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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>
        <generator>Frontiers Feed Generator,version:1</generator>
        <pubDate>2026-06-06T06:40:41.672+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1825728</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1825728</link>
        <title><![CDATA[SIGMA: self-supervised inference of gene networks via masked auto-encoding]]></title>
        <pubdate>2026-06-05T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Qian Wang</author><author>Ziyi Zhang</author><author>Nan-Qing Liao</author><author>Shibin Yang</author><author>Zehua He</author>
        <description><![CDATA[ObjectivesInferring gene regulatory networks (GRNs) from expression profiles is essential for identifying critical genes within complex disease pathways. However, current machine learning-based GRN inference methods face two challenges. Unsupervised methods struggle to achieve satisfactory accuracy in inference, while supervised methods are limited by the scarcity of high-quality interaction labels. Further, existing models demonstrate significant shortcomings when it comes to transferring reasoning to other GRN task subtypes. These issues affect GRN inference and hinder the ability to discover new regulatory patterns.FindingsTo address these challenges, we have developed SIGMA: a transformer-based framework that uses self-supervised learning to pretrain the encoder on expression profiles. This alleviates the need for high-quality labels. During pretraining, it converts gene expression pairs into non-overlapping patches, and randomly masks some of these patches. This forces the encoder to extract correlation representations from the unmasked patches without label guidance, enabling the decoder to reconstruct the masked patches while preserving their similarity. Experiments have demonstrated that the pretrained encoder can accurately infer GRNs and be used to infer other subtypes, thereby reducing reliance on labels. Benchmark tests on human and mouse datasets have shown that SIGMA outperforms state-of-the-art methods. When applied to breast cancer datasets, SIGMA produced predictions that were consistent with established networks and identified candidate interactions that were not present in the gold-standard networks. Further investigation and experimental validation of these relationships is warranted.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1765512</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1765512</link>
        <title><![CDATA[Exploration of candidate genes associated with rare SNVs in pulmonary stenosis using whole-exome sequencing and machine learning]]></title>
        <pubdate>2026-06-05T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yuting Liu</author><author>Sun Chen</author><author>Yongzhou Liang</author><author>Suqiu Huang</author><author>Bingyao Zhang</author><author>Shuqi Liu</author><author>Ling Yang</author><author>Liqing Zhao</author><author>Rang Xu</author><author>Yurong Wu</author>
        <description><![CDATA[BackgroundPulmonary stenosis (PS) is a common form of congenital heart disease (CHD) that impairs cardiopulmonary function and can be life-threatening in severe cases. As a complex polygenic disorder, the genetic basis of PS remains incompletely understood.MethodsRare pathogenic single nucleotide variants (SNVs) were identified from whole-exome sequencing (WES) data of 185 sporadic PS patients and 100 healthy controls using multiple pathogenicity-filtering strategies. Gene-level burden test was performed, with complementary analysis using sequence kernel association test–optimal (SKAT-O). Three machine learning algorithms—least absolute shrinkage and selection operator (LASSO), random forest (RF), and extreme gradient boosting (XGBoost)—were applied to prioritize candidate genes. The overlap between machine learning–based selections and burden test results was systematically evaluated. Final candidate genes were further prioritized through protein–protein interaction (PPI) network analysis, and their expression in human pulmonary artery endothelial cells (HPAECs) was assessed by reverse transcription quantitative polymerase chain reaction (RT-qPCR).ResultsComparative analyses showed that different machine learning algorithms exhibited distinct feature selection patterns, with RF demonstrating the highest concordance with burden test results. A total of 17 candidate genes were prioritized (HAND2, SETD2, KDM6B, NCOR2, FLNB, NOTCH3, DNAH5, PLEC, COL5A1, KIF7, CLTCL1, XRN1, ITPR2, SCRIB, PYGB, IQGAP3, and SHC2).ConclusionThese findings indicate that machine learning can complement conventional gene-based analyses of WES data. This study provides a set of candidate genes associated with PS and offers a basis for further investigation of its genetic architecture.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1809097</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1809097</link>
        <title><![CDATA[Diagnostic yield of long-read sequencing for rare diseases: a systematic review]]></title>
        <pubdate>2026-06-05T00:00:00Z</pubdate>
        <category>Systematic Review</category>
        <author>Amal Abdulsalam Ibrahim</author><author>Khalid A. Fakhro</author><author>Atiyeh M. Abdallah</author>
        <description><![CDATA[BackgroundNearly half of patients with rare genetic disorders remain undiagnosed, which may in part be due to limitations of current short-read sequencing (SRS) approaches in detecting complex genomic alterations. Long-read whole genome sequencing (lrWGS) technologies can address these limitations through enhanced detection of structural variants (SVs), repetitive regions, and epigenetic changes.MethodsTo evaluate the diagnostic yield of lrWGS in patients with rare genetic diseases receiving inconclusive or negative results from standard testing, we searched the PubMed, Science Direct, Scopus, and ProQuest databases to July 2025 for studies applying lrWGS to unresolved rare disease cases and reporting diagnostic outcomes. Risk of bias was assessed using the QUADAS-2 tool.ResultsNine studies involving 646 previously unresolved cases that underwent lrWGS met the inclusion criteria. Of these, 29 individuals (24 unique diagnoses involving 25 genes) received a definitive diagnosis through lrWGS, a diagnostic yield of 4.5%. SVs accounted for the majority of identified variants (41.67%), followed by combined SV/single-nucleotide variants (20.83%), methylation changes (16.67%), and other variant types (copy number variations, indels, and tandem repeats). Most detected variants were in regions typically inaccessible to short-read whole-exome sequencing (WES). lrWGS also enabled phasing and methylation analysis in a single assay, which was valuable for compound-heterozygosity detection and diagnostic interpretation.ConclusionlrWGS shows clear potential for improving diagnostic rates in previously unresolved rare disease cases, particularly when applied after WES and combined with advanced tools such as phasing and methylation profiling. As technologies evolve and become more accessible, lrWGS may increasingly become a first-tier diagnostic approach, especially in phenotypically complex conditions.Systematic Review Registrationhttps://osf.io/y5azb/overview, identifier 10.17605/OSF.IO/Y5AZB.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1840344</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1840344</link>
        <title><![CDATA[Genetic heterogeneity correlated with phenotypic variability in 6 Chinese families with Alport syndrome]]></title>
        <pubdate>2026-06-05T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Jinghan Gao</author><author>Huan Zhou</author><author>Li Zhang</author><author>Zihan Su</author><author>Shiguo Liu</author>
        <description><![CDATA[BackgroundAlport syndrome (AS) is a common hereditary kidney disease, mainly characterized by hematuria, progressive renal dysfunction, sensorineural hearing loss, and ocular symptoms, which significantly impacts patients the quality of life patients’ quality of life and lifespan. However, due to its atypical and heterogeneous clinical features, the relationship between genotype and phenotype remains complex, posing AS diagnostic challenges.MethodGenetic variants were screened by whole exome sequencing (WES) followed by verification with Sanger sequencing. Genotype-phenotype analysis was also conducted, and a novel variant (COL4A3 c.3203G>A) was selected for in vitro functional studies.ResultsWe identified seven variants in six families, including autosomal dominant (COL4A3 c.352G>A, COL4A4 c.71 + 1G>C), autosomal recessive (COL4A3 c.2736dupA, c.4235G>T), X-linked (COL4A5 c.512del,COL4A5 c.3053del), and one spontaneous variant (COL4A3 c.3203G>A). Functional studies on the novel variants (COL4A3 c.3203G>A) demonstrated a significantly decrease significant decrease in the mRNA expression level in HEK293 T cells and the weakened cell migration ability.ConclusionWe identified four novel pathogenic changes causing AS, revealing the genetic heterogeneity of AS and expanding its genotype phenotype spectrum, holding significant implications for prenatal diagnosis.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1764943</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1764943</link>
        <title><![CDATA[HMMR as a robust prognostic biomarker correlates with immune infiltration and cell cycle pathways in oral squamous cell carcinoma: a multi-cohort bioinformatics analysis based on TCGA and GEO databases]]></title>
        <pubdate>2026-06-05T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Lingling Liu</author><author>Shiyan Chen</author><author>Hongxun Gong</author><author>Xingfeng Qi</author><author>Maoxin Wang</author>
        <description><![CDATA[IntroductionOral squamous cell carcinoma (OSCC), a prevalent head and neck malignancy with complex molecular pathogenesis and poor prognosis, remains a critical clinical challenge. This study aimed to elucidate the role of hyaluronic acid mediated motility receptor (HMMR) in OSCC progression and evaluate its potential as a diagnostic and prognostic biomarker.MethodsTranscriptomic data was integrated from the TCGA OSCC cohort and two independent GEO cohorts (GSE37991, GSE41613). Differential expression analysis was performed using DESeq2. Common differentially expressed genes (DEGs) were identified via Venn diagram analysis, followed by functional enrichment analysis using the STRING database. Univariate and multivariate Cox regression analyses were conducted with the survival package to identify prognostic markers, and the predictive performance was evaluated by receiver operating characteristic (ROC) analysis. Immune infiltration analysis, pathway enrichment analysis, and protein–protein interaction (PPI) network analysis via GeneMANIA were further applied to explore biological functions.ResultsA total of 2,477 upregulated and 2,214 downregulated differentially expressed genes (DEGs) were identified, with 245 common DEGs pinpointed across datasets. Cluster1 genes were significantly associated with OSCC pathogenesis in functional enrichment. CCNA1, HMMR, and RAG1 were identified as potential prognostic markers, with HMMR demonstrating the strongest predictive value (AUC = 0.919 in ROC analysis). HMMR was significantly overexpressed in OSCC tissues compared to normal controls (P < 0.001), and its high expression correlated with advanced T stage, N stage, pathological grade, shorter disease-specific survival, and disease-free survival. Multivariate analysis confirmed HMMR as an independent prognostic factor for overall survival. Immune infiltration analysis revealed that HMMR expression was positively correlated with 11 immune cell subsets, particularly Th2 cells (r = 0.465) and T helper cells (r = 0.356), suggesting a role in modulating the tumor immune microenvironment. Pathway enrichment linked HMMR to tumor proliferation, hypoxia response, DNA damage repair, and G2/M cell cycle checkpoints. The PPI network analysis identified HMMR-associated complexes involving cell cycle regulators (e.g., CDK1, CCNB1, AURKA), implicating roles in cell cycle regulation, DNA repair, and mitotic progression.DiscussionCollectively, this study establishes HMMR as a robust prognostic biomarker for OSCC, tightly associated with malignant progression, immune cell infiltration, and key oncogenic pathways. HMMR and its interacting network represent promising targets for OSCC precision medicine, offering new insights into diagnostic strategies and therapeutic development.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1850332</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1850332</link>
        <title><![CDATA[Identification of QTL associated with pod number in soybean]]></title>
        <pubdate>2026-06-04T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yajun Xiong</author><author>Huan Yu</author><author>Alu Mao</author><author>Sawaira Jadoon</author><author>Zhiyu Liu</author><author>Kanglin Liu</author><author>Zhiqing Zhang</author><author>Yijie Chen</author><author>Bernard Gyebi-Nimako</author><author>Lijuan Qiu</author><author>Jun Wang</author>
        <description><![CDATA[Pod number is an important factor influencing soybean yield. In this study, a recombinant inbred line population derived from the cross between improved cultivar (Glycine max) and wild soybean (Glycine soja) was subjected to multi-environment phenotypic evaluation for pod number. Quantitative trait locus (QTL) mapping associated with pod number was performed utilizing both linkage analysis (LA) and genome-wide association study (GWAS) by integrating the phenotypic and genotypic data. The results showed that a total of 16 QTLs associated with pod number, notably, overlapping genomic intervals were observed between qPN10-1 (by linkage analysis) and qPN10-3 (by EMMAX), as well as between qPN11-2 (by LA) and qPN11-3 (by EMMAX), and these intervals were regarded as major-effect Quantitative trait locus regions. Furthermore, two candidate genes (Glyma.10G206300, and Glyma.10G207500) encode a basic Helix-Loop-Helix (bHLH) transcription factor and an armadillo (ARM)-repeat protein respectively, as determined through linkage disequilibrium analysis, SNP variant analysis, haplotype analysis, and gene functional annotation. These two candidates are possibly involved in the regulation of flower number, flowering time, and pod number (siliques number in Arabidopsis thaliana). These findings pave the way for gene cloning related to pod number, and provide novel insights into the genetic architecture underlying pod number variation in soybean.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1857794</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1857794</link>
        <title><![CDATA[Case report: novel DNAH11 compound heterozygous variants including an exon 30–54 duplication in a child with a highly suggestive primary ciliary dyskinesia phenotype]]></title>
        <pubdate>2026-06-04T00:00:00Z</pubdate>
        <category>Case Report</category>
        <author>Shun Wang</author><author>Yuyi Zhang</author><author>Min Wu</author><author>Yanyu He</author><author>Sainan Chen</author><author>Xueyun Xu</author><author>Meng Lv</author><author>Jiapeng Ji</author><author>Yuqing Wang</author>
        <description><![CDATA[Primary ciliary dyskinesia (PCD) is a rare disorder characterized by dysfunction of motile cilia and chronic progressive respiratory disease, mianly inherited in an autosomal recessive manner. Biallelic variants in dynein axonemal heavy chain 11 (DNAH11) have been reported in association with PCD and are typically associated with normal ciliary ultrastructure. In addition, exon-level copy number variants (CNVs) in DNAH11, particularly duplications, remain poorly characterized and are prone to being overlooked by conventional sequencing workflows. We report a 9-year-old Chinese girl with recurrent lower respiratory tract infections, chronic pansinusitis, and bronchiectasis. Pulmonary function testing showed isolated small-airway dysfunction with preserved FEV1, with nasal nitric oxide (nNO) severely reduced (5.4 nL/min). Trio whole-exome sequencing integrated with read-depth CNV analysis detected novel compound heterozygous DNAH11 variants: a paternal inherited missense variant (c.6556A>C, p.Thr2186Pro) and a previously unreported maternally derived intragenic duplication encompassing exons 30–54. The missense variant was confirmed by Sanger sequencing, and the exon-level dosage gain was confirmed by qPCR. This case expands the spectrum of DNAH11 variants and highlights the importance of incorporating CNV detection into exome-based diagnostic process for children with a highly suggestive PCD phenotype.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1786287</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1786287</link>
        <title><![CDATA[The effect of human-specific genetic variants on neuronal spinogenesis]]></title>
        <pubdate>2026-06-03T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Nicolás Matías Rosas</author><author>Anna Szombathy</author><author>Kinga Szigeti</author>
        <description><![CDATA[Fundamental morphological and functional differences between the brains of animal models and humans are at least partially related to human-specific genes and genetic variants. As one of the structural underpinnings of brain function is the dendritic spine, we systematically queried a curated list of human-specific genes and genetic variants. We found that with the current knowledge base, 4.3% are linked to the dendritic spine. Functionally these genes converge on the cytoskeleton, Ca2+ signaling, small GTPases, NMDAR, and WNT signaling and trafficking suggesting human specific modification of canonical pathways. Significant gaps in knowledge are identified and concerted efforts are needed. Understanding human-specific genetic contributions to the unique features of the human brain will address existing translational gaps and facilitate the development of successful treatments for neuropsychiatric disorders, advance environmental neuroscience for early childhood intervention and environmental risk reduction in aging and dementia.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1792190</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1792190</link>
        <title><![CDATA[Derivation of prediction error variance for non-genotyped individuals in genomic selection]]></title>
        <pubdate>2026-06-03T00:00:00Z</pubdate>
        <category>Methods</category>
        <author>Vinícius Silva Junqueira</author><author>Marcos Jun-Iti Yokoo</author><author>Fernando Flores Cardoso</author>
        <description><![CDATA[Genomic selection has transformed plant and animal breeding by enabling accurate prediction of genetic merit using DNA markers; however, comprehensive genotyping of all selection candidates remains economically prohibitive for most breeding programs. While breeding programs must decide which subset of individuals to genotype within budget constraints, current approaches rely primarily on experience-based decisions rather than quantitative frameworks. We present explicit mathematical derivations for prediction error variance (PEV) in non-genotyped individuals under mixed model equations, providing a theoretical foundation for evaluating genotyping strategies prospectively. The approach derives PEV expressions for non-genotyped selection candidates under different relationship matrix structures, including pedigree-based, genomic, and hybrid single-step methodologies that combine both information sources. The derivations accommodate complex breeding program structures with historical training populations containing both genotypes and phenotypes alongside contemporary selection candidates with only pedigree information. Using Schur complement methods applied to partitioned mixed model equations, the framework enables calculation of prediction uncertainty without requiring actual phenotypic data from selection candidates. The expressions simplify under different information scenarios, from cases with complete phenotypic data to situations where only relationship information is available. The method was validated through simulations across six scenarios with populations ranging from 180 to 15,500 individuals, confirming numerical equivalence with direct matrix inversion while demonstrating computational and memory advantages that increase with population size. Although genomic relationship matrix operations dominate the complexity, matrix decomposition techniques, including Cholesky factorization and APY methodology, can improve efficiency. The mathematical framework provides quantitative tools for transitioning from experience-based to mathematically-informed genotyping decisions, with applications extending to any field requiring prospective quantification of prediction uncertainty under resource constraints.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1776108</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1776108</link>
        <title><![CDATA[Temporal trends in artemisinin partial resistance and other antimalarial drug mutations in Plasmodium falciparum from Kagera region, Northwestern Tanzania, 2021–2023]]></title>
        <pubdate>2026-06-03T00:00:00Z</pubdate>
        <category>Brief Research Report</category>
        <author>Alfred Simkin</author><author>Salehe S. Mandai</author><author>Abebe A. Fola</author><author>Neeva Wernsman Young</author><author>Jacob Marglous</author><author>Dativa Pereus</author><author>Catherine Bakari</author><author>Rashid A. Madebe</author><author>Misago D. Seth</author><author>Rule B. Mrengela</author><author>Angelina J. Kisambale</author><author>Gervas A. Chacha</author><author>Celine I. Mandara</author><author>Filbert Francis</author><author>Daniel Mbwambo</author><author>Issa Garimo</author><author>Frank Chacky</author><author>Sijenunu Aaron</author><author>Abdallah Lusasi</author><author>Fabrizio Molteni</author><author>Ritha J. A. Njau</author><author>Stella Kajange</author><author>Samwel L. Nhiga</author><author>Ally Mohamed</author><author>Jonathan J. Juliano</author><author>Deus S. Ishengoma</author><author>Jeffrey A. Bailey</author>
        <description><![CDATA[Artemisinin-based combination therapies (ACTs) remain the cornerstone of malaria treatment, yet the emergence of artemisinin partial resistance (ART-R) in Africa threatens their efficacy. ART-R is primarily associated with mutations in Plasmodium falciparum kelch13 (K13), notably R561H, which has been linked to delayed parasite clearance in East Africa. We genotyped 2,866 P. falciparum isolates from seven districts in Tanzania’s Kagera region (2021–2023) using 121 molecular inversion probes (MIP) targeting key resistance loci to characterize trends in ART-R and other resistance markers. The WHO-validated K13 mutation R561H persisted in border districts of Karagwe and Kyerwa, with prevalence ranging from 14% to 26%, and appeared for the first time in Muleba in 2022 (10.0%) and Bukoba rural district (0.7%) in 2023, indicating eastward spread toward Lake Victoria. Regional prevalence of R561H rose from 5.5% in 2021 to 6.9% in 2023. Additional validated (A675V) and candidate (V568G, P441L) mutations were detected at low frequencies. Markers associated with reduced sensitivity to partner drugs showed minimal change. Early DHFR and DHPS mutations were near fixation and high-level resistance markers (DHFR I164L and DHPS A581G) exhibited marked gradients. These latest mutations are significantly spatially colocalized (weighted spearman R2 = 0.58, P = 0.045) and co-occur within a number of individual genomes. These results highlight notable variation in mutation prevalence and underscore the importance of high-resolution surveillance to identify emerging hotspots and guide targeted interventions. Sustained molecular monitoring is critical to inform treatment policy, preserve ACT efficacy, and mitigate the risk of widespread resistance across East Africa.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1779086</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1779086</link>
        <title><![CDATA[Biobank consent preferences and implications for a mixed consent model: biomedical researchers vs. community stakeholders in a semi-urban Yoruba community, Nigeria]]></title>
        <pubdate>2026-06-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Olubunmi A. Ogunrin</author>
        <description><![CDATA[BackgroundSeveral consent models have been described in the literature for genomic research, with some focusing specifically on biobanking. Sub-Saharan African scholars reported a preference for broad consent among key stakeholders, identical to narratives from most studies in Europe and the USA. However, there have been reports of a generational shift with divergent views among potential genomic research participants in sub-Saharan Africa due to communitarian ethos and relative solidarity. To avoid ethical conflicts in biobanking research in sub-Saharan Africa, it is imperative to explore the preferences of the various stakeholders.ObjectiveTo explore the opinions of research stakeholders, namely: biomedical clinician-researchers, community elders, and community members, on informed consent models in biobanking research.MethodsThis qualitative study employed key-informant semi-structured interviews and focus group discussions to collect data from purposively selected participants. Sample sizes for the stakeholders’ categories were determined by theoretical saturation. Thirty clinician-researchers and four community elders were interviewed. Fifteen focus group sessions were held with 50 community members. The methodological design, adapted from grounded theory, used the constant comparative method of data analysis. Data and methodological triangulation, reflexivity, and code-recode reliability index were used to ascertain data quality.ResultsTwelve of the biomedical researchers preferred blanket consent, aligning with the preferences of adult community members. Ten of the researchers opted for broad consent. The community elders opined that community members would prefer tiered consent. The youth participants differed from the researchers and community adults, preferring re-consenting. The findings of this study showed discordant views on consent model preferences among the various stakeholders.ConclusionDiscordance in consent preferences among the key stakeholders is a potential source of ethical conflict. A hybrid or mixed-consent model that provides participants with the option to choose the consent model they prefer for every research stage, and flexibility to change their choices as the research progresses, is recommended. This will reflect the fundamental principle of autonomy and demonstrate responsive communitarianism and relative solidarity. It will also provide a robust, culturally sensitive, and context-specific model that reflects the preferences of community stakeholders and addresses the fundamental ethical issues encountered in biobanking.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1820930</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1820930</link>
        <title><![CDATA[Genetic variation at the IL-18–137C>G is associated with poor sepsis prognosis and enhanced inflammatory responses: a multicenter hospital-based study]]></title>
        <pubdate>2026-06-03T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zhuoji Li</author><author>Wanjie Gu</author><author>Lizhen Liu</author><author>Jiekai Li</author><author>Manting Zhang</author><author>Wanchun Yang</author><author>Meiting Yang</author><author>Jingqi Zhang</author><author>Haotian Zhong</author><author>Yuchun Liu</author><author>Junbing He</author><author>Haiyan Yin</author><author>Yiming Shao</author>
        <description><![CDATA[BackgroundSepsis is a life-threatening condition caused by dysregulated immune responses, leading to inflammation, tissue damage, and organ failure. This study investigates the role of the IL-18 rs187238 (−137C>G) polymorphism in sepsis susceptibility, progression, and patient prognosis.MethodsA multicenter case-control study was conducted with 784 sepsis patients and 776 healthy controls. The IL-18 rs187238 polymorphism was genotyped using imLDR™ multiplex SNP genotyping method. ELISA and qRT-PCR were used to detect related inflammatory cytokine expression, while functional analysis was performed using dual-luciferase assays to evaluate the impact of the rs187238 variant on IL-18 promoter activity.ResultsWe observed a significant association between the rs187238 polymorphism and 28-day ICU mortality in sepsis patients. The CG/GG genotypes (OR = 1.470, 95% CI = 1.029–2.129, P = 0.037) were more frequently observed in non-survivors compared to survivors, with a notable difference in the frequency of the G allele (OR = 1.534, 95% CI = 1.111–2.133, P = 0.010). Kaplan-Meier survival analysis confirmed that patients with CG/GG genotypes had significantly lower 28-day survival rates compared to those with the CC genotype (P = 0.028). However, no significant differences in genotype and allele frequencies were observed between cases and healthy controls, nor between sepsis and septic shock patients. Sepsis patients with CG/GG genotypes had significantly higher IL-18 levels than those with the CC genotype. Dual-luciferase assays confirmed that the G allele increased IL-18 promoter activity, supporting its genetic influence on IL-18 expression. Additionally, sepsis patients with CG/GG genotypes expressed significantly increased levels of IL-1β, IL-6, and ICAM-1 than those with CC genotype. IL-18 treatment enhanced the expression of IL-1β, IL-6, IL-27, TNF-α, and MCP-1 in THP-1 macrophages upon LPS stimulation. In HUVECs, IL-18 treatment further enhanced LPS-induced IL-6, IL-27, TNF-α, and ICAM-1 expression, while promoting apoptosis and reducing VE-cadherin levels, emphasizing its role in inflammation and endothelial dysfunction in sepsis.ConclusionThe IL-18 rs187238 C>G polymorphism is linked to higher IL-18 expression and intensified inflammatory responses, which are associated with poor sepsis prognosis. The sepsis-associated risk rs187238-G allele serves as a potential prognostic biomarker for sepsis-related mortality. Targeting IL-18 or its genetic variations might offer new avenues for sepsis therapy.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1814462</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1814462</link>
        <title><![CDATA[Pathogenic mechanisms of RPGR mutations in X-linked retinitis pigmentosa: integrating clinical pedigree and single-cell transcriptomics]]></title>
        <pubdate>2026-06-02T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>XinRong Wang</author><author>YuYang Bai</author><author>XiaoYang Zuo</author><author>XiaoYin Lei</author><author>Xue Wang</author><author>Gang Zou</author>
        <description><![CDATA[PurposeThis study aims to identify pathogenic retinitis pigmentosa GTPase regulator (RPGR) mutations in a Chinese pedigree with X-linked retinitis pigmentosa (XLRP) and elucidate the cellular and molecular mechanisms underlying RPGR-associated photoreceptor degeneration through the integrated analysis of clinical data and single-cell transcriptomics.MethodsA three-generation Chinese XLRP pedigree was enrolled for comprehensive ophthalmic examinations, including BCVA, OCT, FAF, and ERG. Whole-exome sequencing was performed on the proband to identify the pathogenic variants, followed by Sanger sequencing for validation in family members. To analyze the downstream molecular mechanisms, we analyzed a public single-cell RNA sequencing dataset (SRP535874) of RPGR mutant retinal organoids across four developmental time-points (D40–D200). Bioinformatics analyses included cell clustering, differential expression analysis, GO/KEGG enrichment, protein–protein interaction (PPI) network construction, and pseudotime trajectory analysis.ResultsA hemizygous frameshift mutation (c.2476_2477del; p.R826Gfs*8) in the ORF15 region of RPGR was identified in the proband and confirmed in his two sons by Sanger sequencing. Clinical examinations revealed severe retinal degeneration in the affected male, intermediate phenotype in female carriers, and early-stage changes in the young affected male. Single-cell transcriptomic analysis of RPGR mutant retinal organoids revealed a paradoxical increase in photoreceptor transcriptional activity at late developmental stages (D150 and D200) despite the loss of the outer retinal structure in the patients, which may reflect aberrant differentiation and impaired functional maturation of photoreceptor precursors. Differential expression analysis showed upregulation of the stress-response genes and downregulation of phototransduction and ciliary transport genes. GO and KEGG enrichment analyses implicated disrupted ribosome biogenesis, RNA metabolism, ubiquitin-mediated proteolysis, and neurodegenerative disease pathways. PPI network analysis indicated decoupling of the core “ciliary transport–phototransduction axis” and activation of a coordinated stress-response module. Pseudotime trajectory analysis showed arrested photoreceptor differentiation at an intermediate stage, preventing the progression to functional maturity.ConclusionWe identify a previously reported but extremely rare RPGR ORF15 frameshift mutation (c.2476_2477del; p.R826Gfs*8) in a Chinese XLRP pedigree. Single-cell transcriptomic analysis indicates that RPGR loss-of-function mutation may disrupt the ciliary transport–phototransduction axis, activate stress responses, and block photoreceptor differentiation. These findings expand the RPGR mutation spectrum, provide mechanistic insights into XLRP pathogenesis, and have implications for genetic counseling and targeted therapy.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1875072</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1875072</link>
        <title><![CDATA[Editorial: Circular RNAs: from anomalies to cellular regulators]]></title>
        <pubdate>2026-06-02T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Davide Barbagallo</author><author>Rosanna Chianese</author><author>Francesco Manfrevola</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1796970</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1796970</link>
        <title><![CDATA[Molecular characterization of a rare heterozygous APOA5 variant in a Chinese family with moderate hypertriglyceridemia]]></title>
        <pubdate>2026-06-02T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Hongxia Liu</author><author>Xiao Yuan</author><author>Jie Wang</author><author>Yuande Mao</author><author>Jinxi Wang</author><author>Dongli Wang</author><author>Fang Tian</author><author>Yili Yang</author><author>Bo Xiang</author>
        <description><![CDATA[BackgroundThe development of hypertriglyceridemia (HTG) can be attributed to either a monogenic or a polygenic etiologic basis, and the understanding of this molecular basis is incomplete. APOA5 plays a critical role in triglyceride (TG) metabolism, and APOA5 deficiency is a recognized cause of HTG. However, the effects of rare APOA5 variants observed only in isolated cases are often difficult to establish conclusively. This study aims to find the genetic cause of moderate HTG in a Chinese family, and conduct preliminary in silico verification.MethodsEight family members received biochemical testing, and genetic testing based on whole-exome sequencing (WES). Basic information including body mass index (BMI), medical history, prescription for TG management, and smoking and drinking habits was recorded. Comprehensive residue conservation analysis and computational simulation of protein structure stability were performed to measure the impact of the assumptive causal variant.ResultsA rare heterozygous APOA5 variant (p.R223C) was identified. Specifically, six family members who carried the variant had substantially higher fasting plasma TG level than the admitted threshold (1.7 mmol/L) with the highest of 4.96 mmol/L, while a non-carrier in this family was normal in TG. The p. R223C variant was absent from ClinVar and gnomAD databases. Besides, in silico predictions results supported the variant’s potential deleteriousness.ConclusionThis study presents a familial case of moderate HTG associated with a rare APOA5 variant, which is classified as Likely Pathogenic (LP) according to the ACMG/AMP guideline. The real effect of this variant requires further investigation via biochemical or cell-based studies.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1811927</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1811927</link>
        <title><![CDATA[MetaComb: a meta-learning framework for drug combination response prediction from cell lines to patients]]></title>
        <pubdate>2026-06-02T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Congcong Guo</author><author>Tongtong Li</author><author>Xinru Deng</author><author>Yajie Ma</author><author>Feng He</author><author>Lihong Diao</author><author>Ze Wang</author><author>Dong Li</author><author>Zhongyang Liu</author>
        <description><![CDATA[IntroductionCombination therapy has emerged as a pivotal strategy in oncology to enhance efficacy and overcome drug resistance. Computational prediction models of drug combinations trained on abundant cell line data provide a starting point, but their applicability to patients remains constrained by inherent biological disparities between cultured cell lines and patient-derived tumors. However, due to ethical and cost issues, patient-derived datasets remain scarce, thus, developing patient-level predictive algorithms must explicitly confront the few-shot problem of relevant data.MethodTo break through the small sample bottleneck, we used the Model-Agnostic Meta-Learning (MAML) to develop a Meta-Learning Drug Combination Response Prediction (MetaComb) method for patient ex vivo drug combination response prediction, using drug structures and gene expression profiles of cell lines/patients as the model input. In MetaComb, the meta-model was trained on data-rich cell line-specific drug combination response prediction tasks and subsequently fine-tuned to adapt to scenarios with limited samples.ResultsMetaComb outperformed conventional transfer learning in predicting drug combination response, improving AUROC by 8.5% for data-poor cell lines and by 7.4% for patient ex vivo samples. And for the patients with ex vivo data, MetaComb also achieved superior accuracy over existing methods. Given the limited patient cohort, these results demonstrate the feasibility of MetaComb, but further validation with larger patient datasets is needed.DiscussionThis study, as a proof-of-concept, provided an initial evidence that the MetaComb meta-learning framework is feasible for patient-derived ex vivo drug combination response prediction under few-shot conditions, by transferring drug-combination response knowledge from preclinical cell lines. Current patient-level assessment is insufficient to support generalization to other cancer types or patient populations, and in the future, with the accumulation of relevant patient-derived data, further validation with larger patient cohorts is required.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1839396</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1839396</link>
        <title><![CDATA[Accuracy of genomic prediction for milk production traits in Mehsana buffalo]]></title>
        <pubdate>2026-06-02T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Mayank R. Patel</author><author>Ashish C. Patel</author><author>Rajesh S. Joshi</author><author>Devanshi V. Patel</author><author>Nilesh Nayee</author><author>A. Sudhakar</author><author>Subhash J. Jakhesara</author><author>Prakash G. Koringa</author>
        <description><![CDATA[IntroductionGenomic information can contribute significantly to the increase in the accuracy of genetic evaluation compared to relying solely on pedigree relationships. Hence, the objective of this study was to compare the accuracy of genomic prediction for 305 days milk yield (305DMY), 305 days fat yield (305DFY), 305 days solid-not-fat yield (305DSNFY) and 305 days protein yield (305DPY) traits in Mehsana buffalo using pedigree best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) models. Prediction bias was assessed by estimating the regression coefficient of corrected yield (Yc) on predicted breeding values (BVs).MethodsThe phenotype dataset comprised of test day records of 10,897 Mehsana buffalo for milk yield, 10,896 for fat yield, 10,581 for SNF yield and 10,578 for protein yield were used for present study. A total of 4,107 blood samples of Mehsana buffaloes were collected and genotyped using BUFFCHIP 54K SNP array. After the quality control, final dataset comprised of 3,887 Mehsana buffalo with 53,292 SNPs.ResultsThe prediction accuracies obtained using PBLUP ranged from 0.078 to 0.088, whereas those from ssGBLUP ranged from 0.088 to 0.100. The average predictive accuracies across traits were 0.083 for PBLUP and 0.093 for ssGBLUP, representing an overall improvement of 11.37% with ssGBLUP. The regression coefficients of predictions ranged from 0.44 to 0.52 for PBLUP and from 0.45 to 0.61 for ssGBLUP across production traits. The average regression coefficients were 0.48 for PBLUP and 0.53 for ssGBLUP, indicating reduced prediction bias under the ssGBLUP model.ConclusionssGBLUP provides more accurate and less biased breeding value predictions than PBLUP for production traits in Mehsana buffaloes.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1827876</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1827876</link>
        <title><![CDATA[Genetic analysis of three familial cases of pure terminal 19p13.3 duplication caused by maternal balanced translocation t(19;21) (p13.3;p12)]]></title>
        <pubdate>2026-06-02T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Jia-yan Chen</author><author>Mei-jiao Cai</author><author>Xiao-lu Chen</author><author>Yun-sheng Ge</author>
        <description><![CDATA[IntroductionThis study presents a genetic analysis of three-generation family exhibiting terminal 19p13.3 duplication resulting from a maternal balanced translocation, t (19; 21) (p13.3; p12). Additionally, we reviewed previously reported cases with similar aberrations.MethodsPeripheral blood or amniotic fluid samples from six family members were comprehensively analyzed using G-banding, N-banding, fluorescence in situ hybridization (FISH), and copy number variation sequencing (CNV-seq). Furthermore, a genomic mapping analysis was performed on 23 cases of terminal 19p13.3 duplication, combining our findings with those from previously reported cases.ResultsThe results demonstrated that the maternal balanced translocation resulted in three offspring inheriting the 19p13.3 terminal duplication. The proband presented with typical clinical features such as intrauterine growth restriction, microcephaly, intellectual disability, developmental delay, and facial abnormalities, in addition to precocious puberty, autism spectrum disorder (ASD) features, and a shortened lingual frenulum. The precocious puberty phenotype is postulated to be associated with the KISS1R gene within the duplicated region. Genomic mapping identified a minimal overlapping region (MOR) of approximately 313 kb (chr19:3,223,850–3,536,224), encompassing four OMIM genes (CELF5, NFIC, DOHH, FZR1) and two protein-coding genes (SMIM24, SMIM44).ConclusionThis study clarifies the genetic mechanism of pure terminal 19p13.3 duplication in offspring resulting from a parental balanced translocation involving D/G group chromosomes. It also defines a novel critical region based on case samples with 19p13.3 terminal duplication, providing new insights into the genotype-phenotype correlations associated with terminal pure 19p13.3 duplications.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1624523</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1624523</link>
        <title><![CDATA[Identification of novel JAK3 variants in a suspected SCID patient and two couples undergoing carrier screening]]></title>
        <pubdate>2026-06-01T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Yao Peng</author><author>Yi-Lin Sang</author><author>Wu Zhu</author><author>Ning Zhang</author><author>Yi Sun</author><author>Ge Lin</author><author>Guang-Xiu Lu</author><author>Yue-Qiu Tan</author><author>Juan Du</author><author>Fu-Yan Wang</author><author>Wen-Bin He</author>
        <description><![CDATA[BackgroundSevere combined immunodeficiency (SCID) is one of the most severe forms of primary immunodeficiency. JAK3 gene is a critical determinant of SCID, as JAK3-STAT pathway regulates development, proliferation, activation, and differentiation of immune cells. This study aimed to identify the genetic cause of a family with a suspected SCID patient, and to perform carrier screening for two couples to assess the risk of conceiving offspring with birth defects.MethodsWhole-Exome Sequencing was performed on five individuals from the three families. A series of in vitro functional experiments, including Western blotting and luciferase assays, were conducted to assess the pathogenicity of the identified JAK3 variants.ResultsWe identified seven JAK3 variants, including five variants of uncertain significance (p.Arg402His, p.ILe688Phe, p.Leu129Phe, p.Met235Thr, p.Ala634Pro) and one pathogenic variant and one likely pathogenic variant (p.Gln1007Ter and p.Cys376Leufs*34). Among these, four variants (p.Gln1007Ter, p.Leu129Phe, p.Cys376Leufs*34 and p.Ala634Pro) were novel. In vitro functional experiments revealed that three of five variants of uncertain significance (VUSs) significantly reduced STAT5 phosphorylation and transcriptional activity, thereby reclassifying two variants (p.Arg402His and p.ILe688Phe) as likely pathogenic variants (LP) and one variant (p.Leu129Phe) as VUS with a Bayesian score of 3. In contrast, the remaining two variants (p.Ala634Pro and p.Met235Thr) did not affect JAK3 function, and were reclassified as VUS with a Bayesian score of 1 or 0.ConclusionThis study identified seven JAK3 variants from three families, including four novel variants. Functional experiments revealed that two VUSs were reclassified as LP and one VUS were reclassified as VUS with a Bayesian score of 3. These findings highlight the importance of integrating genetic and functional analyses to enhance diagnostic accuracy, inform treatment strategies for patients, clarify of the risk for carrier-screening couples, improve genetic counseling, and guide reproductive interventions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fgene.2026.1797093</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fgene.2026.1797093</link>
        <title><![CDATA[Integrated metabolomic and transcriptomic analysis of anthocyanin accumulation mechanisms in maize kernels of different colors]]></title>
        <pubdate>2026-06-01T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Chao Jiang</author><author>Hanbo Shi</author><author>Linan Yan</author><author>Wenxu Yin</author><author>Hui Li</author><author>Haibo Lu</author><author>Haichao Zhao</author><author>Songtao Liu</author><author>Shuo Wang</author><author>Dong Wei</author><author>Zhihong Huang</author>
        <description><![CDATA[IntroductionAnthocyanins are important natural pigments and bioactive compounds in colored maize kernels. Although colored fresh-eating maize has attracted increasing attention because of its nutritional and functional value, the molecular basis underlying anthocyanin accumulation in maize kernels with different colors remains incompletely understood.MethodsIn this study, four fresh-eating maize cultivars with contrasting kernel colors, including white (WN 2000), yellow (HN), multicolored (CN1), and black (HTN188), were used to investigate the mechanism of anthocyanin accumulation. Total anthocyanin content was measured across developmental stages, and integrated metabolomic and transcriptomic analyses were performed to identify anthocyanin-related metabolites, differentially expressed genes, and candidate regulatory factors associated with kernel pigmentation.ResultsMetabolomic profiling identified 49 anthocyanin-related metabolites/features, with marked enrichment of cyanidin-, peonidin-, and pelargonidin-related compounds in the black maize cultivar HTN188. Transcriptomic analysis identified 12,557 differentially expressed genes among the four cultivars, which were mainly enriched in phenylpropanoid biosynthesis, flavonoid biosynthesis, glutathione metabolism, fructose and mannose metabolism, and glyoxylate and dicarboxylate metabolism pathways. Several anthocyanin biosynthetic genes and regulatory transcription factor candidates were upregulated in anthocyanin-rich kernels, including DFR (Zm00001d011438), MYB (Zm00001d003052), bHLH (Zm00001d015990), and NAC (Zm00001d012508). In particular, the expression of DFR (Zm00001d011438) was strongly positively correlated with total anthocyanin content. Weighted gene co-expression network analysis further identified gene modules and candidate hub regulators associated with anthocyanin accumulation.DiscussionThese findings provide a comparative multi-omics perspective on anthocyanin accumulation in fresh-eating maize kernels of different colors. The results suggest that the high anthocyanin accumulation in black maize is associated with the coordinated enrichment of anthocyanin-related metabolites and the upregulation of key structural genes and transcription factors. This study provides candidate genes and regulatory information for future functional studies and anthocyanin-oriented breeding in fresh-eating maize.]]></description>
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