转录组学、蛋白质组学和基于图像的分析的集成记录了不同组学技术的一致性。(A)显示在我们的数据集中识别的主要肾元段的方案。Sc和sn数据集可以单独分析,也可以合并分析。均匀流形近似和投影记录了组合分析的结果。从分离的分析中获得细胞亚型计数(图S4, A和B)。相应的LMD片段显示包括用于识别每个亚段的标记物:phalloidin,荧光素异硫氰酸酯标记的phalloidin,用于分离肾小球和其他结构;LRP2, megalin与Alexa Fluor 568二级(红色);UMOD,直接偶联Alexa Fluor 546抗尿调素(红色);荧光素标记的PNA,花生凝集素标记收集管(绿色);4 ',6-二氨基-2-苯基吲哚为核(蓝色)。(B)在联合转录组分析中,我们使用基因表达数据的Pearson相关分析来识别LMD RNAseq数据中每个细胞或细胞核的封闭亚段。 Numbers document the number of cells/nuclei of each cluster mapped to each segment. (C) We calculated log2 fold changes between podocyte (or glomerulus) and PT cells (or tubulointerstitium) for each subject based on each assay. Pairwise correlation coefficients between all log2 fold changes were determined and used for hierarchical clustering. The variation in the axial ranges represents the divergences in the dynamic range of different assays as the axes are non-normalized. (D) Log2 fold changes obtained by the same assay were averaged across all subjects, followed by averaging of the results across all four transcriptomics and two proteomics assays. Positive or negative log2 fold changes indicate podocyte/glomerular or PT/tubulointerstitial expression. (E) Pairwise correlations between the sc/sn RNAseq and proteomic datasets document highest concordance between both proteomic and single-cell assays. Positive and negative log2 fold changes indicate podocyte/glomerular and PT/tubulointerstitial expression, respectively. Credit:科学的进步(2022)。DOI: 10.1126 / sciadv.abn4965
预测的钠转运能力与实验确定的重吸收曲线相匹配。(A)从实验确定的总钠重吸收剖面中去除估计的胞旁钠重吸收前后的估计跨细胞钠重吸收。(B)使用我们的和另外两个sn RNAseq数据集,我们计算了所有mRNA计数的总和,这些mRNA计数与肾小管每个节段的钠管腔到血液(L2B)和血到管腔(B2L)运输相关的基因有关。钠的净重吸收能力(彩色条)通过减去两者之和来确定,并与实验确定的跨细胞钠重吸收(灰色条)进行比较。(C)横坐标上方和下方分别可见L2B和B2L细胞类型特异性钠转运机制。错误条文档SEs。亲子关系记录在图例中,其中子scp写在其父scp的下面,并向右移动。为了防止重复计算,我们从每个父SCP中删除了已经被视为其子SCP一部分的任何mRNA水平。图中缺失的父SCP被添加到图例中一个无颜色框的旁边,以适当地记录SCP层次结构。对于多个父scp,我们只显示一个父scp。 Stacked bar diagram colors are in the same or reverse order as in the legend for L2B and B2L, respectively. Credit:科学的进步(2022)。DOI: 10.1126 / sciadv.abn4965