Genetic Variation Analysis on the Whole Genomic Sequence of a H9N2 Subtype Avian Influenza Virus Isolate

A Objective3 This study was to understand the genetic variation characters of the H9N2 subtype avian influenza virus isolate （A/Chicken/ Hebei/WD/98, abbreviated as WD98） by comparing with other reference strains. I-Method3 Eight complete genes were amplified by RT-PCR and sequenced. The homology and genetic evolution relationship were analyzed between these sequences and that of the seven reference strains. [Result] The whole genomic sequence of WD98 strain was 91.1% -95.8% homologous to that of seven reference strains tested. This isolate shared the highest homology （95.8%） to D/HK/Y280/97 and the lowest homology （91.1% ） to C/Pak/2/99. The HA cleavage site of the WD98 strain was R-S-S-R G, and the 226th amino acid at receptor-binding site was Gin. [ Condmion] WD98 strain belongs to mildly pathogenic avian in- fluenza virus and may not infect human. The genetic relationship is the closest between A/Chicken/Hebei/wD/98 and A/duck/HongKong/Y280/ 97, both of which belong to the sub-line of A/Chicken/Beijing/1/94 in Eurasian line. And A/Chicken/Hebei/WD/98 and A/Chicken/Beijing/1/94 are genetically distant within the same sub-line.

Genomic Sequence Determination of Classical Swine Fever Virus Persistent Infection Strain

Full genomic sequence of a newly isolated persistent infection strain of classical swine fever virus was firstly determined. It was demonstrated by sequence analyses that nucleotides homologies of this strain compared with virulent Shimen and vaccine HCLV were 89.7%and 87.7%, and homologies of amino acids were 94.8%and 93.3%, respectively. The sequencing results primarily suggest a tighter relationship between this persistent infection strain and virulent Shimen strain than vaccine HCLV strain.

The Application of Nicotiana benthamiana as a Transient Expression Host to Clone the Coding Sequences of Plant Genes

Coding sequences (CDS) are commonly used for transient gene expression, in yeast two-hybrid screening, to verify protein interactions and in prokaryotic gene expression studies. CDS are most commonly obtained using complementary DNA (cDNA) derived from messenger RNA (mRNA) extracted from plant tissues and generated by reverse transcription. However, some CDS are difficult to acquire through this process as they are expressed at extremely low levels or have specific spatial and/or temporal expression patterns in vivo. These challenges require the development of alternative CDS cloning technologies. In this study, we found that the genomic intron-containing gene coding sequences (gDNA) from Arabidopsis thaliana, Oryza sativa, Brassica napus, and Glycine max can be correctly transcribed and spliced into mRNA in Nicotiana benthamiana. In contrast, gDNAs from Triticum aestivum and Sorghum bicolor did not function correctly. In transient expression experiments, the target DNA sequence is driven by a constitutive promoter. Theoretically, a sufficient amount of mRNA can be extracted from the N. benthamiana leaves, making it conducive to the cloning of CDS target genes. Our data demonstrate that N. benthamiana can be used as an effective host for the cloning CDS of plant genes.

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.

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.

Computational analysis and prediction for exons of PAC579 genomic sequence

To isolate the novel genes related to human hepatocellular carcinoma (HCC), we sequenced P1-derived artificial chromosome PAC579 (D17S926 locus) mapped in the minimum LOH (loss of heterozygosity) deletion region of chromosome 17p13.3 in HCC, Four novel genes mapped in this genomic sequence area were isolated and cloned by wet-lab experiments, and the exons of these genes were located. 0-60 kb of this genomic sequence including the genes of interest was scanned with five different computational exon prediction programs as well as four splice site recognition programs. After analyzing and comparing the computationally predicted results with the wet-lab experiment results, some potential exons were predicted in the genomic sequence by using these programs.

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.

Complete Nucleotide Sequence of a Newly Avirulent Newcastle Disease Virus Hubei 92(HB92) Strain

A new avirulent, heat-resistance HB92 strain of newcastle Disease Virus (NDV) was acquired from Australia V4 strain. Its complete nucleotides sequence was first determined. The entire genome of NDV HB92 consists of 15 186 nucleotides (GenBank accession no. AY225110). It was demonstrated by sequence analysis that nucleotides homology of HB92 strain with virulent strain ZJ1 were 83.9%, and the homology compared with avirulent vaccine strain La Sota and B1 were 94.0% and 93.5%, respectively. These results might be contributive to the study of the molecular mechanism of evolution of the NDV strain HB92 and to develop the engineered recombinant vaccine. Key words newcastle disease virus - genomic sequence - sequence analysis CLC number S 852. 65 Foundation item: Supported by Hubei Natural Science Foundation (2002AB144)Biography: Pan Zhi-shu(1961-), male, Ph. D, Associate professor, research direction: molecular biology and pathogenesis of eucaryotic viruses.

Isolation and Characterization of SARS-CoV-2 in Kenya

The discovery of Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) in Wuhan, Hubei province, China, in December 2019 raised global health warnings. Quickly, in 2020, the virus crossed borders and infected individuals across the world, evolving into the COVID-19 pandemic. Notably, early signs of the virus’s existence were observed in various countries before the initial outbreak in Wuhan. As of 12th of April, the respiratory disease had infected over 762 million people worldwide, with over 6.8 million deaths recorded. This has led scientists to focus their efforts on understanding the virus to develop effective means to diagnose, treat, prevent, and control this pandemic. One of the areas of focus is the isolation of this virus, which plays a crucial role in understanding the viral dynamics in the laboratory. In this study, we report the isolation and detection of locally circulating SARS-CoV-2 in Kenya. The isolates were cultured on Vero Cercopithecus cell line (CCL-81) cells, RNA extraction was conducted from the supernatants, and reverse transcriptase-polymerase chain reaction (RT-PCR). Genome sequencing was done to profile the strains phylogenetically and identify novel and previously reported mutations. Vero CCL-81 cells were able to support the growth of SARS-CoV-2 in vitro, and mutations were detected from the two isolates sequenced (001 and 002). Genome sequencing revealed the circulation of two isolates that share a close relationship with the Benin isolate with the D614G common mutation identified along the S protein. These virus isolates will be expanded and made available to the Kenya Ministry of Health and other research institutions to advance SARS-CoV-2 research in Kenya and the region.

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.

Complete genome sequences of four isolates of Citrus leaf blotch virus from citrus in China

Citrus leaf blotch virus （CLBV） is a member of the genus Citrivirus, in the family Betaflexiviridae. It has been reported CLBV could infect kiwi, citrus and sweet cherry in China. Of 289 citrus samples from six regions of China, 15 were detected to be infected with CLBV in this study. The complete genome of four isolates of CLBV was obtained from Reikou in Sichuan （CLBV-LH）, Yura Wase in Zhejiang （CLBV-YL）, Bingtangcheng in Hunan （CLBV-BT）, Fengjie 72-1 in Chongqing （CLBV- F J）, respectively. While they all represented 8 747 nucleotides in monopartite size, excluding the poly（A） tail, each of the isolates coded three open reading frames （ORFs）. Identity of the four isolates ranged from 98.9 to 99.8% to each other and from 96.8 to 98.1% to the citrus references in GenBank by multiple alignment of genomes. A phylogenetic tree based on the genome sequences of available CLBV isolates indicated that the four isolates were clustered together, suggesting that CLBV isolates from citrus in China did not have obvious variation. This is the first report of the complete nucleotide sequences of CLBV isolates infecting citrus in China.

Complete genome sequence and proteomic analysis of a thermophilic bacteriophage BV1

Viruses of thermophiles are of great interest due to their roles in gene transfer, global geochemical cycle and evolution of life on earth. However, the thermophilic bacteriophages have not been studied extensively. In this investigation, a typical bacteriophage BV1 was obtained from a thermophilic bacterium Geobacillus sp. 6k512, which was isolated from an inshore hot spring in Xiamen of China. The BV1 contained a double-stranded linear DNA of 35 055 bp, which encodes 54 open reading frames （ORFs）. Interestingly, eight of the 54 BV1 ORFs shared sequence similarities to genes from human disease-relevant bacteria. Seven proteins of the purified BV1 virions were identified by proteomic analysis. Determination of BV1 functional genomics would facilitate the better understanding of the mechanism for virus-thermophile interaction.

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.

Complete genome of Cobetia marina JCM 21022T and phylogenomic analysis of the family Halomonadaceae

Cobetia marina is a model proteobacteria in researches on marine biofouling. Its taxonomic nomenclature has been revised many times over the past few decades. ~To better understand the role of the surface-associated lifestyle of C. marina and the phylogeny of the family Halomonadaceae, we sequenced the entire genome of C. marina JCM 21022 ~T using single molecule real-time sequencing technology(SMR^T) and performed comparative genomics and phylogenomics analyses. ~The circular chromosome was 4 176 300 bp with an average GC content of 62.44% and contained 3 611 predicted coding sequences, 72 t RNA genes, and 21 r RNA genes. ~The C. marina JCM 21022 ~T genome contained a set of crucial genes involved in surface colonization processes. ~The comparative genome analysis indicated the significant diff erences between C. marina JCM 21022 ~T and Cobetia amphilecti KMM 296(formerly named C. marina KMM 296) resulted from sequence insertions or deletions and chromosomal recombination. Despite these diff erences, pan and core genome analysis showed similar gene functions between the two strains. ~The phylogenomic study of the family Halomonadaceae is reported here for the first time. We found that the relationships were well resolved among every genera tested, including Chromohalobacter, Halomonas, Cobetia, Kushneria, Zymobacter, and Halotalea.

Complete nucleotide sequences of two isolates of Cherry virus A from sweet cherry in China

Cherry virus A（CVA） is a member of the genusCapilovirus, in the familyBetalfexiviridae. The infection rate of CVA was high in sweet cherry in China. We determined the complete nucleotide sequences of two isolates of CVA from Tai’an, Shan-dong Province, China using high ifdelity PCR enzymes and speciifc primer pairs for amplifying long fragments in RT-PCR and RACE. The ful-length sequences from isolates ChTA11 and ChTA12 are both 7382 nucleotide （nt） long, excluding the poly（A） tail, encode two open reading frames （ORFs） and have similar genome organization to the two isolates in Gen-Bank. The complete nucleotide sequence of ChTA11 is 98.2 and 81.2% nt identity to the isolates from Germany and India in GenBank, respectively, and the ChTA12 isolate is 98.2 and 81.0% similar. Analysis of the nucleotide and amino acid sequences showed that the domain of unknown function （DUF1717） is more variable compared with other domains. This is the ifrst report of the complete nucleotide sequences of CVA isolates infecting sweet cherry in China.

The complete genome sequence of Citrus vein enation virus from China

The complete nucleotide sequence of an isolate of Citrus vein enation virus（CVEV-XZG） from China has been determined for the first time. The genome consisted of 5 983 nucleotides, coding for five open reading frames（ORFs）, had a similar genomic organization features with Pea enation mosaic virus（PEMV）. Nucleotide and deduced amino acid sequence identity of the five ORFs compared to isolate CVEV VE-1 range from 97.1 to 99.0% and 97.4 to 100.0%, these values compared to isolate PEMV-1 range from 45.2 to 51.6% and 31.1 to 45.2%. Phylogenetic analysis based on the complete genome sequence showed that the isolate CVEV-XZG had close relationship with Pea enation mosaic virus. The results supports CVEV may be a new member of genus Enamovirus. The full sequence of CVEV-XZG presented here may serve as a basis for future study of CVEV in China.

Complete Genome Sequence of Mycoplasma ovipneumoniae Strain NM2010, Which Was Isolated from a Sheep in China

Mycoplasma ovipneumoniae, a kind of mycoplasma bacteria, commonly infects the respiratory tract causing respiratory disease in sheep and goats worldwide. Here, the complete genome sequence of M. ovipneumoniae strain NM2010 isolated from a sheep in China was reported for the ifrst time.

Genomics of pancreatic ductal adenocarcinoma

Pancreatic cancer is one of the worst prognostic cancers because of the late diagnosis and the absence of effective treatment. Within all subtypes of this disease, ductal adenocarcinoma has the shortest survival time. In recent years,global genomics profiling allowed the identification of hundreds of genes that are perturbed in pancreatic cancer. The integration of different omics sources in the study of pancreatic cancer has revealed several molecular mechanisms, indicating the complex history of its development. However, validation of these genes as biomarkers for early diagnosis, prognosis or treatment efficacy is still incomplete but should lead to new approaches for the treatment of the disease in the future.

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.