ZFP92, a KRAB domain zinc finger protein enriched in pancreatic islets, binds to B1/Alu SINE transposable elements and regulates retroelements and genes


Anna B. Osipovich , et al.


Repressive KRAB domain-containing zinc-finger proteins (KRAB-ZFPs) are abundant in mammalian genomes and contribute both to the silencing of transposable elements (TEs) and to the regulation of developmental stage- and cell type-specific gene expression. Here we describe studies of zinc finger protein 92 (Zfp92), an X-linked KRAB-ZFP that is highly expressed in pancreatic islets of adult mice, by analyzing global Zfp92 knockout (KO) mice. Physiological, transcriptomic and genome-wide chromatin binding studies indicate that the principal function of ZFP92 in mice is to bind to and suppress the activity of B1/Alu type of SINE elements and modulate the activity of surrounding genomic entities. Deletion of Zfp92 leads to changes in expression of select LINE and LTR retroelements and genes located in the vicinity of ZFP92-bound chromatin. The absence of Zfp92 leads to altered expression of specific genes in islets, adipose and muscle that result in modest sex-specific alterations in blood glucose homeostasis, body mass and fat accumulation. In islets, Zfp92 influences blood glucose concentration in postnatal mice via transcriptional effects on Mafb, whereas in adipose and muscle, it regulates Acacb, a rate-limiting enzyme in fatty acid metabolism. In the absence of Zfp92, a novel TE-Capn11 fusion transcript is overexpressed in islets and several other tissues due to de-repression of an IAPez TE adjacent to ZFP92-bound SINE elements in intron 3 of the Capn11 gene. Together, these studies show that ZFP92 functions both to repress specific TEs and to regulate the transcription of specific genes in discrete tissues.


Zinc finger proteins (ZFPs) containing classical C2H2 (Cys2-His2) zinc finger domains, a conserved DNA-binding motif, represent a large but poorly explored family of higher eukaryotic transcription factors (TFs) [1]. The human genome encodes 747 C2H2 finger-containing proteins which represent nearly half of all human TFs [2], most of which bind DNA and regulate transcription [3]. Each C2H2 zinc finger consists of a 23–30 amino-acid motif stabilized by a zinc ion and binds to a 3–4 nucleotide target DNA sequence [4]. ZFPs typically contain one to more than a dozen of zinc finger motifs as well as other domains such as protein-protein interacting SCAN domains (7% of C2H2 ZFPs), transcriptional regulatory BTB/POZ domains (7%), and KRAB domains (43%) [5,6]. Some C2H2-ZFPs have been highly conserved throughout evolution and partner with conserved nuclear receptors, consistent with their involvement in preserved biological activities such as general transcriptional regulation and early organogenesis [7]. However, other C2H2-ZFPs, particularly those containing repressive KRAB domains, have undergone evolutionary gene duplication and expansion, particularly in mammals, and are thought to be involved in modulating complex species-specific gene transcriptional networks [7].

KRAB-ZFPs contain an N-terminal Krüppel-associated box (KRAB) domain that functions by attracting repressive co-factors, such as the principal co-repressor KRAB-associated protein-1 (KAP1, also known as TRIM28), heterochromatin protein 1 (HP1), histone deacetylases, corepressor complexes (NuRD and NCOR), the histone methyltransferase SETDB1 and DNA methyltransferases [8]. Despite their genomic abundance, the function of most KRAB-ZFPs remains undefined [9]. While KRAB-mediated transcriptional repression is linked to diverse biological functions including regulation of cell proliferation, differentiation and apoptosis [10], evidence also points to a primary role of KRAB-ZFPs in silencing of transposable elements (TEs) in the genome [1113].

TEs account for more than half of the human and murine genomes [14] and are important drivers of genomic regulatory diversity and evolution. However, due to their abundance, they also represent threats to genomic integrity and gene regulation [15,16]. Retrotransposons, the predominant TEs found in mammalian genomes, have been grouped into three classes: short interspersed nuclear elements (SINEs), long interspersed nuclear elements (LINEs), and long terminal repeat retrotransposons (LTRs) [17]. The LTR class is represented by endogenous retroviruses (ERVs) containing retroviral structures with gag-pol-env genes flanked by LTRs that contain cis-regulatory elements [18]. While most retroelements are inactive due to silencing and mutations, some remain or can become active and may contribute to disease through deleterious insertion mutations and dysregulation of host gene expression [19,20].

Many KRAB-ZFPs have similar evolutionary ages to their target TEs, and exist in roughly equal proportions, suggesting that they co-evolved in response to TE infiltration [21]. Indeed, a dynamic competition, or so-called arms race, between TEs and KRAB-ZFPs has been suggested to have occurred during mammalian evolution with the selection, expansion and adaptation of specific KRAB-ZFP serving to silence TE expression and retrotransposon activity [22,23]. However, another proposed complementary evolutionary driver is the domestication of TE-derived regulatory sequences whereby KRAB-ZFPs co-evolve with TEs to rewire gene regulatory networks in each species, therefore impacting on development and function of different tissues [9,24]. For example, Zfp932 and Gm15446, two mouse KRAB-ZFPs, have been shown to not only repress ERVs but to also modify the expression of neighboring genes in embryonic stem cells and adult tissues [25]. Similarly, two primate-specific KRAB-ZFPs, ZNF417 and ZNF587, repress human ERV and SINE elements in embryonic stem cells and, through expression in specific brain regions, influence the differentiation and neurotransmission profile of neurons [26]. Indeed, both TEs and their KRAB-ZFP controllers have been shown to regulate gene expression in the human brain in a region-specific manner and to drive transcriptional innovation [27,28]. These studies suggest that TEs and KRAB-ZFPs establish transcriptional networks that regulate cell differentiation and function in a species- and tissue-specific manner.

Pancreatic endocrine cells in the islets of Langerhans regulate blood glucose homeostasis through secretion of hormones into the bloodstream. There are five distinct cell types, the most abundant of which are α- and β- cells that secrete glucagon and insulin, respectively [29]. Alterations in TFs that regulate differentiation and function of β-cells contribute to development of diabetes [30]. Previously, we derived a developmental gene co-expression network (GCN) for mouse pancreatic β-cells that revealed 81 C2H2-ZFPs whose expression was associated with endocrine specification and pancreatic β-cell maturation [31]. Among these genes, Zfp92, a KRAB-ZFP located on the X chromosome, was found to be highly expressed in nascent and mature β-cells, prompting us to explore its role in pancreatic β-cell gene regulation by using CRISPR/Cas9 to generate a global knockout (KO) allele.

Here, we describe Zfp92 KO mice. We found that the absence of Zfp92 in islets modestly impairs insulin gene transcription in post-natal mice via transcriptional effects on Mafb. Additionally, the analysis revealed that Zfp92 KO male mice had impaired expression of Acacb, a rate-limiting enzyme in fatty acid β-oxidation, that results in sex-specific alterations in insulin sensitivity and body mass when fed a high fat diet. However, the major role of Zfp92 is to potentially suppress the activity of B1/Alu SINE elements by binding to a 28 bp consensus ZFP92 binding motif. De-repression of an IAPez ERV located next to SINE elements in Capn11 gene intron in the absence of Zfp92 leads to marked overproduction of a novel fusion TE-Capn11 transcript the function of which remains unknown. Together, our data reveal a multifunctional role for Zfp92 in regulating gene expression in the mouse, providing another example of how KRAB-ZFPs can simultaneously be involved in suppressing specific TEs and in the regulation of tissue-specific gene regulation.


Zfp92 tissue expression, mRNA forms and Zfp92 knockout mice

Using data from our prior gene correlation network analysis of purified cell populations representing main stages of β-cell development from embryonic day (E) 8.0 to postnatal day (P) 60 in mice [31], we observed that Zfp92 expression is increased at E15.5 in pro-endocrine pancreatic progenitor cells that express Neurog3, further upregulated in nascent β-cells and maintained in mature β-cells (Fig 1A). RT-qPCR of mouse adult tissues showed that Zfp92 is predominantly expressed in pancreatic islets, with higher levels also detected in brain, whole pancreas, and testis samples (Fig 1B). In addition, scRNA-Seq data from Tabula Muris [32] indicate that Zfp92 is predominantly expressed in β-cells, with lower levels in α- and δ-cells in mouse islets [31].


Fig 1. Zfp92 expression and CRISPR-derived knock-out allele.

A) Expression levels of Zfp92 mRNA profiled by RNA-seq in sorted pancreatic developmental lineages: gut tube endoderm (Sox17+ at E8.0/8.5), posterior foregut endoderm (Pdx1+ at E9.5), pancreatic multipotent progenitor cells (Ptf1a+ at E10.5), endocrine progenitor cells (Neurog3+ and Insm1+ at E15.5), nascent β-cells (Ins+ at E16.5), and adult β-cells (Ins+ at P60). Two profiled mutant conditions for endocrine progenitor cells (Neurog3-/- and Insm1-/- at E15.5) indicate that Zfp92 is reduced in the absence of Neurog3. N = 3.B) Tissue expression patterns of Zfp92 determined by the RT-qPCR analysis of RNA from tissues from adult mice (10 weeks old). All tissues, except ovaries, are from male mice. N = 3. Relative expression is calculated in comparison to the same gene expression in the intestine. Br, brain; Lu, lung; He, heart; Th, thymus; Mu, skeletal muscle; Sk, skin; Ad, adipose; Li, liver; Pa, whole pancreas; Is, pancreatic islets; Sp, spleen; In, small intestine; Ki, kidney; Ov, ovary; Te, testis. C) Schematic representation of Zfp92 gene and relative gene location and sequence of CRISPR/Cas9 generated 7 bp deletion. Deletion of 7 bp in Zfp92 causes a frameshift that interrupts ZFP92 protein translation resulting in a predicted 50 aa peptide containing 8 missense amino acids. D) Representative image of a PCR genotyping gel for Zfp92 wild type (WT), heterozygous (Het), and knockout (KO) mice.


Since the Zfp92 gene model predicts two mRNA forms, a long form that encodes a full length ZFP92 protein and a short form that encodes a C-terminally truncated ZFP92 (S1A Fig), we designed primer pairs specific to each form and performed RT-PCR and qPCR on islet samples to establish which is predominantly expressed in islets, (S1A–S1D Fig). The results show that the predominant RNA form expressed in pancreatic islets is the longer variant that encodes a 488 aa protein containing an N-terminal KRAB domain and an array of 8 C2H2 zinc fingers.

Since Zfp92 is highly enriched in both islets and pancreatic β-cells, we hypothesized that this gene may serve an important but undefined role in pancreatic islet development and/or function. For this reason, we performed CRISPR/Cas9 mutagenesis by injecting guide RNAs targeting Zfp92 into mouse zygotes that express CRISPR/Cas9. Analysis of the offspring revealed a founder animal bearing a 7 bp frameshift deletion downstream of the translation initiation codon in the gene (Fig 1C and 1D). The 7 bp deletion creates a frameshift in an open reading frame that leads to a premature STOP codon resulting in a truncated 50 aa protein thereby generating a null (KO) allele for Zfp92 (Fig 1C).

Zfp92 KO mice exhibit sex-specific alterations in body weight and fasting blood glucose

Zfp92 homozygous KO mice were viable, fertile and did not demonstrate any gross abnormalities. Weekly monitoring of body weight for 10 weeks of male and female mice maintained on normal diet revealed that Zfp92 KO males have lower body weight than their wild type (WT) counterparts beginning from 6 months of age (Fig 2A). We did not observe any significant differences in body composition measurements at 14 months indicating that weight differences are not due to disproportionate accumulation of fat (Fig 2B and 2C). We assessed glucose homeostasis in WT and KO mice by measuring fasting and fed blood glucose, plasma insulin, and by performing intraperitoneal glucose and insulin tolerance tests (Fig 2D–2I, S2A and S2B Fig). These measurements revealed a slight decrease in fasting blood glucose in male mice (Fig 2D), however, the mice showed similar fed blood glucose and insulin, insulin secretion in response to glucose injection (Fig 2H), and no differences in glucose (Fig 2G) and insulin tolerance (Fig 2I). Immunostaining and morphometric analyses of pancreatic tissue sections from KO and WT mice did not show any abnormalities in islet architecture, islet composition or β-cell area (Fig 2J and 2K).


Fig 2. Growth, body fat composition, glucose homeostasis, and islet structure of Zfp92 KO mice.

A) Body weight measurements from 4 to 14 weeks showing Zfp92 KO male mice have reduced growth in comparison to WT males (n = 7,8 for each sex and genotype. Lean body mass (B) and body fat (C) measurements show no difference between KO and WT mice body composition at (n = 5–7 for each sex and genotype). Fasted (D) and fed (E) blood glucose concentration measurements. KO mice have lower fasting blood glucose than WT mice. (n = 8–11 for each sex and genotype). F) Random fed plasma insulin levels (n = 4, male mice). G) Intraperitoneal glucose tolerance test (GTT) results are presented as the area under the curve (AUC) measurements for S2A Fig (n = 7 for each sex and genotype). H) Insulin secretion in response to glucose injection in GTT (n = 4, males). Both genotypes show an equal increase in plasma insulin concentration 15 min after injection. I) Intraperitoneal insulin tolerance test (ITT) results presented as the area under the curve (AUC) measurements for S2B Fig (n = 7–8 for each sex and genotype). J) Immunofluorescent staining for insulin (red) and glucagon (green) of pancreatic islet tissues from WT and Zfp92 KO mice. Nuclei are stained with DAPI (blue). Scale bar: 100 microns. K) Quantification of hormone-positive areas in KO and WT islets (n = 3, males at 14–15 weeks). B-K) All mice are 14–15 weeks old. Statistical significance between KO and WT samples is indicated by black brackets, and between sexes by gray brackets. Error bars: ± SEM. **p≤0.01; *p≤0.05. p-value determined by ANOVA or by t-test (panels F, K).


Zfp92 KO mice have altered body composition and elevated fasting blood glucose on a high fat diet

To investigate whether Zfp92 influences β-cell function in response to metabolic stress, we fed WT and Zfp92 KO mice a high fat diet (HFD) for 10 weeks and then assessed body composition and glucose homeostasis at 14–15 weeks of age. While WT and KO mice gained similar amounts of weight on HFD (Fig 3A), KO female mice had decreased lean body mass and increased body fat after 10 weeks on a HFD (Fig 3B and 3C). Glucose homeostasis measurements showed that KO male mice have slightly increased fasting blood glucose (Fig 3D), but no significant differences in fed blood glucose, insulin, or glucose tolerance were found (Fig 3E–3G, S2C and S2D Fig). Male KO mice had increased insulin sensitivity, suggesting that Zfp92 affects the function of one or more insulin target tissues (Fig 3H). Feeding of a HFD did not significantly affect β-cell area in mice lacking Zfp92 (Fig 3I and 3J). Combined, these data indicate that the absence of Zfp92 has only a mild effect on β-cell function, even during metabolic stress brought on by the feeding of a HFD. However, sex-specific differences in fat accumulation and insulin sensitivity were observed, suggesting a role for Zfp92 in insulin target tissues such as adipose, muscle and liver.


Fig 3. Effects of a high fat diet (HFD) on weight gain, body composition, glucose homeostasis and islet structure of Zfp92 KO mice.

A) Weight gain on HFD for 10 weeks was similar for both wild type (WT) and Zfp92 knockout (KO) animals (n = 7–9 for each sex and genotype). Lean body mass (B) and body fat (C) measurements show an increase in body fat content and a decrease in lean body mass in KO female mice on HFD (n = 7–8 for each sex and genotype). Fasted (D) and fed (E) blood glucose concentration measurements. KO male mice have higher fasting blood glucose than WT mice on HFD (n = 7,8 for each sex and genotype). F) Random fed plasma insulin levels (n = 4, male mice). G) Intraperitoneal glucose tolerance test (GTT) results are presented as the area under the curve (AUC) measurements for S2C Fig (n = 8 for each sex and genotype). H) Intraperitoneal insulin tolerance test (ITT) results are presented as the area under the curve (AUC) measurements for S2D Fig (n = 8 for each sex and genotype). KO male mice have higher insulin sensitivity than WT mice on HFD. I) Quantification of insulin-positive β-cell areas in KO and WT islets on HFD (n = 4, males at 14–15 weeks). J) Immunofluorescence staining for insulin (red) of pancreatic islet tissues from HFD-fed WT and Zfp92 KO mice. Nuclei are stained with DAPI (blue). Scale bar: 100 microns. B-J) All mice are 14–15 weeks old. Statistical significance between KO and WT samples is indicated by black brackets, and between sexes by gray brackets. Error bars: ± SEM. **p≤0.01; *p≤0.05. p-value determined by ANOVA or by unpaired t-test (panels F, K).


Transcriptional profiling of Zfp92 KO islets reveals an increase in Capn11 and a decrease in Mafb expression

To determine whether Zfp92 influences gene expression in mouse islets, we performed RNA-Seq of male WT and KO islet samples. Differential expression analysis showed that the expression of only 30 genes was significantly affected (padj<0.05), with 9 genes being upregulated and 21 genes downregulated in Zfp92 KOs (Fig 4A and 4B and S2 Table). Notably, there was a very pronounced increase in expression of Capn11 gene (Log2FoldChange = 4.39), a gene that encodes a calcium-dependent protease calpain 11 that is usually expressed only specifically in testis [33]. Zfp92 was also increased in KO samples suggesting that ZFP92 may repress its own expression. The downregulated genes included the transcriptional regulators Mafb, Mamld1, Cited2, and Tref1, the former of which is known to be enriched in pancreatic α-cells in adult islets where it regulates the expression of pancreatic hormone glucagon (Gcg) [34]. To validate RNA-seq findings, we performed RT-qPCR on islet RNA and confirmed that the expression of Capn11 was increased more than 200 times, and that expression of Zfp92 is significantly upregulated and Mafb is downregulated in samples from KO mice (Fig 4C). While expression of Gcg was also decreased, and similar to the RNA-seq result, the changes were not significant. With the exception of Capn11, Mafb, and a few other genes, these results indicate that Zfp92 contributes in only a modest way to gene expression in adult islets.


Fig 4. RNA-seq analysis of islets from Zfp92 KOs shows an increase in Capn11 and a decrease in Mafb gene expression.

A) Volcano plot showing differentially expressed genes (Log2Fold Change (FC) over padj-value) in Zfp92 KO vs WT islets from 15 week-old male mice (N = 4). The top 10 differentially expressed genes (based on padj-value) are indicated by names and total numbers of downregulated (green) and upregulated (red) genes are provided (padj<0.05). B) Heat map showing clustering of the top variant genes (based on p-value) dysregulated in Zfp92 KO vs WT islets. C. RT-qPCR analysis of RNA expression for select genes in islet RNA samples collected from 15 week-old male mice. Zfp92 wild type (WT), and knockout (KO) samples. N = 4, error bars: ± SEM. ***p≤0.001; *p≤0.05. p-value is determined by an unpaired t-test.


Blood glucose and Mafb expression are decreased in Zfp92 KO mice at P1

In mice, the transcription factor Mafb is critical for the terminal differentiation of β cells during development through regulation of key β-cell genes. After birth, the function of Mafb in β-cells is largely replaced by Mafa, a closely related transcription factor [35]. Indeed, pancreas-specific Mafb KO mice display deficiencies in β-cell development and associated increased blood glucose levels at birth, but these defects are resolved by three weeks of age due to increased Mafa expression [36]. To determine whether the absence of Zfp92 and related decrease in Mafb expression affects early endocrine development, we analyzed blood glucose levels and gene expression in the pancreata of postnatal mice at P1 (postnatal day 1) (Fig 5A and 5B). We observed an increase in blood glucose concentration and a decrease in expression of Mafb and insulin (Ins1) at P1 in KO mouse samples (Fig 5A and 5B). These results indicate that pancreatic β-cell development is compromised in the absence of Zfp92 due to its effect on Mafb expression. As in adult islets, there was also a very strong increase in Capn11 expression in one day old Zfp92 KO neonates (Fig 5B). To confirm that ZFP92 regulates Mafb, we overexpressed Zfp92 in MIN6 cells, a mouse β-cell line, and observed a strong increase in Mafb expression. In addition, the expression of Ins1 and Slc2a2, two Mafb target genes [37], was also increased. These data all point to ZFP92 functioning as a positive regulator of Mafb expression.


Fig 5. Zfp92 KO mice have increased blood glucose and decreased Mafb and insulin expression at P1.

A) Random fed blood glucose concentration measurements in wild type (WT) and Zfp92 knockout (KO) animals show increased blood glucose levels in KO pups at P1 (N = 11,12). B) RT-qPCR analysis of mRNA expression for select genes in pancreatic RNA samples collected from newborn pups (P1). Zfp92 wild type (WT), and knockout (KO) samples (N = 5). C) RT-qPCR analysis of mRNA expression for select genes in MIN6 mouse β-cell line that was infected with lentivirus to overexpress Zfp92 (Zfp92-OE) and control cells (WT) (N = 6). The samples where Zfp92 was increased >10 times are shaded light blue. Error bars: ± SEM. **p≤0.01; *p≤0.05. p-value is determined by an unpaired t-test.


De-repression of an IAPez transposable retroelement in intron 3 of Capn11 in the absence of Zfp92

The striking increase in Capn11 gene expression in Zfp92 KOs prompted us to examine the alignment of RNA-seq reads in relation to the Capn11 gene. We observed an increase in mRNA reads in Zfp92 KO samples that maps to a location more than 10 kb downstream from the Capn11 transcription start site, with exon alignments starting only from exon 4 (Fig 6). Notably, there is an increase in expressed reads present in intron 3 preceding exon 4. Examination of RepeatMasker annotation revealed that these reads align with an IAPez TE consisting of IAPLTR1-Mm1 and IAPez-int repeating elements (ERVK family; LTR class) and adjacent small SINE repetitive elements (B1_mus2 and B1Mus_1, B3A, PB1D10; B1/Alu and B2 families; SINE class). Intracisternal A particles (IAPs) are LTR-containing ERV sequences belonging to an active class of TEs that can compromise genomic integrity and affect genome regulation by providing cis-regulatory modules [38]. Considering that many KRAB-ZFPs are linked to repression of TEs, these data suggest that ZFP92 functions to repress TEs within the intron 3 of Capn11 gene on chromosome 17 in mice. In the absence of Zfp92, the IAPez retroelement is re-activated and this, in turn, results in the marked expression of downstream Capn11 gene sequences. Since our qPCR primers for Capn11 were designed to amplify exons 4 and 5, we were able to detect a strong increase in Capn11 expression in Zfp92 KO mice (Figs 4C and 5B). RT-qPCR with primers designed to amplify exons 1–2 of Capn11 gene did not yield any product in islet samples, confirming that Capn11 gene is activated only downstream of IAPez insertion. To investigate whether IAPez-driven Capn11 expression is de-repressed in other tissues besides pancreatic islets, we performed RT-qPCR on RNA from WT and KO samples from whole pancreas, brain, lung, muscle, intestine testis, and liver (S3 Fig). These results show that while IAPez-driven Capn11 expression is increased to varying degrees in multiple tissues, the largest increase is in pancreatic islets, indicating that Zfp92 represses Capn11 IAPez activity in a cell type-specific manner. Further, to assess changes in global IAPez expression, we designed primers along different regions of IAPez from Capn11 locus (S4A Fig). RT-qPCR analysis with these primers on islet RNA samples did not reveal any differences in expression between WT and KO samples (S4B Fig), suggesting that ZFP92 represses IAPez in a genomic region-specific manner.


Fig 6. IAPez ERVK LTR retroelement in Capn11 gene intron 3 is de-repressed in Zfp92 KO islets.

UCSC Genome Browser view of Capn11 gene region on the mouse chromosome 17 (GRCm38/mm10 assembly). Alignments of RNA-seq sequenced reads for the representative WT (blue) and Zfp92 KO (red) islet samples are displayed by density graphs and show a strong increase in expressed reads in intron 3 of Capn11 gene (encoded on the opposite DNA strand) and in further downstream exons of Capn11. Full view of RepeatMasker tracks shows that this region is occupied by IAPez ERV consisting of IAPLTR1, IAPez-int repeat elements (ERVK family, LTR class) and adjacent B1_Mus1 Alu-repeat SINE element that appear to be expressed and therefore de-repressed in Zfp92 KO islets. Capn11 gene exons are shaded in light gray, SINE element—light orange, IAPez-int element—light green.


Zfp92 KO-activated IAPez LTR and B1/Alu SINE retroelements form a fusion gene transcript with Capn11 gene

To further define how re-activation of an IAPez TE in Zfp92 KO mice drives the expression of Capn11 mRNA, we performed rapid amplification of 5’ cDNA ends (5’-RACE) on RNA from WT and KO islet samples using reverse primers in exon 5 of Capn11 gene (Fig 7A). While the WT samples did not yield specific PCR products, the KO sample yielded a 1538 bp product that contained a portion of IAPez and immediately adjacent B1/Alu SINE transposable elements that are then spliced to the exon 4 and 5 of Capn11 gene (Fig 7A). These data indicate that ZFP92 represses these TEs in Capn11 locus and, in the absence of this KRAB-ZFP, the IAPez element is activated and acts as a novel promoter region that drives the expression of a fusion TE-Capn11 transcript. The full-length TE-Capn11 transcript contains an open reading frame for an N-terminally truncated 481 aa form of CAPN11 protein (Fig 7B), however, we were unable to detect any specific protein bands by Western blots with antibodies raised against human CAPN11 gene (S5 Fig). These data suggest that ZFP92 binds to the TEs in intron 3 of Capn11 gene, producing a repressive chromatin environment that blocks IAPez expression. In the absence of Zfp92, the IAPez is de-repressed and serves as an alternative promoter that drives transcription of a novel IAPez-Capn11 transcript.


Fig 7. De-repressed IAPez LTR retroelement sequences drive the expression of a fusion TE-Capn11 transcript in Zfp92 KOs.

A) 5’-RACE analysis of mRNA from Zfp92 KO islet sample revealed the production of a TE-Capn11 fusion transcript when the IAPez ERVK LTR element is derepressed. The panel shows a schematic representation of Capn11 gene (blue) and a relative location of B1 SINE (light green) and IAPez ERVK LTR (tan) TEs within the Capn11 intron 3, location of 5’ RACE primers (blue arrowheads), schematic, and the sequence of obtained 5’RACE product that represents fusion transcript. The IAPez-derived sequence is highlighted in tan, B1 SINE-derived sequence–in light green and a Capn11 downstream exon sequence—in blue. ZFP92 binding sequence is in red font. B) Structure of the full-length CAPN11 and N-terminally truncated CAPN11 protein that is encoded by the open reading frame within the TE-Capn11 fusion transcript.


Dysregulation of LINEs and LTR elements in Zfp92 KO islets

To determine whether Zfp92 influences the expression of additional TE elements we re-analyzed islet RNA-seq data by using the TE database and randomly assigning multi-mapped reads. To quantify the findings, we performed differential expression (DE) analysis both on a global and individual chromosome basis. The global DE analysis suggests that expression of 11 TEs is altered (padj<0.1). Among them, RLTR44B showed the largest increase (S6A Fig and S3 Table). However, similar to our qPCR results, there is no change in expression of IAPez TEs at a global level. Considering the very few changes in TE expression and that TE dysregulation might be locus dependent (like the IAPez in Capn11 locus) we also performed DE analysis at the chromosomal level. These results revealed significant changes in expression of 25 TEs, including ERVs and LINE elements, with the top dysregulated TEs all belonging to ERVK (or ERV2) family of LTR retrotransposons (Fig 8A and S3 Table). Specifically, reads attributable to RLTR44 ERVK-related sequences (RLTR44C, RLTR44-int, RLTR44B) on chromosomes 9 and 2 showed high increases. At the same time, most downregulated TEs were also from the ERVK family including RLTR19C and IAPEy-int elements on chromosomes Y and 4, respectively. Manual inspection of the read alignments for selected individual RLTR44 TEs on chromosome 9 and RLTR19C TE on chromosome Y confirmed respective strong increase or decrease in mapped reads at unique locations (Fig 8B). However, many other retroelements of the same kind in other locations on the same or different chromosomes either did not have any expressed reads or did not show any visible change in expression (S6B Fig). These results indicate that in the absence of Zfp92, there is a genome-wide dysregulation of retroelements and that their expression varies both by the specific retroelement and by the genomic context of the retroelement.


Fig 8. RNA-seq analysis against the TE database shows dysregulation of LINE and LTR retroelements in Zfp92 KO islets.

A) Volcano plot showing differentially expressed TEs in Zfp92 KO vs WT islets collected from 15 week-old male mice (N = 4). RNA-seq read alignment was done by using random assignment of multi-mapped reads to the TE database (RepeatMasker annotations) and differential expression analysis was done for each individual chromosome separately. The volcano plot only shows the TEs whose expression was significantly changed (FDR padj-value <0.1). TEs are labeled by name:family:class and chromosome (Ch) for which differential expression was identified. Top differentially expressed TEs with Log2(Fold Change) higher than 2 are labeled in red. B) UCSC Genome Browser view of representative top upregulated (RLTR44C) and downregulated (RLTR19B) TEs on the mouse chromosomes 9 and Y, respectively (GRCm38/mm10 assembly). Alignments of RNA-seq sequenced reads for the representative WT (blue) and Zfp92 KO (red) islet samples are displayed by density graphs.


Genome-wide analysis of ZFP92 binding reveals that ZFP92 preferentially binds to B1/Alu SINE elements

To identify binding sites for ZFP92 we performed CUT&RUN (Cleavage Under Targets & Release Using Nuclease) experiments on MIN6 cells overexpressing HA-tagged ZFP92 protein. Next generation sequencing and data analysis of the resulting chromatin fragments revealed more than 500 ZFP92 binding peaks (q value<0.05). These peaks were further analyzed to determine whether they contain TEs, other genomic features, or ENCODE Candidate Cis-Regulatory Elements (cCREs) [39] (Fig 9A–9C and S4 Table). We found that 93% of the ZFP92-bound peaks contained one or more TEs with SINE elements being the most common (39%), followed by LINE elements (16%), LTR class (15%) of retroelements, and simple repeats (13%). Within the SINE element-bound peaks, the majority (53%) contained B1 type of Alu family of SINEs (Fig 9A). Enrichment analysis of specific TE classes and families in binding sites relative to their genomic distribution showed that SINE elements are the most enriched class (5.2 FoldChange (FC)), followed by DNA elements (2.2 FC) and LTR elements (1.2 FC), while LINE elements show negative enrichment (0.8 FC). Among the families of TEs, the most highly enriched families are B1/Alu (8.2 FC), B4 (4.6 FC) and MIR (3.1 FC) SINE elements (S4 Table). Notably, many of the ZFP92-bound peaks are located in gene-rich regions, with 40% of the peaks located within gene introns, 9% within exons, 6% within extended gene promoters, and 1% within 3’-UTRs (Fig 9B). Moreover, almost 13% of ZFP92-bound peaks contain distal enhancers, 5.5% proximal enhancers and 1% CTCF sites (Fig 9C). Importantly, one of the most enriched ZFP92 binding peaks is in the Capn11 gene intron 3, with the summit of ZFP92 binding peak being located over the B1/Alu SINE element adjacent to the IAPez element (Fig 9D). The peak extends further into IAPez element that becomes re-activated in the absence of ZFP92. qPCR of chromatin from independent ZFP92 CUT&RUN pulldowns with primer pairs specific to different regions under the ZFP92 peak showed the strongest enrichment for the Capn11 intron and B1 element, with less enrichment for IAPLTR, and no enrichment for the IAPez body (IAP1), confirming our chromatin sequencing data (Fig 9D and 9E).


Fig 9. Genome-wide analysis reveals ZFP92 binds preferentially to B1/Alu SINE elements.

A) Pie chart showing the percentage distribution of different TE classes within the ZFP92 binding peaks obtained by CUT&RUN analysis. 93% of peaks have TEs with SINE elements being the largest group. The inset pie chart shows the family distribution of ZFP92-bound SINEs, with Alu/B1 family being most represented. B) Pie chart showing the distribution of ZFP92 binding peaks within different genomic features. C) Pie chart showing the distribution of different ENCODE Candidate Cis-Regulatory Elements (cCREs) within the ZFP92 binding peaks. enhD, distal enhancer signature; enhP, proximal enhancer-like signature; prom, promoter-like signature; CTCF, CTCF-only; K4m3, DNase-H3K4me3. D) UCSC Genome Browser view of Capn11 locus showing ZFP92 binding peaks and RNA-seq reads in WT and Zfp92 KO samples (GRCm38/mm10 assembly). The main peak containing the B1 SINE element is highlighted in gray, with red lines denoting amplicons and primer pairs that were used for qPCR shown in (E). E) qPCR on CUT&RUN chromatin samples with the primers shown in (D) to different regions of Capn11 locus and TE elements found there. (N = 3) Error bars: ± SEM. **p≤0.01; *p≤0.05. p-value is determined by an unpaired t-test. F) ZFP92 binding motif predicted by MEME analysis of ZFP92 binding peaks. Under the ZFP92 motif are the two similar motifs (ZNF460 and ZNF135) that were identified by TomTom analysis from the MEME suite. G) Pie chart showing the distribution of ZFP92 binding motif within TE elements in ZFP92 peaks. The inset pie chart shows the family distribution of SINEs with FP92 motif, with Alu/B1 family being most represented.


We next used the MEME motif-discovery tool to analyze the ZFP92 peaks that revealed a 28 bp consensus ZFP92 binding sequence (Fig 9F). Comparison of the consensus ZFP92 binding motif with those predicted based on the protein sequence of ZFP92 [40] shows only minimal similarities within repeated ‘GAG’ sequences (S7A Fig) highlighting limitations of the latter approach. BLAST alignment search of ZFP92 motif against Dfam TE database [41] retrieved matches to a part of B1 Alu elements, further suggesting that these elements are the main target of ZFP92. Comparison of the ZFP92 binding motif against a database of known motifs revealed similarities to binding motifs for ZNP460 and ZNF135 (Fig 9F), two human KRAB-ZFPs that bind to SINE elements [24]. Moreover, 67% of ZFP92 binding motifs in ZFP92 peaks occur within SINEs, of which 76% are in B1/Alu elements, 17% in B4 elements and 7% in B2 elements (Fig 9G). The ZFP92 binding site is also found in 14% of LTR elements and 12% of LINE elements (Fig 9G and S7B Fig) indicating that SINE-derived sequences are present in some of these elements as well. Inspection of the RNA-seq tracks that span SINE element-specific ZFP92 peaks shows that expected de-repression of SINEs in Zfp92 KO samples does not lead to an increase in transcription of SINEs. Similarly, neighboring LINE and LTR elements are also often not de-repressed (S8A Fig). However, the absence of Zfp92 causes some LTR elements to be de-repressed in a context-dependent manner, such as in the Capn11 locus (Fig 9D) and a few other loci (S8B Fig). These observations confirm our RNA-seq analysis of TE expression highlighting the locus-dependent nature of TE dysregulation in the absence of Zfp92.

Combined, our chromatin binding data indicate that ZFP92 binds to multiple TE elements with preferential binding to B1/Alu SINE elements. In the absence of Zfp92, chromatin changes may lead to de-repression of select retroelements in a locus-dependent manner. The ZFP92 binding peaks and corresponding TEs are often found within the gene bodies and may contain regulatory elements, indicating that ZFP92 might function not only as a repressor of TEs but as a potential regulator of gene transcription.

ZFP92 binds within and affects the expression of Sox17 and Acacb genes

Strong ZFP92 binding peaks were identified within the Sox17 and Acacb genes (S4 Table). To determine the potential significance of these bindings we further investigated both genes. Sox17 encodes a transcription factor that is important for early endoderm, vascular and hematopoietic cell development [42]. While Sox17 is expressed in islets at low levels, RNA-seq did not show any difference in total mRNA expression between WT or KO islets (S2 Table). The ZFP92 binding peak in Sox17 is located within the exon 4 and an alternative second promoter region that was shown to drive the expression of the short form of Sox17 mRNA containing only the extended exon 4 and exon 5 [43] (Fig 10A and 10B). To determine whether binding of ZFP92 to this region may affect expression of different Sox17 mRNA forms, we performed RT-qPCR on mRNA from WT and Zfp92 KO lung and testes, tissues where Sox17 is expressed at high levels in adult animals. This experiment revealed an increase in expression of the short Sox17 form in Zfp92 KO tissues with no change in expression of the long Sox17 form that contains exons 1 through 5 (Fig 10C), suggesting that ZFP92 represses expression of the short form of Sox17. Although there are no TEs recognized by the Repeat Masker within the Sox17 ZFP92 binding peak, there is a stretch of sequence (GAGGCAGG) within the extended exon 4 that is part of the identified putative ZFP92 binding sequence. In addition, a second strong ZFP92 binding peak is located 128 kb upstream of the Sox17 gene (Fig 10D). This second peak is located within conserved sequences that may be involved in formation of regulatory chromatin loop with the ZFP92-bound alternative Sox17 promoter, further suggesting a yet-to-be-defined regulatory function for ZFP92.


Fig 10. ZFP92 binds within the Sox17 locus and may regulate expression of the short form of Sox17 mRNA.

A) UCSC Genome Browser view of Sox17 locus showing ZFP92 CUT&RUN binding peak and RNA-seq reads for mRNA expression in WT and Zfp92 KO samples in Sox17 locus. The peak is highlighted in gray and covers the extended Sox17 exon 4, the boundary of which is indicated by the dashed blue line defined by the transcription start site for the short Sox17 isoform (TSS Sox17-1), and an alternative Sox17 promoter preceding it. TSS for Sox17 short (Sox17-1) and long (Sox17-2) isoforms are from the Promoters from the EPD track in the UCSC browser (GRCm38/mm10 assembly). B) qPCR on CUT&RUN chromatin samples with the primers for the Sox17 peak (extended Sox17 exon 4) shows strong enrichment at the locus. (N = 3) Error bars: ± SEM. **p≤0.01; *p≤0.05. p-value is determined by an unpaired t-test. C) RT-qPCR analysis of different Sox17 isoforms expression in testes and lung tissues of WT and Zfp92 KO mice shows an increased expression of the short Sox17 isoform. Primers specific to extended exon 4 amplify the short Sox17 isoform (short), exons 1,2 –long Sox17 isoform (long), and exons 4,5 –both isoforms (both). (N = 3) Error bars: ± SEM. **p≤0.01; *p≤0.05. p-value is determined by an unpaired t-test. D) UCSC Genome Browser view of Sox17 locus showing two distant ZFP92 binding peaks in Sox17 locus. The peaks are highlighted in gray, the distal peak is located -128kb upstream of the main peak within extended Sox17 exon 4 and lies within a conserved DNA sequence that contains a distal enhancer signature (cCRE track) (GRCm38/mm10 assembly).


Another strong ZFP92 binding peak was identified in an intron of Acacb (Fig 11A) that coincides with a PB1D10 B1/Alu SINE element, an overlapping MT2B2 LTR element, and an L1 LINE element (S7A Fig). While we did not observe significant differences in Acacb expression in islets (S2 Table), where it expressed at very low levels, there was an observable decrease in RNA-seq aligned reads for exons surrounding the ZFP92-bound region in the Zfp92 KO sample (Fig 11A). Acacb encodes acetyl coenzyme A carboxylase β, the rate-limiting enzyme in fatty acid β-oxidation, and a decrease in Acacb expression is associated with increased lipolysis and insulin sensitivity [44]. Since our physiological studies revealed sex-based differences in fat accumulation and insulin sensitivity in mice fed a HFD, we explored whether they could be due to changes in Acacb expression by analyzing mRNA from WT and KO male and female mice from three tissues associated with body fat metabolism and insulin sensitivity: white adipose, muscle, and liver. RT-qPCR with primers to the Acacb exons surrounding the ZFP92 peak showed a decrease in expression of Acacb mRNA in adipose and muscle tissues from male Zfp92 KO but not in female KO tissues (Fig 11B). These results indicate that in the absence Zfp92 there is a decrease in expression of Acacb in males that may have contributed to the observed increased insulin sensitivity in Zfp92 KO male mice and higher fat accumulation in KO female mice on a HFD.


Fig 11. ZFP92 binds a B1/Alu SINE element within the Acacb locus and affects the expression of Acacb mRNA in adipose and muscle tissues of male mice.

A) UCSC Genome Browser view of Acacb locus showing ZFP92 CUT&RUN binding peak and RNA-seq reads for mRNA expression in WT and Zfp92 KO samples in Acacb locus. The peak is highlighted in gray and contains B1/Alu SINE, as well as LINE and LTR elements (see S7 Fig for a close up). The expression levels of exons surrounding the ZFP92 binding site (arrows) appear to be reduced. B) RT-qPCR analysis of Acacb mRNA expression in adipose, muscle and liver tissues from male and female WT and Zfp92 KO mice. Decreased expression of Acacb is observed in Zfp92 KO male adipose and muscle tissues. (N = 3,4) Error bars: ± SEM. **p≤0.01; *p≤0.05. p-value is determined by an unpaired t-test.



In this study, we show that Zfp92, a gene encoding KRAB-ZFP that is highly expressed in mouse pancreatic islets, preferentially binds to B1 SINE transposable elements, and is involved in regulation of other nearby retroelements activity and gene expression, including the expression of endocrine cell-defining transcription factor Mafb in islets and a regulator of fat metabolism Acacb in adipose and muscle tissues.

Murine Zfp92 is located on the X chromosome and exhibits relatively high sequence conservation among placental mammals where 69 out of 89 (or 77%) of placental mammals have a Zfp92 ortholog (ensembl.org). Mouse ZFP92 protein is 61.8% identical to its human ortholog that is also located on the X chromosome. Alignment of ten ZFP92 ortholog proteins from species representing different mammalian branches shows that the first 8 zinc fingers are well conserved with the 9th zinc finger showing more variation and being conserved only in rodents (S9 Fig). Our qPCR data and as well as Tabula Muris scRNA-seq data indicate that mouse Zfp92 is highly expressed in pancreatic endocrine islet cells, with lower levels expressed in brain, testis, and intestinal tissues. In contrast, gene expression data for human ZFP92 from the GTEx portal indicate that its expression is higher in ovary, uterus, brain, lung, and adipose tissues. The different expression patterns suggest that, despite the conservation of amino acid sequence, the mouse and human genes have diverged in terms of their tissue expression patterns. This may reflect divergence in their function, especially with respect to the species-specific silencing of transposable retroelements. Considering that retroelements have species-specific evolutionary origins, the species-restricted evolutionary divergence in KRAB-ZFP-TE regulatory relationships may affect specific gene regulatory networks and their associated phenotypes in a species-specific manner [24,38,45]. For example, it was recently shown that LINE-element suppressing KRAB-ZFP ZNF528 is expressed in human but not in chimpanzee neural progenitor cells and contributes to human brain function through regulation of mitophagy gene SPATA18 [46]. It is possible, therefore, that ZFP92 has some murine-specific regulatory functions, such as those we identified in pancreatic islets and male adipose tissue.

ZFP92 predominately binds to SINE elements and regulates TE activity

Our chromatin binding and RNA expression data indicate that the main function of mouse ZFP92 is to regulate the activity of specific TEs consistent with an emerging role for KRAB domain containing ZFPs. Most of the binding sites identified for ZFP92 coincide with TEs, with a large proportion of these being B1/Alu type of SINE elements. Mouse B1 SINE elements are ~140 bp in length and like human Alu elements are derived from the signal recognition particle 7SL and contain a promoter for RNA polymerase III-dependent transcription [47]. SINE elements require LINE-encoded proteins for their mobilization, although the SINE retrotransposition rate is estimated to be higher than that of LINEs with some de novo insertions being potentially contributing to disease [48]. There are approximately 500,000 B1/Alu SINEs in the mouse genome that comprise approximately 2.7% of mouse DNA. The majority of B1 SINEs and other TEs are silenced through chromatin repression and DNA methylation by DNA methyltransferases (DNMTs) [49, 50]. However, while KRAB-ZFPs play a vitally important role in repressing TEs, few have been identified that bind to SINE elements. Consistent with ZFP92 preferentially binding to B1/Alu SINE elements, the predicted ZFP92 binding motif is a 28 bp sequence that is highly similar to B1/Alu SINEs. While shorter in length, the predicted binding motifs for ZNF460 and ZNF135, two other KRAB-ZFPs that bind SINEs [24], are very similar to that for ZFP92. Our analysis also revealed that while ZFP92 binds predominately in SINE elements, it sometimes also binds to LINE and LTR TEs, indicating that SINE sequence fragments are present in other TEs and, possibly, other genomic features [51]. Recent studies indicate that SINE sequences within the genome can play important functions such as act as enhancers, promote chromatin compartmentalization, and regulate chromatin accessibility through SINE-KRAB-ZFP interactions [5254].

Interestingly, we did not observe a global increase in SINE expression in Zfp92 KO tissues, suggesting that the absence of ZFP92 alone is not enough to activate the transcription of silenced SINEs. While it is possible that the methods used to construct the library for RNAseq did not capture small SINE transcripts, we did observe the altered expression of several LINE, LTR elements, and genes in the Zfp92 KO mice, indicating significant genomic dysregulation in the absence of ZFP92. The most striking example of such dysregulation is the very strong activation of a novel TE-Capn11 fusion transcript in Zfp92 KO islets due to the activation of an IAPez retroelement located next to the ZFP92-bound B1 SINE element in the 3rd intron of the Capn11 gene. In the absence of Zfp92, the IAPez ERV in this location is activated and serves as an alternative promoter that drives the robust expression of the TE-Capn11 transcript that contains IAPez and SINE sequences that are spliced to the downstream Capn11 exons. This surprising finding provides a very stark example of how de-repression of TEs can lead to creation and strong expression of a brand-new transcript and, potentially, impact cell function. It also indicates that ZFP92 is indeed involved in repressive complexes and its removal leads to chromatin opening and activation of nearby regulatory elements. Interestingly, similar activation of IAPez expression within Capn11 locus was observed in DNA methyltransferase Dnmt1 KO mice [55], further suggesting that ZFP92 is a part of TE repressive complex.

Although the novel TE-Capn11 fusion transcript contains an open reading frame that encodes an N-terminally truncated form of calpain 11, a calcium-dependent protease normally expressed only in adult testis in mice [56], we did not detect any protein product in islets using available antibodies. Despite this, we cannot rule out that the protein can potentially be made in islets or other tissues. While the predicted protein would lack only part of the N-terminal protease domain, so might not be catalytically active, it would still be expected to contain five C-terminal calcium-binding EF-hand domains (Fig 7B). EF-hand domain-containing proteins often act as calcium buffers which control the level of free Ca2+ ions in the cytoplasm [57]. It is possible, therefore, that the TE-Capn11 -transcript-derived CASPN11 protein, even if truncated, could influence function of different tissues. In Zfp92 KO mice, besides being overexpressed in islets, Capn11 fusion transcript is highly expressed in brain, intestine, testis, and liver, suggesting that Zfp92 may regulate the Capn11 IAPez in a tissue-specific manner. Even though the level of Zfp92 expression was low in some of these adult tissues, it may have been expressed in progenitor tissues at some point during development. In the absence of Zfp92, changes in the chromatin environment and de-repression of IAPez during development could lead to continuous overexpression of TE-Capn11 transcript at later stages in these tissues.

Global analysis of TE expression in Zfp92 KOs showed varied increases and decreases in several types of LINE and LTR elements. We also observed that the same types of elements were dysregulated in one position and unchanged in others. Similarly, while some changed elements were in proximity to ZFP92 binding sites, others were not. This suggests that regulation of TEs by ZFP92 is influenced by genomic context, the state of chromatin in the locus, distal chromatin interactions and by chromatin modifying complexes that may interact with this KRAB-ZFP. Indeed, a recent study reports that chromatin modifications affect TE expression in a complex way where not only repressive marks, but widespread marking of TEs by bivalent or activating marks, were shown to influence TE expression and chromatin accessibility. Furthermore, the effects of chromatin modifications are sequence- and context-specific, with different chromatin modifiers regulating the expression and chromatin accessibility of specific subsets of TEs [5860]. For example, different LTR retrotransposons can also be modulated by different chromatin modifying complexes. RLTR44 is upregulated in the absence of Zfp92 and is repressed by the polycomb complex [61] suggesting that ZFP92 associates with polycomb or other repressive complexes to repress RTLR44. On the other hand, several IAPey retroelements are downregulated in the absence of Zfp92. IAPeys are enriched on the Y chromosome and are active in male germline [62,63]. While KRAB-ZFPs are generally considered to be transcriptional repressors, some KRAB-ZFPs activate gene transcription through interaction with activating complexes [64,65]. In any case, our studies of Zfp92 add to the growing evidence that IAPs and other LTR transposons act as cis-modifiers of gene expression and that KRAB-ZFPs regulate them in locus-, tissue-, species-, and strain-specific manners [25,6669].

Role of Zfp92 in islets

The expression of mouse Zfp92 increases during development as endocrine progenitor cells are converted into nascent β-cells, and then is maintained in adult β-cells. Zfp92 KO mice fed a regular diet do not display major abnormalities in pancreatic islet structure, insulin secretion, or β-cell effects on glucose homeostasis. However, we did observe a decrease in fasting blood glucose levels in Zfp92 KO males which may be due to reduced levels of glucagon associated with a decrease expression of Mafb, a transcription factor that is important for islet maturation and function. Indeed, among the very few changes observed in the transcriptome of adult Zfp92 KO islets, there was a verified decrease in Mafb gene expression. The absence of an overt β-cell phenotype in adult Zfp92 KO mice is similar to pancreas-specific Mafb KO mice where only a decrease of glucagon secretion is observed in adult mice [36]. Mafb is highly expressed in progenitor α- and β-cells, is required for β-cell development, becomes largely replaced by Mafa in adult mouse β-cells, and continues to be expressed and regulate glucagon expression in adult α-cells [34,37,70]. Consistent with the role of Mafb during β-cell development, we showed that in the absence of Zfp92, newborn mice have decreased expression of Mafb and Ins1 genes that is accompanied by increased blood glucose levels. Additionally, Zfp92 KO mice exhibit increased fasting blood glucose levels when fed a HFD for 12 weeks, indicating a modest impairment of β-cell function under metabolic stress. Together, these results indicate that Zfp92 contributes to Mafb regulation, both during β-cell development and in adult islets.

The mechanism whereby ZFP92 protein promotes the expression of Mafb is not clear. We observed only weak ZFP92 binding peaks around Mafb promoter although there are several sites of stronger ZFP92 binding within the 20 kb of DNA surrounding Mafb gene that either bind to a TE element or to a partially conserved binding motif sequence (S10 Fig). It is also possible that there is a de-regulation of TEs that are more distal to Mafb gene that are important for the regulation of Mafb in islets. Indeed, several studies have shown that TEs can serve as enhancers, are associated with open chromatin regions, contain transcription factor binding sites, and are involved in cell-type specific chromatin domain organization and gene regulation [7173]. Alternately, the dysregulation of other genes in endocrine cells that are important for Mafb expression could be affected.

Role of Zfp92 in other tissues

While our study began with a focus on pancreatic islets, our physiological studies also revealed a role for Zfp92 in adipose tissue of male mice. Male KO mice on a normal diet grew at a slower rate and exhibited increased insulin sensitivity and body fat content when on a HFD compared to female KO mice. An increase in total body fat is one of the two significant phenotypes reported by the International Mouse Phenotyping Consortium (IMPC) for an independently derived Zfp92 KO allele on different mouse strain (C57Bl/6NJ) [74]. The second significant phenotype described for IMPC Zfp92 KO mice was a decreased bone mineral content, something we did not study.

The sex-specific differences in body fat accumulation and insulin sensitivity in Zfp92 KO mice on a HFD are likely due to sex-specific changes in Acacb gene expression. ZFP92 binds to an array of TE elements that includes B1/Alu SINE element within the intron of Acacb gene and deletion of Zfp92 leads to a male-specific reduction in the expression of Acacb in adipose and muscle tissue. By catalyzing synthesis of malonyl-CoA, an inhibitor of rate-limiting step in fatty acid uptake and oxidation, ACACB is thought to be a key regulator of fatty acid oxidation [75,76]. Global deletion of Acacb in mice leads to decreased fat accumulation and increased insulin sensitivity due to increased fat metabolism in muscle and adipose tissues [77, 78]. The Zfp92-dependent reduction of Acacb only in males in our study may explain the greater fat accumulation in KO females and increased insulin sensitivity in male KO mice fed a HFD. The mechanisms responsible for the sex-specific regulation of Acacb are not clear, although Acacb was previously shown to be more highly expressed in female liver [79] and hypothalamus [80]. Interestingly, in humans a strong QTL influencing increased percent body fat specifically in women is located on chromosome 12q (12q24.3–12q24.32) near ACACB [81], further suggesting sex-specific differences in the expression or function of this gene.

In this study, we also showed that ZFP92 is involved in regulation of expression of essential transcription factor Sox17 [82]. We have previously shown that during early development Sox17 is expressed in two distinct progenitor cell populations, endodermal and hemogenic endothelial cells, that preferentially express short or long Sox17 RNA forms driven by two different promoters [43,44]. We discovered that ZFP92 binds to the promoter region for the short RNA form that, in the absence of Zfp92, is upregulated in adult lung and testis tissues. We also identified a distal site upstream of Sox17 that is bound by ZFP92. Additional studies are necessary to determine whether either of these two binding sites has effects on the development of endodermal, vascular, or other lineages that express Sox17.

Finally, while we only studied gene and TE expression differences for selected genes and tissues, it is possible that genome-wide chromatin dysregulation due to the lack of Zfp92 may impact other genes, tissues, and developmental processes. However, the observed mild phenotype of Zfp92 KO mice indicates that there’s a redundancy among KRAB-ZFPs targeting different TEs. Indeed, mice in which an entire cluster of KRAB-ZFPs is deleted are viable and relatively normal [23].


Mouse lines and husbandry

Zfp92 KO mice were derived using CRISPR/Cas as previously described [31]. Briefly, guide RNAs (gRNAs) were microinjected into Cas9-expressing embryos heterozygous B6J/129(Cg)-Gt(ROSA)26Sortm1.1(CAG-cas9*, -EGFP)Fezh/J mice (JAX 026179) by the Vanderbilt Genome Editing Resource. Founder animals were then backcrossed to C57Bl/6J mice for 7 generations, segregating the Cas9-expressing ROSA26 allele in the process. Pups were genotyped by PCR using primers surrounding the deletion site (S1 Table).


The quality of RNA samples was assessed using an Agilent 2100 Bioanalyzer. Only those samples with an RNA integrity number (RIN) 7 or above were used for sequencing. cDNA libraries were constructed using the Low Input Library Prep Kit pipeline. An Illumina NovaSeq6000 instrument at Novogene Corp was used to produce paired-end, 150 nucleotide reads for each RNA sample. Paired-end sequencing produced approximately 55 million reads per sample, which were processed utilizing Trim Galore 0.5.0 (which relies on Cutadapt 1.18) to remove adapter sequences and pairs that were either shorter than 20 bp or that had Phred scores less than 20. The Spliced Transcripts Alignment to a Reference (STAR v2.6.0c) application [83] was used to perform sequence alignments to the mm10 (GRCm38) mouse genome reference and GENCODE comprehensive gene annotations (Release M17). STAR’s two-pass mapping approach was used to increase the detection of reads mapping to novel junctions identified during the first mapping pass. Overall, approximately 85–87% of the raw sequencing reads were uniquely mapped to genomic sites. For additional sample-level quality control analysis and downstream pairwise comparisons, DESeq2 was employed [84]. For the analysis of TEs, the parameters for STAR were modified to account for the more complex TE content in mice by allowing a higher number of multi-mapped reads [85] (S1 Method). The alignments were then analyzed using the count feature of TE transcripts [86]. In addition, TE annotations were extracted from the UCSC Genome Browser’s RepeatMasker-generated RMSK track [87] which enabled the screening of DNA sequences enriched in interspersed repeats and low complexity DNA sequences. While alignments were run on the entire genome, the TE mapping and read counting were performed both on the whole genome and on a per-chromosome basis. DESEq2 was used for downstream pairwise comparisons. All data processing was performed at the Advanced Computing Center for Research and Education (ACCRE) at Vanderbilt University.

Identification of ZFP92 binding sites

HA-ZFP92 lentivirus-infected MIN6 cells were trypsinized and washed 2 times with 1%BSA in PBS solution (150 x 103 cells were used per pull-down). The CUT&RUN (Cleavage Under Targets and Release Using Nuclease) assay was performed by using the CUT&RUN Assay KIT (#86652 Cell Signaling Technology) following the manufacturer’s protocol. For anti-HA-ZFP92 pulldowns from MIN6 cells, rabbit anti-HA antibodies (#3724) and normal rabbit control IgGs from the kit were used (all antibodies are from Cell Signaling). Briefly, buffer-washed cells were bound to Concanavalin A-coated magnetic beads, permeabilized with 0.05% digitonin buffer, incubated with antibodies at 4°C overnight, washed twice with digitonin buffer, and incubated with Protein A-MNase (pA-MN) for 1 hour at 4°C. After two washes, cell-bound beads were incubated for 30 min at 4°C in 2 mM CaCl2 for pA-MN digestion, then incubated with RNAse-containing Stop Buffer (30 min. at 37°C) to release DNA. DNA was further purified using spin columns (14209S, Cell Signaling) and directly used for library prep or qPCR. For sequencing, DNA was processed through the ChIP-seq library prep and Illumina NovaSeq6000 PE150 next-generation sequencing pipeline at Novogene Corporation. The sequencing reads were processed with nf-core/cutandrun version 3.0 [88,89], which is an analysis pipeline for CUT&RUN experiments built using Nextflow for portability and reproducibility. FastQC was used for sequencing quality control reporting and Trim Galore for adapter trimming and to remove low quality reads. Bowtie2 [90] was used for DNA alignment against the UCSC mm10 mouse genome reference and gene annotations. Samtools [91] was then used to filter on quality, sort, and index alignments, followed by duplicate removal by Picard [92]. Peak calling was performed with MACS2 [93]. To quantify the frequency of classes and families of repeat elements across the genome, we calculated the total genomic length of each element from the coordinate data available from the RMSK track [87] and aggregated these either by class or family, then divided by the genome length to obtain a coverage ratio. Then, to determine enrichment of such elements within the CUT&RUN peaks, we matched repeat elements to the coordinate regions of the peaks and then aggregated these to determine enrichment frequency. The MEME,TomTom and FIMO tools within the MEME suit were used for the de novo prediction of the ZFP92 binding motif within ZFP92-bound peaks, comparison of the ZFP92 motif against a database of known motifs and finding occurrences of the ZFP92 binding motif within the peak TEs, respectively [94].

Immunofluorescent staining

Whole pancreata were fixed for 4 hours in 4% paraformaldehyde, incubated overnight at 4°C in 30% sucrose, embedded in OCT compound (Tissue Tek), frozen on dry ice, and sectioned at a depth of 8 μm. The staining was performed following standard procedure as previously described [95]. Two primary antibodies were used, a guinea pig anti-insulin (ThermoFisher, 1:1000) and a rabbit anti-glucagon (Linco, 1:1000). Two secondary antibodies used were a donkey anti-rabbit IgG Alexa-488 conjugated and donkey anti-guinea pig IgG Alexa-555 conjugated (ThermoFisher,1:1000). After antibody staining, slides were mounted with Invitrogen ProLong Gold antifade reagent with DAPI (ThermoFisher). Images were acquired using Aperio ScanScope CS imaging system. Quantifications of cell area were done on evenly spaced pancreatic sections at 150 μm apart. Relative β-cell (insulin+) and α-cell (glucagon+) areas were calculated by dividing the area of hormone+ cells by that of the whole pancreas (DAPI+). The images shown are representative of the phenotype observed in at least three different animals per genotype.

Supporting information

S7 Fig. Analysis of ZFP92 binding motif.

A) Comparison of consensus ZPF92 binding motif (top) predicted by MEME analysis of ZFP92 CUT&RUN peaks with computational predictions of ZFP92 binding site based on the protein sequence at http://zf.princeton.edu/. The sequences from top to bottom are predicted with expanded linear svm, polynomial svm, and B1H algorithms, respectively. Shaded boxes denote similarities with tandem GGAG and GAGG sequences. B) Pie charts show the family distribution of LINE, LTR and DNA elements (Fig 9G) containing ZFP92 binding motif.



S8 Fig. ZFP92 binding within different loci and its differential effect on LTR TE expression.

A) UCSC Genome Browser view of Acacb locus showing ZFP92 CUT&RUN binding peak and RNA-seq reads for mRNA expression in WT and Zfp92 KO samples (zoomed out view in Fig 11A). Repeat masker and cCRE tracks show ZFP92-bound SINE, LINE, and LTR TEs and nearby distal enhancer. No expression of ZFP92-bound TE elements is detected in Zfp92 KOs. B) UCSC Genome Browser view of Il1r locus showing ZFP92 CUT&RUN binding peak and RNA-seq reads for mRNA expression in WT and Zfp92 KO. Repeat masker and cCRE tracks show ZFP92-bound LTR TE and nearby distal enhancer. The expression of the ZFP92-bound LTR element is increased in Zfp92 KOs (GRCm38/mm10 assembly).




  1. 1.
    Klug A. The discovery of zinc fingers and their development for practical applications in gene regulation and genome manipulation. Q Rev Biophys. 2010;43(1):1–21. pmid:20478078
  2. 2.
    Lambert SA, Jolma A, Campitelli LF, Das PK, Yin Y, Albu M, et al. The Human Transcription Factors. Cell. 2018;172(4):650–65. pmid:29425488
  3. 3.
    Vilas CK, Emery LE, Denchi EL, Miller KM. Caught with One’s Zinc Fingers in the Genome Integrity Cookie Jar. Trends Genet. 2018;34(4):313–25. pmid:29370947
  4. 4.
    Pabo CO, Peisach E, Grant RA. Design and selection of novel Cys2His2 zinc finger proteins. Annu Rev Biochem. 2001;70:313–40. pmid:11395410
  5. 5.
    Fedotova AA, Bonchuk AN, Mogila VA, Georgiev PG. C2H2 Zinc Finger Proteins: The Largest but Poorly Explored Family of Higher Eukaryotic Transcription Factors. Acta Naturae. 2017;9(2):47–58. pmid:28740726
  6. 6.
    Emerson RO, Thomas JH. Adaptive evolution in zinc finger transcription factors. PLoS Genet. 2009;5(1):e1000325. pmid:19119423
  7. 7.
    Mackeh R, Marr AK, Fadda A, Kino T. C2H2-Type Zinc Finger Proteins: Evolutionarily Old and New Partners of the Nuclear Hormone Receptors. Nucl Recept Signal. 2018;15:1550762918801071. pmid:30718982
  8. 8.
    Cheng CT, Kuo CY, Ann DK. KAPtain in charge of multiple missions: Emerging roles of KAP1. World J Biol Chem. 2014;5(3):308–20. pmid:25225599
  9. 9.
    Ecco G, Imbeault M, Trono D. KRAB zinc finger proteins. Development. 2017;144(15):2719–29. pmid:28765213
  10. 10.
    Lupo A, Cesaro E, Montano G, Zurlo D, Izzo P, Costanzo P. KRAB-Zinc Finger Proteins: A Repressor Family Displaying Multiple Biological Functions. Curr Genomics. 2013;14(4):268–78. pmid:24294107
  11. 11.
    Schmitges FW, Radovani E, Najafabadi HS, Barazandeh M, Campitelli LF, Yin Y, et al. Multiparameter functional diversity of human C2H2 zinc finger proteins. Genome Res. 2016;26(12):1742–52. pmid:27852650
  12. 12.
    Yang P, Wang Y, Macfarlan TS. The Role of KRAB-ZFPs in Transposable Element Repression and Mammalian Evolution. Trends Genet. 2017;33(11):871–81. pmid:28935117
  13. 13.
    Najafabadi HS, Mnaimneh S, Schmitges FW, Garton M, Lam KN, Yang A, et al. C2H2 zinc finger proteins greatly expand the human regulatory lexicon. Nat Biotechnol. 2015;33(5):555–62. pmid:25690854
  14. 14.
    de Koning AP, Gu W, Castoe TA, Batzer MA, Pollock DD. Repetitive elements may comprise over two-thirds of the human genome. PLoS Genet. 2011;7(12):e1002384. pmid:22144907
  15. 15.
    Sundaram V, Wysocka J. Transposable elements as a potent source of diverse cis-regulatory sequences in mammalian genomes. Philos Trans R Soc Lond B Biol Sci. 2020;375(1795):20190347. pmid:32075564
  16. 16.
    Chuong EB, Elde NC, Feschotte C. Regulatory activities of transposable elements: from conflicts to benefits. Nat Rev Genet. 2017;18(2):71–86. pmid:27867194
  17. 17.
    Wicker T, Sabot F, Hua-Van A, Bennetzen JL, Capy P, Chalhoub B, et al. A unified classification system for eukaryotic transposable elements. Nat Rev Genet. 2007;8(12):973–82. pmid:17984973
  18. 18.
    Stocking C, Kozak CA. Murine endogenous retroviruses. Cell Mol Life Sci. 2008;65(21):3383–98. pmid:18818872
  19. 19.
    Singh SK. Endogenous retroviruses: suspects in the disease world. Future Microbiol. 2007;2(3):269–75. pmid:17661701
  20. 20.
    Weiss RA. Human endogenous retroviruses: friend or foe? APMIS. 2016;124(1–2):4–10. pmid:26818257
  21. 21.
    Thomas JH, Schneider S. Coevolution of retroelements and tandem zinc finger genes. Genome Res. 2011;21(11):1800–12. pmid:21784874
  22. 22.
    Bruno M, Mahgoub M, Macfarlan TS. The Arms Race Between KRAB-Zinc Finger Proteins and Endogenous Retroelements and Its Impact on Mammals. Annu Rev Genet. 2019;53:393–416. pmid:31518518
  23. 23.
    Wolf G, de Iaco A, Sun MA, Bruno M, Tinkham M, Hoang D, et al. KRAB-zinc finger protein gene expansion in response to active retrotransposons in the murine lineage. Elife. 2020;9. pmid:32479262
  24. 24.
    Imbeault M, Helleboid PY, Trono D. KRAB zinc-finger proteins contribute to the evolution of gene regulatory networks. Nature. 2017;543(7646):550–4. pmid:28273063
  25. 25.
    Ecco G, Cassano M, Kauzlaric A, Duc J, Coluccio A, Offner S, et al. Transposable Elements and Their KRAB-ZFP Controllers Regulate Gene Expression in Adult Tissues. Dev Cell. 2016;36(6):611–23. pmid:27003935
  26. 26.
    Turelli P, Playfoot C, Grun D, Raclot C, Pontis J, Coudray A, et al. Primate-restricted KRAB zinc finger proteins and target retrotransposons control gene expression in human neurons. Sci Adv. 2020;6(35):eaba3200. pmid:32923624
  27. 27.
    Playfoot CJ, Duc J, Sheppard S, Dind S, Coudray A, Planet E, et al. Transposable elements and their KZFP controllers are drivers of transcriptional innovation in the developing human brain. Genome Res. 2021;31(9):1531–45. pmid:34400477
  28. 28.
    Farmiloe G, Lodewijk GA, Robben SF, van Bree EJ, Jacobs FMJ. Widespread correlation of KRAB zinc finger protein binding with brain-developmental gene expression patterns. Philos Trans R Soc Lond B Biol Sci. 2020;375(1795):20190333. pmid:32075554
  29. 29.
    Pan FC, Wright C. Pancreas organogenesis: from bud to plexus to gland. Developmental dynamics: an official publication of the American Association of Anatomists. 2011;240(3):530–65. pmid:21337462
  30. 30.
    Balakrishnan S, Dhavamani S, Prahalathan C. beta-Cell specific transcription factors in the context of diabetes mellitus and beta-cell regeneration. Mech Dev. 2020;163:103634.
  31. 31.
    Osipovich AB, Dudek KD, Greenfest-Allen E, Cartailler JP, Manduchi E, Potter Case L, et al. A developmental lineage-based gene co-expression network for mouse pancreatic beta-cells reveals a role for Zfp800 in pancreas development. Development. 2021;148(6).
  32. 32.
    Tabula Muris C, Overall c, Logistical c, Organ c, processing, Library p, et al. Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris. Nature. 2018;562(7727):367–72. pmid:30283141
  33. 33.
    Ben-Aharon I, Brown PR, Shalgi R, Eddy EM. Calpain 11 is unique to mouse spermatogenic cells. Mol Reprod Dev. 2006;73(6):767–73. pmid:16541461
  34. 34.
    Artner I, Le Lay J, Hang Y, Elghazi L, Schisler JC, Henderson E, et al. MafB: an activator of the glucagon gene expressed in developing islet alpha- and beta-cells. Diabetes. 2006;55(2):297–304. pmid:16443760
  35. 35.
    Hang Y, Stein R. MafA and MafB activity in pancreatic beta cells. Trends Endocrinol Metab. 2011;22(9):364–73.
  36. 36.
    Conrad E, Dai C, Spaeth J, Guo M, Cyphert HA, Scoville D, et al. The MAFB transcription factor impacts islet alpha-cell function in rodents and represents a unique signature of primate islet beta-cells. Am J Physiol Endocrinol Metab. 2016;310(1):E91–E102.
  37. 37.
    Artner I, Blanchi B, Raum JC, Guo M, Kaneko T, Cordes S, et al. MafB is required for islet beta cell maturation. Proc Natl Acad Sci U S A. 2007;104(10):3853–8. pmid:17360442
  38. 38.
    Sharif J, Shinkai Y, Koseki H. Is there a role for endogenous retroviruses to mediate long-term adaptive phenotypic response upon environmental inputs? Philos Trans R Soc Lond B Biol Sci. 2013;368(1609):20110340. pmid:23166400
  39. 39.
    Consortium EP, Moore JE, Purcaro MJ, Pratt HE, Epstein CB, Shoresh N, et al. Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature. 2020;583(7818):699–710. pmid:32728249
  40. 40.
    Persikov AV, Singh M. De novo prediction of DNA-binding specificities for Cys2His2 zinc finger proteins. Nucleic Acids Res. 2014;42(1):97–108. pmid:24097433
  41. 41.
    Hubley R, Finn RD, Clements J, Eddy SR, Jones TA, Bao W, et al. The Dfam database of repetitive DNA families. Nucleic Acids Res. 2016;44(D1):D81–9. pmid:26612867
  42. 42.
    Choi E, Kraus MR, Lemaire LA, Yoshimoto M, Vemula S, Potter LA, et al. Dual lineage-specific expression of Sox17 during mouse embryogenesis. Stem Cells. 2012;30(10):2297–308. pmid:22865702
  43. 43.
    Trinh LT, Osipovich AB, Sampson L, Wong J, Wright CVE, Magnuson MA. Differential regulation of alternate promoter regions in Sox17 during endodermal and vascular endothelial development. iScience. 2022;25(9):104905. pmid:36046192
  44. 44.
    Choi CS, Savage DB, Abu-Elheiga L, Liu ZX, Kim S, Kulkarni A, et al. Continuous fat oxidation in acetyl-CoA carboxylase 2 knockout mice increases total energy expenditure, reduces fat mass, and improves insulin sensitivity. Proc Natl Acad Sci U S A. 2007;104(42):16480–5. pmid:17923673
  45. 45.
    Friedli M, Trono D. The developmental control of transposable elements and the evolution of higher species. Annu Rev Cell Dev Biol. 2015;31:429–51. pmid:26393776
  46. 46.
    Johansson PA, Brattas PL, Douse CH, Hsieh P, Adami A, Pontis J, et al. A cis-acting structural variation at the ZNF558 locus controls a gene regulatory network in human brain development. Cell Stem Cell. 2022;29(1):52–69 e8. pmid:34624206
  47. 47.
    Richardson SR, Doucet AJ, Kopera HC, Moldovan JB, Garcia-Perez JL, Moran JV. The Influence of LINE-1 and SINE Retrotransposons on Mammalian Genomes. Microbiol Spectr. 2015;3(2):MDNA3-0061-2014. pmid:26104698
  48. 48.
    Hancks DC, Kazazian HH Jr. Active human retrotransposons: variation and disease. Curr Opin Genet Dev. 2012;22(3):191–203. pmid:22406018
  49. 49.
    Mouse Genome Sequencing C, Waterston RH, Lindblad-Toh K, Birney E, Rogers J, Abril JF, et al. Initial sequencing and comparative analysis of the mouse genome. Nature. 2002;420(6915):520–62. pmid:12466850
  50. 50.
    Crichton JH, Dunican DS, Maclennan M, Meehan RR, Adams IR. Defending the genome from the enemy within: mechanisms of retrotransposon suppression in the mouse germline. Cell Mol Life Sci. 2014;71(9):1581–605. pmid:24045705
  51. 51.
    Babarinde IA, Ma G, Li Y, Deng B, Luo Z, Liu H, et al. Transposable element sequence fragments incorporated into coding and noncoding transcripts modulate the transcriptome of human pluripotent stem cells. Nucleic Acids Res. 2021;49(16):9132–53. pmid:34390351
  52. 52.
    Kaemena DF, Yoshihara M, Beniazza M, Ashmore J, Zhao S, Bertenstam M, et al. B1 SINE-binding ZFP266 impedes mouse iPSC generation through suppression of chromatin opening mediated by reprogramming factors. Nat Commun. 2023;14(1):488. pmid:36717582
  53. 53.
    Lu JY, Chang L, Li T, Wang T, Yin Y, Zhan G, et al. Homotypic clustering of L1 and B1/Alu repeats compartmentalizes the 3D genome. Cell Res. 2021;31(6):613–30. pmid:33514913
  54. 54.
    Zhang XO, Gingeras TR, Weng Z. Genome-wide analysis of polymerase III-transcribed Alu elements suggests cell-type-specific enhancer function. Genome Res. 2019;29(9):1402–14. pmid:31413151
  55. 55.
    Dahlet T, Argueso Lleida A, Al Adhami H, Dumas M, Bender A, Ngondo RP, et al. Genome-wide analysis in the mouse embryo reveals the importance of DNA methylation for transcription integrity. Nat Commun. 2020;11(1):3153. pmid:32561758
  56. 56.
    Dear TN, Boehm T. Diverse mRNA expression patterns of the mouse calpain genes Capn5, Capn6 and Capn11 during development. Mech Dev. 1999;89(1–2):201–9. pmid:10559499
  57. 57.
    Schwaller B. Cytosolic Ca(2+) Buffers Are Inherently Ca(2+) Signal Modulators. Cold Spring Harb Perspect Biol. 2020;12(1).
  58. 58.
    He J, Fu X, Zhang M, He F, Li W, Abdul MM, et al. Transposable elements are regulated by context-specific patterns of chromatin marks in mouse embryonic stem cells. Nat Commun. 2019;10(1):34. pmid:30604769
  59. 59.
    Taylor D, Lowe R, Philippe C, Cheng KCL, Grant OA, Zabet NR, et al. Locus-specific chromatin profiling of evolutionarily young transposable elements. Nucleic Acids Res. 2021.
  60. 60.
    Costello KR, Leung A, Trac C, Lee M, Basam M, Pospisilik JA, et al. Sequence features of retrotransposons allow for epigenetic variability. Elife. 2021;10. pmid:34668484
  61. 61.
    Reichmann J, Crichton JH, Madej MJ, Taggart M, Gautier P, Garcia-Perez JL, et al. Microarray analysis of LTR retrotransposon silencing identifies Hdac1 as a regulator of retrotransposon expression in mouse embryonic stem cells. PLoS Comput Biol. 2012;8(4):e1002486. pmid:22570599
  62. 62.
    Shimosuga KI, Fukuda K, Sasaki H, Ichiyanagi K. Locus-specific hypomethylation of the mouse IAP retrotransposon is associated with transcription factor-binding sites. Mob DNA. 2017;8:20. pmid:29255492
  63. 63.
    Sakashita A, Maezawa S, Takahashi K, Alavattam KG, Yukawa M, Hu YC, et al. Endogenous retroviruses drive species-specific germline transcriptomes in mammals. Nat Struct Mol Biol. 2020;27(10):967–77. pmid:32895553
  64. 64.
    Hallen L, Klein H, Stoschek C, Wehrmeyer S, Nonhoff U, Ralser M, et al. The KRAB-containing zinc-finger transcriptional regulator ZBRK1 activates SCA2 gene transcription through direct interaction with its gene product, ataxin-2. Hum Mol Genet. 2011;20(1):104–14. pmid:20926453
  65. 65.
    Yi Z, Li Y, Ma W, Li D, Zhu C, Luo J, et al. A novel KRAB zinc-finger protein, ZNF480, expresses in human heart and activates transcriptional activities of AP-1 and SRE. Biochem Biophys Res Commun. 2004;320(2):409–15. pmid:15219843
  66. 66.
    Chen W, Schwalie PC, Pankevich EV, Gubelmann C, Raghav SK, Dainese R, et al. ZFP30 promotes adipogenesis through the KAP1-mediated activation of a retrotransposon-derived Pparg2 enhancer. Nat Commun. 2019;10(1):1809. pmid:31000713
  67. 67.
    Shi H, Strogantsev R, Takahashi N, Kazachenka A, Lorincz MC, Hemberger M, et al. ZFP57 regulation of transposable elements and gene expression within and beyond imprinted domains. Epigenetics Chromatin. 2019;12(1):49. pmid:31399135
  68. 68.
    Iouranova A, Grun D, Rossy T, Duc J, Coudray A, Imbeault M, et al. KRAB zinc finger protein ZNF676 controls the transcriptional influence of LTR12-related endogenous retrovirus sequences. Mob DNA. 2022;13(1):4. pmid:35042549
  69. 69.
    Bertozzi TM, Takahashi N, Hanin G, Kazachenka A, Ferguson-Smith AC. A spontaneous genetically induced epiallele at a retrotransposon shapes host genome function. Elife. 2021;10.
  70. 70.
    Katoh MC, Jung Y, Ugboma CM, Shimbo M, Kuno A, Basha WA, et al. MafB Is Critical for Glucagon Production and Secretion in Mouse Pancreatic alpha Cells In Vivo. Mol Cell Biol. 2018;38(8).
  71. 71.
    Chandrasekaran S, Espeso-Gil S, Loh YE, Javidfar B, Kassim B, Zhu Y, et al. Neuron-specific chromosomal megadomain organization is adaptive to recent retrotransposon expansions. Nat Commun. 2021;12(1):7243. pmid:34903713
  72. 72.
    Chuong EB, Rumi MA, Soares MJ, Baker JC. Endogenous retroviruses function as species-specific enhancer elements in the placenta. Nat Genet. 2013;45(3):325–9. pmid:23396136
  73. 73.
    Bakoulis S, Krautz R, Alcaraz N, Salvatore M, Andersson R. Endogenous retroviruses co-opted as divergently transcribed regulatory elements shape the regulatory landscape of embryonic stem cells. Nucleic Acids Res. 2022;50(4):2111–27. pmid:35166831
  74. 74.
    Groza T, Gomez FL, Mashhadi HH, Munoz-Fuentes V, Gunes O, Wilson R, et al. The International Mouse Phenotyping Consortium: comprehensive knockout phenotyping underpinning the study of human disease. Nucleic Acids Res. 2023;51(D1):D1038–D45. pmid:36305825
  75. 75.
    Ha J, Lee JK, Kim KS, Witters LA, Kim KH. Cloning of human acetyl-CoA carboxylase-beta and its unique features. Proc Natl Acad Sci U S A. 1996;93(21):11466–70. pmid:8876158
  76. 76.
    Alam N, Saggerson ED. Malonyl-CoA and the regulation of fatty acid oxidation in soleus muscle. Biochem J. 1998;334 (Pt 1)(Pt 1):233–41. pmid:9693125
  77. 77.
    Oh W, Abu-Elheiga L, Kordari P, Gu Z, Shaikenov T, Chirala SS, et al. Glucose and fat metabolism in adipose tissue of acetyl-CoA carboxylase 2 knockout mice. Proc Natl Acad Sci U S A. 2005;102(5):1384–9. pmid:15677334
  78. 78.
    Abu-Elheiga L, Oh W, Kordari P, Wakil SJ. Acetyl-CoA carboxylase 2 mutant mice are protected against obesity and diabetes induced by high-fat/high-carbohydrate diets. Proc Natl Acad Sci U S A. 2003;100(18):10207–12. pmid:12920182
  79. 79.
    Tuazon MA, McConnell TR, Wilson GJ, Anthony TG, Henderson GC. Intensity-dependent and sex-specific alterations in hepatic triglyceride metabolism in mice following acute exercise. J Appl Physiol (1985). 2015;118(1):61–70. pmid:25257878
  80. 80.
    Ruigrok SR, Stoberl N, Yam KY, de Lucia C, Lucassen PJ, Thuret S, et al. Modulation of the Hypothalamic Nutrient Sensing Pathways by Sex and Early-Life Stress. Front Neurosci. 2021;15:695367. pmid:34366778
  81. 81.
    Lewis CE, North KE, Arnett D, Borecki IB, Coon H, Ellison RC, et al. Sex-specific findings from a genome-wide linkage analysis of human fatness in non-Hispanic whites and African Americans: the HyperGEN study. Int J Obes (Lond). 2005;29(6):639–49. pmid:15809668
  82. 82.
    Kanai-Azuma M, Kanai Y, Gad JM, Tajima Y, Taya C, Kurohmaru M, et al. Depletion of definitive gut endoderm in Sox17-null mutant mice. Development. 2002;129(10):2367–79. pmid:11973269
  83. 83.
    Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29(1):15–21. pmid:23104886
  84. 84.
    Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550. pmid:25516281
  85. 85.
    Teissandier A, Servant N, Barillot E, Bourc’his D. Tools and best practices for retrotransposon analysis using high-throughput sequencing data. Mob DNA. 2019;10:52. pmid:31890048
  86. 86.
    Jin Y, Tam OH, Paniagua E, Hammell M. TEtranscripts: a package for including transposable elements in differential expression analysis of RNA-seq datasets. Bioinformatics. 2015;31(22):3593–9. pmid:26206304
  87. 87.
    Smit A, Hubley, R & Green, P. RepeatMasker Open-4.0. 2013–2015 [<http://www.repeatmasker.org>
  88. 88.
    https://doi.org/10.5281/zenodo.7257061 [
  89. 89.
    Ewels PA, Peltzer A, Fillinger S, Patel H, Alneberg J, Wilm A, et al. The nf-core framework for community-curated bioinformatics pipelines. Nat Biotechnol. 2020;38(3):276–8. pmid:32055031
  90. 90.
    Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357–9. pmid:22388286
  91. 91.
    Danecek P, Bonfield JK, Liddle J, Marshall J, Ohan V, Pollard MO, et al. Twelve years of SAMtools and BCFtools. Gigascience. 2021;10(2). pmid:33590861
  92. 92.
    http://broadinstitute.github.io/picard/ [
  93. 93.
    Zhang Y, Liu T, Meyer CA, Eeckhoute J, Johnson DS, Bernstein BE, et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 2008;9(9):R137. pmid:18798982
  94. 94.
    Bailey TL, Johnson J, Grant CE, Noble WS. The MEME Suite. Nucleic Acids Res. 2015;43(W1):W39–49. pmid:25953851
  95. 95.
    Osipovich AB, Gangula R, Vianna PG, Magnuson MA. Setd5 is essential for mammalian development and the co-transcriptional regulation of histone acetylation. Development. 2016;143(24):4595–607. pmid:27864380

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