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Genes, Volume 1, Issue 2 (September 2010), Pages 143-334

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Research

Jump to: Review

Open AccessArticle 454-Pyrosequencing: A Molecular Battiscope for Freshwater Viral Ecology
Genes 2010, 1(2), 210-226; doi:10.3390/genes1020210
Received: 11 May 2010 / Revised: 8 July 2010 / Accepted: 20 July 2010 / Published: 21 July 2010
Cited by 7 | PDF Full-text (1273 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Viruses, the most abundant biological entities on the planet, are capable of infecting organisms from all three branches of life, although the majority infect bacteria where the greatest degree of cellular diversity lies. However, the characterization and assessment of viral diversity in [...] Read more.
Viruses, the most abundant biological entities on the planet, are capable of infecting organisms from all three branches of life, although the majority infect bacteria where the greatest degree of cellular diversity lies. However, the characterization and assessment of viral diversity in natural environments is only beginning to become a possibility. Through the development of a novel technique for the harvest of viral DNA and the application of 454 pyrosequencing, a snapshot of the diversity of the DNA viruses harvested from a standing pond on a cattle farm has been obtained. A high abundance of viral genotypes (785) were present within the virome. The absolute numbers of lambdoid and Shiga toxin (Stx) encoding phages detected suggested that the depth of sequencing had enabled recovery of only ca. 8% of the total virus population, numbers that agreed within less than an order of magnitude with predictions made by rarefaction analysis. The most abundant viral genotypes in the pond were bacteriophages (93.7%). The predominant viral genotypes infecting higher life forms found in association with the farm were pathogens that cause disease in cattle and humans, e.g. members of the Herpesviridae. The techniques and analysis described here provide a fresh approach to the monitoring of viral populations in the aquatic environment, with the potential to become integral to the development of risk analysis tools for monitoring the dissemination of viral agents of animal, plant and human diseases. Full article
(This article belongs to the Special Issue Next Generation DNA Sequencing)
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Open AccessArticle A Computer Simulator for Assessing Different Challenges and Strategies of de Novo Sequence Assembly
Genes 2010, 1(2), 263-282; doi:10.3390/genes1020263
Received: 1 June 2010 / Revised: 18 August 2010 / Accepted: 31 August 2010 / Published: 13 September 2010
Cited by 5 | PDF Full-text (513 KB) | HTML Full-text | XML Full-text
Abstract
This study presents a new computer program for assessing the effects of different factors and sequencing strategies on de novo sequence assembly. The program uses reads from actual sequencing studies or from simulations with a reference genome that may also be real [...] Read more.
This study presents a new computer program for assessing the effects of different factors and sequencing strategies on de novo sequence assembly. The program uses reads from actual sequencing studies or from simulations with a reference genome that may also be real or simulated. The simulated reads can be created with our read simulator. They can be of differing length and coverage, consist of paired reads with varying distance, and include sequencing errors such as color space miscalls to imitate SOLiD data. The simulated or real reads are mapped to their reference genome and our assembly simulator is then used to obtain optimal assemblies that are limited only by the distribution of repeats. By way of this mapping, the assembly simulator determines which contigs are theoretically possible, or conversely (and perhaps more importantly), which are not. We illustrate the application and utility of our new simulation tools with several experiments that test the effects of genome complexity (repeats), read length and coverage, word size in De Bruijn graph assembly, and alternative sequencing strategies (e.g., BAC pooling) on sequence assemblies. These experiments highlight just some of the uses of our simulators in the experimental design of sequencing projects and in the further development of assembly algorithms. Full article
(This article belongs to the Special Issue Next Generation DNA Sequencing)
Open AccessArticle Expression of the Y-Encoded TSPY is Associated with Progression of Prostate Cancer
Genes 2010, 1(2), 283-293; doi:10.3390/genes1020283
Received: 9 August 2010 / Revised: 1 September 2010 / Accepted: 2 September 2010 / Published: 14 September 2010
Cited by 6 | PDF Full-text (410 KB) | HTML Full-text | XML Full-text
Abstract
TSPY is a Y-encoded gene that is expressed in normal testicular germ cells and various cancer types including germ cell tumor, melanoma, hepatocellular carcinoma, and prostate cancer. Currently, the correlation between TSPY expression and oncogenic development has not been established, particularly in [...] Read more.
TSPY is a Y-encoded gene that is expressed in normal testicular germ cells and various cancer types including germ cell tumor, melanoma, hepatocellular carcinoma, and prostate cancer. Currently, the correlation between TSPY expression and oncogenic development has not been established, particularly in somatic cancers. To establish such correlation, we analyzed the expression of TSPY, in reference to its interactive oncoprotein, EEF1A, tumor biomarker, AMACR, and normal basal cell biomarker, p63, in 41 cases of clinical prostate cancers (CPCa), 17 cases of latent prostate cancers (LPCa), and 19 cases of non-cancerous prostate (control) by immunohistochemistry. Our results show that TSPY was detected more frequently (78%) in the clinical prostate cancer specimens than those of latent prostate cancer (47%) and control (50%). In the latent cancer group, the levels of TSPY expression could be correlated with increasing Gleason grades. TSPY expression was detected in seven out of nine high-grade latent cancer samples (Gleason 7 and more). The expression of the TSPY binding partner EEF1A was detectable in all prostate specimens, but the levels were higher in cancer cells in clinical and latent prostate cancer specimens than normal prostatic cells. These observations suggest that expressions of TSPY and its binding partner EEF1A are associated with the development and progression of prostate cancer. Full article
(This article belongs to the Special Issue The TSPY Gene Family)

Review

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Open AccessReview Next Generation Sequencing: Advances in Characterizing the Methylome
Genes 2010, 1(2), 143-165; doi:10.3390/genes1020143
Received: 3 May 2010 / Revised: 22 June 2010 / Accepted: 28 June 2010 / Published: 1 July 2010
Cited by 2 | PDF Full-text (629 KB) | HTML Full-text | XML Full-text
Abstract
Epigenetic modifications play an important role in lymphoid malignancies. This has been evidenced by the large body of work published using microarray technologies to generate methylation profiles for numerous types and subtypes of lymphoma and leukemia. These studies have shown the importance [...] Read more.
Epigenetic modifications play an important role in lymphoid malignancies. This has been evidenced by the large body of work published using microarray technologies to generate methylation profiles for numerous types and subtypes of lymphoma and leukemia. These studies have shown the importance of defining the epigenome so that we can better understand the biology of lymphoma. Recent advances in DNA sequencing technology have transformed the landscape of epigenomic analysis as we now have the ability to characterize the genome-wide distribution of chromatin modifications and DNA methylation using next-generation sequencing. To take full advantage of the throughput of next-generation sequencing, there are many methodologies that have been developed and many more that are currently being developed. Choosing the appropriate methodology is fundamental to the outcome of next-generation sequencing studies. In this review, published technologies and methodologies applicable to studying the methylome are presented. In addition, progress towards defining the methylome in lymphoma is discussed and prospective directions that have been made possible as a result of next-generation sequencing technology. Finally, methodologies are introduced that have not yet been published but that are being explored in the pursuit of defining the lymphoma methylome. Full article
(This article belongs to the Special Issue Next Generation DNA Sequencing)
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Open AccessReview Review of the Application of Modern Cytogenetic Methods (FISH/GISH) to the Study of Reticulation (Polyploidy/Hybridisation)
Genes 2010, 1(2), 166-192; doi:10.3390/genes1020166
Received: 18 May 2010 / Revised: 30 June 2010 / Accepted: 30 June 2010 / Published: 2 July 2010
Cited by 23 | PDF Full-text (392 KB) | HTML Full-text | XML Full-text
Abstract
The convergence of distinct lineages upon interspecific hybridisation, including when accompanied by increases in ploidy (allopolyploidy), is a driving force in the origin of many plant species. In plant breeding too, both interspecific hybridisation and allopolyploidy are important because they facilitate introgression [...] Read more.
The convergence of distinct lineages upon interspecific hybridisation, including when accompanied by increases in ploidy (allopolyploidy), is a driving force in the origin of many plant species. In plant breeding too, both interspecific hybridisation and allopolyploidy are important because they facilitate introgression of alien DNA into breeding lines enabling the introduction of novel characters. Here we review how fluorescence in situ hybridisation (FISH) and genomic in situ hybridisation (GISH) have been applied to: 1) studies of interspecific hybridisation and polyploidy in nature, 2) analyses of phylogenetic relationships between species, 3) genetic mapping and 4) analysis of plant breeding materials. We also review how FISH is poised to take advantage of nextgeneration sequencing (NGS) technologies, helping the rapid characterisation of the repetitive fractions of a genome in natural populations and agricultural plants. Full article
(This article belongs to the Special Issue Reticulate Evolution)
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Open AccessReview Staggered Chromosomal Hybrid Zones in the House Mouse: Relevance to Reticulate Evolution and Speciation
Genes 2010, 1(2), 193-209; doi:10.3390/genes1020193
Received: 11 May 2010 / Revised: 5 July 2010 / Accepted: 8 July 2010 / Published: 19 July 2010
Cited by 7 | PDF Full-text (308 KB) | HTML Full-text | XML Full-text
Abstract
In the house mouse there are numerous chromosomal races distinguished by different combinations of metacentric chromosomes. These may come into contact with each other and with the ancestral all-acrocentric race, and form hybrid zones. The chromosomal clines that make up these hybrid [...] Read more.
In the house mouse there are numerous chromosomal races distinguished by different combinations of metacentric chromosomes. These may come into contact with each other and with the ancestral all-acrocentric race, and form hybrid zones. The chromosomal clines that make up these hybrid zones may be coincident or separated from each other (staggered). Such staggered hybrid zones are interesting because they may include populations of individuals homozygous for a mix of features of the hybridising races. We review the characteristics of four staggered hybrid zones in the house mouse and discuss whether they are examples of primary or secondary contact and whether they represent reticulate evolution or not. However, the most important aspect of staggered hybrid zones is that the homozygous populations within the zones have the potential to expand their distributions and become new races (a process termed ‘zonal raciation’). In this way they can add to the total ‘stock’ of chromosomal races in the species concerned. Speciation is an infrequent phenomenon that may involve an unusual set of circumstances. Each one of the products of zonal raciation has the potential to become a new species and by having more races increases the chance of a speciation event. Full article
(This article belongs to the Special Issue Reticulate Evolution)
Open AccessReview Next Generation Sequencing of Ancient DNA: Requirements, Strategies and Perspectives
Genes 2010, 1(2), 227-243; doi:10.3390/genes1020227
Received: 31 May 2010 / Revised: 20 July 2010 / Accepted: 23 July 2010 / Published: 28 July 2010
Cited by 46 | PDF Full-text (321 KB) | HTML Full-text | XML Full-text
Abstract
The invention of next-generation-sequencing has revolutionized almost all fields of genetics, but few have profited from it as much as the field of ancient DNA research. From its beginnings as an interesting but rather marginal discipline, ancient DNA research is now on [...] Read more.
The invention of next-generation-sequencing has revolutionized almost all fields of genetics, but few have profited from it as much as the field of ancient DNA research. From its beginnings as an interesting but rather marginal discipline, ancient DNA research is now on its way into the centre of evolutionary biology. In less than a year from its invention next-generation-sequencing had increased the amount of DNA sequence data available from extinct organisms by several orders of magnitude. Ancient DNA  research is now not only adding a temporal aspect to evolutionary studies and allowing for the observation of evolution in real time, it also provides important data to help understand the origins of our own species. Here we review progress that has been made in next-generation-sequencing of ancient DNA over the past five years and evaluate sequencing strategies and future directions. Full article
(This article belongs to the Special Issue Next Generation DNA Sequencing)
Open AccessReview Transgenic Mouse Studies to Understand the Regulation, Expression and Function of the Testis-Specific Protein Y-Encoded (TSPY) Gene
Genes 2010, 1(2), 244-262; doi:10.3390/genes1020244
Received: 30 June 2010 / Revised: 13 August 2010 / Accepted: 16 August 2010 / Published: 18 August 2010
Cited by 2 | PDF Full-text (862 KB) | HTML Full-text | XML Full-text
Abstract
The TSPY gene, which encodes the testis-specific protein, Y-encoded, was first discovered and characterized in humans, but orthologous genes were subsequently identified on the Y chromosome of many other placental mammals. TSPY is expressed in the testis [...] Read more.
The TSPY gene, which encodes the testis-specific protein, Y-encoded, was first discovered and characterized in humans, but orthologous genes were subsequently identified on the Y chromosome of many other placental mammals. TSPY is expressed in the testis and to a much lesser extent in the prostate gland, and it is assumed that TSPY serves function in spermatogonial proliferation and/or differentiation. It is further supposed that TSPY is involved in male infertility and exerts oncogenic effects in gonadal and prostate tumor formation. As a member of the TSPY/SET/NAP protein family, TSPY is able to bind cyclin B types, and stimulates the cyclin B1-CDK1 kinase activity, thereby accelerating the G2/M phase transition of the cell cycle of target cells. Because the laboratory mouse carries only a nonfunctional Y-chromosomal Tspy-ps pseudogene, a knockout mouse model for functional research analyses is not a feasible approach. In the last decade, three classical transgenic mouse models have been developed to contribute to our understanding of TSPY regulation, expression and function. The different transgenic mouse approaches and their relevance for studying TSPY regulation, expression and function are discussed in this review. Full article
(This article belongs to the Special Issue The TSPY Gene Family)
Open AccessReview Bioinformatics for Next Generation Sequencing Data
Genes 2010, 1(2), 294-307; doi:10.3390/genes1020294
Received: 27 July 2010 / Revised: 30 August 2010 / Accepted: 14 September 2010 / Published: 14 September 2010
Cited by 29 | PDF Full-text (434 KB) | HTML Full-text | XML Full-text
Abstract
The emergence of next-generation sequencing (NGS) platforms imposes increasing demands on statistical methods and bioinformatic tools for the analysis and the management of the huge amounts of data generated by these technologies. Even at the early stages of their commercial availability, a [...] Read more.
The emergence of next-generation sequencing (NGS) platforms imposes increasing demands on statistical methods and bioinformatic tools for the analysis and the management of the huge amounts of data generated by these technologies. Even at the early stages of their commercial availability, a large number of softwares already exist for analyzing NGS data. These tools can be fit into many general categories including alignment of sequence reads to a reference, base-calling and/or polymorphism detection, de novo assembly from paired or unpaired reads, structural variant detection and genome browsing. This manuscript aims to guide readers in the choice of the available computational tools that can be used to face the several steps of the data analysis workflow. Full article
(This article belongs to the Special Issue Next Generation DNA Sequencing)
Open AccessReview TSPY and Male Fertility
Genes 2010, 1(2), 308-316; doi:10.3390/genes1020308
Received: 7 July 2010 / Revised: 1 September 2010 / Accepted: 14 September 2010 / Published: 21 September 2010
Cited by 7 | PDF Full-text (103 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Spermatogenesis requires the concerted action of thousands of genes, all contributing to its efficiency to a different extent. The Y chromosome contains several testis-specific genes and among them the AZF region genes on the Yq and the TSPY1 array on the Yp [...] Read more.
Spermatogenesis requires the concerted action of thousands of genes, all contributing to its efficiency to a different extent. The Y chromosome contains several testis-specific genes and among them the AZF region genes on the Yq and the TSPY1 array on the Yp are the most relevant candidates for spermatogenic function. TSPY1 was originally described as the putative gene for the gonadoblastoma locus on the Y (GBY) chromosome. Besides its oncogenic properties, expression analyses in the testis and in vitro and in vivo studies all converge on a physiological involvement of the TSPY1 protein in spermatogenesis as a pro-proliferative factor. The majority of TSPY1 copies are arranged in 20.4 kb of tandemly repeated units, with different copy numbers among individuals. Our recent study addressing the role of TSPY1 copy number variation in spermatogenesis reported that TSPY1 copy number influences spermatogenic efficiency and is positively correlated with sperm count. This finding provides further evidence for a role of TSPY1 in testicular germ cell proliferation and stimulates future research aimed at evaluating the relationship between the copy number and the protein expression level of the TSPY1 gene. Full article
(This article belongs to the Special Issue The TSPY Gene Family)
Open AccessReview Statistical Issues in the Analysis of ChIP-Seq and RNA-Seq Data
Genes 2010, 1(2), 317-334; doi:10.3390/genes1020317
Received: 17 August 2010 / Accepted: 20 September 2010 / Published: 27 September 2010
Cited by 9 | PDF Full-text (378 KB) | HTML Full-text | XML Full-text
Abstract
The recent arrival of ultra-high throughput, next generation sequencing (NGS) technologies has revolutionized the genetics and genomics fields by allowing rapid and inexpensive sequencing of billions of bases. The rapid deployment of NGS in a variety of sequencing-based experiments has resulted in [...] Read more.
The recent arrival of ultra-high throughput, next generation sequencing (NGS) technologies has revolutionized the genetics and genomics fields by allowing rapid and inexpensive sequencing of billions of bases. The rapid deployment of NGS in a variety of sequencing-based experiments has resulted in fast accumulation of massive amounts of sequencing data. To process this new type of data, a torrent of increasingly sophisticated algorithms and software tools are emerging to help the analysis stage of the NGS applications. In this article, we strive to comprehensively identify the critical challenges that arise from all stages of NGS data analysis and provide an objective overview of what has been achieved in existing works. At the same time, we highlight selected areas that need much further research to improve our current capabilities to delineate the most information possible from NGS data. The article focuses on applications dealing with ChIP-Seq and RNA-Seq. Full article
(This article belongs to the Special Issue Next Generation DNA Sequencing)

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