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Lung cancer is a leading cause of cancer related morbidity and mortality globally, and carries a dismal prognosis. Improved understanding of the biology of cancer is required to improve patient outcomes. Next-generation sequencing (NGS) is a powerful tool for whole genome characterisation, enabling comprehensive examination of somatic mutations that drive oncogenesis. Most NGS methods are based on polymerase chain reaction (PCR) amplification of platform-specific DNA fragment libraries, which are then sequenced. These techniques are well suited to high-throughput sequencing and are able to detect the full spectrum of genomic changes present in cancer. However, they require considerable investments in time, laboratory infrastructure, computational analysis and bioinformatic support. Next-generation sequencing has been applied to studies of the whole genome, exome, transcriptome and epigenome, and is changing the paradigm of lung cancer research and patient care. The results of this new technology will transform current knowledge of oncogenic pathways and provide molecular targets of use in the diagnosis and treatment of cancer. Somatic mutations in lung cancer have already been identified by NGS, and large scale genomic studies are underway. Personalised treatment strategies will improve care for those likely to benefit from available therapies, while sparing others the expense and morbidity of futile intervention. Organisational, computational and bioinformatic challenges of NGS are driving technological advances as well as raising ethical issues relating to informed consent and data release. Differentiation between driver and passenger mutations requires careful interpretation of sequencing data. Challenges in the interpretation of results arise from the types of specimens used for DNA extraction, sample processing techniques and tumour content. Tumour heterogeneity can reduce power to detect mutations implicated in oncogenesis. Next-generation sequencing will facilitate investigation of the biological and clinical implications of such variation. These techniques can now be applied to single cells and free circulating DNA, and possibly in the future to DNA obtained from body fluids and from subpopulations of tumour. As costs reduce, and speed and processing accuracy increase, NGS technology will become increasingly accessible to researchers and clinicians, with the ultimate goal of improving the care of patients with lung cancer.

Recent technological advances that allow faster and cheaper DNA sequencing are now driving biological and medical research. In this review, we provide an overview of state-of-the-art next-generation sequencing (NGS) platforms and their applications, including in genome sequencing and resequencing, transcriptional profiling (RNA-Seq) and high-throughput survey of DNA-protein interactions (ChIP-Seq) and of the epigenome. Particularly, we focus on how new methods made possible by NGS can help unravel the biological and genetic mechanisms of aging, longevity and age-related diseases. In the same way, however, NGS platforms open discovery not available before, they also give rise to new challenges, in particular in processing, analyzing and interpreting the data. Bioinformatics and software issues plus statistical difficulties in genome-wide studies are discussed, as well as the use of targeted sequencing to decrease costs and facilitate statistical analyses. Lastly, we discuss a number of methods to gather biological insights from massive amounts of data, such as functional enrichment, transcriptional regulation and network analyses. Although in the fast-moving field of NGS new platforms will soon take center stage, the approaches made possible by NGS will be at the basis of molecular biology, genetics and systems biology for years to come, making them instrumental for research on aging.

Next generation sequencing has revolutionized the status of biological research. For a long time, the gold standard of DNA sequencing was considered to be the Sanger method. However, in 2005, commercial launching of next generation sequencing has made it possible to generate massively parallel and high resolution DNA sequence data. Its usefulness in various genomic applications such as genome-wide detection of SNPs, DNA methylation profiling, mRNA expression profiling, whole-genome re-sequencing and so on are now well recognized. There are several platforms for generating next generation sequencing (NGS) data which we briefly discuss in this mini overview. With new technologies come new challenges for the data analysts. This mini review attempts to present a collection of selected topics in the current development of statistical methods dealing with these novel data types. We believe that knowing the advances and bottlenecks of this technology will help the researchers to benchmark the analytical tools dealing with these data and will pave the path for its proper application into clinical diagnostics.

This article reviews basic concepts, general applications, and the potential impact of next-generation sequencing (NGS) technologies on genomics, with particular reference to currently available and possible future platforms and bioinformatics. NGS technologies have demonstrated the capacity to sequence DNA at unprecedented speed, thereby enabling previously unimaginable scientific achievements and novel biological applications. But, the massive data produced by NGS also presents a significant challenge for data storage, analyses, and management solutions. Advanced bioinformatic tools are essential for the successful application of NGS technology. As evidenced throughout this review, NGS technologies will have a striking impact on genomic research and the entire biological field. With its ability to tackle the unsolved challenges unconquered by previous genomic technologies, NGS is likely to unravel the complexity of the human genome in terms of genetic variations, some of which may be confined to susceptible loci for some common human conditions. The impact of NGS technologies on genomics will be far reaching and likely change the field for years to come.

Recent advances in high-throughput technologies have transformed methodologies employed to study cell-specific epigenomes and the approaches to investigate complex cellular phenotypes. Application of next-generation sequencing technology in the skeletal muscle differentiation field is rapidly extending our knowledge on how chromatin modifications, transcription factors and chromatin regulators orchestrate gene expression pathways guiding myogenesis. Here, we review recent biological insights gained by the application of next-generation sequencing techniques to decode the epigenetic profile and gene regulatory networks underlying skeletal muscle differentiation.

High throughput RNA sequencing (RNA-Seq) is becoming increasingly utilized as the technology of choice to detect and quantify known and novel transcripts. Multiple next-generation sequencing (NGS) platforms are available that enable transcriptome profiling through RNA-Seq workflows. Demonstrations of the power of RNA-Seq to profile the well annotated transcriptome and also identify novel transcribed regions, gene fusions, and even identify novel classes of RNA are rapidly increasing in the field of RNA research. Our aim has been to develop library preparation methods and tools that aid in the reliable generation of libraries for next generation sequencing from total RNA. Reported here are results from the development of the Ambion® RNA-Seq Library Construction kit optimized for sequencing on the Illumina® next generation sequencing instruments. We show results from two protocols utilizing the same reagents that allow generation of RNA-Seq libraries targeting either the small RNA fraction of total RNA, or the whole transcriptome which includes transcripts larger than 100 base pairs. Results are reported from Illumina® Genome Analyzer II sequencing of both small RNA and transcriptome libraries with a focus on mapping to the miRBase and RefSeq references respectively. We also demonstrate the use of External RNA Control Consortium (ERCC) transcripts as spike-in controls for transcriptome libraries that aid in quality control of the library generation procedure and aid in downstream data analysis. The library construction technology embedded in the Ambion® RNA-Seq Library Construction kit enables researchers to analyze the transcriptome of their research samples in a precise, sensitive and robust manner while maintaining information regarding the genomic DNA strand to which the RNA transcript maps utilizing the Illumina® Genome Analyzer II sequencing platform. The workflow and results reported here demonstrate new commercially available options for library construction enabling small RNA and transcriptome profiling and novel discovery using next-generation sequencing technology.

Rationale

Transcriptional profiling can detect subclinical heart disease and provide insight into disease etiology and functional status. Current microarray-based methods are expensive and subject to artifact.

Objective

To develop RNA sequencing methodologies using next generation massively parallel platforms for high throughput comprehensive analysis of individual mouse cardiac transcriptomes. To compare the results of sequencing- and array-based transcriptional profiling in the well-characterized Gαq transgenic mouse hypertrophy/cardiomyopathy model.

Methods and Results

The techniques for preparation of individually bar-coded mouse heart RNA libraries for Illumina Genome Analyzer II resequencing are described. RNA sequencing showed that 234 high abundance transcripts (>60 copies/cell) comprised 55% of total cardiac mRNA. Parallel transcriptional profiling of Gαq transgenic and non-transgenic hearts by Illumina RNA sequencing and Affymetrix Mouse Gene 1.0 ST arrays revealed superior dynamic range for mRNA expression and enhanced specificity for reporting low-abundance transcripts by RNA sequencing. Differential mRNA expression in Gαq and non-transgenic hearts correlated well between microarrays and RNA sequencing for highly abundant transcripts. RNA sequencing was superior to arrays for accurately quantifying lower-abundance genes, which represented the majority of the regulated genes in the Gαq transgenic model.

Conclusions

RNA sequencing is rapid, accurate, and sensitive for identifying both abundant and rare cardiac transcripts, and has significant advantages in time- and cost-efficiencies over microarray analysis.

Summary: Methyl-Analyzer is a python package that analyzes genome-wide DNA methylation data produced by the Methyl-MAPS (methylation mapping analysis by paired-end sequencing) method. Methyl-MAPS is an enzymatic-based method that uses both methylation-sensitive and -dependent enzymes covering >80% of CpG dinucleotides within mammalian genomes. It combines enzymatic-based approaches with high-throughput next-generation sequencing technology to provide whole genome DNA methylation profiles. Methyl-Analyzer processes and integrates sequencing reads from methylated and unmethylated compartments and estimates CpG methylation probabilities at single base resolution.

Availability and implementation: Methyl-Analyzer is available at http://github.com/epigenomics/methylmaps. Sample dataset is available for download at http://epigenomicspub.columbia.edu/methylanalyzer_data.html.

Contact: fgh3@columbia.edu

Supplementary information: Supplementary data are available at Bioinformatics online.

Fuelled by new sequencing technologies, epigenome mapping projects are revealing epigenomic variation at all levels of biological complexity, from species to cells. Comparisons of methylation profiles among species reveal evolutionary conservation of gene body methylation patterns, pointing to the fundamental role of epigenomes in gene regulation. At the human population level, epigenomic changes provide footprints of the effects of genomic variants within the vast non-protein coding fraction of the genome while comparisons of the epigenomes of parents and their offspring point to quantitative epigenomic parent-of-origin effects confounding classical Mendelian genetics. At the organismal level, comparisons of epigenomes from diverse cell types provide insights into cellular differentiation. Finally, comparisons of epigenomes from monozygotic twins help dissect genetic and environmental influences on human phenotypes and longitudinal comparisons reveal aging-associated epigenomic drift. The development of new bioinformatic frameworks for comparative epigenome analysis is putting epigenome maps within reach of researchers across a wide spectrum of biological disciplines.

Monozygotic twins are considered to be genetically identical, yet can show high discordance in their phenotypes and disease susceptibility. Several studies have emphasized the influence of external factors and the role of epigenetic polymorphism in conferring this variability. However, some recent high-resolution studies on DNA methylation show contradicting evidence, which poses questions on the extent of epigenetic variability between twins. The advent of next-generation sequencing technologies now allow us to interrogate multiple epigenomes on a massive scale and understand the role of epigenetic modification, especially DNA methylation, in regulating complex traits. This article briefly discusses the recent key findings, unsolved questions in the area, and speculates on the future directions in the field

Epigenetic states are responsive to developmental and environmental signals, and as a consequence a eukaryotic cell can have many different epigenomes. In this issue of Cell, Lister et al. (2008) present the floral epigenome of Arabidopsis using next-generation sequencing technology to analyze both DNA methylation at single-base resolution and the expression of small RNAs.

Background

Massively parallel sequencing readouts of epigenomic assays are enabling integrative genome-wide analyses of genomic and epigenomic variation. Pash 3.0 performs sequence comparison and read mapping and can be employed as a module within diverse configurable analysis pipelines, including ChIP-Seq and methylome mapping by whole-genome bisulfite sequencing.

Results

Pash 3.0 generally matches the accuracy and speed of niche programs for fast mapping of short reads, and exceeds their performance on longer reads generated by a new generation of massively parallel sequencing technologies. By exploiting longer read lengths, Pash 3.0 maps reads onto the large fraction of genomic DNA that contains repetitive elements and polymorphic sites, including indel polymorphisms.

Conclusions

We demonstrate the versatility of Pash 3.0 by analyzing the interaction between CpG methylation, CpG SNPs, and imprinting based on publicly available whole-genome shotgun bisulfite sequencing data. Pash 3.0 makes use of gapped k-mer alignment, a non-seed based comparison method, which is implemented using multi-positional hash tables. This allows Pash 3.0 to run on diverse hardware platforms, including individual computers with standard RAM capacity, multi-core hardware architectures and large clusters.

Background

The combination of high-throughput transcript profiling and next-generation sequencing technologies is a prerequisite for genome-wide comprehensive transcriptome analysis. Our recent innovation of deepSuperSAGE is based on an advanced SuperSAGE protocol and its combination with massively parallel pyrosequencing on Roche's 454 sequencing platform. As a demonstration of the power of this combination, we have chosen the salt stress transcriptomes of roots and nodules of the third most important legume crop chickpea (Cicer arietinum L.). While our report is more technology-oriented, it nevertheless addresses a major world-wide problem for crops generally: high salinity. Together with low temperatures and water stress, high salinity is responsible for crop losses of millions of tons of various legume (and other) crops. Continuously deteriorating environmental conditions will combine with salinity stress to further compromise crop yields. As a good example for such stress-exposed crop plants, we started to characterize salt stress responses of chickpeas on the transcriptome level.

Results

We used deepSuperSAGE to detect early global transcriptome changes in salt-stressed chickpea. The salt stress responses of 86,919 transcripts representing 17,918 unique 26 bp deepSuperSAGE tags (UniTags) from roots of the salt-tolerant variety INRAT-93 two hours after treatment with 25 mM NaCl were characterized. Additionally, the expression of 57,281 transcripts representing 13,115 UniTags was monitored in nodules of the same plants. From a total of 144,200 analyzed 26 bp tags in roots and nodules together, 21,401 unique transcripts were identified. Of these, only 363 and 106 specific transcripts, respectively, were commonly up- or down-regulated (>3.0-fold) under salt stress in both organs, witnessing a differential organ-specific response to stress.

Profiting from recent pioneer works on massive cDNA sequencing in chickpea, more than 9,400 UniTags were able to be linked to UniProt entries. Additionally, gene ontology (GO) categories over-representation analysis enabled to filter out enriched biological processes among the differentially expressed UniTags. Subsequently, the gathered information was further cross-checked with stress-related pathways.

From several filtered pathways, here we focus exemplarily on transcripts associated with the generation and scavenging of reactive oxygen species (ROS), as well as on transcripts involved in Na+ homeostasis. Although both processes are already very well characterized in other plants, the information generated in the present work is of high value. Information on expression profiles and sequence similarity for several hundreds of transcripts of potential interest is now available.

Conclusions

This report demonstrates, that the combination of the high-throughput transcriptome profiling technology SuperSAGE with one of the next-generation sequencing platforms allows deep insights into the first molecular reactions of a plant exposed to salinity. Cross validation with recent reports enriched the information about the salt stress dynamics of more than 9,000 chickpea ESTs, and enlarged their pool of alternative transcripts isoforms.

As an example for the high resolution of the employed technology that we coin deepSuperSAGE, we demonstrate that ROS-scavenging and -generating pathways undergo strong global transcriptome changes in chickpea roots and nodules already 2 hours after onset of moderate salt stress (25 mM NaCl). Additionally, a set of more than 15 candidate transcripts are proposed to be potential components of the salt overly sensitive (SOS) pathway in chickpea.

Newly identified transcript isoforms are potential targets for breeding novel cultivars with high salinity tolerance. We demonstrate that these targets can be integrated into breeding schemes by micro-arrays and RT-PCR assays downstream of the generation of 26 bp tags by SuperSAGE.

Massively parallel sequencing technologies continue to alter the study of human genetics. As the cost of sequencing declines, next-generation sequencing (NGS) instruments and datasets will become increasingly accessible to the wider research community. Investigators are understandably eager to harness the power of these new technologies. Sequencing human genomes on these platforms, however, presents numerous production and bioinformatics challenges. Production issues like sample contamination, library chimaeras and variable run quality have become increasingly problematic in the transition from technology development lab to production floor. Analysis of NGS data, too, remains challenging, particularly given the short-read lengths (35–250 bp) and sheer volume of data. The development of streamlined, highly automated pipelines for data analysis is critical for transition from technology adoption to accelerated research and publication. This review aims to describe the state of current NGS technologies, as well as the strategies that enable NGS users to characterize the full spectrum of DNA sequence variation in humans.

The beginning of this century was not only marked by the publication of the first draft of the human genome but also set off a decade of intense research on epigenetic phenomena. Apart from DNA methylation, it became clear that many other factors including a wide range of histone modifications, different shades of chromatin accessibility, and a vast suite of noncoding RNAs comprise the epigenome. With the recent advances in sequencing technologies, it has now become possible to analyze many of these features in depth, allowing for the first time the establishment of complete epigenomic profiles for basically every cell type of interest. Here, we will discuss the recent advances that allow comprehensive epigenetic mapping, highlight several projects that set out to better understand the epigenome, and discuss the impact that epigenomic mapping can have on our understanding of both healthy and diseased cells.

New DNA sequencing technologies present an exceptional opportunity for novel and creative applications with the potential for breakthrough discoveries. To support such research efforts, the Cornell University Life Sciences Core Laboratories Center has implemented the Illumina HiSeq 2000 and the Roche 454 GS FLX platforms as academic core facility shared research resources. We have established sample handling methods, LIMS tools and BioHPC informatics analysis pipelines in support of these new technologies. Our genomics core laboratory, in collaboration with our epigenomics core and bioinformatics core, provides sample preparation and data generation services and both project consultation and analysis support for a wide range of possible applications, including de novo or reference based genome assembly, detection of genetic variation, transcriptome sequencing, small RNA profiling, and genome-wide epigenomic measurements of methylation and protein-nucleic acid interactions. Implementation of next generation sequencing platforms as shared resources with multidisciplinary core facility support enables cost effective access and broad based use of these technologies.

The past decade has highlighted the central role of epigenetic processes in cancer causation, progression and treatment. Next-generation sequencing is providing a window for visualizing the human epigenome and how it is altered in cancer. This view provides many surprises, including linking epigenetic abnormalities to mutations in genes that control DNA methylation, the packaging and the function of DNA in chromatin, and metabolism. Epigenetic alterations are leading candidates for the development of specific markers for cancer detection, diagnosis and prognosis. The enzymatic processes that control the epigenome present new opportunities for deriving therapeutic strategies designed to reverse transcriptional abnormalities that are inherent to the cancer epigenome.

Environmental factors have a significant impact on biology. Therefore, environmental toxicants through similar mechanisms can modulate biological systems to influence physiology and promote disease states. The majority of environmental toxicants do not have the capacity to modulate DNA sequence, but can alter the epigenome. In the event an environmental toxicant such as an endocrine disruptor modifies the epigenome of a somatic cell, this may promote disease in the individual exposed, but not be transmitted to the next generation. In the event a toxicant modifies the epigenome of the germ line permanently, then the disease promoted can become transgenerationaly transmitted to subsequent progeny. The current review focuses on the ability of environmental factors such as endocrine disruptors to promote transgenerational phenotypes.

Background

Next-generation sequencing techniques enable several novel transcriptome profiling approaches. Recent studies indicated that digital gene expression profiling based on short sequence tags has superior performance as compared to other transcriptome analysis platforms including microarrays. However, the transcriptomic analysis with tag-based methods often depends on available genome sequence. The use of tag-based methods in species without genome sequence should be complemented by other methods such as cDNA library sequencing. The combination of different next generation sequencing techniques like 454 pyrosequencing and Illumina Genome Analyzer (Solexa) will enable high-throughput and accurate global gene expression profiling in species with limited genome information. The combination of transcriptome data acquisition methods requires cross-platform transcriptome data analysis platforms, including a new software package for data processing.

Results

Here we presented a software package, CPTRA: Cross-Platform TRanscriptome Analysis, to analyze transcriptome profiling data from separate methods. The software package is available at http://people.tamu.edu/~syuan/cptra/cptra.html. It was applied to the case study of non-target site glyphosate resistance in horseweed; and the data was mined to discover resistance target gene(s). For the software, the input data included a long-read sequence dataset with proper annotation, and a short-read sequence tag dataset for the quantification of transcripts. By combining the two datasets, the software carries out the unique sequence tag identification, tag counting for transcript quantification, and cross-platform sequence matching functions, whereby the short sequence tags can be annotated with a function, level of expression, and Gene Ontology (GO) classification. Multiple sequence search algorithms were implemented and compared. The analysis highlighted the importance of transport genes in glyphosate resistance and identified several candidate genes for down-stream analysis.

Conclusion

CPTRA is a powerful software package for next generation sequencing-based transcriptome profiling in species with limited genome information. According to our case study, the strategy can greatly broaden the application of the next generation sequencing for transcriptome analysis in species without reference genome sequence.

A variety of techniques that specifically target human gene sequences for differential capture from a genomic sample, coupled with next-generation, massively parallel DNA sequencing instruments, is rapidly supplanting the combination of polymerase chain reaction and capillary sequencing to discover coding variants in medically relevant samples. These studies are most appropriate for the sample numbers necessary to identify both common and rare single nucleotide variants, as well as small insertion or deletion events, which may cause complex inherited diseases. The same massively parallel sequencers are simultaneously being used for whole-genome resequencing and comprehensive, genome-wide variant discovery in studies of somatic diseases such as cancer. Viral and microbial researchers are using next-generation sequences to identify unknown etiologic agents in human diseases, to study the viral and microbial species that occupy surfaces of the human body, and to inform the clinical management of chronic infectious diseases such as human immunodeficiency virus (HIV). Taken together, these approaches are dramatically accelerating the pace of human disease research and are already impacting patient care.

Reduced representation bisulfite sequencing (RRBS), which couples bisulfite conversion and next generation sequencing, is an innovative method that specifically enriches genomic regions with a high density of potential methylation sites and enables investigation of DNA methylation at single-nucleotide resolution. Recent advances in the Illumina DNA sample preparation protocol and sequencing technology have vastly improved sequencing throughput capacity. Although the new Illumina technology is now widely used, the unique challenges associated with multiplexed RRBS libraries on this platform have not been previously described. We have made modifications to the RRBS library preparation protocol to sequence multiplexed libraries on a single flow cell lane of the Illumina HiSeq 2000. Furthermore, our analysis incorporates a bioinformatics pipeline specifically designed to process bisulfite-converted sequencing reads and evaluate the output and quality of the sequencing data generated from the multiplexed libraries. We obtained an average of 42 million paired-end reads per sample for each flow-cell lane, with a high unique mapping efficiency to the reference human genome. Here we provide a roadmap of modifications, strategies, and trouble shooting approaches we implemented to optimize sequencing of multiplexed libraries on an a RRBS background.

The development of DNA sequencing more than 30 years ago has profoundly impacted biological research. In the last couple of years, remarkable technological innovations have emerged that allow the direct and cost-effective sequencing of complex samples at unprecedented scale and speed. These next-generation technologies make it feasible to sequence not only static genomes, but also entire transcriptomes expressed under different conditions. These and other powerful applications of next-generation sequencing are rapidly revolutionizing the way genomic studies are carried out. Below, we provide a snapshot of these exciting new approaches to understanding the properties and functions of genomes. Given that sequencing-based assays may increasingly supersede microarray-based assays, we also compare and contrast data obtained from these distinct approaches.

SUMMARY

Early life experiences have a major impact on adult phenotypes [1–3]. However, the mechanisms by which animals retain a cellular memory of early experience are not well understood. Here we show that adult wild-type C. elegans that transiently passed through the stress-resistant dauer larval stage exhibit distinct gene expression profiles and life history traits, as compared to adult animals that bypassed this stage. Using chromatin immmunoprecipitation experiments coupled with massively parallel sequencing, we find that genome-wide levels of specific histone tail modifications are markedly altered in post-dauer animals. Mutations in subsets of genes implicated in chromatin remodeling abolish, or alter, the observed changes in gene expression and life history traits in post-dauer animals. Modifications to the epigenome as a consequence of early experience may contribute in part to a memory of early experience, and generate phenotypic variation in an isogenic population.

Background

For next generation DNA sequencing, we have developed a rapid and simple approach for preparing DNA libraries of targeted DNA content. Current protocols for preparing DNA for next-generation targeted sequencing are labor-intensive, require large amounts of starting material, and are prone to artifacts that result from necessary PCR amplification of sequencing libraries. Typically, sample preparation for targeted NGS is a two-step process where (1) the desired regions are selectively captured and (2) the ends of the DNA molecules are modified to render them compatible with any given NGS sequencing platform.

Results

In this proof-of-concept study, we present an integrated approach that combines these two separate steps into one. Our method involves circularization of a specific genomic DNA molecule that directly incorporates the necessary components for conducting sequencing in a single assay and requires only one PCR amplification step. We also show that specific regions of the genome can be targeted and sequenced without any PCR amplification.

Conclusion

We anticipate that these rapid targeted libraries will be useful for validation of variants and may have diagnostic application.

Background

The methylotrophic yeast Pichia pastoris is widely used as a bioengineering platform for producing industrial and biopharmaceutical proteins, studying protein expression and secretion mechanisms, and analyzing metabolite synthesis and peroxisome biogenesis. With the development of DNA microarray and mRNA sequence technology, the P. pastoris transcriptome has become a research hotspot due to its powerful capability to identify the transcript structures and gain insights into the transcriptional regulation model of cells under protein production conditions. The study of the P. pastoris transcriptome helps to annotate the P. pastoris transcript structures and provide useful information for further improvement of the production of recombinant proteins.

Results

We used a massively parallel mRNA sequencing platform (RNA-Seq), based on next-generation sequencing technology, to map and quantify the dynamic transcriptome of P. pastoris at the genome scale under growth conditions with glycerol and methanol as substrates. The results describe the transcription landscape at the whole-genome level and provide annotated transcript structures, including untranslated regions (UTRs), alternative splicing (AS) events, novel transcripts, new exons, alternative upstream initiation codons (uATGs), and upstream open reading frames (uORFs). Internal ribosome entry sites (IRESes) were first identified within the UTRs of genes from P. pastoris, encoding kinases and the proteins involved in the control of growth. We also provide a transcriptional regulation model for P. pastoris grown on different carbon sources.

Conclusions

We suggest that the IRES-dependent translation initiation mechanism also exists in P. pastoris. Retained introns (RIs) are determined as the main AS event and are produced predominantly by an intron definition (ID) mechanism. Our results describe the metabolic characteristics of P. pastoris with heterologous protein production under methanol induction and provide rich information for further in-depth studies of P. pastoris protein expression and secretion mechanisms.