Transferability of the EST-SSRs developed on Nules clementine (<Emphasis Type="Italic">Citrus clementina</Emphasis> Hort ex Tan) to other <Emphasis Type="Italic">Citrus</Emphasis> species and their effectiveness for genetic mapping

Background

During the last decade, numerous microsatellite markers were developed for genotyping and to identify closely related plant genotypes. In citrus, previously developed microsatellite markers were arisen from genomic libraries and more often located in non coding DNA sequences. To optimize the use of these EST-SSRs as genetic markers in genome mapping programs and citrus systematic analysis, we have investigated their polymorphism related to the type (di or trinucleotide) or their position in the coding sequences.

Results

Among 11000 unigenes from a Clementine EST library, we have found at least one microsatellite sequence (repeated units size ranged from 2 to 6 nucleotides) in 1500 unigenes (13.6%). More than 95% of these SSRs were di or trinucleotides. If trinucleotide microsatellites were encountered trough all part of EST sequences, dinucleotide microsatellites were preferentially (50%) concentrated in the 5' 100th nucleotides. We assessed the polymorphism of 41 EST-SSR, by PCR amplification droved with flanking primers among ten Citrus species plus 3 from other genera. More than 90% of EST-SSR markers were polymorphic. Furthermore, dinucleotide microsatellite markers were more polymorphic than trinucleotide ones, probably related to their distribution that was more often located in the 5' UnTranslated Region (UTR). We obtained a good agreement of diversity relationships between the citrus species and relatives assessed with EST-SSR markers with the established taxonomy and phylogeny. To end, the heterozygosity of each genotype and all dual combinations were studied to evaluate the percentage of mappable markers. Higher values (> 45%) were observed for putative Citrus inter-specific hybrids (lime lemon, or sour orange) than for Citrus basic true species (mandarin, pummelo and citron) (<30%). Most favorable combinations for genome mapping were observed in those involving interspecific hybrid genotypes. Those gave higher levels of mappable markers (>70%) with a significant proportion suitable for synteny analysis.

Conclusion

Fourty one new EST-SSR markers were produced and were available for citrus genetic studies. Whatever the position of the SSR in the ESTs the EST-SSR markers we developed are powerful to investigate genetic diversity and genome mapping in citrus.

     

Inferring angiosperm phylogeny from EST data with widespread gene duplication

Background

Most studies inferring species phylogenies use sequences from single copy genes or sets of orthologs culled from gene families. For taxa such as plants, with very high levels of gene duplication in their nuclear genomes, this has limited the exploitation of nuclear sequences for phylogenetic studies, such as those available in large EST libraries. One rarely used method of inference, gene tree parsimony, can infer species trees from gene families undergoing duplication and loss, but its performance has not been evaluated at a phylogenomic scale for EST data in plants.

Results

A gene tree parsimony analysis based on EST data was undertaken for six angiosperm model species and Pinus, an outgroup. Although a large fraction of the tentative consensus sequences obtained from the TIGR database of ESTs was assembled into homologous clusters too small to be phylogenetically informative, some 557 clusters contained promising levels of information. Based on maximum likelihood estimates of the gene trees obtained from these clusters, gene tree parsimony correctly inferred the accepted species tree with strong statistical support. A slight variant of this species tree was obtained when maximum parsimony was used to infer the individual gene trees instead.

Conclusion

Despite the complexity of the EST data and the relatively small fraction eventually used in inferring a species tree, the gene tree parsimony method performed well in the face of very high apparent rates of duplication.

     

GLOSSary: the GLobal Ocean 16S subunit web accessible resource

Background

Environmental metagenomics is a challenging approach that is exponentially spreading in the scientific community to investigate taxonomic diversity and possible functions of the biological components. The massive amount of sequence data produced, often endowed with rich environmental metadata, needs suitable computational tools to fully explore the embedded information. Bioinformatics plays a key role in providing methodologies to manage, process and mine molecular data, integrated with environmental metagenomics collections. One such relevant example is represented by the Tara Ocean Project.

Results

We considered the Tara 16S miTAGs released by the consortium, representing raw sequences from a shotgun metagenomics approach with similarities to 16S rRNA genes. We generated assembled 16S rDNA sequences, which were classified according to their lengths, the possible presence of chimeric reads, the putative taxonomic affiliation. The dataset was included in GLOSSary (the GLobal Ocean 16S Subunit web accessible resource), a bioinformatics platform to organize environmental metagenomics data. The aims of this work were: i) to present alternative computational approaches to manage challenging metagenomics data; ii) to set up user friendly web-based platforms to allow the integration of environmental metagenomics sequences and of the associated metadata; iii) to implement an appropriate bioinformatics platform supporting the analysis of 16S rDNA sequences exploiting reference datasets, such as the SILVA database. We organized the data in a next-generation NoSQL “schema-less” database, allowing flexible organization of large amounts of data and supporting native geospatial queries. A web interface was developed to permit an interactive exploration and a visual geographical localization of the data, either raw miTAG reads or 16S contigs, from our processing pipeline. Information on unassembled sequences is also available. The taxonomic affiliations of contigs and miTAGs, and the spatial distribution of the sampling sites and their associated sequence libraries, as they are contained in the Tara metadata, can be explored by a query interface, which allows both textual and visual investigations. In addition, all the sequence data were made available for a dedicated BLAST-based web application alongside the SILVA collection.

Conclusions

GLOSSary provides an expandable bioinformatics environment, able to support the scientific community in current and forthcoming environmental metagenomics analyses.

     

LitMiner: integration of library services within a bio-informatics application

Background

This paper examines how the adoption of a subject-specific library service has changed the way in which its users interact with a digital library. The LitMiner text-analysis application was developed to enable biologists to explore gene relationships in the published literature. The application features a suite of interfaces that enable users to search PubMed as well as local databases, to view document abstracts, to filter terms, to select gene name aliases, and to visualize the co-occurrences of genes in the literature. At each of these stages, LitMiner offers the functionality of a digital library. Documents that are accessible online are identified by an icon. Users can also order documents from their institution's library collection from within the application. In so doing, LitMiner aims to integrate digital library services into the research process of its users.

Methods

Case study

Results

This integration of digital library services into the research process of biologists results in increased access to the published literature.

Conclusion

In order to make better use of their collections, digital libraries should customize their services to suit the research needs of their patrons.

     

Development of SSR markers and identification of major quantitative trait loci controlling shelling percentage in cultivated peanut (<Emphasis Type="Italic">Arachis hypogaea</Emphasis> L.)

Key message

A total of 204,439 SSR markers were developed in diploid genomes, and 25 QTLs for shelling percentage were identified in a RIL population across 4 years including five consistent QTLs.

Abstract

Cultivated peanut (Arachis hypogaea L.) is an important grain legume providing edible oil and protein for human nutrition. Genome sequences of its diploid ancestors, Arachis duranensis and A. ipaensis, were reported, but their SSRs have not been well exploited and utilized hitherto. Shelling percentage is an important economic trait and its improvement has been one of the major objectives in peanut breeding programs. In this study, the genome sequences of A. duranensis and A. ipaensis were used to develop SSR markers, and a mapping population (Yuanza 9102 × Xuzhou 68-4) with 195 recombinant inbred lines was used to map QTLs controlling shelling percentage. The numbers of newly developed SSR markers were 84,383 and 120,056 in the A. duranensis and A. ipaensis genomes, respectively. Genotyping of the mapping population was conducted with both newly developed and previously reported markers. QTL analysis using the phenotyping data generated in Wuhan across four consecutive years and genotyping data of 830 mapped loci identified 25 QTLs with 4.46–17.01% of phenotypic variance explained in the four environments. Meta-analysis revealed five consistent QTLs that could be detected in at least two environments. Notably, the consistent QTL cqSPA09 was detected in all four environments and explained 10.47–17.01% of the phenotypic variance. The segregation in the progeny of a residual heterozygous line confirmed that the cpSPA09 locus had additive effect in increasing shelling percentage. These consistent and major QTL regions provide opportunity not only for further gene discovery, but also for the development of functional markers for breeding.

     

PMicroRNA-124a regulates LPS-induced septic cardiac dysfunction by targeting STX2

Objective

To examine the role of miR-124a in LPS-induced septic cardiac insufficiency where underlying mechanism is unclear.

Results

Expression of miR-124a was decreased in myocardium of LPS-induced septic cardiac dysfunction model. miR-124a antagomiR or agomiR were injected via tail vein to induce miR-124a-dysregulated model. miR-124a antagomiR aggravated LPS-induced cardiac dysfunction and apoptosis, while miR-124a agomiR had the opposite effect. Syntaxin-2 (STX2) was indicated as a candidate target gene by bioinformatic software. Further experiments confirmed that STX2 was downregulated in miR-124a agomiR-treated rats but upregulated in miR-124a antagomiR-treated rats, and STX2 inhibition could strongly block the miR-124a antagomiR-associated increase in cell apoptosis. Luciferase reporter activity assay indicated that STX2 was a direct target of miR-124a. Serological detection reveled that miR-124a was down-regulated in the plasma of septic cardiac dysfunction rats.

Conclusions

miR-124a aggravates LPS-induced cardiac dysfunction and the miR-124a/STX2 pathway might serve as the potential diagnostic and therapeutic targets for septic cardiac dysfunction.

     

Multi-target drug repositioning by bipartite block-wise sparse multi-task learning

Background

Finding potential drug targets is a crucial step in drug discovery and development. Recently, resources such as the Library of Integrated Network-Based Cellular Signatures (LINCS) L1000 database provide gene expression profiles induced by various chemical and genetic perturbations and thereby make it possible to analyze the relationship between compounds and gene targets at a genome-wide scale. Current approaches for comparing the expression profiles are based on pairwise connectivity mapping analysis. However, this method makes the simple assumption that the effect of a drug treatment is similar to knocking down its single target gene. Since many compounds can bind multiple targets, the pairwise mapping ignores the combined effects of multiple targets, and therefore fails to detect many potential targets of the compounds.

Results

We propose an algorithm to find sets of gene knock-downs that induce gene expression changes similar to a drug treatment. Assuming that the effects of gene knock-downs are additive, we propose a novel bipartite block-wise sparse multi-task learning model with super-graph structure (BBSS-MTL) for multi-target drug repositioning that overcomes the restrictive assumptions of connectivity mapping analysis.

Conclusions

The proposed method BBSS-MTL is more accurate for predicting potential drug targets than the simple pairwise connectivity mapping analysis on five datasets generated from different cancer cell lines.

Availability

The code can be obtained at http://gr.xjtu.edu.cn/web/liminli/codes.

     

Metabolic markers for differentiation between renal allograft rejection and immunosuppressant toxicity in rat urine

Introduction

Although current immunosuppressive protocols have dramatically improved 1-year survival of kidney transplants, there has been less progress in terms of long-term graft survival over the last two decades. The key to avoiding late graft loss is early diagnosis and differentiation between anti-allograft immune processes and immunosuppressant toxicity (IS-Tox). Modern bioanalytical technologies have opened new opportunities for the development of sensitive and specific diagnostic tools. There is an immediate need for biomarkers that are able to differentiate between renal allograft rejection and immunosuppressant toxicity.

Objective

To test our hypothesis that changes of metabolite patterns in urine have the potential to serve as a non-invasive combinatorial biomarker that can differentiate between allograft immune reactions and IS-Tox.

Methods

We used ¹H-NMR spectroscopy and Luminex multiplexing for metabolic profiling of rat urine and the analysis of protein biomarkers in urine and plasma, respectively, to compare the effects of chronic allograft rejection in a Fisher-to-Lewis rat transplant model with IS-Tox induced by cyclosporine, tacrolimus and/or sirolimus in Lewis rats.

Results

Our results showed that, while IS-Tox caused changes in metabolite patterns that are typically associated with proximal tubule damage, rejection caused more profuse changes not specifically focused on a particular kidney region. Moreover, metabolite pattern changes were more sensitive than changes in protein markers that were evident only during the later stages of rejection.

Conclusion

The present study provides first proof-of-concept that longitudinal monitoring of urine metabolite markers has the potential to differentiate between early renal allograft rejection and immunosuppressant nephrotoxicity.

     

Identification of novel therapeutics for complex diseases from genome-wide association data

Background

Human genome sequencing has enabled the association of phenotypes with genetic loci, but our ability to effectively translate this data to the clinic has not kept pace. Over the past 60 years, pharmaceutical companies have successfully demonstrated the safety and efficacy of over 1,200 novel therapeutic drugs via costly clinical studies. While this process must continue, better use can be made of the existing valuable data. In silico tools such as candidate gene prediction systems allow rapid identification of disease genes by identifying the most probable candidate genes linked to genetic markers of the disease or phenotype under investigation. Integration of drug-target data with candidate gene prediction systems can identify novel phenotypes which may benefit from current therapeutics. Such a drug repositioning tool can save valuable time and money spent on preclinical studies and phase I clinical trials.

Methods

We previously used Gentrepid (http://www.gentrepid.org) as a platform to predict 1,497 candidate genes for the seven complex diseases considered in the Wellcome Trust Case-Control Consortium genome-wide association study; namely Type 2 Diabetes, Bipolar Disorder, Crohn's Disease, Hypertension, Type 1 Diabetes, Coronary Artery Disease and Rheumatoid Arthritis. Here, we adopted a simple approach to integrate drug data from three publicly available drug databases: the Therapeutic Target Database, the Pharmacogenomics Knowledgebase and DrugBank; with candidate gene predictions from Gentrepid at the systems level.

Results

Using the publicly available drug databases as sources of drug-target association data, we identified a total of 428 candidate genes as novel therapeutic targets for the seven phenotypes of interest, and 2,130 drugs feasible for repositioning against the predicted novel targets.

Conclusions

By integrating genetic, bioinformatic and drug data, we have demonstrated that currently available drugs may be repositioned as novel therapeutics for the seven diseases studied here, quickly taking advantage of prior work in pharmaceutics to translate ground-breaking results in genetics to clinical treatments.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

New microsatellite markers developed from <Emphasis Type="Italic">Urochloa humidicola</Emphasis> (Poaceae) and cross amplification in different <Emphasis Type="Italic">Urochloa</Emphasis> species

Background

Urochloa humidicola is a forage grass that grows in tropical regions and is recognized for its tolerance to seasonal flooding. It is a polyploid and apomictic species with high phenotypic plasticity. As molecular tools are important in facilitating the development of new cultivars and in the classification of related species, the objectives of this study were to develop new polymorphic microsatellite markers from an enriched library constructed from U. humidicola and to evaluate their transferability to other Urochloa species.

Findings

Microsatellite sequences were identified from a previously constructed enriched library, and specific primers were designed for 40 loci. Isolated di-nucleotide repeat motifs were the most abundant followed by tetra-nucleotide repeats. Of the tested loci, 38 displayed polymorphism when screened across 34 polyploid Urochloa sp. genotypes, including 20 accessions and six hybrids of U. humidicola and two accessions each from U. brizantha, U. dictyoneura, U. decumbens and U. ruziziensis. The number of bands per Simple Sequence Repeat (SSR) locus ranged from one to 29 with a mean of 11.5 bands per locus. The mean Polymorphism Information Content (PIC) of all loci was 0.7136, and the mean Discrimination Power (DP) was 0.7873. Six loci amplified in all species tested. STRUCTURE analysis revealed six different allelic pools, and the genetic similarity values analyzed using Jaccard's coefficient ranged from 0.000 to 0.913.

Conclusions

This work reports new polymorphic microsatellite markers that will be useful for breeding programs for Urochloa humidicola and other Urochloa species as well as for genetic map development, germplasm characterization, evolutionary and taxonomic studies and marker-assisted trait selection.

     

Fine mapping and candidate gene analysis of <Emphasis Type="Italic">qFL-chr1</Emphasis>, a fiber length QTL in cotton

Key message

A fiber length QTL, qFL-chr1, was fine mapped to a 0.9 cM interval of cotton chromosome 1. Two positional candidate genes showed positive correlation between gene expression level and fiber length.

Abstract

Prior analysis of a backcross-self mapping population derived from a cross between Gossypium hirsutum L. and G. barbadense L. revealed a QTL on chromosome 1 associated with increased fiber length (qFL-chr1), which was confirmed in three independent populations of near-isogenic introgression lines (NIILs). Here, a single NIIL, R01-40-08, was used to develop a large population segregating for the target region. Twenty-two PCR-based polymorphic markers used to genotype 1672 BC₄F₂ plants identified 432 recombinants containing breakpoints in the target region. Substitution mapping using 141 informative recombinants narrowed the position of qFL-chr1 to a 1.0-cM interval between SSR markers MUSS084 and CIR018. To exclude possible effects of non-target introgressions on fiber length, different heterozygous BC₄F₃ plants introgressed between SSR markers NAU3384 and CGR5144 were selected to develop sub-NILs. The qFL-chr1 was further mapped at 0.9-cM interval between MUSS422 and CIR018 by comparisons of sub-NIL phenotype, and increased fiber length by ~1 mm. The 2.38-Mb region between MUSS422 and CIR018 in G. barbadense contained 19 annotated genes. Expression levels of two of these genes, GOBAR07705 (encoding 1-aminocyclopropane-1-carboxylate synthase) and GOBAR25992 (encoding amino acid permease), were positively correlated with fiber length in a small F₂ population, supporting these genes as candidates for qFL-chr1.

     

MulSatDB: a first online database for mulberry microsatellites

Key message

Simple sequence repeat motifs were mined from the genome and EST sequences of Morus notabilis and archived in MulSatDB. Bioinformatics tools were integrated with the database for the analysis of genomic datasets.

Abstract

Mulberry is a crop of economic importance in sericulture, which shapes the lives of millions of rural people among different Eurasian and Latin American countries. Limited availability of genomic resources has constrained the molecular breeding efforts in mulberry, a poorly studied crop. Microsatellite or simple sequence repeat (SSR) has revolutionized the plant breeding and is used in linkage mapping, association studies, diversity, and parentage analysis, etc. Recent availability of mulberry whole genome assembly provided an opportunity for the development of mulberry-specific DNA markers. In this study, we mined a total of 217,312 microsatellites from whole genome and 961 microsatellites from EST sequences of Morus notabilis. Mono-repeats were predominant among both whole genome and EST sequences. The SSR containing EST sequences were functionally annotated, and SSRs mined from whole genome were mapped on chromosomes of the phylogenetically related genus—Fragaria vesca, to aid the selection of markers based on the function and location. All the mined markers were archived in the mulberry microsatellite database (MulSatDB), and the markers can be retrieved based on different criteria like marker location, repeat kind, motif type and size. Primer3plus and CMap tools are integrated with the database to design primers for PCR amplification and to visualize markers on F. vesca chromosomes, respectively. A blast tool is also integrated to collate new markers with the database. MulSatDB is the first and complete destination for mulberry researchers to browse SSR markers, design primers, and locate markers on strawberry chromosomes. MulSatDB is freely accessible at http://btismysore.in/mulsatdb.     

A bedr way of genomic interval processing

Background

Next-generation sequencing is making it critical to robustly and rapidly handle genomic ranges within standard pipelines. Standard use-cases include annotating sequence ranges with gene or other genomic annotation, merging multiple experiments together and subsequently quantifying and visualizing the overlap. The most widely-used tools for these tasks work at the command-line (e.g. BEDTools) and the small number of available R packages are either slow or have distinct semantics and features from command-line interfaces.

Results

To provide a robust R-based interface to standard command-line tools for genomic coordinate manipulation, we created bedr. This open-source R package can use either BEDTools or BEDOPS as a back-end and performs data-manipulation extremely quickly, creating R data structures that can be readily interfaced with existing computational pipelines. It includes data-visualization capabilities and a number of data-access functions that interface with standard databases like UCSC and COSMIC.

Conclusions

bedr package provides an open source solution to enable genomic interval data manipulation and restructuring in R programming language which is commonly used in bioinformatics, and therefore would be useful to bioinformaticians and genomic researchers.

     

A study of candidate genes for day blindness in the standard wire haired dachshund

Background

A genetic study was performed to identify candidate genes associated with day blindness in the standard wire haired dachshund. Based on a literature review of diseases in dogs and human with phenotypes similar to day blindness, ten genes were selected and evaluated as potential candidate genes associated with day blindness in the breed.

Results

Three of the genes, CNGB3, CNGA3 and GNAT2, involved in cone degeneration and seven genes and loci, ABCA4, RDH5, CORD8, CORD9, RPGRIP1, GUCY2D and CRX, reported to be involved in cone-rod dystrophies were studied. Polymorphic markers at each of the candidate loci were studied in a family with 36 informative offspring. The study revealed a high frequency of recombinations between the candidate marker alleles and the disease.

Conclusion

Since all of the markers were at the exact position of the candidate loci, and several recombinations were detected for each of the loci, all ten genes were excluded as causal for this canine, early onset cone-rod dystrophy. The described markers may, however, be useful to screen other canine resource families segregating eye diseases for association to the ten genes.