Transcriptome analysis of flower colour reveals the correlation between SNP and differential expression genes in Phalaenopsis.

BACKGROUND: Phalaenopsis is an important ornamental plant that has great economic value in the world flower market as one of the most popular flower resources. OBJECTIVE: To investigate the flower colour formation of Phalaenopsis at the transcription level, the genes involved in flower color formation were identified from RNA-seq in this study. METHODS: In this study, white and purple petals of Phalaenopsis were collected and analyzed to obtained (1) differential expression genes (DEGs) between white and purple flower color and (2) the association between single nucleotide polymorphisms (SNP) mutations and DEGs at the transcriptome level. RESULTS: The results indicated that a total of 1,175 DEGs were identified, and 718 and 457 of them were up- and down-regulated genes, respectively. Gene Ontology and pathway enrichment showed that the biosynthesis of the secondary metabolites pathway was key to color formation, and the expression of 12 crucial genes (C4H, CCoAOMT, F3'H, UA3'5'GT, PAL, 4CL, CCR, CAD, CALDH, bglx, SGTase, and E1.11.17) that are involved in the regulation of flower color in Phalaenopsis. CONCLUSION: This study reported the association between the SNP mutations and DEGs for color formation at RNA level, and provides a new insight to further investigate the gene expression and its relationship with genetic variants from RNA-seq data in other species.

Comparative Analysis of Codon Usage Patterns in Nuclear and Chloroplast Genome of Dalbergia (Fabaceae).

The Dalbergia plants are widely distributed across more than 130 tropical and subtropical countries and have significant economic and medicinal value. Codon usage bias (CUB) is a critical feature for studying gene function and evolution, which can provide a better understanding of biological gene regulation. In this study, we comprehensively analyzed the CUB patterns of the nuclear genome, chloroplast genome, and gene expression, as well as systematic evolution of Dalbergia species. Our results showed that the synonymous and optimal codons in the coding regions of both nuclear and chloroplast genome of Dalbergia preferred ending with A/U at the third codon base. Natural selection was the primary factor affecting the CUB features. Furthermore, in highly expressed genes of Dalbergia odorifera, we found that genes with stronger CUB exhibited higher expression levels, and these highly expressed genes tended to favor the use of G/C-ending codons. In addition, the branching patterns of the protein-coding sequences and the chloroplast genome sequences were very similar in the systematic tree, and different with the cluster from the CUB of the chloroplast genome. This study highlights the CUB patterns and features of Dalbergia species in different genomes, explores the correlation between CUB preferences and gene expression, and further investigates the systematic evolution of Dalbergia, providing new insights into codon biology and the evolution of Dalbergia plants.

High-throughput and high-accuracy single-cell RNA isoform analysis using PacBio circular consensus sequencing.

Although long-read single-cell RNA isoform sequencing (scISO-Seq) can reveal alternative RNA splicing in individual cells, it suffers from a low read throughput. Here, we introduce HIT-scISOseq, a method that removes most artifact cDNAs and concatenates multiple cDNAs for PacBio circular consensus sequencing (CCS) to achieve high-throughput and high-accuracy single-cell RNA isoform sequencing. HIT-scISOseq can yield >10 million high-accuracy long-reads in a single PacBio Sequel II SMRT Cell 8M. We also report the development of scISA-Tools that demultiplex HIT-scISOseq concatenated reads into single-cell cDNA reads with >99.99% accuracy and specificity. We apply HIT-scISOseq to characterize the transcriptomes of 3375 corneal limbus cells and reveal cell-type-specific isoform expression in them. HIT-scISOseq is a high-throughput, high-accuracy, technically accessible method and it can accelerate the burgeoning field of long-read single-cell transcriptomics.

An eco-evo-devo genetic network model of stress response.

The capacity of plants to resist abiotic stresses is of great importance to agricultural, ecological and environmental sustainability, but little is known about its genetic underpinnings. Existing genetic tools can identify individual genetic variants mediating biochemical, physiological, and cellular defenses, but fail to chart an overall genetic atlas behind stress resistance. We view stress response as an eco-evo-devo process by which plants adaptively respond to stress through complex interactions of developmental canalization, phenotypic plasticity, and phenotypic integration. As such, we define and quantify stress response as the developmental change of adaptive traits from stress-free to stress-exposed environments. We integrate composite functional mapping and evolutionary game theory to reconstruct omnigenic, information-flow interaction networks for stress response. Using desert-adapted Euphrates poplar as an example, we infer salt resistance-related genome-wide interactome networks and trace the roadmap of how each SNP acts and interacts with any other possible SNPs to mediate salt resistance. We characterize the previously unknown regulatory mechanisms driving trait variation; i.e. the significance of a SNP may be due to the promotion of positive regulators, whereas the insignificance of a SNP may result from the inhibition of negative regulators. The regulator-regulatee interactions detected are not only experimentally validated by two complementary experiments, but also biologically interpreted by their encoded protein-protein interactions. Our eco-evo-devo model of genetic interactome networks provides an approach to interrogate the genetic architecture of stress response and informs precise gene editing for improving plants' capacity to live in stress environments.

Evaluation on the phenotypic diversity of Calamansi (Citrus microcarpa) germplasm in Hainan island.

Calamansi or Philippine lime (Citrofortunella macrocarpa) is an important crop for local economic in Hainan Island. There is no study about Calamansi germplasm evaluation and cultivar development. In this study, Calamansi data were collected from 151 of Calamansi seedling trees, and 37 phenotypic traits were analyzed to investigate their genetic diversities. The cluster analysis and principal component analysis were conducted aiming to provide a theoretical basis for the Calamansi genetic improvement. The results of the diversity analysis revealed: (1) the diversity indexes for qualitative traits were ranged from 0.46-1.39, and the traits with the highest genetic diversity level were fruit shaped and pulp colored (H' > 1.20); and the diversity indexes for quantitative traits ranged from 0.67-2.10, with the exception of a lower in fruit juice rate (1.08) and lower in number of petals (0.67). (2) The clustering analysis of phenotypic traits have arranged the samples into 4 categories: the first group characterized by fewer flesh Segment number per fruit (SNF) and more Oil cell number (OCN); the second group had 7 samples, all characterized with larger Crown breadth (CB), higher Yield per tree (YPT), the lager leaf, the higher Ascorbic acid (AA), and less Seed number per fruit (SNPF); the third group had 25 samples characterized by smaller Tree foot diameter (TFD),smaller Fruit shape index (FSI) and higher Total soluble solids (TSS) contain; the fourth group had 87 samples, they were characterized by shorter Petiole length (PEL), larger fruit, higher Juice ratio (JR), multiple Stamen number (SN) and longer Pistil length (PIL). (3) The principal component analysis showed the values of the first 9 major components characteristic vectors were all greater than 3, the cumulative contribution rate reach 72.20%, including the traits of single fruit weight, fruit diameter, tree height, tree canopy width etc. Finally, based on the comprehensive main component value of all samples, the Calamansi individuals with higher testing scores were selected for further observation. This study concludes that Calamansi seedling populations in the Hainan Island holds great genetic diversity in varies traits, and can be useful for the Calamansi variety improvements.

SCSit: A high-efficiency preprocessing tool for single-cell sequencing data from SPLiT-seq.

SPLiT-seq provides a low-cost platform to generate single-cell data by labeling the cellular origin of RNA through four rounds of combinatorial barcoding. However, an automatic and rapid method for preprocessing and classifying single-cell sequencing (SCS) data from SPLiT-seq, which directly identified and labeled combinatorial barcoding reads and distinguished special cell sequencing data, is currently lacking. Here, we develop a high-efficiency preprocessing tool for single-cell sequencing data from SPLiT-seq (SCSit), which can directly identify combinatorial barcodes and UMI of cell types and obtain more labeled reads, and remarkably enhance the retained data from SCS due to the exact alignment of insertion and deletion. Compared with the original method used in SPLiT-seq, the consistency of identified reads from SCSit increases to 97%, and mapped reads are twice than the original. Furthermore, the runtime of SCSit is less than 10% of the original. It can accurately and rapidly analyze SPLiT-seq raw data and obtain labeled reads, as well as effectively improve the single-cell data from SPLiT-seq platform. The data and source of SCSit are available on the GitHub website https://github.com/shang-qian/SCSit.

Efficient assembly of nanopore reads via highly accurate and intact error correction.

Long nanopore reads are advantageous in de novo genome assembly. However, nanopore reads usually have broad error distribution and high-error-rate subsequences. Existing error correction tools cannot correct nanopore reads efficiently and effectively. Most methods trim high-error-rate subsequences during error correction, which reduces both the length of the reads and contiguity of the final assembly. Here, we develop an error correction, and de novo assembly tool designed to overcome complex errors in nanopore reads. We propose an adaptive read selection and two-step progressive method to quickly correct nanopore reads to high accuracy. We introduce a two-stage assembler to utilize the full length of nanopore reads. Our tool achieves superior performance in both error correction and de novo assembling nanopore reads. It requires only 8122 hours to assemble a 35X coverage human genome and achieves a 2.47-fold improvement in NG50. Furthermore, our assembly of the human WERI cell line shows an NG50 of 22 Mbp. The high-quality assembly of nanopore reads can significantly reduce false positives in structure variation detection.

Corrigendum: Distribution Patterns of DNA N6-Methyladenosine Modification in Non-coding RNA Genes.

[This corrects the article DOI: 10.3389/fgene.2020.00268.].

DNA N6-Methyladenine Modification in Wild and Cultivated Soybeans Reveals Different Patterns in Nucleus and Cytoplasm.

DNA 6mA modification, an important newly discovered epigenetic mark, plays a crucial role in organisms and has been attracting more and more attention in recent years. The soybean is economically the most important bean in the world, providing vegetable protein for millions of people. However, the distribution pattern and function of 6mA in soybean are still unknown. In this study, we decoded 6mA modification to single-nucleotide resolution in wild and cultivated soybeans, and compared the 6mA differences between cytoplasmic and nuclear genomes and between wild and cultivated soybeans. The motif of 6mA in the nuclear genome was conserved across the two kinds of soybeans, and ANHGA was the most dominant motif in wild and cultivated soybeans. Genes with 6mA modification in the nucleus had higher expression than those without modification. Interestingly, 6mA distribution patterns in cytoplasm for each soybean were significantly different from those in nucleus, which was reported for the first time in soybean. Our research provides a new insight in the deep analysis of cytoplasmic genomic DNA modification in plants.

Distribution Patterns of DNA N6-Methyladenosine Modification in Non-coding RNA Genes.

N6-methyladenosine (6mA) DNA modification played an important role in epigenetic regulation of gene expression. And the aberrational expression of non-coding genes, as important regular elements of gene expression, was related to many diseases. However, the distribution and potential functions of 6mA modification in non-coding RNA (ncRNA) genes are still unknown. In this study, we analyzed the 6mA distribution of ncRNA genes and compared them with protein-coding genes in four species (Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens) using single-molecule real-time (SMRT) sequencing data. The results indicated that the consensus motifs of short nucleotides at 6mA location were highly conserved in four species, and the non-coding gene was less likely to be methylated compared with protein-coding gene. Especially, the 6mA-methylated lncRNA genes were expressed significant lower than genes without methylation in A. thaliana (p = 3.295e-4), D. melanogaster (p = 3.439e-11), and H. sapiens (p = 9.087e-3).. The detection and distribution profiling of 6mA modification in ncRNA regions from four species reveal that 6mA modifications may have effects on their expression level.

Evaluating Structural Variation Detection Tools for Long-Read Sequencing Datasets in Saccharomyces cerevisiae.

Structural variation (SV) represents a major form of genetic variations that contribute to polymorphic variations, human diseases, and phenotypes in many organisms. Long-read sequencing has been successfully used to identify novel and complex SVs. However, comparison of SV detection tools for long-read sequencing datasets has not been reported. Therefore, we developed an analysis workflow that combined two alignment tools (NGMLR and minimap2) and five callers (Sniffles, Picky, smartie-sv, PBHoney, and NanoSV) to evaluate the SV detection in six datasets of Saccharomyces cerevisiae. The accuracy of SV regions was validated by re-aligning raw reads in diverse alignment tools, SV callers, experimental conditions, and sequencing platforms. The results showed that SV detection between NGMLR and minimap2 was not significant when using the same caller. The PBHoney was with the highest average accuracy (89.04%) and Picky has the lowest average accuracy (35.85%). The accuracy of NanoSV, Sniffles, and smartie-sv was 68.67%, 60.47%, and 57.67%, respectively. In addition, smartie-sv and NanoSV detected the most and least number of SVs, and SV detection from the PacBio sequencing platform was significantly more than that from ONT (p = 0.000173).

Genome-wide codon usage pattern analysis reveals the correlation between codon usage bias and gene expression in Cuscuta australis.

The protein-coding genes and pseudogenes of Cuscuta australis had the diverse contribution to the formation and evolution of parasitism. The codon usage pattern analysis of these two type genes could be used to understand the gene transcription and translation. In this study, we systematically analyzed the codon usage patterns of protein-coding sequences and pseudogenes sequences in C. australis. The results showed that the high frequency codons of protein coding sequences and pseudogenes had the same A/U bias in the third position. However, these two sequences had converse bias at the third base in optimal codons: the protein coding sequences preferred G/C-ending codons while pseudogene sequences preferred A/U-ending codons. Neutrality plot and effective number of codons plot revealed that natural selection played a more important role than mutation pressure in two sequences codon usage bias. Furthermore, the gene expression level had a significant positive correlation with codon usage bias in C. australis. Highly-expressed protein coding genes exhibited a higher codon bias than lowly-expressed genes. Meanwhile, the high-expression genes tended to use G/C-ending synonymous codons. This result further verified the optimal codons usage bias and its correlation with the gene expression in C. australis.

MDR: an integrative DNA N6-methyladenine and N4-methylcytosine modification database for Rosaceae.

Eukaryotic DNA methylation has been receiving increasing attention for its crucial epigenetic regulatory function. The recently developed single-molecule real-time (SMRT) sequencing technology provides an efficient way to detect DNA N6-methyladenine (6mA) and N4-methylcytosine (4mC) modifications at a single-nucleotide resolution. The family Rosaceae contains horticultural plants with a wide range of economic importance. However, little is currently known regarding the genome-wide distribution patterns and functions of 6mA and 4mC modifications in the Rosaceae. In this study, we present an integrated DNA 6mA and 4mC modification database for the Rosaceae (MDR, http://mdr.xieslab.org). MDR, the first repository for displaying and storing DNA 6mA and 4mC methylomes from SMRT sequencing data sets for Rosaceae, includes meta and statistical information, methylation densities, Gene Ontology enrichment analyses, and genome search and browse for methylated sites in NCBI. MDR provides important information regarding DNA 6mA and 4mC methylation and may help users better understand epigenetic modifications in the family Rosaceae.

DNA N6-Methyladenosine modification role in transmitted variations from genomic DNA to RNA in Herrania umbratica.

BACKGROUND: DNA methylation is an important epigenetic modification. Recently the developed single-molecule real-time (SMRT) sequencing technology provided an efficient way to detect DNA N6-methyladenine (6mA) modification that played an important role in epigenetic and positively regulated gene expression. In addition, the gene expression was also regulated by genetic variation. However, the relationship between DNA 6mA modification and variation is still unknown. RESULTS: We collected the SMRT long-reads DNA, Illumina short reads DNA and RNA datasets from the young leaves of Herrania umbratica, and used them to detect 35,654 6mA modification sites, 829,894 DNA variations and 60,672 RNA variations respectively, among which, there are 303 DNA variations and 19 RNA variations with 6mA modification, and 57,468 transmitted genetic variations from DNA to RNA. The results illustrated that the genes with 6mA modification were significant disadvantage to mutate than those genes without modification (p-value< 4.9e-08). And result from the linear regression model showed the 6mA densities of genes were associated with the transmitted variations type 0/1 to 1/1 (p-value < 0.001). CONCLUSIONS: The variations of DNA and RNA in genes with 6mA modification were significant less than those in unmodified genes. Furthermore, the variations in 6mA modified genes were easily transmitted from DNA to RNA, especially the transmitted variation from DNA heterozygote to RNA homozygote.

A protein identification algorithm for tandem mass spectrometry by incorporating the abundance of mRNA into a binomial probability scoring model.

Peptide-spectrum matches (PSM) scoring between the experimental and theoretical spectrum is a key step in the identification of proteins using mass spectrometry (MS)-based proteomics analyses. Efficient protein identification using MS/MS data remains a challenge. The strategy of using RNA-seq data increases the number of proteins identified by re-constructing the custom search database and integrating mRNA abundance into the false discovery rate of post-PSM. However, this process lacks an algorithm that can allow the incorporation of mRNA abundance into the key scoring model of PSM. Therefore, we developed a novel PSM scoring model, which incorporates mRNA abundance for improved peptide and protein identification. In the new algorithm, abundance information of mRNA was transformed to the prior probability of protein identification and integrated to re-score in PSM using the binomial probability distribution model. Compared with other algorithms using five MS/MS datasets, the results showed that the least improvement ratios of peptide and protein groups were 3.39%-9.79% and 0.48%-8.16% in different datasets (human, rat, zebrafish, yeast, and Arabidopsis thaliana). The new strategy offers an effective solution for MS-based identification of peptides and proteins. SIGNIFICANCE: The new algorithm identifies proteins by quantifying mRNA abundance (FPKM) and incorporating it into a scoring model for peptide-spectrum matches. It is important to improve peptide and protein identification from MS/MS datasets in proteomics research.

N 6-Methyladenine DNA Modification in the Woodland Strawberry (Fragaria vesca) Genome Reveals a Positive Relationship With Gene Transcription.

N 6-methyladenine (6mA) DNA modification has been detected in several eukaryotic organisms, where it plays important roles in gene regulation and epigenetic memory maintenance. However, the genome-wide distribution patterns and potential functions of 6mA DNA modification in woodland strawberry (Fragaria vesca) remain largely unknown. Here, we examined the 6mA landscape in the F. vesca genome by adopting single-molecule real-time sequencing technology and found that 6mA modification sites were broadly distributed across the woodland strawberry genome. The pattern of 6mA distribution in the long non-coding RNA was significantly different from that in protein-coding genes. The 6mA modification influenced the gene transcription and was positively associated with gene expression, which was validated by computational and experimental analyses. Our study provides new insights into the DNA methylation in F. vesca.

ISOdb: A Comprehensive Database of Full-Length Isoforms Generated by Iso-Seq.

The accurate landscape of transcript isoforms plays an important role in the understanding of gene function and gene regulation. However, building complete transcripts is very challenging for short reads generated using next-generation sequencing. Fortunately, isoform sequencing (Iso-Seq) using single-molecule sequencing technologies, such as PacBio SMRT, provides long reads spanning entire transcript isoforms which do not require assembly. Therefore, we have developed ISOdb, a comprehensive resource database for hosting and carrying out an in-depth analysis of Iso-Seq datasets and visualising the full-length transcript isoforms. The current version of ISOdb has collected 93 publicly available Iso-Seq samples from eight species and presents the samples in two levels: (1) sample level, including metainformation, long read distribution, isoform numbers, and alternative splicing (AS) events of each sample; (2) gene level, including the total isoforms, novel isoform number, novel AS number, and isoform visualisation of each gene. In addition, ISOdb provides a user interface in the website for uploading sample information to facilitate the collection and analysis of researchers' datasets. Currently, ISOdb is the first repository that offers comprehensive resources and convenient public access for hosting, analysing, and visualising Iso-Seq data, which is freely available.

N6-Methyladenine DNA modification in Xanthomonas oryzae pv. oryzicola genome.

DNA N6-methyladenine (6mA) modifications expand the information capacity of DNA and have long been known to exist in bacterial genomes. Xanthomonas oryzae pv. Oryzicola (Xoc) is the causative agent of bacterial leaf streak, an emerging and destructive disease in rice worldwide. However, the genome-wide distribution patterns and potential functions of 6mA in Xoc are largely unknown. In this study, we analyzed the levels and global distribution patterns of 6mA modification in genomic DNA of seven Xoc strains (BLS256, BLS279, CFBP2286, CFBP7331, CFBP7341, L8 and RS105). The 6mA modification was found to be widely distributed across the seven Xoc genomes, accounting for percent of 3.80, 3.10, 3.70, 4.20, 3.40, 2.10, and 3.10 of the total adenines in BLS256, BLS279, CFBP2286, CFBP7331, CFBP7341, L8, and RS105, respectively. Notably, more than 82% of 6mA sites were located within gene bodies in all seven strains. Two specific motifs for 6 mA modification, ARGT and AVCG, were prevalent in all seven strains. Comparison of putative DNA methylation motifs from the seven strains reveals that Xoc have a specific DNA methylation system. Furthermore, the 6 mA modification of rpfC dramatically decreased during Xoc infection indicates the important role for Xoc adaption to environment.

Genome-Wide Association Studies for Five Forage Quality-Related Traits in Sorghum (Sorghum bicolor L.).

Understanding the genetic function of the forage quality-related traits, including crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), hemicellulose (HC), and cellulose (CL) contents, is essential for the identification of forage quality genes and selection of effective molecular markers in sorghum. In this study, we genotyped 245 sorghum accessions by 85,585 single-nucleotide polymorphisms (SNPs) and obtained the phenotypic data from four environments. The SNPs and phenotypic data were applied to multi-locus genome-wide association studies (GWAS) with the mrMLM software. A total of 42 SNPs were identified to be associated with the five forage quality-related traits. Moreover, three and two quantitative trait nucleotides (QTNs) were simultaneously detected among them by three and two multi-locus methods, respectively. One QTN on chromosome 5 was found to be associated simultaneously with CP, NDF, and ADF. Furthermore, 3, 2, 2, 5, and 2 candidate genes were identified to be responsible for CP, NDF, ADF, HC, and CL contents, respectively. These results provided insightful information of the forage quality-related traits and would facilitate the genetic improvement of sorghum forage quality in the future.