Comparison of Burrows-Wheeler Transform-Based Mapping Algorithms Used in High-Throughput Whole-Genome Sequencing: Application to Illumina Data for Livestock Genomes

Genes positively regulated by Mef2c in cortical neurons are enriched for common genetic variation associated with IQ and educational attainment

The myocyte enhancer factor 2 C (MEF2C) gene encodes a transcription factor important for neurogenesis and synapse development and contains common variants associated with intelligence (IQ) and educational attainment (EA). Here, we took gene expression data from the mouse cortex of a Mef2c mouse model with a heterozygous DNA binding-deficient mutation of Mef2c (Mef2c-het) and combined these data with MEF2C ChIP-seq data from cortical neurons and single-cell data from the mouse brain. This enabled us to create a set of genes that were differentially regulated in Mef2c-het mice, represented direct target genes of MEF2C and had elevated in expression in cortical neurons. We found this gene-set to be enriched for genes containing common genetic variation associated with IQ and EA. Genes within this gene-set that were down-regulated, i.e. have reduced expression in Mef2c-het mice versus controls, were specifically significantly enriched for both EA and IQ associated genes. These down-regulated genes were enriched for functionality in the adenylyl cyclase signalling system, which is known to positively regulate synaptic transmission and has been linked to learning and memory. Within the adenylyl cyclase signalling system, three genes regulated by MEF2C, CRHR1, RGS6, and GABRG3, are associated at genome-wide significant levels with IQ and/or EA. Our results indicate that genetic variation in MEF2C and its direct target genes within cortical neurons contribute to variance in cognition within the general population, and the molecular mechanisms involved include the adenylyl cyclase signalling system's role in synaptic function.

Functional mutation, splice, distribution, and divergence analysis of impactful genes associated with heart failure and other cardiovascular diseases

Cardiovascular disease (CVD) is caused by a multitude of complex and largely heritable conditions. Identifying key genes and understanding their susceptibility to CVD in the human genome can assist in early diagnosis and personalized treatment of the relevant patients. Heart failure (HF) is among those CVD phenotypes that has a high rate of mortality. In this study, we investigated genes primarily associated with HF and other CVDs. Achieving the goals of this study, we built a cohort of thirty-five consented patients, and sequenced their serum-based samples. We have generated and processed whole genome sequence (WGS) data, and performed functional mutation, splice, variant distribution, and divergence analysis to understand the relationships between each mutation type and its impact. Our variant and prevalence analysis found FLNA, CST3, LGALS3, and HBA1 linked to many enrichment pathways. Functional mutation analysis uncovered ACE, MME, LGALS3, NR3C2, PIK3C2A, CALD1, TEK, and TRPV1 to be notable and potentially significant genes. We discovered intron, 5' Flank, 3' UTR, and 3' Flank mutations to be the most common among HF and other CVD genes. Missense mutations were less common among HF and other CVD genes but had more of a functional impact. We reported HBA1, FADD, NPPC, ADRB2, ADBR1, MYH6, and PLN to be consequential based on our divergence analysis.

Citric Acid in Rice Root Exudates Enhanced the Colonization and Plant Growth-Promoting Ability of Bacillus altitudinis LZP02

Exploration of the underlying mechanisms of plant-microbe interactions is very important. In the present study, citric acid in the root exudates of rice significantly enhanced the colonization of Bacillus altitudinis LZP02 in the rhizosphere. According to the results of transcriptome and reverse transcription-quantitative PCR or analyses, citric acid increased the expression of several genes involved in bacterial chemotaxis and biofilm formation in B. altitudinis LZP02. In addition, citric acid also increased the expression of several genes associated with S-adenosylmethionine biosynthesis and metabolism. Interestingly, the secretion of citric acid by rice roots could be increased by inoculation with B. altitudinis LZP02. The result indicated that citric acid might be a vital signal in the interaction between rice and B. altitudinis LZP02. Further verification showed that citric acid enhanced the plant growth-promoting ability of B. altitudinis LZP02. IMPORTANCE In a previous study, the mechanism by which citric acid in rice root exudates enhanced the colonization of Bacillus altitudinis LZP02 was discovered. The present study verified that citric acid increased the recruitment and rice growth-promoting ability of B. altitudinis LZP02. These findings serve as an interesting case for explaining the underlying mechanisms of plant-microbe interactions. Henceforth, citric acid and B. altitudinis LZP02 could be exploited for the development of sustainable agronomy.

Multi-omics analyses provide insight into the biosynthesis pathways of fucoxanthin in Isochrysis galbana

Isochrysis galbana is considered an ideal bait for functional foods and nutraceuticals of humans because of its high fucoxanthin (Fx) content. However, multi-omics analysis of the regulation networks for Fx biosynthesis in I. galbana has not been reported. In this study, we report a high-quality genome sequence of I. galbana LG007, which has a 92.73 Mb genome size, with a contig N50 of 6.99 Mb and 14,900 protein-coding genes. Phylogenomic inferences confirmed the monophyly of Haptophyta, with I. galbana sister to Emiliania huxleyi and Chrysochromulina tobinii. Evolutionary analysis revealed an estimated divergence time between I. galbana and E. huxleyi of ∼ 133 million years ago (Mya). Gene family analysis indicated that lipid metabolism-related genes exhibited significant expansion, including IgPLMT, IgOAR1, and IgDEGS1. Metabolome analysis showed that the content of carotenoids in I. galbana cultured under green light for 7 days was higher than that of white light, and β-carotene was the main carotenoid, accounting for 79.09% of the total carotenoids. Comprehensive analysis of multi-omics analysis revealed that β-carotene, antheraxanthin, zeaxanthin, and Fx content was increased by green light induction, which was significantly correlated with the expression of IgMYB98, IgZDS, IgPDS, IgLHCX2, IgZEP, IgLCYb, and IgNSY. These findings contribute to understanding Fx biosynthesis and its regulation, providing a valuable reference for food and pharmaceutical applications.

KSHV RTA antagonizes SMC5/6 complex-induced viral chromatin compaction by hijacking the ubiquitin-proteasome system

Kaposi’s sarcoma-associated herpesvirus (KSHV) is a double-stranded DNA virus with the capacity to establish life-long latent infection. During latent infection, the viral genome persists as a circular episome that associates with cellular histones and exists as a nonintegrated minichromosome in the nucleus of infected cells. Chromatin structure and epigenetic programming are required for the proper control of viral gene expression and stable maintenance of viral DNA. However, there is still limited knowledge regarding how the host regulates the chromatin structure and maintenance of episomal DNA. Here, we found that the cellular protein structural maintenance of chromosome (SMC) complex SMC5/6 recognizes and associates with the KSHV genome to inhibit its replication. The SMC5/6 complex can bind to the KSHV genome and suppress KSHV gene transcription by condensing the viral chromatin and creating a repressive chromatin structure. Correspondingly, KSHV employs an antagonistic strategy by utilizing the viral protein RTA to degrade the SMC5/6 complex and antagonize the inhibitory effect of this complex on viral gene transcription. Interestingly, this antagonistic mechanism of RTA is evolutionarily conserved among γ-herpesviruses. Our work suggests that the SMC5/6 complex is a new host factor that restricts KSHV replication.

KSHV can establish life-long latent infection. During latency, the viral genome is maintained as an extrachromosomal episome in the infected cells. We demonstrated that the host protein SMC5/6 complex associates with the KSHV genome and results in direct transcriptional inhibition by creating a transcriptionally repressive chromatin structure of the viral genome. RTA, the master switch protein of KSHV, can hijack the ubiquitin-proteasome system to degrade the SMC5/6 complex to antagonize its inhibitory effect on viral gene transcription. Interestingly, this function of RTA is evolutionarily conserved among γ-herpesviruses.

Benchmarking DNA Methylation Analysis of 14 Alignment Algorithms for Whole Genome Bisulfite Sequencing in Mammals

Whole genome bisulfite sequencing (WGBS) is an essential technique for methylome studies. Although a series of tools have been developed to overcome the mapping challenges caused by bisulfite treatment, the latest available tools have not been evaluated on the performance of reads mapping as well as on biological insights in multiple mammals. Herein, based on the real and simulated WGBS data of 14.77 billion reads, we undertook 936 mappings to benchmark and evaluate 14 wildly utilized alignment algorithms from reads mapping to biological interpretation in humans, cattle and pigs: Bwa-meth, BSBolt, BSMAP, Walt, Abismal, Batmeth2, Hisat_3n, Hisat_3n_repeat, Bismark-bwt2-e2e, Bismark-his2, BSSeeker2-bwt, BSSeeker2-soap2, BSSeeker2-bwt2-e2e and BSSeeker2-bwt2-local. Specifically, Bwa-meth, BSBolt, BSMAP, Bismark-bwt2-e2e and Walt exhibited higher uniquely mapped reads, mapped precision, recall and F1 score than other nine alignment algorithms, and the influences of distinct alignment algorithms on the methylomes varied considerably at the numbers and methylation levels of CpG sites, the calling of differentially methylated CpGs (DMCs) and regions (DMRs). Moreover, we reported that BSMAP showed the highest accuracy at the detection of CpG coordinates and methylation levels, the calling of DMCs, DMRs, DMR-related genes and signaling pathways. These results suggested that careful selection of algorithms to profile the genome-wide DNA methylation is required, and our works provided investigators with useful information on the choice of alignment algorithms to effectively improve the DNA methylation detection accuracy in mammals.

Functional Genomics Identified Novel Genes Involved in Growth at Low Temperatures in Listeria monocytogenes

Listeria monocytogenes (Lm) is a foodborne pathogen that can cause severe human illness. Standard control measures for restricting bacterial growth, such as refrigeration, are often inadequate as Lm grows well at low temperatures. To identify genes involved in growth at low temperatures, a powerful functional genomics method Tn-seq was performed in this study. This genome-wide screening comprehensively identified the known and novel genetic determinants involved in low-temperature growth. A novel gene lmo1366, encoding rRNA methyltransferase, was identified to play an essential role in Lm growth at 16°C. In contrast, the inactivation of lmo2301, a gene encoding the terminase of phage A118, significantly enhanced the growth of Lm at 16°C. The deletion of lmo1366 or lmo2301 resulted in cell morphology alterations and impaired the growth rate in milk and other conditions at low temperatures. Transcriptomic analysis revealed that the Δlmo1366 and Δlmo2301 mutants exhibited altered transcriptional patterns compared to the wild-type strain at 16°C with significant differences in genes involved in ribosome structural stability and function, and membrane biogenesis, respectively. This work uncovered novel genetic determinants involved in Lm growth at 16°C, which could lead to a better understanding of how bacteria survive and multiply at low temperatures. Furthermore, these findings could potentially contribute to developing novel antibacterial strategies under low-temperature conditions.

IMPORTANCEListeria monocytogenes is a Gram-positive pathogen that contributes to foodborne outbreaks due to its ability to survive at low temperatures. However, the genetic determinants of Lm involved in growth at low temperatures have not been fully defined. Here, the genetic determinants involved in the low-temperature growth of Lm were comprehensively identified on a genome-wide scale by Tn-seq. The gene lmo1366, encoding rRNA methyltransferase, was identified essential for growth under low-temperature conditions. On the other hand, the gene lmo2301, encoding terminase of phage A118, plays a negative role in bacterial growth at low temperatures. The transcriptomic analysis revealed the potential mechanisms. These findings lead to a better understanding of how bacteria survive and multiply at low temperatures and could provide unique targets for novel antibacterial strategies under low-temperature conditions.

Integrative Comparison of Burrows-Wheeler Transform-Based Mapping Algorithm with de Bruijn Graph for Identification of Lung/Liver Cancer-Specific Gene

Cancers of the lung and liver are the top 10 leading causes of cancer death worldwide. Thus, it is essential to identify the genes specifically expressed in these two cancer types to develop new therapeutics. Although many messenger RNA (mRNA) sequencing data related to these cancer cells are available due to the advancement of next-generation sequencing (NGS) technologies, optimized data processing methods need to be developed to identify the novel cancer-specific genes. Here, we conducted an analytical comparison between Bowtie2, a Burrows-Wheeler transform-based alignment tool, and Kallisto, which adopts pseudo alignment based on a transcriptome de Bruijn graph using mRNA sequencing data on normal cells and lung/liver cancer tissues. Before using cancer data, simulated mRNA sequencing reads were generated, and the high Transcripts Per Million (TPM) values were compared. mRNA sequencing reads data on lung/liver cancer cells were also extracted and quantified. While Kallisto could directly give the output in TPM values, Bowtie2 provided the counts. Thus, TPM values were calculated by processing the Sequence Alignment Map (SAM) file in R using package Rsubread and subsequently in python. The analysis of the simulated sequencing data revealed that Kallisto could detect more transcripts and had a higher overlap over Bowtie2. The evaluation of these two data processing methods using the known lung cancer biomarkers concludes that in standard settings without any dedicated quality control, Kallisto is more effective at producing faster and more accurate results than Bowtie2. Such conclusions were also drawn and confirmed with the known biomarkers specific to liver cancer.

Transcriptional dynamics of the circulating chicken primordial germ cells revealing key genes in cell adhesion and proliferation prior to gonad colonization

Primordial germ cells (PGCs), precursors to sperms and oocytes, are responsible for the transfer of genetic information to the next generation. The PGCs arise far away from the developing gonad and thus have to migrate across the embryo to reach their site of function. The migration of PGCs from extraembryonic regions to the genital ridges is accomplished through distinct routes among different species. In particular, the birds PGCs utilized the developing circulation system to travel long distance before settling within the gonad. This study screened the transcriptome profile of chicken PGCs isolated from the bloodstream and the genital ridges to identify the cell intrinsic signals that could guide the unique migration path through circulation. We found cell adhesion and extracellular matrix (ECM) associated pathways were highly enriched in the PGCs from blood but not gonads. The platelet-derived growth factor receptors (PDGFRA and PDGFRB) were downregulated during gonad colonization and knockdown of either PDGFRA or PDGFRB inhibit the proliferation of blood PGCs. Furthermore, the migration of blood PGCs was impaired by the suppression of PDGFRA but not PDGFRB. Hence, the chicken PGCs show dynamic transcriptional remodeling during the blood-to-gonad migration and colonization. The free-floating PGCs in the circulation already express genes associated with cell-cell and cell-ECM interactions and therefore prepare for gonadal colonization.

JWES: a new pipeline for whole genome/exome sequence data processing, management, and gene-variant discovery, annotation, prediction, and genotyping

Whole genome and exome sequencing (WGS/WES) are the most popular next‐generation sequencing (NGS) methodologies and are at present often used to detect rare and common genetic variants of clinical significance. We emphasize that automated sequence data processing, management, and visualization should be an indispensable component of modern WGS and WES data analysis for sequence assembly, variant detection (SNPs, SVs), imputation, and resolution of haplotypes. In this manuscript, we present a newly developed findable, accessible, interoperable, and reusable (FAIR) bioinformatics‐genomics pipeline Java based Whole Genome/Exome Sequence Data Processing Pipeline (JWES) for efficient variant discovery and interpretation, and big data modeling and visualization. JWES is a cross‐platform, user‐friendly, product line application, that entails three modules: (a) data processing, (b) storage, and (c) visualization. The data processing module performs a series of different tasks for variant calling, the data storage module efficiently manages high‐volume gene‐variant data, and the data visualization module supports variant data interpretation with Circos graphs. The performance of JWES was tested and validated in‐house with different experiments, using Microsoft Windows, macOS Big Sur, and UNIX operating systems. JWES is an open‐source and freely available pipeline, allowing scientists to take full advantage of all the computing resources available, without requiring much computer science knowledge. We have successfully applied JWES for processing, management, and gene‐variant discovery, annotation, prediction, and genotyping of WGS and WES data to analyze variable complex disorders. In summary, we report the performance of JWES with some reproducible case studies, using open access and in‐house generated, high‐quality datasets.

Meanders as a scaling motif for understanding of floodplain soil microbiome and biogeochemical potential at the watershed scale

BACKGROUND

Biogeochemical exports from watersheds are modulated by the activity of microorganisms that function over micron scales. Here, we tested the hypothesis that meander-bound regions share a core microbiome and exhibit patterns of metabolic potential that broadly predict biogeochemical processes in floodplain soils along a river corridor.

RESULTS

We intensively sampled the microbiomes of floodplain soils located in the upper, middle, and lower reaches of the East River, Colorado. Despite the very high microbial diversity and complexity of the soils, we reconstructed 248 quality draft genomes representative of subspecies. Approximately one third of these bacterial subspecies was detected across all three locations at similar abundance levels, and ~ 15% of species were detected in two consecutive years. Within the meander-bound floodplains, we did not detect systematic patterns of gene abundance based on sampling position relative to the river. However, across meanders, we identified a core floodplain microbiome that is enriched in capacities for aerobic respiration, aerobic CO oxidation, and thiosulfate oxidation with the formation of elemental sulfur. Given this, we conducted a transcriptomic analysis of the middle floodplain. In contrast to predictions made based on the prominence of gene inventories, the most highly transcribed genes were relatively rare amoCAB and nxrAB (for nitrification) genes, followed by genes involved in methanol and formate oxidation, and nitrogen and CO₂ fixation. Within all three meanders, low soil organic carbon correlated with high activity of genes involved in methanol, formate, sulfide, hydrogen, and ammonia oxidation, nitrite oxidoreduction, and nitrate and nitrite reduction. Overall, the results emphasize the importance of sulfur, one-carbon and nitrogen compound metabolism in soils of the riparian corridor.

CONCLUSIONS

The disparity between the scale of a microbial cell and the scale of a watershed currently limits the development of genomically informed predictive models describing watershed biogeochemical function. Meander-bound floodplains appear to serve as scaling motifs that predict aggregate capacities for biogeochemical transformations, providing a foundation for incorporating riparian soil microbiomes in watershed models. Widely represented genetic capacities did not predict in situ activity at one time point, but rather they define a reservoir of biogeochemical potential available as conditions change. Video abstract.

Performance evaluation of pipelines for mapping, variant calling and interval padding, for the analysis of NGS germline panels

Background

Next-generation sequencing (NGS) represents a significant advancement in clinical genetics. However, its use creates several technical, data interpretation and management challenges. It is essential to follow a consistent data analysis pipeline to achieve the highest possible accuracy and avoid false variant calls. Herein, we aimed to compare the performance of twenty-eight combinations of NGS data analysis pipeline compartments, including short-read mapping (BWA-MEM, Bowtie2, Stampy), variant calling (GATK-HaplotypeCaller, GATK-UnifiedGenotyper, SAMtools) and interval padding (null, 50 bp, 100 bp) methods, along with a commercially available pipeline (BWA Enrichment, Illumina®). Fourteen germline DNA samples from breast cancer patients were sequenced using a targeted NGS panel approach and subjected to data analysis.

Results

We highlight that interval padding is required for the accurate detection of intronic variants including spliceogenic pathogenic variants (PVs). In addition, using nearly default parameters, the BWA Enrichment algorithm, failed to detect these spliceogenic PVs and a missense PV in the TP53 gene. We also recommend the BWA-MEM algorithm for sequence alignment, whereas variant calling should be performed using a combination of variant calling algorithms; GATK-HaplotypeCaller and SAMtools for the accurate detection of insertions/deletions and GATK-UnifiedGenotyper for the efficient detection of single nucleotide variant calls.

Conclusions

These findings have important implications towards the identification of clinically actionable variants through panel testing in a clinical laboratory setting, when dedicated bioinformatics personnel might not always be available. The results also reveal the necessity of improving the existing tools and/or at the same time developing new pipelines to generate more reliable and more consistent data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04144-1.

The long non-coding RNA MEG3 plays critical roles in the pathogenesis of cholesterol gallstone

Background

Cholesterol gallstone (CG) is the most common gallstone disease, which is induced by biliary cholesterol supersaturation. The purpose of this study is to investigate the pathogenesis of CG.

Methods

Sixteen mice were equally and randomly divided into model group and normal control group. The model group was fed with lithogenic diets to induce CG, and then gallbladder bile lipid analysis was performed. After RNA-seq library was constructed, differentially expressed mRNAs (DE-mRNAs) and differentially expressed lncRNAs (DE-lncRNAs) between model group and normal control group were analyzed by DESeq2 package. Using the cluster Profiler package, enrichment analysis for the DE-mRNAs was carried out. Based on Cytoscape software, the protein-protein interaction (PPI) network and competing endogenous RNA (ceRNA) network were built. Using quantitative real-time reverse transcription-PCR (qRT-PCR) analysis, the key RNAs were validated.

Results

The mouse model of CG was suc cessfully established, and then 181 DE-mRNAs and 33 DE-lncRNAs between model and normal groups were obtained. Moreover, KDM4A was selected as a hub node in the PPI network, and lncRNA MEG3 was considered as a key lncRNA in the regulatory network. Additionally, the miR-107-5p/miR-149-3p/miR-346-3-MEG3 regulatory pairs and MEG3-PABPC4/CEP131/NUMB1 co-expression pairs existed in the regulatory network. The qRT-PCR analysis showed that KDM4A expression was increased, and the expressions of MEG3, PABPC4, CEP131, and NUMB1 were downregulated.

Conclusion

These RNAs might be related to the pathogenesis of CG.

GRACy: A tool for analysing human cytomegalovirus sequence data

Modern DNA sequencing has instituted a new era in human cytomegalovirus (HCMV) genomics. A key development has been the ability to determine the genome sequences of HCMV strains directly from clinical material. This involves the application of complex and often non-standardized bioinformatics approaches to analysing data of variable quality in a process that requires substantial manual intervention. To relieve this bottleneck, we have developed GRACy (Genome Reconstruction and Annotation of Cytomegalovirus), an easy-to-use toolkit for analysing HCMV sequence data. GRACy automates and integrates modules for read filtering, genotyping, genome assembly, genome annotation, variant analysis, and data submission. These modules were tested extensively on simulated and experimental data and outperformed generic approaches. GRACy is written in Python and is embedded in a graphical user interface with all required dependencies installed by a single command. It runs on the Linux operating system and is designed to allow the future implementation of a cross-platform version. GRACy is distributed under a GPL 3.0 license and is freely available at https://bioinformatics.cvr.ac.uk/software/ with the manual and a test dataset.

A beginner's guide for FMDV quasispecies analysis: sub-consensus variant detection and haplotype reconstruction using next-generation sequencing

Deep sequencing of viral genomes is a powerful tool to study RNA virus complexity. However, the analysis of next-generation sequencing data might be challenging for researchers who have never approached the study of viral quasispecies by this methodology. In this work we present a suitable and affordable guide to explore the sub-consensus variability and to reconstruct viral quasispecies from Illumina sequencing data. The guide includes a complete analysis pipeline along with user-friendly descriptions of software and file formats. In addition, we assessed the feasibility of the workflow proposed by analyzing a set of foot-and-mouth disease viruses (FMDV) with different degrees of variability. This guide introduces the analysis of quasispecies of FMDV and other viruses through this kind of approach.

Evaluation of variant calling tools for large plant genome re-sequencing

BACKGROUND

Discovering single nucleotide polymorphisms (SNPs) from agriculture crop genome sequences has been a widely used strategy for developing genetic markers for several applications including marker-assisted breeding, population diversity studies for eco-geographical adaption, genotyping crop germplasm collections, and others. Accurately detecting SNPs from large polyploid crop genomes such as wheat is crucial and challenging. A few variant calling methods have been previously developed but they show a low concordance between their variant calls. A gold standard of variant sets generated from one human individual sample was established for variant calling tool evaluations, however hitherto no gold standard of crop variant set is available for wheat use. The intent of this study was to evaluate seven SNP variant calling tools (FreeBayes, GATK, Platypus, Samtools/mpileup, SNVer, VarScan, VarDict) with the two most popular mapping tools (BWA-mem and Bowtie2) on wheat whole exome capture (WEC) re-sequencing data from allohexaploid wheat.

RESULTS

We found the BWA-mem mapping tool had both a higher mapping rate and a higher accuracy rate than Bowtie2. With the same mapping quality (MQ) cutoff, BWA-mem detected more variant bases in mapping reads than Bowtie2. The reads preprocessed with quality trimming or duplicate removal did not significantly affect the final mapping performance in terms of mapped reads. Based on the concordance and receiver operating characteristic (ROC), the Samtools/mpileup variant calling tool with BWA-mem mapping of raw sequence reads outperformed other tests followed by FreeBayes and GATK in terms of specificity and sensitivity. VarDict and VarScan were the poorest performing variant calling tools with the wheat WEC sequence data.

CONCLUSION

The BWA-mem and Samtools/mpileup pipeline, with no need to preprocess the raw read data before mapping onto the reference genome, was ascertained the optimum for SNP calling for the complex wheat genome re-sequencing. These results also provide useful guidelines for reliable variant identification from deep sequencing of other large polyploid crop genomes.

iWhale: a computational pipeline based on Docker and SCons for detection and annotation of somatic variants in cancer WES data

Whole exome sequencing (WES) is a powerful approach for discovering sequence variants in cancer cells but its time effectiveness is limited by the complexity and issues of WES data analysis. Here we present iWhale, a customizable pipeline based on Docker and SCons, reliably detecting somatic variants by three complementary callers (MuTect2, Strelka2 and VarScan2). The results are combined to obtain a single variant call format file for each sample and variants are annotated by integrating a wide range of information extracted from several reference databases, ultimately allowing variant and gene prioritization according to different criteria. iWhale allows users to conduct a complex series of WES analyses with a powerful yet customizable and easy-to-use tool, running on most operating systems (macOs, GNU/Linux and Windows).

iWhale code is freely available at https://github.com/alexcoppe/iWhale and the docker image is downloadable from https://hub.docker.com/r/alexcoppe/iwhale.

A high-quality genome provides insights into the new taxonomic status and genomic characteristics of Cladopus chinensis (Podostemaceae)

The Podostemaceae are ecologically and morphologically unusual aquatic angiosperms that survive only in rivers with pristine hydrology and high water quality and are at a relatively high risk of extinction. The taxonomic status of Podostemaceae has always been controversial. Here, we report the first high-quality genome assembly for Cladopus chinensis of Podostemaceae, obtained by incorporating Hi-C, Illumina and PacBio sequencing. We generated an 827.92 Mb genome with a contig N50 of 1.42 Mb and 27,370 annotated protein-coding genes. The assembled genome size was close to the estimated size, and 659.42 Mb of the assembly was assigned to 29 superscaffolds (scaffold N50 21.22 Mb). A total of 59.20% repetitive sequences were identified, among which long terminal repeats (LTRs) were the most abundant class (28.97% of the genome). Genome evolution analysis suggested that the divergence time of Cladopus chinensis (106 Mya) was earlier than that of Malpighiales (82 Mya) and that this taxon diverged into an independent branch of Podestemales. A recent whole-genome duplication (WGD) event occurred 4.43 million years ago. Comparative genomic analysis revealed that the expansion and contraction of oxidative phosphorylation, photosynthesis and isoflavonoid metabolism genes in Cladopus chinensis are probably related to the genomic characteristics of this growing submerged species. Transcriptome analysis revealed that upregulated genes in the shoot group compared to the root group were enriched in the NAC gene family and transcription factors associated with shoot development and defense responses, including WUSCHEL (WUS), ASYMMETRIC LEAVES (ASL), SHOOT MERISTEMLESS (STM), NAC2, NAC8, NAC29, NAC47, NAC73, NAC83 and NAC102. These findings provide new insights into the genomic diversity of unusual aquatic angiosperms and serve as a valuable reference for the taxonomic status and unusual shoot apical meristem of Podostemaceae.

Transcriptome Analysis Reveals Long Intergenic Non-Coding RNAs Contributed to Intramuscular Fat Content Differences between Yorkshire and Wei Pigs

Intramuscular fat (IMF) content is closely related to various meat traits, such as tenderness, juiciness, and flavor. The IMF content varies considerably among pig breeds with different genetic backgrounds. Long intergenic non-coding RNAs (lincRNAs) have been widely identified in many species and found to be an important class of regulators that can participate in multiple biological processes. However, the mechanism behind lincRNAs regulation of pig IMF content remains unknown and requires further study. In our study, we identified a total of 156 lincRNAs in the longissimus dorsi muscle of Wei (fat-type) and Yorkshire (lean-type) pigs using previously published data. These identified lincRNAs have shorter transcript length, longer exon length, lower exon number, and lower expression level as compared with protein-coding transcripts. We predicted potential target genes (PTGs) that are potentially regulated by lincRNAs in cis or trans regulation. Gene ontology and pathway analyses indicated that many potential lincRNAs target genes are involved in IMF-related processes or pathways, such as fatty acid catabolic process and adipocytokine signaling pathway. In addition, we analyzed quantitative trait locus (QTL) sites that differentially expressed lincRNAs (DE lincRNAs) between Wei and Yorkshire pigs co-localized. The QTL sites where DE lincRNAs co-localize are mostly related to IMF content. Furthermore, we constructed a co-expressed network between DE lincRNAs and their differentially expressed PTGs (DEPTGs). On the basis of their expression levels, we suggest that many DE lincRNAs can affect IMF development by positively or negatively regulating their PTGs. This study identified and analyzed some lincRNAs- and PTGs-related IMF development of the two pig breeds and provided new insight into research on the roles of lincRNAs in the two types of breeds.

Complete Genome Sequencing of Influenza A Viruses Using Next-Generation Sequencing

Recently, chain termination sequencing methods have been replaced by more efficient next-generation sequencing (NGS) methods. For influenza A, NGS allows for deep sequencing to characterize virus populations, efficient complete genome sequencing, and a non-sequence-dependent method to identify viral variants. There are numerous approaches to preparing samples for NGS and subsequent data processing methods that can be applied to influenza A sequencing. This chapter provides a brief overview of the process of NGS for influenza A and some useful bioinformatics tools for developing an NGS workflow for influenza A viruses.

The Interaction between Phagocytes and Streptococcus agalactiae (GBS) Mediated by the Activated Complement System is the Key to GBS Inducing Acute Bacterial Meningitis of Tilapia

Simple Summary

Streptococcus agalactiae (GBS) is a serious threat to farmed tilapia, which results in high mortality and seriously hinders tilapia farming development. The pathogenic mechanism of tilapia infected with GBS which die rapidly in production remains unknown. We provided a comprehensive comparative analysis of the tilapias infected with fish-derived GBS attenuated strain YM001 and its parental virulent strain HN016. The present study indicates that the interaction between phagocytes and GBS mediated by the activated complement system is key to GBS inducing tilapia acute bacterial meningitis. The low survival ability caused by reduced β-lactam antibiotics resistance is one of the important reasons YM001 lost its pathogenicity to tilapia. Our study provided a comprehensive cognition of the mechanism of acute bacterial meningitis caused by GBS.

Abstract

Streptococcus agalactiae is an important pathogen for tilapia meningitis. Most of the infected tilapia die rapidly in production, when the way to study the pathogenic mechanism of bacteria on host through chronic infection in laboratory is not comprehensive and accurate enough to elucidate the real pathogenic mechanism. The objective of this study was to investigate the mechanism of acute bacterial meningitis of tilapia caused by Streptococcus agalactiae (GBS), and provide a theoretical basis for its prevention and treatment. Duel RNA-seq, proteome analysis, histopathological analysis, plasma biochemical indexes, and blood routine examination were performed on tilapias infected with fish-derived GBS attenuated strain YM001 and its parental virulent strain HN016. The results showed that the contents of white blood cell (WBC), monocytes (MON), and neutrophil (NEU) were significantly lower in the HN016 group compared to that in the YM001 group (p < 0.05). Histopathological examination showed that there were partially lesions in the examined tissues of tilapia infected by HN016, while no obvious histopathological changes occurred in the YM001 group. The differential expressed genes (DEGs) and differential expressed proteins (DEPs) between YM001 and HN016 were mainly enriched in the beta-lactam resistance pathway (oppA1, oppA2, oppB, oppC, oppD, oppF, and mrcA). The DEGs DEPs between YM001-brain and HN016-brain were mainly enriched in the complement and coagulation cascades signaling pathway (C2a, c4b, c3b, c7, CD59, ITGB2, and ITGAX). The present study indicates that the interaction between phagocytes and GBS mediated by the activated complement system is the key to GBS inducing tilapia acute bacterial meningitis. The low survival ability caused by reduced β-lactam antibiotics resistance is one of the important reasons for why YM001 lost its pathogenicity to tilapia.

Identification and Functional Prediction of Long Intergenic Non-coding RNAs Related to Subcutaneous Adipose Development in Pigs

An increasing number of studies have shown that long intergenic non-coding RNAs (lincRNAs) are a very important class of non-coding RNAs that plays a vital role in many biological processes. Adipose tissue is an important place for storing energy, but few studies on lincRNAs were related to pig subcutaneous fat development. Here, we used published RNA-seq data from subcutaneous adipose tissue of Italian Large White pigs and identified 252 putative lincRNAs, wherein 34 were unannotated. These lincRNAs had relatively shorter length, lower number of exons, and lower expression level compared with protein-coding transcripts. Gene ontology and pathway analysis indicated that the adjacent genes of lincRNAs were involved in lipid metabolism. In addition, differentially expressed lincRNAs (DELs) between low and high backfat thickness pigs were identified. Through the detection of quantitative trait locus (QTL), DELs were mainly located in QTLs related to adipose development. Based on the expression correlation of DEL genes and their differentially expressed potential target genes, we constructed a co-expression network and a potential pathway of DEL's effect on lipid metabolism. Our study identified and analyzed lincRNAs in subcutaneous adipose tissue, and results suggested that lincRNAs may be involved in the regulation of subcutaneous fat development. Our findings provided new insights into the biological function of porcine lincRNAs.

Calling known variants and identifying new variants while rapidly aligning sequence data

Whole-genome sequencing studies can identify causative mutations for subsequent use in genomic evaluations. Speed and accuracy of sequence alignment can be improved by accounting for known variant locations during alignment instead of calling the variants after alignment as in previous programs. The new programs Findmap and Findvar were compared with alignment using Burrows-Wheeler alignment (BWA) or SNAP and variant identification using Genome Analysis ToolKit (GATK) or SAMtools. Findmap stores the reference map and any known variant locations while aligning reads and counting reference and alternate alleles for each DNA source. Findmap also outputs potential new single nucleotide variant, insertion, and deletion alleles. Findvar separates likely true variants from read errors and outputs genotype probabilities. Strategies were tested using cattle, human, and a completely random reference map and simulated or actual data. Most tests simulated 10 bulls, each with 10× simulated sequence reads containing 39 million variants from the 1000 Bull Genomes Project. With 10 processors, clock times for processing 100× data were 105 h for BWA, 25 h for GATK, and 11 h for SAMtools but only about 4 h for SNAP, 3 h for Findmap, and 1 h for Findvar. Alignment programs required about the same total memory; BWA used 46 GB (4.6 GB/processor), whereas >10 processors can share the same memory in SNAP and Findmap, which used 40 and 46 GB, respectively. Findmap correctly mapped 92.9% of reads (compared with 92.6% from SNAP and 90.5% from BWA) and had high accuracy of calling alleles for known variants. For new variants, Findvar found 99.8% of single nucleotide variants, 79% of insertions, and 67% of deletions; GATK found 99.4, 95, and 90%, respectively; and SAMtools found 99.8, 12, and 16%, respectively. False positives (as percentages of true variants) were 11% of single nucleotide variants, 0.4% of insertions, and 0.3% of deletions from Findvar; 12, 8.4, and 2.9%, respectively, from GATK; and 37, 1.3, and 0.4%, respectively, from SAMtools. Advantages of Findmap and Findvar are fast processing, precise alignment, more useful data summaries, more compact output, and fewer steps. Calling known variants during alignment allows more efficient and accurate sequence-based genotyping.