Next generation transcriptomes for next generation genomes using est2assembly

<p>Abstract</p> <p>Background</p> <p>The decreasing costs of capillary-based Sanger sequencing and next generation technologies, such as 454 pyrosequencing, have prompted an explosion of transcriptome projects in non-model species, where even shallow sequencing of transcriptomes can now be used to examine a range of research questions. This rapid growth in data has outstripped the ability of researchers working on non-model species to analyze and mine transcriptome data efficiently.</p> <p>Results</p> <p>Here we present a semi-automated platform '<it>est2assembly</it>' that processes raw sequence data from Sanger or 454 sequencing into a hybrid <it>de-novo </it>assembly, annotates it and produces GMOD compatible output, including a SeqFeature database suitable for GBrowse. Users are able to parameterize assembler variables, judge assembly quality and determine the optimal assembly for their specific needs. We used <it>est2assembly </it>to process <it>Drosophila </it>and <it>Bicyclus </it>public Sanger EST data and then compared them to published 454 data as well as eight new insect transcriptome collections.</p> <p>Conclusions</p> <p>Analysis of such a wide variety of data allows us to understand how these new technologies can assist EST project design. We determine that assembler parameterization is as essential as standardized methods to judge the output of ESTs projects. Further, even shallow sequencing using 454 produces sufficient data to be of wide use to the community. <it>est2assembly </it>is an important tool to assist manual curation for gene models, an important resource in their own right but especially for species which are due to acquire a genome project using Next Generation Sequencing.</p

Hypoxia Negatively Regulates Antimetastatic PEDF in Melanoma Cells by a Hypoxia Inducible Factor-Independent, Autophagy Dependent Mechanism

Pigment epithelium-derived factor (PEDF), a member of the serine protease inhibitor (SERPIN) superfamily, displays a potent antiangiogenic and antimetastatic activity in a broad range of tumor types. Melanocytes and low aggressive melanoma cells secrete high levels of PEDF, while its expression is lost in highly aggressive melanomas. PEDF efficiently abrogates a number of functional properties critical for the acquisition of metastatic ability by melanoma cells, such as neovascularization, proliferation, migration, invasiveness and extravasation. In this study, we identify hypoxia as a relevant negative regulator of PEDF in melanocytes and low aggressive melanoma cells. PEDF was regulated at the protein level. Importantly, although downregulation of PEDF was induced by inhibition of 2-oxoglutarate-dependent dioxygenases, it was independent of the hypoxia inducible factor (HIF), a key mediator of the adaptation to hypoxia. Decreased PEDF protein was not mediated by inhibition of translation through untranslated regions (UTRs) in melanoma cells. Degradation by metalloproteinases, implicated on PEDF degradation in retinal pigment epithelial cells, or by the proteasome, was also excluded as regulatory mechanism in melanoma cells. Instead, we found that degradation by autophagy was critical for PEDF downregulation under hypoxia in human melanoma cells. Our findings show that hypoxic conditions encountered during primary melanoma growth downregulate antiangiogenic and antimetastasic PEDF by a posttranslational mechanism involving degradation by autophagy and could therefore contribute to the acquisition of highly metastatic potential characteristic of aggressive melanoma cells

Transcriptome characterization of the South African abalone Haliotis midae using sequencing-by-synthesis

<p>Abstract</p> <p>Background</p> <p>Worldwide, the genus <it>Haliotis </it>is represented by 56 extant species and several of these are commercially cultured. Among the six abalone species found in South Africa, <it>Haliotis midae </it>is the only aquacultured species. Despite its economic importance, genomic sequence resources for <it>H. midae</it>, and for abalone in general, are still scarce. Next generation sequencing technologies provide a fast and efficient tool to generate large sequence collections that can be used to characterize the transcriptome and identify expressed genes associated with economically important traits like growth and disease resistance.</p> <p>Results</p> <p>More than 25 million short reads generated by the Illumina Genome Analyzer were <it>de novo </it>assembled in 22,761 contigs with an average size of 260 bp. With a stringent <it>E</it>-value threshold of 10^-10, 3,841 contigs (16.8%) had a BLAST homologous match against the Genbank non-redundant (NR) protein database. Most of these sequences were annotated using the gene ontology (GO) and eukaryotic orthologous groups of proteins (KOG) databases and assigned to various functional categories. According to annotation results, many gene families involved in immune response were identified. Thousands of simple sequence repeats (SSR) and single nucleotide polymorphisms (SNP) were detected. Setting stringent parameters to ensure a high probability of amplification, 420 primer pairs in 181 contigs containing SSR loci were designed.</p> <p>Conclusion</p> <p>This data represents the most comprehensive genomic resource for the South African abalone <it>H. midae </it>to date. The amount of assembled sequences demonstrated the utility of the Illumina sequencing technology in the transcriptome characterization of a non-model species. It allowed the development of several markers and the identification of promising candidate genes for future studies on population and functional genomics in <it>H. midae </it>and in other abalone species.</p

What Can Be Learnt about Disease Progression in Breast Cancer Dormancy from Relapse Data?

Breast cancer patients have an anomalously high rate of relapse many years-up to 25 years-after apparently curative surgery removed the primary tumour. Disease progression during the intervening years between resection and relapse is poorly understood. There is evidence that the disease persists as dangerous, tiny metastases that remain at a growth restricted, clinically undetectable size until a transforming event restarts growth. This is the starting point for our study, where patients who have metastases that are all tiny and growth-restricted are said to have cancer dormancy. Can long-term follow-up relapse data from breast cancer patients be used to extract knowledge about the progression of the undetected disease? Here, we evaluate whether this is the case by introducing and analysing four simple mathematical models of cancer dormancy. These models extend the common assumption that a random transforming event, such as a mutation, can restart growth of a tiny, growth-restricted metastasis; thereafter, cancer dormancy progresses to detectable metastasis. We find that physiopathological details, such as the number of random transforming events that metastases must undergo to escape from growth restriction, cannot be extracted from relapse data. This result is unsurprising. However, the same analysis suggested a natural question that does have a surprising answer: why are interesting trends in long-term relapse data not more commonly observed? Further, our models indicate that (a) therapies which induce growth restriction among metastases but do not prevent increases in metastases' tumourigenicity may introduce a time post-surgery when more patients are prone to relapse; and (b), if a number of facts about disease progression are first established, how relapse data might be used to estimate clinically relevant variables, such as the likely numbers of undetected growth-restricted metastases. This work is a necessary, early step in building a quantitative mechanistic understanding of cancer dormancy

ESTs in Plants: Where Are We Heading?

Expressed sequence tags (ESTs) are the most important resources for transcriptome exploration. Next-generation sequencing technologies have been generating gigabytes of genetic codes representing genes, partial and whole genomes most of which are EST datasets. Niche of EST in plants for breeding, regulation of gene expression through miRNA studies, and their application for adapting to climatic changes are discussed. Some of the recent tools for analysis of EST exclusive to plants are listed out. Systems biology though in its infancy in plants has influenced EST mapping for unraveling gene regulatory circuits, which is illustrated with a few significant examples. This review throws a glance at the evolving role of ESTs in plants