The development of functional mapping by three sex-related loci on the third whorl of different sex types of Carica papaya L

Carica papaya L. is an important economic crop worldwide and is used as a model plant for sex-determination research. To study the different flower sex types, we screened sex-related genes using alternative splicing sequences (AS-seqs) from a transcriptome database of the three flower sex types, i.e., males, females, and hermaphrodites, established at 28 days before flowering using 15 bacterial artificial chromosomes (BACs) of C. papaya L. After screening, the cDNA regions of the three sex-related loci, including short vegetative phase-like (CpSVPL), the chromatin assembly factor 1 subunit A-like (CpCAF1AL), and the somatic embryogenesis receptor kinase (CpSERK), which contained eight sex-related single-nucleotide polymorphisms (SNPs) from the different sex types of C. papaya L., were genotyped using high-resolution melting (HRM). The three loci were examined regarding the profiles of the third whorl, as described below. CpSVPL, which had one SNP associated with the three sex genotypes, was highly expressed in the male and female sterile flowers (abnormal hermaphrodite flowers) that lacked the fourth whorl structure. CpCAF1AL, which had three SNPs associated with the male genotype, was highly expressed in male and normal hermaphrodite flowers, and had no AS-seqs, whereas it exhibited low expression and an AS-seqs in intron 11 in abnormal hermaphrodite flowers. Conversely, carpellate flowers (abnormal hermaphrodite flowers) showed low expression of CpSVPL and AS-seqs in introns 5, 6, and 7 of CpSERK, which contained four SNPs associated with the female genotype. Specifically, the CpSERK and CpCAF1AL loci exhibited no AS-seq expression in the third whorl of the male and normal hermaphrodite flowers, respectively, and variance in the AS-seq expression of all other types of flowers. Functional mapping of the third whorl of normal hermaphrodites indicated no AS-seq expression in CpSERK, low CpSVPL expression, and, for CpCAF1AL, high expression and no AS-seq expression on XY^h-type chromosomes.

A termite symbiotic mushroom maximizing sexual activity at growing tips of vegetative hyphae

BACKGROUND

Termitomyces mushrooms are mutualistically associated with fungus-growing termites, which are widely considered to cultivate a monogenotypic Termitomyces symbiont within a colony. Termitomyces cultures isolated directly from termite colonies are heterokaryotic, likely through mating between compatible homokaryons.

RESULTS

After pairing homokaryons carrying different haplotypes at marker gene loci MIP and RCB from a Termitomyces fruiting body associated with Odontotermes formosanus, we observed nuclear fusion and division, which greatly resembled meiosis, during each hyphal cell division and conidial formation in the resulting heterokaryons. Surprisingly, nuclei in homokaryons also behaved similarly. To confirm if meiotic-like recombination occurred within mycelia, we constructed whole-genome sequencing libraries from mycelia of two homokaryons and a heterokaryon resulting from mating of the two homokaryons. Obtained reads were aligned to the reference genome of Termitomyces sp. J132 for haplotype reconstruction. After removal of the recombinant haplotypes shared between the heterokaryon and either homokaryons, we inferred that 5.04% of the haplotypes from the heterokaryon were the recombinants resulting from homologous recombination distributed genome-wide. With RNA transcripts of four meiosis-specific genes, including SPO11, DMC1, MSH4, and MLH1, detected from a mycelial sample by real-time quantitative PCR, the nuclear behavior in mycelia was reconfirmed meiotic-like.

CONCLUSION

Unlike other basidiomycetes where sex is largely restricted to basidia, Termitomyces maximizes sexuality at somatic stage, resulting in an ever-changing genotype composed of a myriad of coexisting heterogeneous nuclei in a heterokaryon. Somatic meiotic-like recombination may endow Termitomyces with agility to cope with termite consumption by maximized genetic variability.

Hepatocellular carcinoma-associated single-nucleotide variants and deletions identified by the use of genome-wide high-throughput analysis of hepatitis B virus

This study investigated hepatitis B virus (HBV) single-nucleotide variants (SNVs) and deletion mutations linked with hepatocellular carcinoma (HCC). Ninety-three HCC patients and 108 non-HCC patients were enrolled for HBV genome-wide next-generation sequencing (NGS) analysis. A systematic literature review and a meta-analysis were performed to validate NGS-defined HCC-associated SNVs and deletions. The experimental results identified 60 NGS-defined HCC-associated SNVs, including 41 novel SNVs, and their pathogenic frequencies. Each SNV was specific for either genotype B (n = 24) or genotype C (n = 34), except for nt53C, which was present in both genotypes. The pathogenic frequencies of these HCC-associated SNVs showed a distinct U-shaped distribution pattern. According to the meta-analysis and literature review, 167 HBV variants from 109 publications were categorized into four levels (A-D) of supporting evidence that they are associated with HCC. The proportion of NGS-defined HCC-associated SNVs among these HBV variants declined significantly from 75% of 12 HCC-associated variants by meta-analysis (Level A) to 0% of 10 HCC-unassociated variants by meta-analysis (Level D) (P < 0.0001). PreS deletions were significantly associated with HCC, in terms of deletion index, for both genotypes B (P = 0.030) and C (P = 0.049). For genotype C, preS deletions involving a specific fragment (nt2977-3013) were significantly associated with HCC (HCC versus non-HCC, 6/34 versus 0/32, P = 0.025). Meta-analysis of preS deletions showed significant association with HCC (summary odds ratio 3.0; 95% confidence interval 2.3-3.9). Transfection of Huh7 cells showed that all of the five novel NGS-defined HCC-associated SNVs in the small surface region influenced hepatocarcinogenesis pathways, including endoplasmic reticulum-stress and DNA repair systems, as shown by microarray, real-time polymerase chain reaction and western blot analysis. Their carcinogenic mechanisms are worthy of further research. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

The genome and transcriptome of Phalaenopsis yield insights into floral organ development and flowering regulation

The Phalaenopsis orchid is an important potted flower of high economic value around the world. We report the 3.1 Gb draft genome assembly of an important winter flowering Phalaenopsis ‘KHM190’ cultivar. We generated 89.5 Gb RNA-seq and 113 million sRNA-seq reads to use these data to identify 41,153 protein-coding genes and 188 miRNA families. We also generated a draft genome for Phalaenopsis pulcherrima ‘B8802,’ a summer flowering species, via resequencing. Comparison of genome data between the two Phalaenopsis cultivars allowed the identification of 691,532 single-nucleotide polymorphisms. In this study, we reveal that the key role of PhAGL6b in the regulation of labellum organ development involves alternative splicing in the big lip mutant. Petal or sepal overexpressing PhAGL6b leads to the conversion into a lip-like structure. We also discovered that the gibberellin pathway that regulates the expression of flowering time genes during the reproductive phase change is induced by cool temperature. Our work thus depicted a valuable resource for the flowering control, flower architecture development, and breeding of the Phalaenopsis orchids.

Aligning to the sample-specific reference sequence to optimize the accuracy of next-generation sequencing analysis for hepatitis B virus

Background

Hepatitis B virus (HBV) quasispecies are crucial in the pathogenesis of chronic liver disease. Next-generation sequencing (NGS) is powerful for identifying viral quasispecies. To improve mapping quality and single nucleotide variant (SNV) calling accuracy in the NGS analysis of HBV, we compared different mapping references, including the sample-specific reference sequence, same genotype sequences and different genotype sequences, according to the sample.

Methods

Real Illumina HBV datasets from 86 patients, and simulated datasets from 158 HBV strains in the GenBank database, were used to assess mapping quality. SNV calling accuracy was evaluated using different mapping references to align Real Illumina datasets from a single HBV clone.

Results

Using the sample-specific reference sequence as a mapping reference produced the largest number of mappable reads and coverages. With a different genotype mapping reference, the consensus sequence derived from the Real Illumina datasets of the single HBV clone showed 21 false SNV callings in polymerase and surface genes, the regions most divergent between the mapping reference and this HBV clone. A ~6 % coverage of most of these false SNVs was yielded even with a same genotype mapping reference, but none with the sample-specific reference sequence.

Conclusions

Using sample-specific reference sequences as a mapping reference in NGS analysis optimized mapping quality and the SNV calling accuracy for HBV quasispecies.

Electronic supplementary material

The online version of this article (doi:10.1007/s12072-015-9645-x) contains supplementary material, which is available to authorized users.

Global analyses of small interfering RNAs derived from Bamboo mosaic virus and its associated satellite RNAs in different plants

BACKGROUND

Satellite RNAs (satRNAs), virus parasites, are exclusively associated with plant virus infection and have attracted much interest over the last 3 decades. Upon virus infection, virus-specific small interfering RNAs (vsiRNAs) are produced by dicer-like (DCL) endoribonucleases for anti-viral defense. The composition of vsiRNAs has been studied extensively; however, studies of satRNA-derived siRNAs (satsiRNAs) or siRNA profiles after satRNA co-infection are limited. Here, we report on the small RNA profiles associated with infection with Bamboo mosaic virus (BaMV) and its two satellite RNAs (satBaMVs) in Nicotiana benthamiana and Arabidopsis thaliana.

METHODOLOGY/PRINCIPAL FINDINGS

Leaves of N. benthamiana or A. thaliana inoculated with water, BaMV alone or co-inoculated with interfering or noninterfering satBaMV were collected for RNA extraction, then large-scale Solexa sequencing. Up to about 20% of total siRNAs as BaMV-specific siRNAs were accumulated in highly susceptible N. benthamiana leaves inoculated with BaMV alone or co-inoculated with noninterfering satBaMV; however, only about 0.1% of vsiRNAs were produced in plants co-infected with interfering satBaMV. The abundant region of siRNA distribution along BaMV and satBaMV genomes differed by host but not by co-infection with satBaMV. Most of the BaMV and satBaMV siRNAs were 21 or 22 nt, of both (+) and (-) polarities; however, a higher proportion of 22-nt BaMV and satBaMV siRNAs were generated in N. benthamiana than in A. thaliana. Furthermore, the proportion of non-viral 24-nt siRNAs was greatly increased in N. benthamiana after virus infection.

CONCLUSIONS/SIGNIFICANCE

The overall composition of vsiRNAs and satsiRNAs in the infected plants reflect the combined action of virus, satRNA and different DCLs in host plants. Our findings suggest that the structure and/or sequence demands of various DCLs in different hosts may result in differential susceptibility to the same virus. DCL2 producing 24-nt siRNAs under biotic stresses may play a vital role in the antiviral mechanism in N. benthamiana.

Fast splice site detection using information content and feature reduction

BACKGROUND

Accurate identification of splice sites in DNA sequences plays a key role in the prediction of gene structure in eukaryotes. Already many computational methods have been proposed for the detection of splice sites and some of them showed high prediction accuracy. However, most of these methods are limited in terms of their long computation time when applied to whole genome sequence data.

RESULTS

In this paper we propose a hybrid algorithm which combines several effective and informative input features with the state of the art support vector machine (SVM). To obtain the input features we employ information content method based on Shannon's information theory, Shapiro's score scheme, and Markovian probabilities. We also use a feature elimination scheme to reduce the less informative features from the input data.

CONCLUSION

In this study we propose a new feature based splice site detection method that shows improved acceptor and donor splice site detection in DNA sequences when the performance is compared with various state of the art and well known methods.

Splice site identification using probabilistic parameters and SVM classification

BACKGROUND

Recent advances and automation in DNA sequencing technology has created a vast amount of DNA sequence data. This increasing growth of sequence data demands better and efficient analysis methods. Identifying genes in this newly accumulated data is an important issue in bioinformatics, and it requires the prediction of the complete gene structure. Accurate identification of splice sites in DNA sequences plays one of the central roles of gene structural prediction in eukaryotes. Effective detection of splice sites requires the knowledge of characteristics, dependencies, and relationship of nucleotides in the splice site surrounding region. A higher-order Markov model is generally regarded as a useful technique for modeling higher-order dependencies. However, their implementation requires estimating a large number of parameters, which is computationally expensive.

RESULTS

The proposed method for splice site detection consists of two stages: a first order Markov model (MM1) is used in the first stage and a support vector machine (SVM) with polynomial kernel is used in the second stage. The MM1 serves as a pre-processing step for the SVM and takes DNA sequences as its input. It models the compositional features and dependencies of nucleotides in terms of probabilistic parameters around splice site regions. The probabilistic parameters are then fed into the SVM, which combines them nonlinearly to predict splice sites. When the proposed MM1-SVM model is compared with other existing standard splice site detection methods, it shows a superior performance in all the cases.

CONCLUSION

We proposed an effective pre-processing scheme for the SVM and applied it for the identification of splice sites. This is a simple yet effective splice site detection method, which shows a better classification accuracy and computational speed than some other more complex methods.