Basics of high throughput sequencing Summary

Sequencing can provide genomic characterisation of a specific organism, as well as of a whole environmental or clinical sample. High Throughput Sequencing (HTS) makes it possible to generate an enormous amount of genomic data at gradually decreasing costs and almost in real-time. HTS is used, among others, in medicine, veterinary medicine, microbiology, virology and epidemiology. The paper presents practical aspects of the HTS technology. It describes generations of sequencing, which vary in throughput, read length, accuracy and costs ̶ and thus are used for different applications. The stages of HTS, as well as their purposes and pitfalls, are presented: extraction of the genetic material, library preparation, sequencing and data processing. For success of the whole process, all stages need to follow strict quality control measurements. Choosing the right sequencing platform, proper sample and library preparation procedures, as well as adequate bioinformatic tools are crucial for high quality results.

Population Evolution, Genetic Diversity and Structure of the Medicinal Legume, Glycyrrhiza uralensis and the Effects of Geographical Distribution on Leaves Nutrient Elements and Photosynthesis

Glycyrrhiza uralensis is a valuable medicinal legume, which occurs widely in arid and semi-arid regions. G. uralensis demand has risen steeply due to its high medical and commercial value. Interpret genome-wide information can stimulate the G. uralensis development as far as its increased bioactive compound levels, and plant yield are concerned. In this study, leaf nutrient concentration and photosynthetic chlorophyll index of G. uralensis were evaluated to determine the G. uralensis growth physiology in three habitats. We observed that G. uralensis nutrient levels and photosynthesis differed significantly in three regions (p < 0.05). Whole-genome re-sequencing of the sixty G. uralensis populations samples from different habitats was performed using an Illumina HiSeq sequencing platform to elucidate the distribution patterns, population evolution, and genetic diversity of G. uralensis. 150.06 Gb high-quality clean data was obtained after strict filtering. The 895237686 reads were mapped against the reference genome, with an average 89.7% mapping rate and 87.02% average sample coverage rate. A total of 6985987 SNPs were identified, and 117970 high-quality SNPs were obtained after filtering, which were subjected to subsequent analysis. Principal component analysis (PCA) based on interindividual SNPs and phylogenetic analysis based on interindividual SNPs showed that the G. uralensis samples could be categorized into central, southern, and eastern populations, which reflected strong genetic differentiation due to long periods of geographic isolation. In this study, a total of 131 candidate regions were screened, and 145 candidate genes (such as Glyur001802s00036258, Glyur003702s00044485, Glyur001802s00036257, Glyur007364s00047495, Glyur000028s00003476, and Glyur000398s00034457) were identified by selective clearance analysis based on Fst and θπ values. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed significant enrichment of 110 GO terms including carbohydrate metabolic process, carbohydrate biosynthetic process, carbohydrate derivative biosynthetic process, and glucose catabolic process (p < 0.05). Alpha-linolenic acid metabolism, biosynthesis of unsaturated fatty acids, and fatty acid degradation pathways were significantly enriched (p < 0.05). This study provides information on the genetic diversity, genetic structure, and population adaptability of the medicinal legumes, G. uralensis. The data obtained in this study provide valuable information for plant development and future optimization of breeding programs for functional genes.

Integrative profiling of Epstein–Barr virus transcriptome using a multiplatform approach

Background Epstein–Barr virus (EBV) is an important human pathogenic gammaherpesvirus with carcinogenic potential. The EBV transcriptome has previously been analyzed using both Illumina-based short read-sequencing and Pacific Biosciences RS II-based long-read sequencing technologies. Since the various sequencing methods have distinct strengths and limitations, the use of multiplatform approaches have proven to be valuable. The aim of this study is to provide a more complete picture on the transcriptomic architecture of EBV. Methods In this work, we apply the Oxford Nanopore Technologies MinION (long-read sequencing) platform for the generation of novel transcriptomic data, and integrate these with other’s data generated by another LRS approach, Pacific BioSciences RSII sequencing and Illumina CAGE-Seq and Poly(A)-Seq approaches. Both amplified and non-amplified cDNA sequencings were applied for the generation of sequencing reads, including both oligo-d(T) and random oligonucleotide-primed reverse transcription. EBV transcripts are identified and annotated using the LoRTIA software suite developed in our laboratory. Results This study detected novel genes embedded into longer host genes containing 5′-truncated in-frame open reading frames, which potentially encode N-terminally truncated proteins. We also detected a number of novel non-coding RNAs and transcript length isoforms encoded by the same genes but differing in their start and/or end sites. This study also reports the discovery of novel splice isoforms, many of which may represent altered coding potential, and of novel replication-origin-associated transcripts. Additionally, novel mono- and multigenic transcripts were identified. An intricate meshwork of transcriptional overlaps was revealed. Conclusions An integrative approach applying multi-technique sequencing technologies is suitable for reliable identification of complex transcriptomes because each techniques has different advantages and limitations, and the they can be used for the validation of the results obtained by a particular approach.

RNA-combine: a toolkit for comprehensive analyses on transcriptome data from different sequencing platforms

Background Understanding the transcriptome has become an essential step towards the full interpretation of the biological function of a cell, a tissue or even an organ. Many tools are available for either processing, analysing transcriptome data, or visualizing analysis results. However, most existing tools are limited to data from a single sequencing platform and only several of them could handle more than one analysis module, which are far from enough to meet the requirements of users, especially those without advanced programming skills. Hence, we still lack an open-source toolkit that enables both bioinformatician and non-bioinformatician users to process and analyze the large transcriptome data from different sequencing platforms and visualize the results. Results We present a Linux-based toolkit, RNA-combine, to automatically perform the quality assessment, downstream analysis of the transcriptome data generated from different sequencing platforms, including bulk RNA-seq (Illumina platform), single cell RNA-seq (10x Genomics) and Iso-Seq (PacBio) and visualization of the results. Besides, this toolkit is implemented with at least 10 analysis modules more than other toolkits examined in this study. Source codes of RNA-combine are available on GitHub: https://github.com/dongxuemin666/RNA-combine. Conclusion Our results suggest that RNA-combine is a reliable tool for transcriptome data processing and result interpretation for both bioinformaticians and non-bioinformaticians.

The mycobiome of the oral cavity in healthy dogs and dogs with periodontal disease

OBJECTIVE To investigate the mycobiome of the oral cavity in healthy dogs and dogs with various stages of periodontal disease. ANIMALS 51 dogs without periodontal disease (n = 12) or with mild (10), moderate (19), or severe (10) periodontal disease. PROCEDURES The whole maxillary arcade of each dog was sampled with a sterile swab, and swabs were submitted for next-generation DNA sequencing targeting the internal transcribed spacer 2 region with a commercial sequencing platform. RESULTS Fungi were detected in all samples, with a total of 320 fungal species from 135 families detected in the data set. No single fungal species was found in all samples. The 3 most frequently found fungal species were Cladosporium sp (46/51 samples), Malassezia restricta (44/51 samples), and Malassezia arunalokei (36/51 samples). Certain fungi, specifically those of the family Didymellaceae, the family Irpicaceae, and the order Pleosporales, were significantly associated with different stages of periodontitis. Mycobial analysis indicated that Cladosporium sp could be considered part of the core oral cavity mycobiome. CONCLUSIONS AND CLINICAL RELEVANCE Results highlighted that fungi are present in the oral cavity of dogs and are characterized by substantial species diversity, with different fungal communities associated with various stages of periodontal disease. The next-generation DNA sequencing used in the present study revealed substantially more species of fungi than previous culture-based studies.

Transcriptome-wide Identification and Characterization of microRNAs and Their Targets in a Highly Adaptable Conifer Platycladus orientalis

MicroRNAs (miRNAs) are short noncoding RNAs (20–25 nucleotides) that regulate gene expression posttranscriptionally. However, identification and characterization of miRNAs remain limited for conifer species. In this study, we applied transcriptome-wide miRNAs sequencing to a conifer species Platycladus orientalis, which is highly adaptable to a wide range of environmental adversities, including drought, barren soil, and mild salinity. A total of 17,181,542 raw reads were obtained from the Illumina sequencing platform; 31 conserved and 91 novel miRNAs were identified, and their unique characteristics were further analyzed. Ten randomly selected miRNAs were validated by quantificational real-time polymerase chain reaction. Through miRNA target predictions based on psRNATarget, 2331 unique mRNAs were predicted to be targets of P. orientalis miRNAs that involved in 187 metabolic pathways in KEGG database. These targets included not only important transcription factors (e.g., class III homeodomain leucine zipper targeted by por-miR166d) but also indispensable nontranscriptional factor proteins (i.e., por-miR482a-3p regulated nucleotide-binding site leucine-rich repeat protein). Interestingly, six miRNAs (por-miR16, -miR44, -miR60-5p, -miR69–3p, -miR166b-5p, and -miR395c) were found in adaptation-related pathways (e.g., drought), indicating their possible involved in this species’ stress-tolerance characteristics. The present study provided essential information for understanding the regulatory role of miRNAs in P. orientalis and sheds light on their possible use in tree improvement for stress tolerance.

Genomic Identification, Evolution, and Expression Analysis of Bromodomain Genes Family in Buffalo

Bromodomain (BRD) is an evolutionarily conserved protein–protein interaction module that is critical in gene regulation, cellular homeostasis, and epigenetics. This study aimed to conduct an identification, evolution, and expression analysis of the BRD gene family in the swamp buffalo (Bubalus bubalis). A total of 101 BRD protein sequences deduced from 22 BRD genes were found in the buffalo genome. The BRD proteins were classified into six groups based on phylogenetic relationships, conserved motifs, and conserved domains. The BRD genes were irregularly distributed in 13 chromosomes. Collinearity analysis revealed 20 BRD gene pairs that had remarkable homologous relationships between the buffalo and cattle, although no tandem or segmental duplication event was found in the buffalo BRD genes. Comparative transcriptomics using a 10x sequencing platform analysis showed that 22 BRD genes were identified in the Sertoli cells (SCs) at different developmental stages of buffalo. Further, the mRNA expression levels of bromodomain and the extraterminal (BET) family in SCs at the pubertal stage were higher than that at the prepubertal stage of buffalo. However, the SMARCA2, PHIP, BRD9, and TAF1 genes exhibited the opposite trend. The maturation process of SCs may be regulated by the BRD family members expressed differentially in SCs at different developmental stages of buffalo. In summary, our findings provide an understanding of the evolutionary, structural, and functional properties of the buffalo BRD family members, and further characterize the function of the BRD family in the maturation of SCs. It also provides a theoretical basis for further understanding in the future of the mechanism of SCs regulating spermatogenesis.

First high-quality genome assembly data of sago palm (Metroxylon sagu Rottboll)

The sago palm (Metroxylon sagu Rottboll) is a all-rounder palm, it is both a tropical halophytic starch-producing palm as well as an ornamental plant. Recently, a genome survey was conducted on this palm using Illumina sequencing platform but the BUSCO genome completeness is very low (21.5%) and most of them (~78%) are either fragmented or missing. Thus, in this study, the sago palm genome completeness was further improved with the utilization of the Nanopore sequencing platform that produced longer reads. A hybrid genome assembly was conducted and the outcome was a much complete sago palm genome with BUSCO completeness achieved at as high as 97.9% with only ~2% of them either fragmented or missing. The estimated genome size of the sago palm is 509,812,790 bp in this study. A sum of 33,242 protein-coding genes were revealed from the sago palm genome and around 96.39% of them had been functionally annotated. An investigation on the carbohydrate metabolism KEGG pathways also unearthed that starch synthesis was one of the major sago palm activities. These data are indispensable for future molecular evolutionary and genome-wide association studies.

Characterization and Simulation of Metagenomic Nanopore Sequencing Data with Meta-NanoSim

Background: Nanopore sequencing is crucial to metagenomic studies as its kilobase-long reads can contribute to resolving genomic structural differences among microbes. However, sequencing platform-specific challenges, including high base-call error rate, non-uniform read lengths, and the presence of chimeric artifacts, necessitate specifically designed analytical tools, such as microbial abundance estimation and metagenome assembly algorithms. When developing and testing bioinformatics tools and pipelines, the use of simulated datasets with characteristics that are true to the sequencing platform under evaluation is a cost-effective way to provide a ground truth and assess the performance in a controlled environment. Results: Here, we present Meta-NanoSim, a fast and versatile utility that characterizes and simulates the unique properties of nanopore metagenomic reads. It improves upon state-of-the-art methods on microbial abundance estimation through a base-level quantification algorithm. Meta-NanoSim can simulate complex microbial communities composed of both linear and circular genomes, and can stream reference genomes from online servers directly. Simulated datasets showed high congruence with experimental data in terms of read length, error profiles, and abundance levels. We demonstrate that Meta-NanoSim simulated data can facilitate the development of metagenomic algorithms and guide experimental design through a metagenome assembly benchmarking task. Conclusions: The Meta-NanoSim characterization module investigates read features including chimeric information and abundance levels, while the simulation module simulates large and complex multi-sample microbial communities with different abundance profiles. All trained models and the software are freely accessible at Github: https://github.com/bcgsc/NanoSim .

MicroRNA Expression Profile Analysis of Chlamydomonas reinhardtii during Lipid Accumulation Process under Nitrogen Deprivation Stresses

Lipid accumulation in various microalgae has been found induced by nitrogen deprivation, and it controls many different genes expression. Yet, the underlying molecular mechanisms still remain largely unknown. MicroRNA (miRNAs) play a critical role in post-transcriptional gene regulation. In this study, miRNAs were hypothesized involved in lipid accumulation by nitrogen deprivation. A deep-sequencing platform was used to explore miRNAs-mediated responses induced by nitrogen deprivation in Chlamydomonas reinhardtii. The eukaryotic orthologous groups of proteins (KOG) function in the predicted target genes of miRNA with response to nitrogen deprivation were mainly involved in signal transduction mechanisms, including transcription, lipid transport, and metabolism. A total of 109 miRNA were predicted, including 79 known miRNA and 30 novel miRNA. A total of 29 miRNAs showed significantly differential expressions after nitrogen deprivation, and most of them were upregulated. A total of 10 miRNAs and their targeting genes might involve in lipid transport and metabolism biological process. This study first investigates nitrogen deprivation-regulated miRNAs in microalgae and broadens perspectives on miRNAs importance in microalgae lipid accumulation via nitrogen deprivation. This study provides theoretical guidance for the application of microalgae in bio-oil engineering production.