Characterization of long noncoding RNA in nonlactating goat mammary glands reveals their regulatory role in mammary cell involution and remodeling

doi:10.1016/j.ijbiomac.2022.09.291

国际生物大分子杂志

第 222 卷，B 部分，2022 年 12 月 1 日，第 2158-2175 页

International Journal of Biological Macromolecules

https://doi.org/10.1016/j.ijbiomac.2022.09.291 获取权限和内容

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亮点

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奶山羊非泌乳期乳腺组织中 lncRNAs 的特征分析。
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lncRNA 的表达在乳腺腺泡退化过程中发生变化。
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lncRNAs 通过多种作用方式调控多种生理活动以适应乳腺腺泡退化。
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LOC102168552 的过表达通过竞争性结合 chi-miR-324-3p 促进乳腺上皮细胞的生长。

摘要

长链非编码 RNA (lncRNA) 可以调控乳腺发育和泌乳生理活动。然而，lncRNA 在乳腺消退和细胞重塑中的分子遗传机制仍不清楚。本研究分析了山羊乳腺组织在泌乳后期 (LL)、干奶期 (DP) 和妊娠后期 (LG) 阶段 lncRNA 的表达特征和分子功能。测序结果显示，在非泌乳山羊乳腺组织中鉴定出 3074 个 lncRNA。对 lncRNA 长度特征和外显子数量的统计分析发现，山羊 lncRNA 长度较短，外显子较少，表达水平显著低于蛋白质编码基因。在三个比较组（LLvsDP、DPvsLG 和 LLvsLG）中鉴定出 331 个差异表达的 lncRNA，这表明乳腺消退过程中 lncRNA 的转录水平发生了变化。有趣的是，与泌乳期相比，lncRNA 在干奶期表达更活跃，提示乳腺中的 lncRNA 具有发育特异性。基因本体论 (GO) 和京都基因与基因组百科全书 (KEGG) 通路富集分析表明，lncRNA 可以通过多种作用方式调控乳腺中的免疫功能、细胞增殖、细胞凋亡、激素、物质代谢、运输和细胞间通讯。其中，顺式作用的 lncRNA 增强了乳腺在干奶期和妊娠后期的健康保护。以上反映了 lncRNA 适应乳腺退化和重塑发育需求的特殊机制。此外，在与乳腺发育相关的 lncRNA-miRNA-mRNA 网络中，LOC102168552 在妊娠后期的表达高于干奶期和泌乳后期。其表达与 PRLR 呈正相关，与 chi-miR-324-3p 呈负相关。在体外培养的山羊乳腺上皮细胞中过表达 LOC102168552 可以通过竞争性结合 chi-miR-324-3p 上调 PRLR，从而激活催乳素信号通路，促进细胞增殖，减少细胞周期停滞在 G1 / S 期，并抑制细胞凋亡。然而，单独过表达 LOC102168552 并不影响乳腺细胞的生长状态和催乳素信号通路。这表明 LOC102168552 必须依赖 chi-miR-324-3p 才能抑制乳腺细胞凋亡。总之，以上分析表明，山羊乳腺组织中的 lncRNA 在不同的退化阶段差异表达。正如预期的那样，lncRNA 通过多种作用模式适应性地调节乳腺退化过程中的各种生理活动，为新一轮的泌乳做准备。这些发现为进一步理解 lncRNAs 在乳腺细胞退化和重塑中的调控作用提供了参考和帮助。

关键词

长链非编码 RNA 奶山羊乳腺退化细胞重塑竞争性内源 RNA

1. 引言

乳腺退化通常定义为乳腺在泌乳后期恢复到非泌乳状态[1]。根据发生的原因和时期，退化分为三种类型：渐进性退化、老年性退化和主动性退化[2]。乳腺退化是一个复杂的过程，其特征在于上皮和乳腺组织形态的变化、乳腺分泌物的组成变化以及紧密连接的完整性[2]，[3]。此外，免疫系统的成分、几种蛋白酶和各种激素也可以促进和协调退化[4]。细胞凋亡是乳腺退化开始时的标志性特征之一。退化过程中的细胞凋亡伴随着牛奶成分的合成和分泌减少，腺泡上皮细胞之间的连接通透性增加[5]，激活或失活几种蛋白酶及其抑制剂[1]，中性粒细胞和巨噬细胞数量增加[6]，细胞-细胞和细胞-细胞外基质的连接减少[2]。细胞重塑是细胞凋亡后乳腺退化中的另一个重要过程。已经证明，乳腺中的脂肪细胞[3]和成纤维细胞样细胞[7]在繁殖过程中会发生显著的重塑。

值得注意的是，乳腺退化速度和程度在不同物种之间存在差异，尤其是在单胃动物和多胃动物之间。有研究提出，山羊的乳腺退化是由乳腺内压力的增加触发的，而奶牛乳腺的退化则更依赖于泌乳刺激的停止[8]。啮齿动物乳腺细胞凋亡的数量和程度在主动退化过程中比牛更剧烈。相反，牛乳腺的腺泡在退化过程中保留了大部分结构[9]。此外，小鼠乳腺中脂肪组织的退化和重塑明显，而牛乳腺中脂肪组织的退化程度有限[10]。各种动物乳腺退化差异的原因有很多。其中，生理活动和组织结构特征背后的遗传因素对于理解乳腺细胞退化和重塑过程至关重要。近年来，多项研究指出 JAK-STAT 信号通路[11]、溶酶体介导的细胞死亡(LCD)通路[12]、硫酸化糖蛋白-2 (SGP-2) [5]、白介素[13]、白介素-1β转化酶(ICE)、金属蛋白酶组织抑制剂-1 (TIMP1) [5]、胰岛素样生长因子结合蛋白 5 (IGFBP5) [14]、p-53、转化生长因子β-3 (TGFβ3) [15]、凋亡相关基因(CASP3、BCL2 和 BAX) [16]等参与了乳腺退化过程。此外，除了约 2%的蛋白质编码基因外，绝大部分人类基因组由非编码 RNA (ncRNAs)组成，这些非编码 RNA 是通过微阵列技术和全转录组测序发现的[17]，[18]。有趣的是，近年来非编码 RNA 逐渐进入乳腺发育研究领域[19]，[20]。

长链非编码 RNA（lncRNA）是长度超过 200 个核苷酸的非编码 RNA（ncRNA），其在细胞水平上调控许多生物学过程，例如表观遗传调控、转录和转录后调控、细胞凋亡、增殖和细胞周期等[19]，[21]，[22]。此外，lncRNA 还影响乳腺发育和泌乳。最早鉴定出的两种调控性 lncRNA，H19 和 SRA（类固醇受体 RNA 激活剂），可能有利于维持乳腺上皮细胞增殖，增加导管侧支分支，并诱导腺泡分化[23]，[24]。较新的研究也发现了参与青春期后乳腺发育的几种 lncRNA。lncRNA Neat1 可以调控小鼠的乳腺形态发生和泌乳[25]。MALAT1 可以抑制乳腺癌转移[26]。此外，高通量转录组测序技术的应用加速并拓宽了对 lncRNA 在乳腺发育调控中的理解。乳腺中 lncRNA 的鉴定和表达特征已在山羊[27]、绵羊[28]，[29]、奶牛[30]，[31]、小鼠[32]，[33]、猪[34]中相继进行了研究。上述研究表明，lncRNA 在乳腺发育和泌乳中发挥着至关重要的作用，这将是泌乳生物学中的一个重要发现。

然而，目前山羊乳腺消退过程中 lncRNAs 的表达特征和分子功能仍不清楚。因此，本研究对非泌乳期（泌乳后期、干乳期、妊娠后期）山羊乳腺进行了转录组测序。本研究旨在通过 RNA-seq 分析揭示非泌乳期山羊乳腺组织中 lncRNAs 的表达特征，并筛选与乳腺发育和泌乳调节相关的 lncRNAs，这将为 lncRNAs 在乳腺细胞消退和重塑中的调控作用提供新的见解。

2. 材料与方法

2.1. 伦理声明

本实验在山东农业大学动物实验伦理委员会的监督和指导下进行 (SDAUA-2018–048)。所有参与者均需接受培训并遵守严格的实验程序。

2.2. 实验动物管理和乳腺组织采集

选择九只健康的崂山奶山羊用于本研究，并在青岛奥特山羊养殖场（中国山东省青岛市）饲养。所有山羊的平均年龄为四岁，第三胎，并为山羊提供相同的饲养和管理环境。关于山羊的具体信息见我们之前研究的表 S1 [35]。在泌乳后期（LL，n = 3，产后 240 天）、干奶期（DP，n = 3，产后 300 天）和妊娠后期（LG，n = 3，交配后 140 天）阶段，通过手术采集乳腺组织。具体步骤包括：山羊在麻醉前禁食 24 小时，以尽量减少腹胀或瘤胃扩张。在山羊的颈静脉注射戊巴比妥钠（100 mg/kg）后，肌肉松弛，心脏和呼吸停止，立即解剖山羊，每次采集山羊同侧的乳腺组织。一部分乳腺组织直接储存在 4%多聚甲醛中。剩余的组织用焦碳酸二乙酯（DEPC）处理过的水冲洗后，放入无 RNase 冻存管中，并储存在液氮中。

2.3. 转录组测序文库的构建

使用 TRIzol-Based RNAiso Plus 试剂盒（货号 9108Q，Takara）提取总 RNA。使用 NanoDrop 2000 C（Thermo Fisher Scientific）分析 RNA 的质量，并保留 RIN ≥ 8 的样品用于构建测序文库。使用 TruSeq RNA Library Prep Kit v2（Illumina）构建了九个测序文库（LL1、LL2、LL3、DP1、DP2、DP3、LG1、LG2 和 LG3），并在 HiSeq 2500 平台（Illumina）上进行测序。

2.4. 测序数据与山羊参考基因组的比对以及 lncRNA 的鉴定和分类

使用 FastQC 软件（version 0.11.9）[36]检查原始测序数据的质量，并使用 Trimmomatic 软件（version 0.39）[37]过滤测序接头和低质量序列。使用 HISAT2 软件（version 2.2.1）[38]构建山羊参考基因组索引，完成测序 reads 与山羊参考基因组的比对，并统计 reads 比对率。山羊参考基因组的 NCBI BioSample 编号为 SAMN03863711。使用 StringTie 软件（version 2.2.0）[39]组装转录本。使用 StringTie merge 功能获得所有样本的转录本。使用合并的转录本作为新的注释文件，使用 StringTie 软件再次进行转录本的定量分析。通过 GffCompare 软件（version 0.12.6）[40]将剪接的转录本与山羊基因组注释文件进行比较，并筛选 class code 为“u”、“x”、“i”、“j”、“o”的转录本用于下游分析[41]。novel lncRNAs 的筛选条件为长度>200 且覆盖度>1；然后使用新组装的转录本通过四个软件预测其蛋白质编码能力：CPC2（version 2）[42]、CNCI（version 2）[43]、PLEK（version 1.2）[44]和 CPAT（version 1.2.2）[45]，并将四个软件预测结果的交集作为最终的 novel lncRNAs。使用 FEELnc 软件（0.2.1 版）[46]根据 lncRNA 与邻近蛋白编码基因的位置关系，将上述 lncRNA 分为五类：基因外显子型、基因内含子型、基因间下游型、基因间上游型和链未知型。

2.5.差异表达分析

首先使用 RUVseq 软件（版本 1.30.0）[47]对数据进行过滤，并保留 FPKM≥0.5 的 lncRNA 用于所有样本的主成分分析（PCA）。使用 edgeR 软件（版本 3.38.4）[48]进行差异表达分析，当满足条件：log2Foldchange ≥ 1，FDR < 0.05 时，则被鉴定为差异表达的 lncRNA。所有差异表达 lncRNA 的表达模式变化通过热图显示。筛选出每个发育阶段表达量最高的 15 个 lncRNA，并通过条形图显示其表达模式。

2.6. 差异表达 LncRNAs 的顺式调控功能分析

顺式作用是指非编码 RNA 对相邻 mRNA 的转录激活和表达调控[49]。因此，我们使用 BEDTools 软件（版本 2.30.0）[50]，基于 lncRNA 基因组位置注释，筛选 lncRNA 上下游 100 kb 距离内的蛋白质编码基因，用于 GO 功能注释和 KEGG 通路富集分析。

2.7. 差异表达 lncRNA 与蛋白编码基因的表达相关性分析

分别筛选 FPKM≥5 的 lncRNA 和蛋白质编码转录本。使用 R 软件包 psych（版本 2.2.3）计算差异表达的 lncRNA 和蛋白质编码基因之间的 Pearson 相关性，并进行显著性和错误发现率（FDR）检验。筛选与 lncRNA 相关性绝对值≥0.8 且 FDR < 0.05 的蛋白质编码基因，用于 GO 功能注释和 KEGG 通路富集分析。

2.8. 竞争性内源 RNA (ceRNA) 关系分析

筛选每个时期表达水平（FPKM）≥5 的 lncRNA、miRNA 和 mRNA，用于 ceRNA 关系分析。miRNA 和 lncRNA、miRNA 和 mRNA 之间的靶向关系通过 miRanda 软件（版本 3.3a）预测[51]。筛选 Score >= 100 且 Energy <= -15 的靶向关系用于后续分析。使用 R 软件包 TCseq 软件（版本 1.20.0），根据 lncRNA 表达水平对差异表达的 lncRNA 进行聚类，并筛选相应的 miRNA 及其靶基因。对每个簇的靶基因进行 GO 功能注释和 KEGG 通路富集分析。

2.9. 基因本体 (GO) 注释和京都基因与基因组百科全书 (KEGG) 通路富集分析

使用 R 包 clusterProfiler（版本 4.4.4）[52]对筛选出的靶基因进行 GO 注释和 KEGG 通路富集分析。使用 GO 和 KEGG 数据库注释的山羊基因作为富集分析的背景基因，保留 FDR < 0.05 的 GO term 或 KEGG 通路。筛选与乳腺发育、细胞凋亡、免疫、物质运输、生物合成和代谢相关的 GO term 或 KEGG 通路进行展示。

2.10. 中心 lncRNAs、miRNAs 及其靶基因 ceRNA 网络构建

基于 GO 注释和 KEGG 通路分析结果，筛选与乳腺发育相关的 GO 条目或 KEGG 通路。利用 R 包 psych（版本 2.2.3）计算筛选通路中差异表达 lncRNAs 与蛋白编码基因、miRNAs 与差异表达 lncRNAs、miRNAs 与蛋白编码转录本之间的 Pearson 相关性，并进行显著性检验和 FDR 校正。保留相关性值≥0.8 且 FDR≤0.05 的关系。结合上述计算的靶向关系和表达相关性，利用 Cytoscape 软件（版本 3.8.0）构建 miRNA-lncRNA-mRNA（蛋白编码）关系网络。

2.11. 蛋白-蛋白相互作用（PPI）网络分析

将筛选出的基因名称提交至 STRING 网站（https://string-db.org/），并过滤 combined_score≥0.4 的关系，以获得 PPI 网络。利用 Cytoscape 内置软件 NetworkAnalyzer 计算节点度，并根据节点度筛选网络中心基因。

2.12. 细胞培养

乳腺组织取自妊娠后期的山羊，通过手术获得。用无菌 PBS 冲洗乳腺组织后，使用眼科剪刀去除脂肪和结缔组织，并将组织切成小块（0.5–1 mm3）。使用实验室建立的组织块法培养原代山羊乳腺上皮细胞[53]。用于培养山羊乳腺上皮细胞的培养基成分包括：在 Dulbecco's Modified Eagle Medium: Nutrient Mixture F-12 (DMEM/F-12)中，补充 10 %胎牛血清、0.25 mM 氢化可的松、5 mg/mL 胰岛素（Sigma）、50 U/mL 青霉素/链霉素和 10 ng/mL 表皮生长因子 1。上述细胞在 37 °C、含 5 % CO2 的湿润空气的无菌环境中培养。将乳腺上皮细胞以 3 × 105 的密度接种于 6 孔培养板中，当细胞生长达到 75 %时，进行细胞转染实验。

2.13. 荧光素酶报告基因检测

利用 miRanda 软件（3.3a 版）分别预测了 chi-miR-324-3p 与 XR_001918883.1 (LOC102168552)和 XM_018065466.1 (PRLR)的 3'-非翻译区(UTR)片段的靶向关系。筛选能量≤-15 且 Score≥100 的关系对。设计包含限制性内切酶位点的引物。通过反转录 PCR 扩增靶标的 3'-非翻译区(UTR)片段，并使用限制性内切酶 NheI 和 XbaI 将其连接到 pmirGLO 载体(Promega)。细胞转染实验采用原代山羊乳腺上皮细胞，具体分组设置如下：不插入任何片段的空载体 pmirGLO 载体作为对照组(Control)；将靶标 RNA 的 3'UTR 插入 pmirGLO 载体作为野生型载体(WT)；将靶标 RNA 的 3'UTR 突变后插入 pmirGLO 载体作为突变型载体(MT)；插入 miRNA 的反向互补序列作为阳性对照(miRNA_Positive)。在 24 孔板中进行双荧光素酶报告基因检测，每孔加入 300 ng 双荧光素酶报告基因载体和 30 pmol miRNA mimics，并用 Lipofectamine 3000 (Invitrogen)共转染 48 h，三次重复。使用双荧光素酶报告基因试剂盒(Promega)在荧光发光检测仪器(GloMax® 20/20 Luminometer (Promega))上测量萤火虫和海肾荧光素酶活性。

2.14. 细胞转染实验

将 XM_018065466.1 (PRLR)蛋白编码序列(CDS)区域克隆到 pcDNA3.1 载体(Sigma-Aldrich)中，以提高 PRLR mRNA 和蛋白表达水平。将 LOC102168552 克隆到 pcDNA3.1 载体中，以提高 LOC102168552 在乳腺上皮细胞中的表达。chi-miR-324-3p 模拟物（目录号：4464066）由 Thermo Fisher 公司合成。细胞转染实验分为以下八组：无序列插入的空 pcDNA3.1 载体(NC(pcDNA3.1))；PRLR 过表达载体(PRLR)；LOC102168552 过表达载体(LOC102168552)；miRNA 对照组(NC (MIMICS))；chi-miR-324-3p 过表达组(chi-miR-324-3p)；NC (pcDNA3.1 + MIMICS)；chi-miR-324-3p 和 LOC102168552 共过表达组(chi-miR-324-3p + LOC102168552)；chi-miR-324-3p、LOC102168552 和 PRLR 共过表达组(chi-miR-324-3p + LOC102168552 + PRLR)。将上述载体转染到山羊乳腺上皮细胞中。红色荧光蛋白(RFP)片段插入到 pcDNA3.1 过表达载体(LOC102168552 和 PRLR)中，通过荧光显微镜(Keyence Biorevo BZ-9000)观察表达 RFP 的细胞数量，以评估细胞转染 48h 后过表达载体在乳腺上皮细胞中的转染效率。使用 ImageJ 1.48 软件进行细胞计数分析。转染效率通过量化总细胞（DAPI+）群体中 RFP+ 细胞的百分比来确定。细胞转染 48 小时后，通过实时定量逆转录 PCR (RTqPCR) 检测 chi-miR-324-3p、PRLR 和 LOC102168552 的表达水平。此外，通过蛋白质印迹法分析 PRLR 的蛋白表达水平。使用 Lipofectamine 3000 kit (Thermo Fisher Scientific) 转染 PRLR 和 LOC102168552 过表达载体。使用 Lipofectamine™ RNAiMAX (Thermo Fisher Scientific) 转染 chi-miR-324-3p 模拟物及其对照组。

2.15. 细胞凋亡和细胞周期检测分析

将乳腺上皮细胞以 3 × 105 个细胞/孔的密度接种于 6 孔培养板中。转染 48 小时后，向每个孔中加入 5 μL Annexin V-FITC 和 10 μL 碘化丙啶（PI）染色液（Invitrogen），并在室温下避光孵育 10 分钟。然后使用 BD 流式细胞仪（BD Biosciences）进行细胞凋亡和细胞周期检测。使用 FlowJo 7.6.1 软件（BD Biosciences）分析流式细胞术结果。Western blotting 检测转染后 48 h 细胞中 caspase-3、Bax 和 BCL-2 的蛋白表达水平。

2.16. 细胞增殖实验

山羊乳腺上皮细胞以每孔 8000 个细胞的密度接种于 96 孔板中。当细胞融合度达到 75%时进行细胞转染实验。采用 CCK8 法检测细胞增殖。具体步骤包括：在 0、24、48 和 72 h 收获细胞，向每个孔中加入 10 μL CCK8 溶液（碧云天），并在 37 °C 孵育 1 h。使用 SpectraMax ID3 酶标仪（Molecular Devices）在 450 nm 处记录处理孔的吸光度值。使用 GraphPad Prism（版本 8）软件绘制细胞增殖活性曲线图。

2.17. Western blot 和免疫组织化学（IHC）实验

使用放射免疫沉淀分析缓冲液 (RIPA buffer) (碧云天) 提取乳腺组织和上皮细胞的总蛋白。使用微孔板读数器 (Molecular Devices) 通过二辛可宁酸法 (BCA assay) (碧云天) 在 562 nm 处测量蛋白提取物的浓度。制备 10 % 分离胶和 5 % 浓缩胶 (碧云天)。每份样品取 20 μg 总蛋白，通过十二烷基硫酸钠-聚丙烯酰胺凝胶电泳 (SDS-PAGE) 进行分离，并将分离的蛋白转移至聚偏二氟乙烯 (PVDF) 膜。将每张 PVDF 膜在含有 5 % 脱脂奶粉的缓冲液中封闭 1.5 小时，然后在含有针对靶蛋白的一抗的缓冲液中于 4 °C 孵育 12 小时。用含 Tween 20 的 1× Tris 缓冲盐溶液洗涤 3 次后，将 PVDF 膜与适当的二抗在室温下孵育 50 分钟。然后用增强化学发光 (ECL) 缓冲液 (碧云天) 浸润膜 1 分钟，并使用 Azure 300 化学发光 Western Blot 成像系统 (Azure Biosystems) 检测免疫反应蛋白。使用 ImageJ 1.48 软件 (National Institutes of Health) 计算蛋白表达水平，并使用甘油醛-3-磷酸脱氢酶 (GAPDH) 作为蛋白表达水平校正的内参。为了研究乳腺组织的结构特征，本研究对三个时期的乳腺组织进行了苏木精-伊红 (HE) 染色。此外，采用免疫组织化学技术对三个发育阶段获得的乳腺组织切片标本中的蛋白质进行染色。具体步骤如下：将乳腺切片在 50 °C 培养箱中烘烤 20 分钟，然后在二甲苯溶液中浸泡 25 分钟以去除石蜡。然后将切片浸入梯度酒精系列中进行水化。用 1× 磷酸盐缓冲盐水 (PBS) 洗去酒精后，将切片与 3% H2O2 孵育 10 分钟，以灭活内源性过氧化物酶活性，并在 0.01 M 柠檬酸钠缓冲液 (pH = 6.0) 中煮沸 10 分钟。分钟。自然冷却后，使用封闭液封闭 20 分钟。然后将切片与抗 PRLR 的一抗在 4 °C 下孵育 12 小时。通过用 1× PBS 溶液代替一抗来生成阴性对照。将切片用 1× PBS 洗涤三次，每次 7 分钟，室温下与山羊抗兔 IgG 二抗孵育一小时，温度为 37 °C。将链霉亲和素-过氧化物酶逐滴加到切片上，在室温下孵育 30 分钟，用 PBS 洗涤三次，每次 15 分钟，并用 3,3'-二氨基联苯胺染色 5 分钟。使用全景 250 Flash 系列数字扫描仪（3DHISTECH）采集切片图像，并使用 CaseViewer 软件（版本 2.4；3DHISTECH）分析图像（20×视野）。使用 ImageJ 软件通过累加免疫组化图像上每个点的光密度值来计算积分光密度 (IOD)。本研究使用平均光密度 (AOD = IOD / 面积) 进行统计分析。本研究使用的抗体信息如下：anti-PRLR (1:1000 稀释，ab214303，Abcam)，Anti-JAK2 (phospho Y1007 + Y1008) (1:1500 稀释，ab32101，Abcam)，Anti-JAK2(1:1000 稀释，ab108596，Abcam)，Anti-STAT5 (1:1000 稀释，ab178941，Abcam)，Anti-STAT5(1:1000 稀释，ab230670，Abcam)，Anti-SHC (phosphor Y427) (1:1000 稀释，ab68166，Abcam)，Anti-SHC (1:1500 稀释，ab33770，Abcam)，Anti-GRB2(1:1000 稀释，ab32111，Abcam)，Anti-HRAS + KRAS (1:1000 稀释，ab191595，Abcam)，Anti-Raf1 (phospho S259) (1:1000 稀释，ab173539，Abcam)，Anti-Raf1 (1:1000 稀释，ab181115，Abcam)，p38 MAPK (1:1500，#8690，CST)，anti-CCND1 (1:1500 稀释，#55506，CST)，anti-GAPDH (1:2000 稀释，#2118，CST)，anti-PI3K (1:1000 稀释，#4257，CST)，anti-p-PI3K (1:1000 稀释，#17366，CST)，anti-Akt (1:1000 稀释，#4691，CST)，anti-p-Akt (1:1000 稀释，#4060，CST)，anti-caspase-3 (1:2000 稀释，#14220，CST)，anti-BCL-2 (1:1000 稀释，ab182858，Abcam)，anti-Bax (1:1000 稀释，#2772，CST)，以及 HRP-conjugated goat antirabbit IgG (1:2000，CW0103，CWBIO)。

2.18. 实时荧光定量逆转录 PCR (RTqPCR)

为了确定 RNA 测序的稳定性，随机选择 14 个 lncRNA 进行 RTqPCR。引物使用 NCBI Primer-BLAST 设计。总 RNA 使用 Trizol 法从乳腺组织中分离。使用 One-Step TB Green PrimeScript RT-PCR 试剂盒（Takara）进行逆转录和 PCR 扩增。使用 LightCycler® 96 Instrument (Roche)进行定量检测。通过建立标准曲线计算引物扩增效率。使用先前研究中使用的 2 个参考基因（GAPDH 和 MRPL39）的几何平均值作为准确的标准化因子[53]。相对基因表达量通过改进的 Pfaffl 方法[54]计算（详细计算步骤见：https://toptipbio.com/qpcr-multiple-reference-genes/）。引物序列和引物效率见补充表 1。

2.19. 统计分析

使用学生 t 检验来检验实验组和对照组之间差异的显著性；p 值<0.05 表示存在显著差异。使用 Tukey honest test 分析多个组（>2 组）之间的显著性，调整后的 p 值（p.adj）<0.05 被认为具有显著性。

3. 结果

3.1. 测序结果的基本统计分析

对测序数据进行统计分析发现，晚泌乳期 (LL)、干奶期 (DP) 和妊娠后期 (LG) 的测序文库分别获得了 75,670,537 ± 2,451,052、80,547,045 ± 4,443,268 和 73,765,766 ± 1,723,917 条 clean reads。比对结果表明，每个测序文库的比对率均≥95%（补充表 2）。原始测序数据已提交至 NCBI GEO 数据库 (GEO accession: GSE185981)。这表明非哺乳山羊乳腺的文库构建和测序是成功的。结合山羊参考基因组的注释以及 lncRNA 的结构和功能特征，我们鉴定了 2676 个已知的 lncRNA 和 398 个新的 lncRNA（图 1A-B，补充表 3）。发现每个时期 lncRNA 表达的统计数据 (FPKM ≥0.5)：DP 中表达的 lncRNA 数量最多 (826)，LL 中 lncRNA 数量最少 (431)，并且在所有三个时期都表达了 274 个 lncRNA（图 1C）。这表明 lncRNA 表达在 DP 期间更活跃。此外，一些 lncRNA 在每个阶段单独表达，这也反映了乳腺不同发育阶段 lncRNA 表达的阶段特异性。基于 lncRNA 基因组位置信息对 lncRNA 进行分类显示，基因内 lncRNA 的数量高于基因间 lncRNA 的数量（图 1D）。这主要与 lncRNA 序列的长度特征有关，因为 lncRNA 的长度通常定义为≥200 nt。lncRNA 外显子数量统计发现，大多数 lncRNA 具有 2-5 个外显子。长度分布统计发现，大多数 lncRNA 的长度为 200-2000 nt (图 1E-F)。与 lncRNA 相比，mRNA 的外显子数量大多在 1 到 22 之间，长度分布为 400-5000 nt (补充图 1A-B)。此外，mRNA 的整体表达水平也高于 lncRNA (补充图 1C)。这表明 mRNA 的长度和外显子数量均多于 lncRNA。通过查阅 NCBI 数据库中的山羊基因组注释，NCBI 数据库中的山羊 mRNA 注释信息远比 lncRNA 丰富。这暴露出当前山羊 lncRNA 注释的不足，提示需要更多工作来分析 lncRNA 的结构和功能。

3.2. 差异表达分析结果及 RT-qPCR 验证 lncRNA 表达

主成分分析 (PCA) 显示（图 2A），来自同一时期的乳腺样品聚集在一起，而来自不同时期的样品则分散开来。差异表达分析结果表明，在三个比较组中总共鉴定出 331 个差异表达的 lncRNA（补充表 4）。其中，LL 和 DP 之间的比较中差异表达的 lncRNA 数量最多（图 2B）。每个比较组中有 13 个 lncRNA 差异表达（图 2C）。热图显示了 331 个 lncRNA 在三个发育阶段的表达变化（图 2D）。此外，表达直方图显示了每个时期中 15 个高表达的 lncRNA（图 2E）。总之，以上表明 lncRNA 转录组水平在乳腺组织的退化和重塑过程中发生了改变，反映了 lncRNA 表达在乳腺组织中的阶段特异性。此外，RTqPCR 检测到 14 个随机 lncRNA 的表达结果（补充图 2）。RNA-Seq (log2 fold change) 和 RTqPCR (log2 fold change) 的结果呈显着正相关（相关值 = 0.75，p-value <0.01）。这表明测序和差异表达分析结果具有很高的准确性。

3.3. LncRNA 顺式调控作用分析

共筛选出 184710 个 lncRNA 的顺式调控关系（补充表 5）。在 LLvsDP 组中，筛选出与免疫相关的术语，如 T 细胞活化、自然杀伤细胞介导的细胞毒性、适应性免疫应答的调控以及中性粒细胞胞外诱捕网的形成（补充图 3）。此外，它还富集在 ncRNA 代谢过程、ATP 代谢过程的正调控、分解代谢过程的正调控以及其他催化代谢术语中。在 DPvsLG 组中，长寿调控通路——多个物种和细胞衰老显著富集。在 LLvsLG 中，富集了蛋白质合成和修饰术语，如核糖体生物发生、脂蛋白生物合成过程、核糖体组装和蛋白质酰化。以上结果表明，顺式作用的 lncRNAs 可能在乳腺细胞的免疫功能、细胞生长和蛋白质合成等生理过程中发挥作用。

3.4. 乳腺中免疫相关 lncRNA 的分析

通过 lncRNAs 顺式调控分析筛选出 25 个与乳腺免疫功能相关的 lncRNAs（补充图 4）。表达分析显示（补充图 4F-G），在泌乳后期（DP）有 20 个 lncRNAs 上调，在妊娠后期（LG）有 11 个 lncRNAs 上调表达。有趣的是，在 DP 和 LG 期间，也有 26 个免疫相关转录本上调。PPI 网络鉴定了五个枢纽免疫基因（补充图 4C），其中 IL6 和 BCL6 参与适应性免疫反应、淋巴细胞活化、T 细胞活化和其他生理过程。MSTRG.2888.2 和 MSTRG.2888.3 可以调控 IL6，并在 DP 期间高表达。XR_001917933.1 调控 BCL6，并在 LG 期间高表达。上述分析表明，在泌乳期和妊娠后期，免疫功能相关的 lncRNAs 和基因上调，增强了对 DP 和 LG 期间乳腺健康的保护作用。

3.5. lncRNA 与蛋白质编码 RNA 的共表达分析结果

计算了 74 个 lncRNA（FPKM ≥5）和 6866 个 mRNA（FPKM ≥5）之间的 Pearson 相关性，共得到 103275 对绝对相关值≥0.8 且 p 校正<0.05 的关系（补充表 6）。在 LLvsDP（补充图 5）中，富集了与细胞凋亡相关的信号通路，例如内在性细胞凋亡信号通路、外在性细胞凋亡信号通路和细胞凋亡。在 DPvsLG 中，富集了组织重塑、腺体发育、细胞周期以及其他与细胞生长相关的术语。在 LLvsLG 中，富集了与细胞生长相关的术语，例如转化生长因子-β应答、表皮生长因子应答、细胞生长和乳腺发育。此外，还富集了与物质运输和代谢相关的术语，例如脂肪酸跨膜转运、脂肪酸代谢过程和葡萄糖代谢过程。这些结果表明 lncRNA 在乳腺细胞生长、细胞凋亡、物质运输和能量代谢中发挥调控作用。

3.6. 乳腺细胞生长、凋亡及激素相关 lncRNA 分析

lncRNA 和 mRNA 共表达分析筛选出 51 个基因和 12 个与乳腺细胞生长相关的 lncRNA（补充图 6）。PPI 网络鉴定出 7 个中心基因，其中 ITGB1 (NM_001314156.1)、APP (XM_018050523.1)和 CTNNB1 (XM_018066897.1)在 DP 和 LG 高表达。XR_001295805.2 与 ITGB1 (NM_001314156.1)、APP (XM_018050523.1)和 CTNNB1 (XM_018066897.1)显著负相关 (p.adj < 0.05)。此外，XR_001917125.1 与 APP (XM_018050523.1)、MSTRG.12716.2 和 CTNNB1 (XM_018066897.1)显著正相关 (p.adj < 0.05)。本研究还筛选出 27 个与细胞凋亡相关的基因和 25 个 lncRNA（补充图 7）。中心基因 RPS3、RACK1 和 RPS7 在 LL 和 DP 低表达。MSTRG.11612.1、MSTRG.12716.2 和 XR_001295696.2 与 RPS3 正相关 (p.adj < 0.05)。XR_001918883.1、XR_001919191.1 和 XR_001919240.1 与 RACK1 正相关 (p.adj < 0.05)。此外，本研究还筛选出 25 个与激素相关的 lncRNA 和 57 个基因（补充图 8）。这些 lncRNA 和基因可能调控催乳素信号通路、胰岛素信号通路、雌激素信号通路、生长激素的合成、分泌和作用以及其他激素相关通路。总之，以上结果表明 lncRNA 与调控细胞生长、凋亡和激素的基因存在共表达关系。

3. 7. 乳腺中与物质代谢相关的 lncRNA 分析

lncRNA 和 mRNA 共表达分析筛选出 50 个基因和 15 个与物质代谢相关的 lncRNA（补充图 9）。PPI 网络鉴定了 8 个代谢枢纽基因。其中，ECH1、HADHA、ETFA、HADH 和 HSD17B10 参与脂肪酸代谢过程、小分子分解代谢过程和有机酸分解代谢过程等生理过程。它们在 LG 期的表达水平上调。此外，通过代谢 lncRNA 的表达水平发现，有 13 个 lncRNA 在 LG 期的表达水平升高。同样，LG 期高表达的 mRNA 数量也高于其他两个时期（LL 期和 DP 期）。这表明与物质代谢相关的 lncRNA 和 mRNA 在 LG 期活跃表达。它们参与脂类、碳水化合物和蛋白质的合成和代谢，从而为新一轮的泌乳做准备。

3.8. 乳腺组织中 lncRNA-miRNA-mRNA ceRNA 关系的分析

使用 miRanda 软件获得了 61,059 个 miRNA-lncRNA 和 11,037,879 个 miRNA-mRNA 靶向关系（补充表 7）。通过 lncRNA 表达聚类分析（补充表 8），55 个 lncRNA 被分为三个簇（图 3）。第一个簇中 miRNAs 靶基因功能分析结果（图 3A）显示，细胞外基质分解和细胞-基质粘附显著富集 (FDR < 0.05)。外源性凋亡信号通路、内源性凋亡信号通路、坏死性细胞死亡、细胞衰老和其他凋亡相关条目也得到富集。第二个簇的结果（图 3B）表明，胰岛素信号通路、PI3K-Akt 信号通路、催乳素信号通路、JAK-STAT 信号通路和其他与细胞发育相关的通路得到富集。簇 3 的结果（图 3C）表明，组织重塑、细胞外基质组装、紧密连接组织、紧密连接组装、结缔组织发育和其他与细胞连接相关的条目得到富集。此外，免疫和疾病相关的条目，如 Fc gamma R 介导的吞噬作用、吞噬体、沙门氏菌感染、Epstein-Barr 病毒感染和上皮细胞的细菌入侵也得到富集。总的来说，以上结果表明 lncRNAs 可以通过竞争性结合 miRNAs 来影响细胞凋亡、生长、组织重塑、细胞间粘附、细胞-基质连接和通讯、疾病感染以及免疫应答等生理过程。

3.9. 催乳素信号通路中预测的 ceRNA 分子机制

催乳素信号通路是哺乳动物乳腺发育和泌乳生理活动经典的信号通路。本研究将进一步探讨 ceRNA (miRNA-lncRNA-mRNA) 在该通路中的分子机制。催乳素信号通路中的 ceRNA 网络包含 224 个节点和 466 条边（图 4）。其中包含 38 个基因，46 个转录本，47 个 lncRNA 和 93 个 miRNA。从催乳素信号通路图（补充图 10）可以看出，PRLR 位于通路的上游，是协调和沟通细胞内、外信号的关键分子。PRLR 在第二信使级联反应中可以调控的通路包括 JAK-STAT 信号通路、MAPK 信号通路和 PI3K-AKT 信号通路。因此，我们筛选了与 PRLR 具有 ceRNA 调控关系的网络（图 5A）。该网络包含 35 个节点和 84 条边。它们是 PRLR 及其四个转录本、14 个 miRNA 和 16 个 lncRNA。计算了 lncRNA 与转录本之间的表达相关性（图 5B），其中 XM_018065466.1 与 XR_001918883.1 显著正相关，且相关性最高（相关系数=0.97，p.adj < 0.01）。mRNA 和 miRNA 表达相关性分析结果（图 5C) 发现只有 XM_018065466.1 和 chi-miR-324-3p 显著负相关（相关系数 = −0.89，p.adj < 0.05）。miRNA 和 lncRNA 表达的相关性分析显示（图 5D），chi-miR-324-3p 与 XR_001918883.1 显著负相关（相关系数 = −0.9，p.adj < 0.05）。LOC102168552 长度为 1092 bp，包含四个外显子，位于 11 号染色体上的 FAM69B 和 LOC102168737 之间（图 5E）。测序结果显示（图 5F-G），LL 中 chi-miR-324-3p 的表达水平显著高于 DP 和 LG（p.adj < 0.05）。PRLR 和 LOC102168552 在 LG 中高表达。总之，将筛选 LOC102168552 (XR_001918883.1)、chi-miR-324-3p、PRLR (XM_018065466.1) ceRNA 关系进行后续分析。

3.10. 山羊乳腺中 PRLR 的表达

PRLR 在蛋白水平的表达与其在转录水平的表达一致，并且两者在 LG 期均高表达（图 6）。免疫组织化学结果（图 6A）显示，PRLR 定位于 LL 期和 LG 期乳腺上皮细胞的细胞核和细胞质中。在 DP 期，PRLR 在结缔组织细胞中没有显著定位，主要在退化乳腺的腔细胞中表达。免疫组织化学定量分析结果（图 6B）显示，LG 期 PRLR 的 AOD 值分别比 LL 期和 DP 期高 1.38 ± 0.21 倍和 1.41 ± 0.23 倍（p < 0.01）。而 LL 期和 DP 期之间 PRLR 的 AOD 值没有显著差异。这一发现表明，PRLR 在乳腺的不同发育阶段在数量和位置上存在差异表达。

3.11. chi-miR-324-3p 可能靶向 LOC102168552 和 PRLR

使用 miRanda 软件预测发现，chi-miR324-3p 与 LOC102168552 和 PRLR 具有靶向结合位点（Score > 120 且 energy < −15）（图 7A）。双荧光素酶报告基因检测结果（图 7E）表明，与对照组相比，chi-miR-324-3p 使 LOC102168552 野生型载体的荧光活性降低了 52.34 ± 7.61 %。LOC102168552 突变型载体的荧光活性保持不变。同样，chi-miR-324-3p 使 PRLR 野生型载体的荧光活性降低了 62.31 ± 9.54 %。PRLR 突变型载体的荧光活性保持不变。RTqPCR 结果显示（图 7F），过表达 chi-miR-324-3p 可以显著降低 LOC102168552 和 PRLR 的表达水平（p < 0.01）。以上表明 chi-miR-324-3p 可以靶向调控 LOC102168552 和 PRLR。

3.12. PRLR 的过表达可以通过激活 JAK-STAT、PI3K-Akt 和 MAPK 信号通路来促进乳腺上皮细胞增殖

PRLR 是催乳素信号通路的一个重要成员（补充图 10）。结果显示（图 7G），在体外培养的乳腺上皮细胞中，PRLR 的过度表达增加了 p-JAK2 / Total-JAK2 和 p-STAT5 / Total-STAT5 的比例，与对照组相比。此外，在 PRLR 过度表达组中，p-PI3K / Total-PI3K 和 p-Akt / Total-Akt 的比例也相比对照组有所增加（图 9F）。同样，在 MPAK 信号通路中（补充图 11），PRLR 过度表达组中 p-SHC / Total-SHC 和 p-Raf1 / Total-Raf1 的比例相比对照组显著升高。同时，在乳腺上皮细胞中 PRLR 的过度表达还增加了 Grb2、HRAS+KRAS 和 p-MAPK 的蛋白表达。以上结果表明，PRLR 在乳腺上皮细胞中的过度表达激活了下游 JAK-STAT、PI3K-Akt 和 MAPK 信号通路。细胞增殖和凋亡的结果（图 8A）显示，与对照组相比，PRLR 的过度表达使乳腺上皮细胞的凋亡率下降了 40.09 ± 4.72（48 小时），细胞增殖活性分别增加了 22.15 ± 4.14（48 小时）和 18.50 ± 5.10（72 小时）（图 9D-E）。此外，PRLR 的过度表达还促进了 CCND1 的表达（图 8C），降低了 Bcl-2 / Bax 的比例。细胞周期结果显示，与对照组相比，PRLR 过表达组中 G2 期细胞的比例增加了 45.29 ± 6.73。这表明 PRLR 过表达会促进乳腺上皮细胞的增殖并抑制其凋亡。

有趣的是，当 LOC102168552 单独在乳腺上皮细胞中过表达时（图 7G），与对照组相比，PRLR 蛋白的表达没有变化。同时，与对照组相比，单独过表达 LOC102168552 对 JAK-STAT、PI3K-Akt 和 MAPK 信号通路没有影响（图 7G，图 9F，补充图 11）。此外，单独表达 LOC102168552 组的增殖、细胞周期和凋亡与对照组相比没有显著差异。这似乎表明：一方面，LOC102168552 可能不影响乳腺上皮细胞的生长？另一方面，它可能通过一种非独立的模式影响乳腺上皮细胞的生长。在本研究中，分别测试了过表达载体 LOC102168552 和 PRLR 的转染效率，结果表明转染效率均>69%。具体结果请参考补充图 12。

3.13. 过表达 chi-miR-324-3p 下调 PRLR，抑制 JAK-STAT、PI3K-Akt 和 MAPK 信号通路，并促进乳腺上皮细胞凋亡

与 PRLR 过表达结果相反，在体外培养的乳腺上皮细胞中，chi-miR-324-3p 的过表达发现 PRLR 蛋白表达水平与对照组相比减少（图 7G）。在 chi-miR-324-3p 过表达组中，p-JAK2 / Total-JAK2、p-STAT5 / Total-STAT5、p-PI3K / Total-PI3K、p-Akt / Total-Akt、p-SHC / Total-SHC 和 p-Raf1 / Total-Raf1 的比率均下调。此外，chi-miR-324-3p 过表达组中 Grb2、HRAS+KRAS 和 p-MAPK 的蛋白表达也减少。这表明 chi-miR-324-3p 的过表达抑制了 PRLR 的表达及其下游信号通路 JAK-STAT、PI3K-Akt 和 MAPK 信号通路（图 7G，图 9F，补充图 11）。流式细胞术结果（图 8A）显示，chi-miR-324-3p 过表达组的凋亡细胞数量相比对照组增加了 63.84 ± 4.91%。此外，chi-miR-324-3p 的过表达可以促进凋亡相关蛋白 Caspase3 的表达，并减少 Bcl-2 / Bax 的比率。细胞周期分析结果（图 9A）显示，chi-miR-324-3p 的过表达导致细胞在 G1/S 期停滞，并下调了细胞周期蛋白 CCND1 的表达。与此同时，CCK8 的结果（图结果(图 9C-E)显示，与对照组相比，chi-miR-324-3p 过表达降低了乳腺细胞的增殖活性，在 48 h 时降低了 29.13 ± 9.08，在 72 h 时降低了 31.84 ± 7.02。综上所述，上述数据表明，chi-miR-324-3p 的体外过表达通过抑制 PRLR 及其下游信号通路抑制乳腺上皮细胞的增殖并促进细胞凋亡。

3.14. LOC102168552 的过表达可以对抗 chi-miR-324-3p 对 PRLR 及其下游级联信号通路的抑制作用

有趣的是，当 LOC102168552 和 chi-miR-324-3p 共同转染到乳腺上皮细胞中时，与对照组相比，实验组中的 PRLR 表达、p-JAK2 / Total-JAK2 比例和 p-STAT5 / Total-STAT5 比例没有变化（图 7G）。同样，当 LOC102168552 和 chi-miR-324-3p 共同转染到乳腺上皮细胞中时，PI3K-Akt 信号通路和 MPAK 信号通路中的蛋白成员的表达水平也没有变化（图 9F，补充图 11）。此时，细胞生长状态与对照组没有显著差异。然而，当 LOC102168552、chi-miR-324-3p 和 PRLR 共同转染到乳腺上皮细胞中时，PRLR 表达上调，激活了 JAK-STAT、PI3K-Akt 和 MAPK 信号通路。此外，LOC102168552、chi-miR-324-3p 和 PRLR 在乳腺上皮细胞中的共同转染可以抑制乳腺上皮细胞凋亡，减缓 G1/S 期中的细胞周期停滞，并促进乳腺上皮细胞增殖。综合而言，上述结果表明，LOC102168552 可以抵消 chi-miR-324-3p 对 PRLR 及其下游信号通路的抑制作用。

4. 讨论

乳腺在哺乳晚期到妊娠晚期经历了退化和细胞重塑，这伴随着多个生理过程，如细胞凋亡、增殖、分化、乳汁的合成和分泌。从哺乳晚期到妊娠晚期探索分子遗传机制对于深入理解这些生理变化至关重要。目前，越来越多的证据表明，长非编码 RNA (lncRNA) 在细胞增殖、分化和凋亡等各种生物过程中发挥着重要作用。然而，它们在非哺乳山羊乳腺组织中的功能和特征仍然 largely unknown。因此，本研究一方面报告了非哺乳山羊乳腺组织中 lncRNA 的表达特征；另一方面，探讨了 LOC102168522、chi-miR-324-3p 和 PRLR 之间的 ceRNA 关系对山羊乳腺上皮细胞生长的影响。

在本研究中，3074 个 lncRNA 在山羊乳腺中被鉴定（补充表 3）。对 lncRNA 长度特征和外显子数量的分析显示（图 1），lncRNA 的长度分布和外显子数量远低于蛋白编码基因。这与之前的报道一致[55]，[56]，表明鉴定的 lncRNA 的可靠性。其中，274 个 lncRNA 在三个阶段均有表达，特定于干乳期的 lncRNA 数量最高。已知在荷斯坦奶牛的干乳期和哺乳乳腺中比较 lncRNA 发现，在哺乳期和干乳期均有表达的 lncRNA 达到 6130 个，其中特定于干乳期的 lncRNA 数量是哺乳期的 3.4 倍[57]。

此外，在牦牛乳腺组织中，干乳期上调的差异表达 lncRNA 数量高于哺乳期[56]。这反映了我们的研究与上述 RNA-seq 研究结果之间的相似性；它还表明，lncRNA 在反刍动物非哺乳期的乳腺中可能更为活跃。差异表达分析的结果显示（图 2），在三组比较中共识别出 331 个差异表达的 lncRNA。已知微阵列分析识别出 97 个在青春后发育期间乳腺中差异表达的 lncRNA[32]。类似的乳腺转录组分析也在奶牛[30]、羊[28]和山羊[27]的不同发育阶段中识别出差异表达的 lncRNA。这进一步支持了 lncRNA 在乳腺中较高的发育阶段特异性[58]，[59]。

据推测，乳腺是由先天免疫系统演化而来的，因为它在哺乳期间为后代提供免疫保护和营养[60]。本研究发现，lncRNA 可以通过顺式调控增强干期和晚期妊娠中免疫基因的表达，并保护乳腺健康（补充图 4）。已知 lncRNA 在先天免疫细胞中调节炎症基因表达[61]。在免疫系统中描述的第一个 lncRNA，lincRNA-Cox2，是在用 Toll 样受体 4（TLR4）刺激的骨髓源树突状细胞中发现的[62]。此外，lncRNA 在适应性免疫中也发挥着重要作用[63]，[64]。已有报告涉及乳腺中与免疫相关的 lncRNA 研究，例如细菌挑战会触发与免疫反应和防御机制相关的 lncRNA 在山羊乳腺上皮细胞中的表达[65]。Zfas1 是乳腺发育的调节因子，也是乳腺癌的潜在标志物[32]。H19 在乳腺肿瘤的基质细胞中高表达，并与雌激素受体和催乳素受体的存在相关[66]。以上所有表明，lncRNA 可以影响乳腺的免疫功能。此外，对干奶牛乳腺中 lncRNA 的分析显示，lncRNA 在干期对乳腺健康具有保护作用，比如减少乳腺炎的发生[57]，[67]。这与我们的发现相似。总之，上述支持本研究的观点，即长链非编码 RNA 可以通过调节免疫应答基因来保护乳腺在退化过程中的健康。

乳腺上皮细胞是合成和加工乳脂、蛋白质和碳水化合物的工厂[68]。乳腺在从晚期哺乳到晚期妊娠的过渡期间面临能量代谢的挑战[69]。本研究发现，lncRNA 可以调节与物质合成和代谢相关的基因在乳腺中的表达（补充图 9）。越来越多的研究表明，lncRNA 可以调节碳水化合物[70]、脂肪[71]和蛋白质[72]，[73]的合成和代谢。根据羊的乳腺转录组，lncRNA 在调节乳脂合成中起着重要作用。例如，MSTRG.32232.1 可能通过竞争结合 miR-148a 和 miR-152 抑制乳脂合成[74]。此外，细胞呼吸、呼吸电子传递链和电子传递链的富集 GO 术语表明，lncRNA 可能在荷斯坦乳腺的早期生长阶段调节能量代谢[75]。以上所有结果支持 lncRNA 在乳腺代谢中的调节作用。此外，本研究还发现乳腺中与代谢相关的 lncRNA 和基因在晚期妊娠中高表达，但在晚期哺乳和干乳期降低。这与非哺乳乳腺的泌乳活动密切相关。已知代谢是一个复杂的调节系统网络。细胞通常会在环境变化时改变其代谢。因此，lncRNA 可能通过调节与代谢相关的基因为新一轮的乳汁分泌做准备。

凋亡和乳腺上皮细胞的重塑是乳腺退化的重要特征[1]，[76]。本研究发现，中心基因 RPS3、RACK1 和 RPS7 在哺乳末期和干乳期均表现出低表达（补充图 7）。12 个 lncRNA 与 RPS3 表达呈正相关。已知 RPS3 敲除会显著减少结肠癌细胞系 Caco-2 的增殖、存活、迁移和侵袭，并增加凋亡[77]。这 12 个 lncRNA 在哺乳末期和干乳期的低表达可能影响 RPS3 的功能，从而促进乳腺上皮细胞的凋亡。此外，RACK1 沉默会诱导肝细胞癌 MHCC97-H 细胞的凋亡并抑制细胞增殖[78]。本研究还发现，13 个 lncRNA 与 RACK1 表达呈正相关。RACK1 已被证明参与乳腺发育和异常乳腺肿瘤细胞的增殖[79]。这也暗示了 lncRNA 对调节乳腺细胞增殖的影响。已有报道称 lncRNA 可以影响不同的凋亡途径，包括凋亡[80]、自噬[81]、坏死性凋亡[82]和铁死亡[83]。本研究发现，lncRNA 可以影响内源性凋亡信号通路、外源性凋亡信号通路的调控以及氧化应激诱导的细胞死亡调控等生理过程[83]。此外，还验证了 lncRNA 在干乳期对奶牛乳腺细胞凋亡的调控[56]，[57]。这些丰富了对 lncRNA 在乳腺退化和凋亡调控中的认识。

乳腺退化是一种高度复杂的多步骤过程，在该过程中，泌乳乳腺的形态被恢复到接近孕前状态，激素在这一过程发挥着不可替代的作用 [2], [84]。虽然有研究指出小鼠乳腺退化的第一阶段由局部因素而非循环激素调节 [85]。第二阶段则依赖于激素，因为已证明氟氯噻噻唑的应用可以阻止细胞凋亡并恢复乳腺细胞间结合的紧密性 [5], [86]。本研究发现，与 lncRNA 共同表达的基因涉及泌乳素信号通路、雌激素信号通路和生长激素合成（补充图 8）。此外，在 ceRNA 网络中证明了泌乳素信号通路成员与 lncRNA 和 miRNA 之间的调控关系（图 4 和图 5）。这进一步证实了 lncRNA 可能通过调节激素信号通路影响乳腺退化过程。自从 Riddle 等人从腺垂体提纯出一种激素（泌乳素），并发现它可以刺激处女兔乳腺的乳汁分泌 [87]，已经发现泌乳素在细胞生长、凋亡、组织发育、新陈代谢和免疫系统中发挥着多重作用 [88]。目前的研究报告表明，lncRNAs 在泌乳素信号通路中具有调节作用[89], [90], [91]。此外，PRLR 是泌乳素信号通路中的上游核心成员，其表达变化可能导致下游的 JAK-STAT 信号通路、MAPK 信号通路和 PI3K-Akt 信号通路的变化[92]。有趣的是，我们发现 LOC102168552 在山羊乳腺上皮细胞中过表达，可以通过竞争性结合 chi-miR-324-3p 来影响 PRLR 的表达，从而激活泌乳素信号通路，促进乳腺上皮细胞的增殖并抑制凋亡。这个发现证实了一些 lncRNAs 可以通过影响激素通路来影响山羊乳腺细胞的生长。虽然 LOC102168552 的功能很少被报道，但 miR-324-3p 在山羊 granulosa 细胞[93]、乳腺癌细胞[94]、鼻咽癌细胞[95]、心脏成纤维细胞[96]等中被广泛报道为抑制细胞生长的角色。同样，我们发现单独过表达 chi-miR-324-3p 也可以抑制乳腺上皮细胞的增殖。这表明 miR-324-3p 在多种细胞中的生长抑制效应是普遍且相似的。总之，上述结果表明 lncRNA 可以通过调节激素通路影响乳腺的衰退过程。

积累的证据表明，长非编码 RNA（lncRNA）可以作为竞争性内源性 RNA（ceRNA），影响微 RNA（miRNA）与信使 RNA（mRNA）之间的交流，从而调节乳腺发育和泌乳 [97], [98], [99], [100], [101]。本研究表明，LOC102168552 可以竞争结合 chi-miR-324-3p，从而降低 chi-miR-324-3p 对 PRLR 的抑制作用（图 7G）。然而，单独过表达 LOC102168552 并未影响泌乳激素信号通路和乳腺细胞生长状态。这似乎强调了 chi-miR-324-3p 对乳腺细胞生长的重要性，并且还表明 LOC102168552 对乳腺细胞的影响并不是独立的，而必须依赖于 chi-miR-324-3p。此外，通过生物信息学预测，发现有多个 lncRNA 与 chi-miR-324-3p 存在碱基配对靶向调控关系（例如，MSTRG.11612.1，XR_001297263.2，XR_001918192.1 等）。当然，本研究还发现同一 lncRNA 可以被多个 miRNA 靶向和调控。这与之前报告的 lncRNA-miRNA-mRNA 之间的 ceRNA 关系一致，也说明了 ceRNA 交叉对话和竞争的多层次复杂性 [102], [103]。然而，在本研究中，提出了解决上述问题的方法。在筛选乳腺中催乳素信号通路的 ceRNA 关系时，不仅考虑 miRNA 与 lncRNA 或 miRNA 与 mRNA 之间的靶向关系（基于互补碱基配对），还考虑 miRNA-lncRNA-mRNA 之间的定量关系（miRNA 与 lncRNA 或 miRNA 与 mRNA 之间的表达呈负相关，lncRNA 与 mRNA 之间的表达呈正相关）。

本研究也存在一些局限性。首先，如我们之前的工作所解释的[35]，[53]，由于样本量小，检测差异表达的非编码 RNA 的能力有限；第二，我们的分析排除了表达水平非常低的转录本（FPKM <0.5），这可能忽视了低表达 lncRNA 在乳腺细胞退化和重塑中的作用。同时，个体动物之间的遗传背景信息差异可能干扰不同阶段乳腺的差异表达分析结果的准确性[104]。此外，本研究仅评估了乳腺退化过程中的三个时间点（较长时间间隔）。尽管发现了乳腺功能和结构的差异，但乳腺退化和重塑是一个持续的过程。更多的采样和测序时间点可能有助于更好地解释这一过程中变化的分子机制，并提供对乳腺退化期间各种生理活动的时空特征的更清晰和更准确的解释。

5. 结论

本研究从非泌乳山羊乳腺组织中鉴定出了 3074 个 lncRNA。其中，与细胞生长、凋亡、免疫、物质运输、生物合成和代谢相关的 lncRNA 的表达模式在乳腺退化过程中发生了显著变化。这种表达模式表明了 lncRNA 适应乳腺细胞退化与重塑的特定发展需求的机制。有趣的是，lncRNA 在干乳期的表达比在泌乳期更为活跃，表明乳腺中的 lncRNA 表达具有特异性。对 lncRNA 的顺式调控分析表明，lncRNA 在干乳期和妊娠晚期增强了对乳腺健康的保护作用。此外，在与乳腺发育相关的 ceRNA 网络中，LOC102168552-chi-miR-324-3p-PRLR 预计参与了催乳素信号通路的调节。在体外培养的山羊乳腺上皮细胞中，LOC102168552 的过表达可以通过与 chi-miR-324-3p 竞争结合，上调 PRLR 以激活催乳素信号通路，促进乳腺上皮细胞增值，减少 G1/S 期的细胞周期停滞，并抑制凋亡。然而，仅仅过表达 LOC102168552 对乳腺细胞生长状况和催乳素信号通路没有影响。这表明 LOC102168552 必须依赖 chi-miR-324-3p 抑制乳腺细胞凋亡。总之，这项工作为山羊 lncRNA 数据库提供了宝贵资源，并有助于理解 lncRNAs 在乳腺细胞退化和重塑中的分子遗传机制。

以下是与本文相关的补充数据。

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Supplementary Table 1. Primer sequences for real-time quantitative reverse-transcription PCR (RTqPCR).

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Supplementary Table 2. Basic statistical analysis of sequencing data.

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Supplementary Table 3. LncRNA classification information and expression levels.

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Supplementary Table 4. Differentially expressed lncRNAs identified by three comparison groups.

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Supplementary Table 5. GO functional annotation and KEGG pathway enrichment analysis of target genes of cis-acting lncRNA.

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Supplementary Table 6. GO functional annotation and KEGG pathway enrichment analysis of LncRNA co-expressed target genes.

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Supplementary Table 7. Using miRanda software to predict the target relationship between miRNA and lncRNA.

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Supplementary Table 8. LncRNA (FPKM ≥5) cluster analysis results and corresponding target gene GO functional annotation and KEGG pathway enrichment analysis results.

CRediT 作者贡献声明

荣轩：概念化，方法学，软件，初稿写作，审阅和编辑。赵晓东：软件。李清：可视化，调查研究。赵艺林：监督指导。王艳艳：软件，验证。杜善峰：资源。段庆玲：形式分析。郭艳飞：方法学。季志斌：方法学。晁天乐：方法学，软件。王建民：审阅和编辑，项目管理，资金筹措。

利益冲突声明

作者声明，他们没有已知的竞争性经济利益或可能影响本文所报告工作的个人关系。

致谢

本研究由山东省绵羊和山羊产业技术体系 (SDAIT-10-01)；山东省农业良种工程项目 (2021LZGC010)；山东省“双一流”项目基金 (SYL2017YSTD12)；山东省农业良种工程项目 (2019LZGC012) 资助。

数据可用性

数据将在要求时提供。

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MeRIP-seq data analysis and validation reveal the regulatory role of m<sup>6</sup>A modified circRNAs in the apoptosis of secondary hair follicle cells in Inner Mongolia cashmere goats
2025, Comparative Biochemistry and Physiology - Part D: Genomics and Proteomics
As a widely epigenetic modification, m⁶A (N⁶-methyladenosine, m⁶A) can regulate the degradation, translation, and other biological functions of circRNAs through dynamic reversible processes. It plays an important role in regulating the life activities of biological organisms, particularly in cell differentiation, apoptosis, embryonic development, stress response, and innate immunity. In this study, bioinformatics analysis, qRT-PCR identification, FISH subcellular localization, and ceRNA network construction were performed on m⁶A modified circRNAs regulating the apoptosis of secondary hair follicle cells of Inner Mongolia Albas white cashmere goats based on the skin m⁶A sequencing data of secondary hair follicles in anagen and catagen. The results showed that 8 m⁶A modified circRNAs regulating the cell apoptosis of secondary hair follicles, namely circRNA_2130, circRNA_0013, circRNA_1203, circRNA_1462, circRNA_1242, circRNA_2308, circRNA_2654 and circRNA_1442 were identified, and they are respectively derived from ANGEL2, APP, GKAP1, HNRNPC, PTBP3, NUCB1, SNRK and ZNF609 genes. Among them, circRNA_0013, circRNA_1442 and circRNA_1462 were located in the cytoplasm of the secondary hair follicle papilla, while circRNA_1203, circRNA_1242, circRNA_2130, circRNA_2308 and circRNA_2654 were located in the nucleus. There are complex and diverse regulatory relationships among 8 circRNAs, with each circRNA targeting one or more miRNAs, revealing that each m⁶A circRNA can exert regulatory effects through multiple potential miRNA-mRNA axes, to regulate the apoptosis of secondary hair follicle cells of cashmere goats during the growth cycles. This result provides a direction for further elucidating the regulatory mechanism of m⁶A modified circRNAs in cashmere growth and exploring biomarkers.
The TCONS_00046732/chi-miR-135b-5p/PRLR regulatory axis promotes endometrial epithelial cells growth through the PI3K-Akt signaling pathway
2024, International Journal of Biological Macromolecules
Non-coding RNAs are considered key regulatory factors in biological and reproductive physiological processes in mammals. However, the molecular functions of long noncoding RNAs (lncRNAs) in regulating dynamic uterine development and reproductive capacity during sexual maturation remain unclear. This study analyzed the expression characteristics and molecular functions of lncRNAs in uterine tissues from 20 goats at four specific time points during sexual maturation: day 1 after birth (D1), 2 months (M2), 4 months (M4), and 6 months (M6), finding that stage-specific DE lncRNAs may regulate cell proliferation, apoptosis, hormone secretion, metabolism, and immune response through multiple action modes. Within the lncRNA-miRNA-mRNA network, a novel lncRNA, TCONS_00046732, associated with uterine development, exhibited significantly higher expression during sexual maturity compared to the prepubertal stage, correlating positively with PRLR and negatively with chi-miR-135b-5p. FISH and IF analyses revealed significant co-localization and distinct expression patterns of TCONS_00046732, chi-miR-135b-5p, and PRLR in the endometrial epithelium. Further experiments confirmed that TCONS_00046732 competitively binds to chi-miR-135b-5p to upregulate PRLR, thereby activating the PI3K-Akt signaling pathway, promoting primary endometrial epithelial cell proliferation, G1-to-S phase transition, and inhibiting apoptosis. These findings enhance our understanding of uterine molecular regulation and provide key insights into the molecular basis of goat sexual development.
Review on Long Non-Coding RNAs as Biomarkers and Potentially Therapeutic Targets for Bacterial Infections
2024, Current Issues in Molecular Biology
Identification and Characterization of circRNAs in Non-Lactating Dairy Goat Mammary Glands Reveal Their Regulatory Role in Mammary Cell Involution and Remodeling
2023, Biomolecules

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非泌乳山羊乳腺中长链非编码 RNA 的特征分析揭示了其在乳腺细胞退化和重塑中的调控作用

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