Single-molecule Sequencing Technology Research Articles

Moving toward the Inclusion of Epigenomics in Bacterial Genome Evolution: Perspectives and Challenges.

The universality of DNA methylation as an epigenetic regulatory mechanism belongs to all biological kingdoms. However, while eukaryotic systems have been the primary focus of DNA methylation studies, the molecular mechanisms in prokaryotes are less known. Nevertheless, DNA methylation in prokaryotes plays a pivotal role in many cellular processes such as defense systems against exogenous DNA, cell cycle dynamics, and gene expression, including virulence. Thanks to single-molecule DNA sequencing technologies, genome-wide identification of methylated DNA is becoming feasible on a large scale, providing the possibility to investigate more deeply the presence, variability, and roles of DNA methylation. Here, we present an overview of the multifaceted roles of DNA methylation in prokaryotes and suggest research directions and tools which can enable us to better understand the contribution of DNA methylation to prokaryotic genome evolution and adaptation. In particular, we emphasize the need to understand the presence and role of transgenerational inheritance, as well as the impact of epigenomic signatures on adaptation and genome evolution. Research directions and the importance of novel computational tools are underlined.

PathMap: a path-based mapping tool for long noisy reads with high sensitivity.

With the rapid development of single-molecule sequencing (SMS) technologies, the output read length is continuously increasing. Mapping such reads onto a reference genome is one of the most fundamental tasks in sequence analysis. Mapping sensitivity is becoming a major concern since high sensitivity can detect more aligned regions on the reference and obtain more aligned bases, which are useful for downstream analysis. In this study, we present pathMap, a novel k-mer graph-based mapper that is specifically designed for mapping SMS reads with high sensitivity. By viewing the alignment chain as a path containing as many anchors as possible in the matched k-mer graph, pathMap treats chaining as a path selection problem in the directed graph. pathMap iteratively searches the longest path in the remaining nodes; more candidate chains with high quality can be effectively detected and aligned. Compared to other state-of-the-art mapping methods such as minimap2 and Winnowmap2, experiment results on simulated and real-life datasets demonstrate that pathMap obtains the number of mapped chains at least 11.50% more than its closest competitor and increases the mapping sensitivity by 17.28% and 13.84% of bases over the next-best mapper for Pacific Biosciences and Oxford Nanopore sequencing data, respectively. In addition, pathMap is more robust to sequence errors and more sensitive to species- and strain-specific identification of pathogens using MinION reads.

Detection and identification of single ribonucleotide monophosphates using a dual in-plane nanopore sensor made in a thermoplastic via replication.

We report the generation of ∼8 nm dual in-plane pores fabricated in a thermoplastic via nanoimprint lithography (NIL). These pores were connected in series with nanochannels, one of which served as a flight tube to allow the identification of single molecules based on their molecular-dependent apparent mobilities (i.e., dual in-plane nanopore sensor). Two different thermoplastics were investigated including poly(methyl methacrylate), PMMA, and cyclic olefin polymer, COP, as the substrate for the sensor both of which were sealed using a low glass transition cover plate (cyclic olefin co-polymer, COC) that could be thermally fusion bonded to the PMMA or COP substrate at a temperature minimizing nanostructure deformation. Unique to these dual in-plane nanopore sensors was two pores flanking each side of the nanometer flight tube (50 × 50 nm, width × depth) that was 10 μm in length. The utility of this dual in-plane nanopore sensor was evaluated to not only detect, but also identify single ribonucleotide monophosphates (rNMPs) by using the travel time (time-of-flight, ToF), the resistive pulse event amplitude, and the dwell time. In spite of the relatively large size of these in-plane pores (∼8 nm effective diameter), we could detect via resistive pulse sensing (RPS) single rNMP molecules at a mass load of 3.9 fg, which was ascribed to the unique structural features of the nanofluidic network and the use of a thermoplastic with low relative dielectric constants, which resulted in a low RMS noise level in the open pore current. Our data indicated that the identification accuracy of individual rNMPs was high, which was ascribed to an improved chromatographic contribution to the nano-electrophoresis apparent mobility. With the ToF data only, the identification accuracy was 98.3%. However, when incorporating the resistive pulse sensing event amplitude and dwell time in conjunction with the ToF and analyzed via principal component analysis (PCA), the identification accuracy reached 100%. These findings pave the way for the realization of a novel chip-based single-molecule RNA sequencing technology.

Structure of plant-associated microeukaryotes in roots and leaves of aquatic and terrestrial plants revealed by blocking peptide-nucleic acid (PNA) amplification.

Studies of plant-microbe interactions, including mutualistic, antagonistic, parasitic, or commensal microbes, have greatly benefited our understanding of ecosystem functioning. New molecular identification tools have increasingly revealed the association patterns between microorganisms and plants. Here, we integrated long-read PacBio single-molecule sequencing technology with a blocking protein-nucleic acid (PNA) approach to minimise plant amplicons in a survey of plant-eukaryotic microbe relationships in roots and leaves of different aquatic and terrestrial plants to determine patterns of organ, host, and habitat preferences. The PNA approach reduced the samples' relative amounts of plant reads and did not distort the fungal and other microeukaryotic composition. Our analyses revealed that the eukaryotic microbiomes associated with leaves and roots of aquatic plants exhibit a much larger proportion of non-fungal microorganisms than terrestrial plants, and leaf and root microbiomes are similar. Terrestrial plants had much stronger differentiation of leaf and root microbiomes and stronger partner specificity than aquatic plants.

Beam search decoder for enhancing sequence decoding speed in single-molecule peptide sequencing data.

Next-generation single-molecule protein sequencing technologies have the potential to significantly accelerate biomedical research. These technologies offer sensitivity and scalability for proteomic analysis. One auspicious method is fluorosequencing, which involves: cutting naturalized proteins into peptides, attaching fluorophores to specific amino acids, and observing variations in light intensity as one amino acid is removed at a time. The original peptide is classified from the sequence of light-intensity reads, and proteins can subsequently be recognized with this information. The amino acid step removal is achieved by attaching the peptides to a wall on the C-terminal and using a process called Edman Degradation to remove an amino acid from the N-Terminal. Even though a framework (Whatprot) has been proposed for the peptide classification task, processing times remain restrictive due to the massively parallel data acquisicion system. In this paper, we propose a new beam search decoder with a novel state formulation that obtains considerably lower processing times at the expense of only a slight accuracy drop compared to Whatprot. Furthermore, we explore how our novel state formulation may lead to even faster decoders in the future.

Assessing the Resilience of Machine Learning Classification Algorithms on SARS-CoV-2 Genome Sequences Generated with Long-Read Specific Errors.

The emergence of third-generation single-molecule sequencing (TGS) technology has revolutionized the generation of long reads, which are essential for genome assembly and have been widely employed in sequencing the SARS-CoV-2 virus during the COVID-19 pandemic. Although long-read sequencing has been crucial in understanding the evolution and transmission of the virus, the high error rate associated with these reads can lead to inadequate genome assembly and downstream biological interpretation. In this study, we evaluate the accuracy and robustness of machine learning (ML) models using six different embedding techniques on SARS-CoV-2 error-incorporated genome sequences. Our analysis includes two types of error-incorporated genome sequences: those generated using simulation tools to emulate error profiles of long-read sequencing platforms and those generated by introducing random errors. We show that the spaced k-mers embedding method achieves high accuracy in classifying error-free SARS-CoV-2 genome sequences, and the spaced k-mers and weighted k-mers embedding methods are highly accurate in predicting error-incorporated sequences. The fixed-length vectors generated by these methods contribute to the high accuracy achieved. Our study provides valuable insights for researchers to effectively evaluate ML models and gain a better understanding of the approach for accurate identification of critical SARS-CoV-2 genome sequences.

A chromosome-level genome assembly of Callerya speciosa sheds new light on the biosynthesis of root-specific isoflavonoids

The edible tuberous roots of the legume Callerya speciosa (Champ. Ex Benth.) Schot are medicinally important and are a rich source of isoflavonoids. The accumulation of isoflavonoids in the roots is critically important for enhancing the quality of C. speciosa. There is thus a need to develop approaches to manipulate isoflavonoid biosynthesis and breed cultivars that better accommodate the needs of consumers. One of the major impediments to achieving these goals is a lack of available genetic information for C. speciosa. In this study, we present a chromosome-level genome assembly for C. speciosa (total size of 668.5 Mb) using Nanopore single-molecule sequencing and Hi-C technology; a total of 41,467 protein-coding genes were annotated in this genome assembly. The assembled genome comprised 303 contigs and 34 scaffolds, and the contig and scaffold N50 values were 4.18 and 87.4 Mb, respectively. The scaffolds were clustered into eight pseudochromosomes. Metabolites involved in flavonoid biosynthesis in five different tissues were identified via metabolic data. Furthermore, we developed a regulatory network for root-specific isoflavonoid biosynthesis in C. speciosa using gene-to-metabolite correlation analysis and weighted gene co-expression network analysis. A total of nine CsMYBs in the regulatory network were identified as key candidate transcription factors (TFs) that likely play important roles in regulating the content of isoflavonoids in the roots of C. speciosa. Yeast one-hybrid assays revealed interactions between structural genes involved in isoflavonoid biosynthesis and candidate MYB TFs. The reference genome and large-scale transcriptomic and metabolic data presented in our study provide valuable resources that will aid future efforts to enhance the quality of C. speciosa, as well as other agricultural traits.

Beyond assembly: the increasing flexibility of single-molecule sequencing technology.

The maturation of high-throughput short-read sequencing technology over the past two decades has shaped the way genomes are studied. Recently, single-molecule, long-read sequencing has emerged as an essential tool in deciphering genome structure and function, including filling gaps in the human reference genome, measuring the epigenome and characterizing splicing variants in the transcriptome. With recent technological developments, these single-molecule technologies have moved beyond genome assembly and are being used in a variety of ways, including to selectively sequence specific loci with long reads, measure chromatin state and protein-DNA binding in order to investigate the dynamics of gene regulation, and rapidly determine copy number variation. These increasingly flexible uses of single-molecule technologies highlight a young and fast-moving part of the field that is leading to a more accessible era of nucleic acid sequencing.

Advances in Nanopore and Photoelectron-Based High-Throughput Sequencing Technology for Single-Molecule Sequencing

Next-Generation sequencing is a widespread technology of sequencing which is used in genomics research and biotechnology, although it comes with many shortcomings such as short read length or polymerase chain reactions (PCR) bias. In this review, a brief introduction is provided to the Helicos Biosciences true single-molecule sequencing (tSMS), Pacific Biosciences single-molecule real-time (SMRT) sequencing and Oxford Nanopore single-molecule sequencing technologies. In comparison with both first- and second-generation sequencing technologies, third-generation sequencing such as nanopore and photoelectron high-throughput sequencing technologies have the advantages of ultra-long read length and no PCR bias, which help to study repetitive regions of the genome and complex structural variants, thus correctly identifying potential gene mutations in various diseases, and are important for diagnosis and treatment of various diseases. This paper focuses on the sequencing principles of nanopore and photoelectron high-throughput sequencing technologies as well as their applications in cancer, pathogen detection and genetic diseases.

A Global Survey of the Full-Length Transcriptome of Apis mellifera by Single-Molecule Long-Read Sequencing.

As important pollinators, honey bees play a crucial role in both maintaining the ecological balance and providing products for humans. Although several versions of the western honey bee genome have already been published, its transcriptome information still needs to be refined. In this study, PacBio single-molecule sequencing technology was used to sequence the full-length transcriptome of mixed samples from many developmental time points and tissues of A. mellifera queens, workers and drones. A total of 116,535 transcripts corresponding to 30,045 genes were obtained. Of these, 92,477 transcripts were annotated. Compared to the annotated genes and transcripts on the reference genome, 18,915 gene loci and 96,176 transcripts were newly identified. From these transcripts, 136,554 alternative splicing (AS) events, 23,376 alternative polyadenylation (APA) sites and 21,813 lncRNAs were detected. In addition, based on the full-length transcripts, we identified many differentially expressed transcripts (DETs) between queen, worker and drone. Our results provide a complete set of reference transcripts for A. mellifera that dramatically expand our understanding of the complexity and diversity of the honey bee transcriptome.

549. The Application of Nanopore Sequencing Technology to Characterize Rotavirus Genotypes from Young Children with Diarrhea in the United Arab Emirates

Abstract Background In the United Arab Emirates, rotavirus A (RVA) remains a major cause of gastroenteritis in young children despite the universal use of rotavirus vaccines. Monitoring the genetic diversity of circulating strains is essential to better understand the disease burden. Although semi-nested multiplex-PCR is a popular method for RVA genotyping, some clinically significant strains may not be accurately identified by this method. Nanopore sequencing is a third-generation single-molecule sequencing technology that allows for real-time identification of viral and bacterial isolates at competitive costs. This study aims to investigate the use of nanopore sequencing and multiplex-PCR methods to identify RVA genotypes. Methods Thirty-three RVA isolates, obtained from stool specimens collected from children less than 5 years old who presented with diarrhea between December 2017 and April 2019, were used for genotyping by PCR and nanopore sequencing. Sixteen isolates were genotyped by Taqman-based qRT-PCR based on VP7 (G) and VP4 (P) genes and genotypes were confirmed by nanopore sequencing in thirteen isolates; three isolates were excluded from nanopore sequencing due to poor RNA quality. Another fifteen isolates were genotyped by the nanopore method alone and two samples were excluded due to poor RNA quality. Results The majority of isolates genotyped by qRT-PCR (9 out of 16) were found to harbor VP7 gene of G9 genotype, whereas 5 isolates were of G3 genotype. G12 genotype was rare (2 isolates). For VP4 (P) genotypes, P8 was the most prevalent (8 isolates), followed by P4 (7 isolates), and P6 (1 isolate). When combinations of VP7 and VP4 genotypes are considered, G9P[8] and G9P[4] were the most common genotypes. Nanopore sequencing of 28 isolates revealed G3P8 (29%) as the most prevalent G-P combination, followed by G8P[8] (18%). G9P[8] and G2P[4] were present in 14% of samples. G12P[6] was present in 7% of tested samples. Further, G9P[4], G3P[4], G1P[4], and G4P[2] were detected in 4% of total specimens. One sample was non-typable. Conclusion Nanopore sequencing detected various RVA strains among the studied samples including the recently emerging strain, G8P[8]. Using this method in surveillance studies may advance our understanding of the origin, genetic recombination, and burden of disease. Disclosures All Authors: No reported disclosures.

Comparative Transcriptome Analysis to Identify Candidate Genes Related to Chlorogenic Acid and Flavonoids Biosynthesis in Iridaceae

Iris (Iridaceae) is one of the most widely admired ornamental plants. It has been used mainly in medicine due to the high concentration of chlorogenic acid (CGA), flavonoids, isoflavones, lignans, and other compounds in its rhizomes. In iris, the gene functions related to CGA and flavonoids biosynthesis are still unclear. In this study, we compared the I. germanica rhizome with a high accumulation level of CGA but a low accumulation level of flavonoids, and the I. pallida rhizome with a low accumulation level of CGA but a high accumulation level of flavonoids at the transcriptome and metabolome levels. A total of 761 metabolites were detected, including 202 flavonoids and 106 phenolic acids based on metabolome profiling. In total, 135 flavonoids were highly accumulated in I. pallida, including three flavanols, 51 flavonoids, 12 flavonoid carbonosides, 31 flavonols, and 21 isoflavones. Based on single-molecule long-read sequencing technology, 94,461 transcripts were identified in iris. Expression analysis indicated that the high accumulation level of C4H and 4CL in I. germanica were essential for CGA accumulation, while CHS, DFR, ANS, ANR, LAR, and 3GT were essential for flavonoids biosynthesis in I. pallida. Many transcription factors such as transcript_83288 (MYB), transcript_57970 (WRKY), and transcript_77465 (WRKY) act as regulators, playing important roles in these biological processes. Our findings provide new insights into the molecular mechanisms associated with the biosynthesis and regulation of flavonoids and CGA in the iris rhizome, and highlight the usefulness of an integrated approach for understanding this process.

Full-Length Transcriptome Sequencing and Comparative Transcriptomic Analysis Provide Insights Into the Ovarian Maturation of Exopalaemon carinicauda

The ridgetail white shrimp Exopalaemon carinicauda has the potential to be used as a useful experimental organism in the field of crustacean research due to its transparent body, large egg, and short reproductive cycle. However, little is known about the regulatory mechanisms of ovarian maturation in E. carinicauda. In this study, we applied PacBio single-molecule long-read sequencing technology to unveil the whole transcriptome landscape of Exopalaemon carinicauda to better understand the molecular mechanisms of ovarian development. A total of 49.05 G polymerase read bases were generated, finally, 15, 151 unigenes were successfully identified with a mean length of 4, 257 bp and an N50 of 4, 884 bp from ovary tissues (five different ovarian developmental stages). A total of 14, 007 unigenes were successfully annotated in at least one public database. In addition, 8, 861 coding sequences, 4, 594 lncRNAs and 895 transcription factors were identified. Furthermore, we performed RNA-Seq analysis combined with Iso-Seq results to investigate ovarian maturation regulation mechanism and validated the results by quantitative real-time PCR. We annotated five vitellogenin isoforms in the full-length transcriptome, meanwhile these five genes and vitellogenin receptor suggested an important role during previtellogenesis of E. carinicauda. Genes were involved in PI3K-Akt signaling pathway, retinol metabolism, cell cycle and hedgehog signaling pathway, which showed obvious associations with ovarian maturation of E. carinicauda. We identified 40 DEGs, such as forkhead box protein L2, which may be related to ovarian development in the comparisons. The expression profiles of genes such as ecdysone receptor, ecdysone-induced protein 74EF, ecdysone inducible gene E75 and post-molt protein suggest that they were significantly associated with reproductive molting in the ovarian mature stage. In conclusion, the present study identified important genes and pathways involved in ovarian maturation, which might be useful for studying the reproductive regulation and mechanisms of ovarian maturation in E. carinicauda.

A high-resolution single-molecule sequencing-based Arabidopsis transcriptome using novel methods of Iso-seq analysis

BackgroundAccurate and comprehensive annotation of transcript sequences is essential for transcript quantification and differential gene and transcript expression analysis. Single-molecule long-read sequencing technologies provide improved integrity of transcript structures including alternative splicing, and transcription start and polyadenylation sites. However, accuracy is significantly affected by sequencing errors, mRNA degradation, or incomplete cDNA synthesis.ResultsWe present a new and comprehensive Arabidopsis thaliana Reference Transcript Dataset 3 (AtRTD3). AtRTD3 contains over 169,000 transcripts—twice that of the best current Arabidopsis transcriptome and including over 1500 novel genes. Seventy-eight percent of transcripts are from Iso-seq with accurately defined splice junctions and transcription start and end sites. We develop novel methods to determine splice junctions and transcription start and end sites accurately. Mismatch profiles around splice junctions provide a powerful feature to distinguish correct splice junctions and remove false splice junctions. Stratified approaches identify high-confidence transcription start and end sites and remove fragmentary transcripts due to degradation. AtRTD3 is a major improvement over existing transcriptomes as demonstrated by analysis of an Arabidopsis cold response RNA-seq time-series. AtRTD3 provides higher resolution of transcript expression profiling and identifies cold-induced differential transcription start and polyadenylation site usage.ConclusionsAtRTD3 is the most comprehensive Arabidopsis transcriptome currently. It improves the precision of differential gene and transcript expression, differential alternative splicing, and transcription start/end site usage analysis from RNA-seq data. The novel methods for identifying accurate splice junctions and transcription start/end sites are widely applicable and will improve single-molecule sequencing analysis from any species.

Divergence of two cultivated allotetraploid cottons unveiled by single-molecule long-read expression sequencing

Allotetraploid Gossypium hirsutum and G. barbadense are two major cultivated cotton species that have different fiber traits. Research into the molecular basis of those differences is limited by a lack of accurate, complete transcript profiles. Here we adopted joint PacBio Iso-seq and RNA-seq to investigate genome-wide transcript profiles and uncover differences in the expression between G. hirsutum acc. TM-1 and G. barbadense cv. Hai7124. We obtained 178,867 full-length transcripts covering 60.0% of gene loci in the TM-1 reference annotation, including 7846 transcription factors and 3122 lncRNAs. Moreover, we identified 304 and 610 high-confidence (HC) species-specific transcripts in TM-1 and Hai7124, respectively, along with 4156 and 4381 tissue-specific transcripts. Our results update the reference genome annotation and also provide potential resources for studying the molecular mechanisms of fiber development. We are thus able to promote improvements in cotton fiber quality. • Produced 178,867 full-length transcripts from 10 Gossypium hirsutum and G. barbadense tissues using single-molecule sequencing technology. • By contrast, species-specific and tissue-specific transcripts were identified. • Helps to uncover the molecular mechanisms underlying fiber differences at the transcript level in cotton.

DiMeLo-seq: a long-read, single-molecule method for mapping protein-DNA interactions genome wide.

Studies of genome regulation routinely use high-throughput DNA sequencing approaches to determine where specific proteins interact with DNA, and they rely on DNA amplification and short-read sequencing, limiting their quantitative application in complex genomic regions. To address these limitations, we developed Directed Methylation with Long-read sequencing (DiMeLo-seq), which uses antibody-tethered enzymes to methylate DNA near a target protein’s binding sites in situ. These exogenous methylation marks are then detected simultaneously with endogenous CpG methylation on unamplified DNA using long-read, single-molecule sequencing technologies. We optimized and benchmarked DiMeLo-seq by mapping chromatin-binding proteins and histone modifications across the human genome. Furthermore, we identified where centromere protein A (CENP-A) localizes within highly repetitive regions that we re unmappable with short sequencing reads, and we estimated the density of CENP-A molecules along single chromatin fibers. DiMeLo-seq is a versatile method that provides multimodal, genome-wide information for investigating protein-DNA interactions.

Pacific bioscience sequence technology: Review

Pacific Biosciences has developed a platform that may sequence one molecule of DNA in a period via the polymerization of that strand with one enzyme. Single-molecule real-time sequencing by Pacific BioSciences’ technology is one of the most widely utilized third-generation sequencing technologies. PacBio single-molecule real-time Sequencing uses the Zero-mode waveguide’s ingenuity to distinguish the best fluorescence signal from the stable fluorescent backgrounds generated by disorganized free-floating nucleotides. PacBio single-molecule real-time sequencing does not require PCR amplification, and the browse length is a hundred times longer than next-generation sequencing. It will only cover high-GC and high-repeat sections and is more accurate in quantifying low-frequency mutations. PacBio single-molecule real-time sequencing will have a relatively high error rate of 10%-15% (which is practically a standard flaw of existing single-molecule sequencing technology). In contrast to next-generation sequencing, however, the errors are unintentionally random. As a result, multiple sequencing will effectively rectify the bottom deviance. Unlike second-generation sequencing, PacBio sequencing may be a technique for period sequencing and doesn’t need an intermission between browse steps. These options distinguish PacBio sequencing from second-generation sequencing, therefore it’s classified because of the third-generation sequencing. PacBio sequencing produces extremely lengthy reads with a high error rate and low yield. Short reads refine alignments/assemblies/detections to single-nucleotide precision, whereas PacBio long reads provide reliable alignments, scaffolds, and approximate detections of genomic variations. Through extraordinarily long sequencing reads (average >10,000 bp) and high accord precision, the PacBio Sequencing System can provide a terribly high depth of genetic information. To measure and promote the event of modern bioinformatics tools for PacBio sequencing information analysis, a good browse machine is required.

Genome Resource for Elsinoë batatas, the Causal Agent of Stem and Foliage Scab Disease of Sweet Potato.

Elsinoë batatas is a phytopathogenic fungus causing stem and foliage scab disease of sweet potato. At present, there is no reference genome available for E. batatas, limiting basic research for the pathogen. The present study applied the Nanopore single-molecule sequencing technology to sequence the E. batatas genome. This study reports the first high-quality genome sequence of E. batatas, with a total contig size of 26.49 Mb, 50.8% GC content, and an N50 of 2,546,814 bp. The sequences obtained serve as a reference for analysis of E. batatas isolates and provide a resource to better understand the biology of stem and foliage scab disease of sweet potato.

Dioecy in Flowering Plants: From the First Observations of Prospero Alpini in the XVI Century to the Most Recent Advances in the Genomics Era

Prospero Alpini was an Italian physician, botanist and scientist. Born in Marostica, in the Republic of Venice, in his youth he served in the Milanese army, but in 1574 he decided to study medicine at the University of Padova, where he graduated in 1578. After a short period as a doctor in Camposampiero (Padova, Italy), he became the personal doctor of Giorgio Emo, the appointed consul in Cairo in Egypt. In this way, he was able to devote himself to the study of botany. In this country, from the cultivation practices of the date palm, he described for the first time the sexual dimorphism in plants, later adopted as the basis of Linnaeus’ scientific classification system. Since then, this behavior, termed dioecy, has been described in other plant species, and many advances have been made in understanding the molecular mechanisms underlying this phenomenon, especially with the advent of genomics. Starting from a brief description of Prospero’s life and his pioneering scientific contribution, we illustrated the two main models explaining dioecism. This was achieved by taking a cue from two plant species, grapevine and poplar, in which genomics and single molecule sequencing technologies played a pivotal role in scientific advance in this field.

Dynamic Microbial Shifts and Functional Analysis of Saliva Microbial Communities with Caries Children

To observe the dynamic changes in the salivary microbiota of children with dental caries and those who were caries-free and to analyze the functional differences in the oral microecology of the two groups during the course of sugar metabolism and the synthesis and transport of multiple amino acids. Ten children with dental caries and 10 caries-free children were enrolled. We employed Illumina metagenomics technology to analyze the composition and function of salivary microbiome in children with and without caries. Six months later, PacBio single-molecule long-read sequencing technology was used to analyze the changes over time in the oral microbial communities of the two groups. We studied the patterns of change in the oral microbial communities under diseased or healthy conditions and attempted to offer a comprehensive interpretation of children's oral microbiota in terms of its composition and functions. The composition of the oral microbiota of children with or without dental caries changed significantly over time. At the phylum level, changing trends in the salivary microbial communities of children with dental caries were in line with those in caries-free children. In these microbial communities, increased proportions of Firmicutes and decreased proportions of Actinobacteria and Bacteroidetes were found in the two groups. At the genus level, however, the two groups showed significantly different changes of the salivary microbial communities. Upward trends in the abundance of Lactobacillus, Methylobacterium, and Megasphaera were found in the caries group, while the abundance of these genera in the caries-free group showed downward trends. At the species level, L. fermentum, L. gasseri, L. oris, S. downei, and some other species belonging to the genus Lactobacillus showed upward trends in the saliva of children with caries, while they consistently stayed at a relative low level of abundance in caries-free children. The abundance of S. gordonii and S. mutans decreased to a certain extent in children with dental caries, but the abundance of S. gordonii and S. mutans in caries-free children were always at a low level. Species such as S. mutans and C. gracilis were positively correlated to the sum of decayed, missing and filled teeth (dmft), while N. flavescens was negatively correlated to dmft. gltA, icd, and mqo, the key genes related to tricarboxylic acid (TCA) cycle, gudB, a glutamate synthesis-related gene, and argAB/C/J, arginine synthesis-related genes, were significantly increased in caries-free children. In addition, the abundance of the NADH dehydrogenase-related gene nuoB/C/D/E/H/I/J/K/L/M in the electron transport chain increased significantly in caries-free children. Dynamic changes were found in the oral microbiota of children with or without caries. The trends of microbial shifts over time were associated with the oral health status. Oxidative phosphorylation and the synthesis and transport of amino acids such as glutamate and arginine in the oral microecology were more active in caries-free children.