Profiling Genome of Tibetan Chicken

Profiling Genome of Tibetan ChickenProfiling the genome-wide deoxyribonucleic acidmethylation indecadet of Tibetan yellow-belliedvictimization integral genome bisulfite sequencingAbstract primer Tibetan grumblers living at high altitudes show specific adaptations to high-altitude conditions, nevertheless the epi factortic allowance substructures of these adaptations switchnt been characterized.Results We investigated the genome-wide desoxyribonucleic acid methylation patterns in Tibetan xanthous fall using whole genome bisulfite sequencing (WGBS). divisorrally, Tibetan moaner exhibited analogous methylation pattern with that of sea-level chiken. A list of 3.92% of genomic cokes were methyl snows, and 51.22% of cytosines in CG contexts were methylated which was less than those in low-lying white-livered (55.69%). Moreover, the ground side by side(p) to methylcytosine of mCHG in Tibetan chicken had a p deferred payment for T, which was clear from that in lowland ch icken. In Tibetan chicken, the methylation takes in the farmr were relatively low, while the broker body maintained hypomethylated. DNA methylation aims in upriver regions of the system start site ( toxic shock syndrome) of divisorshad a negative relationship with the ingredient facial expression level, and the DNA methylation of divisor-body were also negatively related to gene expression.Conclusions We first gene appreciated the genome-wide DNA methylation patterns in Tibetan chicken, and our results will be helpful for proximo epigenetic studies in adaptations to high-altitude conditions and provide a bare-assed idea for the prevention and word of mountain sickness and some other hypoxia-related diseases to tender.Keywords Epigenetics, DNA methylation, MethylC-Seq, upland chicken, adaptation, utmost(a) environment. BackgroundDNA methylation is a crucial epigenetic modification that plays a vital percentage in genomic imprinting 1, transcriptional repression 2, and chromatin granule activation 3. In recent years, we take for gained knowledge on the necktie of DNA methylation with cellular differentiation, development, and disease, however, exact breeding is available concerning the DNA methylation modifications under long-term extreme environment.Environmental aspects model through both genetic and epigenetic mechanisms 4, 5. Several studies have tried to lay down the relationship amidst environmental factors and DNA methylation in military man. It was reported that reduce global DNA methylation in whole logical argument was related to scene to ambient descent pollution at the home addresses of non adults 6. In cancerous cells, airborne benzene dumb comprise a significant fall down in the methylation of LINE-1 and AluI, and increasing airborne benzene levels can ca uptake hypermethylation in p15 and hypomethylation in MAGE-1 7. The bonnie level of methylation in p16 was increased in patients with benzene inebriation compar ed with control group, while no alternation was observed in the p15 methylation 8. Korea et al. endangered that nearly organochlorine (OC) pesticides were mutually and significantly related to the methylation of Alu 9. In the prenatal pregnant women, lead word-painting was inversely related to genomic DNA methylation in white bank line cells 10. Moreover, base on the epigenetic hereditary pattern mechanisms, adaptive traits that result from the environment can be transferred to the next generation. For instance, environment containing endocrine-disrupting chemicals can affect the germ line and promote disease across offspring via DNA methylation 11.Above researchs shows that environmental conditions could induce DNA methylation alternation to to influence disease, prompting us to explore whether DNA methylation is associated with the alone(p) adaptations of farm animals to hypoxia and high-dose ultraviolet radiation in high-altitude environments. The Tibetan chicken which liv es in high-altitude environment has smaller body, lower heart rate, higher spleen rate and erythrocyte volum than low-altitude chicken. Previous research showed that humans relocating to high-altitudes might undergo discerning mountain sickness, high-altitude pulmonic edema, and high-altitude cerebral edema 12. Whereas, the Tibetan chicken is greatly adapted to the low-oxygen and high-altitude environment and displays good performance in terms of natural selection and has high reproduction 13. Therefore, investigation the genome-wide DNA methylation of Tibetan chicken, understanding the do of DNA methylation on the tableland adaptability, may provide a new idea for the prevention and treatment of mountain sickness and other hypoxia-related diseases to human.In this study, we perform whole genome bisulfite sequencing (WGBS) on Tibetan chicken blood to test their global DNA methylation patterns. The DNA methylome distribution in the Tibetan chicken genome was shown for the first time. Our results will provided an important resource for exploring low-oxygen adaptation mechanism in high-altitude district.MethodsAnimalsIn this study, one Tibetan chicken was obtained from Xiangcheng County in the Ganzi Tibetan self-reliant Prefecture with the living place about 3500 meters above sea level. Blood samples were unruffled and stored at -20 C for bisulfite sequencing. Total genomic DNA was collected from the blood with the use of a TIANamp Genomic DNA Kit (Tiangen, Beijing, China). only experiments in this study were performed in accordance with relevant guidelines and regulations, and were approved by the Science and Technology division of Sichuan Province.MethylC-Seq library construction and sequencingDNA was fragmented by sonication with a Sonicator (Sonics Materials) to a mean size of approxi partner offly 250 bp, followed by blunt ending, 3-end addition of dA, and organiser ligation, in which Illumina methylated adapters were used according to the manufa cturers instructions (Illumina). The bisulfite conversion of Tibetan chicken DNA was carried out using ZYMO EZ DNA Methylation-Gold kit (Zymo Research, Irvine, CA, USA) and amplified via PCR with 12 cycles. Ultra-high-throughput pair-end sequencing was performed by the Illumina Genetic Analyzer (GA2) on the basis of manufacturer instructions. in the bare-assed GA sequencing entropy were processed using Illumina base-calling pipeline (SolexaPipeline-1.0). entropy FilteringData filtering was performed via the elimination of the adaptor seasons, contamination and low-quality reads from raw reads. Low-quality reads consist of third types including 1) adopt adaptor sequence 2) N base add over 10% 3) The number of base whose quality less than 20 over 10% was trimmed, and the read which accord with one of them will be removed. Only cleaned data were used for the downstream analyses.Reads AlignmentOn the forward read of for each one(prenominal) read pair, observed cytosines were re placed with replaced with adenines, and the observed guanines were replaced with adenines on the reverse read of each read pair. The alignment form reads were then mapped to the alignment form gallus_gallus reference genome by SOAP aligner14. Each hit with a single organisation with a minimum number of mismatches and and a clear operation mountain chain was defined as unambiguous alignment (uniquely mapped reads) and was used for ascertainment of methyl-cytosine. The copy song of the local region was estimateed by calculating the the uniquely mapped reads.Estimating methylation levelsMethylation level was set by dividing the number of reads covering each mC by the lend reads covering that cytosine, which was also equal the mC/C ratio at each reference cytosine. The function is showed as by-lineMethylation level = degree Celsius *GO enrichment analysisGO notations of Tibetan chicken genes were downloaded from the Ensembl (ftp//ensembl.org/pub/ catamenia/otherdata/Gene_ontolog y/gallus_gallus_glean_gene.go). GO comparative analyses between interested genes groups were performed using BGI WEGO (http//wego.genomics.org.cn/cgi-bin/wego/index.pl).KEGG Pathway AnalysisDifferent genes usually interact with each other to exercise their biologic functions. Kyoto Encyclopedia of Genes and GenomesKEGGis the main public channel database. Super geometry analyses were conducted to find the KEGG pathways enriched in genes differentially methylated compared to the whole genome. The calculation formula is the same as that in GO function analyses, N re bewilders number of genes with pathway annotation For the number, n is the number of differentially uttered genes corresponding N, M re represents number of all genes which have a particular pathway annotation m represents numbers of differentially expressed genes which have a particular pathway annotation. Pathway mapped Q value 0.05 defined as the pathway of significant enrichment. by dint of significant enrichment of the pathway, we can determine the virtually main in biochemical pathways and signal transduction pathways.Results Global mapping of DNA methylationIn the present study, blood samples from a Tibetan chicken were used to grow third libraries for genome-wide methylation sequencing. All libraries showed nearly complete bisulfite conversion (99.7%). A total of 41.3 Gb raw data were obtained from trey blood samples. After data filtering, 151,345,614, 165,745,108 and 141,554,972 clean reads were generated for the three libraries, respectively. Of the total reads, 75.6% were mapped to the reference genome, with 28 X Whole-genome average reportage discretion, which could reveal the data quantity of clean data be eccentric of the characteristics of bisulfite sequencing (Table 1 and 2).Cytosine patterns have 3 major types (CG, CHG and CHH, H represents non-G base, hereinafter inclusive) according to the sequence context. Therefore, we study the relationships between potent sequencing foresight and genome coverage for different cytosine patterns ( find out S1, S2). Figure S1 reveals that there is a negative correlation coefficient between the loadingive sequencing depth and the percentage of cytosine in genome. The Figure S2 shows that the distribution of genome coverage varies with sequencing depth accord with the Poisson distribution, and the depth of the distributions apex is near to the genome average sequencing depth.In additon, we performed effective coverage analysis base on three different levels chromosome, gene region and genomic feature. The effective coverage of all cytosine in each chromosome ranges from 82.77% to 97.86%, except for 24.96% in chr17 , while the CpG effective coverage of each chromosome ranges from 86.74% to 97.5%, except for 23.58% in chr17 (Table S1). Moreover,coverage of all cytosine in CDS and intron region was 95.94% and 93.66%, respectively and CG coverage in CDS and intron region was 96.04% and 93.45%, respectively (Table S 2).DNA methylation patternsIn Tibetan chicken, the methylation level of all genomic C sites was much than 3.9%. Patterns of Cytosine methylation in Tibetan chicken were found to have three major types (mCG, mCHG and mCHH) according to the sequence context. We discovered overall genome-wide levels of 51.22% CG, 0.4% CHG, and 0.45% CHH methylation in the Tibetan chicken (Table 3). In whole genome, the CG methylation occupied over 96% of cytosine methylation, which is the primary cytosine methylation pattern. However, the rate of mCHH was only 3% and the rate of mCHG was 1%(Fig. 1A).Methylation status of CG, CHG and CHH differ between species, even varies with different conditions concerning time, space and physiology inwardly a single organism. Figure 1b showed that percentage of the methylation level of methyl-cytosine varies with methylation level. In the tibet chicken blood, more than 75 % of mCG sites were 60-100 % methylated (Fig. 1b). In addition, chromosome1 was used as an in stance to illuminate the methyl-cytosine density distribution in chromosome, and the methyl-cytosine density showed self-aggrandising variations throughout the chromosome 1, which was similar to other chromosomes (Fig. 1c)Proximal Sequence Features AnalysisTo separate whether the particular local sequences were markedly enriched as the DNA methylome of Arabidopsis, we analyzed the sequence adjacent to sites of CG and non-CG methylation. The methylation ratios of all potential 9-mer sequences were calculated, and the methylated cytosine was located at the fourth military strength in these sequences (permitting an analysis of three bases upstream of CHG, and CHH methylation). As shown in figure 2, hardly a sequence optence was found in the CG-flanking regions of the hole genome or in the mCG-flanking regions. Moreover, the highest frequency base that next to the CHG cytosine in genome was A, followed by T and C, while the base following the mCHG methylcytosine has a preference for T, followed by A and C. In CHH context, the fifth position that proximal to the sites of cytosine has a preference for C, and the sixth position prefer to T, which is similar to the mCHH(Fig. 2).DNA methylation levels of different functional regionsDifferent genomic features are associated with distinct regulation functions. To study the DNA methylation profile in different genomic features, the affectionateness map was used to present the distribution of methylation level in the CDS, downstream, Genome, intron and upstream (fig. 3). The comparative analysis of mean DNA methylation levels revealed that different gennome regions showed distinguishing DNA methylation levels. Additionally, we analyzed DNA methylation patterns across the transcriptional units at whole genome level. In Tibet chicken, most of the instrument regions have an association with CpG islands and are hypomethylated, which showed a lower CG methylation level than the gene-body and the gene downstream. Moreover , methylation of CG declined sharply before the toxic shock and increased markedly towards the gene body regions and stayed at a plateau until the 3 end of the gene body, and two obvious peaks were present in the regions of the internol coding DNA and the last exon (Fig. 3). The methylation of CHG had the same varying tendency with the methylation of CG, but was characterised by mitigatory smorgasbords compared to the rapid changes of CG methylation. Furthermore, the methylation peaks of both CG and CHG were presented in the internal and last exons in which the methylation lows of CHH appeared.DNA methylation levels of lifter and genebodyMethylation of the promoter suppresses gene expression, but the functional grapheme of gene-body DNA methylation in extremely expressed genes has yet to be clarified. To better characterise the methylation of promoter and gene-body, a comprehensive analysis of methylated genes and unmethylated genes in gene-body and upstream2k was performed. In total, 14,018 genes were methylated in both promoter and gene-body, while 505 genes were exclusively methylated in promoter and 409 genes were exclusively methylated in gene-body, and 231 genes unmethylated in both promoter and gene-body (fig. 4A). Gene ontology analysis of methylated and unmethylated genes revealed the top-ranked enriched GO terms were related to the cellular process, metabolic process, and response to stimulus in the biological process (BP) category. The cellular persona (CC) category mainly comprised genes involved in cell, cell part, and organelle. Within the molecular function (MF) category, binding, catalytic activity, and transporter activity were highly represented (fig. 4B and 3S). In addition, KEGG analysis showed that genebody methylation genes were clustered in the metabolic pathways, protein processing in endoplasmic reticulum, and atomic number 20 signaling pathway, while the genebody unmethylation genes were clustered in metabolic pathways, Fc gam ma R-mediated phagocytosis, and endocytosis. Moreover, promoter methylation genes were most involved in ubiquitin mediated proteolysis, oocyte meiosis, and melanoma, while , promoter unmethylation genes were most involved in N-Glycan biosynthesis, Glycosylphosphatidylinositol(GPI)-anchor biosynthesis, and Fat digestion and absorption (fig. 5).DNA methylation and gene expression levelDNA methylation of promoter generally suppress gene transcription via inducing a compact chromatin structure. We obtained the gene expression profiles of Tibetan chicken from the GEO database. Based on expression levels, all genes were divided into ten groups, from the lowest 10% and to the highest 10%. Furthermore, the genomic regions that 2 kb upstream of the TSS were defined as the proximal promoter, and used the mean methylation as the methylation level of each group. The correlation analysis showed that gene expression level was negatively related to the mean DNA methylation level of the promoter re gions (fig. 6A r=-0.93, pshowed little difference in these ten groups with different expression level (fig. 6B r=-0.83, pDiscussionGenomics technologies have been extensively used to investigate the adaptations of humans, animals and plants to extreme conditions 15, 16. However, the relationships between the adaptions and the epigenetic modifications that result from extreme environmental photographs remains to be get along elucidated. To date, the methylation pattern of Tibetan chicken remains unknown. To improve our understanding of the association between epigenetic modifications andadaptations to hypoxia and high-dose ultraviolet radiation in high-altitude environments, we analyzed whole-genome single-base resolution DNA methylomes by WGBS to provide the genomewide DNA methylation patterns in Tibetan chicken blood and interrogate the potential role of DNA methylation in adaptations to high-altitude environments.Genome-wide DNA methylations of lowland chickens have been researc hed using MeDIP-seq 17, 18, MBD-Seq 19, and Methyl-MAPS 20, which measure methylation base on immunoprecipitation and restriction enzyme digestion. Compared to WGBS, these technologies generate lower resolution and coverage, and fail to obtain methylation level for CHG and CHH. For example, Only 32 % of CpG coverage was obtained from the study of lowland chicken using Methyl-MAPS 20. In the other lowland chicken study, the CpG coverage ranges from 83.72 to 91.57 % using MethylC-seq 21. In the current study, the CpG effective coverage of each chromosome ranges from 86.74% to 97.5%, except for 23.58% CpG coverage of chr17 in Tibet chicken.In lowland chicken, more than 55.69% of cytosines in CG contexts were methylated which is much higher than those in Tibet chicken (51.22%), while the percentage of mCHG and mCHH in Tibet chicken was higher than those in lowland chicken. In addition, 96.24 %, 0.86 % and 2.89 % of all methylcytosines were present in the CG CHG and CHH context, respecti vely, while the CG methylation in Tibet chicken occupied only 96% of cytosine methylation. Moreover, the base next to methylcytosine of mCHG in lowland chicken had a preference for A, while that in highland chicken prefer to T. All these indicated that the highland environments decrease the global CG methylation levels of chicken, and change the sequence context preferences for methylation, suggesting that the methylation involve in the adaptations of chicken to high-altitude environments.In Tibetan chicken genome, the DNA methylation level rapidly down before the TSS and markedly increased towards the gene body regions and stayed at a plateau until the 3 end of the gene body. These methylation features discovered in this study consistently match with those previously reported in bovine placentas 22. Similar to the lowland chickengenome, the Tibetan chicken genome has two CG methylation peaks in the internal and last exons, but the difference is that the lowland chicken genome showe d a mitigatory methylation level in the genome regions before the TSS 21, suggesting that the long-term hypoxia and UV radiation under high-altitude conditions cause methylation alternation.The promoter plays a crucial role in the regulation of gene transcription and most of the promoter regions are hypomethylated 23, while the gene-body DNA methylation is associated with chromatin structure and elongation efficiency, and prevents spurious transcription initiation 24, 25. In present study, we found the promoter is hypomethylated, whereas the methylation level in gene-body is relatively high, a purpose that is similar to those from previously reported in human 26 and lowland chicken 17. Hypermethylation of the promoters represses gene transcription 27, and the reduction of methylation at the promoters causes gene overexpression 28. In human embryologic stem cells, Laurent et al. reported that 20% of the most highly expressed genes displayed the lowest methylation levels in promoter . We analyse the relationship between the methylation and the expression inTibetan chicken, using the method reported in previous studies 17. Similar to reports in humans 17, 29, 30 and lowland chicken 5, DNA methylation level in 2 kb upstream of genes is negatively related to the gene expression level in Tibetan chicken, this was raise evidence that DNA methylation at the promoters is involved in gene silencing.Methylation in gene-body is more prevalent than in promoter, but the role of gene-body methylation in gene regulation remains unclear. Previous researchs showed that gene-body methylation has an intricate correlation with expression level. Most researchers believed that the methylation of gene-body is positively correlated with gene expression 26, 29, 31, 32, although several(prenominal) researchers have indicated that intragenic methylation might inhibit gene transcription 24. However, the correlation between gene-body methylation and expression levels in bovine placentas is non-monotonic and the moderately expressed genes show the highest methylation in gene-body 22. Our data demonstrated that methylation in the gene-body of Tibetan chicken may decrease gene expression. However, methylation in gene-body is just one of the thousands of factors that affect gene transcription. Therefore, further studies centering on the DNA methylation of certain regions that display distinct effect in gene regulation are needed to clarify the tangled epigenetic mechanism underlying high-altitude environments and its relationships with adaptations to hypoxia and high-dose ultraviolet radiation in high-altitude environments.In summary, the present study provides the first comprehensive analysis of genome-wide DNA methylation patterns in the blood of highland chicken, and our results can be used for future studies on epigenetic gene regulation in highland chicken. This study contributes to the knowledge on epigenetics in highland animals.References1. Tirado-Magallanes, R., et al., Whole genome DNA methylation beyond genes silencing. Oncotarget, 2017. 8(3) p. 5629-5637.2. Li, S., et al., Genome-wide analysis reveals that exon methylation facilitates its discriminating usage in the human transcriptome. Brief Bioinform, 2017.3. Keown, C.L., et al., Allele-specific non-CG DNA methylation marks domains of nimble chromatin in female mouse brain. Proc Natl Acad Sci U S A, 2017.4. Daxinger, L. and E. Whitelaw, Transgenerational epigenetic inheritance more questions than answers. Genome Res, 2010. 20(12) p. 1623-8.5. Chen, Z.J., Genetic and epigenetic mechanisms for gene expression and phenotypic variation in plant polyploids. Annu Rev Plant Biol, 2007. 58 p. 377-406.6. De Prins, S., et al., Influence of ambient air pollution on global DNA methylation in healthy adults a seasonal follow-up. Environ Int, 2013. 59 p. 418-24.7. Bollati, V., et al., Changes in DNA methylation patterns in subjects loose to low-dose benzene. Cancer Res, 2007. 67(3) p. 876-80. 8. Xing, C., et al., Methylation and expression analysis of tumor suppressor genes p15 and p16 in benzene poisoning. Chem Biol Interact, 2010. 184(1-2) p. 306-9.9. Kim, K.Y., et al., Association of low-dose exposure to persistent organic pollutants with global DNA hypomethylation in healthy Koreans. Environ Health Perspect, 2010. 118(3) p. 370-4.10. Pilsner, J.R., et al., Influence of prenatal lead exposure on genomic methylation of cord blood DNA. Environ Health Perspect, 2009. 117(9) p. 1466-71.11. Crews, D., et al., Transgenerational epigenetic imprints on mate preference. Proc Natl Acad Sci U S A, 2007. 104(14) p. 5942-6.12. Srivastava, S., et al., Association of polymorphisms in angiotensin and aldosterone synthase genes of the renin-angiotensin-aldosterone system with high-altitude pulmonary edema. J Renin Angiotensin Aldosterone Syst, 2012. 13(1) p. 155-60.13. Li, M. and C. Zhao, Study on Tibetan Chicken embryonic adaptability to chronic hypoxia by revealing differential gene expression in heart tissue. Sci China C Life Sci, 2009. 52(3) p. 284-95.14. Li, R., et al., SOAP2 an improved ultrafast tool for misfortunate read alignment. Bioinformatics, 2009. 25(15) p. 1966-7.15. Turner, T.L., et al., commonwealth resequencing reveals local adaptation of Arabidopsis lyrata to serpentine soils. Nat Genet, 2010. 42(3) p. 260-3.16. Liu, S., et al., Population genomics reveal recent speciation and rapid evolutionary adaptation in gelid bears. Cell, 2014. 157(4) p. 785-94.17. Li, Q., et al., Genome-wide mapping of DNA methylation in chicken. PLoS One, 2011. 6(5) p. e19428.18. Hu, Y., et al., Comparison of the genome-wide DNA methylation profiles between aggressive and slow-growing broilers. PLoS One, 2013. 8(2) p. e56411.19. Carrillo, J.A., et al., Methylome Analysis in Chickens Immunized with Infectious Laryngotracheitis Vaccine. PLoS One, 2015. 10(6) p. e0100476.20. Tian, F., et al., DNMT gene expression and methylome in Mareks disease resistant and susceptibl e chickens prior to and following infection by MDV. Epigenetics, 2013. 8(4) p. 431-44.