Influencing factors and population attributable risk percent of low back pain in automobile assemblers / 中国职业医学

Objective: To investigate the influencing factors and population attributable risk percent (PAR%) of low back pain in automobile assemblers. Methods: A total of 634 assemblers from 11 automobile manufacturers in Shiyan City, Hubei Province were chosen as research subjects using judgment sampling method. The prevalence of low back pain in the past one year was investigated using Musculoskeletal Disorders Questionnaire. PAR% was used to analyze the contribution of influencing factors to low back pain. Results: The annual prevalence of low back pain was 68.8%. The results of multivariate logistics regression showed that length of service>15 years, high school or secondary college education or above, standing most of the time, sitting most of the time, the proportion of cumulative time of poor posture in work shift time ≥1/8, and bending for insufficient height of working space were the risk factors for low back pain (all P<0.05). The PAR% of the proportion of cumulative time of poor posture in work shift time ≥1/8 was 43.0%, 37.8% for standing most of the time, and 12.8% for bending for insufficient height of working space. Conclusion: The annual prevalence of low back pain was higher in automobile assemblers. The influencing factors included individual factors and occupational factors. The proportion of cumulative time of poor posture in work shift time ≥1/8, standing most of the time and bending for insufficient height of working space should be taken as the priority intervention factors to reduce the prevalence of low back pain among assemblers in this enterprise.

Benchmarking and Assessment of Eight De Novo Genome Assemblers on Viral Next-Generation Sequencing Data, Including the SARS-CoV-2.

Viral genomics has become crucial in clinical diagnostics and ecology, not to mention to stem the COVID-19 pandemic. Whole-genome sequencing (WGS) is pivotal in gaining an improved understanding of viral evolution, genomic epidemiology, infectious outbreaks, pathobiology, clinical management, and vaccine development. Genome assembly is one of the crucial steps in WGS data analyses. A series of different assemblers has been developed with the advent of high-throughput next-generation sequencing (NGS). Various studies have reported the evaluation of these assembly tools on distinct datasets; however, these lack data from viral origin. In this study, we performed a comparative evaluation and benchmarking of eight de novo assemblers: SOAPdenovo, Velvet, assembly by short sequences (ABySS), iterative De Bruijn graph assembler (IDBA), SPAdes, Edena, iterative virus assembler, and VICUNA on the viral NGS data from distinct Illumina (GAIIx, Hiseq, Miseq, and Nextseq) platforms. WGS data of diverse viruses, that is, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), dengue virus 3, human immunodeficiency virus 1, hepatitis B virus, human herpesvirus 8, human papillomavirus 16, rhinovirus A, and West Nile virus, were utilized to assess these assemblers. Performance metrics such as genome fraction recovery, assembly lengths, NG50, N50, contig length, contig numbers, mismatches, and misassemblies were analyzed. Overall, three assemblers, that is, SPAdes, IDBA, and ABySS, performed consistently well, including for genome assembly of SARS-CoV-2. These assembly methods should be considered and recommended for future studies of viruses. The study also suggests that implementing two or more assembly approaches should be considered in viral NGS studies, especially in clinical settings. Taken together, the benchmarking of eight de novo genome assemblers reported in this study can inform future public health and ecology research concerning the viruses, the COVID-19 pandemic, and viral outbreaks.

Accuracy and Completeness of Long Read Metagenomic Assemblies.

Microbes influence the surrounding environment and contribute to human health. Metagenomics can be used as a tool to explore the interactions between microbes. Metagenomic assemblies built using long read nanopore data depend on the read level accuracy. The read level accuracy of nanopore sequencing has made dramatic improvements over the past several years. However, we do not know if the increased read level accuracy allows for faster assemblers to make as accurate metagenomic assemblies as slower assemblers. Here, we present the results of a benchmarking study comparing three commonly used long read assemblers, Flye, Raven, and Redbean. We used a prepared DNA standard of seven bacteria as our input community. We prepared a sequencing library using a VolTRAX V2 and sequenced using a MinION mk1b. We basecalled with Guppy v5.0.7 using the super-accuracy model. We found that increasing read depth benefited each of the assemblers, and nearly complete community member chromosomes were assembled with as little as 10× read depth. Polishing assemblies using Medaka had a predictable improvement in quality. We found Flye to be the most robust across taxa and was the most effective assembler for recovering plasmids. Based on Flye's consistency for chromosomes and increased effectiveness at assembling plasmids, we would recommend using Flye in future metagenomic studies.

High-Quality Genome Assembly of Fusarium oxysporum f. sp. lini.

In the present work, a highly pathogenic isolate of Fusarium oxysporum f. sp. lini, which is the most harmful pathogen affecting flax (Linum usitatissimum L.), was sequenced for the first time. To achieve a high-quality genome assembly, we used the combination of two sequencing platforms - Oxford Nanopore Technologies (MinION system) with long noisy reads and Illumina (HiSeq 2500 instrument) with short accurate reads. Given the quality of DNA is crucial for Nanopore sequencing, we developed the protocol for extraction of pure high-molecular-weight DNA from fungi. Sequencing of DNA extracted using this protocol allowed us to obtain about 85x genome coverage with long (N50 = 29 kb) MinION reads and 30x coverage with 2 × 250 bp HiSeq reads. Several tools were developed for genome assembly; however, they provide different results depending on genome complexity, sequencing data volume, read length and quality. We benchmarked the most requested assemblers (Canu, Flye, Shasta, wtdbg2, and MaSuRCA), Nanopore polishers (Medaka and Racon), and Illumina polishers (Pilon and POLCA) on our sequencing data. The assembly performed with Canu and polished with Medaka and POLCA was considered the most full and accurate. After further elimination of redundant contigs using Purge Haplotigs, we achieved a high-quality genome of F. oxysporum f. sp. lini with a total length of 59 Mb, N50 of 3.3 Mb, and 99.5% completeness according to BUSCO. We also obtained a complete circular mitochondrial genome with a length of 38.7 kb. The achieved assembly expands studies on F. oxysporum and plant-pathogen interaction in flax.

Comparative Evaluation of Genome Assemblers from Long-Read Sequencing for Plants and Crops.

The availability of recent state-of-the-art long-read sequencing technologies has significantly increased the ease and speed of producing high-quality plant genome assemblies. A wide variety of genome-related software tools are now available and they are typically benchmarked using microbial or model eukaryotic genomes such as Arabidopsis and rice. However, many plant species have much larger and more complex genomes than these, and the choice of tools, parameters, and/or strategies that can be used is not always obvious. Thus, we have compared the metrics of assemblies generated by various pipelines to discuss how assembly quality can be affected by two different assembly strategies. First, we focused on optimizing read preprocessing and assembler variables using eight different de novo assemblers on five different Pacific Biosciences long-read datasets of diploid and tetraploid species. Then, we examined a single scaffolding tool (quickmerge) that has been employed for the postprocessing step. We then merged the outputs from multiple assemblies to produce a higher quality consensus assembly. Then, we benchmarked the assemblies for completeness and accuracy (assembly metrics and BUSCO), computer memory, and CPU times. Two lightweight assemblers, Miniasm/Minimap/Racon and WTDBG, were deemed good for novice users because they involved smaller required learning curves and light computational resources. However, two heavyweight tools, CANU and Flye, should be the first choice when the goal is to achieve accurate and complete assemblies. Our results will provide valuable guidance in future plant genome projects and beyond.

MELC Genomics: A Framework for De Novo Genome Assembly.

The development of next-generation sequencing platforms increased substantially the capacity of data generation. In addition, in the past years, the costs for whole genome sequencing have been reduced that made it easier to access this technology. As a result, the storage and analysis of the data generated became a challenge, ushering in the development of bioinformatic tools, such as programs and programming languages, able to store, process, and analyze this huge amount of information. In this article, we present MELC genomics, a framework for genome assembly in a simple and fast workflow.

Assessing the Impact of Assemblers on Virus Detection in a De Novo Metagenomic Analysis Pipeline.

Applying high-throughput sequencing to pathogen discovery is a relatively new field, the objective of which is to find disease-causing agents when little or no background information on disease is available. Key steps in the process are the generation of millions of sequence reads from an infected tissue sample, followed by assembly of these reads into longer, contiguous stretches of nucleotide sequences, and then identification of the contigs by matching them to known databases, such as those stored at GenBank or Ensembl. This technique, that is, de novo metagenomics, is particularly useful when the pathogen is viral and strong discriminatory power can be achieved. However, recently, we found that striking differences in results can be achieved when different assemblers were used. In this study, we test formally the impact of five popular assemblers (MIRA, VELVET, METAVELVET, SPADES, and OMEGA) on the detection of a novel virus and assembly of its whole genome in a data set for which we have confirmed the presence of the virus by empirical laboratory techniques, and compare the overall performance between assemblers. Our results show that if results from only one assembler are considered, biologically important reads can easily be overlooked. The impacts of these results on the field of pathogen discovery are considered.

Primordial Germ Cell Specification and Migration.

Primordial germ cells are the progenitor cells that give rise to the gametes. In some animals, the germline is induced by zygotic transcription factors, whereas in others, primordial germ cell specification occurs via inheritance of maternally provided gene products known as germ plasm. Once specified, the primordial germ cells of some animals must acquire motility and migrate to the gonad in order to survive. In all animals examined, perinuclear structures called germ granules form within germ cells. This review focuses on some of the recent studies, conducted by several groups using diverse systems, from invertebrates to vertebrates, which have provided mechanistic insight into the molecular regulation of germ cell specification and migration.