diff --git a/DESCRIPTION b/DESCRIPTION
index 99acc584b..baf2b0528 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,5 +1,5 @@
 Package: Seurat
-Version: 5.2.99.9000
+Version: 5.2.99.9001
 Title: Tools for Single Cell Genomics
 Description: A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031>, and Hao, Hao, et al (2020) <doi:10.1101/2020.10.12.335331> for more details.
 Authors@R: c(
diff --git a/NEWS.md b/NEWS.md
index c0269fdf8..02ce15b92 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,8 @@
+# Unreleased
+
+## Changes
+- Fixed `GroupCorrelation` and `GroupCorrelationPlot` to be compatible with `SeuratObject` >= 5.0.0 ([#9625](https://github.com/satijalab/seurat/pull/9625))
+
 # Seurat 5.2.1 (2025-01-23)
 
 ## Changes
diff --git a/R/utilities.R b/R/utilities.R
index f807ec298..18653d19e 100644
--- a/R/utilities.R
+++ b/R/utilities.R
@@ -986,7 +986,7 @@ GroupCorrelation <- function(
   grp.cors <- as.data.frame(x = grp.cors[which(x = !is.na(x = grp.cors))])
   grp.cors$gene_grp <- gene.grp[rownames(x = grp.cors)]
   colnames(x = grp.cors) <- c(paste0(var, "_cor"), "feature.grp")
-  object[[assay]][] <- grp.cors
+  object[[assay]] <- AddMetaData(object[[assay]], grp.cors)
   if (isTRUE(x = do.plot)) {
     print(GroupCorrelationPlot(
       object = object,
diff --git a/R/visualization.R b/R/visualization.R
index 65ef5c94a..66f53f409 100644
--- a/R/visualization.R
+++ b/R/visualization.R
@@ -4700,7 +4700,7 @@ GroupCorrelationPlot <- function(
   cor = "nCount_RNA_cor"
 ) {
   assay <- assay %||% DefaultAssay(object = object)
-  data <- object[[assay]][c(feature.group, cor)]
+  data <- object[[assay]][[c(feature.group, cor)]]
   data <- data[complete.cases(data), ]
   colnames(x = data) <- c('grp', 'cor')
   data$grp <- as.character(data$grp)