Sequencing technologies — the next generation

A novel framework for human leukocyte antigen (HLA) genotyping using probe capture-based targeted next-generation sequencing and computational analysis

Human leukocyte antigen (HLA) genes play pivotal roles in numerous immunological applications. Given the immense number of polymorphisms, achieving accurate high-throughput HLA typing remains challenging. This study aimed to harness the human pan-genome reference consortium (HPRC) resources as a potential benchmark for HLA reference materials. We meticulously annotated specific four field-resolution alleles for 11 HLA genes (HLA-A, -B, -C, -DPA1, -DPB1, -DQA1, -DQB1, -DRB1, -DRB3, -DRB4 and -DRB5) from 44 high-quality HPRC personal genome assemblies. For sequencing, we crafted HLA-specific probes and conducted capture-based targeted sequencing of the genomic DNA of the HPRC cohort, ensuring focused and comprehensive coverage of the HLA region of interest. We used publicly available short-read whole-genome sequencing (WGS) data from identical samples to offer a comparative perspective. To decipher the vast amount of sequencing data, we employed seven distinct software tools: OptiType, HLA-VBseq, HISAT genotype, SpecHLA, T1K, QzType, and DRAGEN. Each tool offers unique capabilities and algorithms for HLA genotyping, allowing comprehensive analysis and validation of the results. We then compared these results with benchmarks derived from personal genome assemblies. Our findings present a comprehensive four-field-resolution HLA allele annotation for 44 HPRC samples. Significantly, our innovative targeted next-generation sequencing (NGS) approach for HLA genes showed superior accuracy compared with conventional short-read WGS. An integrated analysis involving QzType, T1K, and DRAGEN was developed, achieving 100% accuracy for all 11 HLA genes. In conclusion, our study highlighted the combination of targeted short-read sequencing and astute computational analysis as a robust approach for HLA genotyping. Furthermore, the HPRC cohort has emerged as a valuable assembly-based reference in this realm.

Screening of reference genes for gene expression study in different tissues from the transcriptome data of the vector leafhopper Psammotettix striatus

Selecting appropriate reference genes is crucial for ensuring the accuracy and reliability of gene expression study using reverse transcription-quantitative PCR (RT-qPCR). To screen the optimal reference genes for analyzing gene expression in different tissues of the vector leafhopper Psammotettix striatus which causes extensive damage to a wide range of crops by vectoring multiple plant pathogenic microorganisms, the transcriptome data from Malpighian tubules (MTs) of P. striatus were mined. Twenty alternative candidate reference genes were initially selected for screening, among which seven genes with diverse Gene Ontology (GO) annotations were choosed as candidate reference genes, i.e., ribosomal protein L7A (RPL7A), ribosomal protein S28 (RPS28), ribosomal protein L22 (RPL22), ribosomal protein LP2 (RPLP2), H3 histone family 3A (H3F3A), elongation factor 1γ (EF-1γ), and elongation factor 1α (EF-1α). Gene expression levels in different tissues of P. striatus adults were examined using RT-qPCR, and their expression stability was analyzed using multiple reference gene screening software. This study revealed EF-1α as the most abundantly expressed gene, while RPL22 exhibited the lowest expression levels. EF-1α showed the most stable expression, whereas RPS28 showed the least stability. Various software tools confirmed EF-1α as the most stable single reference gene, and EF-1α and RPLP2 an optimal combination. This study provides a foundation for future investigation of the transmission of pathogenic microorganisms mediated by the vector leafhoppers, the function of the MTs, the biosynthesis of brochosomes, the coevolutionary processes and nutritional interactions of symbionts and host insects, and the gene expression study of other sap-sucking insects.

Highly accurate single-color fluorogenic DNA decoding sequencing for mutational genotyping

We proposed a single-color fluorogenic DNA decoding sequencing method designed to improve sequencing accuracy, increase read length and throughput, as well as decrease scanning time. This method involves the incorporation of a mixture of four types of 3'-O-modified nucleotide reversible terminators into each reaction. Among them, two nucleotides are labeled with the same fluorophore, while the remaining two are unlabeled. Only one nucleotide can be extended in each reaction, and an encoding that partially defines base composition can be obtained. Through cyclic interrogation of a template twice with different nucleotide combinations, two sets of encodings are sequentially obtained, enabling the determination of the sequence. We demonstrate the feasibility of this method using established sequencing chemistry, achieving a cycle efficiency of approximately 99.5 %. Notably, this strategy exhibits remarkable efficacy in the detection and correction of sequencing errors, achieving a theoretical error rate of 0.00016 % at a sequencing depth of ×2, which is lower than Sanger sequencing. This method is theoretically compatible with the existing sequencing-by-synthesis (SBS) platforms, and the instrument is simpler, which may facilitate further reductions in sequencing costs, thereby broadening its applications in biology and medicine. Moreover, we demonstrate the capability to detect known mutation sites using information from only a single sequencing run. We validate this approach by accurately identifying a mutation site in the human mitochondrial DNA.

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.

Next-Generation Sequencing and Emerging Technologies

Genetic sequencing technologies are evolving at a rapid pace with major implications for research and clinical practice. In this review, the authors provide an updated overview of next-generation sequencing (NGS) and emerging methodologies. NGS has tremendously improved sequencing output while being more time and cost-efficient in comparison to Sanger sequencing. The authors describe short-read sequencing approaches, such as sequencing by synthesis, ion semiconductor sequencing, and nanoball sequencing. Third-generation long-read sequencing now promises to overcome many of the limitations of short-read sequencing, such as the ability to reliably resolve repeat sequences and large genomic rearrangements. By combining complementary methods with massively parallel DNA sequencing, a greater insight into the biological context of disease mechanisms is now possible. Emerging methodologies, such as advances in nanopore technology, in situ nucleic acid sequencing, and microscopy-based sequencing, will continue the rapid evolution of this area. These new technologies hold many potential applications for hematological disorders, with the promise of precision and personalized medical care in the future.

Advancing quantitative PCR with color cycle multiplex amplification

Quantitative PCR (qPCR) is the gold standard for detection and quantitation of known DNA targets, but the scarcity of spectrally distinct fluorophores and filter sets limits the number of detectable targets. Here, we introduce color cycle multiplex amplification (CCMA) to significantly increase the number of detectable DNA targets in a single qPCR reaction using standard instrumentation. In CCMA, presence of one DNA target species results in a pre-programmed pattern of fluorescence increases. This pattern is distinguished by cycle thresholds (Cts) through rationally designed delays in amplification. For example, we design an assay wherein Staphylococcus aureus sequentially induces FAM, then Cy5.5, then ROX fluorescence increases with more than 3 cycles between each signal. CCMA offers notably higher potential for multiplexing because it uses fluorescence permutation rather than combination. With 4 distinct fluorescence colors, CCMA theoretically allows the detection of up to 136 distinct DNA target sequences using fluorescence permutation. Experimentally, we demonstrated a single-tube qPCR assay screening 21 sepsis-related bacterial DNA targets in samples of blood, sputum, pleural effusion and bronchoalveolar lavage fluid, with 89% clinical sensitivity and 100% clinical specificity, showing its potential as a powerful tool for advanced quantitative screening in molecular diagnostics.

A correctable decoding DNA sequencing with high accuracy and high throughput

Eliminating errors in next-generation sequencing has proven to be challenging. Here we present a novel strategy for DNA sequencing, called correctable two-color fluorogenic DNA decoding sequencing, which can significantly improve sequencing accuracy and throughput by employing a dual-nucleotide addition combined with fluorogenic sequencing-by-synthesis (SBS) chemistry. This sequencing method involves introducing a mixture of natural nucleotide X, labeled unblocked nucleotide X', 3' blocked nucleotide Y*, and labeled 3' blocked nucleotide Y* into each reaction cycle. By cyclically interrogating a template twice with different nucleotide combinations, two sets of base-encoding are sequentially obtained, enabling accurate deduction of base sequence. We demonstrate the remarkable efficacy of this approach in detecting and correcting sequencing errors, achieving a theoretical error rate of 0.0005%, which is twice as accurate as Sanger sequencing. Furthermore, we show the capability to detect known mutation sites using information from only a single sequencing run. The correctable two-color fluorogenic DNA decoding sequencing approach should enable accurate identification of extremely rare genomic variations in diverse applications in biology and medicine.

Next generation sequencing to detect pathogens causing paediatric community-acquired pneumonia - A systematic review and meta-analysis

BACKGROUND

Paediatric community-acquired pneumonia (CAP) is a major public health challenge in children, requiring accurate and timely diagnosis of causative pathogens for effective antibiotic treatment. We aimed to explore the utility of next-generation sequencing (NGS) in precise diagnosis of pediatric CAP and its effect on treatment outcome of these children.

METHODS

A systematic review and meta-analysis was conducted to compare NGS-guided antibiotic therapy with conventional methods in pediatric CAP. The study followed PRISMA guidelines and searched for electronic databases including PubMed/MEDLINE, Embase, Scopus, and Web of Sciences from 2012 to 2023. Studies on pediatric CAP (<18 years) using NGS alongside conventional diagnostics, were included.

RESULTS

Database search identified 721 studies and 6 were finally included for review, published between 2019 and 2023. Meta-analysis revealed an overall odds ratio of 2.39 (95 % CI 1.22, 3.56) for NGS vs conventional methods. Detection rates using NGS ranged from 86% to 100 %, surpassing conventional methods (26%-78.51 %). Five out of selected 6 studies (83.33 %) have documented that change in treatment based on NGS finding resulted in clinical improvement of patients. There was no significant heterogeneity and potential bias among the studies. Nearly 80 % of the studies were of good quality.

CONCLUSION

The NGS (particularly metagenomic sequencing) is a promising tool for diagnosing paediatric CAP with high accuracy. It can improve antibiotic usage practices and patient outcomes, potentially reducing antibiotic resistance. Based on meta-analysis, training of healthcare professionals in NGS methodologies and result interpretation is highly recommended.

User experience with HIV molecular epidemiology in research, surveillance, and cluster detection and response: a needs assessment

OBJECTIVE

HIV molecular epidemiology (HIV ME) is a tool that aims to improve HIV research, surveillance, and cluster detection and response. HIV ME is a core pillar of the U.S. initiative to End the HIV Epidemic but faces some challenges and criticisms from stakeholders. We sought to assess user experience to identify the current needs for HIV ME.

METHODS

Users of HIV ME, including researchers and public health practitioners, were engaged via a structured survey. Needs were assessed via open-ended questions about HIV ME. Data were analyzed using reflexive thematic analysis; the concordance of results was assessed semi-quantitatively.

RESULTS

Of 90 possible HIV-ME end-users, 57 completed the survey (response rate = 63%), which included users engaged in research (n = 29) and public health (n = 28). Respondents identified current imperatives, challenges, and strategies to improve HIV ME. Imperatives included characterization of the virus, identification of HIV hotspots, and tailoring of HIV interventions. Challenges encompassed technological issues, ethical concerns, and implementation difficulties. Strategies to improve HIV ME involved improving data access and analysis, enhancing implementation guidance and resources, and fostering community engagement and support. Researchers and public health practitioners prioritized different imperatives, but similarly emphasized the ethical concerns with HIV ME.

CONCLUSION

The imperatives identified by users underscore the necessity of HIV ME, while the challenges highlight the hurdles to be overcome, including ethical concerns which emerged as a shared emphasis across user groups. The strategies outlined offer a roadmap for overcoming these challenges. These insights, drawn from user experience, present a valuable opportunity to inform the development of guidelines for the ethical application of HIV ME in research, surveillance, and cluster detection and response.

Repetitive element expansions contribute to genome size gigantism in Pamphagidae: A comparative study (Orthoptera, Acridoidea)

Pamphagidae is a family of Acridoidea that inhabits the desert steppes of Eurasia and Africa. This study employed flow cytometry to estimate the genome size of eight species in the Pamphagidae. The results indicate that the genome size of the eight species ranged from 13.88 pg to 14.66 pg, with an average of 14.26 pg. This is the largest average genome size recorded for the Orthoptera families, as well as for the entire Insecta. Furthermore, the study explored the role of repetitive sequences in the genome, including their evolutionary dynamics and activity, using low-coverage next-generation sequencing data. The genome is composed of 14 different types of repetitive sequences, which collectively make up between 59.9% and 68.17% of the total genome. The Pamphagidae family displays high levels of transposable element (TE) activity, with the number of TEs increasing and accumulating since the family's emergence. The study found that the types of repetitive sequences contributing to the TE outburst events are similar across species. Additionally, the study identified unique repetitive elements for each species. The differences in repetitive sequences among the eight Pamphagidae species correspond to their phylogenetic relationships. The study sheds new light on genome gigantism in the Pamphagidae and provides insight into the correlation between genome size and repetitive sequences within the family.

Recent progress in DNA data storage based on high-throughput DNA synthesis

DNA data storage has emerged as a solution for storing massive volumes of data by utilizing nucleic acids as a digital information medium. DNA offers exceptionally high storage density, long durability, and low maintenance costs compared to conventional storage media such as flash memory and hard disk drives. DNA data storage consists of the following steps: encoding, DNA synthesis (i.e., writing), preservation, retrieval, DNA sequencing (i.e., reading), and decoding. Out of these steps, DNA synthesis presents a bottleneck due to imperfect coupling efficiency, low throughput, and excessive use of organic solvents. Overcoming these challenges is essential to establish DNA as a viable data storage medium. In this review, we provide the overall process of DNA data storage, presenting the recent progress of each step. Next, we examine a detailed overview of DNA synthesis methods with an emphasis on their limitations. Lastly, we discuss the efforts to overcome the constraints of each method and their prospects.

Progress based on a multi-omics research strategy in the biosynthesis and modernization of active ingredients of Herpetospermum pedunculosum seeds

Herpetospermum pedunculosum seeds also known as Herpetospermum caudigerum Wall. is the mature seed of the Herpetospermum pedunculosum(Ser.) C. B. Clarke,Cucurbitaceae. Modern pharmacological studies have shown that H. pedunculosum has hepatoprotective, anti-inflammatory, anti-gout and antibacterial pharmacological activities. The biologically active chemical components include lignin compounds such as Herpetin, Herpetetrone, Herpetoriol and so on. The natural product displays considerable skeletal diversity and structural complexity, offering significant opportunities for novel drug discovery. Based on the multi-omics research strategy and the 'gene-protein-metabolite' research framework, the biosynthetic pathway of terpenoids and lignans in H. pedunculosum has has been elucidated at multiple levels. These approaches provide comprehensive genetic information for cloning and identification of pertinent enzyme genes. Furthermore, the application of multi-omics integrative approaches provides a scientific means to elucidate entire secondary metabolic pathways. We investigated the biosynthetic pathways of lignin and terpene components in H. pedunculosum and conducted bioinformatics analysis of the crucial enzyme genes involved in the biosynthetic process using genomic and transcriptomic data. We identified candidate genes for six key enzymes in the biosynthetic pathway. This review reports on the current literature on pharmacological investigations of H. pedunculosum, proposing its potential as an antidiabetic agent. Moreover, we conclude, for the first time, the identification of key enzyme genes potentially involved in the biosynthesis of active compounds in H. pedunculosum. This review provides a scientific foundation for the discovery of novel therapeutic agents from natural sources.

First metagenomic analysis of virome in Uzbekistan honey bee (Apis mellifera): Investigating basic information on honey bee viruses

Honey bees are economically important insects. However, they face multiple biotic and abiotic stresses, such as diseases, pesticides, climate change, and pests, which cause the loss of honey bee colonies worldwide. Among these factors, viruses have been identified as the major cause of colony loss. Research on honey bee viruses in Uzbekistan is limited. This study investigated the viruses affecting honey bees in Uzbekistan. Virome analysis was conducted for each sample using high-throughput sequencing and bioinformatics. Nine honey bee viruses have been identified: the acute bee paralysis virus, aphid lethal paralysis virus, Apis rhabdovirus 1 and 2, black queen cell virus, deformed wing virus, Lake Sinai virus 10, sacbrood virus, and Hubei partiti-like virus 34. Additionally, 15 plant viruses were identified, 7 of which were novel. This study is the first virome analysis of Uzbekistan honey bees and provides a foundation for understanding the viruses affecting honey bees and plants in Uzbekistan.

Implementing next-generation sequencing for diagnosis and management of hereditary hearing impairment: a comprehensive review

INTRODUCTION

Sensorineural hearing impairment (SNHI), a common childhood disorder with heterogeneous genetic causes, can lead to delayed language development and psychosocial problems. Next-generation sequencing (NGS) offers high-throughput screening and high-sensitivity detection of genetic etiologies of SNHI, enabling clinicians to make informed medical decisions, provide tailored treatments, and improve prognostic outcomes.

AREAS COVERED

This review covers the diverse etiologies of HHI and the utility of different NGS modalities (targeted sequencing and whole exome/genome sequencing), and includes HHI-related studies on newborn screening, genetic counseling, prognostic prediction, and personalized treatment. Challenges such as the trade-off between cost and diagnostic yield, detection of structural variants, and exploration of the non-coding genome are also highlighted.

EXPERT OPINION

In the current landscape of NGS-based diagnostics for HHI, there are both challenges (e.g. detection of structural variants and non-coding genome variants) and opportunities (e.g. the emergence of medical artificial intelligence tools). The authors advocate the use of technological advances such as long-read sequencing for structural variant detection, multi-omics analysis for non-coding variant exploration, and medical artificial intelligence for pathogenicity assessment and outcome prediction. By integrating these innovations into clinical practice, precision medicine in the diagnosis and management of HHI can be further improved.

Advancement of Next-Generation DNA Sequencing through Ionic Blockade and Transverse Tunneling Current Methods

DNA sequencing is transforming the field of medical diagnostics and personalized medicine development by providing a pool of genetic information. Recent advancements have propelled solid-state material-based sequencing into the forefront as a promising next-generation sequencing (NGS) technology, offering amplification-free, cost-effective, and high-throughput DNA analysis. Consequently, a comprehensive framework for diverse sequencing methodologies and a cross-sectional understanding with meticulous documentation of the latest advancements is of timely need. This review explores a broad spectrum of progress and accomplishments in the field of DNA sequencing, focusing mainly on electrical detection methods. The review delves deep into both the theoretical and experimental demonstrations of the ionic blockade and transverse tunneling current methods across a broad range of device architectures, nanopore, nanogap, nanochannel, and hybrid/heterostructures. Additionally, various aspects of each architecture are explored along with their strengths and weaknesses, scrutinizing their potential applications for ultrafast DNA sequencing. Finally, an overview of existing challenges and future directions is provided to expedite the emergence of high-precision and ultrafast DNA sequencing with ionic and transverse current approaches.

Monitoring Escherichia coli in Water through Real-Time Loop-Mediated Isothermal Amplification on Biochips

Access to clean water is fundamental to public health and safety, serving as the cornerstone of well-being in communities. Despite the significant investments of millions of dollars in water testing and treatment processes, the United States continues to grapple with over 7 million waterborne-related cases annually. This persistent challenge underscores the pressing need for the development of a new, efficient, rapid, low-cost, and reliable method for ensuring water quality. The urgency of this endeavor cannot be overstated, as it holds the potential to safeguard countless lives and mitigate the pervasive risks associated with contaminated water sources. In this study, we introduce a biochip LAMP assay tailored for water source monitoring. Our method swiftly detects even extremely low concentrations of Escherichia coli (E. coli) in water, and 10 copies/μL of E. coli aqueous solution could yield positive results within 15 min on a PC-MEDA biochip. This innovation marks a significant departure from the current reliance on lab-dependent methods, which typically necessitate several days for bacterial culture and colony counting. Our multifunctional biochip system not only enables the real-time LAMP testing of crude E. coli samples but also holds promise for future modifications to facilitate on-site usage, thereby revolutionizing water quality assessment and ensuring rapid responses to potential contamination events.

Photothermal-Driven Droplet Manipulation: A Perspective

Optofluidics, which utilizes the interactions between light and fluids to realize various functions, has garnered increasing attention owing to the advantages of operational simplicity, exceptional flexibility, rapid response, etc. As one of the typical light-fluid interactions, the localized photothermal effect serving as a stimulus has been widely used for fluid manipulation. Particularly, significant progress on photothermal-driven droplet manipulation has been made. In this perspective, recent advancements in localized photothermal effect driven droplet manipulation are summarized. First, the photothermal manipulation of droplets on open surfaces is outlined. An attractive droplet manipulation of light droplet levitation above the gas-liquid interface via localized photothermal effect is then discussed. Besides, the photothermal-driven manipulation of droplets in an immiscible liquid phase is also discussed. Although promising, further development of photothermal-driven droplet manipulation is still needed. The challenges and perspectives of this light droplet manipulation strategy for broad implementation are summarized, which will help future studies and applications.

New insights into mycotoxin risk management through fungal population genetics and genomics

Mycotoxin contamination of food and feed is a major global concern. Chronic or acute dietary exposure to contaminated food and feed can negatively affect both human and animal health. Contamination occurs through plant infection by toxigenic fungi, primarily Aspergillus and Fusarium spp., either before or after harvest. Despite the application of various management strategies, controlling these pathogens remains a major challenge primarily because of their ability to adapt to environmental changes and selection pressures. Understanding the genetic structure of plant pathogen populations is pivotal for gaining new insights into their biology and epidemiology, as well as for understanding the mechanisms behind their adaptability. Such deeper understanding is crucial for developing effective and preemptive management strategies tailored to the evolving nature of pathogenic populations. This review focuses on the population-level variations within the two most economically significant toxigenic fungal genera according to space, host, and pathogenicity. Outcomes in terms of migration patterns, gene flow within populations, mating abilities, and the potential for host jumps are examined. We also discuss effective yet often underutilized applications of population genetics and genomics to address practical challenges in the epidemiology and disease control of toxigenic fungi.

Assessing a single-cell multi-omic analytic platform to characterize ex vivo-engineered T-cell therapy products

Genetically engineered CD8+ T cells are being explored for the treatment of various cancers. Analytical characterization represents a major challenge in the development of genetically engineered cell therapies, especially assessing the potential off-target editing and product heterogeneity. As conventional sequencing techniques only provide information at the bulk level, they are unable to detect off-target CRISPR translocation or editing events occurring in minor cell subpopulations. In this study, we report the analytical development of a single-cell multi-omics DNA and protein assay to characterize genetically engineered cell products for safety and genotoxicity assessment. We were able to quantify on-target edits, off-target events, and potential translocations at the targeting loci with per-cell granularity, providing important characterization data of the final cell product. Conclusion: A single-cell multi-omics approach provides the resolution required to understand the composition of cellular products and identify critical quality attributes (CQAs).

A Deniable Encryption Method for Modulation-Based DNA Storage

Recent advancements in synthesis and sequencing techniques have made deoxyribonucleic acid (DNA) a promising alternative for next-generation digital storage. As it approaches practical application, ensuring the security of DNA-stored information has become a critical problem. Deniable encryption allows the decryption of different information from the same ciphertext, ensuring that the "plausible" fake information can be provided when users are coerced to reveal the real information. In this paper, we propose a deniable encryption method that uniquely leverages DNA noise channels. Specifically, true and fake messages are encrypted by two similar modulation carriers and subsequently obfuscated by inherent errors. Experiment results demonstrate that our method not only can conceal true information among fake ones indistinguishably, but also allow both the coercive adversary and the legitimate receiver to decrypt the intended information accurately. Further security analysis validates the resistance of our method against various typical attacks. Compared with conventional DNA cryptography methods based on complex biological operations, our method offers superior practicality and reliability, positioning it as an ideal solution for data encryption in future large-scale DNA storage applications.

Detection of hemophilia A genetic variants using third-generation long-read sequencing

BACKGROUND

Hemophilia A (HA) is an X-linked recessive genetic disorder caused by pathogenic variations of the factor VIII -encoding gene, F8 gene. Due to the large size and diverse types of variations in the F8 gene, causative mutations in F8 cannot be simultaneously detected in one step by traditional molecular analysis, and genetic molecular diagnosis and prenatal screening of HA still face significant difficulties and challenges in clinical practice. Therefore, we aimed to develop and validate an efficient, accurate, and time-saving method for the genetic detection of HA.

METHODS

A comprehensive analysis of hemophilia A (CAHEA) method based on long-range PCR and long-read sequencing (LRS) was used to detect F8 gene mutations in 14 clinical HA samples. The LRS results were compared with those of the conventional methods to evaluate the accuracy and sensitivity of the proposed approach.

RESULTS

The CAHEA method successfully identified 14 F8 variants in all probands, including 3 small insertion deletions, 4 single nucleotide variants, and 7 intron 22 inversions in a "one-step" manner, of which 2 small deletions have not been reported previously. Moreover, this method provided an opportunity to analyze the mechanism of rearrangement and the pathogenicity of F8 variants. The LRS results were validated and found to be in 100% agreement with those obtained using the conventional method.

CONCLUSION

Our proposed LRS-based F8 gene detection method is an accurate and reproducible genetic screening and diagnostic method with significant clinical value. It provides efficient, comprehensive, and accurate genetic screening and diagnostic services for individuals at high risk of HA as well as for premarital and prenatal populations.

Transcriptome analysis of East Asian common octopus, Octopus sinensis, paralarvae

BACKGROUND

The genes involved in cephalopod development and their association with hatching and survival during early life stages have been extensively studied. However, few studies have investigated the paralarvae transcriptome of the East Asian common octopus (Octopus sinen sis).

OBJECTIVE

This study aimed to identify the genes related to embryonic development and hatching in O. sinensis using RNA sequencing (RNA-seq) and verify the genes most relevant to different embryonic stages.

METHODS

RNA samples from hatched and 25 days post-hatching (dph) O. sinensis paralarvae were used to construct cDNA libraries. Clean reads from individual samples were aligned to the reference O. sinensis database to identify the differentially expressed genes (DEGs) between the 0- and 25-dph paralarvae libraries. Real-time quantitative polymerase chain reaction (RT-qPCR) was used to supplement the RNA-seq data for embryogenic developmental stages.

RESULTS

A total of 12,597 transcripts were annotated and 5,468 DEGs were identified between the 0- and 25-dph O. sinensis paralarvae, including 2,715 upregulated and 2,753 downregulated transcripts in the 25-dph paralarvae. Several key DEGs were related to transmembrane transport, lipid biosynthesis, monooxygenase activity, lipid transport, neuropeptide signaling, transcription regulation, and protein-cysteine S-palmitoyltransferase activity during the post-hatching development of O. sinensis paralarvae. RT-qPCR analysis further revealed that SLC5A3A, ABCC12, and NPC1 transcripts in 20 and/or 30 days post-fertilization (dpf) embryos were significantly higher (p < 0.05) than those in 10-dpf embryos.

CONCLUSION

Transcriptome profiles provide molecular targets to understand the embryonic development, hatching, and survival of O. sinensis paralarvae, and enhance octopus production.

RNA-sequencing exploration on SIR2 and SOD genes in Polyalthia longifolia leaf methanolic extracts (PLME) mediated anti-aging effects in Saccharomyces cerevisiae BY611 yeast cells

Polyalthia longifolia is well-known for its abundance of polyphenol content and traditional medicinal uses. Previous research has demonstrated that the methanolic extract of P. longifolia leaves (PLME, 1 mg/mL) possesses anti-aging properties in Saccharomyces cerevisiae BY611 yeast cells. Building on these findings, this study delves deeper into the potential antiaging mechanism of PLME, by analyzing the transcriptional responses of BY611 cells treated with PLME using RNA-sequencing (RNA-seq) technology. The RNA-seq analysis results identified 1691 significantly (padj < 0.05) differentially expressed genes, with 947 upregulated and 744 downregulated genes. Notably, the expression of three important aging-related genes, SIR2, SOD1, and SOD2, showed a significant difference following PLME treatment. The subsequent integration of these targeted genes with GO and KEGG pathway analysis revealed the multifaceted nature of PLME's anti-aging effects in BY611 yeast cells. Enriched GO and KEGG analysis showed that PLME treatment promotes the upregulation of SIR2, SOD1, and SOD2 genes, leading to a boosted cellular antioxidant defense system, reduced oxidative stress, regulated cell metabolism, and maintain genome stability. These collectively increased longevities in PLME-treated BY611 yeast cells and indicate the potential anti-aging action of PLME through the modulation of SIR2 and SOD genes. The present study provided novel insights into the roles of SIR2, SOD1, and SOD2 genes in the anti-aging effects of PLME treatment, offering promising interventions for promoting healthy aging.

FecalSeq enrichment with RAD Sequencing from non-invasive environmental samples holds promise for genetic monitoring of an imperiled lagomorph

Despite advances in genomic sequencing and bioinformatics, conservation genomics is still often hindered by a reliance on non-invasive samples. The presence of exogenous DNA and the low quantity and poor quality of DNA in non-invasive samples have been a roadblock to sequencing, thereby limiting the potential for genomic monitoring of endangered species. Recent molecular advances, such as host DNA enrichment, hold promise for facilitating sequencing from non-invasive samples. We used the FecalSeq method to enrich DNA extracted from wild-collected fecal pellets of the imperiled New England cottontail and identified SNPs from 3RAD Sequencing. We obtained SNPs from rabbit pellets, including pellets that were collected in poor environmental conditions and samples that performed poorly with microsatellites. Measures of sequencing success improved with greater amounts of starting DNA and 32% of samples generated SNP genotypes that passed quality control filtering. Genotyping error rates were high, however, and the approach was unable to consistently distinguish unique individuals or matching genotypes, while it was suitable for recovering the expected population structure. Pairing FecalSeq enrichment with RADseq is a promising low-cost method for monitoring wild populations using non-invasive samples in an environmental context, but it may be better suited for informing conservation through population genomics.

A Protocol to Extract a Specific Genomic Region from a Public Whole-Genome Database and Modify Analytical Bin Length for Population Genetic Studies

With the advent of "next-generation" sequencing and the continuous reduction in sequencing costs, an increasing amount of genomic data has emerged, such as whole-genome, whole-exome, and targeted sequencing data. These applications are popular not only in mega sequencing projects, such as the 1000 Genomes Project and UK BioBank, but also among individual researchers. Evolutionary genetic analyses, such as the dN/dS ratio and Tajima's D, are demanded more and more for whole-genome-level population data. These analyses are often carried out under a uniform custom bin size across the genome. However, these analyses require subdivision of a genomic region into functional units, such as protein-coding regions, introns, and untranslated regions, and computing these genetic measures for large-scale data remains challenging. In a recent investigation, we successfully devised a method to address this issue. This method requires a multi-sample VCF file containing population data, a reference genome, target regions in the BED file, and a list of samples to be included in the analysis. Given that the targeted regions are extracted in a new VCF file, targeted population genetic analysis can be performed. We conducted Tajima's D analysis using this approach on intact and pseudogenes, as well as non-coding regions.

TabDEG: Classifying differentially expressed genes from RNA-seq data based on feature extraction and deep learning framework

Traditional differential expression genes (DEGs) identification models have limitations in small sample size datasets because they require meeting distribution assumptions, otherwise resulting high false positive/negative rates due to sample variation. In contrast, tabular data model based on deep learning (DL) frameworks do not need to consider the data distribution types and sample variation. However, applying DL to RNA-Seq data is still a challenge due to the lack of proper labeling and the small sample size compared to the number of genes. Data augmentation (DA) extracts data features using different methods and procedures, which can significantly increase complementary pseudo-values from limited data without significant additional cost. Based on this, we combine DA and DL framework-based tabular data model, propose a model TabDEG, to predict DEGs and their up-regulation/down-regulation directions from gene expression data obtained from the Cancer Genome Atlas database. Compared to five counterpart methods, TabDEG has high sensitivity and low misclassification rates. Experiment shows that TabDEG is robust and effective in enhancing data features to facilitate classification of high-dimensional small sample size datasets and validates that TabDEG-predicted DEGs are mapped to important gene ontology terms and pathways associated with cancer.

Clinical description and evaluation of 30 pediatric patients with ultra-rare diseases: A multicenter study with real-world data from Saudi Arabia

BACKGROUND

With the advancement of next-generation sequencing, clinicians are now able to detect ultra-rare mutations that are barely encountered by the majority of physicians. Ultra-rare and rare diseases cumulatively acquire a prevalence equivalent to type 2 diabetes with 80% being genetic in origin and more prevalent among high consanguinity communities including Saudi Arabia. The challenge of these diseases is the ability to predict their prevalence and define clear phenotypic features.

METHODS

This is a non-interventional retrospective multicenter study. We included pediatric patients with a pathogenic variant designated as ultra-rare according to the National Institute for Clinical Excellence's criteria. Demographic, clinical, laboratory, and radiological data of all patients were collected and analyzed using multinomial regression models.

RESULTS

We included 30 patients. Their mean age of diagnosis was 16.77 months (range 3-96 months) and their current age was 8.83 years (range = 2-15 years). Eleven patients were females and 19 were males. The majority were of Arab ethnicity (96.77%). Twelve patients were West-Saudis and 8 patients were South-Saudis. SCN1A mutation was reported among 19 patients. Other mutations included SZT2, ROGDI, PRF1, ATP1A3, and SHANK3. The heterozygous mutation was reported among 67.86%. Twenty-nine patients experienced seizures with GTC being the most frequently reported semiology. The mean response to ASMs was 45.50% (range 0-100%).

CONCLUSION

The results suggest that ultra-rare diseases must be viewed as a distinct category from rare diseases with potential demographic and clinical hallmarks. Additional objective and descriptive criteria to detect such cases are needed.

Next generation plant biostimulants & genome sequencing strategies for sustainable agriculture development

The best environment for plant growth and development contains certain essential metabolites. A broad category of metabolites known as "plant biostimulants" (PBs) includes biomolecules such as proteins, carbohydrates, lipids, and other secondary metabolites related to groups of terpenes, specific nitrogen-containing compounds, and benzene ring-conjugated compounds. The formation of biomolecules depends on both biotic and abiotic factors, such as the release of PB by plants, animals, and microorganisms, or it can result from the control of temperature, humidity, and pressure in the atmosphere, in the case of humic substances (HSs). Understanding the genomic outputs of the concerned organism (may be plants or others than them) becomes crucial for identifying the underlying behaviors that lead to the synthesis of these complex compounds. For the purposes of achieving the objectives of sustainable agriculture, detailed research on PBs is essential because they aid in increasing yield and other growth patterns of agro-economic crops. The regulation of homeostasis in the plant-soil-microbe system for the survival of humans and other animals is mediated by the action of plant biostimulants, as considered essential for the growth of plants. The genomic size and gene operons for functional and regulation control have so far been revealed through technological implementations, but important gene annotations are still lacking, causing a delay in revealing the information. Next-generation sequencing techniques, such as nanopore, nanoball, and Illumina, are essential in troubleshooting the information gaps. These technical advancements have greatly expanded the candidate gene openings. The secondary metabolites being important precursors need to be studied in a much wider scale for accurate calculations of biochemical reactions, taking place inside and outside the synthesized living cell. The present review highlights the sequencing techniques to provide a foundation of opportunity generation for agricultural sustainability.

Molecular findings in patients for whole exome sequencing and mitochondrial genome assessment

OBJECTIVE

Whole exome sequencing (WES) is becoming more widely used as a diagnostic tool in the field of medicine. In this article, we reported the diagnostic yield of WES and mitochondrial genome assessment in 2226 consecutive cases in a single clinical laboratory.

MATERIALS AND METHODS

We retrospectively analyzed consecutive WES reports from 2226 patients with various genetic disorders. WES-process was focused exclusively on the probands and aimed at a higher diagnostic capacity. We determined the diagnostic rate of WES overall and by phenotypic category, mode of inheritance, mitochondrial genome variant, and copy number variants (CNVs).

RESULTS

Among the 2226 patients who had diagnostic WES proband-only, the overall diagnostic yield of WES was 34.59% (770/2226). The highest diagnostic yield was observed in autosomal dominant disorders, at 45.58% (351/770), followed by autosomal recessive at 31.95%(246/770), X-linked disorder at 9.61%(74/770), and mitochondrial diseases at a notably lower 0.65%(5/770). The 12.21% (94/770) diagnoses were based on a total of 94 copy number variants reported from WES data. CNVs in children accounted for 67.02% of the total CNVs. While majority of the molecular diagnoses were related to nuclear genes, the inclusion of mitochondrial genome sequencing in the WES test contributed to five diagnoses. all mitochondrial diseases were identified in adults.

CONCLUSIONS

The proband-only WES provided a definitive molecular diagnosis for 34.59% of a large cohort of patients while analysis of WES simultaneously analyzed the SNVs, exons, mitochondrial genome, and CNVs, thereby improving the diagnostic yield significantly compared to the single-detection WES method; and facilitating the identification of novel candidate genes.

SeqCAT: Sequence Conversion and Analysis Toolbox

Dealing with sequence coordinates in different formats and reference genomes is challenging in genetic research. This complexity arises from the need to convert and harmonize datasets of different sources using alternating nomenclatures. Since manual processing is time-consuming and requires specialized knowledge, the Sequence Conversion and Analysis Toolbox (SeqCAT) was developed for daily work with genetic datasets. Our tool provides a range of functions designed to standardize and convert gene variant coordinates based on various sequence types. Its user-friendly web interface provides easy access to all functionalities, while the Application Programming Interface (API) enables automation within pipelines. SeqCAT provides access to human genomic, protein and transcript data, utilizing various data resources and packages and extending them with its own unique features. The platform covers a wide range of genetic research needs with its 14 different applications and 3 info points, including search for transcript and gene information, transition between reference genomes, variant mapping, and genetic event review. Notable examples are 'Convert Protein to DNA Position' for translation of amino acid changes into genomic single nucleotide variants, or 'Fusion Check' for frameshift determination in gene fusions. SeqCAT is an excellent resource for converting sequence coordinate data into the required formats and is available at: https://mtb.bioinf.med.uni-goettingen.de/SeqCAT/.

Developmental validation of the ForenSeq® Kintelligence kit, MiSeq FGx® sequencing system and ForenSeq Universal Analysis Software

Forensic Investigative Genetic Genealogy, a recent sub discipline of forensic genomics, leverages the high throughput and sensitivity of detection of next generation sequencing and established genetic and genealogical approaches to support the identification of human remains from missing persons investigations and investigative lead generation in violent crimes. To facilitate forensic DNA evidence analysis, the ForenSeq® Kintelligence multiplex, consisting of 10,230 SNPs, was developed. Design of the ForenSeq Kintelligence Kit, the MiSeq FGx® Sequencing System and the ForenSeq Universal Analysis Software is described. Developmental validation in accordance with SWGDAM guidelines and forensic quality assurance standards, using single source samples, is reported for the end-to-end workflow from library preparation to data interpretation. Performance metrics support the conclusion that more genetic information can be obtained from challenging samples compared to other commercially available forensic targeted DNA assays developed for capillary electrophoresis (CE) or other current next generation sequencing (NGS) kits due to the higher number of markers, the overall shorter amplicon sizes (97.8% <150 bp), and kit design. Data indicate that the multiplex is robust and fit for purpose for a wide range of quantity and quality samples. The ForenSeq Kintelligence Kit and the Universal Analysis Software allow transfer of the genetic component of forensic investigative genetic genealogy to the operational forensic laboratory.

Identification of a DNA-methylome-based signature for prognosis prediction in driver gene-negative lung adenocarcinoma

"Driver gene-negative" lung adenocarcinoma (LUAD) was of rare treatment options and a poor prognosis. Presently, for them, few biomarkers are available for stratification analysis to make appropriate treatment strategy. This study aimed to develop a DNA-methylome-based signature to realize the precise risk-stratifying. Here, an Illumina MethylationEPIC Beadchip was applied to obtain differentially methylated CpG sites (DMCs). A four-CpG-based signature, named as TLA, was successfully established, whose prognosis-predicting power was well verified in one internal (n = 78) and other external (n = 110) validation cohorts. Patients with high-risk scores had shorter overall survival (OS) in all cohorts [hazard ratio (HR): 11.79, 5.16 and 2.99, respectively]. Additionally, it can effectively divide patients into low-risk and high-risk groups, with significantly different OS in the diverse subgroups stratified by the standard clinical parameters. As an independent prognostic factor, TLA may assist in improving the nomogram's 5-year OS-predicting ability (AUC 0.756, 95% CI:0.695-0.816), superior to TNM alone (AUC 0.644, 95% CI: 0.590-0.698). Additionally, the relationship of TLA-related genes, TAC1, LHX9, and ALX1, with prognosis and tumour invasion made them serve as potential therapy targets for driver gene-negative LUAD.

Selective microRNA expression of exosomes from retinal pigment epithelial cells by oxidative stress

The function of exosomal miRNAs (miRs) in retinal degeneration is largely unclear. We were aimed to investigate the functions of exosomes as well as their miRs derived from retinal pigment epithelial (RPE) cells following exposure to oxidative stress (OS). After the OS by lipopolysaccharide and rotenone on RPE cells, interleukin-1 beta (IL-1β), Interleukin-6 (IL-6), Tumor Necrosis Factor-alpha (TNF-α) were upregulated, along with the decreased mitochondrial membrane potential and upregulated oxidative damage marker 8-OH-dG in RPE cells. RPE-derived exosomes were then isolated, identified, injected into the subretinal space in mice. After subretinal injection, RPE-exosomes after OS not only induced higher ROS level and apoptotic retinal cells, but also elevated IL-1β, IL-6 alongside TNF-α expressions among retina/RPE/choroidal complex. Next, miRs inside the exosomes were sequenced by the next generation sequencing (NGS) technology. NGS revealed that certain miRs were abundant in exosomes, while others were selectively kept by RPE cells. Further, downregulated miRs, like miR-125b-5p, miR-125a-5p, alongside miR-128-3p, and upregulated miR, such as miR-7-5p were validated byRT-qPCR. Finally, Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to find the possible target genes of those selective exosomal miRs. Our results proved that the RPE-derived exosomes after OS selectively express certain miRs, providing novel insights into the pathogenesis of age-related macular degeneration (AMD) in future.

Metabolism-Based Herbicide Resistance to Mesosulfuron-methyl and Identification of Candidate Genes in Bromus japonicus

The evolved resistance of Bromus japonicus Houtt. to ALS-inhibiting herbicides is well established. Previous studies have primarily focused on target-site resistance; however, non-target-site resistance has not been well characterized. This investigation demonstrated that ALS gene sequencing did not detect any previously known resistance mutations in a mesosulfuron-methyl-resistant (MR) population, and notably, treatment with the P450 monooxygenase (P450) inhibitor malathion markedly heightened susceptibility to mesosulfuron-methyl. Utilizing UPLC-MS/MS analysis confirmed elevated mesosulfuron-methyl metabolism in MR plants. The integration of Isoform Sequencing (Iso-Seq) and RNA Sequencing (RNA-Seq) facilitated the identification of candidate genes associated with non-target sites in a subpopulation with two generations of herbicide selection. Through qRT-PCR analysis, 21 differentially expressed genes were characterized, and among these, 10 genes (comprising three P450s, two glutathione S-transferases, one glycosyltransferase, two ATP-binding cassette transporters, one oxidase, and one hydrolase) exhibited constitutive upregulation in resistant plants. Our findings substantiated that increased herbicide metabolism is a driving force behind mesosulfuron-methyl resistance in this B. japonicus population.

Comparative transcriptome analysis reveals molecular damage associated with cryopreservation in Crassostrea angulata D-larvae rather than to cryoprotectant exposure

BACKGROUND

The Portuguese oyster Crassostrea angulata, a bivalve of significant economic and ecological importance, has faced a decline in both production and natural populations due to pathologies, climate change, and anthropogenic factors. To safeguard its genetic diversity and improve reproductive management, cryopreservation emerges as a valuable strategy. However, the cryopreservation methodologies lead to some damage in structures and functions of the cells and tissues that can affect post-thaw quality. Transcriptomics may help to understand the molecular consequences related to cryopreservation steps and therefore to identify different freezability biomarkers. This study investigates the molecular damage induced by cryopreservation in C. angulata D-larvae, focusing on two critical steps: exposure to cryoprotectant solution and the freezing/thawing process.

RESULTS

Expression analysis revealed 3 differentially expressed genes between larvae exposed to cryoprotectant solution and fresh larvae and 611 differentially expressed genes in cryopreserved larvae against fresh larvae. The most significantly enriched gene ontology terms were "carbohydrate metabolic process", "integral component of membrane" and "chitin binding" for biological processes, cellular components and molecular functions, respectively. Kyoto Encyclopedia of Genes and Genomes enrichment analysis identified the "neuroactive ligand receptor interaction", "endocytosis" and "spliceosome" as the most enriched pathways. RNA sequencing results were validate by quantitative RT-PCR, once both techniques presented the same gene expression tendency and a group of 11 genes were considered important molecular biomarkers to be used in further studies for the evaluation of cryodamage.

CONCLUSIONS

The current work provided valuable insights into the molecular repercussions of cryopreservation on D-larvae of Crassostrea angulata, revealing that the freezing process had a more pronounced impact on larval quality compared to any potential cryoprotectant-induced toxicity. Additionally, was identify 11 genes serving as biomarkers of freezability for D-larvae quality assessment. This research contributes to the development of more effective cryopreservation protocols and detection methods for cryodamage in this species.

Uncovering the genetic diversity and adaptability of Butuo Black Sheep through whole-genome re-sequencing

The Butuo Black Sheep (BBS) is well-known for its ability to thrive at high altitudes, resist diseases, and produce premium-quality meat. Nonetheless, there is insufficient data regarding its genetic diversity and population-specific Single nucleotide polymorphisms (SNPs). This paper centers on the genetic diversity of (BBS). The investigation conducted a whole-genome resequencing of 33 BBS individuals to recognize distinct SNPs exclusive to BBS. The inquiry utilized bioinformatic analysis to identify and explain SNPs and pinpoint crucial mutation sites. The findings reveal that reproductive-related genes (GHR, FSHR, PGR, BMPR1B, FST, ESR1), lipid-related genes (PPARGC1A, STAT6, DGAT1, ACACA, LPL), and protein-related genes (CSN2, LALBA, CSN1S1, CSN1S2) were identified as hub genes. Functional enrichment analysis showed that genes associated with reproduction, immunity, inflammation, hypoxia, PI3K-Akt, and AMPK signaling pathways were present. This research suggests that the unique ability of BBS to adapt to low oxygen levels in the plateau environment may be owing to mutations in a variety of genes. This study provides valuable insights into the genetic makeup of BBS and its potential implications for breeding and conservation efforts. The genes and SPNs identified in this study could serve as molecular markers for BBS.

Monitoring Changes in the Antimicrobial-Resistance Gene Set (ARG) of Raw Milk and Dairy Products in a Cattle Farm, from Production to Consumption

Raw milk and dairy products can serve as potential vectors for transmissible bacterial, viral and protozoal diseases, alongside harboring antimicrobial-resistance genes. This study monitors the changes in the antimicrobial-resistance gene pool in raw milk and cheese, from farm to consumer, utilizing next-generation sequencing. Five parallel sampling runs were conducted to assess the resistance gene pool, as well as phage or plasmid carriage and potential mobility. In terms of taxonomic composition, in raw milk the Firmicutes phylum made up 41%, while the Proteobacteria phylum accounted for 58%. In fresh cheese, this ratio shifted to 93% Firmicutes and 7% Proteobacteria. In matured cheese, the composition was 79% Firmicutes and 21% Proteobacteria. In total, 112 antimicrobial-resistance genes were identified. While a notable reduction in the resistance gene pool was observed in the freshly made raw cheese compared to the raw milk samples, a significant growth in the resistance gene pool occurred after one month of maturation, surpassing the initial gene frequency. Notably, the presence of extended-spectrum beta-lactamase (ESBL) genes, such as OXA-662 (100% coverage, 99.3% identity) and OXA-309 (97.1% coverage, 96.2% identity), raised concerns; these genes have a major public health relevance. In total, nineteen such genes belonging to nine gene families (ACT, CMY, EC, ORN, OXA, OXY, PLA, RAHN, TER) have been identified. The largest number of resistance genes were identified against fluoroquinolone drugs, which determined efflux pumps predominantly. Our findings underscore the importance of monitoring gene pool variations throughout the product pathway and the potential for horizontal gene transfer in raw products. We advocate the adoption of a new approach to food safety investigations, incorporating next-generation sequencing techniques.

A novel method addressing NGS-based mappability bias for sensitive detection of DNA alterations

A turning point in cancer research is the introduction of massively parallel sequencing technology which greatly reduced the cost and time for genome sequencing. This enhanced the scope for detecting and analyzing the role of structural alterations in cancer. However, certain bias exists in NGS-based approaches, which badly affects the CNV identification process. Moreover, DNA repeats existing in CNV regions need special attention as they will degrade the performance of majority of the existing CNV detection tools, even after applying generalized bias correction method. This motivated this work, where a novel method has been designed to address the issue of DNA repeats and thereby mappability bias existing in regions of CNV. The method consists of three phases, where the first phase computes the alignment information of uniquely mapped DNA reads, considering the base quality and base mismatch parameters at nucleotide level precision. The second and the third phase use a novel approach to allocate the non-uniquely mapped reads to an optimal region of the DNA repeats based on a probabilistic membership model. The proposed method is capable of identifying CNVs present in coding, as well as non-coding region of the DNA, and is also capable of detecting CNVs existing in DNA repeat regions. The methodology achieves a sensitivity greater than [Formula: see text] during the performed simulations, and on real data, the detected variants are validated with the database of genomic variants, where the percentage overlap is also greater than 95%, and has achieved much better breakpoint prediction, as compared with other popular bias correction CNV detection methods.

Relative frequency of genomic mutations in SARS-CoV-2 recovered from southern Brazilian cases of COVID-19 through the Gamma, Delta and Omicron waves

The presence of different mutations in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome can be related to changes in coronavirus disease (COVID-19) infection. Besides, these viral alterations associated with factors such as massive number of positive cases, vaccination and reinfections can be important in the viral evolution process. As well as, mutations found at low frequencies may have a more neutral action and consequently be less inclined to negative selection, facilitating their spread through the population. Related to that, we aimed to present mutations that are possibly relevant in the process of viral evolution found in 115 SARS-CoV-2 sequences from samples of individuals residing in the metropolitan region of Porto Alegre in the state of Rio Grande do Sul, Brazil. The genome from clinical samples was sequenced using High-Throughput Sequencing (HTS) and analyzed using a workflow to map reads and find variations/SNPs. The samples were separated into 3 groups considering the sample lineage. Of the total number of analyzed sequences, 35 were from the Gamma lineage, 35 from Delta and 45 from Omicron. Amino acid changes present in frequencies lower than 80% of the reads in the sequences were evaluated. 11 common mutations among the samples were found in the Gamma lineage, 1 in the ORF1ab gene, 7 in the S gene, 2 in the ORF6 gene and 1 in the ORF7a gene. While in the Delta lineage, a total of 11 mutations distributed in the ORF1ab, S, ORF7a and N genes, 2, 7, 1 and 1 mutation were found in each gene, respectively. And finally, in the Omicron, 16 mutations were identified, 2 in the ORF1ab gene, 12 in the S gene and 2 in the M gene. In conclusion, we emphasize that genomic surveillance can be a useful tool to assess how mutations play a key role in virus adaptation, and its process of susceptibility to new hosts showing the possible signs of viral evolution.

Next generation sequencing technologies to address aberrant mRNA translation in cancer

In this review, we explore the transformative impact of next generation sequencing technologies in the realm of translatomics (the study of how translational machinery acts on a genome-wide scale). Despite the expectation of a direct correlation between mRNA and protein content, the complex regulatory mechanisms that affect this relationship remark the limitations of standard RNA-seq approaches. Then, the review characterizes crucial techniques such as polysome profiling, ribo-seq, trap-seq, proximity-specific ribosome profiling, rnc-seq, tcp-seq, qti-seq and scRibo-seq. All these methods are summarized within the context of cancer research, shedding light on their applications in deciphering aberrant translation in cancer cells. In addition, we encompass databases and bioinformatic tools essential for researchers that want to address translatome analysis in the context of cancer biology.

Pan-Cancer Molecular Biomarkers: A Paradigm Shift in Diagnostic Pathology

The rapid adoption of next-generation sequencing in clinical oncology has enabled the detection of molecular biomarkers shared between multiple tumor types. These pan-cancer biomarkers include sequence-altering mutations, copy number changes, gene rearrangements, and mutational signatures and have been demonstrated to predict response to targeted therapy. This article reviews issues surrounding current and emerging pan-cancer molecular biomarkers in clinical oncology: technological advances that enable the broad detection of cancer mutations across hundreds of genes, the spectrum of driver and passenger mutations derived from human cancer genomes, and implications for patient care now and in the near future.

The RNAi Machinery in the Fungus Fusarium fujikuroi Is Not Very Active in Synthetic Medium and Is Related to Transposable Elements

Small RNAS (sRNAs) participate in regulatory RNA interference (RNAi) mechanisms in a wide range of eukaryotic organisms, including fungi. The fungus Fusarium fujikuroi, a model for the study of secondary metabolism, contains a complete set of genes for RNAi pathways. We have analyzed by high-throughput sequencing the content of sRNAs in total RNA samples of F. fujikuroi grown in synthetic medium in the dark or after 1 h of illumination, using libraries below 150 nt, covering sRNAs and their precursors. For comparison, a parallel analysis with Fusarium oxysporum was carried out. The sRNA reads showed a higher proportion of 5' uracil in the RNA samples of the expected sizes in both species, indicating the occurrence of genuine sRNAs, and putative miRNA-like sRNAs (milRNAS) were identified with prediction software. F. fujikuroi carries at least one transcriptionally expressed Ty1/copia-like retrotransposable element, in which sRNAs were found in both sense and antisense DNA strands, while in F. oxysporum skippy-like elements also show sRNA formation. The finding of sRNA in these mobile elements indicates an active sRNA-based RNAi pathway. Targeted deletion of dcl2, the only F. fujikuroi Dicer gene with significant expression under the conditions tested, did not produce appreciable phenotypic or transcriptomic alterations.

Unveiling heterogeneity in MSCs: exploring marker-based strategies for defining MSC subpopulations

Mesenchymal stem/stromal cells (MSCs) represent a heterogeneous cell population distributed throughout various tissues, demonstrating remarkable adaptability to microenvironmental cues and holding immense promise for disease treatment. However, the inherent diversity within MSCs often leads to variability in therapeutic outcomes, posing challenges for clinical applications. To address this heterogeneity, purification of MSC subpopulations through marker-based isolation has emerged as a promising approach to ensure consistent therapeutic efficacy. In this review, we discussed the reported markers of MSCs, encompassing those developed through candidate marker strategies and high-throughput approaches, with the aim of explore viable strategies for addressing the heterogeneity of MSCs and illuminate prospective research directions in this field.

Selective Capture and Manipulation of DNA through Double Charged Nanopores

In the past few decades, nanometer-scale pores have been employed as powerful tools for sensing biological molecules. Owing to its unique structure and properties, solid-state nanopores provide interesting opportunities for the development of DNA sequencing technology. Controlling DNA translocation in nanopores is an important means of improving the accuracy of sequencing. Here we present a proof of principle study of accelerating DNA captured across targeted graphene nanopores using surface charge density and find the intrinsic mechanism of the combination of electroosmotic flow induced by charges of nanopore and electrostatic attraction/repulsion between the nanopore and ssDNA. The theoretical study performed here provides a new means for controlling DNA transport dynamics and makes better and cheaper application of graphene in molecular sequencing.

Proteogenomic Gene Structure Validation in the Pineapple Genome

MD2 pineapple (Ananas comosus) is the second most important tropical crop that preserves crassulacean acid metabolism (CAM), which has high water-use efficiency and is fast becoming the most consumed fresh fruit worldwide. Despite the significance of environmental efficiency and popularity, until very recently, its genome sequence has not been determined and a high-quality annotated proteome has not been available. Here, we have undertaken a pilot proteogenomic study, analyzing the proteome of MD2 pineapple leaves using liquid chromatography-mass spectrometry (LC-MS/MS), which validates 1781 predicted proteins in the annotated F153 (V3) genome. In addition, a further 603 peptide identifications are found that map exclusively to an independent MD2 transcriptome-derived database but are not found in the standard F153 (V3) annotated proteome. Peptide identifications derived from these MD2 transcripts are also cross-referenced to a more recent and complete MD2 genome annotation, resulting in 402 nonoverlapping peptides, which in turn support 30 high-quality gene candidates novel to both pineapple genomes. Many of the validated F153 (V3) genes are also supported by an independent proteomics data set collected for an ornamental pineapple variety. The contigs and peptides have been mapped to the current F153 genome build and are available as bed files to display a custom gene track on the Ensembl Plants region viewer. These analyses add to the knowledge of experimentally validated pineapple genes and demonstrate the utility of transcript-derived proteomics to discover both novel genes and genetic structure in a plant genome, adding value to its annotation.

scPRAM accurately predicts single-cell gene expression perturbation response based on attention mechanism

MOTIVATION

With the rapid advancement of single-cell sequencing technology, it becomes gradually possible to delve into the cellular responses to various external perturbations at the gene expression level. However, obtaining perturbed samples in certain scenarios may be considerably challenging, and the substantial costs associated with sequencing also curtail the feasibility of large-scale experimentation. A repertoire of methodologies has been employed for forecasting perturbative responses in single-cell gene expression. However, existing methods primarily focus on the average response of a specific cell type to perturbation, overlooking the single-cell specificity of perturbation responses and a more comprehensive prediction of the entire perturbation response distribution.

RESULTS

Here, we present scPRAM, a method for predicting perturbation responses in single-cell gene expression based on attention mechanisms. Leveraging variational autoencoders and optimal transport, scPRAM aligns cell states before and after perturbation, followed by accurate prediction of gene expression responses to perturbations for unseen cell types through attention mechanisms. Experiments on multiple real perturbation datasets involving drug treatments and bacterial infections demonstrate that scPRAM attains heightened accuracy in perturbation prediction across cell types, species, and individuals, surpassing existing methodologies. Furthermore, scPRAM demonstrates outstanding capability in identifying differentially expressed genes under perturbation, capturing heterogeneity in perturbation responses across species, and maintaining stability in the presence of data noise and sample size variations.

AVAILABILITY AND IMPLEMENTATION

https://github.com/jiang-q19/scPRAM and https://doi.org/10.5281/zenodo.10935038.

Are cereal grasses a single genetic system?

In 1993, a passionate and provocative call to arms urged cereal researchers to consider the taxon they study as a single genetic system and collaborate with each other. Since then, that group of scientists has seen their discipline blossom. In an attempt to understand what unity of genetic systems means and how the notion was borne out by later research, we survey the progress and prospects of cereal genomics: sequence assemblies, population-scale sequencing, resistance gene cloning and domestication genetics. Gene order may not be as extraordinarily well conserved in the grasses as once thought. Still, several recurring themes have emerged. The same ancestral molecular pathways defining plant architecture have been co-opted in the evolution of different cereal crops. Such genetic convergence as much as cross-fertilization of ideas between cereal geneticists has led to a rich harvest of genes that, it is hoped, will lead to improved varieties.

Paving the path for implementation of clinical genomic sequencing globally: Are we ready?

Despite the emerging evidence in recent years, successful implementation of clinical genomic sequencing (CGS) remains limited and is challenged by a range of barriers. These include a lack of standardized practices, limited economic assessments for specific indications, limited meaningful patient engagement in health policy decision-making, and the associated costs and resource demand for implementation. Although CGS is gradually becoming more available and accessible worldwide, large variations and disparities remain, and reflections on the lessons learned for successful implementation are sparse. In this commentary, members of the Global Economics and Evaluation of Clinical Genomics Sequencing Working Group (GEECS) describe the global landscape of CGS in the context of health economics and policy and propose evidence-based solutions to address existing and future barriers to CGS implementation. The topics discussed are reflected as two overarching themes: (1) system readiness for CGS and (2) evidence, assessments, and approval processes. These themes highlight the need for health economics, public health, and infrastructure and operational considerations; a robust patient- and family-centered evidence base on CGS outcomes; and a comprehensive, collaborative, interdisciplinary approach.

Genetic insights into agronomic and morphological traits of drug-type cannabis revealed by genome-wide association studies

Cannabis sativa L., previously concealed by prohibition, is now a versatile and promising plant, thanks to recent legalization, opening doors for medical research and industry growth. However, years of prohibition have left the Cannabis research community lagging behind in understanding Cannabis genetics and trait inheritance compared to other major crops. To address this gap, we conducted a comprehensive genome-wide association study (GWAS) of nine key agronomic and morphological traits, using a panel of 176 drug-type Cannabis accessions from the Canadian legal market. Utilizing high-density genotyping-by-sequencing (HD-GBS), we successfully generated dense genotyping data in Cannabis, resulting in a catalog of 800 K genetic variants, of which 282 K common variants were retained for GWAS analysis. Through GWAS analysis, we identified 18 markers significantly associated with agronomic and morphological traits. Several identified markers exert a substantial phenotypic impact, guided us to putative candidate genes that reside in high linkage-disequilibrium (LD) with the markers. These findings lay a solid foundation for an innovative cannabis research, leveraging genetic markers to inform breeding programs aimed at meeting diverse needs in the industry.

Integrated analysis of single-cell RNA-seq and bulk RNA-seq reveals immune suppression subtypes and establishes a novel signature for determining the prognosis in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer with lower survival rates. Recent advancements in targeted therapies and immunotherapies targeting immune checkpoints have achieved remarkable success, there is still a large percentage of LUAD that lacks available therapeutic options. Due to tumor heterogeneity, the diagnosis and treatment of LUAD are challenging. Exploring the biology of LUAD and identifying new biomarker and therapeutic targets options are essential.

METHOD

We performed single-cell RNA sequencing (scRNA-seq) of 6 paired primary and adjacent LUAD tissues, and integrative omics analysis of the scRNA-seq, bulk RNA-seq and whole-exome sequencing data revealed molecular subtype characteristics. Our experimental results confirm that CDC25C gene can serve as a potential marker for poor prognosis in LUAD.

RESULTS

We investigated aberrant gene expression in diverse cell types in LUAD via the scRNA-seq data. Moreover, multi-omics clustering revealed four subgroups defined by transcriptional profile and molecular subtype 4 (MS4) with poor survival probability, and immune cell infiltration signatures revealed that MS4 tended to be the immunosuppressive subtype. Our study revealed that the CDC25C gene can be a distinct prognostic biomarker that indicates immune infiltration levels and response to immunotherapy in LUAD patients. Our experimental results concluded that CDC25C expression affects lung cancer cell invasion and migration, might play a key role in regulating Epithelial-Mesenchymal Transition (EMT) pathways.

CONCLUSIONS

Our multi-omics result revealed a comprehensive set of molecular attributes associated with prognosis-related genes in LUAD at the cellular and tissue level. Identification of a subtype of immunosuppressive TME and prognostic signature for LUAD. We identified the cell cycle regulation gene CDC25C affects lung cancer cell invasion and migration, which can be used as a potential biomarker for LUAD.