8,964 research outputs found
No wisdom in the crowd: genome annotation at the time of big data - current status and future prospects
Science and engineering rely on the accumulation
and dissemination of knowledge to make discoveries
and create new designs. Discovery-driven genome
research rests on knowledge passed on via gene
annotations. In response to the deluge of sequencing
big data, standard annotation practice employs automated
procedures that rely on majority rules. We
argue this hinders progress through the generation
and propagation of errors, leading investigators into
blind alleys. More subtly, this inductive process discourages
the discovery of novelty, which remains
essential in biological research and reflects the nature
of biology itself. Annotation systems, rather than
being repositories of facts, should be tools that support
multiple modes of inference. By combining
deduction, induction and abduction, investigators can
generate hypotheses when accurate knowledge is
extracted from model databases. A key stance is to
depart from ‘the sequence tells the structure tells the
function’ fallacy, placing function first. We illustrate
our approach with examples of critical or unexpected
pathways, using MicroScope to demonstrate how
tools can be implemented following the principles we
advocate. We end with a challenge to the reader
Sequencing the potato genome: outline and first results to come from the elucidation of the sequence of the world's third most important food crop
Potato is a member of the Solanaceae, a plant family that includes several other economically important species, such as tomato, eggplant, petunia, tobacco and pepper. The Potato Genome Sequencing Consortium (PGSC) aims to elucidate the complete genome sequence of potato, the third most important food crop in the world. The PGSC is a collaboration between 13 research groups from China, India, Poland, Russia, the Netherlands, Ireland, Argentina, Brazil, Chile, Peru, USA, New Zealand and the UK. The potato genome consists of 12 chromosomes and has a (haploid) length of approximately 840 million base pairs, making it a medium-sized plant genome. The sequencing project builds on a diploid potato genomic bacterial artificial chromosome (BAC) clone library of 78000 clones, which has been fingerprinted and aligned into ~7000 physical map contigs. In addition, the BAC-ends have been sequenced and are publicly available. Approximately 30000 BACs are anchored to the Ultra High Density genetic map of potato, composed of 10000 unique AFLPTM markers. From this integrated genetic-physical map, between 50 to 150 seed BACs have currently been identified for every chromosome. Fluorescent in situ hybridization experiments on selected BAC clones confirm these anchor points. The seed clones provide the starting point for a BAC-by-BAC sequencing strategy. This strategy is being complemented by whole genome shotgun sequencing approaches using both 454 GS FLX and Illumina GA2 instruments. Assembly and annotation of the sequence data will be performed using publicly available and tailor-made tools. The availability of the annotated data will help to characterize germplasm collections based on allelic variance and to assist potato breeders to more fully exploit the genetic potential of potat
Crosstalk and the Dynamical Modularity of Feed-Forward Loops in Transcriptional Regulatory Networks
Network motifs, such as the feed-forward loop (FFL), introduce a range of complex behaviors to transcriptional regulatory networks, yet such properties are typically determined from their isolated study. We characterize the effects of crosstalk on FFL dynamics by modeling the cross regulation between two different FFLs and evaluate the extent to which these patterns occur in vivo. Analytical modeling suggests that crosstalk should overwhelmingly affect individual protein-expression dynamics. Counter to this expectation we find that entire FFLs are more likely than expected to resist the effects of crosstalk (approximate to 20% for one crosstalk interaction) and remain dynamically modular. The likelihood that cross-linked FFLs are dynamically correlated increases monotonically with additional crosstalk, but is independent of the specific regulation type or connectivity of the interactions. Just one additional regulatory interaction is sufficient to drive the FFL dynamics to a statistically different state. Despite the potential for modularity between sparsely connected network motifs, Escherichia coli (E. coli) appears to favor crosstalk wherein at least one of the cross-linked FFLs remains modular. A gene ontology analysis reveals that stress response processes are significantly overrepresented in the cross-linked motifs found within E. coli. Although the daunting complexity of biological networks affects the dynamical properties of individual network motifs, some resist and remain modular, seemingly insulated from extrinsic perturbations-an intriguing possibility for nature to consistently and reliably provide certain network functionalities wherever the need arise
Ancestral genome estimation reveals the history of ecological diversification in Agrobacterium
Horizontal gene transfer (HGT) is considered as a major source of innovation in bacteria, and as such is expected to drive adaptation to new ecological niches. However, among the many genes acquired through HGT along the diversification history of genomes, only a fraction may have actively contributed to sustained ecological adaptation. We used a phylogenetic approach accounting for the transfer of genes (or groups of genes) to estimate the history of genomes in Agrobacterium biovar 1, a diverse group of soil and plant-dwelling bacterial species. We identified clade-specific blocks of cotransferred genes encoding coherent biochemical pathways that may have contributed to the evolutionary success of key Agrobacterium clades. This pattern of gene coevolution rejects a neutral model of transfer, in which neighboring genes would be transferred independently of their function and rather suggests purifying selection on collectively coded acquired pathways. The acquisition of these synapomorphic blocks of cofunctioning genes probably drove the ecological diversification of Agrobacterium and defined features of ancestral ecological niches, which consistently hint at a strong selective role of host plant rhizospheres
metaSHARK: software for automated metabolic network prediction from DNA sequence and its application to the genomes of Plasmodium falciparum and Eimeria tenella
The metabolic SearcH And Reconstruction Kit
(metaSHARK) is a new fully automated software package
for the detection of enzyme-encoding genes
within unannotated genome data and their visualization
in the context of the surrounding metabolic network.
The gene detection package (SHARKhunt) runs
on a Linux systemand requires only a set of raw DNA
sequences (genomic, expressed sequence tag and/
or genome survey sequence) as input. Its output
may be uploaded to our web-based visualization
tool (SHARKview) for exploring and comparing data
from different organisms. We first demonstrate the
utility of the software by comparing its results for
the raw Plasmodium falciparum genome with the
manual annotations available at the PlasmoDB and
PlasmoCyc websites. We then apply SHARKhunt to
the unannotated genome sequences of the coccidian
parasite Eimeria tenella and observe that, at an
E-value cut-off of 10(-20), our software makes 142
additional assertions of enzymatic function compared
with a recent annotation package working
with translated open reading frame sequences. The
ability of the software to cope with low levels of
sequence coverage is investigated by analyzing
assemblies of the E.tenella genome at estimated
coverages from 0.5x to 7.5x. Lastly, as an example
of how metaSHARK can be used to evaluate the
genomic evidence for specific metabolic pathways,
we present a study of coenzyme A biosynthesis in
P.falciparum and E.tenella
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