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        <title>Frontiers in Genetics | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/genetics</link>
        <description>RSS Feed for Frontiers in Genetics | New and Recent Articles</description>
        <language>en-us</language>
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        <pubDate>2026-07-08T10:28:53.246+00:00</pubDate>
        <ttl>60</ttl>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1884212</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1884212</link>
        <title><![CDATA[Correction: Mesoangioblasts at 20: from the embryonic aorta to the patient bed]]></title>
        <pubdate>2026-07-08T00:00:00Z</pubdate>
        <category>Correction</category>
        <author>Giulio Cossu</author><author>Rossana Tonlorenzi</author><author>Silvia Brunelli</author><author>Maurilio Sampaolesi</author><author>Graziella Messina</author><author>Emanuele Azzoni</author><author>Sara Benedetti</author><author>Stefano Biressi</author><author>Chiara Bonfanti</author><author>Laricia Bragg</author><author>Jordi Camps</author><author>Ornella Cappellari</author><author>Marco Cassano</author><author>Fabio Ciceri</author><author>Marcello Coletta</author><author>Diego Covarello</author><author>Stefania Crippa</author><author>M. Gabriella Cusella-De Angelis</author><author>Luciana De Angelis</author><author>Arianna Dellavalle</author><author>Jordi Diaz-Manera</author><author>Irene Fancello</author><author>Daniela Galli</author><author>Francesco Galli</author><author>Cesare Gargioli</author><author>Mattia F. M. Gerli</author><author>Giorgia Giacomazzi</author><author>Beatriz G. Galvez</author><author>Hidetoshi Hoshiya</author><author>Maria Guttinger</author><author>Anna Innocenzi</author><author>M. Giulia Minasi</author><author>Laura Perani</author><author>Stefano C. Previtali</author><author>Mattia Quattrocelli</author><author>Martina Ragazzi</author><author>Urmas Roostalu</author><author>Giuliana Rossi</author><author>Sabrina Santoleri</author><author>Raffaella Scardigli</author><author>Dario Sirabella</author><author>Francesco Saverio Tedesco</author><author>Yvan Torrente</author><author>Gonzalo Ugarte</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1857456</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1857456</link>
        <title><![CDATA[Biallelic RSPH4A loss-of-function variants cause primary ciliary dyskinesia in a Chinese patient]]></title>
        <pubdate>2026-07-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yu-Ting Lu</author><author>Hui-Yan Tang</author><author>Kai Chen</author><author>Ding-Yuan Lai</author><author>De-Cheng Wang</author><author>Fan Yang</author>
        <description><![CDATA[BackgroundPrimary ciliary dyskinesia (PCD) is a rare autosomal recessive disorder characterized by defective motile cilia function, affecting approximately one in 7,500 to one in 10,000 live births. Pathogenic variants in radial spoke head genes, including RSPH4A, cause PCD with distinctive central-microtubular-pair defects. However, the functional consequences of novel RSPH4A variants remain poorly characterized, limiting genetic counseling and prenatal diagnostic capabilities. This study aims to reveal the genetic etiology of PCD in an affected family and the clinical significance of the two novel RSPH4A variants identified in this PCD-affected pedigree.MethodsWe recruited a five-member Chinese family including an 11-year-old female PCD proband presenting with chronic bronchiectasis and recurrent respiratory infections. Comprehensive clinical evaluations, whole exome sequencing (WES), and Sanger sequencing were performed to identify genetic variants. Bioinformatics analyses including protein sequence alignment and structural modeling were conducted. Experimental validation employed site-directed mutagenesis, quantitative real-time PCR, and Western blotting in HEK293T cells to characterize variant effects on mRNA stability and protein expression.ResultsWES identified compound heterozygous RSPH4A variants in the proband: RSPH4A (NM_001010892.3): c.2T>C (p.Met1Thr) inherited from the mother and RSPH4A (NM_001010892.3): c.854delA (p.Lys286Serfs*22) inherited from the father, showing strict co-segregation with the disease phenotype. The c.2T>C variant disrupted the translation initiation codon, while c.854delA introduced a premature termination codon within the radial spoke head domain. Cross-species analysis demonstrated high conservation of the affected region across 15 vertebrate species. Structural modeling predicted complete loss of the radial spoke head domain in the truncated protein. Functional studies revealed that c.2T>C severely impaired protein translation despite intact mRNA levels, whereas c.854delA triggered nonsense-mediated mRNA decay and produced unstable truncated protein. Both variants resulted in substantial reduction in functional RSPH4A protein expression.ConclusionThis study identifies novel loss-of-function RSPH4A variants causing PCD through distinct molecular mechanisms, expanding the mutational spectrum of radial spoke head protein-related ciliopathies. These findings offer compelling proof in favor of a molecular diagnosis of PCD in this family and enable carrier screening for at-risk relatives. The experimental validation strategy establishes a framework for interpreting variants of uncertain significance in PCD genes, facilitating accurate prenatal diagnosis and preimplantation genetic testing to reduce the recurrence risk and birth defect incidence in PCD. Furthermore, understanding the precise functional consequences of RSPH4A variants informs genotype-phenotype correlations and may guide future development of targeted therapeutic interventions for this debilitating respiratory disorder.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1893561</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1893561</link>
        <title><![CDATA[Correction: Genetic determinants of age-related macular degeneration in Middle Eastern populations: a systematic review]]></title>
        <pubdate>2026-07-08T00:00:00Z</pubdate>
        <category>Correction</category>
        <author>Naif S. Sannan</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1901215</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1901215</link>
        <title><![CDATA[Editorial: Hepatocellular carcinoma: from bench to bedside]]></title>
        <pubdate>2026-07-07T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Evin İşcan</author><author>Aaron B. Koenig</author><author>Xiaogang Wu</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1870725</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1870725</link>
        <title><![CDATA[Modifiable risk factors and skin cancers: a multi-omics Mendelian randomization study from causal inference to drug target discovery]]></title>
        <pubdate>2026-07-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zhen Qin</author><author>Wuda Huoshen</author><author>Xueqing Li</author><author>Shiyu Li</author><author>Chen Sun</author><author>Sha Yi</author>
        <description><![CDATA[IntroductionRecent studies have linked modifiable risk factors (RFs) to melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC). This study aimed to investigate the causal relationships between 11 modifiable RFs and these skin cancers and to identify novel therapeutic targets using multi-omics approaches.MethodsExposure data were obtained from genome-wide association studies (GWAS). Mendelian randomization (MR) analyses were performed using the inverse variance weighted (IVW) method as the primary approach, and results from discovery and replication cohorts were combined by meta-analysis. Functional Mapping and Annotation (FUMA) and summary-data-based MR (SMR) were used to prioritize therapeutic targets. Drug prediction, phenome-wide association studies (PheWAS), and single-cell analyses were conducted to evaluate target druggability and biological relevance.ResultsActinic keratosis (AK) was associated with an increased risk of melanoma (OR = 1.24, 95% CI 1.07-1.43, P < 0.01), whereas alcohol consumption was negatively associated with SCC risk (OR = 0.77, 95% CI 0.62-0.95, P = 0.02). No causal relationships were observed between the investigated RFs and BCC. One potential therapeutic target for melanoma (EDEM2, PSMR = 0.03) and five candidate therapeutic targets for SCC (MAPK3, PSMR = 5.30E-04; NRBP1, PSMR = 4.32E-04; ANKK1, PSMR = 1.89E-06; IL27, PSMR = 3.04E-03; ADH5, PSMR = 0.02) were identified. Drug prediction, PheWAS, and single-cell analyses further supported the therapeutic potential of these genes.DiscussionAK appears to increase the risk of melanoma, whereas alcohol consumption may be protective against SCC. EDEM2 may represent a potential therapeutic target for melanoma, while MAPK3, NRBP1, ANKK1, IL27, and ADH5 are promising candidate targets for SCC. Further experimental and clinical studies are warranted to validate these findings.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1882818</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1882818</link>
        <title><![CDATA[Escape and evasion: when immunosurveillance of senescent cells goes wrong]]></title>
        <pubdate>2026-07-07T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Elina Shakur</author><author>Abraham Jacobs</author><author>Rituparna Ghosh</author><author>Matthew J. Yousefzadeh</author>
        <description><![CDATA[Aging involves molecular changes that can give rise to different cell fates, one of those being cellular senescence. Senescent cells stably arrest in the cell cycle and play important roles in physiological processes and can act in a tumor-suppressive manner. However, senescent cells accumulate throughout the body with both chronological and biological aging, promoting chronic inflammation and tissue dysfunction. One of the features of senescent cells is their ability to adopt a secretory phenotype, which can act as a chemotactic gradient to attract immune cells. These infiltrating immune cells are capable of recognizing senescent cells and targeting them for destruction, thus maintaining a balance between senescent cell generation and elimination. Unfortunately, with age, the immune system undergoes changes that alter functional capacity, referred to as immunosenescence. Immunosenescence impacts both innate and adaptive immune cells, impairing their protective functions, like immunosurveillance, or causing them to adopt a hyperinflammatory phenotype, which may further enhance senescent cell burden. These age-related changes in immune function can compromise immunosurveillance, further exacerbating senescent cell burden and its effects. Additionally, senescent cells themselves can modulate markers on their cell surface that make detection by immune cells more difficult and allow them to escape immune clearance. The role of the immune system in limiting senescent cell burden to maintain homeostasis and how immunosurveillance is compromised with age is explored. Furthermore, mechanisms by which senescent cells evade immunosurveillance and potential strategies to restore age-related deficits in immune cell-mediated clearance of senescent cells are also discussed.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1814500</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1814500</link>
        <title><![CDATA[Genetic profiling of healthy family members of breast and ovarian cancer patients in Estonia]]></title>
        <pubdate>2026-07-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Mikk Tooming</author><author>Kadri Rekker</author><author>Kadri Toome</author><author>Laura Roht</author><author>Piret Laidre</author><author>Olga Fjodorova</author><author>Hanno Roomere</author><author>Ülle Murumets</author><author>Ustina Šamarina</author><author>Sander Pajusalu</author><author>Riina Žordania</author><author>Kristi Tael</author><author>Eve Vaidla</author><author>Elvira Kurvinen</author><author>Neeme Tõnisson</author><author>Mihkel Ilisson</author><author>Peeter Padrik</author><author>Jaak Lehtsaar</author><author>Riina Kütner</author><author>Elen Vettus</author><author>Helen Vahar</author><author>Katrin Õunap</author><author>Tiina Kahre</author>
        <description><![CDATA[BackgroundGenetic testing for likely pathogenic/pathogenic variants (PV) in BRCA1, BRCA2, and other cancer-associated genes plays a critical role in the diagnosis, prognosis, and management of breast and ovarian cancer (BCOC). Extending testing to healthy family members (HFM) of affected individuals enables early prevention strategies and timely referrals for enhanced screening, thereby improving cancer risk management. This study aimed to characterize the demographic profile and genetic findings among HFMs of BCOC patients in Estonia within routine clinical practice.MethodsA retrospective analysis was conducted on 3,472 HFMs who underwent genetic testing. Demographic data were collected, and the presence of PVs was assessed. Statistical comparisons were made between individuals with and without known familial PVs, and between male and female participants, using descriptive statistics and proportion comparisons.ResultsOf the 3,472 HFMs tested, 87.6% were female and 12.4% male, with a mean age of 41.1 ± 13.0 years. Notably, 78.6% were younger than 51 years, the typical age for initiating standard screening. PVs were identified in 683 individuals (19.7%). Among those with a known familial PV (n = 1,009), 41.8% were carriers, compared to 8.0% among those without a known familial PV (n = 2,408). Males were more likely to be tested when a familial PV was known (26.6%) than when it was not (6.6%), and 34.0% of tested males were PV carriers. PVs were found in 23 different genes, with BRCA1/2 accounting for 58.4% of all PVs, followed by ATM, BRIP1, CHEK2, and PALB2.ConclusionThe findings highlight the value of genetic testing in identifying at-risk individuals among HFMs of BCOC patients. The predominance of BRCA1/2 variants and the significant detection rate among younger individuals underscore the importance of early testing. The expansion of HFM testing in Estonia reflects increased public awareness and clinical integration of genetic risk assessment in cancer prevention strategies.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1653878</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1653878</link>
        <title><![CDATA[Genome-wide association study of the reproductive, body size, and carcass-related latent and directly measured traits in admixed beef heifers]]></title>
        <pubdate>2026-07-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Muhammad Anas</author><author>Bin Zhao</author><author>Haipeng Yu</author><author>Carl R. Dahlen</author><author>Kendall C. Swanson</author><author>Kris A. Ringwall</author><author>Lauren L. Hulsman Hanna</author>
        <description><![CDATA[Latent variables derived through factor analysis reveal the underlying biological traits (UBT) in organisms. However, research on UBT development and genomic applications in beef cattle is limited. This study aimed to model previously identified economically important UBT in genome-wide association studies (GWAS) using univariate and multivariate approaches. Data on 35 traits related to the body size, reproduction, and carcass characteristics from 297 admixed beef heifers were analyzed using two models. Due to the sample-size constraints, the two models utilized were: 1) all traits included (n = 161) and 2) optimized record numbers by segregating the reproductive and body size traits (n = 297) from carcass traits (n = 161). The UBT identified from a prior study included body size (BS) and body composition (BC) in model 1 and BS, ovary size (OS), and yield grade (YG) in model 2, along with non-contributing but economically relevant traits such as body density (DENS) and intra-muscular fat (IMF). Genotypically adjusted causal networks showed that BS influenced BC (model 1) and OS (model 2). Multi-trait and structural equation modeling (SEM) GWAS approaches were used to integrate BS with BC and OS, while univariate modeling was used for unrelated UBT and direct traits, such as YG, IMF, and DENS. Across all the approaches, 1,911 SNP from nine different regions were identified and mapped to 98 features, including genes, pseudogenes, and multiple non-coding and translational RNA. Enrichment analysis highlighted extracellular matrix-receptors, HERC family genes in cellular growth, desmosomes in morphogenesis, and energy metabolism related to PIGY genes. Genes linked to muscle and carcass traits, including FAM184B, NCAPG, and LCORL, were also identified. The heritability of UBT (0.46–0.84) was higher than that of individual traits, particularly for reproductive and carcass-related traits. This study provides insights into the relationships of body and carcass-oriented traits in admixed beef heifers that are directly relevant to phenotyping and genetic evaluations being conducted in the beef industry.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1874675</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1874675</link>
        <title><![CDATA[Remodelin treatment reshapes inflammation-related transcriptomic signatures in experimental thalamic hemorrhage]]></title>
        <pubdate>2026-07-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zi Wang</author><author>Yaqun Li</author><author>Yinggang Xiao</author><author>Ju Gao</author><author>Tianfeng Huang</author>
        <description><![CDATA[BackgroundThalamic hemorrhage is a severe subtype of intracerebral hemorrhage in which secondary neuroinflammation contributes to tissue injury and neurological deterioration. N-acetyltransferase 10 (NAT10), an RNA N4-acetylcytidine writer, has been implicated in inflammatory regulation and neurological disorders. However, inflammation-related transcriptomic changes associated with Remodelin treatment after thalamic hemorrhage remain unclear.MethodsmRNA transcriptome sequencing was performed on perilesional thalamic tissues from control, thalamic hemorrhage model, and Remodelin-treated mice. Differentially expressed genes were identified for the Model versus Control and Remodelin Intervention versus Model comparisons. Genes showing opposite directions of regulation across the two comparisons were defined as Remodelin-reversed differentially expressed genes. GeneCards-derived inflammation-related genes were converted to mouse orthologs and intersected with Remodelin-reversed genes. Protein-protein interaction analysis, Gene Ontology and KEGG enrichment analyses, gene set enrichment analysis, immune-cell signature estimation, and transcription factor/miRNA regulatory network prediction were performed. Key candidates were validated by quantitative RT-PCR.ResultsRNA-seq identified 499 differentially expressed genes in the Model versus Control comparison and 664 in the Remodelin Intervention versus Model comparison. Among 46 shared differentially expressed genes, 42 showed opposite-direction regulation. Ortholog-corrected screening identified 9 Remodelin-reversed inflammation-related candidates: Cxcl1, Ccl2, Ncf4, Ptx3, Pomc, Masp2, Tnfrsf8, Card9, and Gpr84. Enrichment analyses linked these genes mainly to leukocyte- and neutrophil-mediated immunity, tumor necrosis factor production, cytokine-cytokine receptor interaction, IL-17 signaling, TNF signaling, chemokine signaling, and NOD-like receptor signaling. Protein-protein interaction analysis highlighted Ccl2, Cxcl1, and Pomc as prominent candidate nodes. qRT-PCR using independent biological samples provided preliminary transcript-level support for Remodelin-associated changes in Cxcl1 and Pomc expression, whereas Ccl2 was increased after hemorrhage but was not significantly reduced by Remodelin.ConclusionThis study identifies Remodelin-reversed inflammation-related transcriptomic signatures in experimental thalamic hemorrhage. Cxcl1 and Pomc represent the most consistently supported Remodelin-responsive transcriptomic candidates, whereas Ccl2 appears to be a hemorrhage-associated inflammatory hub without robust reversal at the examined time point. These findings provide an exploratory neurogenomic framework for investigating inflammation-related transcriptional remodeling associated with Remodelin treatment.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1828450</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1828450</link>
        <title><![CDATA[Genomic innovations in cancer prevention, diagnosis, prognosis and precision therapeutics]]></title>
        <pubdate>2026-07-06T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Hanumappa Ananda</author><author>Sadhu R. Sahana</author><author>Shruthi R. Murthy</author><author>Amrutha N. Kunnath</author><author>Akila Prashant</author><author>Jussuf T. Kaifi</author><author>Pura K. Kiran</author><author>Kanve N. Suvilesh</author>
        <description><![CDATA[Cancer research has undergone a transformative change with the advent of high-throughput genomic technologies. Advances in next-generation sequencing accelerated the identification of somatic and germline alterations that drive tumorigenesis enabling the transition from traditional histology-based cancer classification to molecularly informed precision oncology. Large-scale sequencing initiatives and clinical genomic profiling facilitated the development of companion diagnostic assays and targeted therapies. Beyond targeted therapies, genomic innovations have also catalyzed the emergence of novel therapeutic strategies including immunogenomics-driven immunotherapies, RNA-based therapeutics, cancer vaccines and genome editing technologies based on CRISPR-Cas systems. This review summarizes the major technological developments in cancer genomics, including sequencing platforms, transcriptomic profiling, liquid biopsy, and functional genomic screening, and highlights the utility of these innovations in discovery of actionable biomarkers and next-generation therapeutic strategies. Collectively, these advances underscore the central role of genomic technologies in driving the evolution of precision oncology toward more personalized and effective cancer treatment strategies.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1874969</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1874969</link>
        <title><![CDATA[Mitochondrial DNA reveals high maternal diversity within a weak breed structure in native Kazakhstani horses]]></title>
        <pubdate>2026-07-06T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Daniya Ualiyeva</author><author>Kairat Dossybayev</author><author>Tilek Kapassuly</author><author>Altynay Kozhakhmet</author><author>Zhassulan Kozhanov</author><author>Kirill Kryukov</author><author>Masanori Arita</author><author>Merey Torekhanov</author><author>Aibyn Torekhanov</author>
        <description><![CDATA[Understanding the genetic diversity and evolutionary history of domestic horses (Equus caballus) is essential for reconstructing their population dynamics and origins. In this study, we analyzed mitochondrial DNA variation (COI and cytb) in six Kazakhstani horse populations representing four native breeds (Kazakh, Kostanay, Adai, and Mugalzhar) to assess genetic diversity, population structure, and evolutionary relationships within a broader phylogenetic framework. High haplotype diversity combined with low nucleotide diversity revealed population expansion and admixture. Population structure analyses revealed weak genetic differentiation and a lack of breed-specific structuring, with most variation occurring within populations. Phylogenetic reconstruction and haplotype network analyses showed that Kazakhstani horses are interspersed among global domestic lineages, reflecting extensive historical connectivity and admixture. Demographic analyses based on neutrality tests and mismatch distributions support signals of ancient population expansion, while the multimodal distribution patterns suggest a complex demographic history involving population substructure and multiple expansion events rather than a single, sudden expansion. Times since expansion were calculated to be around 205 Kya. Divergence time estimates place the diversification of all caballine horses, including Kazakhstani horses, within the Pleistocene (0.89 Mya) with the majority of them grouping with different horse breeds across the world. These results indicate that the maternal genetic structure of Kazakhstani horses has been shaped by a combination of ancient evolutionary processes and more recent demographic dynamics, including recurrent gene flow across Eurasian steppe environments. Overall, this study highlights a reticulate evolutionary history of domestic horses, emphasizing the role of long-term connectivity and population expansion in shaping mitochondrial diversity.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1841048</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1841048</link>
        <title><![CDATA[Effects of prenatal transportation stress on liver gene expression in male and female Brahman calves]]></title>
        <pubdate>2026-07-06T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sierra R. Sebesta</author><author>Emilie C. Baker</author><author>Kubra Z. Cilkiz</author><author>Rodolfo C. Cardoso</author><author>Thomas B. Hairgrove</author><author>Charles R. Long</author><author>Ronald D. Randel</author><author>Thomas H. Welsh</author><author>David G. Riley</author>
        <description><![CDATA[The liver is a central regulator of metabolic and endocrine functions that support fetal growth and postnatal development. Prenatal stress can reprogram hepatic development in the offspring, potentially causing long-term changes in metabolism and production efficiency. However, the influence of prenatal stress on hepatic molecular function and resulting phenotypes in beef cattle remains poorly understood. Therefore, the objectives of this study were to evaluate phenotypic traits and liver tissue gene expression in Brahman heifer and bull calves from prenatal transportation stress (PNS) and control (Control) treatment groups. One group of pregnant Brahman cows were transported for a 2-h period every 20 (±5) d from 60 to 140 days of gestation. Another group of pregnant Brahman cows served as Control. Thirty-two calves, eight heifer and eight bull calves from the PNS and Control groups, respectively, were utilized. Calves were weighed at approximately 25 (±2) d of age. The following day, calves were euthanized, and liver tissues were harvested. Phenotypic traits evaluated include birth weight, harvest weight, liver weight, pen score, and liver weight:harvest weight. Interaction of sex and treatment did not explain substantial variation for any trait (P > 0.28). Sex influenced birth weight, harvest weight, liver weight (P < 0.05), and treatment influenced liver weight:harvest weight (P < 0.10). Linear regression coefficients of traits on calf age as a linear covariate were not different from 0 (P > 0.41). Controlling false discovery rate at 0.10, there were no differentially expressed genes for PNS relative to Control and 13 differentially expressed genes for male relative to female comparisons. No genes were found to be differentially expressed across all comparisons. It is possible that the few differences between sexes and treatments may be due to relatively small sample sizes or to an unknown adaptation mechanism to the stress prenatally induced by this young age. Heightening the severity of prenatal transportation stress through increased duration or frequency of transportation may result in more differentially expressed genes.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1818099</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1818099</link>
        <title><![CDATA[Complementary structure of statistical significance and predictive relevance in explainable machine learning–based transcriptomic tissue classification of Hanwoo cattle]]></title>
        <pubdate>2026-07-06T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Dogyeong Lee</author><author>Junyoung Lee</author><author>Inchul Choi</author><author>Dajeong Lim</author>
        <description><![CDATA[Understanding tissue-specific transcriptomic structures in livestock is essential for elucidating the molecular basis of economically important traits. Conventional differential gene expression analysis efficiently identifies genes with large average expression differences but does not fully capture multivariate expression structures and gene-gene interaction patterns that define tissue identity. In this study, we developed an explainable machine learning framework to classify seven Hanwoo cattle tissues using RNA sequencing data and to systematically compare the relative contributions of statistical and model-derived signals. A Random Forest–based one-versus-rest classification model was trained on 130 Hanwoo transcriptomes and externally validated using 231 independent Bos taurus samples derived from heterogeneous public datasets following reference-based batch correction. Repeated balanced validation demonstrated stable generalization performance, achieving a mean accuracy of 0.907 and a macro-average area under the receiver operating characteristic curve of 0.963. A comparative analysis of gene sets selected by differential expression analysis, genes prioritized by model-based feature attribution, their union, and randomly selected genes within the same classification framework revealed that strongly differentially expressed genes form the primary discriminatory structure for tissue classification. In contrast, integration of model-prioritized genes enhanced classification performance, particularly for biologically related tissues, whereas randomly selected genes produced reduced and unstable predictive performance. Model interpretation further revealed that highly contributory genes were consistent with known tissue-specific biological functions and exhibited non-linear, expression-dependent contribution patterns shaped by coordinated multigene contexts. These findings indicate that tissue identity is supported by a hierarchical transcriptional structure in which dominant differential signals establish primary class boundaries and multivariate interaction patterns refine decision surfaces. The proposed framework provides an interpretable strategy for distinguishing statistical significance from predictive relevance in high-dimensional transcriptomic data and offers practical implications for molecular marker development in livestock genomics and breeding programs.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1850219</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1850219</link>
        <title><![CDATA[CNNKSCEC: a deep learning-based framework for chromatin loop prediction with multi-source feature integration]]></title>
        <pubdate>2026-07-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Junfeng Wang</author><author>Bingzi Zheng</author><author>Lili Wu</author><author>Xiaoyan Liu</author><author>Haixia Zhai</author><author>Junwei Luo</author>
        <description><![CDATA[MotivationChromatin in the cell nucleus adopts a complex three-dimensional (3D) structure shaped by folding and interactions, with chromatin loops serving as fundamental organizational units. Accurate loop prediction is essential for understanding gene regulation and disease mechanisms. However, existing chromatin loop prediction methods still face challenges in noise handling, data imbalance, and multi-omics integration.ResultsIn this study, we present CNNKSCEC, a deep learning-based framework for chromatin loop prediction via multi-source feature fusion. The model integrates Hi-C and DNase-seq data into a dual-channel feature matrix as input. It employs a three-stage iterative feature extraction framework consisting of a dual-branch convolutional module (CNNC), a SCConv module combining SRU and CRU, and an ECHybridAddition module integrating both ECA and CBAM attention mechanisms. This design enables iterative multi-scale feature extraction and enhances the feature representation capability of the input matrix. Finally, the model uses a fully connected layer for classification, generating candidate chromatin loops with prediction scores, and filters out false candidates through density-based clustering. In the experiments, we compare CNNKSCEC with existing chromatin loop prediction methods, and the results demonstrate that the approach outperforms other methods overall in terms of performance. The code is available from https://github.com/zhengbingzi/CNNKSCEC.git.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1795267</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1795267</link>
        <title><![CDATA[Identification of potential biomarkers and therapeutic targets for osteoarthritis associated with arginine and proline metabolism based on transcriptome sequencing and bioinformatics]]></title>
        <pubdate>2026-07-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Xiao-Hua Chen</author><author>Jun Liu</author><author>Ling Qiu</author><author>Yang Zhan</author><author>Zhuo-Ming Zheng</author><author>Peng Chen</author><author>You-Xin Su</author><author>Jie-Mei Guo</author><author>Sheng-Jian Weng</author>
        <description><![CDATA[Background and ObjectivesOsteoarthritis (OA) is a chronic degenerative joint disease. Approximately 300 million people worldwide suffer from OA, which shows a high incidence in middle-aged and elderly populations, with a prevalence of 50% among individuals aged over 60 years. Its core clinical symptoms consist of joint pain, swelling, and dysfunction. Studies have shown that arginine and proline metabolism play an important role in the pathogenesis and progression of OA, but the specific mechanism is still unclear. This study aimed to identify biomarkers and drug therapeutic targets for OA associated with arginine and proline metabolism.MethodsSynovial tissues of healthy individuals and OA patients were collected for transcriptome sequencing, and the differentially expressed genes (DEGs) between the two groups were compared and analyzed. Arginine and proline metabolism-related genes (APRGs) were obtained from the molecular signature database. The candidate genes were identified by weighted gene co-expression network analysis (WGCNA), and then gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis and protein-protein interaction (PPI) were performed. Expression validation was performed using machine learning and ROC analysis to identify key genes. Gene set enrichment analysis (GSEA), immune cell infiltration, and drug prediction were used to explore the mechanism of key genes in OA and potential therapeutic drugs. Finally, clinical samples were experimentally validated through RT-qPCR experiments.ResultsTwo hub genes (MYOM2 and TCAP) involved in arginine and proline metabolism were identified. A nomogram constructed based on these genes indicated that MYOM2 and TCAP are key and reliable predictors for osteoarthritis risk. The RT-qPCR experiments on clinical samples showed that the expression levels of these hub genes were significantly downregulated in the synovial tissue of OA patients (p < 0.05), suggesting their potential as diagnostic biomarkers.DiscussionMYOM2 and TCAP are hub genes in OA metabolism with arginine and proline, which may become new diagnostic markers and potential therapeutic targets for OA.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1828693</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1828693</link>
        <title><![CDATA[Application of acute myocardial infarction-related key genes in noninvasive diagnosis: a comprehensive analysis based on transcriptome and single-cell transcriptome]]></title>
        <pubdate>2026-07-02T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Mingbin Xie</author><author>Yuanhong Wu</author><author>Xinyao Jin</author><author>Fengchun Jiang</author><author>Qiang Yao</author>
        <description><![CDATA[BackgroundAcute myocardial infarction (AMI), a highly fatal cardiovascular emergency, presents ongoing clinical challenges in both early diagnosis and the elucidation of its associated immuno-inflammatory processes. By integrating multi-omics data, this research seeks to identify novel diagnostic biomarkers and uncover their potential mechanisms in AMI.MethodsBy integrating transcriptomic data, core genes linked to AMI were identified by differential expression and weighted gene co-expression network analysis (WGCNA). A multivariate logistic regression diagnostic model was constructed based on these genes, and its diagnostic efficacy was evaluated with receiver operating characteristic (ROC) curve analysis. In vitro, an oxygen-glucose deprivation/reperfusion (OGD/R) model was generated in AC16 human cardiomyocytes. We used lentiviral transduction to knock down the key gene. Cell proliferation was evaluated by Cell Counting Kit-8 (CCK-8) assay, apoptosis levels were measured by Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining and flow cytometry, and the mRNA and protein expression of key genes were detected with qRT-PCR and Western blot.ResultsThree AMI core genes (PLA2G15, ADAP2, and FAM20C) were successfully identified. The diagnostic model established via multifactorial logistic regression exhibited satisfactory discriminatory power. In vitro experiments confirmed that ADAP2 expression was markedly upregulated in the OGD/R model. Knocking down ADAP2 effectively alleviated OGD/R-induced suppression of cell proliferation, apoptosis enhancement, and expression increase of inflammatory factors (TNF-α, IL-6, IL-1β). Mechanistically, ADAP2 knockdown inhibited the expression of key proteins in the IL-17 signaling pathway (IL-17A, IL-17RA, ACT1). Exogenous addition of rhIL-17A reversed the protective effect of ADAP2 knockdown against cellular injury.ConclusionThe combined diagnostic model derived from the AMI core genes PLA2G15, ADAP2, and FAM20C exhibited robust diagnostic power for noninvasive diagnosis. ADAP2 can influence AMI-induced myocardial injury through the IL-17 signaling pathway.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1841116</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1841116</link>
        <title><![CDATA[Homozygous familial hypercholesterolemia, experience with Evinacumab treatment in two Mexican pediatric patients: case report]]></title>
        <pubdate>2026-07-02T00:00:00Z</pubdate>
        <category>Case Report</category>
        <author>Ramón Madriz Prado</author><author>Yazmín Guadalupe Ríos Solís</author><author>Diana Estefanía Guerrero Dávila</author><author>Lucía Molina Fernández</author><author>Omar Spencer Aguilar Reyes</author><author>Ilse Ordóñez</author><author>Leticia Ramos</author><author>Marisol González</author>
        <description><![CDATA[Homozygous familial hypercholesterolemia (HoFH) is a rare and life-threatening genetic disorder characterized by extremely elevated low-density lipoprotein cholesterol (LDL-C) levels from birth, leading to accelerated atherosclerotic cardiovascular disease and premature mortality. Conventional lipid-lowering therapies often provide insufficient LDL-C reduction, particularly in patients with minimal or absent LDL receptor (LDLR) function. Evinacumab, an angiopoietin-like protein 3 (ANGPTL3) inhibitor, lowers LDL-C independently of LDLR activity and represents a major therapeutic advance. Here we report two Mexican pediatric patients with HoFH who demonstrated profound LDL-C reductions following initiation of Evinacumab (59% and 68% within the first month of treatment), exceeding reductions observed in pivotal clinical trials. Both patients maintained sustained LDL-C reductions during long-term follow-up (up to 22 months). Importantly, temporary treatment interruption in both cases due to administrative and supply related difficulties limited access to Evinacumab was associated with marked rebound hypercholesterolemia. Reinitiation of therapy led to rapid and substantial lipid reduction, demonstrating a clear dechallenge–rechallenge effect and confirming the relevance of a continuous pharmacologic treatment with ANGPTL3 inhibition. Serial vascular imaging in one patient revealed partial regression of subclavian and carotid artery stenosis, as well as reduced aortic wall thickening following sustained LDL-C reduction; adding evidence to the recently described vascular improvement associated with Evinacumab therapy in pediatric HoFH. Both patients also experienced clinically meaningful improvements in quality of life, and treatment was well tolerated without serious adverse events.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1865257</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1865257</link>
        <title><![CDATA[Disease-predominant loci across Alzheimer’s disease, Parkinson’s disease and Lewy body dementia: evidence from the UK Biobank prospective cohort, conditional GWAS and colocalization]]></title>
        <pubdate>2026-07-02T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ying Zhang</author><author>Zhishuai Zhang</author><author>Shizheng Qiu</author><author>Yang Hu</author>
        <description><![CDATA[BackgroundAlzheimer’s disease (AD), Parkinson’s disease (PD) and Lewy body dementia (LBD) overlap clinically, pathologically and genetically, complicating interpretation of cross-disorder genome-wide association study (GWAS) signals.MethodsWe analysed 322,963 UK Biobank participants with bidirectional time-varying Cox models, one-year and two-year lag analyses, and competing-risk sensitivity models to quantify AD-PD clinical co-occurrence. We then analysed European-ancestry AD, PD and LBD GWAS summary statistics using linkage disequilibrium score regression (LDSC), GCTA-mtCOJO/GSMR, MAGMA, stratified LDSC, brain eQTL/mQTL SMR with HEIDI filtering, and Bayesian colocalization for selected methylation probes. Conditional loci were compared with original GWAS loci to separate shared liability from retained disorder-predominant associations.ResultsPD was associated with subsequent AD (fully adjusted HR 2.27, 95% CI 1.94–2.65; P = 6.40E-25), and AD was associated with subsequent PD (HR 3.14, 95% CI 2.56–3.85; P = 2.10E-28). Lag and competing-risk sensitivity analyses remained concordant. LDSC estimated positive genetic correlations for AD-PD (rg = 0.20; P = 0.0086) and PD-LBD (rg = 0.61; P = 0.0005). Conditioning reduced genome-wide significant loci from 14 to 9 for AD, from 24 to 21 for PD and from 5 to 2 for LBD. Retained loci included AD signals near CR1, BIN1, CLU, SPI1, MS4A, PICALM, ABCA7 and APOE; PD signals near GBA, NUCKS1, TMEM163, STK39, GAK/TMEM175, BST1, SNCA, LRRK2, MAPT and RIT2; and LBD signals near SNCA/MMRN1 and APOE. MAGMA and S-LDSC highlighted amyloid, lipid, immune, synaptic-vesicle and brain-tissue enrichment patterns. Brain QTL analyses prioritized retained eQTL and mQTL signals, and colocalization supported shared PD-GWAS/mQTL signals at HLA-DRB5, ARHGAP27, CRHR1, MAPT and KANSL1.ConclusionAD and PD show bidirectional clinical co-occurrence, whereas conditional genetic analyses retain a smaller set of disease-predominant loci and regulatory signals across AD, PD and LBD. These findings refine cross-disorder interpretation and nominate loci for independent genetic and functional validation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1874960</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1874960</link>
        <title><![CDATA[S100A9 as a shared biomarker and mediator of metabolic dysfunction in peripheral artery disease and sarcopenia]]></title>
        <pubdate>2026-07-02T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yaming Guo</author><author>Wenxin Zhao</author><author>Hai Feng</author><author>Yongjun Li</author>
        <description><![CDATA[BackgroundsPeripheral artery disease (PAD) frequently causes to persistent functional impairment in skeletal muscle even after successful revascularization, implicating non-ischemic pathological mechanisms. Sarcopenia, a myopathy characterized by progressive loss of muscle mass, strength, and function—shares these non-ischemic features and affects approximately one-third of PAD patients, yet the molecular basis of their comorbidity remains poorly defined.MethodsThree transcriptome datasets (GSE120642, GSE181930, and GSE226151) were included in the analysis, covering skeletal muscle samples from peripheral artery disease (PAD) and sarcopenia. Weighted gene co-expression network analysis (WGCNA) was performed independently for each disease cohort, followed by parallel feature selection using three machine learning algorithms (LASSO, Random Forest, and Boruta) to identify shared diagnostic biomarkers. Immune cell infiltration was deconvoluted using CIBERSORT. Drug-gene interaction analysis was conducted via DGIdb. The functional role of the lead candidate S100A9 was validated by untargeted metabolomic profiling of C2C12 myoblasts treated with recombinant S100A9.ResultsSeventy-six overlapping disease-associated genes were identified from WGCNA, and five core diagnostic biomarkers—BCKDHB, PIM1, JAML, NFE2, and S100A9 — were selected through three-way machine learning consensus. Enrichment analyses revealed shared involvement of innate immune activation, granulocyte infiltration, and branched-chain amino acid (BCAA) catabolism. CIBERSORT deconvolution confirmed elevated neutrophil abundance as a convergent immune feature of both diseases. Metabolomic profiling demonstrated that recombinant S100A9 disrupted nucleotide and energy homeostasis, induced mitophagy dysregulation, and promoted oxidative stress in C2C12 myoblasts. DGIdb screening identified Paquinimod, a selective S100A9 inhibitor with Phase II clinical safety data, as a candidate for therapeutic repositioning.ConclusionThis study reveals that upregulation of skeletal muscle inflammation and abnormal branched-chain amino acid metabolism may be common features of PAD and sarcopenia. BCKDHB, PIM1, JAML, NFE2, and S100A9 were identified as common diagnostic biomarkers, and metabolomics further confirmed that S100A9 may be a potential intervention target.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1827858</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1827858</link>
        <title><![CDATA[Integrative serum metabolite prioritization and functional screening identify N-acetyl-L-glutamine as a protective candidate in premature ovarian insufficiency]]></title>
        <pubdate>2026-07-02T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Xinyue Zhang</author><author>Chen Chen</author><author>Xiaolan Zhu</author>
        <description><![CDATA[BackgroundPremature ovarian insufficiency (POI) is a major cause of female infertility and is increasingly associated with systemic metabolic dysregulation. However, whether circulating metabolic alterations contribute causally to POI development or primarily arise as secondary consequences of ovarian failure remains unclear. In this study, bidirectional Mendelian randomization (MR), cell-based screening, and exploratory target-prioritization analyses were integrated to identify POI-related metabolites and functionally relevant candidates.MethodsTwo-sample MR was performed using genome-wide association studies (GWAS) summary data for 1,400 serum metabolites/metabolite ratios and POI. After instrumental variable filtering and harmonization, 1,352 exposures with valid inverse-variance weighted (IVW) estimates were retained for forward MR and multiple-testing correction. Both Benjamini–Hochberg false discovery rate (FDR) and Bonferroni correction were applied. Reverse MR was then conducted as a secondary directionality analysis to assess whether genetic liability to POI was also associated with circulating metabolic alterations. Experimentally tractable metabolites were screened in cyclophosphamide (CTX)-injured KGN cells using CCK-8 assays and Western blotting. For the prioritized metabolite, further functional validation was performed using SA-β-gal staining, ROS detection, and JC-1 assays. Proteome-wide MR, colocalization analysis, summary-data-based MR (SMR), drug prediction, and molecular docking were subsequently conducted as exploratory downstream analyses.ResultsAmong the 1,352 analysable exposures, 54 showed nominal associations with POI at PIVW < 0.05. After FDR and Bonferroni correction, sphinganine-1-phosphate remained the only metabolite that reached multiple-testing-corrected significance and was positively associated with POI risk, suggesting that it may represent a risk-associated metabolic candidate. Reverse MR identified exploratory POI-to-metabolite associations for six metabolites, indicating that genetic liability to POI may also be linked to systemic metabolic alterations. The experimental screening aimed to identify protective metabolites; therefore, N-acetyl-L-glutamine was prioritized from nominal inverse MR signals on the basis of its protective direction, glutamine-related identity, biological plausibility, and feasibility for cell-based assays. Among the five screened metabolites, N-acetyl-L-glutamine had the most consistent protective effect in CTX-injured KGN cells, attenuating p21 and p53 upregulation, reducing the number of SA-β-gal-positive cells and the accumulation of ROS, and partially restoring the mitochondrial membrane potential. Downstream analyses identified LILRB1 as an exploratory candidate protein linked to N-acetyl-L-glutamine levels that warrants further investigation, and cianidanol as a computational lead requiring functional validation.ConclusionThis study identifies N-acetyl-L-glutamine as a biologically plausible and experimentally supported protective metabolite candidate that attenuates CTX-induced senescence, oxidative stress, and mitochondrial dysfunction in granulosa-like cells. By integrating metabolome-wide MR with bidirectional analyses, our findings support a metabolite-centred framework for investigating POI-related metabolic vulnerability and oncofertility-related ovarian injury. Sphinganine-1-phosphate emerged as a multiple-testing-corrected risk-associated metabolite, whereas LILRB1 and cianidanol generated exploratory hypotheses for future mechanistic and pharmacological studies.]]></description>
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