Abstract: Mammalian development requires substantial coordination to translate transcriptional and epigenetic programs into organized cellular behavior such as lineage specification. Using single-cell genomics, the comprehensive molecular landscape of mouse gastrulation and organogenesis has been well described. Because these atlas data lack the lineage information to connect profiled cell states to ultimate cell fates, it remains unclear how these molecular programs control cell fate choices during tissue diversification. The advances in single-cell genetic lineage tracing approaches provides a new lens for parallel assessment of cell fate and gene expression. Recent studies have combined cellular barcoding with single-cell multi-omics approaches to decipher fate-specific epigenome changes. However, it remains a challenge to simultaneously record cell lineage, transcriptomic, and epigenomic information in tissues with a massive number of cells. In this study, we developed a Cre-driven lineage-tracing approach that has high lineage recovery efficiency in single-cell assays and thus enables large-scale single-cell multi-omics lineage tracing in vivo. We validated this approach in embryos and demonstrated the robust capture of lineage barcodes across bulk-seq and scRNA-seq, revealing that epiblasts have heterogeneous lineage contribution to form embryonic tissues. We further leveraged this high-throughput lineage tracing approach by paring it with single-cell multi-omics profiling, to characterize transcriptomic and epigenomic changes in organ progenitors during early organogenesis, particular for the neuro-mesodermal progenitors (NMPs). Due to the addition of epigenomic information to gene expression, this approach allowed us to identify the essential TF in NMP fate decision. We uncovered the transcription factor Cdx2 as a central regulator of mesoderm fate determination, promoting NMP differentiation to mesoderm lineages. Collectively, we demonstrated the ability of in vivo single-cell multi-omics lineage tracing approach to quantify fate contribution of embryonic progenitors, to identify new progenitor subpopulations, as well as to provide new insights into the coordination between the transcriptome and epigenome in cell fate decisions.
