A Comprehensive Guide to Quality Assessment and Data Submission for Genomic Surveillance of Enteric Pathogens.

This document outlines the steps necessary to assemble and submit the standard data package required for contributing to the global genomic surveillance of enteric pathogens. Although targeted to GenomeTrakr laboratories and collaborators, these protocols are broadly applicable for enteric pathogens collected for different purposes. There are five protocols included in this chapter: (1) quality control (QC) assessment for the genome sequence data, (2) validation for the contextual data, (3) data submission for the standard pathogen package or Pathogen Data Object Model (DOM) to the public repository, (4) viewing and querying data at NCBI, and (5) data curation for maintaining relevance of public data. The data are available through one of the International Nucleotide Sequence Database Consortium (INSDC) members, with the National Center for Biotechnology Information (NCBI) being the primary focus of this document. NCBI Pathogen Detection is a custom dashboard at NCBI that provides easy access to pathogen data plus results for a standard suite of automated cluster and genotyping analyses important for informing public health and regulatory decision-making.

Updated techniques and evidence for endoscopic ultrasound-guided tissue acquisition from solid pancreatic lesions.

Endoscopic ultrasound-guided tissue acquisition (EUS-TA), including fine-needle aspiration (EUS-FNA) and fine-needle biopsy (EUS-FNB), has revolutionized specimen collection from intra-abdominal organs, especially the pancreas. Advances in personalized medicine and more precise treatment have increased demands to collect specimens with higher cell counts, while preserving tissue structure, leading to the development of EUS-FNB needles. EUS-FNB has generally replaced EUS-FNA as the procedure of choice for EUS-TA of pancreatic cancer. Various techniques have been tested for their ability to enhance the diagnostic performance of EUS-TA, including multiple methods of sampling at the time of puncture, on-site specimen evaluation, and specimen processing. In addition, advances in next-generation sequencing have made comprehensive genomic profiling of EUS-TA samples feasible in routine clinical practice. The present review describes updates in EUS-TA sampling techniques of pancreatic lesions, as well as methods for their evaluation.

Image Analysis Protocol for DNA/RNA/Immunofluorescence (IF)-seqFISH Data.

Imaging-based spatial multi-omics technologies facilitate the analysis of higher-order genomic structures, gene transcription, and the localization of proteins and posttranslational modifications (PTMs) at the single-allele level, thereby enabling detailed observations of biological phenomena, including transcription machinery within cells and tissues. This chapter details the principles of such technologies, with a focus on DNA/RNA/immunofluorescence (IF) sequential fluorescence in situ hybridization (seqFISH). A comprehensive step-by-step protocol for image analysis is provided, covering image preprocessing, spot detection, and data visualization. For practical application, complete Jupyter Notebook codes are made available on GitHub ( https://github.com/Ochiai-Lab/seqFISH_analysis ).

Using GWAS and Machine Learning to Identify and Predict Genetic Variants Associated with Foodborne Bacteria Phenotypic Traits.

One of the main challenges in food microbiology is to prevent the risk of outbreaks by avoiding the distribution of food contaminated by bacteria. This requires constant monitoring of the circulating strains throughout the food production chain. Bacterial genomes contain signatures of natural evolution and adaptive markers that can be exploited to better understand the behavior of pathogen in the food industry. The monitoring of foodborne strains can therefore be facilitated by the use of these genomic markers capable of rapidly providing essential information on isolated strains, such as the source of contamination, risk of illness, potential for biofilm formation, and tolerance or resistance to biocides. The increasing availability of large genome datasets is enhancing the understanding of the genetic basis of complex traits such as host adaptation, virulence, and persistence. Genome-wide association studies have shown very promising results in the discovery of genomic markers that can be integrated into rapid detection tools. In addition, machine learning has successfully predicted phenotypes and classified important traits. Genome-wide association and machine learning tools have therefore the potential to support decision-making circuits intending at reducing the burden of foodborne diseases. The aim of this chapter review is to provide knowledge on the use of these two methods in food microbiology and to recommend their use in the field.

Barley's gluten challenge: A path to hordein-free food and malt.

Barley, a vital cereal crop worldwide, is hindered by hordeins, gluten proteins triggering adverse reactions in those with celiac disease (CeD) and non-celiac gluten sensitivity (NCGS). Recent barley breeding advancements focus on creating varieties with reduced hordein content. Researchers have developed ultra-low gluten barley mutants via targeted genetic modifications, showing significantly decreased hordein levels, potentially safe for CeD and NCGS individuals. However, some mutants carry undesirable traits, which are addressed through further breeding and new genomic techniques. These innovative methods offer promising ways to eliminate unwanted traits and transfer the ultra-low gluten characteristic to diverse barley cultivars, expanding dietary choices and potentially transforming the food and beverage industry with gluten-free barley-based products. This review addresses hordeins' impact and ultra-low gluten barley development and proposes using new genomic techniques for safe barley lines.

Mobilome impacts on physiology in the widely used non-toxic mutant Microcystis aeruginosa PCC 7806 ΔmcyB and toxic wildtype.

The Microcystis mobilome is a well-known but understudied component of this bloom-forming cyanobacterium. Through genomic and transcriptomic comparisons, we found five families of transposases that altered the expression of genes in the well-studied toxigenic type-strain, Microcystis aeruginosa PCC 7086, and a non-toxigenic genetic mutant, Microcystis aeruginosa PCC 7806 ΔmcyB. Since its creation in 1997, the ΔmcyB strain has been used in comparative physiology studies against the wildtype strain by research labs throughout the world. Some differences in gene expression between what were thought to be otherwise genetically identical strains have appeared due to insertion events in both intra- and intergenic regions. In our ΔmcyB isolate, a sulfate transporter gene cluster (sbp-cysTWA) showed differential expression from the wildtype, which may have been caused by the insertion of a miniature inverted repeat transposable element (MITE) in the sulfate-binding protein gene (sbp). Differences in growth in sulfate-limited media also were also observed between the two isolates. This paper highlights how Microcystis strains continue to "evolve" in lab conditions and illustrates the importance of insertion sequences / transposable elements in shaping genomic and physiological differences between Microcystis strains thought otherwise identical. This study forces the necessity of knowing the complete genetic background of isolates in comparative physiological experiments, to facilitate the correct conclusions (and caveats) from experiments.

Genetic Profiling of Non-Small Cell Lung Cancer in Moroccan Patients by Targeted Next-Generation Sequencing.

OBJECTIVES: We retrospectively analyzed the next-generation sequencing (NGS) results from diagnosed NSCLC patients to identify and compare genomic alterations of NSCLC between Moroccan patients and the Cancer Genome Atlas (TCGA). We also aimed to investigate the distribution and frequency of concurrent genomic alterations. METHODS: From December 2022 to December 2023, a retrospective study of 76 formalin-fixed paraffin-embedded (FFPE) samples have been profiled using the Oncomine™ Precision Assay on the Ion Torrent™ Genexus™ Integrated Sequencer across the panel of 50 key genes that are applicable for the selection of targeted therapy. RESULTS: Seventy of the 76 FFPE sequenced samples carried at least one genetic alteration in the tested genes. The study identified 234 genetic alterations in 18 genes. Targetable genetic alterations in EGFR, KRAS, MET, BRAF, ALK, RET and ROS1 were identified in 84.3% of tumors. EGFR and KRAS mutations were frequently reported, occurring in 24.3% and 22.9% of cases, respectively. The untargetable genetic alterations were found in 74.3% of the specimens in FGFR3, TP53, ERBB2, PIK3CA, CDKN2A, PDL1, FGFR1, PTEN, CHEK2 and ERBB3. There were additional uncommon/rare mutations in EGFR, BRAF, RET and ROS1. Comparing the prevalence of selected mutated genes in the NSCLC patients from the TCGA database identified substantial differences in EGFR (24.3%, vs14.97%), KRAS (22.9%, vs 25.99%), and TP53 (34.3%, vs 50.94%). ALK, ROS1, and RET gene rearrangements were detected in 4.3% of the 70 tumors tested. The ALK/RET/MET/ROS1/EML4 fusions were detected in 11.4% of samples. Co-alterations occurred in 67.1% of specimens. Co-occurring driver gene mutations were observed in 44.3%. TP53 mutations co-occurred driver gene mutations in 30% of tumors. Three cases (4.3%) harbored concurrent FGFR3, TP53, and PIK3CA alterations. CONCLUSION: Our results regarding the proportion of samples with actionable mutations demonstrate the value of NGS testing for NSCLC patients in a real-world clinical diagnostic setting.

Driver gene alterations in NSCLC patients in southern China and their correlation with clinicopathologic characteristics.

Introduction: In this study, we aimed to explore the relationship between clinicopathological features and driver gene changes in Chinese NSCLC patients. Methods: Amplification refractory mutation system PCR was used to detect the aberrations of 10 driver oncogenes in 851 Chinese NSCLC patients, and their correlation with clinicopathological characteristics was also analyzed. Moreover, three models of logistic regression were used to analyze the association between histopathology and EGFR or KRAS mutations. Results: The top two most frequently aberrant target oncogenes were EGFR (48.06%) and KRAS (9.51%). These were followed by ALK (5.41%), HER2 (2.35%), MET (2.23%), RET (2.11%), ROS1 (1.88%), BRAF (0.47%), NRAS (0.24%), and PIK3CA (0.12%). Additionally, 11 (1.29%) patients had synchronous gene alterations in two genes. The main EGFR mutations were exon 21 L858R and exon 19-Del, which accounted for 45.97% and 42.79% of all EGFR mutations, respectively. Logistic regression analysis showed that the frequency of EGFR mutations was positively correlated with women, non-smokers, lung adenocarcinoma, and invasive non-mucinous adenocarcinoma (IA), and negatively correlated with solid nodule, micro-invasive adenocarcinoma, and solid-predominant adenocarcinoma. KRAS mutations were positively associated with men and longer tumor long diameters and negatively correlated with lung adenocarcinoma (P < 0.05 for all). Conclusion: Our findings suggest that the EGFR mutation frequency was higher in women, non-smokers, lung adenocarcinoma, and the IA subtype in lung adenocarcinoma patients, while the KRAS mutation rate was higher in men and patients with longer tumor long diameter and lower in lung adenocarcinoma patients.

Genetic improvement and genomic resources of important cyprinid species: status and future perspectives for sustainable production.

Cyprinid species are the most cultured aquatic species around the world in terms of quantity and total value. They account for 25% of global aquaculture production and significantly contribute to fulfilling the demand for fish food. The aquaculture of these species is facing severe concerns in terms of seed quality, rising feed costs, disease outbreaks, introgression of exotic species, environmental impacts, and anthropogenic activities. Numerous researchers have explored biological issues and potential methods to enhance cyprinid aquaculture. Selective breeding is extensively employed in cyprinid species to enhance specific traits like growth and disease resistance. In this context, we have discussed the efforts made to improve important cyprinid aquaculture practices through genetic and genomic approaches. The recent advances in DNA sequencing technologies and genomic tools have revolutionized the understanding of biological research. The generation of a complete genome and other genomic resources in cyprinid species has significantly strengthened molecular-level investigations into disease resistance, growth, reproduction, and adaptation to changing environments. We conducted a comprehensive review of genomic research in important cyprinid species, encompassing genome, transcriptome, proteome, metagenome, epigenome, etc. This review reveals that considerable data has been generated for cyprinid species. However, the seamless integration of this valuable data into genetic selection programs has yet to be achieved. In the upcoming years, genomic techniques, gene transfer, genome editing tools are expected to bring a paradigm shift in sustainable cyprinid aquaculture production. The comprehensive information presented here will offer insights for the cyprinid aquaculture research community.

Transcriptome-based prediction for polygenic traits in rice using different gene subsets.

BACKGROUND: Transcriptome-based prediction of complex phenotypes is a relatively new statistical method that links genetic variation to phenotypic variation. The selection of large-effect genes based on a priori biological knowledge is beneficial for predicting oligogenic traits; however, such a simple gene selection method is not applicable to polygenic traits because causal genes or large-effect loci are often unknown. Here, we used several gene-level features and tested whether it was possible to select a gene subset that resulted in better predictive ability than using all genes for predicting a polygenic trait. RESULTS: Using the phenotypic values of shoot and root traits and transcript abundances in leaves and roots of 57 rice accessions, we evaluated the predictive abilities of the transcriptome-based prediction models. Leaf transcripts predicted shoot phenotypes, such as plant height, more accurately than root transcripts, whereas root transcripts predicted root phenotypes, such as crown root length, more accurately than leaf transcripts. Furthermore, we used the following three features to train the prediction model: (1) tissue specificity of the transcripts, (2) ontology annotations, and (3) co-expression modules for selecting gene subsets. Although models trained by a gene subset often resulted in lower predictive abilities than the model trained by all genes, some gene subsets showed improved predictive ability. For example, using genes expressed in roots but not in leaves, the predictive ability for crown root diameter was improved by more than 10% (R2 = 0.59 when using all genes; R2 = 0.66, using 1,554 root-specifically expressed genes). Similarly, genes annotated as "gibberellic acid sensitivity" showed higher predictive ability than using all genes for root dry weight. CONCLUSIONS: Our results highlight both the possibility and difficulty of selecting an appropriate gene subset to predict polygenic traits from transcript abundance, given the current biological knowledge and information. Further integration of multiple sources of information, as well as improvements in gene characterization, may enable the selection of an optimal gene set for the prediction of polygenic phenotypes.

Transcriptomic analyses in the gametophytes of the apomictic fern Dryopteris affinis.

MAIN CONCLUSION: A novel genomic map of the apogamous gametophyte of the fern Dryopteris affinis unlocks oldest hindrance with this complex plant group, to gain insight into evo-devo approaches. The gametophyte of the fern Dryopteris affinis ssp. affinis represents a good model to explore the molecular basis of vegetative and reproductive development, as well as stress responses. Specifically, this fern reproduces asexually by apogamy, a peculiar case of apomixis whereby a sporophyte forms directly from a gametophytic cell without fertilization. Using RNA-sequencing approach, we have previously annotated more than 6000 transcripts. Here, we selected 100 of the inferred proteins homolog to those of Arabidopsis thaliana, which were particularly interesting for a detailed study of their potential functions, protein-protein interactions, and distance trees. As expected, a plethora of proteins associated with gametogenesis and embryogenesis in angiosperms, such as FERONIA (FER) and CHROMATING REMODELING 11 (CHR11) were identified, and more than a dozen candidates potentially involved in apomixis, such as ARGONAUTE family (AGO4, AGO9, and AGO 10), BABY BOOM (BBM), FASCIATED STEM4 (FAS4), FERTILIZATION-INDEPENDENT ENDOSPERM (FIE), and MATERNAL EFFECT EMBRYO ARREST29 (MEE29). In addition, proteins involved in the response to biotic and abiotic stresses were widely represented, as shown by the enrichment of heat-shock proteins. Using the String platform, the interactome revealed that most of the protein-protein interactions were predicted based on experimental, database, and text mining datasets, with MULTICOPY SUPPRESSOR OF IRA4 (MSI4) showing the highest number of interactions: 16. Lastly, some proteins were studied through distance trees by comparing alignments with respect to more distantly or closely related plant groups. This analysis identified DCL4 as the most distant protein to the predicted common ancestor. New genomic information in relation to gametophyte development, including apomictic reproduction, could expand our current vision of evo-devo approaches.

Genomic signature for oligometastatic disease in non-small cell lung cancer patients with brain metastases.

Purpose/objectives: Biomarkers for extracranial oligometastatic disease remain elusive and few studies have attempted to correlate genomic data to the presence of true oligometastatic disease. Methods: Patients with non-small cell lung cancer (NSCLC) and brain metastases were identified in our departmental database. Electronic medical records were used to identify patients for whom liquid biopsy-based comprehensive genomic profiling (Guardant Health) was available. Extracranial oligometastatic disease was defined as patients having ≤5 non-brain metastases without diffuse involvement of a single organ. Widespread disease was any spread beyond oligometastatic. Fisher's exact tests were used to screen for mutations statistically associated (p<0.1) with either oligometastatic or widespread extracranial disease. A risk score for the likelihood of oligometastatic disease was generated and correlated to the likelihood of having oligometastatic disease vs widespread disease. For oligometastatic patients, a competing risk analysis was done to assess for cumulative incidence of oligometastatic progression. Cox regression was used to determine association between oligometastatic risk score and oligoprogression. Results: 130 patients met study criteria and were included in the analysis. 51 patients (39%) had extracranial oligometastatic disease. Genetic mutations included in the Guardant panel that were associated (p<0.1) with the presence of oligometastatic disease included ATM, JAK2, MAP2K2, and NTRK1, while ARID1A and CCNE1 were associated with widespread disease. Patients with a positive, neutral and negative risk score for oligometastatic disease had a 78%, 41% and 11.5% likelihood of having oligometastatic disease, respectively (p<0.0001). Overall survival for patients with positive, neutral and negative risk scores for oligometastatic disease was 86% vs 82% vs 64% at 6 months (p=0.2). Oligometastatic risk score was significantly associated with the likelihood of oligoprogression based on the Wald chi-square test. Patients with positive, neutral and negative risk scores for oligometastatic disease had a cumulative incidence of oligometastatic progression of 77% vs 35% vs 33% at 6 months (p=0.03). Conclusions: Elucidation of a genomic signature for extracranial oligometastatic disease derived from non-invasive liquid biopsy appears feasible for NSCLC patients. Patients with this signature exhibited higher rates of early oligoprogression. External validation could lead to a biomarker that has the potential to direct local therapies in oligometastatic patients.

Diversification of Antibodies: From V(D)J Recombination to Somatic Exon Shuffling.

Antibodies that gain specificity by a large insert encoding for an extra domain were described for the first time in 2016. In malaria-exposed individuals, an exon deriving from the leukocyte-associated immunoglobulin-like 1 (LAIR1) gene integrated via a copy-and-paste insertion into the immunoglobulin heavy chain encoding region. A few years later, a second example was identified, namely a dual exon integration from the leukocyte immunoglobulin-like receptor B1 (LILRB1) gene that is located in close proximity to LAIR1. A dedicated high-throughput characterization of chimeric immunoglobulin heavy chain transcripts unraveled, that insertions from distant genomic regions (including mitochondrial DNA) can contribute to human antibody diversity. This review describes the modalities of insert-containing antibodies. The role of known DNA mobility aspects, such as genomic translocation, gene conversion, and DNA fragility, is discussed in the context of insert-antibody generation. Finally, the review covers why insert antibodies were omitted from the past repertoire analyses and how insert antibodies can contribute to protective immunity or an autoreactive response.

Genomic and clinical landscape of metastatic hormone receptors-positive breast cancers carrying ESR1 alterations.

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 (ESR1MUT) and ESR1 wild type (ESR1WT) 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 ESR1MUT among 131 tumors were found (19.2%). The frequency of ESR1MUT 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 ESR1WT mBC, ESR1MUT 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 ESR1WT tumors (36% versus 14%) [odds ratio (OR) 3.17, 95% confidence interval (CI) 1.88-5.64, q = 0.001]. Considering signaling pathways, ESR1MUT 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 ESR1MUT. CONCLUSIONS: ER+/HER2- mBCs carrying ESR1MUT 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.

Pedigree reconstruction based on genotype data in chickens.

A reliable pedigree serves as the backbone of genetic evolution in domesticated animals, providing guidance for daily management and breeding strategies. However, in commercial chicken breeding, pedigree errors and omissions are common. The large-scale application of genomic selection provides an opportunity to reconstruct chicken pedigrees using SNP markers. Here, to reconstruct pedigrees in chickens, we detected high-quality SNPs from 2866 parent-offspring pairs and calculated their genomic relationship and identity by descent (IBD). The results showed that the IBD values for parent-offspring pairs ranged from 0.48 to 0.58, clearly distinguishing them from nonparent-offspring pairs and demonstrating robustness in parentage assignment. In contrast, the genomic relatedness coefficients varied from 0.32 to 0.65. The accuracy of pedigree reconstruction significantly improved as the SNP number and minor allele frequency (MAF) increased. When the number of SNPs exceeded 200, better inference power was exhibited with IBD than with genomic relatedness. Upon reaching an effective SNP quantity of 350, despite a MAF of 0.01, the accuracy of the pedigrees inferred reached a remarkable level of 99%. Furthermore, with a doubled SNP quantity of 700 and a MAF of 0.05, the accuracy increased to a perfect 100%. This study demonstrated the feasibility of accurately constructing pedigrees in chickens using low-density SNP markers and emphasized the importance of considering the number and MAFs of these markers to achieve optimal outcomes. The adoption of the IBD as a suitable metric for pedigree inference is promising for improving the efficiency and accuracy of genetic breeding programs. These findings are paramount for the development of cost-effective yet accurate parentage verification systems.

Oxford Nanopore's 2024 sequencing technology for Listeria monocytogenes outbreak detection and source attribution: progress and clone-specific challenges.

Whole genome sequencing is an essential cornerstone of pathogen surveillance and outbreak detection. Established sequencing technologies are currently being challenged by Oxford Nanopore Technologies (ONT), which offers an accessible and cost-effective alternative enabling gap-free assemblies of chromosomes and plasmids. Limited accuracy has hindered its use for investigating pathogen transmission, but recent technology updates have brought significant improvements. To evaluate its readiness for outbreak detection, we selected 78 Listeria monocytogenes isolates from diverse lineages or known epidemiological clusters for sequencing with ONT's V14 Rapid Barcoding Kit and R10.4.1 flow cells. The most accurate of several tested workflows generated assemblies with a median of one error (SNP or indel) per assembly. For 66 isolates, the cgMLST profiles from ONT-only assemblies were identical to those generated from Illumina data. Eight assemblies were of lower quality, with more than 20 erroneous sites each, primarily caused by methylations at the GAAGAC motif (5'-GAAG6mAC-3'/5'-GT4mCTTC-3'). This led to inaccurate clustering, failing to group isolates from a persistence-associated clone that carried the responsible restriction-modification system. Out of 50 methylation motifs detected among the 78 isolates, only the GAAGAC motif was linked to substantially increased error rates. Our study shows that most L. monocytogenes genomes assembled from ONT-only data are suitable for high-resolution genotyping, but further improvements of chemistries or basecallers are required for reliable routine use in outbreak and food safety investigations.

Integrating targeted genetic markers to genotyping-by-sequencing for an ultimate genotyping tool.

New selection methods, using trait-specific markers (marker-assisted selection (MAS)) and/or genome-wide markers (genomic selection (GS)), are becoming increasingly widespread in breeding programs. This new era requires innovative and cost-efficient solutions for genotyping. Reduction in sequencing cost has enhanced the use of high-throughput low-cost genotyping methods such as genotyping-by-sequencing (GBS) for genome-wide single-nucleotide polymorphism (SNP) profiling in large breeding populations. However, the major weakness of GBS methodologies is their inability to genotype targeted markers. Conversely, targeted methods, such as amplicon sequencing (AmpSeq), often face cost constraints, hindering genome-wide genotyping across a large cohort. Although GBS and AmpSeq data can be generated from the same sample, an efficient method to achieve this is lacking. In this study, we present the Genome-wide & Targeted Amplicon (GTA) genotyping platform, an innovative way to integrate multiplex targeted amplicons into the GBS library preparation to provide an all-in-one cost-effective genotyping solution to breeders and research communities. Custom primers were designed to target 23 and 36 high-value markers associated with key agronomical traits in soybean and barley, respectively. The resulting multiplex amplicons were compatible with the GBS library preparation enabling both GBS and targeted genotyping data to be produced efficiently and cost-effectively. To facilitate data analysis, we have introduced Fast-GBS.v3, a user-friendly bioinformatic pipeline that generates comprehensive outputs from data obtained following sequencing of GTA libraries. This high-throughput low-cost approach will greatly facilitate the application of DNA markers as it provides required markers for both MAS and GS in a single assay.

Advancing prognostic understanding in hepatocellular carcinoma through the integration of genomic instability and lncRNA signatures: GILncSig model.

The recently published study by Duan et al introduces a promising method that combines genomic instability and long non-coding RNAs to improve the prognostic evaluation of hepatocellular carcinoma (HCC), a deadly cancer associated with considerable morbidity and mortality. This editorial aims to analyze the methodology, key findings, and broader implications of the study within the fields of gastroenterology and oncological surgery, highlighting the shift towards precision medicine in the management of HCC.

Leveraging non-coding regions to guarantee the accuracy of small-sized panel-based tumor mutational burden estimates.

Accurate estimation of tumor mutational burden (TMB) as a predictor of responsiveness to immune checkpoint inhibitors in gene panel assays requires an adequate panel size. The current calculations of TMB only consider coding regions, while most of gene panel assays interrogate non-coding regions. Leveraging the non-coding regions is a potential solution to address this panel size limitation. However, the impact of including non-coding regions on the accuracy of TMB estimates remains unclear. This study investigated the validity of leveraging non-coding regions to supplement panel size using the OncoGuide NCC Oncopanel System (NOP). The aim of this study was to evaluate test performance against orthogonal assays and the association with responsiveness to immune checkpoint inhibitors was not included in the evaluation. We compared TMB status and values between TMB calculated only from coding regions (NOP-coding) and from both coding and non-coding regions (NOP-overall) using whole exome sequencing (WES) and FoundationOne®CDx (F1CDx) assay. Our findings revealed that NOP-overall significantly improved the overall percent agreement (OPA) with TMB status compared with NOP-coding for both WES (OPA: 96.7% vs. 73.3%, n = 30) and F1CDx (OPA: 90.0% vs. 73.3%). Additionally, the mean difference in TMB values compared with WES was lower for NOP-overall (3.55 [95% CI: 0.98-6.13]) than for NOP-coding (6.22 [95% CI: 3.73-8.70]). These results exemplify the utility of incorporating non-coding regions to maintain accurate TMB estimates in small-sized panels.