Dose-dependent responses to canonical Wnt transcriptional complexes in the regulation of mammalian nephron progenitors

Wnt/ß-catenin signaling is a highly conserved molecular pathway that plays a crucial role in stem/progenitor systems and cancer. ß-catenin, the main Wnt pathway effector, has two pools within a cell: one for cell-cell adhesion at the membrane and the other for transcriptional functions in the nucleus. However, the mechanism by which ß-catenin mediates both roles remain unclear. The tightly controlled, well characterized system of nephrogenesis is an ideal model to decouple the roles of ß-catenin at the membrane and in the nucleus. In kidney development, a delicate balance of nephron progenitor cell self-renewal and differentiation is required for the mesenchymal to epithelial transition (MET) in nephrogenesis and is driven by Wnt/ß-catenin signaling. Given an ability to isolate and manipulate large numbers of NPCs in tissue culture, we can dissect the dual nature of ß-catenin as a transcriptional activator and component of a cell membrane complex in adhesion. We pioneered a method using CRISPR/Cas9 gene editing to rapidly remove ß-catenin, Tcf/Lef factors and simultaneous cadherin genes in primary NPCs. We have characterized the effects of modulating ß-catenin and integrated RNA-seq results from ß-catenin's removal with mouse ChIP-seq and mouse single cell RNA -seq data. Functional analysis of ß-catenin removal provides strong evidence for ß-catenin regulation of NPC proliferation, independent of a direct Lef/Tcf associated transcriptional program. Together these data suggest ß-catenin mediates aggregation, the first step in MET, through ß-catenin mediated cell adhesion complexes while simultaneous transcriptional activation within these structures initiates the nephrogenic program. The studies provide new insight into the direct transcriptional role of Lef/Tcf/ß-catenin complexes associated with the initiation of a nephron forming program. Overall, this study enhances an understanding of the molecular mechanisms underlying kidney development and the dual nature of ß-catenin stem/progenitor systems at large. Overall design: Primary nephron progenitors (NPCs)were isolated using the methods published in Brown et al., 2015 and were cultured in NPEM media. NPCs were then transfected using Lipofectamine™ MessengerMAX™ Transfection Reagent (Thermofisher, Cat # LMRNA015) with gene editing components (sgRNAs or Cre mRNA) and mCherry mRNA to distinguish transfected cells. Cells were cultured and lifted for FAC sorting. RNA was extracted from FAC sorted samples using mCherry+ NPCs were sorted on BD SORP FACS Aria IIu into RLT buffer with 1:100 beta-mercaptoethanol prior to RNA isolation. RNA was isolated using Qiagen RNeasy Micro Kit (74004). Total RNA integrity was determined using Agilent Bioanalyzer or 4200 Tapestation. Library preparation was performed with 10ng of total RNA with a Bioanalyzer RIN score greater than 8.0. ds-cDNA was prepared using the SMARTer Ultra Low RNA kit for Illumina Sequencing (Takara-Clontech) per manufacturer's protocol. cDNA was fragmented using a Covaris E220 sonicator using peak incident power 18, duty factor 20%, cycles per burst 50 for 120 seconds. cDNA was blunt ended, had an A base added to the 3' ends, and then had Illumina sequencing adapters ligated to the ends. Ligated fragments were then amplified for 12-15 cycles using primers incorporating unique dual index tags. Fragments were sequenced on an Illumina NovaSeq-6000 using paired end reads extending 150 bases. Basecalls and demultiplexing were performed with Illumina's bcl2fastq2 software. RNA-seq reads were then aligned to the combined mouse GRCm38 and human GRCh38 Ensembl release 76 primary assemblies with STAR version 2.5.1a1. Gene counts were derived from the number of uniquely aligned unambiguous reads by Subread:featureCount version 1.4.6-p52. Isoform expression of known Ensembl transcripts were estimated with Salmon version 0.8.23. Sequencing performance was assessed for the total number of aligned reads, total number of uniquely aligned reads, and features detected. The ribosomal fraction, known junction saturation, and read distribution over known gene models were quantified with RSeQC version 2.6.24. Normalized counts tables were ran through DeSEQ2 (Love, 2014 #412) to create differential gene expression tables with Log2Fc cut offs no less than 1 and p-adjusted values no greater than 0.05. Significance of Cre and Cas9 intersected gene lists was calculated with hypergeometric function in R. Differential expression tables were passed through Gene Ontology package clusterProfiler (Yu, 2012). Data was visualized using ggplot and Complex heatmap functions in R (Gu, 2016). Benjamini-Hochberg correction (False Discovery Rate) applied as well as significance associated with intersections compared to all genes expressed with gene normalized counts greater than or equal to 10 using hypergeometric test.