79 research outputs found
RNA-Seq Atlas of Glycine max: A guide to the soybean transcriptome
<p>Abstract</p> <p>Background</p> <p>Next generation sequencing is transforming our understanding of transcriptomes. It can determine the expression level of transcripts with a dynamic range of over six orders of magnitude from multiple tissues, developmental stages or conditions. Patterns of gene expression provide insight into functions of genes with unknown annotation.</p> <p>Results</p> <p>The RNA Seq-Atlas presented here provides a record of high-resolution gene expression in a set of fourteen diverse tissues. Hierarchical clustering of transcriptional profiles for these tissues suggests three clades with similar profiles: aerial, underground and seed tissues. We also investigate the relationship between gene structure and gene expression and find a correlation between gene length and expression. Additionally, we find dramatic tissue-specific gene expression of both the most highly-expressed genes and the genes specific to legumes in seed development and nodule tissues. Analysis of the gene expression profiles of over 2,000 genes with preferential gene expression in seed suggests there are more than 177 genes with functional roles that are involved in the economically important seed filling process. Finally, the Seq-atlas also provides a means of evaluating existing gene model annotations for the <it>Glycine max </it>genome.</p> <p>Conclusions</p> <p>This RNA-Seq atlas extends the analyses of previous gene expression atlases performed using Affymetrix GeneChip technology and provides an example of new methods to accommodate the increase in transcriptome data obtained from next generation sequencing. Data contained within this RNA-Seq atlas of <it>Glycine max </it>can be explored at <url>http://www.soybase.org/soyseq</url>.</p
Gene expression patterns are correlated with genomic and genic structure in soybean
Studies have indicated that exon and intron size and intergenic distance are correlated with gene expression levels and expression breadth. Previous reports on these correlations in plants and animals have been conflicting. In this study, next-generation sequence data, which has been shown to be more sensitive than previous expression profiling technologies, were generated and analyzed from 14 tissues. Our results revealed a novel dichotomy. At the low expression level, an increase in expression breadth correlated with an increase in transcript size because of an increase in the number of exons and introns. No significant changes in intron or exon sizes were noted. Conversely, genes expressed at the intermediate to high expression levels displayed a decrease in transcript size as their expression breadth increased. This was due to smaller exons, with no significant change in the number of exons. Taking advantage of the known gene space of soybean, we evaluated the positioning of genes and found significant clustering of similarly expressed genes. Identifying the correlations between the physical parameters of individual genes could lead to uncovering the role of regulation owing to nucleotide composition, which might have potential impacts in discerning the role of the noncoding regions
A distinct lineage of giant viruses brings a rhodopsin photosystem to unicellular marine predators.
Giant viruses are remarkable for their large genomes, often rivaling those of small bacteria, and for having genes thought exclusive to cellular life. Most isolated to date infect nonmarine protists, leaving their strategies and prevalence in marine environments largely unknown. Using eukaryotic single-cell metagenomics in the Pacific, we discovered a Mimiviridae lineage of giant viruses, which infects choanoflagellates, widespread protistan predators related to metazoans. The ChoanoVirus genomes are the largest yet from pelagic ecosystems, with 442 of 862 predicted proteins lacking known homologs. They are enriched in enzymes for modifying organic compounds, including degradation of chitin, an abundant polysaccharide in oceans, and they encode 3 divergent type-1 rhodopsins (VirR) with distinct evolutionary histories from those that capture sunlight in cellular organisms. One (VirRDTS) is similar to the only other putative rhodopsin from a virus (PgV) with a known host (a marine alga). Unlike the algal virus, ChoanoViruses encode the entire pigment biosynthesis pathway and cleavage enzyme for producing the required chromophore, retinal. We demonstrate that the rhodopsin shared by ChoanoViruses and PgV binds retinal and pumps protons. Moreover, our 1.65-Å resolved VirRDTS crystal structure and mutational analyses exposed differences from previously characterized type-1 rhodopsins, all of which come from cellular organisms. Multiple VirR types are present in metagenomes from across surface oceans, where they are correlated with and nearly as abundant as a canonical marker gene from Mimiviridae Our findings indicate that light-dependent energy transfer systems are likely common components of giant viruses of photosynthetic and phagotrophic unicellular marine eukaryotes
A distinct lineage of giant viruses brings a rhodopsin photosystem to unicellular marine predators
Significance:
Although viruses are well-characterized regulators of eukaryotic algae, little is known about those infecting unicellular predators in oceans. We report the largest marine virus genome yet discovered, found in a wild predatory choanoflagellate sorted away from other Pacific microbes and pursued using integration of cultivation-independent and laboratory methods. The giant virus encodes nearly 900 proteins, many unlike known proteins, others related to cellular metabolism and organic matter degradation, and 3 type-1 rhodopsins. The viral rhodopsin that is most abundant in ocean metagenomes, and also present in an algal virus, pumps protons when illuminated, akin to cellular rhodopsins that generate a proton-motive force. Giant viruses likely provision multiple host species with photoheterotrophic capacities, including predatory unicellular relatives of animals.
Abstract:
Giant viruses are remarkable for their large genomes, often rivaling those of small bacteria, and for having genes thought exclusive to cellular life. Most isolated to date infect nonmarine protists, leaving their strategies and prevalence in marine environments largely unknown. Using eukaryotic single-cell metagenomics in the Pacific, we discovered a Mimiviridae lineage of giant viruses, which infects choanoflagellates, widespread protistan predators related to metazoans. The ChoanoVirus genomes are the largest yet from pelagic ecosystems, with 442 of 862 predicted proteins lacking known homologs. They are enriched in enzymes for modifying organic compounds, including degradation of chitin, an abundant polysaccharide in oceans, and they encode 3 divergent type-1 rhodopsins (VirR) with distinct evolutionary histories from those that capture sunlight in cellular organisms. One (VirRDTS) is similar to the only other putative rhodopsin from a virus (PgV) with a known host (a marine alga). Unlike the algal virus, ChoanoViruses encode the entire pigment biosynthesis pathway and cleavage enzyme for producing the required chromophore, retinal. We demonstrate that the rhodopsin shared by ChoanoViruses and PgV binds retinal and pumps protons. Moreover, our 1.65-Å resolved VirRDTS crystal structure and mutational analyses exposed differences from previously characterized type-1 rhodopsins, all of which come from cellular organisms. Multiple VirR types are present in metagenomes from across surface oceans, where they are correlated with and nearly as abundant as a canonical marker gene from Mimiviridae. Our findings indicate that light-dependent energy transfer systems are likely common components of giant viruses of photosynthetic and phagotrophic unicellular marine eukaryotes
Following Mitochondrial Footprints through a Long Mucosal Path to Lung Cancer
BACKGROUND:Mitochondrial DNA (mtDNA) mutations are reported in different tumors. However, there is no information on the temporal development of the mtDNA mutations/content alteration and their extent in normal and abnormal mucosa continuously exposed to tobacco smoke in lung cancer patients. METHODOLOGY:We examined the pattern of mtDNA alteration (mtDNA mutation and content index) in 25 airway mucosal biopsies, corresponding tumors and normal lymph nodes obtained from three patients with primary lung cancers. In addition, we examined the pattern of mtDNA mutation in corresponding tumors and normal lymph nodes obtained from eight other patients with primary lung cancers. The entire 16.5 kb mitochondrial genome was sequenced on Affymetrix Mitochip v2.0 sequencing platform in every sample. To examine mtDNA content index, we performed real-time PCR analysis. PRINCIPAL FINDINGS:The airway mucosal biopsies obtained from three lung cancer patients were histopathologically negative but exhibited multiple clonal mtDNA mutations detectable in the corresponding tumors. One of the patients was operated twice for the removal of tumor from the right upper and left lower lobe respectively within a span of two years. Both of these tumors exhibited twenty identical mtDNA mutations. MtDNA content increased significantly (P<0.001) in the lung cancer and all the histologically negative mucosal biopsies except one compared to the control lymph node. CONCLUSIONS/SIGNIFICANCE:Our results document the extent of massive clonal patches that develop in lifetime smokers and ultimately give rise to clinically significant cancers. These observations shed light on the extent of disease in the airway of smokers traceable through mtDNA mutation. MtDNA mutation could be a reliable tool for molecular assessment of respiratory epithelium exposed to continuous smoke as well as disease detection and monitoring. Functional analysis of the pathogenic mtDNA mutations may be useful to understand their role in lung tumorigenesis
Development of Base Train Equivalents to Standardize Trains for Capacity Analysis
A conventional railway system usually has multiple train types with various service patterns operating on the same line. Differences in train characteristics lead to varied capacity effects on the system. Rail line capacity is commonly defined as the maximum number of trains that can be operated on a section of track with an expected level of service within a given time period. However, a particular unit (trains/hour or trains/day) does not reflect the train type the unit refers to. In this study, a new concept is proposed, namely, the base train equivalent (BTE), along with a standardization process to classify different train types in accordance with the particular type defined by the user. This concept is similar to the passenger car equivalent, which converts trucks to passenger car units in classifying highway transportation. A delay-based approach is also developed to determine BTEs on the basis of results obtained from two common capacity evaluation methods: parametric capacity analysis and simulation. With the proposed method, capacity measurements from different lines or systems can be compared and evaluated, resulting in meaningful and useful attributes
Comprehensive Approach to Allocate Reliability and Cost in Passenger Rail System Design
Rail system design and procurement comprise the process of identifying, acquiring, selecting, and purchasing the right products to form a rail system. To acquire a new system, various products with specific costs and reliability for each subsystem and corresponding components are chosen from equipment suppliers. Planners must carefully examine the trade-offs between life-cycle cost (LCC), system reliability, and service reliability to allocate resources optimally. This study developed a comprehensive allocation process with four types of optimization models for passenger rail system design: (a) maximization of system reliability, (b) maximization of service reliability, (c) minimization of LCC, and (d) minimization of a combination of service unreliability (delay cost) and LCC. On the basis of the characteristics of a passenger rail system and possible alternatives, the proposed process can allocate LCC and service reliability optimally to determine the ideal investment plan for rail system design. Empirical case studies have demonstrated that the proposed optimization process and models can evaluate efficiently and successfully all possible alternatives and determine the best allocation among all subsystems and corresponding components. This comprehensive approach can help users identify the ideal balance between cost and reliability to achieve an optimal rail system design
Railway Capacity Model and Decision Support Process for Strategic Capacity Planning
The demand for railway transportation is expected to increase significantly worldwide and railway agencies are looking for better tools to allocate their capital investments in capacity planning in the best possible way. A capacity model has been developed to evaluate the network capacity of a conventional railway system with predominantly passenger trains. A capacity planning process is presented to help planners enumerate possible expansion options and to determine the optimal network investment plan for meeting future demand. Use of this capacity evaluation tool and capacity planning process will help railway agencies provide satisfactory service to their customers and pleasing returns on shareholder investments
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