Computational identification of novel biochemical systems involved in oxidation,glycosylation and other complex modifications of bases in DNA

Discovery of the TET/JBP family of dioxygenases that modify bases in DNA has sparked considerable interest in novel DNA base modifications and their biological roles. Using sensitive sequence and structure analyses combined with contextual information from comparative genomics, we computationally characterize over 12 novel biochemical systems for DNA modifications. We predict previously unidentified enzymes, such as the kinetoplastid J-base generating glycosyltransferase (and its homolog GREB1), the catalytic specificity of bacteriophage TET/JBP proteins and their role in complex DNA base modifications. We also predict the enzymes involved in synthesis of hypermodified bases such as alpha-glutamylthymine and alpha-putrescinylthymine that have remained enigmatic for several decades. Moreover, the current analysis suggests that bacteriophages and certain nucleo-cytoplasmic large DNA viruses contain an unexpectedly diverse range of DNA modification systems, in addition to those using previously characterized enzymes such as Dam, Dcm, TET/JBP, pyrimidine hydroxymethylases, Mom and glycosyltransferases. These include enzymes generating modified bases such as deazaguanines related to queuine and archaeosine, pyrimidines comparable with lysidine, those derived using modified S-adenosyl methionine derivatives and those using TET/JBP-generated hydroxymethyl pyrimidines as biosynthetic starting points. We present evidence that some of these modification systems are also widely dispersed across prokaryotes and certain eukaryotes such as basidiomycetes, chlorophyte and stramenopile alga, where they could serve as novel epigenetic marks for regulation or discrimination of self from non-self DNA. Our study extends the role of the PUA-like fold domains in recognition of modified nucleic acids and predicts versions of the ASCH and EVE domains to be novel ‘readers’ of modified bases in DNA. These results open opportunities for the investigation of the biology of these systems and their use in biotechnology.     

Predicting the accuracy of multiple sequence alignment algorithms by using computational intelligent techniques

Multiple sequence alignments (MSAs) have become one of the most studied approaches in bioinformatics to perform other outstanding tasks such as structure prediction, biological function analysis or next-generation sequencing. However, current MSA algorithms do not always provide consistent solutions, since alignments become increasingly difficult when dealing with low similarity sequences. As widely known, these algorithms directly depend on specific features of the sequences, causing relevant influence on the alignment accuracy. Many MSA tools have been recently designed but it is not possible to know in advance which one is the most suitable for a particular set of sequences. In this work, we analyze some of the most used algorithms presented in the bibliography and their dependences on several features. A novel intelligent algorithm based on least square support vector machine is then developed to predict how accurate each alignment could be, depending on its analyzed features. This algorithm is performed with a dataset of 2180 MSAs. The proposed system first estimates the accuracy of possible alignments. The most promising methodologies are then selected in order to align each set of sequences. Since only one selected algorithm is run, the computational time is not excessively increased.     

Matching roots to their environment

Background

Plants form the base of the terrestrial food chain and provide medicines, fuel, fibre and industrial materials to humans. Vascular land plants rely on their roots to acquire the water and mineral elements necessary for their survival in nature or their yield and nutritional quality in agriculture. Major biogeochemical fluxes of all elements occur through plant roots, and the roots of agricultural crops have a significant role to play in soil sustainability, carbon sequestration, reducing emissions of greenhouse gasses, and in preventing the eutrophication of water bodies associated with the application of mineral fertilizers.

Scope

This article provides the context for a Special Issue of Annals of Botany on ‘Matching Roots to Their Environment’. It first examines how land plants and their roots evolved, describes how the ecology of roots and their rhizospheres contributes to the acquisition of soil resources, and discusses the influence of plant roots on biogeochemical cycles. It then describes the role of roots in overcoming the constraints to crop production imposed by hostile or infertile soils, illustrates root phenotypes that improve the acquisition of mineral elements and water, and discusses high-throughput methods to screen for these traits in the laboratory, glasshouse and field. Finally, it considers whether knowledge of adaptations improving the acquisition of resources in natural environments can be used to develop root systems for sustainable agriculture in the future.     

Mycorrhizal preference promotes habitat invasion by a native Australian orchid: Microtis media

Background and Aims

Mycorrhizal specialization has been shown to limit recruitment capacity in orchids, but an increasing number of orchids are being documented as invasive or weed-like. The reasons for this proliferation were examined by investigating mycorrhizal fungi and edaphic correlates of Microtis media, an Australian terrestrial orchid that is an aggressive ecosystem and horticultural weed.

Methods

Molecular identification of fungi cultivated from M. media pelotons, symbiotic in vitro M. media seed germination assays, ex situ fungal baiting of M. media and co-occurring orchid taxa (Caladenia arenicola, Pterostylis sanguinea and Diuris magnifica) and soil physical and chemical analyses were undertaken.

Key Results

It was found that: (1) M. media associates with a broad taxonomic spectrum of mycobionts including Piriformospora indica, Sebacina vermifera, Tulasnella calospora and Ceratobasidium sp.; (2) germination efficacy of mycorrhizal isolates was greater for fungi isolated from plants in disturbed than in natural habitats; (3) a higher percentage of M. media seeds germinate than D. magnifica, P. sanguinea or C. arenicola seeds when incubated with soil from M. media roots; and (4) M. media–mycorrhizal fungal associations show an unusual breadth of habitat tolerance, especially for soil phosphorus (P) fertility.

Conclusions

The findings in M. media support the idea that invasive terrestrial orchids may associate with a diversity of fungi that are widespread and common, enhance seed germination in the host plant but not co-occurring orchid species and tolerate a range of habitats. These traits may provide the weedy orchid with a competitive advantage over co-occurring orchid species. If so, invasive orchids are likely to become more broadly distributed and increasingly colonize novel habitats.     

Structural insights into the targeting of mRNA GU-rich elements by the three RRMs of CELF1

The CUG-BP, Elav-like family (CELF) of RNA-binding proteins control gene expression at a number of different levels by regulating pre-mRNA splicing, deadenylation and mRNA stability. We present structural insights into the binding selectivity of CELF member 1 (CELF1) for GU-rich mRNA target sequences of the general form 5′-UGUN_xUGUN_yUGU and identify a high affinity interaction (K_d ∼ 100 nM for x = 2 and y = 4) with simultaneous binding of all three RNA recognition motifs within a single 15-nt binding element. RNA substrates spin-labelled at either the 3′ or 5′ terminus result in differential nuclear magnetic resonance paramagnetic relaxation enhancement effects, which are consistent with a non-sequential 2-1-3 arrangement of the three RNA recognition motifs on UGU sites in a 5′ to 3′ orientation along the RNA target. We further demonstrate that CELF1 binds to dispersed single-stranded UGU sites at the base of an RNA hairpin providing a structural rationale for recognition of CUG expansion repeats and splice site junctions in the regulation of alternative splicing.     

ParseCNV integrative copy number variation association software with quality tracking

A number of copy number variation (CNV) calling algorithms exist; however, comprehensive software tools for CNV association studies are lacking. We describe ParseCNV, unique software that takes CNV calls and creates probe-based statistics for CNV occurrence in both case–control design and in family based studies addressing both de novo and inheritance events, which are then summarized based on CNV regions (CNVRs). CNVRs are defined in a dynamic manner to allow for a complex CNV overlap while maintaining precise association region. Using this approach, we avoid failure to converge and non-monotonic curve fitting weaknesses of programs, such as CNVtools and CNVassoc, and although Plink is easy to use, it only provides combined CNV state probe-based statistics, not state-specific CNVRs. Existing CNV association methods do not provide any quality tracking information to filter confident associations, a key issue which is fully addressed by ParseCNV. In addition, uncertainty in CNV calls underlying CNV associations is evaluated to verify significant results, including CNV overlap profiles, genomic context, number of probes supporting the CNV and single-probe intensities. When optimal quality control parameters are followed using ParseCNV, 90% of CNVs validate by polymerase chain reaction, an often problematic stage because of inadequate significant association review. ParseCNV is freely available at http://parsecnv.sourceforge.net.