PD-1-cis IL-2R agonism yields better effectors from stem-like CD8+ T cells.

Expansion and differentiation of antigen-experienced PD-1+TCF-1+ stem-like CD8+ T cells into effector cells is critical for the success of immunotherapies based on PD-1 blockade1-4. Hashimoto et al. have shown that, in chronic infections, administration of the cytokine interleukin (IL)-2 triggers an alternative differentiation path of stem-like T cells towards a distinct population of 'better effector' CD8+ T cells similar to those generated in an acute infection5. IL-2 binding to the IL-2 receptor α-chain (CD25) was essential in triggering this alternative differentiation path and expanding better effectors with distinct transcriptional and epigenetic profiles. However, constitutive expression of CD25 on regulatory T cells and some endothelial cells also contributes to unwanted systemic effects from IL-2 therapy. Therefore, engineered IL-2 receptor ß- and γ-chain (IL-2Rßγ)-biased agonists are currently being developed6-10. Here we show that IL-2Rßγ-biased agonists are unable to preferentially expand better effector T cells in cancer models and describe PD1-IL2v, a new immunocytokine that overcomes the need for CD25 binding by docking in cis to PD-1. Cis binding of PD1-IL2v to PD-1 and IL-2Rßγ on the same cell recovers the ability to differentiate stem-like CD8+ T cells into better effectors in the absence of CD25 binding in both chronic infection and cancer models and provides superior efficacy. By contrast, PD-1- or PD-L1-blocking antibodies alone, or their combination with clinically relevant doses of non-PD-1-targeted IL2v, cannot expand this unique subset of better effector T cells and instead lead to the accumulation of terminally differentiated, exhausted T cells. These findings provide the basis for the development of a new generation of PD-1 cis-targeted IL-2R agonists with enhanced therapeutic potential for the treatment of cancer and chronic infections.

Waves of retrotransposon expansion remodel genome organization and CTCF binding in multiple mammalian lineages.

CTCF-binding locations represent regulatory sequences that are highly constrained over the course of evolution. To gain insight into how these DNA elements are conserved and spread through the genome, we defined the full spectrum of CTCF-binding sites, including a 33/34-mer motif, and identified over five thousand highly conserved, robust, and tissue-independent CTCF-binding locations by comparing ChIP-seq data from six mammals. Our data indicate that activation of retroelements has produced species-specific expansions of CTCF binding in rodents, dogs, and opossum, which often functionally serve as chromatin and transcriptional insulators. We discovered fossilized repeat elements flanking deeply conserved CTCF-binding regions, indicating that similar retrotransposon expansions occurred hundreds of millions of years ago. Repeat-driven dispersal of CTCF binding is a fundamental, ancient, and still highly active mechanism of genome evolution in mammalian lineages.

A stromal cell population that inhibits adipogenesis in mammalian fat depots.

Adipocyte development and differentiation have an important role in the aetiology of obesity and its co-morbidities1,2. Although multiple studies have investigated the adipogenic stem and precursor cells that give rise to mature adipocytes3-14, our understanding of their in vivo origin and properties is incomplete2,15,16. This is partially due to the highly heterogeneous and unstructured nature of adipose tissue depots17, which has proven difficult to molecularly dissect using classical approaches such as fluorescence-activated cell sorting and Cre-lox lines based on candidate marker genes16,18. Here, using the resolving power of single-cell transcriptomics19 in a mouse model, we reveal distinct subpopulations of adipose stem and precursor cells in the stromal vascular fraction of subcutaneous adipose tissue. We identify one of these subpopulations as CD142+ adipogenesis-regulatory cells, which can suppress adipocyte formation in vivo and in vitro in a paracrine manner. We show that adipogenesis-regulatory cells are refractory to adipogenesis and that they are functionally conserved in humans. Our findings point to a potentially critical role for adipogenesis-regulatory cells in modulating adipose tissue plasticity, which is linked to metabolic control, differential insulin sensitivity and type 2 diabetes.

LncRNA Ctcflos orchestrates transcription and alternative splicing in thermogenic adipogenesis.

The recruitment of thermogenic brite adipocytes within white adipose tissue attenuates obesity and metabolic comorbidities, arousing interest in understanding the underlying regulatory mechanisms. The molecular network of brite adipogenesis, however, remains largely unresolved. In this light, long noncoding RNAs (lncRNAs) emerged as a versatile class of modulators that control many steps within the differentiation machinery. Leveraging the naturally varying propensities of different inbred mouse strains for white adipose tissue browning, we identify the nuclear lncRNA Ctcflos as a pivotal orchestrator of thermogenic gene expression during brite adipocyte differentiation. Mechanistically, Ctcflos acts as a pleiotropic regulator, being essential for the transcriptional recruitment of the early core thermogenic regulatory program and the modulation of alternative splicing to drive brite adipogenesis. This is showcased by Ctcflos-regulated gene transcription and splicing of the key browning factor Prdm16 toward the isoform that is specific for the thermogenic gene program. Conclusively, our findings emphasize the mechanistic versatility of lncRNAs acting at several independent levels of gene expression for effective regulation of key differentiation factors to direct cell fate and function.

Insights into negative regulation by the glucocorticoid receptor from genome-wide profiling of inflammatory cistromes.

How the glucocorticoid receptor (GR) activates some genes while potently repressing others remains an open question. There are three current models for suppression: transrepression via GR tethering to AP-1/NF-κB sites, direct GR association with inhibitory elements (nGREs), and GR recruitment of the corepressor GRIP1. To gain insights into GR suppression, we used genomic analyses and genome-wide profiling of GR, p65, and c-Jun in LPS-stimulated macrophages. We show that GR mediates both activation and repression at tethered sites, GREs, and GRIP1-bound elements, indicating that motif classification is insufficient to predict regulatory polarity of GR binding. Interestingly, sites of GR repression utilize GRIP1's corepressor function and display reduced histone acetylation. Together, these findings suggest that while GR occupancy confers hormone responsiveness, the receptor itself may not participate in the regulatory effects. Furthermore, transcriptional outcome is not established by sequence but is influenced by epigenetic regulators, context, and other unrecognized regulatory determinants.

Latent regulatory potential of human-specific repetitive elements.

At least half of the human genome is derived from repetitive elements, which are often lineage specific and silenced by a variety of genetic and epigenetic mechanisms. Using a transchromosomic mouse strain that transmits an almost complete single copy of human chromosome 21 via the female germline, we show that a heterologous regulatory environment can transcriptionally activate transposon-derived human regulatory regions. In the mouse nucleus, hundreds of locations on human chromosome 21 newly associate with activating histone modifications in both somatic and germline tissues, and influence the gene expression of nearby transcripts. These regions are enriched with primate and human lineage-specific transposable elements, and their activation corresponds to changes in DNA methylation at CpG dinucleotides. This study reveals the latent regulatory potential of the repetitive human genome and illustrates the species specificity of mechanisms that control it.

ASAP: a web-based platform for the analysis and interactive visualization of single-cell RNA-seq data.

MOTIVATION: Single-cell RNA-sequencing (scRNA-seq) allows whole transcriptome profiling of thousands of individual cells, enabling the molecular exploration of tissues at the cellular level. Such analytical capacity is of great interest to many research groups in the world, yet these groups often lack the expertise to handle complex scRNA-seq datasets. RESULTS: We developed a fully integrated, web-based platform aimed at the complete analysis of scRNA-seq data post genome alignment: from the parsing, filtering and normalization of the input count data files, to the visual representation of the data, identification of cell clusters, differentially expressed genes (including cluster-specific marker genes), and functional gene set enrichment. This Automated Single-cell Analysis Pipeline (ASAP) combines a wide range of commonly used algorithms with sophisticated visualization tools. Compared with existing scRNA-seq analysis platforms, researchers (including those lacking computational expertise) are able to interact with the data in a straightforward fashion and in real time. Furthermore, given the overlap between scRNA-seq and bulk RNA-seq analysis workflows, ASAP should conceptually be broadly applicable to any RNA-seq dataset. As a validation, we demonstrate how we can use ASAP to simply reproduce the results from a single-cell study of 91 mouse cells involving five distinct cell types. AVAILABILITY AND IMPLEMENTATION: The tool is freely available at asap.epfl.ch and R/Python scripts are available at github.com/DeplanckeLab/ASAP. CONTACT: bart.deplancke@epfl.ch. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Cross-Tissue Identification of Somatic Stem and Progenitor Cells Using a Single-Cell RNA-Sequencing Derived Gene Signature.

A long-standing question in biology is whether multipotent somatic stem and progenitor cells (SSPCs) feature molecular properties that could guide their system-independent identification. Population-based transcriptomic studies have so far not been able to provide a definite answer, given the rarity and heterogeneous nature of these cells. Here, we exploited the resolving power of single-cell RNA-sequencing to develop a computational model that is able to accurately distinguish SSPCs from differentiated cells across tissues. The resulting classifier is based on the combined expression of 23 genes including known players in multipotency, proliferation, and tumorigenesis, as well as novel ones, such as Lcp1 and Vgll4 that we functionally validate in intestinal organoids. We show how this approach enables the identification of stem-like cells in still ambiguous systems such as the pancreas and the epidermis as well as the exploration of lineage commitment hierarchies, thus facilitating the study of biological processes such as cellular differentiation, tissue regeneration, and cancer. Stem Cells 2017;35:2390-2402.

Insights into hominid evolution from the gorilla genome sequence.

Gorillas are humans' closest living relatives after chimpanzees, and are of comparable importance for the study of human origins and evolution. Here we present the assembly and analysis of a genome sequence for the western lowland gorilla, and compare the whole genomes of all extant great ape genera. We propose a synthesis of genetic and fossil evidence consistent with placing the human-chimpanzee and human-chimpanzee-gorilla speciation events at approximately 6 and 10 million years ago. In 30% of the genome, gorilla is closer to human or chimpanzee than the latter are to each other; this is rarer around coding genes, indicating pervasive selection throughout great ape evolution, and has functional consequences in gene expression. A comparison of protein coding genes reveals approximately 500 genes showing accelerated evolution on each of the gorilla, human and chimpanzee lineages, and evidence for parallel acceleration, particularly of genes involved in hearing. We also compare the western and eastern gorilla species, estimating an average sequence divergence time 1.75 million years ago, but with evidence for more recent genetic exchange and a population bottleneck in the eastern species. The use of the genome sequence in these and future analyses will promote a deeper understanding of great ape biology and evolution.

Cohesin regulates tissue-specific expression by stabilizing highly occupied cis-regulatory modules.

The cohesin protein complex contributes to transcriptional regulation in a CTCF-independent manner by colocalizing with master regulators at tissue-specific loci. The regulation of transcription involves the concerted action of multiple transcription factors (TFs) and cohesin's role in this context of combinatorial TF binding remains unexplored. To investigate cohesin-non-CTCF (CNC) binding events in vivo we mapped cohesin and CTCF, as well as a collection of tissue-specific and ubiquitous transcriptional regulators using ChIP-seq in primary mouse liver. We observe a positive correlation between the number of distinct TFs bound and the presence of CNC sites. In contrast to regions of the genome where cohesin and CTCF colocalize, CNC sites coincide with the binding of master regulators and enhancer-markers and are significantly associated with liver-specific expressed genes. We also show that cohesin presence partially explains the commonly observed discrepancy between TF motif score and ChIP signal. Evidence from these statistical analyses in wild-type cells, and comparisons to maps of TF binding in Rad21-cohesin haploinsufficient mouse liver, suggests that cohesin helps to stabilize large protein-DNA complexes. Finally, we observe that the presence of mirrored CTCF binding events at promoters and their nearby cohesin-bound enhancers is associated with elevated expression levels.

Tumor-agnostic transcriptome-based classifier identifies spatial infiltration patterns of CD8+T cells in the tumor microenvironment and predicts clinical outcome in early-phase and late-phase clinical trials.

BACKGROUND: The immune status of a patient's tumor microenvironment (TME) may guide therapeutic interventions with cancer immunotherapy and help identify potential resistance mechanisms. Currently, patients' immune status is mostly classified based on CD8+tumor-infiltrating lymphocytes. An unmet need exists for comparable and reliable precision immunophenotyping tools that would facilitate clinical treatment-relevant decision-making and the understanding of how to overcome resistance mechanisms. METHODS: We systematically analyzed the CD8 immunophenotype of 2023 patients from 14 phase I-III clinical trials using immunohistochemistry (IHC) and additionally profiled gene expression by RNA-sequencing (RNA-seq). CD8 immunophenotypes were classified by pathologists into CD8-desert, CD8-excluded or CD8-inflamed tumors using CD8 IHC staining in epithelial and stromal areas of the tumor. Using regularized logistic regression, we developed an RNA-seq-based classifier as a surrogate to the IHC-based spatial classification of CD8+tumor-infiltrating lymphocytes in the TME. RESULTS: The CD8 immunophenotype and associated gene expression patterns varied across indications as well as across primary and metastatic lesions. Melanoma and kidney cancers were among the strongest inflamed indications, while CD8-desert phenotypes were most abundant in liver metastases across all tumor types. A good correspondence between the transcriptome and the IHC-based evaluation enabled us to develop a 92-gene classifier that accurately predicted the IHC-based CD8 immunophenotype in primary and metastatic samples (area under the curve inflamed=0.846; excluded=0.712; desert=0.855). The newly developed classifier was prognostic in The Cancer Genome Atlas (TCGA) data and predictive in lung cancer: patients with predicted CD8-inflamed tumors showed prolonged overall survival (OS) versus patients with CD8-desert tumors (HR 0.88; 95% CI 0.80 to 0.97) across TCGA, and longer OS on immune checkpoint inhibitor administration (phase III OAK study) in non-small-cell lung cancer (HR 0.75; 95% CI 0.58 to 0.97). CONCLUSIONS: We provide a new precision immunophenotyping tool based on gene expression that reflects the spatial infiltration patterns of CD8+ lymphocytes in tumors. The classifier enables multiplex analyses and is easy to apply for retrospective, reverse translation approaches as well as for prospective patient enrichment to optimize the response to cancer immunotherapy.

Myeloid-T cell interplay and cell state transitions associated with checkpoint inhibitor response in melanoma.

BACKGROUND: The treatment of melanoma, the deadliest form of skin cancer, has greatly benefited from immunotherapy. However, many patients do not show a durable response, which is only partially explained by known resistance mechanisms. METHODS: We performed single-cell RNA sequencing of tumor immune infiltrates and matched peripheral blood mononuclear cells of 22 checkpoint inhibitor (CPI)-naive stage III-IV metastatic melanoma patients. After sample collection, the same patients received CPI treatment, and their response was assessed. FINDINGS: CPI responders showed high levels of classical monocytes in peripheral blood, which preferentially transitioned toward CXCL9-expressing macrophages in tumors. Trajectories of tumor-infiltrating CD8+ T cells diverged at the level of effector memory/stem-like T cells, with non-responder cells progressing into a state characterized by cellular stress and apoptosis-related gene expression. Consistently, predicted non-responder-enriched myeloid-T/natural killer cell interactions were primarily immunosuppressive, while responder-enriched interactions were supportive of T cell priming and effector function. CONCLUSIONS: Our study illustrates that the tumor immune microenvironment prior to CPI treatment can be indicative of response. In perspective, modulating the myeloid and/or effector cell compartment by altering the described cell interactions and transitions could improve immunotherapy response. FUNDING: This research was funded by Roche Pharma Research and Early Development.

Profiling the heterogeneity of colorectal cancer consensus molecular subtypes using spatial transcriptomics.

The consensus molecular subtypes (CMS) of colorectal cancer (CRC) is the most widely-used gene expression-based classification and has contributed to a better understanding of disease heterogeneity and prognosis. Nevertheless, CMS intratumoral heterogeneity restricts its clinical application, stressing the necessity of further characterizing the composition and architecture of CRC. Here, we used Spatial Transcriptomics (ST) in combination with single-cell RNA sequencing (scRNA-seq) to decipher the spatially resolved cellular and molecular composition of CRC. In addition to mapping the intratumoral heterogeneity of CMS and their microenvironment, we identified cell communication events in the tumor-stroma interface of CMS2 carcinomas. This includes tumor growth-inhibiting as well as -activating signals, such as the potential regulation of the ETV4 transcriptional activity by DCN or the PLAU-PLAUR ligand-receptor interaction. Our study illustrates the potential of ST to resolve CRC molecular heterogeneity and thereby help advance personalized therapy.

A CTCF-independent role for cohesin in tissue-specific transcription.

The cohesin protein complex holds sister chromatids in dividing cells together and is essential for chromosome segregation. Recently, cohesin has been implicated in mediating transcriptional insulation, via its interactions with CTCF. Here, we show in different cell types that cohesin functionally behaves as a tissue-specific transcriptional regulator, independent of CTCF binding. By performing matched genome-wide binding assays (ChIP-seq) in human breast cancer cells (MCF-7), we discovered thousands of genomic sites that share cohesin and estrogen receptor alpha (ER) yet lack CTCF binding. By use of human hepatocellular carcinoma cells (HepG2), we found that liver-specific transcription factors colocalize with cohesin independently of CTCF at liver-specific targets that are distinct from those found in breast cancer cells. Furthermore, estrogen-regulated genes are preferentially bound by both ER and cohesin, and functionally, the silencing of cohesin caused aberrant re-entry of breast cancer cells into cell cycle after hormone treatment. We combined chromosomal interaction data in MCF-7 cells with our cohesin binding data to show that cohesin is highly enriched at ER-bound regions that capture inter-chromosomal loop anchors. Together, our data show that cohesin cobinds across the genome with transcription factors independently of CTCF, plays a functional role in estrogen-regulated transcription, and may help to mediate tissue-specific transcriptional responses via long-range chromosomal interactions.

Dissecting the Mechanisms Underlying the Cytokine Release Syndrome (CRS) Mediated by T-Cell Bispecific Antibodies.

PURPOSE: Target-dependent TCB activity can result in the strong and systemic release of cytokines that may develop into cytokine release syndrome (CRS), highlighting the need to understand and prevent this complex clinical syndrome. EXPERIMENTAL DESIGN: We explored the cellular and molecular players involved in TCB-mediated cytokine release by single-cell RNA-sequencing of whole blood treated with CD20-TCB together with bulk RNA-sequencing of endothelial cells exposed to TCB-induced cytokine release. We used the in vitro whole blood assay and an in vivo DLBCL model in immunocompetent humanized mice to assess the effects of dexamethasone, anti-TNFα, anti-IL6R, anti-IL1R, and inflammasome inhibition, on TCB-mediated cytokine release and antitumor activity. RESULTS: Activated T cells release TNFα, IFNγ, IL2, IL8, and MIP-1ß, which rapidly activate monocytes, neutrophils, DCs, and NKs along with surrounding T cells to amplify the cascade further, leading to TNFα, IL8, IL6, IL1ß, MCP-1, MIP-1α, MIP-1ß, and IP-10 release. Endothelial cells contribute to IL6 and IL1ß release and at the same time release several chemokines (MCP-1, IP-10, MIP-1α, and MIP-1ß). Dexamethasone and TNFα blockade efficiently reduced CD20-TCB-mediated cytokine release whereas IL6R blockade, inflammasome inhibition, and IL1R blockade induced a less pronounced effect. Dexamethasone, IL6R blockade, IL1R blockade, and the inflammasome inhibitor did not interfere with CD20-TCB activity, in contrast to TNFα blockade, which partially inhibited antitumor activity. CONCLUSIONS: Our work sheds new light on the cellular and molecular players involved in cytokine release driven by TCBs and provides a rationale for the prevention of CRS in patients treated with TCBs. See related commentary by Luri-Rey et al., p. 4320.

Combinations of Toll-like receptor 8 agonist TL8-506 activate human tumor-derived dendritic cells.

BACKGROUND: Dendritic cells (DCs) are professional antigen presenting cells that initiate immune defense to pathogens and tumor cells. Human tumors contain only few DCs that mostly display a non-activated phenotype. Hence, activation of tumor-associated DCs may improve efficacy of cancer immunotherapies. Toll-like receptor (TLR) agonists and interferons are known to promote DC maturation. However, it is unclear if DCs in human tumors respond to activation signals and which stimuli induce the optimal activation of human tumor DCs. METHODS: We first screened combinations of TLR agonists, a STING agonist and interferons (IFNs) for their ability to activate human conventional DCs (cDCs). Two combinations: TL8-506 (a TLR8 agonist)+IFN-γ and TL8-506+Poly(I:C) (a TLR3 agonist) were studied in more detail. cDC1s and cDC2s derived from cord blood stem cells, blood or patient tumor samples were stimulated with either TL8-506+IFN-γ or TL8-506+Poly(I:C). Different activation markers were analyzed by ELISA, flow cytometry, NanoString nCounter Technology or single-cell RNA-sequencing. T cell activation and migration assays were performed to assess functional consequences of cDC activation. RESULTS: We show that TL8-506 synergized with IFN-γ or Poly(I:C) to induce high expression of different chemokines and cytokines including interleukin (IL)-12p70 in human cord blood and blood cDC subsets in a combination-specific manner. Importantly, both combinations induced the activation of cDC subsets in patient tumor samples ex vivo. The expression of immunostimulatory genes important for anticancer responses including CD40, IFNB1, IFNL1, IL12A and IL12B were upregulated on stimulation. Furthermore, chemokines associated with CD8+ T cell recruitment were induced in tumor-derived cDCs in response to TL8-506 combinations. In vitro activation and migration assays confirmed that stimulated cDCs induce T cell activation and migration. CONCLUSIONS: Our data suggest that cord blood-derived and blood-derived cDCs are a good surrogate to study treatment responses in human tumor cDCs. While most cDCs in human tumors display a non-activated phenotype, TL8-506 combinations drive human tumor cDCs towards an immunostimulatory phenotype associated with Th1 responses on stimulation. Hence, TL8-506-based combinations may be promising candidates to initiate or boost antitumor responses in patients with cancer.

Besca, a single-cell transcriptomics analysis toolkit to accelerate translational research.

Single-cell RNA sequencing (scRNA-seq) revolutionized our understanding of disease biology. The promise it presents to also transform translational research requires highly standardized and robust software workflows. Here, we present the toolkit Besca, which streamlines scRNA-seq analyses and their use to deconvolute bulk RNA-seq data according to current best practices. Beyond a standard workflow covering quality control, filtering, and clustering, two complementary Besca modules, utilizing hierarchical cell signatures and supervised machine learning, automate cell annotation and provide harmonized nomenclatures. Subsequently, the gene expression profiles can be employed to estimate cell type proportions in bulk transcriptomics data. Using multiple, diverse scRNA-seq datasets, some stemming from highly heterogeneous tumor tissue, we show how Besca aids acceleration, interoperability, reusability and interpretability of scRNA-seq data analyses, meeting crucial demands in translational research and beyond.

Positive selection in tick saliva proteins of the Salp15 family.

When taking their blood meal on the mammalian host, ticks transfer a multitude of different proteins from their saliva into the host. Some of these proteins are hijacked by pathogens for their own purposes. Borrelia burgdorferi, the Lyme disease agent, is critically dependent on the presence of the tick protein Salp15 when infecting the host. Similarly, Anaplasma phagocytophilum, which causes anaplasmosis, needs Salp16, a homologue of Salp15, to get transferred from the host into the tick. Here we analyzed whether adaptive evolution has shaped the Salp15 protein family. Using site-specific estimates of K(A)/K(S) ratios, we identified different positions within the Salp15 protein family which have undergone a phase of positive selection. Additionally, we analyzed the B. burgdorferi protein interacting with Salp15, OspC. Again, sites showing signs of positive selection were identified, although they are more likely a result of the antigenic features of OspC than of the influence of Salp15. The identification of probably functionally relevant sites in the Salp15 family might direct the detailed experimental analysis of their interaction with human and bacterial proteins.

Systems-Genetics-Based Inference of a Core Regulatory Network Underlying White Fat Browning.

Recruitment of brite/beige cells, known as browning of white adipose tissue (WAT), is an efficient way to turn an energy-storing organ into an energy-dissipating one and may therefore be of therapeutic value in combating obesity. However, a comprehensive understanding of the regulatory mechanisms mediating WAT browning is still lacking. Here, we exploit the large natural variation in WAT browning propensity between inbred mouse strains to gain an inclusive view of the core regulatory network coordinating this cellular process. Combining comparative transcriptomics, perturbation-based validations, and gene network analyses, we present a comprehensive gene regulatory network of inguinal WAT browning, revealing up to four distinct regulatory modules with key roles for uncovered transcriptional factors, while also providing deep insights into the genetic architecture of brite adipogenesis. The presented findings therefore greatly increase our understanding of the molecular drivers mediating the intriguing cellular heterogeneity and plasticity of adipose tissue.

ZFP30 promotes adipogenesis through the KAP1-mediated activation of a retrotransposon-derived Pparg2 enhancer.

Krüppel-associated box zinc finger proteins (KZFPs) constitute the largest family of mammalian transcription factors, but most remain completely uncharacterized. While initially proposed to primarily repress transposable elements, recent reports have revealed that KFZPs contribute to a wide variety of other biological processes. Using murine and human in vitro and in vivo models, we demonstrate here that one poorly studied KZFP, ZFP30, promotes adipogenesis by directly targeting and activating a retrotransposon-derived Pparg2 enhancer. Through mechanistic studies, we further show that ZFP30 recruits the co-regulator KRAB-associated protein 1 (KAP1), which, surprisingly, acts as a ZFP30 co-activator in this adipogenic context. Our findings provide an understanding of both adipogenic and KZFP-KAP1 complex-mediated gene regulation, showing that the KZFP-KAP1 axis can also function in a non-repressive manner.