNext Ul-tra™ II RNA Library Prep Kit (New England Biolabs) according to the manufacturer's protocol. Each library was sequenced at a minimum of 20 million, 150 bp paired-end reads per sample. The FASTQ read files from RNA-seq analysis have been deposited in NCBI's Gene Expression Omnibus (GSE217310). We checked the quality of each FASTQ read file using fastQC (version 0.11.9) and trimmed the adaptor sequence with TrimGalore (version 0.6.7). The trimmed FASTQ files were aligned against bGalGal1.mat.broiler.GRCg7b (NCBI annotation release 106) reference chicken genome using STAR aligner (version 2.7.10a) [42]. Raw read counts were extracted by HTSeq (version 0.13.5) from each aligned bam file and used to identify differentially expressed genes (DEGs) [43]. EdgeR R package (version 3.38.4) was used to identify DEGs between transcriptomes (false discovery rate (FDR) < 5%) [37]. Functional annotations for significantly differentially expressed genes were performed using DAVID 2021 [44,45]. The enriched gene ontology (GO) terms on biological processes and the pathways obtained from DAVID functional analysis were filtered for significance by gene count ≥ 5 and p-value < 0.05.

Establishment of CRISPRa and CRISPRi Chicken DF-1 Cell Lines
To examine the effectiveness of diverse CRISPRa and CRISPRi systems in chickens, we established multiple CRISPRa and CRISPRi DF-1 cell lines. To establish the CRISPRa DF-1 cell lines, CRISPR/Cas9-nonhomologous end joining (NHEJ) mediated gene targeting methods were adapted [34]. To induce constant and robust expression of the inserted gene, the 3 region of the housekeeping gene GAPDH was targeted without disturbing gene expression ( Figure S1A). The targeted cleavage of all-in-one CRISPR vector targeting the 3 region of the GAPDH gene (GAPDH#1) was validated by T7E1 assay and subsequent sequencing analysis ( Figure S1B,C). The all-in-one CRISPR vector GAPDH #1 was then transfected to chicken DF-1 cells with the donor plasmids containing CRISPRa effectors (dCas9-VP64, dCas9-VPR, or dCas9-p300) ( Figure 1A) and another all-in-one CRISPR vector targeting the CRISPRa donor plasmids (CRISPRa #1) for linearization of the donor. After the antibiotic selection using G418, successful integration of the donor plasmid into the targeted region was confirmed by genomic DNA PCR and sequencing of the PCR products ( Figure S1D). The RT-PCR results showed that the CRISPRa components, VP64, p65 or p300, were strongly expressed in each cell line ( Figure 1B). These results confirmed the successful establishment of the CRISPRa DF1 cell lines. For CRISPRi cell line establishment, piggyBac transposition allowing direct integration of the gene of interest into the genome was adapted [46]. The piggyBac vectors containing CRISPRi effectors (dCas9, dCas9-KRAB or dCas9-MeCP2) ( Figure 1C) were transfected to chicken DF-1 cells with piggyBac transposase and stably integrated cells were selected with blasticidin for at least 2 weeks. After the antibiotic selection, RT-PCR was performed and the expression of dCas9, KRAB or MeCP2, were successfully detected in the established CRISPRi DF-1 cell lines ( Figure 1D). genome was adapted [46]. The piggyBac vectors containing CRISPRi effectors (dCas dCas9-KRAB or dCas9-MeCP2) ( Figure 1C) were transfected to chicken DF-1 cells wit piggyBac transposase and stably integrated cells were selected with blasticidin for at lea 2 weeks. After the antibiotic selection, RT-PCR was performed and the expression o dCas9, KRAB or MeCP2, were successfully detected in the established CRISPRi DF-1 ce lines ( Figure 1D).

CRISPRa and CRISPRi-Mediated HMGA1, SMARCB1, IRF7 and PPARG Regulation
To demonstrate the transcriptional regulation of CRISPRa and CRISPRi in chicke cell lines, four genes with diverse expression levels in DF-1, HMGA1, SMARCB1, IRF7 an PPARG were selected that have FPKM values of 107, 56, 4.5 and 1.2, respectively. Thre (HMGA1, SMARCB1, and PPARG) or five (for IRF7) gRNAs targeting near the TSS of eac gene were designed and the gRNA expression vector was constructed. For HMGA1, th three gRNAs were designed in locations within −161 bp to +40 bp (1, 2, and 3), and all o the gRNAs were co-transfected to the CRISPRa and CRISPRi in chicken cell lines. Th quantitative PCR analysis revealed that the HMGA1 expression was significantly in creased in the VP64 and VPR CRISPRa cell lines when all gRNAs were combined. VP6 displayed the highest level of gene upregulation, with a +22% gene activation. Howeve there was no significance among the p300, dCas9, dCas9-KRAB, or dCas9-KRAB-MeCP cell lines (Figure 2A).

CRISPRa and CRISPRi-Mediated HMGA1, SMARCB1, IRF7 and PPARG Regulation
To demonstrate the transcriptional regulation of CRISPRa and CRISPRi in chicken cell lines, four genes with diverse expression levels in DF-1, HMGA1, SMARCB1, IRF7 and PPARG were selected that have FPKM values of 107, 56, 4.5 and 1.2, respectively. Three (HMGA1, SMARCB1, and PPARG) or five (for IRF7) gRNAs targeting near the TSS of each gene were designed and the gRNA expression vector was constructed. For HMGA1, the three gRNAs were designed in locations within −161 bp to +40 bp (1, 2, and 3), and all of the gRNAs were co-transfected to the CRISPRa and CRISPRi in chicken cell lines. The quantitative PCR analysis revealed that the HMGA1 expression was significantly increased in the VP64 and VPR CRISPRa cell lines when all gRNAs were combined. VP64 displayed the highest level of gene upregulation, with a +22% gene activation. However, there was no significance among the p300, dCas9, dCas9-KRAB, or dCas9-KRAB-MeCP2 cell lines (Figure 2A).  For SMARCB1, the three gRNAs were designed at locations within −296 to −85 bp (1, 2, and 3). The quantitative analysis shows that the VP64 and p300 cell lines represented significant upregulation. The VP64 cell line displayed the highest level of gene upregulation with a +62% gene activation; however, there were no significant values observed for the VPR and CRISPRi cell lines ( Figure 2B). For IRF7, five different locations of gRNAs (1, 2, 3, 4 and 5) were designed spanning from −256 to +163 for gene activation or repression. As results, the expression of IRF7 was significantly upregulated in the VP64 and VPR CRISPRa cell lines; however, there was no significant gene upregulation in the p300 CRISPRa cell line. On the other hand, in the CRISPRi cell lines, the IRF7 gene expression in dCas9 (−67%) and dCas9-KRAB (−58%) was significantly downregulated in comparison to mock control; however, there was no significance within the dCas9-KRAB-MeCP2 CRISPRi cell line ( Figure 2C). PPARG had gRNA locations designed within −230 to −36 bp. PPARG was only tested in CRISPRa cell lines due to lower expression and significant upregulation was observed among each of the CRISPRa cell lines. The VP64 cell line displayed the highest level of gene upregulation, with a +65% activation ( Figure 2D).

Effects of Individual gRNAs for Gene Regulation
To further validate the effects of the location of each individual gRNAs in CRISPRa and CRISPRi cell lines, each gRNA targeting SMARCB1 and IRF7 was separately transfected in CRISPRa and CRISPRi cell lines. Three gRNAs targeting near the TSS of SMARCB1 gene were examined ( Figure 3A), and the results showed that only gRNA 3 induced a significantly higher SMARCB1 expression in VP64 and p300 CRISPRa cell lines ( Figure 3B). On the other hand, gRNA 2 could only downregulate the gene expression in KRAB and MeCP2 CRISPRi cell lines ( Figure 3C).  For IRF7 gene regulation, five individual gRNAs targeting near the TSS of IRF7 gene were examined ( Figure 4A). Based on the results, only gRNA 2 induced a significantly higher IRF7 expression in VP64 and VPR CRISPRa cell lines, while it was not significant in the p300 CRISPRa cell line. In VP64 and VPR, gRNA 2-transfected samples were significantly increased by 428% and 518% compared to mock controls, respectively ( Figure 4B). The same five individual gRNAs were examined in CRISPRi cell lines, and significant IRF7 downregulation among gRNAs 1, 4, and 5 in dCas9 was observed, with the most downregulation being observed in gRNA 5-transfected samples with a −63% reduction. In the dCas9-KRAB cell line, all of the individual gRNAs induced a significant IRF7 downregulation and the most downregulation was observed in gRNA 4-transfected samples with a −71% reduction. However, no significant downregulation was observed in the dCas9-KRAB-MeCP2 cell line ( Figure 4C).  . Data are shown as the mean ± SEM. Significant differences between the mock controls and gRNAs-transfected samples were determined by Student's t-test. Statistical significance was ranked as * p < 0.05, *** p < 0.001.

Transcriptomic Profile of IRF7-Regulated DF-1 Cells
To explore the global effect of the CRISPRa and CRISPRi systems in chicken cells, the . Data are shown as the mean ± SEM. Significant differences between the mock controls and gRNAs-transfected samples were determined by Student's t-test. Statistical significance was ranked as * p < 0.05, *** p < 0.001.

Transcriptomic Profile of IRF7-Regulated DF-1 Cells
To explore the global effect of the CRISPRa and CRISPRi systems in chicken cells, the transcriptomic profiles of the IRF7-regulated DF-1 cells were analyzed by RNA sequencing and subsequent informatic analysis. The dCas9-VPR and dCas9-KRAB were selected based on their expression modulation efficacy and all five gRNAs were introduced to activate (32% upregulation) or repress (58% downregulation) the IRF7 expression in the cell lines. In CRISPRa cell lines, 259 genes were differentially expressed-200 were upregulated and 59 were downregulated (FDR < 5%) ( Figure 5A). In CRISPRi cell lines, a total of 644 genes were DEGs, with 159 upregulated and 485 downregulated as a result of the targeted downregulation of IRF7 ( Figure 5B). One potential off-target transcript was included in the DEG listed, vinexin-like (LOC107050638), in dCas9-KRAB cell line (FDR < 5%) (Table S2). Functional enrichment analysis of the DEGs was conducted by DAVID to identify the effect of the targeted IRF7 gene modulation. The effect of IRF7 upregulation was seen in the enriched GO:biological process (BP) terms in the genes from the CRISPRa cell lines. These terms were "Extracellular matrix organization", "Cell adhesion", and "Collagen fibril organization". In the KEGG pathway, "ECM-receptor interaction", "Fatty acid metabolism", and "PPAR signaling pathway" were considerably enriched ( Figure 5C). Knockdown of IRF7 showed the function of IRF7, the enriched in GO:BP terms of "Defense response to virus", "Translation", and "Immune system process" were found in the genes from the CRISPRi cell lines. Significant enrichment was found in the KEGG pathways known as "Influenza A", "Herpes simplex virus 1 infection", and "Ribosome" ( Figure 5D).

Discussion
Targeted gene regulation is an efficient method for investigating the function of the genome in relation to important phenotypes in living organisms [47]. The importance of tools that allow for functional studies such as this will allow for greater utilization in farm animals, which are a valuable protein resource in human society [48]. Particularly, poultry has substantial benefits in academic fields as well as industrial areas due to its unique developmental and reproductive characteristics [49]. However, there are still limitations Functional enrichment analysis of the DEGs was conducted by DAVID to identify the effect of the targeted IRF7 gene modulation. The effect of IRF7 upregulation was seen in the enriched GO:biological process (BP) terms in the genes from the CRISPRa cell lines. These terms were "Extracellular matrix organization", "Cell adhesion", and "Collagen fibril organization". In the KEGG pathway, "ECM-receptor interaction", "Fatty acid metabolism", and "PPAR signaling pathway" were considerably enriched ( Figure 5C). Knockdown of IRF7 showed the function of IRF7, the enriched in GO:BP terms of "Defense response to virus", "Translation", and "Immune system process" were found in the genes from the CRISPRi cell lines. Significant enrichment was found in the KEGG pathways known as "Influenza A", "Herpes simplex virus 1 infection", and "Ribosome" (Figure 5D).

Discussion
Targeted gene regulation is an efficient method for investigating the function of the genome in relation to important phenotypes in living organisms [47]. The importance of tools that allow for functional studies such as this will allow for greater utilization in farm animals, which are a valuable protein resource in human society [48]. Particularly, poultry has substantial benefits in academic fields as well as industrial areas due to its unique developmental and reproductive characteristics [49]. However, there are still limitations to identifying specific genetic functions by gene editing, such as changes in genetic information [24]. Therefore, we applied diverse dCas9-mediated CRISPRa and CRISPRi systems to chicken cells and compared for further practical uses in this study. An advantage of the CRISPRa system is the low risk of off-target effects as well as the upregulation of the endogenous genes in their native context [1]. CRISPRi enables the downregulation of multiple genes independently and it circumvents the potential adverse effect of CRISPR knockout [16,50]. An additional advantageous feature of both CRISPRa and CRISPRi is the reversibility of gene manipulation.
To evaluate the effective use of the CRISPRa and CRISPRi systems in chickens, DF-1 cell lines expressing the CRISPRa and CRISPRi components were established. To induce robust expression of the components, the CRISPR/Cas9-NHEJ-mediated gene targeting method and the piggyBac transposition-mediated transgenic technique were adopted for CRISPRa and CRISPRi [34,46], respectively, which have been determined as efficient genome-editing methods in chicken [51,52]. To acquire robust exogenous gene expression, the intergenic 3 region of chicken-the housekeeping gene GAPDH-was targeted for insertion of the CRISPRa components. Through NHEJ and targeting GAPDH, the integration of CRISPRa components into the targeted regions was maintained in the established cell lines. The piggy-Bac transposition-mediated CRISPRi integration was also successfully achieved, suggesting the versatility of the gene insertion methods in chicken DF-1 cells.
Combination gRNAs were introduced to validate the CRISPRa and CRISPRi DF-1 cell lines for endogenous chicken gene regulation. The results displayed that the introduction of gRNAs targeting the TSS significantly upregulates gene expression. On the contrary, the introduction of gRNAs targeting HMGA1 and SMARCB1 could not downregulate gene expression. Relatively higher expression levels of HMGA1 and SMARCB1 were observed throughout the data and could be the reason why there was not significant downregulation. Both significant upregulation and downregulation were observed in IRF7. Based on these results, the CRISPRa and CRISPRi systems could be applicable in chicken DF-1 cells and the targeting regions of gRNAs are critical for gene regulation.
This research reveals that each effector shows a variable range of gene regulation. VPR allows for strong multi-genome activation, indicating expression levels several times higher than VP64 in the gene panel, while p300 did not show improved levels of activation compared to other activators [53]. In another human cell line, human embryonic kidney 293T (HEK 293T), VPR showed 22-to 320-fold improved activation compared to the VP64 activator [13]. In this research, VP64 and VPR were more effective than p300, although there is little significant difference between VP64 and VPR. p300 involves the use of a histone acetyltransferase (HAT). HAT is responsible for catalyzing the acetylation of histones, which are involved in the regulation of gene expression and the difference in gene activation mechanism may be the reason for discrepancy between the effectors [13,54,55].
In terms of CRISPRi, SMARCB1 displayed significant downregulation in gRNA2 in the dCas9-KRAB. CRISPRi gRNAs were exclusively efficient in promotor regions near the TSS, reducing the possibility of off-target effects from transcriptional interference elsewhere in the genome [56]. A few studies show that CRISPRi gRNAs are effective near TSS [16,56], but this limits the effectiveness of transcript production for genes that have TSSs that are not well characterized or genes that have many TSSs. IRF7 had significant downregulation in the dCas9 cell line for gRNAs 1, 4, and 5, and the dCas9-KRAB cell line had the most significance among all of the gRNAs. It has been determined that the optimal inhibition can be induced with gRNAs designed within a window of −50 to +300 bp [16]. Therefore, the results of IRF7 in the dCas9 cell line also support that the gRNA location is critical and the gene regulation effect is independent of the DNA strand targeted [21]. Nevertheless, it was found that gRNAs that did not fall into the window could also downregulate the gene expression (gRNA1 in dCas9 and gRNA2 in dCas9-KRAB). This suggests that gRNAs targeting not only the optimal window but other parts of the gene, including exons and introns, could also induce the downregulation of the gene expression. Other studies have found that by targeting an intron, there has been less opportunity for off-target effects, along with having a three-fold increase in knock-in efficiency [23,57]. Therefore, the results suggest that the differential gene-regulating effects of the IRF7 gRNA2 and gRNA3 are caused by effector proteins.
The fusion of dCas9-KRAB was highly efficient, showing a significant downregulation amongst each of the gRNAs and the combination. The mechanism used by dCas9-KRAB to enhance transcriptional repression is that the KRAB domain interacts with KAP1, which ultimately recruits a variety of corepressors including heterochromatin protein 1 (HP1), histone deacetylases, and SET domain bifurcated histone lysine methyltransferase 1 (SETDB1) [21]. While there are data in humans and mice to demonstrate that the dCas9-KRAB-MeCP2 fusion protein is the most effective, that was not replicated in this study [21]. MeCP2 utilizes a different set of transcriptional repressors than KRAB, which include DNA methyltransferase DNMT1 and the SIN3A-histone deacetylase corepressor complex [58][59][60]. Therefore, the difference in transcriptional machinery of KRAB and MeCP2 may indicate why the dCas9-KRAB-MeCP2 cell line was unable to effectively downregulate the genes in this study. Another potential reason for unsuccessful downregulation could be the limited cross activity of the rat MeCP2 in chicken, since it has a low amino acid sequence identity (42%) compared to the chicken MeCP2 [21].
To investigate the effects of individual gRNAs on gene regulation, SMARCB1 and IRF7 were further examined in CRISPRa and CRISPRi cell lines. Three gRNAs were designed for SMARCB1 and five gRNAs were designed for IRF7 in different locations, either on the positive or negative strand, to determine if different locations or directions were more efficient. For the CRISPRa system, only gRNA3 significantly increased SMARCB1 expression in the VP64 and P300 cell lines and for IRF7, gRNA2 increased gene expression significantly in the VP64 and VPR cell lines. Both of these gRNAs were located close to the TATA box. The result indicates that the location of gRNA is critical for gene regulation in dCas9-mediated gene regulation platforms, which corresponds to the previous research describing optimal gRNA location for CRISPRa (from −400 to −50 bp upstream of the TSS) [53].
Collectively, these results indicate that the diverse effector domains for the dCas9 toolkit are applicable in the chicken system with a variable range of gene regulation. Further studies using additional effector domains that were not validated in this study, such as SunTag, SAM, LSD1 or DNMT1 and a combination of gRNAs, could help optimize chicken gene regulation.
To test the potential use of the CRISPRa and CRISPRi systems as a platform for functional studies in chickens, activation and repression of chicken IRF7 were further tested to compare with our previous studies [61][62][63]. Through RNAseq, transcriptomic profiles of IRF7-regulated DF-1 cells were further validated. IRF7 is known as the master transcription factor of the type I interferon response in mammals and birds, and IRF7 gene knockout resulted in increased virus replication with significant downregulation of antiviral activities [63].
In summary, the CRISPRa and CRISPRi systems using diverse effectors in chicken DF-1 fibroblast cells were successfully evaluated in this study, and significant results were observed when evaluating the combination of gRNAs and individual gRNAs in both the CRISPRa and CRISPRi cell lines. With the combination of bioinformatic analysis, the parallel studies of CRISPRa and CRISPRi using diverse effector domains are expected to not only contribute to regulating specific gene expression but also help to annotate the functional elements, including enhancer and repressor regions in the chicken genome. Further studies are warranted to utilize different cell lines to address the different biological contexts of gene expression.  Table S1. Oligos used in this study.

Conflicts of Interest:
The authors declare no conflict of interest.