Integration analysis of ATAC-seq and RNA-seq provides insight into fatty acid biosynthesis in Schizochytrium limacinum under nitrogen limitation stress

Chen, Duo; Chen, **g; Dai, Rongchun; Zheng, Xuehai; Han, Yuying; Chen, Youqiang; Xue, Ting

doi:10.1186/s12864-024-10043-5

Integration analysis of ATAC-seq and RNA-seq provides insight into fatty acid biosynthesis in Schizochytrium limacinum under nitrogen limitation stress

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Published: 05 February 2024

Volume 25, article number 141, (2024)
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Integration analysis of ATAC-seq and RNA-seq provides insight into fatty acid biosynthesis in Schizochytrium limacinum under nitrogen limitation stress

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Duo Chen¹^na1,
**g Chen¹^na1,
Rongchun Dai¹^na1,
Xuehai Zheng¹,
Yuying Han¹,
Youqiang Chen¹ &
…
Ting Xue¹

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Abstract

Background

Schizochytrium limacinum holds significant value utilized in the industrial-scale synthesis of natural DHA. Nitrogen-limited treatment can effectively increase the content of fatty acids and DHA, but there is currently no research on chromatin accessibility during the process of transcript regulation. The objective of this research was to delve into the workings of fatty acid production in S. limacinum by examining the accessibility of promoters and profiling gene expressions.

Results

Results showed that differentially accessible chromatin regions (DARs)-associated genes were enriched in fatty acid metabolism, signal transduction mechanisms, and energy production. By identifying and annotating DARs-associated motifs, the study obtained 54 target transcription factor classes, including BPC, RAMOSA1, SPI1, MYC, and MYB families. Transcriptomics results revealed that several differentially expressed genes (DEGs), including SlFAD2, SlALDH, SlCAS1, SlNSDHL, and SlDGKI, are directly related to the biosynthesis of fatty acids, meanwhile, SlRPS6KA, SlCAMK1, SlMYB3R1, and SlMYB3R5 serve as transcription factors that could potentially influence the regulation of fatty acid production. In the integration analysis of DARs and ATAC-seq, 13 genes were identified, which were shared by both DEGs and DARs-associated genes, including SlCAKM, SlRP2, SlSHOC2, SlTN, SlSGK2, SlHMP, SlOGT, SlclpB, and SlDNAAF3.

Conclusions

SlCAKM may act as a negative regulator of fatty acid and DHA synthesis, while SlSGK2 may act as a positive regulator, which requires further study in the future. These insights enhance our comprehension of the processes underlying fatty acid and DHA production in S. limacinum. They also supply a foundational theoretical framework and practical assistance for the development of strains rich in fatty acids and DHA.

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Background

Thraustochytrids, including Schizochytrium and Thraustochytrium [1], are found in diverse marine environments, ranging from tropical to Antarctic waters. These organisms thrive from the ocean's surface to depths of up to 2000 m in nutrient-rich areas enriched by decaying organic matter. Their habitats span from seabed sediments to mangrove ecosystems and sewage outfalls. This abundance of nutrients fosters their heterotrophic lifestyle, making them integral to the decomposition of organic materials and the carbon cycle [2]. Within the mangrove forests, the leaf litter provides a conducive environment for growth and acts as a nutrient source, particularly for Schizochytrium limacinum, a member of the Cystachyclaceae family that relies on organic materials for survival [3]. In these ecosystems, chytrid fungi, algae, and various bacterial organisms serve as decomposers. Notably, chytrid fungi and algae differentiate themselves from bacteria by their ability to secrete a range of extracellular enzymes, such as proteases, esterases, cellulases, and chitinases, enhancing their decomposition capabilities [4]. Docosahexaenoic acid (DHA), an essential unsaturated fatty acid, is crucial for lowering cholesterol and triglyceride levels and preventing cardiovascular diseases like atherosclerosis, cerebral thrombosis, cerebral hemorrhage, and hypertension. It holds significant nutritional and medicinal importance [Full size image

Validation of the candidate genes by RT- qPCR

To further validate the gene expression levels, we selected 10 candidate genes (SlFAD2, SlALDH, SlMYB98, SlMKK, SlCALM, SlCAMK1, SlMYB3R1, SlMYB3R5, SlSGK2, and SlCALM) for qRT-PCR analysis. The results of qRT-PCR were consistent with the expression levels obtained from RNA-Seq and ATAC-seq (Figure S5).

Discussion

To develop algae and fungus species with enhanced fatty acid and DHA levels, a deep understanding of the lipid biosynthesis regulatory mechanisms is essential. Recent research has shed light on the impact of nitrogen limitation on fatty acid and DHA biosynthesis pathways. However, the detailed molecular mechanisms governing these biosynthetic processes in response to nitrogen limitation at various culture stages are not fully understood. Previous studies have confirmed that nitrogen limitation effectively boosts fatty acid and DHA accumulation [12], but there has been limited investigation into how chromatin accessibility influences transcriptional regulation during this process. In this study, we aimed to fill this research gap by analyzing the chromatin accessibility under nitrogen-limited conditions using ATAC-seq. We identified crucial transcription factors and functional genes that play significant roles in fatty acid and DHA biosynthesis. By combining ATAC-seq and RNA-seq analyses post-nitrogen limitation treatment, we gained insights into how chromatin opening influences gene expression and, subsequently, the biosynthesis of fatty acids and DHA. This integrative approach allows us to better understand the complex interplay between chromatin structure and gene regulation, specifically under nutrient-stressed conditions, paving the way for more efficient strategies in enhancing fatty acid and DHA production in algae and fungus.

Following the completion of KEGG and GO enrichment analyses, the outcomes indicated the participation of peak-associated genes in various processes, including lipid transport and metabolism, as well as signal transduction mechanisms. MYB transcription factors, and energy production and conversion were significantly enriched, including SlSCP2 (schi20031420), SlSLD (schi20021550), SlSNQ2 (schi20046190), SlALDH (schi20015830), SlMYB98 (schi20043810), and SlMKK (schi20040620). This indicates that nitrogen-limited treatment could play an important role in the regulation of fatty acid and DHA biosynthesis in S. limacinum. SCP2, also known as sterol carrier protein-2, plays a pivotal role in facilitating the transportation of lipids across membranes [17]. SLD, a delta8-fatty-acid desaturase, was initially identified in the protist Euglena gracilis. This enzyme introduces a double bond at the 8-position in 20-carbon fatty acids and plays a significant role in the synthesis of eicosanoids from precursors, including polyunsaturated fatty acids with chain lengths of 20 carbons or longer. SLD is a vital component of the alternative pathway for the biosynthesis of longer chain polyunsaturated fatty acids [18]. SNQ2 is a gene encoding an ATP-binding cassette (ABC) transporter. ABC transporters play a crucial role in the transport and distribution of lipids and are closely associated with fatty acid metabolism. They have a great influence on the seed oil yield of camelina, and it has been found that ABC transporter can potentially be applied to improving oil production for camelina [19]. Studies have also revealed a fundamental similarity in the core biochemical function of peroxisome ABC transporters between oilseeds and cereals; however, its physiological effects and importance may vary [16]. By thoroughly characterizing the peroxisomal ABC transporter defective mutant, it showed that TAG is a key intermediate in mobilizing fatty acids from membrane lipids for peroxisome beta oxidation under prolonged dark treatment [20]. Numerous studies have established a strong connection between ABC transporters and fatty acid metabolism. Acetaldehyde dehydrogenase (ALDH) genes are ubiquitously found across various organisms, with Arabidopsis possessing a total of 14 ALDHs. Among these, ALDH3I1, ALDH3H1, and ALDH7B4 exhibit tissue-specific activation in response to dehydration, high salinity, and ABA (abscisic acid), respectively. Transcriptional analysis of Arabidopsis mutants, namely ALDH3I1 and ALDH7B4, provides insights into the regulatory role of the plant hormone ABA in stress responses, as well as its impact on pathways governing glucose metabolism and the composition of membrane lipid fatty acids. ALDH genes associated with stress responses participate in diverse pathways, and their regulation encompasses various signal transduction pathways [21]. In Arabidopsis, the ALDH enzymes belonging to family 2 catalyze the oxidation of acetaldehyde, generating acetate for the biosynthesis of acetyl-CoA through the activity of acetyl-CoA synthetase. This metabolic pathway, known as the "pyruvate dehydrogenase bypass," is intricately connected to fatty acid biosynthesis [22]. In S. limacinum, we found that transcription factors MYB98 and MKK play major roles in fatty acid and DHA accumulation under nitrogen-limited treatment. Previous studies of MYB98 have mainly focused on its developmental regulatory effects on plant reproductive organs or cells of plants, such as the fertilization in flowering plants, the development of female gametophytes, and the activation of gene expression necessary for pollen tube guidance and filiform apparatus formation in synergid cells [23,24,25]. Our preliminary research has found that IgMYB98 may play a negative regulatory effect on fucoxanthin biosynthesis in I. galbana, a fucoxanthin-producing single-cell organism, induced by green light [26]. MKK is a crucial serine/threonine-protein kinase involved in various signaling pathways, including nitrogen signaling, among others, in eukaryotes. Additionally, MKK acts as a target for rapamycin (TOR) signaling. Research has shown that TOR plays an important role in the accumulation of triacylglycerols (TAGs), and the accumulation of lipid droplets requires de novo fatty acid synthesis, which is dependent on fatty acid synthetase. Furthermore, it has been observed that rapamycin treatment leads to an increase in triacylglycerol (TAG) content and up-regulation of DGAT gene expression in the unicellular green algae Chlamydomonas reinhardtii. These discoveries indicate the widespread involvement of TOR signaling in the accumulation of TAG in microalgae [27]. Some of the genes mentioned above are directly related to the synthesis of fatty acids, and some are transcription factors, all of which are involved in the regulation of substance biosynthesis. These candidate genes may therefore be involved in the biosynthesis mechanism of fatty acids and DHA caused by nitrogen-limited treatment in S. limacinum. By identifying and annotating 989 DARs-associated motifs, we obtained 54 target TF classes, including BPC, RAMOSA1, SPI1, MYC, and MYB families. AtBPC6 was found to regulate photosynthesis, photoreactions, photosynthetic membranes, and reproductive development during flower morphogenesis in petunias [28]. BPC1 has the ability to induce the upregulation of the Arabidopsis thaliana SEEDSTICK gene (STK), thereby governing the identity of ovules [29]. Additionally, BPC1 may play an important role as a calcium-sensitive signal molecule in pollination of Arabidopsis thaliana [30]. MYB3, characterized as a transcriptional repressor, plays an important role in lignin and anthocyanin biosynthesis under salt stress conditions in Arabidopsis [31]. As a positive regulator, AtMYB111 expression could be highly induced under salt treatment in Arabidopsis, and its role was dependent on its regulation of flavonoid synthesis [32]. These transcription factors primarily regulate the biosynthesis of plant substances, and further studies on their function verification should be carried out in the future to investigate their potential role in the synthesis of fatty acids and DHA.

To better understand the regulatory mechanism of fatty acid and DHA accumulation, transcriptomics was performed on S. limacinum under nitrogen-limited treatment, revealing candidate genes involved in fatty acid and DHA metabolism. In schi-RC compared with schi-RT, we found up-regulation of SlFAD2, SlALDH, SlHSD17B8, SlglpQ, SlACADS, SlSMT1, SlCAS1, SlRPS6KA, SlSTE11, SlNRT, and SlNR, while SlNSDHL, SlSLC27A4, SlLPCAT2, SlDGKI, SlCALM, SlCAMK1, SlMYB3R1, and Slmyb3r5 were down-regulated. Among these genes, SlFAD2, SlALDH, SlHSD17B8, SlglpQ, SlACADS, SlSMT1, SlCAS1, SlNSDHL, lSLC27A4, SlLPCAT2, and SlDGKI are directly related to fatty acid biosynthesis, and SlRPS6KA, SlSTE11, SlCALM, SlCAMK1, SlMYB3R1, and SlMYB3R5 are transcription factors that regulate the biosynthesis process. SlFAD2, which encodes omega-6 fatty acid desaturase, is positioned within the endoplasmic reticulum and plastid membrane of plant cells. Its primary role entails the insertion of a double bond between carbons 12 and 13 of the monounsaturated fatty acid oleic acid, ultimately generating a polyunsaturated fatty acid with two double bonds, namely linoleic acid [33]. It is a key enzyme in the formation of linoleic acid through oleic acid dehydrogenation and a rate-limiting enzyme in the metabolic pathway of polyunsaturated fatty acids, governing the synthesis of the majority of unsaturated fats in plant cells. Functional studies have demonstrated the significant involvement of IgFAD2, isolated from the marine microalgae I. galbana, in the biosynthetic pathways of polyunsaturated fatty acids [34]. Recently, the content and composition of unsaturated fatty acids have been shown to be regulated by mutations and modifications of the FAD2 gene in many plants [34,35,36,37]. We found that nitrogen-limited treatment significantly up-regulated the expression of SlFAD2 gene, indicating its important role in increasing the contents of fatty acids and DHA in S. limacinum. In addition, SlALDH was also significantly up-regulated in both ATAC-seq and transcriptome differential expression gene analysis, indicating the potential role of IgFAD2 in regulating fatty acid metabolism, potentially through the regulation of metabolic flow. Therefore, we concluded that SlALDH plays an important role in the effects of nitrogen-limited treatment on the contents of fatty acids and DHA in S. limacinum. Notably, among the identified transcription factors and regulatory genes, SlRPS6KA, SlSTE11, SlCALM, SlCAMK1, SlMYB3R1, and SlMYB3R5 belong to plant MAP kinase signaling components that play crucial roles in plant growth and development. These components include the MEKK/STE11, RAF, MLK, and CDC7 families [38]. Previous studies have proposed that the A. thaliana ATMEKK1 might be involved in the osmotic stress response pathway and could mediate the response at the level of the MEKK kinase ste11 in Saccharomyces cerevisiae [39]. Calmodulin (CaM) is a significant regulator that plays diverse roles in the growth and development of plants. Several studies have shown that CALM gene expression changes are correlated with metabolic changes of fatty acids, suggesting that CALM exerts a regulatory influence on the metabolism of fatty acids [40,41,42,43,44,45,46]. In our study, we observed a significant decrease in the expression of SlCALM under nitrogen stress treatment. Calmodulin kinases (CaM kinases) are serine/threonine protein kinases that are regulated by calcium/calmodulin complexes downstream of CALM. We also observed a significant down-regulation of SlCAMK1 during nitrogen-limited treatment, which is consistent with the down-regulation of SlCALM. Additional investigation is required to elucidate the precise mechanism by which these genes operate. The MYB transcription factor subclass contains three R domains, and MYB3R proteins in plants are mainly involved in the regulation of cell cycle, cell differentiation, plant tolerance to adversity, and the synthesis of plant metabolites [47,48,49,50]. To further elucidate the regulatory dynamics of fatty acid and DHA production, we undertook transcriptomic analysis on S. limacinum subjected to nitrogen-deprivation. This revealed a cadre of genes integral to fatty acid and DHA metabolism. Comparing schi-RC to schi-RT, transcription factors like SlRPS6KA, SlSTE11, and SlMYB3R1 potentially influence the biosynthesis procedure. In our study, we found that two MYB3R genes, SlMYB3R1 and SlMYB3R5, were significantly down-regulated under nitrogen-limited treatment, which negatively regulated the synthesis of fatty acids and DHA. These genes are promising candidates for further investigation.

In our integrated analysis of DARs of ATAC-seq, we found that 13 genes were shared by DEGs and DARs-associated genes, namely SlCAMK, SlIFT74, SlRP2, SlSHOC2, SlTN, SlSGK2, SlHMP, SlOGT, SlclpB, SlDNAAF3, and SlE2.4.1.173. Many studies have demonstrated the close relationship between CAMK and SGK2 and plant fatty acid metabolism. CAMK1 participates in the encoding and synthesis of calcineurin, and in Arabidopsis thaliana, the calcineurin B-like (CBL) protein serves a vital function in the regulation of ion fluxes and responses to abiotic stress. Arabidopsis seeds with the cbl2/3rf mutation displayed reduced size, weight, and fatty acid content when compared to the wild-type seeds [51]. B-like (CBL)-interacting protein kinase 9 (CIPK9) of Brassica napus was reported to regulate seed oil content, and both rapeseed knock-out lines and gene-silenced lines showed decreased levels of polyunsaturated fatty acids [52]. SGK2 is responsible for encoding a ribosomal protein S6-like protein that is localized in the plastids, and by map-based cloning, it was revealed that the Arabidopsis rfc (regulator of fatty acid composition) 3 gene can alter the fatty acid composition of membrane lipids, resulting in an increase in oleic acid (18:1) levels and a decrease in α-linolenic acid (18:3) levels among total fatty acids [53,54,55]. In our integration analysis, we found that SlCAKM was down-regulated and SlSGK2 was up-regulated under nitrogen-limited treatment. It is possible that the levels of polyunsaturated fatty acids increased with SlCAKM down-regulation, while SlSGK2 up-regulation increased the degree of unsaturated fatty acids by enhancing the expression levels of FAD2 and FAD3 [53]. Therefore, SlCAKM may act as a negative regulator of fatty acid and DHA synthesis, while SlSGK2 as a positive regulator, which requires further investigation. Our findings offer valuable insights into the molecular regulatory mechanisms of fatty acids and docosahexaenoic acid (DHA) in S. limacinum and may aid in the development of high content fatty acid and DHA strains for S. limacinum.

Conclusions

S. limacinum holds significant importance for the commercial production of natural DHA. While a few studies have initially explored the transcriptional regulatory mechanisms of DHA in S. limacinum preliminarily, it is still unknown whether chromatin remodeling is related to DHA biosynthesis and how it responds to nitrogen limitation-mediated culture. This study analyzed the chromatin opening profile of nitrogen-limited using ATAC-seq and identified the key transcription factors and functional genes that affect fatty acid and DHA biosynthesis through ATAC-seq and RNA-seq analysis after nitrogen-limited treatment. The study found that SlFAD2, SlALDH, SlMYB98, SlMKK, SlCALM, SlCAMK1, SlMYB3R1, SlMYB3R5, SlSGK2, and SlCALM genes were significantly enriched in lipid transport and metabolism, signal transduction mechanisms, and energy production and conversion. These candidate genes may be involved in the biosynthesis mechanism of fatty acids and DHA caused by nitrogen-limited treatment in S. limacinum. The findings of this study will facilitate in-depth understanding the molecular regulation mechanisms of fatty acid and DHA biosynthesis in S. limacinum and its role in response to nitrogen limitation stress, providing theoretical basis and technical support for the construction of high content fatty acid and DHA strains.

Materials and methods

Samples and culture conditions

The S. limacinum MYA-1381 strain was procured from the American Type Culture Collection (ATCC). For the experiment, two types of mediums were prepared: the control medium contained 5.0 g glucose, 1 g peptone, and 1.0 g yeast extract, all dissolved in 1L of seawater; the treatment medium was similar, but contained only 0.5 g yeast extract. Algal liquid cultures were then inoculated at a concentration of 1% into 2L Erlenmeyer flasks, each filled with 1L of the respective medium, and incubated at 28 °C and 200 rpm for 48 h. Afterward, the algae solution was portioned into 250 mL centrifuge tubes and spun at 8,000 rpm and 20 °C for 5 min, with the supernatant subsequently removed. The collected pellet was then resuspended in 10 mL of PBS buffer within a sterile 50 mL centrifuge tube, centrifuged again under the same conditions, and the supernatant discarded. Lastly, the retrieved pellet was combined with 10 mL of sterilized ultra-pure water and centrifuged at 10,000 rpm and 20 °C for 10 min. After removing the supernatant, the resulting algae mud was promptly flash-frozen in liquid nitrogen and stored at -80 °C for subsequent fatty acid and DHA detection as well as omics research. For the purpose of examining the build-up of fatty acids and DHA within S. limacinum, under different nitrogen supply conditions, including nitrogen-replete (NR) as control and nitrogen-limited (NL) as treatment conditions. The incubation time was 12 h, 24 h,36 h,48 h,60 h and 72 h. We measured the content of fatty acids and DHA in control and nitrogen-limited at 6 fermentation stages of algae by GC–MS.

Fatty acid and DHA content detection

Fifty milliliters of the algal liquid cultures were spun at 8,000 rpm for 5 min, following which the supernatant was removed. The resulting algal slurry was subsequently frozen at -80℃ and then dried in a vacuum freeze dryer for a duration of 48 h. The dry weight of this dehydrated algal slurry was then recorded.

For fatty acid extraction, 50 mg of algal powder was combined with 3 mL of a 10% NaCl solution, then thoroughly mixed using a vortex mixer until no clumps remained. Subsequently, an equal volume of a chloroform:methanol mixture (2:1 ratio) was added and vortexed, followed by centrifugation at 8,000 rpm for 5 min. The bottom layer contained the fatty acids within the chloroform phase. The middle layer was cautiously discarded, while the chloroform phase was transferred into a fresh tube. This process was carried out twice more to ensure complete collection of all chloroform phases. The chloroform solution containing fatty acids was blown dry with a nitrogen blower to obtain the fatty acid extract, which could be stored at -80 °C.

For fatty acid composition analysis, the fatty acid extract was dissolved in 1 mL of toluene. Then, 200μL of 1 mg/mL BHT antioxidant and 2 mL of chloracetyl solution were added and mixed well. The solution was incubated overnight at 50 °C. The next day, 1 mL of n-hexane containing 1 mg/mL methyl 19 acid was added to the fatty acid and mixed. After standing and stratifying, the upper n-hexane layer was passed through a 0.22 μm nylon membrane for gas chromatography analysis.

The gas chromatography used was an Agilent 7697B, with a detector set at FID and temperature maintained at 250℃. The chromatographic analysis was conducted on a SUPELCO SPTM-2560 column (100 m × 0.25 mm × 0.2 μm) with a flow rate set at 1.2 mL/min. Nitrogen served as the carrier gas and the injection volume was fixed at 1μL, with a split ratio of 10:1. The oven temperature program started at 140℃ for 5 min, followed by a ramp of 4℃/min up to 250℃, which was then maintained for 12.5 min. The blend, DHA, and EPA standards were examined, and standard curves for each fatty acid were generated using the internal standard method, facilitating the computation of each fatty acid's content in the samples under scrutiny.

ATAC sequencing and analysis

Six samples were used for ATAC sequencing: schi-AC1, schi-AC2, schi-AC3 (control: samples cultured for 48 h on control medium), and schi-AT1, schi-AT2, and schi-AT3 (treatment: samples cultured for 48 h on treatment medium). Algal cells underwent centrifugation at 4℃ for 5 min at 500 g, following which the supernatant was discarded. The cells were then given a wash with cold PBS, with the resultant supernatant similarly removed after an additional centrifugation under identical conditions. Subsequently, the cells were resuspended in cold lysis buffer and subjected to a final centrifugation step at 4℃ for 10 min at 500 g to eliminate the supernatant. The transposition reaction was prepared using the Tn5 transposase. Nuclei were resuspended in this transposition mixture and incubated at 37℃ for 30 min prior to the DNA purification step. The purified DNA was subjected to PCR amplification reactions and the final libraries were run on the Illumina platform. Initial reads were managed using Cutadapt 1.8.3 [56] to ensure quality control. Following this, the refined reads were mapped onto the S. limacinum MYA-1381 genome via Bowtie2 (version 2.2.4) [57]. Coverage maps were subsequently generated with deepTools2.07 [58] and peak calling was done with MACS2.1.1, with a threshold of FDR < 0.05. The annotation of genome-wide peak was performed with ChIPseeker1.2.6 [59, 60]. Motif identification and annotation were executed through MEME-ChIP4.11.2 [61]. We used DiffBind2.2.11 to pinpoint differential peaks, setting parameters for a fold change of 1.2 or greater and a false discovery rate (FDR) of less than 0.05. We annotated the genes associated with the differentially accessible regions (DARs) by cross-referencing them with various databases, including NR, Swiss-prot, GO, KEGG, COG, KOG, eggNOG, and Pfam [62,63,64,65,66,67,68]. GO and KEGG enrichment of DARs-associated genes were analyzed using the R package clusterProfiler4.2 [64, 65].

mRNA sequencing and analysis

Six samples were used for mRNA sequencing, labeled as schi-RC1, schi-RC2, schi-RC3 (control: samples cultured for 48 h on control medium), and schi-RT1, schi-RT2, and schi-RT3 (treatment: samples cultured for 48 h on treatment medium). The extraction of total RNA was performed using TRIzol reagent (Invitrogen Life Technologies, CA, USA). To ensure purity and quality, the extracted RNA was assessed using a NanoPhotometer (IMPLEN, CA, USA) and a 2100 Bioanalyzer (Agilent Technologies, USA). For the preparation of RNA libraries, the previously described method was employed, and subsequently, sequencing was carried out on the Novaseq 6000 platform using PE150. Trimmomatic (version 0.36) was used to obtain clean reads from Illumina raw reads, which were then mapped to the genome using HISAT2 (version 2.2.1) [69, 70]. EdgeR (version 4.2) was employed to detect differentially expressed genes (DEGs) using the thresholds of |log2 Fold change| being equal to or greater than 1.5, and a p-value being less than 0.05. For enrichment analysis, the topGO R package (version 3.8) was used for Gene Ontology (GO), while KOBAS (version 3.0) was used for KEGG pathway analysis [71].

Combined analysis of ATAC-Seq and RNA-Seq data

The genes related to differential peaks identified by ATAC-seq were compared with the differentially expressed genes (DEGs) identified by RNA-seq. Specifically, the upregulated peaks from ATAC-seq were compared with the associated upregulated DEGs from RNA-seq, and the downregulated peaks from ATAC-seq were compared with the associated downregulated DEGs from RNA-seq. Genes identified from both ATAC-seq and RNA-seq analyses were further analyzed using Gene Ontology (GO) and KEGG enrichment, utilizing the topGO R package (version 3.8) and KOBAS (version 3.0) respectively, as outlined by **e et al. [71].

Real-time quantitative PCR

Total RNA extraction was carried out using the TRIzol Kit (Takara, Tokyo, Japan). Subsequently, cDNA synthesis was facilitated by the TransScript One-Step gDNA Removal and cDNA synthesis SuperMix (Bei**g TransGen Biotech Co., Ltd.). RT-PCR was executed with the aid of the TransScript® Green One-Step qRT-PCR SuperMix Kit (TransGen Biotech, China), with glyceraldehyde-3-phosphate dehydrogenase (GAPDH) utilized as a reference gene.

Availability of data and materials

The ATAC sequencing data have been archived at the National Genomics Data Center, Bei**g Institute of Genomics, Chinese Academy of Sciences, under the BioProject accession number CRA010780 (https://ngdc.cncb.ac.cn/gsa). For annotation and biological analyses, raw RNA-seq sequencing data were utilized and are available in the BIG Subsystem with the BioProject accession number PRJCA002397 (http://bigd.big.ac.cn).

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Funding

This research received support from the Natural Science Foundation of Fujian Province, China (No. 2020J01178), and the China Agriculture Research System of MOF and MARA (No. CARA-170501).

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Duo Chen, **g Chen and Rongchun Dai are contributed equally to this work.

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The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Center of Engineering Technology Research for Microalga Germplasm Improvement of Fujian, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, College of Life Sciences, Fujian Normal University, Fuzhou, China
Duo Chen, **g Chen, Rongchun Dai, Xuehai Zheng, Yuying Han, Youqiang Chen & Ting Xue

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Duo Chen
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**g Chen
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Rongchun Dai
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Xuehai Zheng
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Yuying Han
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Youqiang Chen
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Ting Xue
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Contributions

T. X. and Y. C. designed the research. R. D. and X. Z. performed the statistical analysis. D. C. and J. C. contributed gene expression analysis. Y. H. collected the experimental materials. T. X. analyzed chromosome accessibility and wrote the manuscript. All authors approved the final submitted manuscript.

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Additional file 1:

Table S1. Evaluation statistics of sample sequencing data. Table S2. Map** statistical of each sample. Table S3. Distribution statistics of Reads in gene functional elements. Table S4. Motif enrichment analysis showed the potential functions of DARs-associated genes between control and treatment group. Table S5. TFs identification of DEGs between control and treatment group. Table S6. Annotation of up-DEGs in the treatment compared with control group. Table S7. Annotation of down-DEGs in the treatment compared with control group. Table S8. Annotation of shared genes from DEGs and DARs-associated genes by RNA-seq and ATAC-seq.

Additional file 2:

Fig. S1. KEGG (a) and GO (b) enrichment analysis showed the potential functions of peak-associated genes in the control group. Fig. S2. KEGG (a) and GO (b) enrichment analysis showed the potential functions of peak-associated genes in the treatment group. Fig. S3. GO enrichment in biological process (a) and molecular function (b) terms analysis showed the potential functions of DARs-associated genes between control and treatment group. Fig. S4. KEGG enrichment analysis showed the potential functions of DARs-associated genes between control and treatment group. Fig. S5. Real-time quantitative RT-qPCR confirmation of SlFAD2, SlALDH, SlMYB98, SlMKK, SlCALM, SlCAMK1, SlMYB3R1, SlMYB3R5, SlSGK2, and SlCALM. Relative gene expressions were analyzed using the 2−ΔΔCt method. Experiments were performed in triplicate. Error bars indicate standard deviation.

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Chen, D., Chen, J., Dai, R. et al. Integration analysis of ATAC-seq and RNA-seq provides insight into fatty acid biosynthesis in Schizochytrium limacinum under nitrogen limitation stress. BMC Genomics 25, 141 (2024). https://doi.org/10.1186/s12864-024-10043-5

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Received: 08 June 2023
Accepted: 22 January 2024
Published: 05 February 2024
DOI: https://doi.org/10.1186/s12864-024-10043-5

Integration analysis of ATAC-seq and RNA-seq provides insight into fatty acid biosynthesis in Schizochytrium limacinum under nitrogen limitation stress

Abstract

Background

Results

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