To Analyze the Sensitivity of RT-PCR Assays Employing S Gene Target Failure with Whole Genome Sequencing Data during Third Wave by SARS-CoV-2 Omicron Variant

Introduction: Omicron is a highly divergent variant of concern (VOCs) of a severe acute respiratory syndrome SARS-CoV-2. It carries a high number of mutations in its spike protein hence;it is more transmissible in the community by immune evasion mechanisms. Due to mutation within S gene, most Omicron variants have reported S gene target failure (SGTF) with some commercially available PCR kits. Such diagnostic features can be used as markers to screen Omicron. However, Whole Genome Sequencing (WGS) is the only gold standard approach to confirm novel microorganisms at genetically level as similar mutations can also be found in other variants that are circulating at low frequencies worldwide. This Retrospective study is aimed to assess RT-PCR sensitivity in the detection of S gene target failure in comparison with whole genome sequencing to detect variants of Omicron. Methods: We have analysed retrospective data of SARS-CoV-2 positive RT-PCR samples for S gene target failure (SGTF) with TaqPath COVID-19 RT-PCR Combo Kit (ThermoFisher) and combined with sequencing technologies to study the emerged pattern of SARS-CoV-2 variants during third wave at the tertiary care centre, Surat. Results: From the first day of December 2021 till the end of February 2022, a total of 321,803 diagnostic RT-PCR tests for SARS-CoV-2 were performed, of which 20,566 positive cases were reported at our tertiary care centre with an average cumulative positivity of 6.39% over a period of three months. In the month of December 21 samples characterized by the SGTF (70/129) were suggestive of being infected by the Omicron variant and identified as Omicron (B.1.1.529 lineage) when sequence. In the month of January, we analysed a subset of samples (n = 618) with SGTF (24%) and without SGTF (76%) with Ct values Conclusions: During the COVID-19 pandemic, it took almost more than 15 days to diagnose infection and identify pathogen by sequencing technology. In contrast to that molecular assay provided quick identification with the help of SGTF phenomenon within 5 hours of duration. This strategy helps scientists and health policymakers for the quick isolation and identification of clusters. That ultimately results in a decreased transmission of pathogen among the community.

Safety evaluation and whole genome sequencing for revealing the ability of Penicillium oxalicum WX-209 to safely and effectively degrade citrus segments

The microbial potential of Penicillium has received critical attention.The present research aimed to elucidate the efficacy of crude enzyme secreted from Penicillium oxalicum WX-209 in degrading citrus segments and evaluate the safety of the process.Results showed that citrus segment membranes gradually dissolved after treatment with the crude enzyme solution,indicating good degradation capability.No significant differences in body weight,food ingestion rate,hematology,blood biochemistry,and weight changes of different organs were found between the enzyme intake and control groups.Serial experiments showed that the crude enzyme had high biological safety.Moreover,the whole genome of P.oxalicum WX-209 was sequenced by PacBio and Illumina platforms.Twenty-five scaffolds were assembled to generate 36 Mbp size of genome sequence comprising 11369 predicted genes modeled with a GC content of 48.33%.A total of 592 genes were annotated to encode enzymes related to carbohydrates,and some degradation enzyme genes were identified in strain P.oxalicum WX-209.

Genome sequencing provides potential strategies for drug discovery and synthesis

Medicinal plants are renowned for their abundant production of secondary metabolites,which exhibit notable pharmacological activities and great potential for drug development.The biosynthesis of secondary metabolites is highly intricate and influenced by various intrinsic and extrinsic factors,resulting in substantial species diversity and content variation.Consequently,precise regulation of secondary metabolite synthesis is of utmost importance.In recent years,genome sequencing has emerged as a valuable tool for investigating the synthesis and regulation of secondary metabolites in medicinal plants,facilitated by the widespread use of high-throughput sequencing technologies.This review highlights the latest advancements in genome sequencing within this field and presents several strategies for studying secondary metabolites.Specifically,the article elucidates how genome sequencing can unravel the pathways for secondary metabolite synthesis in medicinal plants,offering insights into the functions and regulatory mechanisms of participating enzymes.Comparative analyses of plant genomes allow identification of shared pathways of metabolite synthesis among species,thereby providing novel avenues for obtaining cost-effective biosynthetic intermediates.By examining individual genomic variations,genes or gene clusters associated with the synthesis of specific compounds can be discovered,indicating potential targets and directions for drug development and the exploration of alternative compound sources.Moreover,the advent of gene-editing technology has enabled the precise modifications of medicinal plant genomes.Optimization of specific secondary metabolite synthesis pathways becomes thus feasible,enabling the precise editing of target genes to regulate secondary metabolite production within cells.These findings serve as valuable references and lessons for future drug development endeavors,conservation of rare resources,and the exploration of new resources.

Breed identification using breed‑informative SNPs and machine learning based on whole genome sequence data and SNP chip data

Background Breed identification is useful in a variety of biological contexts.Breed identification usually involves two stages,i.e.,detection of breed-informative SNPs and breed assignment.For both stages,there are several methods proposed.However,what is the optimal combination of these methods remain unclear.In this study,using the whole genome sequence data available for 13 cattle breeds from Run 8 of the 1,000 Bull Genomes Project,we compared the combinations of three methods(Delta,FST,and In)for breed-informative SNP detection and five machine learning methods(KNN,SVM,RF,NB,and ANN)for breed assignment with respect to different reference population sizes and difference numbers of most breed-informative SNPs.In addition,we evaluated the accuracy of breed identification using SNP chip data of different densities.Results We found that all combinations performed quite well with identification accuracies over 95%in all scenarios.However,there was no combination which performed the best and robust across all scenarios.We proposed to inte-grate the three breed-informative detection methods,named DFI,and integrate the three machine learning methods,KNN,SVM,and RF,named KSR.We found that the combination of these two integrated methods outperformed the other combinations with accuracies over 99%in most cases and was very robust in all scenarios.The accuracies from using SNP chip data were only slightly lower than that from using sequence data in most cases.Conclusions The current study showed that the combination of DFI and KSR was the optimal strategy.Using sequence data resulted in higher accuracies than using chip data in most cases.However,the differences were gener-ally small.In view of the cost of genotyping,using chip data is also a good option for breed identification.

Improving the accuracy of genomic prediction for meat quality traits using whole genome sequence data in pigs

Background Pork quality can directly affect customer purchase tendency and meat quality traits have become valu-able in modern pork production.However,genetic improvement has been slow due to high phenotyping costs.In this study,whole genome sequence(WGS)data was used to evaluate the prediction accuracy of genomic best linear unbiased prediction(GBLUP)for meat quality in large-scale crossbred commercial pigs.Results We produced WGS data(18,695,907 SNPs and 2,106,902 INDELs exceed quality control)from 1,469 sequenced Duroc×(Landrace×Yorkshire)pigs and developed a reference panel for meat quality including meat color score,marbling score,L*(lightness),a*(redness),and b*(yellowness)of genomic prediction.The prediction accuracy was defined as the Pearson correlation coefficient between adjusted phenotypes and genomic estimated breeding values in the validation population.Using different marker density panels derived from WGS data,accuracy differed substantially among meat quality traits,varied from 0.08 to 0.47.Results showed that MultiBLUP outperform GBLUP and yielded accuracy increases ranging from 17.39%to 75%.We optimized the marker density and found medium-and high-density marker panels are beneficial for the estimation of heritability for meat quality.Moreover,we conducted genotype imputation from 50K chip to WGS level in the same population and found average concord-ance rate to exceed 95%and r^(2)=0.81.Conclusions Overall,estimation of heritability for meat quality traits can benefit from the use of WGS data.This study showed the superiority of using WGS data to genetically improve pork quality in genomic prediction.

Surveillance of emerging SARS-CoV-2 variants by nanopore technology-based genome sequencing

Objective:To surveill emerging variants by nanopore technology-based genome sequencing in different COVID-19 waves in Sri Lanka and to examine the association with the sample characteristics,and vaccination status.Methods:The study analyzed 207 RNA positive swab samples received to sequence laboratory during different waves.The N gene cut-off threshold of less than 30 was considered as the major inclusion criteria.Viral RNA was extracted,and elutes were subjected to nanopore sequencing.All the sequencing data were uploaded in the publicly accessible database,GISAID.Results:The Omicron,Delta and Alpha variants accounted for 58%,22%and 4%of the variants throughout the period.Less than 1%were Kappa variant and 16%of the study samples remained unassigned.Omicron variant was circulated among all age groups and in all the provinces.Ct value and variants assigned percentage was 100%in Ct values of 10-15 while only 45%assigned Ct value over 25.Conclusions:The present study examined the emergence,prevalence,and distribution of SARS-CoV-2 variants locally and has shown that nanopore technology-based genome sequencing enables whole genome sequencing in a low resource setting country.

Genome‑wide DNA methylation and transcriptome analyses reveal the key gene for wool type variation in sheep

Background Wool fibers are valuable materials for textile industry.Typical wool fibers are divided into medullated and non-medullated types,with the former generated from primary wool follicles and the latter by either primary or secondary wool follicles.The medullated wool is a common wool type in the ancestors of fine wool sheep before breeding.The fine wool sheep have a non-medullated coat.However,the critical period determining the type of wool follicles is the embryonic stage,which limits the phenotypic observation and variant contrast,making both selection and studies of wool type variation fairly difficult.Results During the breeding of a modern fine(MF)wool sheep population with multiple-ovulation and embryo transfer technique,we serendipitously discovered lambs with ancestral-like coarse(ALC)wool.Whole-genome rese-quencing confirmed ALC wool lambs as a variant type from the MF wool population.We mapped the significantly associated methylation locus on chromosome 4 by using whole genome bisulfite sequencing signals,and in turn identified the SOSTDC1 gene as exons hypermethylated in ALC wool lambs compare to their half/full sibling MF wool lambs.Transcriptome sequencing found that SOSTDC1 was expressed dozens of times more in ALC wool lamb skin than that of MF and was at the top of all differentially expressed genes.An analogy with the transcriptome of coarse/fine wool breeds revealed that differentially expressed genes and enriched pathways at postnatal lamb stage in ALC/MF were highly similar to those at the embryonic stage in the former.Further experiments validated that the SOSTDC1 gene was specifically highly expressed in the nucleus of the dermal papilla of primary wool follicles.Conclusion In this study,we conducted genome-wide differential methylation site association analysis on differen-tial wool type trait,and located the only CpG locus that strongly associated with primary wool follicle development.Combined with transcriptome analysis,SOSTDC1 was identified as the only gene at this locus that was specifically overexpressed in the primary wool follicle stem cells of ALC wool lamb skin.The discovery of this key gene and its epigenetic regulation contributes to understanding the domestication and breeding of fine wool sheep.

Evaluation of A Single-reaction Method for Whole Genome Sequencing of Influenza A Virus using Next Generation Sequencing

Objective To evaluate a single-reaction genome amplification method, the multisegment reverse transcription-PCR （M-RTPCR）, for its sensitivity to full genome sequencing of influenza A virus, and the ability to differentiate mix-subtype virus, using the next generation sequencing （NGS） platform. Methods Virus genome copy was quantified and seria（iy diluted to different titers, followed by amplification with the M-RTPCR method and sequencing on the NGS platform. Furthermore, we manually mixed two subtype viruses to different titer rate and amplified the mixed virus with the M-RTPCR protocol, followed by whole genome sequencing on the NGS platform. We also used clinical samples to test the method performance. Results The M-RTPCR method obtained complete genome of testing virus at 125 copies/reaction and determined the virus subtype at titer of 25 copies/reaction. Moreover, the two subtypes in the mixed virus could be discriminated, even though these two virus copies differed by 200-fold using this amplification protocol. The sensitivity of this protocol we detected using virus RNA was also confirmed with clinical samples containing Iow-titer virus. Conclusion The M-RTPCR is a robust and sensitive amplification method for whole genome sequencing of influenza A virus using NGS platform.

Identification of candidate genes for drought stress tolerance in rice by the integration of a genetic (QTL) map with the rice genome physical map

Genetic improvement for drought stress tolerance in rice involves the quantitative nature of the trait, which reflects the additive effects of several genetic loci throughout the genome. Yield components and related traits under stressed and well-water conditions were assayed in mapping populations derived from crosses of Azucena×IR64 and Azucena×Bala. To find the candidate rice genes underlying Quantitative Trait Loci (QTL) in these populations, we conducted in silico analysis of a candidate region flanked by the genetic markers RM212 and RM319 on chromosome 1, proximal to the semi-dwarf (sd1) locus. A total of 175 annotated genes were identified from this region. These included 48 genes annotated by functional homology to known genes, 23 pseudogenes, 24 ab initio predicted genes supported by an alignment match to an EST (Expressed sequence tag) of unknown function, and 80 hypothetical genes predicted solely by ab initio means. Among these, 16 candidate genes could potentially be involved in drought stress response.

A Roadmap for Whitefly Genomics Research:Lessons from Previous Insect Genome Projects

Due to evolving molecular and informatics technologies,modern genome sequencing projects have more different characteristics than what most biologists have become accustomed to during the capillary-based sequencing era.In this paper,we explore the characteristics that made past insect genome projects successful and place them in the context of next-generation sequencing.By taking into account the intricacies of whitefly biology and the community,we present a roadmap for whitefly-omics,which focuses on the formation of an international consortium,deployment of informatic platforms and realistic generation of reference sequence data.

Rapid and Accurate Sequencing of Enterovirus Genomes Using MinION Nanopore Sequencer

Objective Knowledge of an enterovirus genome sequence is very important in epidemiological investigation to identify transmission patterns and ascertain the extent of an outbreak. The MinION sequencer is increasingly used to sequence various viral pathogens in many clinical situations because of its long reads, portability, real-time accessibility of sequenced data, and very low initial costs. However, information is lacking on MinION sequencing of enterovirus genomes. Methods In this proof-of-concept study using Enterovirus 71 （EV71） and Coxsackievirus A16 （CA16） strains as examples, we established an amplicon-based whole genome sequencing method using MinION. We explored the accuracy, minimum sequencing time, discrimination and high-throughput sequencing ability of MinION, and compared its performance with Sanger sequencing. Results Within the first minute （min） of sequencing, the accuracy of MinION was 98.5% for the single EV71 strain and 94.12%-97.33% for 10 genetically-related CA16 strains. In as little as 14 min, 99% identity was reached for the single EV71 strain, and in 17 min （on average）, 99% identity was achieved for 10 CA16 strains in a single run. Conclusion MinION is suitable for whole genome sequencing of enteroviruses with sufficient accuracy and fine discrimination and has the potential as a fast, reliable and convenient method for routine use.

Genome-wide mining, characterization, and development of microsatellite markers in Marsupenaeus japonicus by genome survey sequencing

The kuruma prawn, Marsupenaeus japonicus, is one of the most cultivated and consumed species of shrimp. However, very few molecular genetic/genomic resources are publically available for it. Thus, the characterization and distribution of simple sequence repeats(SSRs) remains ambiguous and the use of SSR markers in genomic studies and marker-assisted selection is limited. The goal of this study is to characterize and develop genome-wide SSR markers in M. japonicus by genome survey sequencing for application in comparative genomics and breeding. A total of 326 945 perfect SSRs were identified, among which dinucleotide repeats were the most frequent class(44.08%), followed by mononucleotides(29.67%), trinucleotides(18.96%), tetranucleotides(5.66%), hexanucleotides(1.07%), and pentanucleotides(0.56%). In total, 151 541 SSR loci primers were successfully designed. A subset of 30 SSR primer pairs were synthesized and tested in 42 individuals from a wild population, of which 27 loci(90.0%) were successfully amplified with specific products and 24(80.0%) were polymorphic. For the amplified polymorphic loci, the alleles ranged from 5 to 17(with an average of 9.63), and the average PIC value was 0.796. A total of 58 256 SSR-containing sequences had significant Gene Ontology annotation; these are good functional molecular marker candidates for association studies and comparative genomic analysis. The newly identified SSRs significantly contribute to the M. japonicus genomic resources and will facilitate a number of genetic and genomic studies, including high density linkage mapping, genome-wide association analysis, marker-aided selection, comparative genomics analysis, population genetics, and evolution.

Mutation Prediction for Coronaviruses Using Genome Sequence and Recurrent Neural Networks

The study of viruses and their genetics has been an opportunity as well as a challenge for the scientific community.The recent ongoing SARSCov2(Severe Acute Respiratory Syndrome)pandemic proved the unpreparedness for these situations.Not only the countermeasures for the effect caused by virus need to be tackled but the mutation taking place in the very genome of the virus is needed to be kept in check frequently.One major way to find out more information about such pathogens is by extracting the genetic data of such viruses.Though genetic data of viruses have been cultured and stored as well as isolated in form of their genome sequences,there is still limited methods on what new viruses can be generated in future due to mutation.This research proposes a deep learning model to predict the genome sequences of the SARS-Cov2 virus using only the previous viruses of the coronaviridae family with the help of RNN-LSTM(Recurrent Neural Network-Long ShortTerm Memory)and RNN-GRU(Gated Recurrent Unit)so that in the future,several counter measures can be taken by predicting possible changes in the genome with the help of existing mutations in the virus.After the process of testing the model,the F1-recall came out to be more than 0.95.The mutation detection’s accuracy of both the models come out about 98.5%which shows the capability of the recurrent neural network to predict future changes in the genome of virus.

Sequencing of the Cultivated Tetraploid Cotton Genome-Gossypium hirsutum

Cotton is an important cash crop in the world,and it plays an irreplaceable role in China's national economy.Cultivated upland cotton(Gossypium hirsutum L.) represents 95% of the world's cotton production,but it has a complex allotetraploid genome that contains at least 30000 genes in 2500

Family Competition Pheromone Genetic Algorithm for Comparative Genome Assembly

Genome assembly is a prerequisite step for analyzing next generation sequencing data and also far from being solved. Many assembly tools have been proposed and used extensively. Majority of them aim to assemble sequencing reads into contigs; however, we focus on the assembly of contigs into scaffolds in this paper. This is called scaffolding, which estimates the relative order of the contigs as well as the size of the gaps between these contigs. Pheromone trail-based genetic algorithm （PGA） was previously proposed and had decent performance according to their paper. From our previous study, we found that family competition mechanism in genetic algorithm is able to further improve the results. Therefore, we propose family competition pheromone genetic algorithm （FCPGA） and demonstrate the improvement over PGA.

Current practices and guidelines for clinical next-generation sequencing oncology testing

Next-generation sequencing(NGS) has been rapidly integrated into molecular pathology, dramatically increasing the breadth genomic of information available to oncologists and their patients. This review will explore the ways in which this new technology is currently applied to bolster care for patients with solid tumors and hematological malignancies, focusing on practices and guidelines for assessing the technical validity and clinical utility of DNA variants identified during clinical NGS oncology testing.

An efficient approach for obtaining plant organelle genomes

Plant organelle(plastid and mitochondrial)genomes contain substantial information for plant evolution and adaptation.Therefore,it’s important to reveal plant whole-genome sequences including plastid and mitochondrial genomes.To decode these sequences,it is required to efficiently separate organelle genomic DNA from nucleus genome,which is difficult and laborious.In this study,an efficient procedure was established to obtain plant organelle genomes without extraction of plastid and mitochondria.Organelle DNA was extracted from three materials including Sinapis arvensis var.‘Yeyou 18’,a cytoplasmic male sterile line(Nsa CMS)and its corresponding maintainer line‘Zhongshuang 4’.DNA was sequenced by Roche 454 FLXt and Illumina Miseq platforms.Organelle genomes were assembled using the generated reads and public organelle genome sequences.This research presented a procedure that efficiently assembled organelle genomes and subsequent fill gaps by extending the consensus contig terminals.This method enabled us to assemble plant plastid and mitochondrial genomes simultaneously.The obtained organelle genomes could accelerate understanding of mitochondrial rearrangements and laid a foundation for further study of Sinapis arvensis evolution and sterility gene of Nsa CMS.

Compound Heterozygous PLD1 Variants in Right-Sided Heart Malformations

We report a three-year-old male child who presented with congenital valvular defects,right ventricular malformation,and initial developmental delay.Genome sequencing showed rare deleterious biallelic missense variants in PLD1.In his parents’second pregnancy,echocardiogram at 13 weeks gestation revealed right-sided cardiac malformations resembling the clinical presentation of the family’s first child.Targeted DNA analysis showed that the fetus carried the same biallelic PLD1 variants as their older sibling.This case helps to further delineate the clinical spectrum of PLD1-related defects and highlights the value of both genome sequencing in congenital heart disease and early fetal echocardiography to establish phenotype.

The evolution of cancer genomic medicine in Japan and the role of the National Cancer Center Japan

The journey to implement cancer genomic medicine(CGM)in oncology practice began in the 1980s,which is considered the dawn of genetic and genomic cancer research.At the time,a variety of activating oncogenic alterations and their functional significance were unveiled in cancer cells,which led to the development of molecular targeted therapies in the 2000s and beyond.Although CGM is still a relatively new discipline and it is difficult to predict to what extent CGM will benefit the diverse pool of cancer patients,the National Cancer Center(NCC)of Japan has already contributed considerably to CGM advancement for the conquest of cancer.Looking back at these past achievements of the NCC,we predict that the future of CGM will involve the following:1)A biobank of paired cancerous and non-cancerous tissues and cells from various cancer types and stages will be developed.The quantity and quality of these samples will be compatible with omics analyses.All biobank samples will be linked to longitudinal clinical information.2)New technologies,such as whole-genome sequencing and artificial intelligence,will be introduced and new bioresources for functional and pharmacologic analyses(e.g.,a patient-derived xenograft library)will be systematically deployed.3)Fast and bidirectional translational research(bench-to-bedside and bedside-to-bench)performed by basic researchers and clinical investigators,preferably working alongside each other at the same institution,will be implemented;4)Close collaborations between academia,industry,regulatory bodies,and funding agencies will be established.5)There will be an investment in the other branch of CGM,personalized preventive medicine,based on the individual's genetic predisposition to cancer.

Complete Sequence and Gene Organization of the Mitochondrial Genome of Tokay (Gekko gecko)

Long-PCR amplification, clone and primer-walking sequencing methods were employed in determine the complete sequence of mitochondrial genome of tokay (Gekko gecko). The genome is 16 435 bp in size, contains 13 protein-coding, 2 ribosomal and 22 transfer RNA genes. The mt genome of Gekko is similar to most of the vertebrates in gene components, order, orientation, tRNA structures, low percentage of guanine and high percentage of thymine, and skews of base GC and AT. Base A was preferred at third codon positions for protein genes is similar to amphibians and fishes rather than amnion vertebrates. The standard stop codes (TAA) present only in three protein genes, less than those of most vertebrates. Transfer RNA genes range in length from 63 to 76 nt, their planar structure present characteristic clover leaf, except for tRNA-Cys and tRNA-Ser (AGY) because of lacking the D arm.