RNA Processing: A Practical Approach: Volume II

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Herpes simplex virus ICP27 regulates alternative pre-mRNA polyadenylation and splicing in a sequence-dependent manner. The alternative splicing program of differentiated smooth muscle cells involves concerted non-productive splicing of post-transcriptional regulators. CIT, a gene involved in neurogenic cytokinesis, is mutated in human primary microcephaly. Next-generation sequencing of hereditary hemochromatosis-related genes: Novel likely pathogenic variants found in the Portuguese population.

Becker muscular dystrophy due to an intronic splicing mutation inducing a dual dystrophin transcript. A computational approach for prediction of donor splice sites with improved accuracy. Exome sequencing explained: a practical guide to its clinical application.

RNA Processing in eukaryotes - RNA splicing, capping and editing

The RNA-binding profile of Acinus, a peripheral component of the exon junction complex, reveals its role in splicing regulation. Mutations in LTBP3 cause acromicric dysplasia and geleophysic dysplasia. IntSplice: prediction of the splicing consequences of intronic single-nucleotide variations in the human genome.

A splicing mutation of proteolipid protein 1 in Pelizaeus-Merzbacher disease. Collagen COL4A mutations are the most frequent mutations underlying adult focal segmental glomerulosclerosis. MIR retroposon exonization promotes evolutionary variability and generates species-specific expression of IGF-1 splice variants. A novel homozygous splice site mutation in NALCN identified in siblings with cachexia, strabismus, severe intellectual disability, epilepsy and abnormal respiratory rhythm.

Lynch syndrome mutation spectrum in New South Wales, Australia, including 55 novel mutations. Recognition of alternatively spliced cassette exons based on a hybrid model. Unmasking a novel disease gene NEO1 associated with autism spectrum disorders by a hemizygous deletion on chromosome 15 and a functional polymorphism. A novel homozygous splicing mutation of CASC5 causes primary microcephaly in a large Pakistani family. A targeted next-generation sequencing assay for the molecular diagnosis of genetic disorders with orodental involvement.

Allelic variation of the COMT gene in a despotic primate society: A haplotype is related to cortisol excretion in Macaca fuscata. Loss of the smallest subunit of cytochrome c oxidase, COX8A, causes Leigh-like syndrome and epilepsy. A dynamic intron retention program enriched in RNA processing genes regulates gene expression during terminal erythropoiesis. Cellular identity at the single-cell level. Mini-gene assays confirm the splicing effect of deep intronic variants in the factor VIII gene. Diagnostic Genomics and Clinical Bioinformatics. Nail—Patella Syndrome: clinical and molecular data in 55 families raising the hypothesis of a genetic heterogeneity.

Discover hidden splicing variations by mapping personal transcriptomes to personal genomes. There is variability in the attainment of developmental milestones in the CDKL5 disorder. DiffLogo: a comparative visualization of sequence motifs. Deciphering targeting rules of splicing modulator compounds: case of TG Gene activity in primary T cells infected with HIV Promoter-like epigenetic signatures in exons displaying cell type-specific splicing. Widespread intron retention diversifies most cancer transcriptomes. The functional relevance of somatic synonymous mutations in melanoma and other cancers.

Intron retention is a widespread mechanism of tumor-suppressor inactivation. Varying levels of complexity in transcription factor binding motifs. Determination of window size and identification of suitable method for prediction of donor splice sites in rice Oryza sativa genome. Cis -acting signals modulate the efficiency of programmed DNA elimination in Paramecium tetraurelia. A splicing mutation in the DMD gene detected by next-generation sequencing and confirmed by mRNA and protein analysis.

Recurrent and novel GLB1 mutations in India. Short linear motif acquisition, exon formation and alternative splicing determine a pathway to diversity for NCoR-family co-repressors. Frequency and phenotypic spectrum of germline mutations in POLE and seven other polymerase genes in patients with colorectal adenomas and carcinomas. Germline recessive mutations in PI4KA are associated with perisylvian polymicrogyria, cerebellar hypoplasia and arthrogryposis. Determination of the allelic frequency in Smith-Lemli-Opitz syndrome by analysis of massively parallel sequencing data sets.

Extensive functional analyses of RHD splice site variants: Insights into the potential role of splicing in the physiology of Rh. New splicing mutation in the choline kinase beta CHKB gene causing a muscular dystrophy detected by whole-exome sequencing. Splicing of many human genes involves sites embedded within introns. Predicting survival in head and neck squamous cell carcinoma from TP53 mutation. Non-manifesting AHI1 truncations indicate localized loss-of-function tolerance in a severe Mendelian disease gene.

Recursive splicing in long vertebrate genes. Splicing defects caused by exonic mutations in PKD1 as a new mechanism of pathogenesis in autosomal dominant polycystic kidney disease. BAP1 Missense Mutation c. Neural circular RNAs are derived from synaptic genes and regulated by development and plasticity. Interpretation of mRNA splicing mutations in genetic disease: review of the literature and guidelines for information-theoretical analysis.

Molecular characterization of leukocyte adhesion deficiency-I in Indian patients: Identification of 9 novel mutations. Real-time resolution of point mutations that cause phenovariance in mice. A review of mismatch repair gene transcripts: issues for interpretation of mRNA splicing assays. Integrated allelic, transcriptional, and phenomic dissection of the cardiac effects of titin truncations in health and disease.

The influence of Argonaute proteins on alternative RNA splicing. Detained introns are a novel, widespread class of post-transcriptionally spliced introns. Identification of deep intronic variants in 15 haemophilia A patients by next generation sequencing of the whole factor VIII gene. VaRank: a simple and powerful tool for ranking genetic variants.

Asymptotic normality in the maximum entropy models on graphs with an increasing number of parameters. PRPF8 defects cause missplicing in myeloid malignancies. In silico prediction of splice-altering single nucleotide variants in the human genome. Whole exome sequence analysis of Peters anomaly.

A novel splice-site mutation in ATP6V0A4 gene in two brothers with distal renal tubular acidosis from a consanguineous Tunisian family. Transcriptome-wide modulation of splicing by the exon junction complex. Mutations in PLK4, encoding a master regulator of centriole biogenesis, cause microcephaly, growth failure and retinopathy. Mutations in STX1B, encoding a presynaptic protein, cause fever-associated epilepsy syndromes.

Widespread intron retention in mammals functionally tunes transcriptomes.

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Transcriptional diversity during lineage commitment of human blood progenitors. Atypical RNAs in the coelacanth transcriptome. National mutation study among Danish patients with hereditary haemorrhagic telangiectasia. Genetic testing in Tunisian families with heritable retinoblastoma using a low cost approach permits accurate risk prediction in relatives and reveals incomplete penetrance in adults.

Exposing synonymous mutations. A classification of alternatively spliced cassette exons using AdaBoost-based algorithm. In silico tools for splicing defect prediction: a survey from the viewpoint of end users. Prophylactic total gastrectomy in hereditary diffuse gastric cancer: identification of two novel CDH1 gene mutations—a clinical observational study. Exonic splicing signals impose constraints upon the evolution of enzymatic activity. A first Glimpse at the genome of the Baikalian amphipod Eulimnogammarus verrucosus.

A rare sequence variant in intron 1 of THAP1 is associated with primary dystonia. In silico to in vivo splicing analysis using splicing code models. POT1 loss-of-function variants predispose to familial melanoma. BRCA1 exon 11 a model of long exon splicing regulation. Functional analysis of 11 novel GBA alleles. Functional characterization of two novel splicing mutations of glucokinase gene associated with maturity-onset diabetes of the young type 2 MODY2.

Computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors. Predominance of spliceosomal complex formation over polyadenylation site selection in TDP autoregulation. His41Arg Is a Pathogenic Mutation. Experience of targeted Usher exome sequencing as a clinical test.

ExoLocator—an online view into genetic makeup of vertebrate proteins. MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing. Predicting Alternative Splicing. Splicing Code Modeling. Lessons from postgenome-wide association studies: functional analysis of cancer predisposition loci.

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SON connects the splicing-regulatory network with pluripotency in human embryonic stem cells. A synonymous polymorphic variation in ACADM exon 11 affects splicing efficiency and may affect fatty acid oxidation. Dystrophin rescue by trans -splicing: a strategy for DMD genotypes not eligible for exon skipping approaches. Molecular and biochemical characterization of a novel intronic single point mutation in a Tunisian family with glycogen storage disease type III. Molecular basis of acid ceramidase deficiency in a neonatal form of Farber disease: Identification of the first large deletion in ASAH1 gene.

Analysis of the effects of rare variants on splicing identifies alterations in GABAA receptor genes in autism spectrum disorder individuals. Promoter directionality is controlled by U1 snRNP and polyadenylation signals. Identification of germline mutations in the cancer predisposing gene CDH1 in patients with orofacial clefts. Next-generation sequencing NGS as a diagnostic tool for retinal degeneration reveals a much higher detection rate in early-onset disease. The mechanism of alternative splicing of the X-linked NDUFB11 gene of the respiratory chain complex I, impact of rotenone treatment in neuroblastoma cells.

TrueSight: a new algorithm for splice junction detection using RNA-seq. A prevalent and three novel mutations in CYP11B1 gene identified in Chinese patients with beta hydroxylase deficiency. Phenotypic and molecular characterisation of type 3 von Willebrand disease in a cohort of Indian patients. Cystic fibrosis testing in a referral laboratory: results and lessons from a six-year period. Functional analysis of synonymous substitutions predicted to affect splicing of the CFTR gene.

A guide for functional analysis of BRCA1 variants of uncertain significance. The HIV-1 major splice donor D1 is activated by splicing enhancer elements within the leader region and the pinhibitory sequence. Splicing of internal large exons is defined by novel cis -acting sequence elements. Heterozygous de-novo mutations in ATP1A3 in patients with alternating hemiplegia of childhood: a whole-exome sequencing gene-identification study.

Neonatal progeria: increased ratio of progerin to lamin A leads to progeria of the newborn. Globozoospermia is mainly due to DPY19L2 deletion via non-allelic homologous recombination involving two recombination hotspots. Next generation sequencing for molecular diagnosis of neuromuscular diseases. A splice site mutation in a gene encoding for PDK4, a mitochondrial protein, is associated with the development of dilated cardiomyopathy in the Doberman pinscher.

Nucleosome organization in sequences of alternative events in human genome. Cryptic transcripts from a ubiquitous plasmid origin of replication confound tests for cis-regulatory function. MUTYH gene expression and alternative splicing in controls and polyposis patients. Identification of allele-specific alternative mRNA processing via transcriptome sequencing. Advances in genetics show the need for extending screening strategies for autosomal dominant hypercholesterolaemia. Mutations in CIZ1 cause adult onset primary cervical dystonia.

Molecular analysis of the UROD gene in 17 Argentinean patients with familial porphyria cutanea tarda: Characterization of four novel mutations. Exon-centric regulation of pyruvate kinase M alternative splicing via mutually exclusive exons. Molecular and functional analysis of two new MTTP gene mutations in an atypical case of abetalipoproteinemia. Bioinformatic Analysis of Splicing Events.

Detection of a large rearrangement in PALB2 in Spanish breast cancer families with male breast cancer. Functional characterization of splicing and ligand-binding domain variants in the LDL receptor.

Functional characterization and targeted correction of ATM mutations identified in Japanese patients with ataxia-telangiectasia. Usher syndrome type 2 caused by activation of an USH2A pseudoexon: Implications for diagnosis and therapy. Bioinformatics and Mutations Leading to Exon Skipping. GC content around splice sites affects splicing through pre-mRNA secondary structures. Clinical and molecular characterization of a cohort of patients with novel nucleotide alterations of the Dystrophin gene detected by direct sequencing.

Insertion of 16 amino acids in the BAR domain of the oligophrenin 1 protein causes mental retardation and cerebellar hypoplasia in an Italian family. Germline mutations in RAD51D confer susceptibility to ovarian cancer. Computational discovery of human coding and non-coding transcripts with conserved splice sites. Splicing signals in the human hemoglobin genes at the sequence and folding levels. Expression of ribosomal protein L22e family members in Drosophila melanogaster: rpLlike is differentially expressed and alternatively spliced.

Prediction of single-nucleotide substitutions that result in exon skipping: identification of a splicing silencer in BRCA1 exon 6. Nonsense mutation-associated Becker muscular dystrophy: interplay between exon definition and splicing regulatory elements within the DMD gene. Using bioinformatics to predict the functional impact of SNVs. Autoregressive modeling of DNA features for short exon recognition. A method of predicting changes in human gene splicing induced by genetic variants in context of cis-acting elements.

Unifying generative and discriminative learning principles. Apples and oranges: avoiding different priors in Bayesian DNA sequence analysis. Statistical analysis strategies for association studies involving rare variants. Analysis of LDLR mRNA in patients with familial hypercholesterolemia revealed a novel mutation in intron 14, which activates a cryptic splice site.

Systems analysis of alternative splicing and its regulation. Position-dependent alternative splicing activity revealed by global profiling of alternative splicing events regulated by PTB. Evolution of alternative splicing in primate brain transcriptomes. Overlapping splicing regulatory motifs—combinatorial effects on splicing. Mutational screening of VSX1 in keratoconus patients from the European population. Novel exon nucleotide substitution at the splice junction causes a neonatal Marfan syndrome. Fast and SNP-tolerant detection of complex variants and splicing in short reads.

The deep intronic c. Transposable elements in disease-associated cryptic exons. Loss of N-acetylglucosaminephosphotransferase gamma subunit due to intronic mutation in GNPTG causes mucolipidosis type III gamma: Implications for molecular and cellular diagnostics. Comparative in silico analyses and experimental validation of novel splice site and missense mutations in the genes MLH1 and MSH2.

Gene Structure Submodels. Autosomal recessive inheritance of classic Bethlem myopathy. Splice site strength—dependent activity and genetic buffering by poly-G runs. Disease-causing mutations improving the branch site and polypyrimidine tract: Pseudoexon activation of LINE-2 and antisense Alu lacking the poly T -tail. Human Splicing Finder: an online bioinformatics tool to predict splicing signals.

Antisense therapeutics for neurofibromatosis type 1 caused by deep intronic mutations. Aromatic l-amino acid decarboxylase deficiency in Taiwan. Ab initio exon definition using an information theory-based approach. Molecular and functional analysis of the HEXB gene in Italian patients affected with Sandhoff disease: identification of six novel alleles. A PEX10 defect in a patient with no detectable defect in peroxisome assembly or metabolism in cultured fibroblasts.

Functional and computational assessment of missense variants in the ataxia-telangiectasia mutated ATM gene: mutations with increased cancer risk. Mutation analysis of the MDM4gene in German breast cancer patients.

Rna Processing a Practical Approach Volume 2 - AbeBooks

Fast splice site detection using information content and feature reduction. Using estimative reaction free energy to predict splice sites and their flanking competitors. Prediction and assessment of splicing alterations: implications for clinical testing. Evaluation of in silico splice tools for decision-making in molecular diagnosis.

Exon skipping mutations in collagen VI are common and are predictive for severity and inheritance. Spontaneous symmetry breaking in genome evolution. Transcriptional control of human pregulated genes. Patterns of missplicing caused by RB1 gene mutations in patients with retinoblastoma and association with phenotypic expression. Modeling regulatory sites with higher order position-dependent weight matrices.

DMD pseudoexon mutations: splicing efficiency, phenotype, and potential therapy. Features generated for computational splice-site prediction correspond to functional elements. Coevolutionary networks of splicing cis-regulatory elements. Comparison with other European studies. Global control of aberrant splice-site activation by auxiliary splicing sequences: evidence for a gradient in exon and intron definition.

Increased progerin expression associated with unusual LMNA mutations causes severe progeroid syndromes.

Global donor and acceptor splicing site kinetics in human cells

A protocol for imaging alternative splicing regulation in vivo using fluorescence reporters in transgenic mice. Does distance matter? Putting numbers on the network connections. A deep intronic mutation in the RB1 gene leads to intronic sequence exonisation. Molecular characterization of Portuguese patients with mucopolysaccharidosis type II shows evidence that the IDS gene is prone to splicing mutations.

Splice site identification using probabilistic parameters and SVM classification. Optimized mixed Markov models for motif identification. Evidence implicating BRD1 with brain development and susceptibility to both schizophrenia and bipolar affective disorder. Comprehensive splice-site analysis using comparative genomics. Phenotypic consequences of branch point substitutions. Gene finding using multiple related species: a classification approach. The average quality values for each sequence position are indicated by a thin curved line. The number of reads after filtering was reduced to 2,, The Y-axis on the graph shows the quality scores.

A higher score reflects better base call. The background of the graph divides the Y-axis into high Upper , moderate Center , and poor Lower quality calls. B Effect of filtering sequence reads. The sequence reads obtained before and after filtering, as indicated in A, were mapped to the reference genome and visualized. Mismatches are indicated by black circles. Williams et al. Therefore, if trimming is applied, extreme care should be taken, and other measures, such as length filtering, should be considered in the preprocessing pipeline to minimize the introduction of unwanted bias.

In our follow-up examination of the reads obtained using an Illumina MiSeq platform, we concluded that for relatively long sequencing reads, such as or bases, with low sequence errors, aggressive trimming of sequencing reads is generally no longer necessary for estimating the gene expression level. In the following section, we propose correction of the reference sequence using RNA-Seq reads in cases in which the genome sequence of the same strain used in the RNA-Seq experiment is not available to avoid mismatches between the RNA-Seq reads and the reference.

The removal and trimming of unreliable sequences are necessary for this purpose. The pipeline effectively works for microorganisms, genome sequences, and gene models, which are reliable due to significant correction and curation by the efforts of a large number of researchers. Typical examples of such microorganism are Escherichia coli , Bacillus subtilis , Saccharomyces cerevisiae , Schizosaccharomyces pombe , Neurospora crassa , and Aspergillus nidulans , which are known as model organisms.

Among microorganisms, filamentous fungi generally have the largest genome sizes and introns in most existing genes and are thus thought to require a pipeline with the highest performance and various functions for the analyses. Furthermore, filamentous fungi are potential producers of various secondary metabolites, which are economically important and have a large number of highly diverse secondary metabolism-related genes. Thus, the genomes of filamentous fungi and actinomycetes remain attractive targets in this field. Example of the RNA-Seq analysis pipeline. A Typical simple pipeline. Next, tools such as Cufflinks count the number of reads mapped to each genomic feature and extract differentially expressed genes DEGs.

B Proposed pipeline for microorganisms whose reference sequence and gene models are not extensively corrected or curated. GenRecon is a Perl script that outputs a consensus sequence based on output by the variant detect tool, VarScan [11]. SpliceSelect is a Perl script that integrates splice site positions from multiple TopHat output files. RNA-Seq reads can be analyzed without their corresponding genome sequence as a reference through the de novo assembly of the reads. However, we do not include the de novo assembly of RNA-Seq reads in this chapter because sequencing the genome of a microorganism using next-generation sequencers, such as Illumina technology, is relatively inexpensive in terms of cost and time.

For example, we have used the improved pipeline for the analysis of the genome sequences obtained from a short-read sequencer, SOLiD xl, in combination with the de novo assembly pipeline that the manufacturer developed for mate-paired sequences [ 8 ] with successive automatic annotation. Based on the assumption that the genome sequence is available as a reference for the microorganism, the strategy of mapping the transcriptome is not included in this chapter. The sequencing platforms described above are widely used, and bioinformatics tools have been extensively developed for each platform.

The characteristics of the errors depend on the sequencing platform, such as those manufactured by Illumina, Life Technologies, and Pacific Bioscience. The number of reads, read length, and data format also varies by platform. Furthermore, more than one platform, such as a combination of Illumina and Pacific Bioscience or Life Technologies and Illumina [ 9 ], might be used, which also requires a specific methodology for obtaining reasonable results. Most of the mapping tools search the nucleotide sequences with a similarity greater than a certain threshold value in the reference sequence for each RNA-Seq read.

Multiple mapping algorithms are widely used to accurately identify the most homologous positions on the reference sequence. However, a shorter read length than the repetitive elements in the reference sequence and sequencing errors complicates the problem. A typical RNA-Seq experiment consists of the sequencing of both ends of a cDNA fragment to generate two reads a read pair separated by a sequence of variable length. The accurate alignment of these read pairs is essential to the downstream analysis of an RNA-Seq experiment, but RNA-Seq read alignment is challenging due to the noncontiguous nature of mRNA transcripts resulting from the existence of introns in eukaryotic genes.

Software programs that support splice alignment use different strategies from several perspectives [ 15 ]. The method of determining the position on the reference sequence where a read is mapped can be roughly classified into two groups: exon first and seed and extend.

Exon-first methods, such as TopHat, utilize a two-step process. First, they map reads to the reference sequence without allowing large gaps. Subsequently, the unmapped reads are divided into short segments, and each is independently aligned to the reference sequence. The discontinued region on the genome where contiguous segments are mapped is treated as a candidate of two connected exons obtained by splice alignment.

The exon-first approach is the most effective in cases in which a majority of the reads can be mapped without gaps. If retrotransposed genes or pseudogenes originating from transcripts with multiple exons are present in the genome sequence, software that employs the exon-first approach might preferentially map the reads to the retrotransposed region. In seed-and-extend methods, such as STAR, reads are divided into short seeds k-mers , the positions where they are present in the genome are searched, and alignments are built and extended using this information.

Seed-and-extend methods are generally considered more sensitive but slower than exon-first methods. However, with great efforts, excellent software programs using seed-and-extend or hybrid methods have been developed in recent years. Substantial effort has been spared, and software using the seed-and-extend method has become sufficiently fast. In a typical expression analysis of microorganisms using RNA-Seq, the computational processing time required for mapping reads to the reference genome sequence is no longer a major problem.

For transcript quantification, software such as Kallisto [ 16 ] and Salmon [ 17 ], which use newer algorithms that do not require the pre-mapping of reads to a reference sequence, has become increasingly faster. A very large-scale expression analysis with RNA-Seq could be performed using this type of software. Widely distributed strains, such as S. The mutation frequency can be decreased by careful handling, such as decreasing the number of inoculation processes and avoiding stressful conditions. However, the introduction of mutations cannot be completely prevented due to spontaneous mutation, which is a natural characteristic of all organisms.

The basic procedure for resolving this problem is to sequence the genome of the strain for which RNA-Seq is performed. However, because the sequencing strategy, including sample preparation, for genome sequencing is different from that used for RNA-Seq and because of the cost- and time-saving requirements, RNA-Seq data sometime have to be analyzed using the reference sequence deposited in a public database. To overcome this problem without losing reliability, we have addressed the correction of the reference sequence using RNA-Seq reads based on two methods: 1 RNA-Seq reads are mapped to the reference sequence using the spliced mapper mentioned in the previous section, and the reference sequence is corrected using the consensus of the mapped reads.

The former method was almost completely automatable and worked well for small variations, such as single-base substitution. With the latter method, it was necessary to process a number of isoform candidates at the same loci of the reference genome outputted by the transcriptome assembler, which required time and effort to tune the various parameters and threshold values. Unless the genome has undergone a complicated structural change from the reference sequence, the former method is sufficient.

After correcting the reference sequence, the reads were again mapped to the corrected reference sequence. This strategy worked fairly well. Typical examples of the gene modeling problem are found by analyzing filamentous fungi. Industrially important fungi are often isolated due to their production of useful secondary metabolites.

Because their genomes are generally unknown, sequencing and successive gene modeling are indispensable but are performed by a limited number of researchers with a limited amount of knowledge. In such cases, RNA-Seq reads can be used to correct gene models prior to expression analysis to obtain accurate expression levels. Several researchers have attempted to improve the accuracy of predicting protein-coding genes, and these attempts have included the use of RNA-Seq.

After RNA-Seq reads are mapped to the genome, spliced mapped reads can be used as valuable information for gene finding. In recent years, gene prediction software using RNA-Seq for both model training and gene prediction with the trained model has been developed and has demonstrated high accuracy for gene structure prediction [ 19 , 20 ]. The training of conventional gene finding depends on the gene models in the genomes of species other than the target one.

However, the gene models of the species already deposited in public databases have not always been experimentally confirmed but are the results of predictions based on the results of other genomes. Thus, the use of the results of RNA-Seq read mapping, which provides direct information of the CDSs of the target species, in combination with recent gene finding algorithms, enables significant improvement in gene modeling.

In this pipeline, exon-intron boundary information is predicted using mapped RNA-Seq, and coding sequence candidates is obtained by homology searches between the genome sequence and protein sequence databases, such as the Swiss-Prot database. This pipeline worked well for gene prediction of non-model organisms and has been used for the genome analysis of various filamentous fungi.

The improvements in the predicted gene structures are thought to contribute to more accurate RNA-Seq expression quantification as transcript references. Because the degradation will not be complete, the ribosomal RNA sequences have to be removed after sequencing by searching the consensus sequence in the reads. Another problem is that bacterial genes are sometimes overlapped on the genome and might be transcribed even in different orientations. To solve this problem, strand-specific RNA-Seq has the advantage of obtaining useful information for gene modeling.

However, because bacterial mRNA does not have poly-A tails, as described above, preparation of a strand-specific library is more difficult than the preparation of eukaryotic mRNA. A strand-specific library for bacteria can be prepared basically by two methods [ 21 ]: i adapter ligation to the first strand synthesized in the cDNA preparation [ 22 ] and ii chemical modification of RNA or the second strand of the cDNA [ 23 — 25 ].

Expression analysis with RNA-Seq typically begins by counting the number of reads mapped to reference transcript sequences. We can resolve the various mapping problems mentioned above and perform mapping to the genome with accurately predicted gene structures or assembled transcript sequences using transcriptome assembly software.

Microarrays are widely used for the quantification of the abundance of mRNAs corresponding to genes. In microarray experiments, the gene expression level is measured as a continuous value, intensity. RNA-Seq differs from microarrays in that it addresses nonnegative discrete values, i. Analytical methods for microarray data that assume a Gaussian distribution, such as linear discriminant analysis, might not perform as well for RNA-Seq data with a discrete distribution.

Let us consider the problem of quantifying gene expression levels using discrete RNA-Seq data and a related problem, namely, the identification of differentially expressed genes DEGs between conditions. Thus, the total number of observed reads for a transcript is proportional to the number of expressed mRNAs for the transcript multiplied by the length of the transcript. To compensate for this bias, it is a common practice to divide the number of mapped reads by the transcript length.

Unfortunately, this correction is not sufficient to test whether gene expression differs between conditions. Oshlack and Wakefield showed that the power of a t -test of the count data, regardless of whether it is divided by the length of the transcript, is proportional to the square root of the length of the transcript [ 26 ]. Therefore, for a given expression level, the test becomes more significant for longer transcripts. Many methods have been developed for assessing differential expression from RNA-Seq data. Count data, such as the counts of mapped fragments of RNA-Seq data, are often modeled as a Poisson distribution.

The Poisson distribution has equal mean and variance values, and DEGs can be identified by conducting a likelihood ratio test between conditions. Real RNA-Seq data often exhibits overdispersion. The count data measured via RNA-Seq often has a variance that is larger than the mean due to various biases and errors as well as length bias. A negative binomial distribution is widely used for modeling such cases.

Several RNA-Seq data analysis software packages incorporating these models have been developed. Soneson and Delorenzi evaluated eleven software packages that implemented various methods to model count data for differential expression analyses of RNA-Seq data [ 27 ]. When designing experiments to analyze differential expressions using RNA-Seq, it is necessary to carefully consider the type of method used for DEG extraction and the amount of biological replications that are needed.

Three replicates often give reproducible results in successive independent experiments in terms of the assignment of a gene s with the expression of interest, although a single experiment often fails to yield reproducible results. The comparison of the transcriptome for each condition often shows a large number of DEGs. Therefore, outlining the changes in the expression profile by extracting features common to genes whose expression intensity has changed is a common approach.

Gene set enrichment analysis GSEA is a popular method for condensing information from gene expression profiles into a summary of pathways or functional groups. However, most RNA-Seq data obtained so far have only small replicates, which enforces application of the gene-permuting GSEA method or preranked GSEA , resulting in a great number of false positives due to the inter-gene correlation in each gene set.

Yoon et al. As shown recently, RNA-Seq also enables the detection of alternative slicing from various fungi and higher organisms, such as mammals and plants. Both tools can detect isoforms of transcripts based on mapping information generated by TopHat using a graph-based method. These tools are widely used for the analysis of higher organisms, such as mammals and plants, but not fungi. Splicing variants have been found in various fungi, including Aspergillus oryzae [ 32 ], Magnaporthe grisea [ 33 ], Cryptococcus neoformans [ 34 ], and Trichoderma longibrachiatum [ 35 ], by deep RNA-Seq despite their significantly lower frequency compared with that found in higher organisms.