Dataset Information

Transcriptomic analysis of different tissue layers in antler growth Center in Sika Deer (Cervus nippon).

ABSTRACT: BACKGROUND:With the unprecedented rapid growth rate (up to 2.75?cm/day), velvet antler is an invaluable model for the identification of potent growth factors and signaling networks for extremely fast growing tissues, mainly cartilage. Antler growth center (AGC) locates in its tip and consists of five tissue layers: reserve mesenchyme (RM), precartilage (PC), transition zone (TZ), cartilage (CA) and mineralized cartilage (MC). The aim of this study was to investigate the transcription dynamics in the AGC using RNA-seq technology. RESULTS:Five tissue layers in the AGC were collected from three 3-year-old male sika deer using our previously reported sampling method (morphologically distinguishable). After sequencing (15 samples; triplicates/tissue layer), we assembled a reference transcriptome de novo and used RNA-seq to measure gene expression profiles across these five layers. Nine differentially expressed genes (DEGs) were selected from our data and subsequently verified using qRT-PCR. The results showed a high consistency with the RNA-seq results (R2?=?0.80). Nine modules were constructed based on co-expression network analysis, and these modules contained 370 hub genes. These genes were found to be mainly involved in mesenchymal progenitor cell proliferation, chondrogenesis, osteogenesis and angiogenesis. Combination of our own results with the previously published reports, we found that Wnt signaling likely plays a key role not only in stimulating the antler stem cells or their immediate progeny, but also in promoting chondrogenesis and osteogenesis during antler development. CONCLUSION:We have successfully assembled a reference transcriptome, generated gene expression profiling across the five tissue layers in the AGC, and identified nine co-expressed modules that contain 370 hub genes and genes predorminantly expressed in and highly relevant to each tissue layer. We believe our findings have laid the foundation for the identification of novel genes for rapid proliferation and chondrogenic differentiation of antler cells.

SUBMITTER: Ba H

PROVIDER: S-EPMC6402185 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Transcriptomic analysis of different tissue layers in antler growth Center in Sika Deer (Cervus nippon).

Ba Hengxing H Wang Datao D Yau Tung On TO Shang Yudong Y Li Chunyi C

BMC genomics 20190305 1

<h4>Background</h4>With the unprecedented rapid growth rate (up to 2.75 cm/day), velvet antler is an invaluable model for the identification of potent growth factors and signaling networks for extremely fast growing tissues, mainly cartilage. Antler growth center (AGC) locates in its tip and consists of five tissue layers: reserve mesenchyme (RM), precartilage (PC), transition zone (TZ), cartilage (CA) and mineralized cartilage (MC). The aim of this study was to investigate the transcription dyn ...[more]

PMID: 30836939

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Project description:BackgroundChina is the birthplace of the deer family and the country with the most abundant deer resources. However, at present, China's deer industry faces the problem that pure sika deer and hybrid deer cannot be easily distinguished. Therefore, the development of a SNP identification chip is urgently required.ResultsIn this study, 250 sika deer, 206 red deer, 23 first-generation hybrid deer (F1), 20 s-generation hybrid deer (F2), and 20 third-generation hybrid deer (F3) were resequenced. Using the chromosome-level sika deer genome as the reference sequence, mutation detection was performed on all individuals, and a total of 130,306,923 SNP loci were generated. After quality control filtering was performed, the remaining 31,140,900 loci were confirmed. From molecular-level and morphological analyses, the sika deer reference population and the red deer reference population were established. The Fst values of all SNPs in the two reference populations were calculated. According to customized algorithms and strict screening principles, 1000 red deer-specific SNP sites were finally selected for chip design, and 63 hybrid individuals were determined to contain red deer-specific SNP loci. The results showed that the gene content of red deer gradually decreased in subsequent hybrid generations, and this decrease roughly conformed to the law of statistical genetics. Reaction probes were designed according to the screening sites. All candidate sites met the requirements of the Illumina chip scoring system. The average score was 0.99, and the MAF was in the range of 0.3277 to 0.3621. Furthermore, 266 deer (125 sika deer, 39 red deer, 56 F1, 29 F2,17 F3) were randomly selected for 1 K SNP chip verification. The results showed that among the 1000 SNP sites, 995 probes were synthesized, 4 of which could not be typed, while 973 loci were polymorphic. PCA, random forest and ADMIXTURE results showed that the 1 K sika deer SNP chip was able to clearly distinguish sika deer, red deer, and hybrid deer and that this 1 K SNP chip technology may provide technical support for the protection and utilization of pure sika deer species resources.ConclusionWe successfully developed a low-density identification chip that can quickly and accurately distinguish sika deer from their hybrid offspring, thereby providing technical support for the protection and utilization of pure sika deer germplasm resources.

Project description:BackgroundTwo species of deer ked (Lipoptena cervi and L. mazamae) have been identified as vectors of Bartonella bacteria in cervids in Europe and the USA. In an earlier study we showed that Japanese sika deer (Cervus nippon) harbor three Bartonella species, namely B. capreoli (lineage A) and two novel Bartonella species (lineages B and C); however, there is currently no information on the vector of Bartonella bacteria in sika deer. The aim of this study was to clarify potential vectors of Bartonella in Japanese sika deer.MethodsThirty-eight wingless deer keds (L. fortisetosa) and 36 ticks (Haemaphysalis and Ixodes species) were collected from sika deer. The prevalence of Bartonella in the arthropods was evaluated by real-time PCR targeting the 16S-23S internal transcribed spacer (ITS) and by culture of the organisms. The total number of Bartonella bacteria were quantified using real-time PCR. The distribution of Bartonella bacteria in deer ked organs was examined by immunofluorescence analysis. The relationship of Bartonella strains isolated from sika deer and arthropods were examined by a phylogenetic analysis based on concatenated sequences of the gltA, rpoB, ftsZ, and ribC genes, followed by a BLAST search for gltA and rpoB.ResultsBartonella prevalence in deer keds was 87.9% by real-time PCR and 51.5% in culture and that in the ticks was 8.3% by real-time PCR and 2.8% in culture. The mean number of Bartonella bacteria per ked was calculated to be 9.2 × 105 cells. Bartonella aggregates were localized in the midgut of the keds. The phylogenetic analysis and BLAST search showed that both the host deer and the keds harbored two Bartonella species (lineages B and C), while B. capreoli (lineage A) was not detected in the keds. Two novel Bartonella species (lineages D and E) were isolated from one ked.ConclusionsLipoptena fortisetosa likely serves as a vector of at least two Bartonella species (lineages B and C), whereas ticks do not seem to play a significant role in the transmission of Bartonella between sika deer based on the lower detection rates of Bartonella in ticks compared to keds. Bartonella species in lineages D and E appear to be L. fortisetosa-specific strains.

Dataset Information

Transcriptomic analysis of different tissue layers in antler growth Center in Sika Deer (Cervus nippon).

Publications

Transcriptomic analysis of different tissue layers in antler growth Center in Sika Deer (Cervus nippon).

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