渔业科学进展  2023, Vol. 44 Issue (5): 125-136  DOI: 10.19663/j.issn2095-9869.20220413001
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引用本文 

李雨, 凌乐妍, 金鸿浩, 李哲, 高源, 刘蕃, 罗辉, 叶华. 基于转录组测序技术挖掘长吻生长关键基因[J]. 渔业科学进展, 2023, 44(5): 125-136. DOI: 10.19663/j.issn2095-9869.20220413001.
LI Yu, LING Leyan, JIN Honghao, LI Zhe, GAO Yuan, LIU Fan, LUO Hui, YE Hua. Mining of Key Genes Related to Growth of Chinese Longsnout Catfish (Leiocassis longirostris) Based on Transcriptome Analysis[J]. Progress in Fishery Sciences, 2023, 44(5): 125-136. DOI: 10.19663/j.issn2095-9869.20220413001.

基金项目

国家自然科学基金(31402302)、重庆市自然科学基金(cstc2021jcyj-msxmX0837)、重庆市水产科技创新重点攻关项目和重庆市大学生创新创业训练计划(S202110635274)共同资助

作者简介

李雨,E-mail: aliyu0208@163.com

通讯作者

叶华,教授,E-mail: yhlh2000@126.com

文章历史

收稿日期:2022-04-13
收修改稿日期:2022-06-01
基于转录组测序技术挖掘长吻生长关键基因
李雨 , 凌乐妍 , 金鸿浩 , 李哲 , 高源 , 刘蕃 , 罗辉 , 叶华     
西南大学水产学院 淡水鱼类资源与生殖发育教育部重点实验室 重庆 402460
摘要:为挖掘我国名优鱼类长吻(Leiocassis longirostris)生长相关基因,本研究运用Illumina高通量测序技术比较分析了快速生长组[平均体质量为(534.02±53.68) g]和缓慢生长组[平均体质量为(108.41±4.96) g]各9尾长吻的脑组织基因表达谱。测序共获得267 404 674个高质量测序片段(clean reads),通过2种不同生长速率长吻脑组织转录组比较筛选出518个差异表达基因,其中,412个基因表达量上调,106个基因表达量下调。对12个差异表达基因进行实时荧光定量PCR验证的结果与转录组测序结果一致。GO功能分类显示,大量差异表达基因富集到生长(growth)、生长因子活性(growth factor activity)和激素介导的信号通路(hormone-mediated signaling pathway) GO条目中。KEGG富集分析显示,一些差异表达基因在MAPK信号通路(MAPK signaling pathway)、转化生长因子β信号通路(TGF-beta signaling pathway)、钙离子信号通路(calcium signaling pathway)和神经活性配体–受体相互作用(neuroactive ligand-receptor interaction)等途径中富集。根据GO功能注释和KEGG富集分析,筛选出gnrhthregr1fgf18sstgiprcartcrf等基因是调控长吻生长发育的关键候选基因。本研究结果为后续深入研究长吻生长调控机制提供了重要的参考资料。
关键词长吻    鱼类生长    转录组测序    神经内分泌因子    
Mining of Key Genes Related to Growth of Chinese Longsnout Catfish (Leiocassis longirostris) Based on Transcriptome Analysis
LI Yu , LING Leyan , JIN Honghao , LI Zhe , GAO Yuan , LIU Fan , LUO Hui , YE Hua     
Key Laboratory of Freshwater Fish Reproduction and Development, Ministry of Education, College of Fisheries, Southwest University, Chongqing 402460, China
Abstract: The Chinese longsnout catfish (Leiocassis longirostris) is a rare and valuable freshwater fish wildly distributed throughout China. Fish growth is one of the most economically important traits in fish farming. Cultured fish with high growth performance can often bring direct economic benefits while meeting human food demand. The hypothalamus is an important regulatory organ in fish metabolic processes and endocrine activities, directly or indirectly regulating fish growth. Although significant research on L. longirostris has been reported, the molecular mechanisms and key genes involved in its growth are still unclear. Therefore, we performed comparative transcriptomics analysis using Illumina high throughput sequencing technology and analyzed transcript profiles of the brains from fast-growth (FG) with average body mass of (534.02±53.68) g, and slow-growth (SG) with average body mass og (108.41±4.96) g L. longirostris individuals. A total of 267 404 674 clean reads were generated, and 518 differentially expressed genes were identified, of which 412 genes were up-regulated and 106 genes were down-regulated in fast-growth fishes. Then, we subjected all these differentially expressed genes to GO term enrichment and KEGG pathway analysis to find the underlying function annotation. Based on Gene Ontology analysis, plenty of differentially expressed genes were enriched in growth, growth factor activity, and hormone-mediated signaling pathway. KEGG enrichment analysis indicated that some differentially expressed genes involved in MAPK signaling pathway, TGF-beta signaling pathway, calcium signaling pathway, and neuroactive ligand-receptor interaction were enriched. With the differentially expressed genes identified from GO and KEGG enrichment analysis, several key genes related to the growth of L. longirostris were screened, such as gnrh, thr, egr1, fgf18, sst, gipr, cart, and crf. The results of this study enriched the gene resources and provided valuable references for further study on the regulation mechanism of growth of L. longirostris.
Key words: Leiocassis longirostris    Fish growth    Transcriptome sequencing    Neuroendocrine factors    

生长是养殖水产动物最具经济价值的性状之一,生长性能高的养殖鱼类往往能在满足人类食物需求的同时带来直接的经济效益。与哺乳动物相似,鱼类生长包括了能量代谢和肌肉生长等多种过程,主要受环境、基因以及基因与环境相互作用的影响,是一个复杂的数量性状(Dai et al, 2015)。目前,研究者们从肌肉生成和肝脏代谢过程的角度出发,已挖掘出多种鱼类的生长相关基因和生长调控机制。如王兰梅等(2021)确定了mbmy12btnnil等6个基因为福瑞鲤2号(Cyprinus carpio)肌肉生长的关键基因;Li等(2022)初步证明禾花鲤(Cyprinus carpio)生长差异可能是由于蛋白质沉积引起肌纤维肥大所致,进而表明了泛素–蛋白酶体途径是影响禾花鲤生长的重要因素;Zhang等(2021)在草鱼(Ctenopharyngodon idella)肝脏组织中鉴定出的ghrigf1igf1r主要在PI3K-Akt和mTOR信号通路中参与生长调控。然而,下丘脑可直接或间接地对机体生理节律、摄食、繁殖和生长等生命活动进行调控,是代谢过程和内分泌活动的重要神经调节中枢(Piórkowska et al, 2020)。一些神经内分泌因子(GH、GnRH、NPY、THR、CCK和SST等)和神经调控轴也对鱼类的生长调节起着不可或缺的作用(Canosa et al, 20072020; Dai et al, 2015; Li et al, 2010; Christian et al, 2007; Peng et al, 1997)。因此,利用脑组织开展鱼类生长的研究有利于分析生长相关的神经内分泌调控网络及关键基因。

转录组测序技术有助于深入探究细胞中基因的转录和转录调控。近年来,转录组学技术已广泛应用于水产动物免疫应答(Xue et al, 2021)、生长发育(Liu et al, 2020)、生物进化(Schunter et al, 2014)和环境适应(Yao et al, 2021)等方面的研究,有效地进行了功能基因挖掘、特异性状主效基因搜索和基因表达调控等研究(Ye et al, 2018; 罗辉等, 2015)。转录组测序技术的运用在很大程度上满足了水产动物生长发育相关功能基因和调节机制研究的需要,已在多种鱼类中确定了与生长相关的候选基因及其表达模式(王兰梅等, 2021; Lu et al, 2020; Tian et al, 2020; Lin et al, 2019)。

长吻(Leiocassis longirostris)是我国名贵淡水经济鱼类之一,曾广泛分布于辽河、黄河、淮河、长江、珠江和岷江(Xiao et al, 2009)。因其肉质鲜美、口感爽滑、无肌间刺、含肉率高,且肌肉中粗蛋白和鲜味氨基酸总量高于青鱼(Mylopharyngodon piceus)、草鱼和鳙鱼(Aristichthys nobilis)等常见食用鱼类,而深受广大消费者的喜爱(张升利等, 2013)。2020年我国长吻年产量接近2.12万t (农业农村部渔业渔政管理局等, 2021),在名优经济鱼类养殖中占有重要地位。目前,关于长吻的报道多见于对养殖环境条件的免疫应答(Han et al, 2011; Zhao et al, 2009; Han et al, 2005)和营养与饲料等方面(Su et al, 2020; Pei et al, 2015; Dong et al, 2011; Zhu et al, 2005),其生长相关的关键基因未见报道,生长的分子调控机制尚不清晰。本课题组近两年在长吻染色体水平基因组组装(He et al, 2021)、生长相关SNP标记开发(Zhao et al, 2020)以及形态性状与体质量的关系(李哲等, 2021)方面做了大量工作。在此基础上,本研究拟采用高通量测序技术对生长速率呈现极端差异的长吻个体脑组织转录组进行比较分析,旨在筛选出与长吻生长相关的候选基因,以期为长吻生长性状改良以及后续基因的功能研究提供参考依据。

1 材料与方法 1.1 实验鱼与样品采集

实验用长吻采自四川省农科院水产研究所宜宾基地。随机选取200尾30月龄同一批次繁殖、同一个池塘养殖的长吻,依次用低剂量MS-222麻醉后,称量体重并记录数据。根据体质量选取其中9尾极大个体作为快速生长组(fast-growing, FG),9尾极小个体作为缓慢生长组(slow-growing, SG) (表 1)。解剖判定性别后,快速分离出脑组织,充分浸泡于Sample Protector for RNA/DNA (TaKaRa)中,过夜后置于–80 ℃冰箱保存备用。

表 1 长吻体质量测定结果(g, 平均值±标准差) Tab.1 Body mass of L. longirostris (g, Mean±SD)
1.2 长吻脑组织总RNA提取

参照TRIzol试剂(Invitrogen, 美国)的操作说明提取18尾长吻脑组织的总RNA,并用DNaseⅠ(TaKaRa)去除总RNA中的基因组DNA。使用Agilent 2100 Bioanalyzer检测RNA完整性及总量,Qubit® 2.0 Flurometer (Life Technologies, 美国)测定总RNA浓度。所提取的总RNA一部分用于转录组测序,另一部分用于后续实时荧光定量PCR (qRT-PCR)验证。

1.3 cDNA文库构建与测序

分别从2个组中随机选择3个个体RNA等量混合,通过带有Oligo (dT)的磁珠富集mRNA后,用Fragmentation Buffer将mRNA随机打断,再以片段化的mRNA为模板合成cDNA第一链和第二链。合成的双链cDNA经纯化后,先进行末端修复、加A尾并连接测序接头,再用AMPure XP beads筛选370~420 bp左右的cDNA片段进行PCR扩增并纯化扩增产物,最终构建长吻 FG组和SG组脑组织文库各3个,标记为FG1、FG2、FG3和SG1、SG2、SG3。质检合格的文库最终进行Illumina NovaSeq 6000上机测序,测序读长为双端150 bp。文库构建和转录组测序工作均由诺禾致源生物信息科技有限公司(天津)完成。

1.4 转录组测序质量控制

测序获得的原始数据(raw reads)中包含少量带有接头或测序质量较低的reads,为保证转录组分析质量及有效性,需对原始数据进行过滤。具体包括:剔除由于测序仪器误差和人为因素导致的低质量reads (QPhred≤20的碱基数占整个read长度的50%以上);去除含N (无法确定碱基信息)比率超过10%的reads;识别并切除带有接头序列的reads。

1.5 基因功能注释和基因差异表达分析

使用HISAT2(v2.0.5)软件将clean reads与长吻参考基因组(He et al, 2021)进行比对,以获取reads在参考基因组上的定位信息。根据FPKM (fragments per kilobase of exon model per million mapped reads)值估计FG组和SG组的基因表达量。利用DEGseq2 (v1.20.0)软件进行FG组和SG组之间的差异表达分析,差异基因筛选阈值为P < 0.05且|log2(fold change)| > 1。通过clusterProfiler (v3.4.4)软件实现差异表达基因的GO功能注释和KEGG富集分析。

1.6 qRT-PCR验证

选取12个差异倍数较大的差异表达基因进行qRT-PCR,验证测序结果的准确度,相关引物见表 2。参照PrimeScriptTM RT-PCR (TaKaRa)试剂盒说明书进行逆转录,获得对应cDNA,以β-actin为内参基因,在ABI QuantStudio 3 Real-Time PCR系统上进行,每个样品的技术重复均为3。反应体系为10 μL: 5 μL 2×TB Green Premix Ex Taq Ⅱ (TaKaRa),0.2 μL ROX Reference Dye Ⅱ (50×),3 μL灭菌水,1 μL cDNA模板和上下游引物各0.4 μL (10 μmol/L)。反应条件:预变性95 ℃ 30 s;95 ℃ 5 s,60 ℃ 34 s,40个循环;95 ℃ 15 s,60 ℃ 1 min,95 ℃ 15 s。

表 2 验证所用引物信息 Tab.2 The information of primers used for validation
1.7 数据统计及分析

体质量测定数据均以平均值±标准差(Mean±SD)表示,并采用SPSS 26.0软件进行独立样本T检验,P < 0.05表示差异极显著。qRT-PCR验证数据以2–ΔΔCt法计算基因的相对表达量,并采用SPSS 26.0软件对结果进行统计分析。

2 结果 2.1 长吻体质量测定结果

所选18尾长吻中,FG组包含6尾雌性个体和3尾雄性个体,SG组包含5尾雄性个体和4尾雌性个体。实验鱼体质量数据的独立样本T检验结果表明,雄性长吻和雌性长吻体质量的平均值无显著差异,且同一生长速率组中,雌、雄个体体质量平均值无显著差异;FG组和SG组各9尾长吻体质量的平均值差异显著(P < 0.05) (表 1)。

2.2 转录组测序结果

经转录组测序获得的FG和SG文库的raw reads分别为134 682 652和137 487 704。质控后获得的clean reads分别为132 315 488和135 089 186。碱基质量及组成分析显示,各组GC含量区间为45.04%~ 45.64%,各样品Q30的碱基质量值比例均大于92% (表 3),表明转录组测序数据质量高,可以用于后续分析。长吻 FG和SG组脑组织的转录组测序结果已提交至NCBI的SRA数据库(PRJNA833735)。

表 3 RNA-Seq数据统计 Tab.3 Summary of RNA-Seq data
2.3 差异表达基因统计及表达模式分析

基于表达量指标FPKM,以P < 0.05、|log2(fold change)| > 1为阈值,对同一基因在FG组和SG组中的表达进行统计分析。与SG组相比,FG组中有412个基因表达量上调,106个基因表达量下调(图 1)。进一步对FG组和SG组间的518条差异基因进行层次聚类(hierarchical clustering)分析(图 2)。聚类结果显示,这些差异基因在2个比较组间的表达模式相差较大,而在组内不同样品间的表达模式比较相似。

图 1 长吻脑组织差异表达基因火山图 Fig.1 Volcano plot of L. longirostris brain transcriptome differentially expressed genes
图 2 差异表达基因聚类热图 Fig.2 Heat-map of differentially expressed genes 图中每行代表一个基因,每列代表一个样品;不同颜色区域分别代表不同的聚类分组信息,颜色由红到蓝表示差异表达基因的表达量由高到低。 In the heat-map, each row represents one gene and each column represents one sample; Different color areas represent different clustering information, the color from red to blue represents the expression intensity of differentially expressed genes from high to low.
2.4 差异表达基因的GO功能分类和KEGG富集分析

通过clusterProfiler (v3.8.1)软件对差异表达基因进行GO和KEGG富集分析,在GO功能分类体系中,518条差异表达基因共获得463个GO功能注释。其中,生物学过程类别(biological process, BP) 215个,细胞组分(cell composition, CC) 51个,分子功能类别(molecular function, MF) 197个。由前30个显著富集的GO terms可见,在生物学过程类型中,大量上调基因富集到免疫反应(immune response)、免疫系统过程(immune system process)和细胞死亡(cell death)等;细胞组分类别中,质膜部分(plasma membrane part)、细胞质膜(plasma membrane)和质膜蛋白复合物(plasma membrane protein complex)富集到的差异表达基因最多;涉及到分子功能的差异表达基因主要参与的生命过程有四吡咯结合(tetrapyrrole binding)、血红素结合(heme binding)以及辅因子结合(cofactor binding)等(图 3)。此外,有部分差异表达基因在生长(growth)、生长因子活性(growth factor activity)和激素介导的信号通路(hormone-mediated signaling pathway) GO terms中富集。

图 3 长吻脑组织差异表达基因GO富集分析 Fig.3 Gene ontology assignment of differentially expressed genes of L. longirostris

差异基因KEGG富集分析结果显示,长吻脑组织的差异表达基因富集到82条特定的代谢通路,其中,发生显著富集的KEGG通路有细胞因子与细胞因子受体相互作用(cytokine-cytokine receptor interaction)、产生IgA的肠道免疫网络(intestinal immune network for IgA production)、吞噬体(phagosome)、C型凝集素受体信号通路(C-type lectin receptor signaling pathway)和细胞粘附分子(cell adhesion molecules)(图 4)。此外,分别有17、21、16和7个差异表达基因在丝裂原活化蛋白激酶信号通路(MAPK signaling pathway)、神经活性配体–受体相互作用(neuroactive ligand-receptor interaction)、钙信号通路(calcium signaling pathway)和TGF-β (TGF-beta signaling pathway)途径中富集。

图 4 长吻脑组织差异表达基因KEGG通路图 Fig.4 KEGG pathway of differentially expressed genes of L. longirostris

参考脊椎动物生长信号通路调控模式和差异基因的功能,并根据差异表达基因的GO功能分类和KEGG富集分析,在相应的调控通路中初步筛选出19个与长吻生长相关的基因(图 5)。其中,参与神经活性配体–受体相互作用信号通路的有胃抑制多肽受体基因(gipr)、可卡因–安非他明调节转录肽(cart)和生长激素释放抑制激素(sst)等8个基因。参与丝裂原活化蛋白激酶信号通路的有成纤维细胞生长因子结合蛋白1 (fgfbp1)、成纤维细胞生长因子18 (fgf18)和E3泛素连接酶TRIM25等6个基因。参与TGF-β信号通路的有骨形态发生蛋白1 (bmp1)、骨形态发生蛋白4 (bmp4)和肌肉生长抑素(mstn)等4个基因。另外,促性腺激素释放激素受体(gnrhr)除了在促性腺激素释放激素信号通路(GnRH signaling pathway)发挥作用外,还参与到神经活性配体–受体相互作用信号通路。

图 5 筛选到的长吻生长相关基因 Fig.5 Screening of genes related to growth of L. longirostris x轴表示差异表达基因的差异倍数,y轴表示4个通路上的生长相关基因。其中,神经活性配体–受体相互作用信号通路:1. 生长激素释放抑制激素基因(sst);2. 催乳素基因(prl);3. 可卡因–安非他明调节转录肽基因(cart);4. 胃抑制多肽受体基因(gipr);5. 生长抑素和血管紧张素样肽受体基因;6. 促肾上腺皮质激素释放激素基因(crf);7. 5-羟色氨受体基因(5-htr);8. 促甲状腺激素释放激素受体基因(trhr)。丝裂原活化蛋白激酶信号通路:1. 成纤维细胞生长因子结合蛋白1基因(fgfbp1);2. 成纤维细胞生长因子18基因(fgf18);3. E3泛素连接酶TRIM25基因;4. 促血管生成素2基因(ang2);5. 胰岛素样生长因子Ⅱ基因(igfⅡ);6. 促红细胞生成素产生肝细胞配体A1基因(ephrin-a1)。促性腺激素释放激素信号通路:1. 促性腺激素释放激素受体基因(gnrhr)。转化生长因子β信号通路:1. 骨形态发生蛋白1基因(bmp1);2. 骨形态发生蛋白4基因(bmp4);3. 肌肉生长抑素基因(mstn);4. Persephin基因(pspn)。 The x-axis represents the fold change of the differentially expressed genes, and the y-axis represents the growth-related genes of four pathways. For neuroactive ligand-receptor interaction signaling pathway: 1. Somatostatin (sst); 2. Prolactin (prl); 3. Cocaine- and amphetamine- regulated transcript protein (cart); 4. Gastric inhibitory polypeptide receptor (gipr); 5. Somatostatin- and angiotensin-like peptide receptor; 6. Corticotropin-releasing factor (crf); 7. 5-hydroxytryptamine receptor (5-htr); 8. Thyrotropin-releasing hormone receptor (trhr). For MAPK signaling pathway: 1. Fibroblast growth factor binding protein 1 (fgfbp1); 2. Fibroblast growth factor 18 (fgf18); 3. E3 ubiquitin/ISG15 ligase TRIM25; 4. Angiopoietin-2 (ang2); 5. Insulin-like growth factor Ⅱ (igfⅡ); 6. Ephrin-A1 (ephrin-a1). For GnRH signaling pathway: 1. Gonadotropin-releasing hormone receptor (gnrhr). For TGF-β signaling pathway: 1. Bone morphogenetic protein 1 (bmp1); 2. Bone morphogenetic protein 4 (bmp4); 3. Myostatin (mstn); 4. Persephin (pspn).
2.5 qRT-PCR结果

用于qRT-PCR验证的差异表达基因包括4个上调基因:脂肪细胞型脂肪酸结合蛋白、同源异型盒蛋白、成纤维细胞生长因子结合蛋白1和成纤维细胞生长因子18;8个下调基因:小脑肽2、含DEP结构域的蛋白7、神经胶质蛋白、转录中介复合物亚基31、NADH泛醌氧化还原酶亚基10、生长激素抑制素、叉头框转录因子D3以及可卡因–安非他明调节转录肽。qRT-PCR验证结果显示,这12个差异表达基因的表达趋势与转录组测序结果基本一致(图 6),说明RNA-Seq分析结果可信。

图 6 差异表达基因的转录组测序和qRT-PCR比较(β-actin为内参基因) Fig.6 Comparison of differentially expressed genes by RNA-Seq and qRT-PCR (β-actin was used as an internal gene)
3 讨论

目前,运用转录组测序技术对水产动物生长发育进行的研究主要是针对肌肉生成和肝脏代谢过程。如Zhang等(2020)和Lu等(2020)分别构建了不同生长速率的青鱼和草鱼的肝脏以及肌肉转录组文库,筛选了几个与生长发育相关的关键基因和代谢途径;而对鱼类脑组织进行的转录组分析主要为了探究脑组织基因表达与生殖发育(Cardoso et al, 2018; Saaristo et al, 2017; Partridge et al, 2016)、生物学特性(Vu et al, 2021; Wei et al, 2021; Wang et al, 2020)以及环境适应能力(Bao et al, 2021; Feng et al, 2021; Zhang et al, 2020)的关系。鱼体的正常生理活动和生化过程是在神经系统的主导下实现的。脑作为中枢神经系统的重要组成部分,对神经内分泌轴上生长相关激素的合成和分泌具有不可替代的调控作用。除此之外,鱼类的生长涉及到复杂的调控网络,生长轴上的基因在调控鱼类的生长和代谢过程中扮演着关键的角色,而生长轴往往是处于脑的支配下参与鱼类生长过程。然而,目前鲜有通过鱼类脑组织挖掘生长相关基因的研究报道。现有研究主要有:Li等(2021)通过高通量测序,初步阐明了三倍体鲫鱼(Carassius auratus)生长快、抗病能力强的分子机制与基因表达水平升高密切相关;Robledo等(2017)分析了不同生长速率大菱鲆(Scophthalmus maximus)肌肉和脑组织基因表达谱,但在脑组织中只检测到几个差异表达基因,这些基因在先前的研究中被证实与鱼类感觉调控有关;Lin等(2021)对不同生长速率黑鲷(Acanthopagrus schlegelii)肝脏、肌肉和脑组织的混合样本进行了转录组测序,旨在挖掘生长相关候选基因和调控途径,但其结果尚不能说明黑鲷脑组织与其生长之间的关联。由此,仍需进一步明确鱼类脑组织与生长之间的关系和潜在的分子机制。因此,为探明长吻个体生长速率差异较大的原因,本研究选用不同生长速率的长吻脑组织构建文库进行转录组测序分析,拟筛选出与长吻生长相关的关键候选基因,以期为长吻生长性状改良以及后续功能基因研究提供参考依据。此外,将本研究结果与现有的以肌肉生长和肝脏代谢为主的鱼类生长调控模式研究进行对比,发掘更多潜在的关键基因和相关通路并深入了解长吻生长发育的内分泌调控机制。

鱼类的生长和发育受体内各种激素及其相互作用的调节,其中生长激素–胰岛素样生长因子轴(growth hormone-insulin like growth factor axis, GH-IGFs)是调控鱼类生长的内分泌核心(代向燕等, 2014),GH的合成和分泌是该过程的重要基础。在内分泌调节活动中,激素本身与相应受体匹配是其发挥作用的关键环节,促性腺激素释放激素(gonadotropin-releasing hormone, GnRH)和促甲状腺激素释放激素(thyrotropin-releasing hormone, TRH)主要是通过相应受体来介导并发挥生理功能。在本研究FG组和SG组脑组织的差异表达基因中,促性腺激素释放激素受体基因(gonadotropin- releasing hormone receptor, gnrhr)和促甲状腺激素释放激素受体基因(thyrotropin-releasing hormone receptor, trhr)高表达于FG组,提示可能有大量gnrhtrh与这些受体结合,并参与刺激长吻脑垂体释放GH,进而增强新陈代谢、细胞生长等过程的调节,最终达到促进长吻生长的目的。此外,在差异表达基因基因中,还筛选到生长激素释放抑制激素(somatostatin, SST)。SST是一种最早从绵羊下丘脑中分离获得的神经肽类激素(Brazeau et al, 1973),对GH的分泌起着最主要的抑制作用,在对虹鳟(Oncorhynchus mykiss)、金鱼(Carassius auratus)、红鲑鱼(Oncorhynchus nerka)和鲤鱼等的研究中,sst均被证明可以抑制GH的分泌(Fontaine et al, 2020)。本研究中,sst基因在SG组长吻脑组织中表达上调,表明该基因可能是导致长吻生长缓慢的主要因子之一。

除与生长激素调控相关的内分泌因子外,在差异表达基因中还筛选到了胰岛素样生长因子Ⅱ(insulin- like growth factor Ⅱ, igfⅡ)、成纤维细胞生长因子18 (fibroblast growth factor 18, fgf18)、成纤维细胞生长因子结合蛋白1 (fibroblast growth factor-binding protein 1, fgfbp1)和早期生长反应蛋白1 (early growth response protein, egr1)等生长相关基因以及NGFI-A结合蛋白2基因(NGFI-A-binding protein 2, nab2)。FGF家族nab2egr1的特异性抑制剂,可通过抑制egr1的转录调控过程来有效减少egr1的表达(陈子翔, 2016)。egr1是转录因子锌指蛋白家族的重要成员之一,可正向调控igfⅡfgf的表达,以达到促进机体生长发育的作用(Liu et al, 1996)。本研究中,igfⅡ、fgf18fgfbp1的表达趋势与egr1一致,均在FG组中上调表达,表明这几个基因可能是影响长吻生长性状的重要功能基因;而相较于FG组,nab2在SG组中上调表达,进一步说明在SG组中,该基因可能抑制了egr1的表达,从而导致长吻生长速率减慢,再次表明egr1可能与长吻生长密切相关。

本研究还鉴定了胃抑制多肽受体基因(gastric inhibitory polypeptide receptor, gipr)、可卡因–苯丙胺调节转录肽基因(cocaine- and amphetamine-regulated transcript, cart)和促肾上腺皮质激素释放激素基因(corticotropin-releasing factor, crf)。相关研究指出,gipr基因作为肥胖、脂代谢紊乱及代谢综合征的易感基因(晋梦诗, 2014),可直接作用于脂肪组织,促进脂质沉积,gipr基因敲除或缺失的小鼠通过改变其能量消耗和脂肪代谢,以抵抗高脂饮食引起的肥胖(Boer et al, 2021; Miyawaki et al, 2002)。cart最早在大鼠弓状核中分离得到(Douglass et al, 1995),是一种可作用于下丘脑的厌食肽(Valassi et al, 2008),参与哺乳动物机体的进食行为和体重调节。相对于野生型小鼠,cart基因敲除小鼠在正常饮食条件下体重明显增加(Wierup et al, 2005)。该基因在金鱼中同样被证明是一种厌食因子(Hélène et al, 2000),在大西洋鲑(Salmo salar)中发挥抑制食欲的功能(Murashita et al, 2009)。Crf为CRF系统中的一员,可作用于下丘脑–垂体–肾上腺(hypothalamic-pituitary-adrenal, HPA)轴,刺激垂体释放促肾上腺皮质激素(adrenocorticotropic hormone, ATCH)进而调控动物的摄食行为(齐锦雯等, 2018)。在对金鱼(De Pedro et al, 1993)和虹鳟(Ortega et al, 2013)的研究中,发现注射CRF后实验鱼的摄食量减少,推测CRF可能通过中枢调控影响鱼类的摄食行为。Wang等(2014)发现,齐口裂腹鱼(Schizothorax prenanti)在长期禁食(7 d)条件下,其下丘脑crf基因的表达量明显下降,复食后则回升,表明crf可能作为厌食欲因子调控鱼类摄食。此外,Smith等(2004)对大鼠的研究表明crf可上调cart参与厌食欲作用。因此,推测crf可能同样可与cart互作共同调控鱼类的摄食行为。本研究中,gipr在FG组长吻脑组织中高表达,推测gipr基因或为一种长吻生长和肥胖的调节因子,但其作用机制有待于进一步研究。而cartcrf在SG组中的表达量明显高于FG组,说明cartcrf可能通过影响长吻摄食而使其营养物质的消化吸收发生改变,进而导致其生长表现差异化。

值得关注的是,我们发现参与生长调节的激素基因大多在神经活性配体–受体相互作用(neuroactive ligand-receptor interaction)和GnRH信号通路(GnRH signaling pathway)中富集,表明这些基因可能作为神经内分泌调节因子,对长吻的生长进行调控。另外,在FG组中上调表达的多数差异基因在部分免疫相关的通路中富集,推测长吻的生长性能与其免疫能力具有一定程度的耦合关系,但其作用机制尚不明确,值得进一步深入研究。本研究比较分析了不同生长速率长吻脑组织的转录组图谱,筛选出长吻生长相关候选基因,为长吻下一步功能基因的挖掘以及生长调控的分子机制提供了基础资料。

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