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This study examined the lignin degradation characteristics of Bacillus amyloliquefaciens MN-13. Specifically, whole-genome sequencing and comparative proteomic analysis were performed to investigate the responses of the MN-13 strain to lignin. A maximum lignin removal of 38.0 % was achieved after 36 h of inoculation in mineral salt medium with 0.2 g/L alkaline lignin, under the following conditions: the carbon to nitrogen ratio C/N = 1/1; inoculum size 6 %; addition of glucose as an exogenous carbon source. When the MN-13 strain was inoculated into mineral salt medium with and without lignin, respectively, 831 differentially expressed proteins were identified, 404 of which were up-regulated and 427 were down-regulated. Enrichment analysis revealed that up-regulated proteins were associated with microbial metabolism in diverse environment, biosynthesis of amino acids, and pathways related to energy production, including carbon metabolism, pyruvate metabolism, the TCA cycle etc. Genomic analysis revealed that the MN-13 strain possesses many ligninolytic enzymes and aromatics degradation pathway, including benzoate degradation and aminobenzoate degradation etc. Taken together, the proteomic and genomic analyses indicated that the meta-cleavage pathway of catechol, including benzoate degradation, etc., is the main lignin degradation pathway. These findings provide new insight into lignin degradation mediated by B. amyloliquefaciens., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Artificial intelligence (AI) and synthetic biology will transform civilization. The only question is how. In this paper, I explore some recent developments in medical AI, genomics, and synthetic biology. I speculate about the implications of these technologies for the practice of medicine and conclude that they will fundamentally alter our ideas of health, disease, medicine, and what it means to be human. I have three conclusions. First, AI and synthetic biology will force us to examine whether humanistic skills can be uniquely human and, if so, whether they are skills or natural gifts. AI will offer opportunities to examine what we mean by empathy, how we develop skills in communication, and when the human touch is essential for healing. Second, these technologies will change the ways that we will assess the value of doctors' work. Skills that can be mechanized will be devalued and delegated to machines. Doctors will either need to learn new skills or become irrelevant. Finally, AI and synthetic biology will force us to deeply examine what it means to be human. For humans to remain uniquely valuable, we will need to develop those aspects of our humanity that cannot be mechanized. Doctors will need to carefully attune themselves to the non-physical aspects of disease and suffering. Ultimately, AI and synthetic biology will force us to redesign both or systems of medical education and the systems of health care delivery in ways that meet both the medical and non-medical needs of patients., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Increased adoption of personalized medicine has brought comprehensive genomic profiling (CGP) to the forefront. However, differences in assay, bioinformatics, and reporting systems and lack of understanding of their complex interplay are a challenge for implementation and achieving uniformity in CGP testing. Two commercially available, tissue-based, in-house CGP assays were compared, in combination with a tertiary analysis solution in a research use only (RUO) context: the AVENIO Tumor Tissue CGP RUO Kit paired with navify Mutation Profiler (RUO) software and the TruSight Oncology 500 RUO assay paired with PierianDx Clinical Genomics Workspace software. Agreements and differences between the assays were assessed for short variants, copy number alterations, rearrangements, tumor mutational burden, and microsatellite instability, including variant categorization and clinical trial-matching (CTM) recommendations. Results showed good overall agreement for short variant, known gene fusion, and microsatellite instability detection. Important differences were obtained in tumor mutational burden scoring, copy number alteration detection, and CTM. Differences in variant and biomarker detection could be explained by bioinformatic approaches to variant calling, filtering, tiering, and normalization; differences in CTM, by underlying reported variants and conceptual differences in system parameters. Thus, distinctions between different approaches may lead to inconsistent results. Complexities in calling, filtering, and interpreting variants illustrate key considerations for implementation of any high-quality CGP in the laboratory and bringing uniformity to genomic insight results., Competing Interests: Disclosure Statement H.-P.A., F.F., and U.S. are employees of Signature Diagnostics GmbH (H.-P.A. at the time of the analysis, but now retired). M.C.H., J.O., and J.M.A. are employees of Foundation Medicine, Inc. (J.O. at the time of the analysis, but is no longer an employee), and M.C., S.O., and T.W. are employees of Foundation Medicine GmbH; all hold stock in F. Hoffmann-La Roche Ltd. K.H. is an employee of Helios MVZ Pathologie Erfurt GmbH. M.T. is an employee of F. Hoffmann-La Roche AG and holds stock in F. Hoffmann-La Roche Ltd. D.G. holds stock in Univ8 Genomics Ltd.; has received honoraria (institution) from Roche, Illumina, Novartis, AstraZeneca, Eli Lilly, Amgen, and Janssen; has participated in a consulting or advisory role (institution) for AstraZeneca and Novartis; has participated in a speakers' bureau (institution) for AstraZeneca; and has received travel, accommodations, and expenses (institution) from Roche, AstraZeneca, and Illumina. E.P. received compensation for speaking engagements and advisory roles, with payments made directly to his affiliated university, from Roche, AstraZeneca, Novartis, and MSD. H.S. and M.D.V. are employees of Roche Diagnostics Solutions, Inc., and M.D.V. holds stock in F. Hoffmann-La Roche Ltd. E.S. reports lectures for Bio-Rad, Seracare, Novartis, Roche, Biocartis, Illumina, Eli Lilly, Janssen-Cilag, Pfizer, AstraZeneca, and Agena Bioscience; he is consultant in advisory boards for MSD/Merck, GSK, AstraZeneca, Astellas Pharma, Sysmex, Roche, Pfizer, Novartis, Bayer, Bristol Myers Squibb, Eli Lilly, Amgen, Biocartis, Illumina, Agena Bioscience, Janssen-Cilag (Johnson & Johnson), Sinnovisionlab, Diaceutics, and CC Diagnostics; and received research grants from Pfizer, Biocartis, Invitae-ArcherDX, AstraZeneca, Agena Bio-science, Bristol Myers Squibb, Bio-Rad, Roche, Boehringer Ingelheim, CC Diagnostics, and Abbott (all paid to University Medical Center Groningen account); and travel reimbursements from Bio-Rad, Abbott, Illumina, Agena Bioscience, and Roche. All authors received support in the form of third-party writing assistance for this manuscript, furnished by Nucleus Global, an Inizio company, and provided by F. Hoffmann-La Roche Ltd./Roche Diagnostics Solutions, Inc., (Copyright © 2024 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Abscisic acid (ABA) is a pivotal regulator of plant growth, development, and responses to environmental stresses. The ABA signaling pathway involves three key components: ABA receptors known as PYLs, PP2Cs, and SnRK2s, which are conserved across higher plants. This study comprehensively investigated the PYL-PP2C-SnRK gene family in pecan, identifying 14 PYL genes, 97 PP2C genes, and 44 SnRK genes, which were categorized into subgroups through phylogenetic and sequence structure analysis. Whole-genome duplication (WGD) and dispersed duplication (DSD) were identified as major drivers of family expansion, and purifying selection was the primary evolutionary force. Tissue-specific expression analysis suggested diverse functions in different pecan tissues. qRT-PCR validation confirmed the involvement of CiPawPYLs, CiPawPP2CAs, and CiPawSnRK2s in salt stress response. Subcellular localization analysis revealed CiPawPP2C1 in the nucleus and CiPawPYL1 and CiPawSnRK2.1 in both the nucleus and the plasma membrane. In addition, VIGS indicated that CiPawSnRK2.1-silenced pecan seedling leaves display significantly reduced salt tolerance. Y2H and LCI assays verified that CiPawPP2C3 can interact with CiPawPYL5, CiPawPYL8, and CiPawSnRK2.1. This study characterizes the role of CiPawSnRK2.1 in salt stress and lays the groundwork for exploring the CiPawPYL-PP2C-SnRK module, highlighting the need to investigate the roles of other components in the pecan ABA signaling pathway., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Genome wide analysis identified 14 OBPs in B. tabaci Asia II-1, of which six are new to science. Phylogenetic analysis traced their diversity and evolutionary lineage among Hemipteran insects. Comparative analysis reclassified the OBP gene families among B. tabaci cryptic species: Asia I, II-1, MEAM1, and MED. The 14 OBPs were clustered on four chromosomes of B. tabaci. RT-qPCR showed high expression of OBP3 and 8 across all body tissues and OBP10 in the abdomen. Molecular docking showed that OBP 3 and 10 had high affinity bonding with different candidate ligands, with binding energies ranging from -5.0 to -7.7 kcal/mol. Competitive fluorescence binding assays revealed that β-caryophyllene and limonene had high binding affinities for OBP3 and 10, with their IC50 values ranging from 9.16 to 14 μmol·L-1 and KD values around 7 to 9 μmol·L-1. Behavioural assays revealed that β-caryophyllene and carvacrol were attractants, β-ocimene and limonene were repellents, and γ-terpinene and β-ocimene were oviposition deterrents to B. tabaci. Functional validation by RNAi demonstrated that OBP3 and OBP10 modulated host recognition of B. tabaci. This study expands our understanding of the genomic landscape of OBPs in B. tabaci, offering scope for developing novel pest control strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Genomic tumour profiling has a crucial role in the management of patients with solid cancers, as it helps selecting and prioritising therapeutic interventions based on prognostic and predictive biomarkers, as well as identifying markers of hereditary cancers. Harmonised approaches to interpret the results of genomic testing are needed to support physicians in their decision making, prevent inequalities in precision medicine and maximise patient benefit from available cancer management options., Methods: The European Society for Medical Oncology (ESMO) Translational Research and Precision Medicine Working Group assembled a group of international experts to propose recommendations for preparing clinical genomic reports for solid cancers. These recommendations aim to foster best practices in integrating genomic testing within clinical settings. After review of available evidence, several rounds of surveys and focused discussions were conducted to reach consensus on the recommendation statements. Only consensus recommendations were reported. Recommendation statements were graded in two tiers based on their clinical importance: level A (required to maintain common standards in reporting) and level B (optional but necessary to achieve ideal practice)., Results: Genomics reports should present key information in a front page(s) followed by supplementary information in one or more appendices. Reports should be structured into sections: (i) patient and sample details; (ii) assay and data analysis characteristics; (iii) sample-specific assay performance and quality control; (iv) genomic alterations and their functional annotation; (v) clinical actionability assessment and matching to potential therapy indications; and (vi) summary of the main findings. Specific recommendations to prepare each of these sections are made., Conclusions: We present a set of recommendations aimed at structuring genomics reports to enhance physician comprehension of genomic profiling results for solid cancers. Communication between ordering physicians and professionals reporting genomic data is key to minimise uncertainties and to optimise the impact of genomic tests in patient care., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Purpose: Pediatric cholestasis is the phenotypic expression of clinically and genetically heterogeneous disorders of bile acid synthesis and flow. Although a growing number of monogenic causes of pediatric cholestasis have been identified, the majority of cases remain undiagnosed molecularly., Methods: In a cohort of 299 pediatric participants (279 families) with intrahepatic cholestasis, we performed exome sequencing as a first-tier diagnostic test., Results: A likely causal variant was identified in 135 families (48.56%). These comprise 135 families that harbor variants spanning 37 genes with established or tentative links to cholestasis. In addition, we propose a novel candidate gene (PSKH1) (HGNC:9529) in 4 families. PSKH1 was particularly compelling because of strong linkage in 3 consanguineous families who shared a novel hepatorenal ciliopathy phenotype. Two of the 4 families shared a founder homozygous variant, whereas the third and fourth had different homozygous variants in PSKH1. PSKH1 encodes a putative protein serine kinase of unknown function. Patient fibroblasts displayed abnormal cilia that are long and show abnormal transport. A homozygous Pskh1 mutant mouse faithfully recapitulated the human phenotype and displayed abnormally long cilia. The phenotype could be rationalized by the loss of catalytic activity observed for each recombinant PSKH1 variant using in vitro kinase assays., Conclusion: Our results support the use of genomics in the workup of pediatric cholestasis and reveal PSKH1-related hepatorenal ciliopathy as a novel candidate monogenic form., Competing Interests: Conflict of Interest The authors declare no conflicts of interest., (Copyright © 2024 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Genetic manipulation of hematopoietic stem cells (HSCs) is being developed as a therapeutic strategy for several inherited disorders. This field is rapidly evolving with several novel tools and techniques being employed to achieve desired genetic changes. While commercial products are now available for sickle cell disease, transfusion-dependent β-thalassemia, metachromatic leukodystrophy and adrenoleukodystrophy, several challenges remain in patient selection, HSC mobilization and collection, genetic manipulation of stem cells, conditioning, hematologic recovery and post-transplant complications, financial issues, equity of access and institutional and global preparedness. In this report, we explore the current state of development of these therapies and provide a comprehensive assessment of the challenges these therapies face as well as potential solutions., Competing Interests: Declaration of competing interest Ashish Gupta is a site principal investigator at University of Minnesota for clinical trials in genome editing for sickle cell disease sponsored by Bluebird Bio (NCT04293185) and Beam Therapeutics (NCT05456880). He is also the site principal investigator at University of Minnesota for clinical trials in genome editing for Hurler syndrome (NCT06149403). He has received consultancy fees from Vertex Pharmaceuticals and is on speaker bureau for Emerging Therapies Solutions. He also has research funding from Jazz Pharmaceuticals for an investigator initiated trial. Akshay Sharma has received consultant fees from Spotlight Therapeutics, Medexus Inc., Vertex Pharmaceuticals, Sangamo Therapeutics and Editas Medicine. He is a medical monitor for an RCI BMT clinical trial for which he receives financial compensation. He has also received research funding from CRISPR Therapeutics and honoraria from Vindico Medical Education. Akshay Sharma is also the St. Jude Children's Research Hospital site principal investigator for clinical trials of genome editing for sickle cell disease sponsored by Vertex Pharmaceuticals/CRISPR Therapeutics (NCT03745287), Novartis Pharmaceuticals (NCT04443907) and Beam Therapeutics (NCT05456880). The industry sponsors provide funding for the clinical trials, which includes salary support paid to the investigator's institution. Akshay Sharma has no direct financial interest in these therapies. Jaap Jan Boelens has received consultant fees from Sanofi, Sobi, Merck, Immusoft and Smart Immune, is the MSKCC site PI for Novartis Pharmaceuticals (NCT04443907) and received research funding from Sanofi (for investigator-initiated research). Jaap Jan Boelens is also the chair of an independent data safety monitoring board (for bluebird bio gene therapy trials), for which he receives compensation (CRO; Advanced Clinical). Susan Prockop has received support for the conduct of clinical trials from AlloVir, Atara, and Jasper through Boston Children's Hospital. She has received an honorarium from Pierre Fabre and Regeneron and consults for CellEvolve, Smart Immune and Century. She has IP related to the implementation of third-party viral-specific T cells, with all rights assigned to Memorial Sloan Kettering Cancer Center. Chrystal U. Louis has equity in and is an employee of TScan Therapeutics. The other authors have nothing to disclose., (Copyright © 2024 International Society for Cell & Gene Therapy. Published by Elsevier Inc. All rights reserved.)

Purpose: Clinical next-generation sequencing is an effective approach for identifying pathogenic sequence variants that are medically actionable for participants and families but are not associated with the participant's primary diagnosis. These variants are called secondary findings (SFs). According to the literature, there is no report of the types and frequencies of SFs in a large pediatric cohort that includes substantial African-American participants. We sought to investigate the types (including American College of Medical Genetics and Genomics [ACMG] and non-ACMG-recommended gene lists), frequencies, and rates of SFs, as well as the effects of SF disclosure on the participants and families of a large pediatric cohort at the Center for Applied Genomics at The Children's Hospital of Philadelphia., Methods: We systematically identified pathogenic (P) and likely pathogenic (LP) variants in established disease-causing genes, adhering to ACMG v3.2 secondary finding guidelines and beyond. For non-ACMG SFs, akin to incidental findings in clinical settings, we utilized a set of criteria focusing on pediatric onset, high penetrance, moderate to severe phenotypes, and the clinical actionability of the variants. This criteria-based approach was applied rather than using a fixed gene list to ensure that the variants identified are likely to affect participant health significantly. To identify and categorize these variants, we used a clinical-grade variant classification standard per ACMG/AMP recommendations; additionally, we conducted a detailed literature search to ensure a comprehensive exploration of potential SFs relevant to pediatric participants., Results: We report a distinctive distribution of 1464 P/LP SF variants in 16,713 participants. There were 427 unique variants in ACMG genes and 265 in non-ACMG genes. The most frequently mutated genes among the ACMG and non-ACMG gene lists were TTR(41.6%) and CHEK2 (7.16%), respectively. Overall, variants of possible medical importance were found in 8.76% of participants in both ACMG (5.81%) and non-ACMG (2.95%) genes., Conclusion: Our study revealed that 8.76% of a large, multiethnic pediatric cohort carried actionable secondary genetic findings, with 5.81% in ACMG genes and 2.95% in non-ACMG genes. These findings emphasize the importance of including diverse populations in genetic research to ensure that all groups benefit from early identification of disease risks. Our results provide a foundation for expanding the ACMG gene list and improving clinical care through early interventions., Competing Interests: Conflict of Interest Hakon Hakonarson and Children’s Hospital of Philadelphia are equity holders in Nobias Therapeutics, developing mitogen-activated protein kinase inhibitor therapy for complex lymphatic anomalies. All other authors declare no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Purpose: As population-based screening programs to identify genetic conditions in adults using genomic sequencing (GS) are increasingly available, validated patient-centered outcome measures are needed to understand participants' experience. We aimed to develop and validate an instrument to assess the perceived utility of GS in the context of adult screening., Methods: Informed by a 5-domain conceptual model, we used a 5-step approach to instrument development and validation: (1) item writing, (2) cognitive testing, (3) pilot testing and item reduction, (4) psychometric testing, and (5) evaluation of construct validity. Adults undergoing risk-based or population-based GS who had received GS results as part of ongoing research studies participated in structured cognitive interviews and 2 rounds of surveys. After item pool refinement, we conducted an exploratory factor analysis and calculated Pearson correlations with related instruments., Results: We derived the 18-item Adult Screening version of the GENEtic Utility scale (total sum score α = .87). Mirroring the Pediatric Diagnostic version, the instrument has a 2-factor structure, including an Informational Utility subscale (14 items, α = .89) and an Emotional Utility subscale (4 items, α = .75). The Informational Utility subscale was strongly associated with empowerment and personal utility of GS. Correlations of the Emotional Utility subscale with psychosocial impact and anxiety and depression were weak to moderate., Conclusion: Initial psychometric testing of the Adult Screening GENEtic Utility scale demonstrates its promise, and additional validation in translational genomics research is warranted., Competing Interests: Conflict of Interest Dr Smith’s work has been funded by the NIH. She has received compensation as a consultant for Illumina, Inc and RTI International, unrelated to this work. Mr Buchanan has an equity stake in MeTree, Inc and You, Inc, unrelated to this work. Dr McGuire is a member of the Scientific Advisory Board for Nurture Genomics. All other authors declare no conflicts of interest., (Copyright © 2024 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Background: Somatic genetic alterations of the estrogen receptor 1 gene (ESR1) are enriched in endocrine therapy-resistant, estrogen receptor-positive (ER+) metastatic breast cancer (mBC). Herein, we investigated and compared the clinical and genomic landscape of ESR1-mutant (ESR1 MUT ) and ESR1 wild type (ESR1 WT ) ER+/ human epidermal growth factor receptor 2 (HER2)- mBCs., Methods: Clinical and genomic data were retrieved from cBioPortal using the publicly-available MSK MetTropism dataset. Metastatic, ER+/HER2- mBC samples were included in the analysis. Only oncogenic and likely oncogenic alterations according to OncoKB were included. Statistical analyses were carried out using alpha level of 0.05, with a false discovery rate threshold of 10% for multiple comparisons using the Benjamini-Hochberg method., Results: Among 679 samples, 136 ESR1 MUT among 131 tumors were found (19.2%). The frequency of ESR1 MUT was higher in ductal versus lobular mBC (21.2% versus 13.8%, P = 0.052) and enriched in liver metastasis compared with other sites (22.5% versus 12.7%; q = 0.02). Compared with ESR1 WT mBC, ESR1 MUT tumors showed higher fraction of genome altered (FGA) {[0.28 interquartile range (IQR), 0.15-0.43] versus 0.22 (0.11-0.38); P = 0.04} and tumor mutational burden (TMB) [4.89 (IQR 3.46-6.85) versus 3.92 (2.59-6.05) mut/Mb; P = 0.001]. Tumors harboring p.E380X alterations showed higher TMB compared with those with H11-12 alterations [8.24 (IQR 5.06-15.3) versus 4.89 (IQR 3.46-6.75) mut/Mb; P = 0.01]. Genetic alterations of TP53 were enriched in ESR1 WT tumors (36% versus 14%) [odds ratio (OR) 3.17, 95% confidence interval (CI) 1.88-5.64, q = 0.001]. Considering signaling pathways, ESR1 MUT tumors showed a lower occurrence of TP53 (OR 0.48, 95% CI 0.30-0.74; q = 0.003) and MAPK (OR 0.29, 95% CI 0.11-0.65; q = 0.009) alterations. TP53 (q < 0.001), CDH1 (q < 0.001), and ERBB2 (q < 0.001) demonstrated mutual exclusivity with ESR1 MUT ., Conclusions: ER+/HER2- mBCs carrying ESR1 MUT exhibit a divergent genomic background, characterized by a lower prevalence of TP53 and MAPK pathway alterations. Less common ESR1 alterations falling outside the H11-H12 region seem to occur in tumors with higher TMB, deserving further investigation to understand their potential actionability., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Next-generation sequencing (NGS) has become widely available but molecular profiling-guided therapy (MGT) had not been well established in the real world due to lack of available therapies and expertise to match treatment. Our study was designed to test the feasibility of a nationwide platform of NGS-guided MGT recommended by a central molecular tumor board (cMTB) for metastatic solid tumors., Patients and Methods: Patients with advanced or metastatic solid tumors with available NGS results and without standard treatment were enrolled. The cMTB interpreted the patients' NGS reports and recommended the following: (i) investigational medicinal products (IMPs) approved in other indications; (ii) alternative treatments; (iii) clinical trials. The primary variables were the proportion of patients with actionable genomic alterations and those receiving MGT as per cMTB recommendations. Others included treatment duration (TD), overall response rate (ORR), disease control rate (DCR), and safety., Results: From February 2021 to February 2022, 193 cases [99 (51.3%) men; median age 58 years (range 24-88 years); median line of previous treatment 3 (range 0-9)] from 29 sites were enrolled for 60 cMTB sessions. The median time from case submission to cMTB discussion was 7 days (range 2-20 days), and to IMP treatment initiation was 28 days (range 14-90 days). Actionable genetic alterations were found in 145 patients (75.1%). A total of 89 (46.1%) patients received actual dosing of IMPs, and 10 (5.2%) were enrolled in cMTB-recommended clinical trials, achieving an MGT rate of 51.3%. ORR and DCR of IMPs were 10.1% and 72.5%, respectively. The median TD was 3.5 months [95% confidence interval (CI) 2.8-5.5 months], and the 4-month TD rate was 44.9%. The median overall survival of patients who received IMPs was 6.9 months (95% CI 5.2-10.0 months)., Conclusion: KOSMOS confirmed the feasibility of MGT recommended by the cMTB, achieving a high MGT match rate and promising effectiveness in heavily pretreated advanced cancer patients., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Single-cell multi-omics and spatial technology have been widely applied to biomedical studies and recently to environmental studies. The cell size detected by single-cell omics ranges from ∼2 µm (e.g., Bacillus subtilis) to ∼120 µm (e.g., human oocytes). Simultaneous detection of single-cell multi-omics is available to human and plant tissues while limited to microbial samples. Spatial technology enables mapping the detected biomolecules in situ. The recent advances in Matrix-Assisted Laser Desorption/Ionization-Mass Spectrometry Imaging and Micro/Nanodroplet Processing in One Pot for Trace Samples for the first time allow the application of spatial multi-omics in highly heterogeneous environmental samples composed of plants, fungi, and bacteria. We envision that these technologies will continue to advance our understanding of unique cell types, their developmental trajectory, and the intercellular signaling and interaction within biological samples., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2024 Battelle Memorial Institute. Published by Elsevier Ltd.. All rights reserved.)

Cytokinin oxidase/dehydrogenase (CKX) regulates cytokinin levels in plants which are vital for plant growth and development. However, there is a paucity of evidence regarding their role in controlling embryo/seed development in pigeonpea. This comprehensive study provides information on the identification and characterization of CKX genes in pigeonpea. A genome-wide analysis identified 18 CKX genes, each with distinct structure, expression patterns, and possible diverse functions. Domain analysis revealed the presence of the sequences including FAD and CK-Binding domain, and subcellular localization analysis showed that almost 50 % of them reside within the nucleus. They were observed to be located unevenly on chromosome numbers 2, 4, 6, 7, and 11 with a majority of them present on the scaffolds. The 8 homologous pairs and various orthologous gene pairs provided further insights into their evolution pattern. Further, SNP/Indels variation in CKX genes and haplotype groups among contrasting genotypes for SNPP (seed number per pod) were analyzed. Spatiotemporal expression analysis revealed the significant expression pattern of CcCKX15, CcCKX17, and CcCKX2 in genotypes carrying low SNPP reiterating their possible role as negative regulators. These genes can be potential targets to undertake seed and biomass improvement in pigeonpea., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The integration of multi-omics data offers a robust approach to understanding the complexity of diseases by combining information from various biological levels, such as genomics, transcriptomics, proteomics, and metabolomics. This integrated approach is essential for a comprehensive understanding of disease mechanisms and for developing more effective diagnostic and therapeutic strategies. Nevertheless, most current methodologies fail to effectively extract both shared and specific representations from omics data. This study introduces MOSDNET, a multi-omics classification framework that effectively extracts shared and specific representations. This framework leverages Simplified Multi-view Deep Discriminant Representation Learning (S-MDDR) and Dynamic Edge GCN (DEGCN) to enhance the accuracy and efficiency of disease classification. Initially, MOSDNET utilizes S-MDDR to establish similarity and orthogonal constraints for extracting these representations, which are then concatenated to integrate the multi-omics data. Subsequently, MOSDNET constructs a comprehensive view of the sample data by employing patient similarity networks. By incorporating similarity networks into DEGCN, MOSDNET learns intricate network structures and node representations, which enables superior classification outcomes. MOSDNET is trained through a multitask learning approach, effectively leveraging the complementary knowledge from both the data integration and classification components. After conducting extensive comparative experiments, we have conclusively demonstrated that MOSDNET outperforms leading state-of-the-art multi-omics classification models in terms of classification accuracy. Simultaneously, we employ MOSDNET to identify pivotal biomarkers within the multi-omics data, providing insights into disease etiology and progression., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Purpose: Elective genomic testing (EGT) is increasingly available clinically. Limited real-world evidence exists about attitudes and knowledge of EGT recipients., Methods: After web-based education, patients who enrolled in an EGT program at a rural nonprofit health care system completed a survey that assessed attitudes, knowledge, and risk perceptions., Results: From August 2020 to April 2022, 5920 patients completed the survey and received testing. Patients most frequently cited interest in learning their personal disease risks as their primary motivation. Patients most often expected results to guide medication management (74.0%), prevent future disease (70.4%), and provide information about risks to offspring (65.4%). Patients were "very concerned" most frequently about the privacy of genetic information (19.8%) and how well testing predicted disease risks (18.0%). On average, patients answered 6.7 of 11 knowledge items correctly (61.3%). They more often rated their risks for colon and breast cancers as lower rather than higher than the average person but more often rated their risk for a heart attack as higher rather than lower than the average person (all P < .001)., Conclusion: Patients pursued EGT because of the utility expectations but often misunderstood the test's capabilities., Competing Interests: Conflict of Interest Robert C. Green, Kurt D. Christensen, Emilie S. Zoltick, Madison R. Hickingbotham, Jessica L. LeBlanc, and Lauren N. Galbraith were supported by a research grant from Sanford Health. Madison R. Hickingbotham, Madison R. Hickingbotham, Ann Chen Wu, Lauren N. Galbraith, and Jessica L. LeBlanc have been funded by National Center for Advancing Translational Sciences (NCATS), National Heart, Lung, and Blood Institute (NHLBI), and National Institute of Child Health and Human Development (NICHD). Ann Chen Wu has received grants from NICHD, NHLBI, and GlaxoSmithKline. Catherine Hajek is an employee of Helix OpCo. Christine Y. Lu undertook contract work with Illumina Inc outside the submitted work and has received research grants and contracts from National Human Genome Research Institute (NHGRI), NIMH, NICHD, National Cancer Institute, and Centers for Disease Control and Prevention. Emilie S. Zoltick has been funded by NIMHD. Hadley Stevens Smith has been funded by NHGRI and NICHD, has consulted for Illumina, Inc and received compensation, and has received compensation from Elsevier and the Eastern Society of Pediatric Research. Kurt D. Christensen has received research grants from NHGRI, NCATS, NHLBI, and NICHD. Lauren N. Galbraith is an employee of Pfizer, Inc. Robert C. Green has received compensation for advising the following companies: AIA, Allelica, Atria, Fabric, Genome Web, Genomic Life, Verily, and VinBigData; is cofounder of Genome Medical and Nurture Genomics; and has received research grants from NCATS, NHLBI, the Danaher Foundation, the Southcentral Foundation, GRAIL, and Beaumont Health. All other authors declare no conflicts of interest., (Copyright © 2024 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Purpose: To develop and evaluate a scalable national program to build confidence, competence and capability in the use of rapid genomic testing (rGT) in the acute pediatric setting., Methods: We used theory-informed approaches to design a modular, adaptive program of blended learning aimed at diverse professional groups involved in acute pediatric care. The program comprised 4 online learning modules and an online workshop and was centered on case-based learning. We evaluated the program using the Kirkpatrick 4-level model of training evaluation and report our findings using the Reporting Item Standards for Education and its Evaluation (RISE2) guidelines for genomics education and evaluation., Results: Two hundred and two participants engaged with at least 1 component of the program. Participants self-reported increased confidence in using rGT, (P < .001), and quiz responses objectively demonstrated increased competence (eg, correct responses to a question on pretest counseling increased from 30% to 64%; P < .001). Additionally, their capability in applying genomic principles to simulated clinical cases increased (P < .001), as did their desire to take on more responsibility for performing rGT. The clinical interpretation of more complex test results (such as negative results or variants of uncertain significance) appeared to be more challenging, indicating a need for targeted education in this area., Conclusion: The program format was effective in delivering multidisciplinary and wide-scale genomics education in the acute care context. The modular approach we have developed now lends itself to application in other medical specialties or areas of health care., Competing Interests: Conflict of Interest The authors declare no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Since the first novel gene discovery for a Mendelian condition was made via exome sequencing, the rapid increase in the number of genes known to underlie Mendelian conditions coupled with the adoption of exome (and more recently, genome) sequencing by diagnostic testing labs has changed the landscape of genomic testing for rare diseases. Specifically, many individuals suspected to have a Mendelian condition are now routinely offered clinical ES. This commonly results in a precise genetic diagnosis but frequently overlooks the identification of novel candidate genes. Such candidates are also less likely to be identified in the absence of large-scale gene discovery research programs. Accordingly, clinical laboratories have both the opportunity, and some might argue a responsibility, to contribute to novel gene discovery, which should, in turn, increase the diagnostic yield for many conditions. However, clinical diagnostic laboratories must necessarily balance priorities for throughput, turnaround time, cost efficiency, clinician preferences, and regulatory constraints and often do not have the infrastructure or resources to effectively participate in either clinical translational or basic genome science research efforts. For these and other reasons, many laboratories have historically refrained from broadly sharing potentially pathogenic variants in novel genes via networks such as Matchmaker Exchange, much less reporting such results to ordering providers. Efforts to report such results are further complicated by a lack of guidelines for clinical reporting and interpretation of variants in novel candidate genes. Nevertheless, there are myriad benefits for many stakeholders, including patients/families, clinicians, and researchers, if clinical laboratories systematically and routinely identify, share, and report novel candidate genes. To facilitate this change in practice, we developed criteria for triaging, sharing, and reporting novel candidate genes that are most likely to be promptly validated as underlying a Mendelian condition and translated to use in clinical settings., Competing Interests: Conflict of Interest All authors of this manuscript are funded by the NIH. Erica Smith is a current employee of Ambry Genetics and a stockholder of Invitae genetics. Megan H. Hawley is an employee of Invitae and own stock in the company. Michael J. Bamshad is the chair of the Scientific Advisory Board of GeneDx and receives funding from the American Society of Human Genetics as the Editor-in-Chief of HGG Advances. Jessica X. Chong receives funding from the American Society of Human Genetics as the Deputy Editor of HGG Advances. Heidi L. Rehm has received rare-disease research funding from Microsoft and Illumina and compensation as a past member of the scientific advisory board of Genome Medical., (Copyright © 2024 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Medical laboratory services enable precise measurement of thousands of biomolecules and have become an inseparable part of high-quality healthcare services, exerting a profound influence on global health outcomes. The integration of omics technologies into laboratory medicine has transformed healthcare, enabling personalized treatments and interventions based on individuals' distinct genetic and metabolic profiles. Interpreting laboratory data relies on reliable reference values. Presently, population-derived references are used for individuals, risking misinterpretation due to population heterogeneity, and leading to medical errors. Thus, personalized references are crucial for precise interpretation of individual laboratory results, and the interpretation of omics data should be based on individualized reference values. We reviewed recent advancements in personalized laboratory medicine, focusing on personalized omics, and discussed strategies for implementing personalized statistical approaches in omics technologies to improve global health and concluded that personalized statistical algorithms for interpretation of omics data have great potential to enhance global health. Finally, we demonstrated that the convergence of nanotechnology and omics sciences is transforming personalized laboratory medicine by providing unparalleled diagnostic precision and innovative therapeutic strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The human brain is composed of increasingly recognized heterogeneous cell types. Applying single-cell genomics to brain tissue can elucidate relative cell type proportions as well as differential gene expression and regulation among humans and other species. Here, we review recent studies that utilized high-throughput genomics approaches to compare brains among species at single-cell resolution. These studies identified genomic elements that are similar among species as well as evolutionary novelties on the human lineage. We focus on those human-relevant innovations and discuss the biological implications of these modifications. Finally, we discuss areas of comparative single-cell genomics that remain unexplored either due to needed technological advances or due to biological availability at the brain region or species level., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Rhizoctonia solani is a soil-borne pathogen with 14 anastomosis groups (AGs), and different subgroups are genetically diverse. However, the genetic factors contributing to the pathogenicity of the fungus have not been well characterized. In this study, the genome of R. solani AG1-ZJ was sequenced. As the result, a 41.57 Mb draft genome containing 12,197 putative coding genes was obtained. Comparative genomic analysis of 11 different AGs revealed conservation and unique characteristics between the AGs. Furthermore, a novel effector family containing a 68 amino acid conserved domain unique in basidiomycetous fungi was characterized. Two effectors containing the conserved domain in AG4-JY were identified, and named as RsUEB1 and RsUEB2. Furthermore, the spray-induced gene silencing strategy was used to generate a dsRNA capable of silencing the conserved domain sequence of RsUEB1 and RsUEB2. This dsRNA can significantly reduce the expression of RsUEB1 and RsUEB2 and the pathogenicity of AG4-JY on foxtail millet, maize, rice and wheat. In conclusion, this study provides significant insights into the pathogenicity mechanisms of R. solani. The identification of the conserved domain and the successful use of dsRNA silencing of the gene containing the conserved domain will offer a new strategy for controlling sheath blight in cereal crops., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Phenotypic variation within the skeleton has biological, behavioral, and biomedical functional implications for individuals and species. Thus, it is critical to understand how genomic, environmental, and mediating regulatory factors combine and interact to drive skeletal trait development and evolution. Recent research efforts to clarify these mechanisms have been made possible by expanded collections of genomic and phenotypic data from in vivo skeletal tissues, as well as the development of relevant in vitro skeletal cell culture systems. This review outlines this current work and recommends that continued exploration of this complexity should include an increased focus on how interactions between genomic and physiologically relevant contexts contribute to skeletal trait variation at population and evolutionary scales., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Young women with breast cancer (YWBC; ≤40 years) often have a poorer prognosis than older women with breast cancer (OWBC; ≥65 years). We explored molecular features of tumors from YWBC and OWBC to identify a biologic connection for these patterns., Materials and Methods: We retrospectively analyzed the molecular profiles of 1879 breast tumors. Testing included immunohistochemistry (IHC), in situ hybridization (ISH), and next-generation sequencing. Statistical analyses included Pearson's chi 2 test for comparisons, with significance defined as FDR (false discovery rate)-P < .05., Results: TP53 and BRCA1 somatic mutations were more common in YWBC tumors than in OWBC tumors (53%, 42%; P = .0001, FDR-P = .0025 and 7%, 2%; P = .0001, FDR-P = .0025; respectively). Conversely, OWBC tumors had higher androgen receptor expression (55%, 45%; P = .0002, FDR-P = .0025) higher PD-L1 expression detected by IHC (8%, 5%; P = .0476, FDR-P = .2754), and more frequent PIK3CA mutations (33%, 17%; P = < .0001, FDR-P = < .0001). Among HR+/HER2- samples, YWBC had more gene amplifications in FGF3 (27%, 10%; P = .0353, FDR-P = .2462), FGF4 (27%, 9%; P = .0218, FDR-P = .1668), FGF19 (30%, 12%; P = .034, FDR-P = .2462) and CCND1 (37%, 18%; P = .0344, FDR-P = .2462) than OWBC., Conclusions: Our data suggest distinct molecular aberrations exist between YWBC and OWBC. Exploiting these molecular changes could refine our treatment strategies in YWBC and OWBC., Competing Interests: Disclosure Arielle L. Heeke: consulting (Caris Life Sciences). Wei Sha: no relevant conflicts to disclose. Rebecca Feldman: employee (Caris Life Sciences) Julie Fisher: no relevant conflicts to disclose. Lejla Hadzikadic-Gusic: no relevant conflicts to disclose. James T. Symanowski: no relevant conflicts to disclose. Richard L. White, Jr: no relevant conflicts to disclose. Antoinette R. Tan: meeting travel and accommodations (Caris Life Sciences)., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Abstract: B-cell progenitor acute lymphoblastic leukemia (BCP-ALL) is the most common childhood malignancy and is driven by multiple genetic alterations that cause maturation arrest and accumulation of abnormal progenitor B cells. Current treatment protocols with chemotherapy have led to favorable outcomes but are associated with significant toxicity and risk of side effects, highlighting the necessity for highly effective, less toxic, targeted drugs, even in subtypes with a favorable outcome. Here, we used multimodal single-cell sequencing to delineate the transcriptional, epigenetic, and immunophenotypic characteristics of 23 childhood BCP-ALLs belonging to the BCR::ABL1+, ETV6::RUNX1+, high hyperdiploid, and recently discovered DUX4-rearranged (DUX4-r) subtypes. Projection of the ALL cells along the normal hematopoietic differentiation axis revealed a diversity in the maturation pattern between the different BCP-ALL subtypes. Although the BCR::ABL1+, ETV6::RUNX1+, and high hyperdiploidy cells mainly showed similarities to normal pro-B cells, DUX4-r ALL cells also displayed transcriptional signatures resembling mature B cells. Focusing on the DUX4-r subtype, we found that the blast population displayed not only multilineage priming toward nonhematopoietic cells, myeloid, and T-cell lineages, but also an activation of phosphatidylinositol 3-kinase (PI3K)/AKT signaling that sensitized the cells to PI3K inhibition in vivo. Given the multilineage priming of DUX4-r blasts with aberrant expression of myeloid marker CD371 (CLL-1), we generated chimeric antigen receptor T cells, which effectively eliminated DUX4-r ALL cells in vivo. These results provide a detailed characterization of BCP-ALL at the single-cell level and reveal therapeutic vulnerabilities in the DUX4-r subtype, with implications for the understanding of ALL biology and new therapeutic strategies., (© 2024 American Society of Hematology. Published by Elsevier Inc. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

Abstract: Recent advancements in single-cell genomics have enriched our understanding of hematopoiesis, providing intricate details about hematopoietic stem cell biology, differentiation, and lineage commitment. Technological advancements have highlighted extensive heterogeneity of cell populations and continuity of differentiation routes. Nevertheless, intermediate "attractor" states signify structure in stem and progenitor populations that link state transition dynamics to fate potential. We discuss how innovative model systems quantify lineage bias and how stress accelerates differentiation, thereby reducing fate plasticity compared with native hematopoiesis. We conclude by offering our perspective on the current model of hematopoiesis and discuss how a more precise understanding can translate to strategies that extend healthy hematopoiesis and prevent disease., (© 2024 American Society of Hematology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.)

We introduce XGR-model (or XGRm), a web server made accessible at http://www.xgrm.pro, with the aim of meeting the increasing demand for effectively interpreting summary-level genomic data in model organisms. Currently, it hosts two enrichment analysers and two subnetwork analysers to support enrichment and subnetwork analyses for user-input mouse genomic data, whether gene-centric or genomic region-centric. The enrichment analysers identify ontology term enrichments for input genes (GElyser) or for genes linked from input genomic regions (RElyser). The subnetwork analysers rely on our previously established network algorithm to identify gene subnetworks from input gene-centric summary data (GSlyser) or from input region-centric summary data (RSlyser), leveraging network information about either functional interactions or pathway-derived interactions. Collectively, XGRm offers an all-in-one solution for gaining systems biology insights into summary-level genomic data in mice, underpinned by our commitment to regular updates as well as natural extensions to other model organisms., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Competing Interests: Disclosures The authors have no conflicts of interest to disclose.

As one of the most specific, yet most diverse of human behaviors, language is shaped by both genomic and extra-genomic evolution. Sharing methods and models between these modes of evolution has significantly advanced our understanding of language and inspired generalized theories of its evolution. Progress is hampered, however, by the fact that the extra-genomic evolution of languages, i.e. linguistic evolution, maps only partially to other forms of evolution. Contrasting it with the biological evolution of eukaryotes and the cultural evolution of technology as the best understood models, we show that linguistic evolution is special by yielding a stationary dynamic rather than stable solutions, and that this dynamic allows the use of language change for social differentiation while maintaining its global adaptiveness. Linguistic evolution furthermore differs from technological evolution by requiring vertical transmission, allowing the reconstruction of phylogenies; and it differs from eukaryotic biological evolution by foregoing a genotype vs phenotype distinction, allowing deliberate and biased change. Recognising these differences will improve our empirical tools and open new avenues for analyzing how linguistic, cultural, and biological evolution interacted with each other when language emerged in the hominin lineage. Importantly, our framework will help to cope with unprecedented scientific and ethical challenges that presently arise from how rapid cultural evolution impacts language, most urgently from interventional clinical tools for language disorders, potential epigenetic effects of technology on language, artificial intelligence and linguistic communicators, and global losses of linguistic diversity and identity. Beyond language, the distinctions made here allow identifying variation in other forms of biological and cultural evolution, developing new perspectives for empirical research., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Single-cell genomics provide researchers with tools to assess host-pathogen interactions at a resolution previously inaccessible. Transcriptome analysis, epigenome analysis, and immune profiling techniques allow for a better comprehension of the heterogeneity underlying both the host response and infectious agents. Here, we highlight technological advancements and data analysis workflows that increase our understanding of host-pathogen interactions at the single-cell level. We review various studies that have used these tools to better understand host-pathogen dynamics in a variety of infectious disease contexts, including viral, bacterial, and parasitic diseases. We conclude by discussing how single-cell genomics can advance our understanding of host-pathogen interactions., (Copyright © 2024 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

Background: Mutation or amplification of the mesenchymal-epithelial transition (MET) tyrosine kinase receptor causes dysregulation of receptor function and stimulates tumor growth in non-small cell lung cancer (NSCLC) with the most common mutation being MET exon 14 (METex14). We sought to compare the genomic and immune landscape of MET-altered NSCLC with MET wild-type NSCLC., Methods: 18,047 NSCLC tumors were sequenced with Tempus xT assay. Tumors were categorized based on MET exon 14 (METex14) mutations; low MET amplification defined as a copy number gain (CNG) 6-9, high MET amplification defined as CNG ≥ 10, and MET other type mutations. Immuno-oncology (IO) biomarkers and the frequency of other somatic gene alterations were compared across MET-altered and MET wild-type groups., Results: 276 (1.53%) METex14, 138 (0.76%) high METamp, 63 (0.35%) low METamp, 27 (0.15%) MET other, and 17,543 (97%) MET wild-type were identified. Patients with any MET mutation including METex14 were older, while patients with METex14 were more frequently female and nonsmokers. MET gene expression was highest in METamp tumors. PD-L1 positivity rates were higher in MET-altered groups than MET wild-type. METex14 exhibited the lowest tumor mutational burden (TMB) and lowest neoantigen tumor burden (NTB). METamp exhibited the lowest proportion of CD4 T cells and the highest proportion of NK cells. There were significant differences in co-alterations between METamp and METex14., Conclusions: METex14 tumors exhibited differences in IO biomarkers and the somatic landscape compared to non-METex14 NSCLC tumors. Variations in immune profiles can affect immunotherapy selection in MET-altered NSCLC and require further exploration., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Purpose: Germline testing in pediatric cancer presents opportunities and challenges. Understanding family perspectives, experiences, and preferences will optimize integration into routine care., Methods: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we searched 4 databases for studies exploring perspectives, experiences, and preferences of parents/caregivers and/or patients regarding germline testing of children with cancer. Qualitative and quantitative data were extracted, organized, and summarized by research question and themes., Results: We identified 2286 unique articles, of which 24 were included. Interest in and uptake of testing was high. Families were motivated by altruism and a desire for inheritance/causation information. Testing barriers included psychological concerns, timing of the testing approach if offered at diagnosis or in a high-risk cancer setting and privacy/discrimination. Testing experiences highlighted challenges yet also positive impacts, with results providing psychological relief and informing proactive decision making. Timing preferences varied; however, allowing time to adjust to a new diagnosis was a common theme. Most wanted to receive as many germline sequencing-related results as possible., Conclusion: Findings underscore the importance of integrating germline analyses into pediatric cancer care with flexibility and support for families facing challenges. Where possible, consent should be provided at a time that suits each family's situation with access to information aligning with their needs and preferences., Prospero: CRD42023444890., Competing Interests: Conflict of Interest The authors declare no conflicts of interest., (Copyright © 2024 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

The uncertainty resulting from missing genotypes in low-coverage whole-genome sequencing (LCWGS) data complicates genotype imputation. The aim of this study is to find out an optimal strategy for accurately imputing LCWGS data and assess its effectiveness for genomic prediction (GP) and genome-wide association study (GWAS) on economically important traits of Large White pigs. The LCWGS data of 1 423 Large White pigs were imputed using three different strategies: (1) using the high-coverage whole-genome sequencing (HCWGS) of 30 key progenitors as the reference panel (Ref&#95;LG); (2) mixing HCWGS of key progenitors with LCWGS (Mix&#95;HLG) and (3) self-imputation in LCWGS (Within&#95;LG). Additionally, to compare the imputation effects of LCWGS, we also imputed SNP chip data of 1 423 Large White pigs to the whole-genome sequencing level using the reference panel consisting of key progenitors (Ref&#95;SNP). To evaluate effects of the imputed sequencing data, we compared the accuracies of GP and statistical power of GWAS for four reproductive traits based on the chip data, sequencing data imputed from chip data and LCWGS data using an optimal strategy. The average imputation accuracies of the Within&#95;LG, Ref&#95;LG and Mix&#95;HLG were 0.9893, 0.9899 and 0.9875, respectively, which were higher than that of the Ref&#95;SNP (0.8522). Using the imputed sequencing data from LCWGS with the Ref&#95;LG imputation strategy, the accuracies of GP for four traits improved by approximately 0.31-1.04% compared to the chip data, and by 0.7-1.05% compared to the imputed sequencing data from chip data. Furthermore, by using the sequence data imputed from LCWGS with the Ref&#95;LG, 18 candidate genes were identified to be associated with the four reproductive traits of interest in Large White pigs: total number of piglets born - EPC2, MBD5, ORC4 and ACVR2A; number of piglets born healthy - IKBKE; total litter weight of piglets born alive - HSPA13 and CPA1; gestation length - GTF2H5, ITGAV, NFE2L2, CALCRL, ITGA4, STAT1, HOXD10, MSTN, COL5A2 and STAT4. With the exception of EPC2, ORC4, ACVR2A and MSTN, others represent novel candidates. Our findings can provide a reference for the application of LCWGS data in livestock and poultry., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Congenital heart disease (CHD) affects approximately 1 % of live births worldwide, making it the most common congenital anomaly in newborns. Recent advancements in genetics and genomics have significantly deepened our understanding of the genetics of CHDs. While the majority of CHD etiology remains unclear, evidence consistently indicates that genetics play a significant role in its development. CHD etiology holds promise for enhancing diagnosis and developing novel therapies to improve patient outcomes. In this review, we explore the contributions of both monogenic and polygenic factors of CHDs and highlight the transformative impact of emerging technologies on these fields. We also summarized the state-of-the-art techniques, including targeted next-generation sequencing (NGS), whole genome and whole exome sequencing (WGS, WES), single-cell RNA sequencing (scRNA-seq), human induced pluripotent stem cells (hiPSCs) and others, that have revolutionized our understanding of cardiovascular disease genetics both from diagnosis perspective and from disease mechanism perspective in children and young adults. These molecular diagnostic techniques have identified new genes and chromosomal regions involved in syndromic and non-syndromic CHD, enabling a more defined explanation of the underlying pathogenetic mechanisms. As our knowledge and technologies continue to evolve, they promise to enhance clinical outcomes and reduce the CHD burden worldwide., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The Mouse Variation Registry (MVAR) resource is a scalable registry of mouse single nucleotide variants and small indels and variant annotation. The resource accepts data in standard Variant Call Format (VCF) and assesses the uniqueness of the submitted variants via a canonicalization process. Novel variants are assigned a unique, persistent MVAR identifier; variants that are equivalent to an existing variant in the resource are associated with the existing identifier. Annotations for variant type, molecular consequence, impact, and genomic region in the context of specific transcripts and protein sequences are generated using Ensembl's Variant Effect Predictor (VEP) and Jannovar. Access to the data and annotations in MVAR are supported via an Application Programming Interface (API) and web application. Researchers can search the resource by gene symbol, genomic region, variant (expressed in Human Genome Variation Society syntax), refSNP identifiers, or MVAR identifiers. Tabular search results can be filtered by variant annotations (variant type, molecular consequence, impact, variant region) and viewed according to variant distribution across mouse strains. The registry currently comprises more than 99 million canonical single nucleotide variants for 581 strains of mice. MVAR is accessible from https://mvar.jax.org., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background and Objective: Stroke is a disease with high mortality and disability. Importantly, the fatality rate demonstrates a significant increase among patients afflicted by recurrent strokes compared to those experiencing their initial stroke episode. Currently, the existing research encounters three primary challenges. The first is the lack of a reliable, multi-omics image dataset related to stroke recurrence. The second is how to establish a high-performance feature extraction model and eliminate noise from continuous magnetic resonance imaging (MRI) data. The third is how to integration multi-omics data and dynamically weighted for different omics data., Methods: We systematically compiled MRI and conventional detection data from a cohort comprising 737 stroke patients and established PSTSZC, a multi-omics dataset for predicting stroke recurrence. We introduced the first-ever Integrated Multi-omics Prediction Model for Stroke Recurrence, MPSR, which is based on ResNet, L net -transformer, LSTM and dynamically weighted DNN. The MPSR model comprises two principal modules, the Feature Extraction Module, and the Integrated Multi-Omics Prediction Module. In the Feature Extraction module, we proposed a novel L net regularization layer, which effectively addresses noise issues in MRI data. In the Integrated Multi-omics Prediction Module, we propose a dynamic weighted mechanism based on evaluators, which mitigates the noise impact brought about by low-performance omics., Results: We compared seven single-omics models and six state-of-the-art multi-omics stroke recurrence models. The experimental results demonstrate that the MPSR model exhibited superior performance. The accuracy, AUROC, specificity, and sensitivity of the MPSR model can reach 0.96, 0.97, 1, and 0.94, respectively, which is higher than the results of contrast model., Conclusion: MPSR is the first available high-performance multi-omics prediction model for stroke recurrence. We assert that the MPSR model holds the potential to function as a valuable tool in assisting clinicians in accurately diagnosing individuals with a predisposition to stroke recurrence., Competing Interests: Declaration of competing interest All authors declare that we have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Purpose: Research that includes diverse patient populations is necessary to optimize implementation of telehealth., Methods: As part of a Clinical Sequencing Evidence-Generating Research Consortium cross-site study, we assessed satisfaction with mode of return of results (RoR) delivery across a diverse sample of participants receiving genetic testing results in person vs telemedicine (TM)., Results: Ninety-eight percent of participants were satisfied with their mode of results delivery. Participants receiving results by TM were more likely to report a preference for receiving results in a different way and challenges with providers noticing difficulties with understanding. More than 90% reported satisfaction across all items measuring support and interaction during sessions. Participants self-reporting Hispanic/Latino or Black/African American race and ethnicity compared with White/European American, fewer years of education, and having lower health literacy were more likely to report challenges with understanding the information or asking questions. Participants who were White/European American, had more years of education, and higher health literacy reported higher communication scores, reflecting more positive evaluations of the communication experience., Conclusion: TM is an acceptable mode of return of results delivery across diverse settings and populations. Research optimizing approaches for underrepresented populations, populations with lower levels of education and health literacy, and multilingual populations is necessary., Competing Interests: Conflict of Interest Laura Amendola is an employee and shareholder of Illumina, Inc. All other authors declare no conflicts of interest., (Copyright © 2024 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Next-generation sequencing-based genomic testing is standard of care for tumor workflows. However, its application across different institutions continues to be challenging given the diversity of needs and resource availability among different institutions globally. Moreover, the use of a variety of different panels, including those from a few individual genes to those involving hundreds of genes, results in a relatively skewed distribution of care for patients. It is imperative to obtain a higher level of standardization without having to be restricted to specific kits or requiring repeated validations, which are generally expensive. We show the validation and clinical implementation of the DH-CancerSeq assay, a tumor-only whole-exome-based sequencing assay with integrated informatics, while providing similar input requirements, sensitivity, and specificity to a previously validated targeted gene panel and maintaining similar turnaround times for patient care., Competing Interests: Disclosure Statement None declared., (Copyright © 2024 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Background: Comprehensive cancer genomic profiling tests have recently been used clinically to guide optimal treatment. Currently approved tests use DNA from tissue or plasma samples to analyze a few hundred genes. RNA panels complement DNA panels to detect fusion and exon skipping., Methods: Between April 2017 and March 2022, we analyzed non-small cell lung cancer samples using Todai OncoPanel, a matched tumor/normal pair panel targeting both DNA and RNA. Publicly available genomic data was downloaded from the Center for Cancer Genomics and Advanced Therapeutics database on 2022/11/3., Results: Sixty non-small cell lung cancer (NSCLC) samples were analyzed. With the DNA panel, 32 samples (53%) had TP53 loss-of-function mutations. Among adenocarcinoma, 17 (33%) had EGFR activating mutations, and 6 (12%) had ERBB2 activating mutations. One BRCA1 and one BRCA2 pathogenic germline variant were also detected. With the RNA panel, 11 fusion genes were detected, all in adenocarcinoma. Specifically, EML4-ALK and KIF5B-RET were detected from one sample each, and 9 others were all novel fusions with unknown pathogenicity. In addition, 4 of 60 (7%) NSCLC samples harbored MET exon 14 skipping. Analysis of the Center for Cancer Genomics and Advanced Therapeutics database found 37 MET exon 14 splice site mutations in 1514 NSCLC samples (2%, p = 0.039)., Conclusions: Analysis of NSCLC with Todai OncoPanel detected many druggable targets. Its RNA panel may detect MET exon 14 skipping with high sensitivity., Competing Interests: Declaration of competing interest Hidenori Kage Shinji Kohsaka, Kenji Tatsuno, Hiroyuki Aburatani, Hiroyuki Mano, and Katsutoshi Oda received research funds from Konica Minolta, Inc. Shinji Kohsaka, Kenji Tatsuno, Hiroyuki Aburatani, Hiroyuki Mano received patent royalties from Konica Minolta, Inc. Katsutoshi Oda received honoraria from Chugai Pharmaceutical Co. The other authors have no conflicts of interest., (Copyright © 2024 [The Author]. Published by Elsevier B.V. All rights reserved.)

A pervasive question in biological research studying gene regulation, chromatin structure, or genomics is where, and to what extent, does a signal of interest arise genome-wide? This question is addressed using a variety of methods relying on high-throughput sequencing data as their final output, including ChIP-seq for protein-DNA interactions, 1 GapR-seq for measuring supercoiling, 2 and HBD-seq or DRIP-seq for R-loop positioning. 3,4 Current computational methods to calculate genome-wide enrichment of the signal of interest usually do not properly handle the count-based nature of sequencing data, they often do not make use of the local correlation structure of sequencing data, and they do not apply any regularization of enrichment estimates. This can result in unrealistic estimates of the true underlying biological enrichment of interest, unrealistically low estimates of confidence in point estimates of enrichment (or no estimates of confidence at all), unrealistic gyrations in enrichment estimates at very close (<10 bp) genomic loci due to noise inherent in sequencing data, and in a multiple-hypothesis testing problem during interpretation of genome-wide enrichment estimates. We developed a tool called Enricherator to infer genome-wide enrichments from sequencing count data. Enricherator uses the variational Bayes algorithm to fit a generalized linear model to sequencing count data and to sample from the approximate posterior distribution of enrichment estimates (https://github.com/jwschroeder3/enricherator). Enrichments inferred by Enricherator more precisely identify known binding sites in cases where low coverage between binding sites leads to false-positive peak calls in these noisy regions of the genome; these benefits extend to published datasets., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: P.L. Freddolino is an Editorial Board Member/Editor-in-Chief/Associate Editor/Guest Editor for Scientific Reports and EcoSal Plus; neither organization was involved in the editorial review or the decision to publish this article. P.L. Freddolino is on the Scientific Advisory Board and is a Consultant for CircNova, Inc; CircNova provided no financial support for this work, and was not involved in any way in the performance of the research, manuscript preparation, editorial review, or decision to publish this article. J.W. Schroeder declares that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Purpose: We evaluated DECIDE, an online pretest decision-support tool for diagnostic genomic testing, in nongenetics specialty clinics where there are no genetic counselors (GCs)., Methods: Families of children offered genomic testing were eligible to participate. Fifty-six parents/guardians completed DECIDE at home, at their convenience. DECIDE includes an integrated knowledge quiz and decisional conflict screen. Six months later, parents were offered follow-up questionnaires and interviews about their experiences., Results: Forty parents (71%) had sufficient knowledge and no decisional conflict surrounding their testing decision, but 6 of this group had residual questions. These 6, plus 16 with decisional conflict or insufficient knowledge, saw a GC. At follow-up, little-to-no decisional regret and few negative emotions were identified in any parents. Most chose testing and described their decision as easy, yet stressful, and described many motivations for sequencing. Parents appreciated the simple comprehensive information DECIDE provided and the ability to view it in a low-stress environment., Conclusion: DECIDE provides adequate decision-support to enable most parents to make value-consistent choices about genetic testing for their child. Parents reported that DECIDE helped to clarify motivations for pursuing (or declining) testing. DECIDE is a timely, well-tested, and accessible tool in clinical settings without GCs., Competing Interests: Conflict of Interest The authors declare no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Suicide is the second leading cause of death in U.S. adolescents and young adults and is generally associated with a psychiatric disorder. Suicidal behavior has a complex etiology and pathogenesis. Moderate heritability suggests genetic causes. Associations between childhood and recent life adversity indicate contributions from epigenetic factors. Genomic contributions to suicide pathogenesis remain largely unknown. This article is based on a workshop held to design strategies to identify molecular drivers of suicide neurobiology that would be putative new treatment targets. The panel determined that while bulk tissue studies provide comprehensive information, single-nucleus approaches that identify cell type-specific changes are needed. While single-nuclei techniques lack information on cytoplasm, processes, spines, and synapses, spatial multiomic technologies on intact tissue detect cell alterations specific to brain tissue layers and subregions. Because suicide has genetic and environmental drivers, multiomic approaches that combine cell type-specific epigenome, transcriptome, and proteome provide a more complete picture of pathogenesis. To determine the direction of effect of suicide risk gene variants on RNA and protein expression and how these interact with epigenetic marks, single-nuclei and spatial multiomics quantitative trait loci maps should be integrated with whole-genome sequencing and genome-wide association databases. The workshop concluded with a recommendation for the formation of an international suicide biology consortium that will bring together brain banks and investigators with expertise in cutting-edge omics technologies to delineate the biology of suicide and identify novel potential treatment targets to be tested in cellular and animal models for drug and biomarker discovery to guide suicide prevention., (Copyright © 2024 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Trisomy, a form of aneuploidy wherein the cell possesses an additional copy of a specific chromosome, exhibits a high correlation with cancer. Studies from across different hosts, cell-lines, and labs into the cellular effects induced by aneuploidy have conflicted, ranging from small, chaotic global changes to large instances of either overexpression or underexpression throughout the trisomic chromosome. We ascertained that conflicting findings may be correct but miss the overarching ground truth due to injudicious use of thresholds. To correct this deficiency, we introduce the Meta-analytic Operation of Threshold-independent Filtering (MOTiF) method, which begins by providing a panoramic view of all thresholds, transforms the data to eliminate the effects accounted for by known mechanisms, and then reconstructs an explanation of the mechanisms that underly the difference between the baseline and the uncharacterized effects observed. As a proof of concept, we applied MOTiF to human colonic epithelial cells, discovering a uniform decrease in gene expression levels throughout the genome, which while significant, is beneath most common thresholds. Using Hi-C data we identified the structural correlate, wherein the physical genomic architecture condenses, compactifying in a uniform, genome-wide manner. This effect, which we dub the Jörmungandr Effect, is likely a robustness mechanism counteracting the addition of a chromosome. We were able to break down the gene expression alterations into three overlapping mechanisms: the raw chromosome content, the genomic compartmentalization, and the global structural condensation. While further studies must be conducted to corroborate the hypothesized Jörmungandr Effect, MOTiF presents a useful meta-analytic tool in the realm of gene expression and beyond., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Genomic data is growing exponentially, posing new challenges for sequence analysis and classification, particularly for managing and understanding harmful new viruses that may later cause pandemics. Recent genome sequence classification models yield promising performance. However, the majority of them do not consider the sequential arrangement of nucleotides and amino acids, a critical aspect for uncovering their inherent structure and function. To overcome this, we introduce GenoAnaCla, a novel approach for analyzing and classifying genome sequences, based on sequential pattern mining (SPM). The proposed approach first constructs and preprocesses datasets comprising RNA virus genome sequences in three formats: nucleotide, coding region, and protein. Then, to capture sequential features for the analysis and classification of viruses, GenoAnaCla extracts frequent sequential patterns and rules in three forms and in codons. Eight classifiers are utilized, and their effectiveness is assessed by employing a variety of evaluation metrics. A performance comparison demonstrates that the suggested approach surpasses the current state-of-the-art genome sequence classification and detection techniques with a 3.18% performance increase in accuracy on average., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The Androgen receptor (AR) is known to manifest the biological actions of male sex hormones. Androgens are now known to exert a multitude of responses, sometimes contrasting, in physiological and pathological conditions. Several groups have attempted to explain the underlying mechanisms of these varying androgen responses, including the non-genomic actions of androgens. These actions lead to increased activity of pro-proliferative signal transduction pathways, resulting in rapid molecular effects that cannot be explained by the conventional model in which AR functions as a transcription factor to modulate target gene expression [1,2]. This spotlight article examines Safi et al.'s research on the androgen receptor (AR) in prostate cancer, revealing that low androgen levels drive proliferation via non-genomic mechanisms involving AR monomers, while high levels suppress growth through genomic actions with AR dimers. These findings challenge current paradigms and suggest novel therapeutic strategies targeting both AR forms, particularly focusing on the role of AR monomers in cancer progression and treatment resistance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Structural variants (SVs) account for the majority of base pair differences both within and between primate species. However, our understanding of inter- and intra-species SV has been historically hampered by the quality of draft primate genomes and the absence of genome resources for key taxa. Recently, advances in long-read sequencing and genome assembly have begun to radically reshape our understanding of SVs. Two landmark achievements include the publication of a human telomere-to-telomere (T2T) genome as well as the development of the first human pangenome reference. In this review, we first look back to the major works laying the foundation for these projects. We then examine the ways in which T2T genome assemblies and pangenomes are transforming our understanding of and approach to primate SV. Finally, we discuss what the future of primate SV research may look like in the era of T2T genomes and pangenomics., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Adolescents and young adults (AYAs) represent a small proportion of patients with cancer. The genomic profiles of AYA patients with cancer are not well-studied, and outcomes of genome-matched therapies remain largely unknown., Patients and Methods: We investigated differences between Japanese AYA and older adult (OA) patients in genomic alterations, therapeutic evidence levels, and genome-matched therapy usage by cancer type. We also assessed treatment outcomes., Results: AYA patients accounted for 8.3% of 876 cases. Microsatellite instability-high and/or tumor mutation burden was less common in AYA patients (1.4% versus 7.7% in OA; P = 0.05). However, BRCA1 alterations were more common in AYA patients with breast cancer (27.3% versus 1.7% in OA; P = 0.01), as were MYC alterations in AYA patients with colorectal cancer (23.5% versus 5.8% in OA; P = 0.02) and sarcoma (31.3% versus 3.4% in OA; P = 0.01). Genome-matched therapy use was similar between groups, with overall survival tending to improve in both. However, in AYA patients, the small number of patients prevented statistical significance. Comprehensive genomic profiling-guided genome-matched therapy yielded encouraging results, with progression-free survival of 9.0 months in AYA versus 3.7 months in OA patients (P = 0.59)., Conclusion: Our study suggests that tailored therapeutic approaches can benefit cancer patients regardless of age., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)