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Implications of noncoding regulatory functions in the development of insulinomas.

Insulinomas are rare neuroendocrine tumors arising from pancreatic β cells, characterized by aberrant proliferation and altered insulin secretion, leading to glucose homeostasis failure. With the aim of uncovering the role of noncoding regulatory regions and their aberrations in the development of these tumors, we coupled epigenetic and transcriptome profiling with whole-genome sequencing. As a result, we unraveled somatic mutations associated with changes in regulatory functions. Critically, these regions impact insulin secretion, tumor development, and epigenetic modifying genes, including polycomb complex components. Chromatin remodeling is apparent in insulinoma-selective domains shared across patients, containing a specific set of regulatory sequences dominated by the SOX17 binding motif. Moreover, many of these regions are H3K27me3 repressed in β cells, suggesting that tumoral transition involves derepression of polycomb-targeted domains. Our work provides a compendium of aberrant cis-regulatory elements affecting the function and fate of β cells in their progression to insulinomas and a framework to identify coding and noncoding driver mutations.

Humans↗

DKK1-SE recruits AP1 to activate the target gene DKK1 thereby promoting pancreatic cancer progression.

Super-enhancers are a class of DNA cis-regulatory elements that can regulate cell identity, cell fate, stem cell pluripotency, and even tumorigenesis. Increasing evidence shows that epigenetic modifications play an important role in the pathogenesis of various types of cancer. However, the current research is far from enough to reveal the complex mechanism behind it. This study found a super-enhancer enriched with abnormally active histone modifications in pancreatic ductal adenocarcinoma (PDAC), called DKK1-super-enhancer (DKK1-SE). The major active component of DKK1-SE is component enhancer e1. Mechanistically, AP1 induces chromatin remodeling in component enhancer e1 and activates the transcriptional activity of DKK1. Moreover, DKK1 was closely related to the malignant clinical features of PDAC. Deletion or knockdown of DKK1-SE significantly inhibited the proliferation, colony formation, motility, migration, and invasion of PDAC cells in vitro, and these phenomena were partly mitigated upon rescuing DKK1 expression. In vivo, DKK1-SE deficiency not only inhibited tumor proliferation but also reduced the complexity of the tumor microenvironment. This study identifies that DKK1-SE drives DKK1 expression by recruiting AP1 transcription factors, exerting oncogenic effects in PDAC, and enhancing the complexity of the tumor microenvironment.

Humans↗

Rare variant contribution to the heritability of coronary artery disease.

Whole genome sequences (WGS) enable discovery of rare variants which may contribute to missing heritability of coronary artery disease (CAD). To measure their contribution, we apply the GREML-LDMS-I approach to WGS of 4949 cases and 17,494 controls of European ancestry from the NHLBI TOPMed program. We estimate CAD heritability at 34.3% assuming a prevalence of 8.2%. Ultra-rare (minor allele frequency ≤ 0.1%) variants with low linkage disequilibrium (LD) score contribute ~50% of the heritability. We also investigate CAD heritability enrichment using a diverse set of functional annotations: i) constraint; ii) predicted protein-altering impact; iii) cis-regulatory elements from a cell-specific chromatin atlas of the human coronary; and iv) annotation principal components representing a wide range of functional processes. We observe marked enrichment of CAD heritability for most functional annotations. These results reveal the predominant role of ultra-rare variants in low LD on the heritability of CAD. Moreover, they highlight several functional processes including cell type-specific regulatory mechanisms as key drivers of CAD genetic risk.

Humans↗

3D epigenome of glial cell types in developing human cortex.

The human cortex is complex and heterogeneous, undergoing extensive expansion during development1,2. Our prior study of neurogenesis, including radial glia (RG), intermediate progenitor cells, excitatory neurons and interneurons demonstrated that chromatin looping underlies transcriptional regulation for lineage-specific genes, shedding light on how non-coding genetic variants contribute to neuropsychiatric disorders by means of cell-type-specific gene regulation3. RG have a crucial role in generating cellular diversity through both neurogenesis and gliogenesis and can be further classified into ventricular RG (vRG) and outer RG (oRG)4,5. Given their significance in cortical development, we conducted a comprehensive three-dimensional (3D) epigenomic analysis of four main glial populations, including vRG, oRG, oligodendrocyte precursor cells and microglia, from the mid-gestational human neocortex. By integrating gene expression, chromatin accessibility, DNA methylation and 3D chromatin interactions, we identified cell-type-specific candidate cis-regulatory elements (cCREs) and validated their regulatory function using transgenic mouse embryos. Using machine learning, we prioritized 112 schizophrenia risk variants within glia cCREs and further confirmed the predicted vRG enhancer disruption by the rs4449074 risk allele in vivo. Finally, oRG cCREs are enriched for human accelerated regions compared with other cCREs and a subset of human accelerated regions show activity differences from their chimpanzee orthologues that interact with genes involved in neuronal development. Our findings advance the understanding of human-specific gene regulation during corticogenesis.

Journal Article↗

Mechanisms and functional implications of long-range enhancer-dependent gene regulation.

Metazoan development relies on the coordinated establishment of diverse gene regulatory programs that drive the formation of specific cell types, tissues and organs. The temporal and spatial control of gene expression is achieved through the concerted activity of multiple classes of cis-regulatory elements encoded in the genome. Among these, enhancers enable the establishment of specific and precise gene expression patterns and control gene expression over long linear distances, a property often referred to as distance-independent regulatory activity. However, enhancer activity is, in fact, inversely correlated with linear genomic distance, and target gene expression and transcriptional precision decrease with increasing enhancer-promoter linear distances. Here, we highlight emerging insights into multiple mechanisms that enable enhancers to precisely and robustly activate gene expression across large genomic distances. Finally, we provide a more speculative perspective on the potential advantages that long-range regulation might confer during the establishment of developmental gene expression programs.

Enhancer Elements, Genetic↗

Multichannel genomic recording of biological information with ENGRAM.

Molecular recording is an emerging paradigm for measuring biology over time. Enhancer-mediated genomic recording of activity in multiplex (ENGRAM) is a recently described synthetic biology circuit architecture that converts the transient activity of cis-regulatory elements (CREs) into stable genomic records that can be retrospectively recovered via DNA sequencing. Here we provide a step-by-step protocol for conducting ENGRAM experiments and analyzing the resulting data. We also describe key design considerations for ENGRAM recorders, summarize the strengths and limitations of ENGRAM, and highlight applications, including multiplex signal recording and high-throughput CRE screening. In contrast to other systems for DNA-based recording in mammalian systems, ENGRAM relies on prime editing-mediated insertions to record the activity of a given CRE, such that it is inherently multiplexable-for example, four-base-pair insertions can represent the activities of up to 256 distinct CREs. A further contrast lies with ENGRAM's compatibility with DNA Typewriter, which facilitates the capture of signal order. For users with basic skills in molecular biology, mammalian cell culture and DNA sequencing analysis, ENGRAM experiments can typically be completed within 5-6 weeks.

Genomics↗

Pangenome-wide identification and expression analysis of the chalcone synthase (CHS) gene family in five yellowhorn spp.

Chalcone synthase (CHS) is a pivotal enzyme in flavonoid biosynthesis involved in plant development, defense, and secondary metabolism. Xanthoceras sorbifolium (yellowhorn) is a medicinal and ornamental species with high resistance to environmental stresses, but its CHS gene family remains uncharacterized. We performed a pangenome-wide identification of CHS genes across five yellowhorn genomes (Xzs4, Xwf8, Xjg, Xg11, and Xzg2). Across the five yellowhorn genomes, 27 CHS genes were identified and classified into four core pangenes, present in all five genomes, and two dispensable genes, present only in a subset of genomes. Phylogenetic analysis grouped these genes into three major clades, and chromosomal mapping and duplication analyses identified four tandemly duplicated gene pairs under purifying selection. The analyses of conserved structural features, including protein motifs and exon-intron organization, together with promoter cis-regulatory elements and gene ontology annotation, further indicated the potential involvement of CHS genes in flavonoid biosynthesis and stress-responsive mechanisms. Gene expression profiling identified significant upregulation of Xg11_CHS1 and Xg11_CHS3 under cold and drought stress, with tissue-specific expression patterns. These findings provide valuable insights into the evolution, functional diversification, and stress-responsive roles of the CHS gene family, identifying candidate genes for future studies targeting stress tolerance and flavonoid biosynthesis in yellowhorn.

Acyltransferases↗

ChromBERT-tools: a versatile toolkit for context-specific regulatory representations of transcription regulators across different cell types.

SUMMARY: Representations that encode the genome-wide regulatory behavior of transcription regulators provide a foundation for flexible transcription modeling and in silico regulatory analysis. Existing regulator representations are commonly derived from gene co-expression, motif annotations, or static protein features, which capture useful but limited aspects of regulator identity but do not directly model how regulators participate in region-specific regulatory programs across the genome. ChromBERT addresses this gap by learning context-aware regulatory representations from large-scale ChIP-seq data. However, routine bioinformatics applications require lightweight, accessible, and modular tools for generating, adapting, and interpreting these representations in user-defined biological contexts. Here, we present ChromBERT-tools, a user-oriented toolkit built upon ChromBERT that converts its regulatory representation framework into practical workflows for customizable analysis across cellular contexts. ChromBERT-tools provides command-line interfaces and Python APIs organized into three functional layers: representation generation, predictive modeling, and regulatory interpretation. The representation generation layer produces representations of genomic regions and transcription regulators. The predictive modeling layer fine-tunes ChromBERT for genome-wide regulatory activity prediction through classification or regression tasks, with optimized implementation to reduce running time and computational resource requirements. The regulatory interpretation layer supports inference of the context-specific roles of cis-regulatory elements and transcription regulators. These modules can be used independently or integrated into end-to-end workflows, enabling flexible analyses across diverse datasets. ChromBERT-tools lowers the barrier to applying context-specific regulatory representations in routine genomic analyses. AVAILABILITY AND IMPLEMENTATION: ChromBERT-tools is freely available at https://github.com/TongjiZhanglab/ChromBERT-tools, with documentation at https://chrombert-tools.readthedocs.io/en/latest/. A frozen archival snapshot is available on Zenodo under DOI: 10.5281/zenodo.20094206.

Software↗

DeepGeSeq: deep learning library for genomic sequence modeling and analysis.

MOTIVATION: Deep learning methods have demonstrated significant potential in genomics, enabling broad applications such as sequence activity prediction, regulatory rule identification, and variant effect quantification. However, their widespread adoption is often hindered by the steep computational learning curve required for model construction, training, and downstream biological interpretation. Here, we introduce DeepGeSeq, a user-friendly Deep-learning library tailored for Genomic Sequence modeling and analysis. RESULTS: By integrating state-of-the-art architectural modules, DeepGeSeq streamlines the entire deep learning workflow, requiring minimal user input via a simple configuration file and an intuitive agentic skill. We comprehensively validate the efficacy of DeepGeSeq through diverse case studies, encompassing pipeline verification using synthetic datasets, the reproduction and application of established models, and model fine-tuning coupled with biological interpretation on user-defined data. Furthermore, we demonstrate DeepGeSeq's versatility in domain-specific applications, including single-cell ATAC-seq modeling for cell-type clustering, and MPRA data modeling coupled with in silico saturation mutagenesis to dissect cis-regulatory elements. Ultimately, DeepGeSeq bridges the gap between computational complexity and biological discovery, providing an accessible resource that facilitates the development and broad application of deep learning methods in genomics research. AVAILABILITY AND IMPLEMENTATION: https://github.com/JiaqiLi1024/DeepGeSeq.

Deep Learning↗

Parent-of-origin effects on allelic expression bias in interspecific poplar hybrids.

In hybrid plants, phenotypic outcomes are governed by interactions between the two parental genomes. However, the mechanisms underlying the interplay of divergent regulatory networks from these genomes remain poorly understood. In this study, we compared gene-level and allele-specific expression patterns, as well as differentially enriched pathways between F₁ and complex backcross (CBC) lines derived from a natural interspecific hybrid population of Populus fremontii (Pf) and P. angustifolia (Pa). Metabolic differences between Pf and Pa which exhibit low and high levels respectively of phenylpropanoid-derived condensed tannins were leveraged. Using individualized transcriptome references, differential expression and clustering analyses revealed CBC-biased and F₁-biased expression for genes involved in phenylpropanoid metabolism and photosynthesis, respectively. Biased expression of these genes at the allele level was also observed in F1. At the whole-transcriptome level, Pa-biased genes predominated in F₁ hybrids, and Pa alleles displayed more conserved expression patterns than Pf alleles across examined samples. Further analyses indicated that allelic expression bias was significantly associated with parental origin, which could be driven by sequence variations in cis-regulatory elements and differences in CpG island length. Our findings demonstrate strong parent-of-origin effects on divergent regulatory networks governing gene expression in poplar hybrids and provide clues for strategic parental selection tailored to specific metabolic pathways of interest.

cis-regulation↗

De novo structural variants in autism spectrum disorder disrupt distal regulatory interactions of neuronal genes.

Three-dimensional genome organization plays a critical role in gene regulation, and disruptions can lead to developmental disorders by altering the contact between genes and their distal regulatory elements. Structural variants (SVs) can disturb local genome organization, such as the merging of topologically associating domains upon boundary deletion. Testing large numbers of SVs experimentally for their effects on chromatin structure and gene expression is time and cost prohibitive. To address this, we propose a computational approach to predict SV impacts on genome folding, which can help prioritize causal hypotheses for functional testing. We developed a weighted scoring method that measures chromatin contact changes specifically affecting regions of interest, such as regulatory elements or promoters, and implemented it in the SuPreMo-Akita software (Gjoni and Pollard 2024). With this tool, we ranked hundreds of de novo SVs (dnSVs) from autism spectrum disorder (ASD) individuals and their unaffected siblings based on predicted disruptions to nearby neuronal regulatory interactions. This revealed that putative cis-regulatory element interactions (CREints) are more disrupted by dnSVs from ASD probands versus unaffected siblings. We prioritized candidate variants that disrupt ASD CREints and validated our top-ranked locus using isogenic excitatory neurons with and without the dnSV, confirming accurate predictions of disrupted chromatin contacts. This study establishes disrupted genome folding as a potential genetic mechanism in ASD and provides a general strategy for prioritizing variants predicted to disrupt regulatory interactions across tissues.

Journal Article↗

De novo structural variants in autism spectrum disorder disrupt distal regulatory interactions of neuronal genes.

Three-dimensional genome organization plays a critical role in gene regulation, and disruptions can lead to developmental disorders by altering the contact between genes and their distal regulatory elements. Structural variants (SVs) can disturb local genome organization, such as the merging of topologically associating domains upon boundary deletion. Testing large numbers of SVs experimentally for their effects on chromatin structure and gene expression is time and cost prohibitive. To address this, we propose a computational approach to predict SV impacts on genome folding, which can help prioritize causal hypotheses for functional testing. We develop a weighted scoring method that measures chromatin contact changes specifically affecting regions of interest, such as regulatory elements or promoters, and implement it in the SuPreMo-Akita software. With this tool, we rank hundreds of de novo SVs (dnSVs) from autism spectrum disorder (ASD) individuals and their unaffected siblings based on predicted disruptions to nearby neuronal regulatory interactions. This reveals that putative cis-regulatory element interactions (CREints) are more disrupted by dnSVs from ASD probands versus unaffected siblings. We prioritize candidate variants that disrupt ASD CREints and validate our top-ranked locus using isogenic excitatory neurons with and without the dnSV, confirming accurate predictions of disrupted chromatin contacts. This study suggests that disrupted genome folding is a potential genetic mechanism in a subset of ASD cases and provides a general strategy for prioritizing variants predicted to disrupt regulatory interactions across tissues.

Humans↗

Genetic effects on chromatin accessibility reveal the molecular mechanisms of complex traits in maize.

Cis-regulatory elements (CREs) are critical for modulating gene expression and phenotypic diversity in maize. While genome-wide association study (GWAS) hits and expression quantitative trait loci (eQTLs) are often enriched in CREs, their molecular mechanisms remain poorly understood. Characterizing CREs within accessible chromatin regions (ACRs) offers a powerful approach to link noncoding variants to chromatin structure alterations and phenotypic variation. Here, we generated ATAC-seq profiles from seedling leaves of 214 maize inbred lines, identifying 82 174 consensus ACRs. Notably, 39.55% of these ACRs exhibited significant population-wide chromatin accessibility variation. By mapping chromatin accessibility quantitative trait loci (caQTLs), we discovered 27 004 loci, including 1398 predicted to disrupt transcription factor (TF)-binding sites. Integration with multi-omics data revealed 7405 caACR-target gene pairs and linked 56 caACRs to GWAS signals for 51 agronomic traits, with significant enrichment in flowering-related pathways. Functional candidates such as ZmZIM30 - putatively regulated by caACRs - emerged as key regulators of flowering time. At the fad7 locus associated with linolenic acid content, allelic variants overlapping a caQTL showed differential chromatin accessibility. Our study provides a high-resolution cis-elements of maize leaves, deciphers the genetic basis of chromatin accessibility variation, and bridges noncoding caQTLs to molecular mechanisms underlying GWAS hits.

Zea mays↗

The structured mRNA element 45ABC mediates auto- and cross-regulation of RBP45 genes via alternative splicing.

Alternative splicing (AS) is a common gene regulatory mechanism involving distinct interactions between trans-acting factors and cis-regulatory elements on the precursor messenger RNA (pre-mRNA). In this study, we have functionally characterized the structured motif 45ABC, which is located in the pre-mRNAs of RNA-binding protein (RBP) 45 genes in many plant species. Our data revealed that this element mediates a negative auto- and cross-regulatory feedback loop via AS of the three 45ABC-containing RBP45 genes in Arabidopsis thaliana. We identified a G-rich stretch within the first stem as a potential RBP45 binding site and observed increased RBP45-dependent AS upon structural weakening of this pairing element. The second stem includes the alternative 5' splice site being activated in the presence of RBP45. Based on the known interaction between RBP45 homologs and U1 snRNP components required for 5' splice site recognition, we propose that RBP45 recruitment to stem I of 45ABC may induce usage of the alternative 5' splice site in stem II. The resulting splicing variant is unproductive, thereby diminishing RBP45 expression. Analysing the splicing-regulatory impact of the three At-RBP45 genes in auto- and cross-regulation and a transcriptome-wide manner revealed unequal genetic redundancy with a major role of RBP45B. Furthermore, phenotypical analysis of single- and higher-order rbp45 mutants pointed at these genes' functions in controlling primary root growth and flowering time. Taken together, we demonstrated that both sequence and structural features of 45ABC are critical for proper splicing control, balancing RBP45 expression and functions in plants via a conserved mRNA motif.

Alternative Splicing↗

Partitioned blood pressure polygenic risk reveals differential genetic effects of tissue-specific enhancers and their interactions on cardiovascular disease.

Polygenic risk scores (PRS) compress genome-wide associations into a single predictor, but this aggregation obscures the distinct biological mechanisms through which genetic variation shapes complex traits. Here we introduce a framework that additively decomposes a trait's PRS, without loss of SNP heritability, into independent components defined by the tissue-specific and tissue-agnostic cis-regulatory elements (CREs) in which its variants act. Applied to blood pressure (BP) using ~0.5 million CREs across four BP-relevant tissues (adrenal gland, artery, heart, kidney), the framework reveals that regulatory effects are globally additive across tissues yet locally non-additive, and that the resulting partitioned scores carry pronounced, reproducible heterogeneity in their effects on BP and cardiovascular outcomes. We show this heterogeneity reflects gene-environment interactions, and trace one example to its mechanism: a kidney-CRE-partitioned score is protective against coronary artery disease and myocardial infarction through an interaction between ATP2B1 and antihypertensive medication. Explicitly modeling these interactions improves prediction and transferability, and tissue-focused partitioning increases power to resolve causal genes and reveals genes such as ADAMTS8 with antagonistic effects across BP components. Validated in an independent All of Us cohort, these findings recast the PRS from a blunt aggregate predictor into a mechanistic probe of context-dependent genetic architecture.

Journal Article↗

Developmental patterning of adipose tissue by abd-A and Abd-B homeotic genes in Drosophila melanogaster.

The Bithorax Complex (BX-C) homeobox proteins specify segmental identities along the anterior-posterior axis during Drosophila embryogenesis. Differential expression of the BX-C genes abd-A and Abd-B distinguishes abdominal from thoracic adipocytes, yet the mechanism regulating this heterogeneity remains poorly understood. Here, we identify cis-regulatory elements (CREs) and transcription factors that direct abdominal-specific expression of abd-A and Abd-B in the larval fat body. Fine-mapping analyses identified a 627-bp CRE within the Abd-B locus and a ~6-kb CRE within the abd-A locus sufficient to drive heterogeneous expression. Yeast one-hybrid screening combined with functional analyses identified Lola, Lolal, and Combgap as key repressors of Abd-B, whereas Piragua (Prg) and Seven up (Svp) function as transcriptional activators, indicating that adipocyte heterogeneity in postembryonic adipose tissue is actively regulated. In turn, lola and prg are repressed by Abd-B, whereas lolal and svp are activated, forming a feedback circuit further modulated by Wnt signaling, which promotes lola and lolal expression while repressing svp. CUT&RUN analyses suggest that these interactions are direct, with dTCF/Pan and Abd-B occupancy detected at target loci. Together, our findings define a transcriptional circuit that regulates Abd-B gene transcription to pattern adipose tissue and may establish the developmental basis of fat depot specialization.

Abd-B↗

Mining the sHSP20 (small heat-shock protein) gene family in finger millet (Eleusine coracana (L.) Gaertn.): structural, evolutionary and predicted abiotic-stress-responsive insights.

Small heat-shock proteins (sHSPs, the HSP20 family) are ATP-independent molecular chaperones that hold partially unfolded substrates and protect the proteome during heat and other abiotic stresses; every member is defined by a conserved &#x3b1;-crystallin domain (ACD). Finger millet (Eleusine coracana) is a climate-resilient, calcium-rich allotetraploid cereal of the semi-arid tropics whose HSP20 repertoire had not been catalogued. The present study is an entirely computational (in silico) analysis of the chromosome-scale reference genome of finger millet (NCBI GenBank assembly GCA_032690845.1, cultivar KNE 796-S). Mining the predicted proteome with the ACD profile (Pfam PF00011) and confirming every candidate by NCBI CD-search recovered 76 non-redundant ACD-bearing HSP20 genes (EcHSP20-1-EcHSP20-76). Based on phylogeny and TargetP-predicted localization, the members were classified into ten subfamilies: seven cytosolic/nuclear classes (C-I to C-VII, 60 members) together with chloroplastic (11), mitochondrial (3) and endoplasmic-reticulum (2) groups. The proteins ranged from 110 to 355 amino acids (12.1-39.2&#xa0;kDa) with theoretical pI of 4.85-9.69. The 76 loci were distributed over 14 of the 18 chromosomes and were conspicuously absent from chromosomes 8&#xa0;A, 8B, 9&#xa0;A and 9B, with pronounced clustering on chromosomes 1, 2, 3 and 6. Duplication analysis detected 149 paralogous pairs (49 homoeologous, 80 segmental/dispersed and 18 tandem); 147 of 148 pairs for which substitution rates could be calculated returned Ka/Ks&#x2009;<&#x2009;1 (mean 0.20), indicating strong purifying selection consistent with retention after whole-genome/allopolyploid duplication. Promoter analysis (PlantCARE) revealed enrichment of abscisic-acid-responsive (ABRE), MYB/MYC drought-related, STRE, DRE, low-temperature (LTR) and methyl-jasmonate/salicylic-acid elements, whereas canonical heat-shock elements (HSE) were not recovered. Expression profiling against a public drought transcriptome (SRP081350) showed that about half of the genes (39 of 76) are transcribed in leaf tissue, the expressed fraction being dominated by the cytosolic class C-I. This first finger-millet HSP20 catalogue provides a verified, reproducible framework and nominates computationally predicted candidate genes for future functional work on thermotolerance in cereals.

Allotetraploid↗

Cis-regulatory variation in the MdCKX6 promoter is associated with allele-specific expression and fruit size in apple.

Fruit size is a key determinant of apple fruit quality and market value and is strongly influenced by phytohormone-regulated cell proliferation and expansion during early fruit development. Cytokinin oxidase/dehydrogenase (CKX) enzymes regulate cytokinin homeostasis by irreversibly degrading active cytokinins, but the contribution of natural variation in CKX genes to fruit size remains poorly understood. Here, we identified MdCKX6 as a candidate regulator of fruit growth in apple (Malus domestica). MdCKX6 exhibited pronounced allele-specific expression during fruit development in the cultivar 'Royal Gala'. Sequence analysis identified a promoter SNP associated with differential promoter activity and allele-specific expression. Genotyping of diverse apple cultivars and wild Malus accessions revealed a significant association between MdCKX6 promoter genotype and fruit size. Cultivars carrying low-expression alleles produced larger fruits, whereas high-expression alleles were associated with smaller fruits. To investigate gene function, MdCKX6 was overexpressed in tomato, resulting in reduced fruit size. Histological analyses of the transgenic tomato fruit revealed smaller pericarp cells. Transcriptome analysis of transgenic fruits revealed widespread changes in genes associated with cell-cycle regulation, cell wall modification, hormone-related processes, and transcriptional regulation. Together, these results identify MdCKX6 as a potential negative regulator of apple fruit growth and reveal an association between cis-regulatory variants, gene expression, and fruit size. This study provides new insights into the role of cytokinin metabolism in fruit development and highlights regulatory variation in MdCKX6 as a potential target for apple breeding.

Malus↗