214 research outputs found
A general approach for discriminative de-novo motif discovery from highthroughput data
De novo motif discovery has been an important challenge of bioinformatics for the past two decades. Since the emergence of high-throughput techniques like ChIP-seq, ChIP-exo and protein-binding microarrays (PBMs), the focus of de novo motif discovery has shifted to runtime and accuracy on large data sets. For this purpose, specialized algorithms have been designed for discovering motifs in ChIP-seq or PBM data. However, none of the existing approaches work perfectly for all three high-throughput techniques. In this article, we propose Dimont, a general approach for fast and accurate de novo motif discovery from high-throughput data. We demonstrate that Dimont yields a higher number of correct motifs from ChIP-seq data than any of the specialized approaches and achieves a higher accuracy for predicting PBM intensities from probe sequence than any of the approaches specifically designed for that purpose. Dimont also reports the expected motifs for several ChIP-exo data sets. Investigating differences between in vitro and in vivo binding, we find that for most transcription factors, the motifs discovered by Dimont are in good accordance between techniques, but we also find notable exceptions. We also observe that modeling intra-motif dependencies may increase accuracy, which indicates that more complex motif models are a worthwhile field of research
On the search for the vernalization locus in caraway (Carum carvi) using genotyping by sequencing data
Kümmel (Carum carvi) kann in zweijährige und einjährige Blühtypen unterteilt werden. Zweijährige benötigen einen Kältereiz für die Blühinduktion, während Einjährige keinen Vernalisationsbedarf haben. Aufgrund der besseren Integration in die Fruchtfolge und der geringeren Produktionskosten wird der Anbau Einjähriger als vorteilhaft angesehen. Die verfügbaren einjährigen Sorten weisen jedoch ein unzureichendes Ertragspotential und einen zu geringen Ätherischölgehalt auf. Der zweijährige Genpool enthält wertvolle genetische Diversität, die durch Kreuzungen auf den einjährigen Genpool übertragen werden kann. Laut Literatur zeigen F1-Pflanzen aus Kreuzungen zwischen ein- und zweijährigen Blühtypen ein uniform einjähriges Blühverhalten. Resultierende F2-Populationen zeigen ein Mendelsches 3:1-Verhältnis zwischen einjährigen und zweijährigen Blühtypen. Dies deutet auf eine monogenetische Vererbung der Vernalisation beim Kümmel mit dominanter Einjährigkeit hin.
Nach Kreuzungen zwischen ein- und zweijährigen Blühtypen kann das rezessive Allel für die zweijährige Blüte über mehrere Generationen im Zuchtmaterial verbleiben. Daher wäre ein genetischer Marker, der mit dem Vernalisations-Locus assoziiert ist, vorteilhaft, um das rezessive Allel in einem Selektionsschritt zu entfernen. Um Marker zu identifizieren, die mit dem Vernalisations-Locus assoziiert sind, wurden Genotyping by Sequencing (GBS)-Daten zu 70 zweijährigen und 67 einjährigen Blühtypen genutzt. Case-Control-Studien und populationsgenetische Studien wurden durchgeführt. Insgesamt wurden 60 gemeinsame Marker gefunden, die signifikant mit dem Vernalisationsbedarf assoziiert waren. Für 19 Marker wurden diagnostische Marker entwickelt. Diese könnten in Zukunft genutzt werden, um rezessive Allele in segregierenden Populationen zu detektieren.Caraway (Carum carvi) can be divided into biennial and annual flowering types. Biennials require a cold stimulus for initiation of flowering, whereas annuals lack any vernalization requirement. Cultivation of annuals is considered advantageous due to better integration into crop rotation and reduced production costs. However, available annual varieties lack a sufficient yield potential and essential oil content. Valuable genetic diversity exists within the biennial genepool, which can be transferred to the annual genepool by crossbreeding. According to literature, F1 plants from crosses between annual and biennial flowering types uniformly show annual flowering. Resulting F2 populations show a Mendelian 3:1 ratio between annual and biennial flowering types. This indicates a monogenetic inheritance of vernalization requirement in caraway with dominant annual flowering.
After crossbreeding annual and biennial flowering types, the recessive allele for biennial flowering can remain within the breeding material over multiple generations. Thus, a genetic marker associated with the vernalization locus would be beneficial to remove the recessive allele in one selection step. To identify markers associated with vernalization requirement, we used genotyping by sequencing (GBS) data of 70 biennial and 67 annual flowering types. We conducted case-control studies and population differentiation-based tests. In total, 60 common markers were found that were significantly associated with vernalization requirement. Out of these, we developed 19 diagnostic markers. In future, these diagnostic markers might be used to detect recessive alleles in segregating populations
MotifAdjuster: a tool for computational reassessment of transcription factor binding site annotations
MotifAdjuster helps to detect errors in binding site annotations
Adaptive Matrix Metrics for Attribute Dependence Analysis in Differential High-Throughput Data
Unifying generative and discriminative learning principles
<p>Abstract</p> <p>Background</p> <p>The recognition of functional binding sites in genomic DNA remains one of the fundamental challenges of genome research. During the last decades, a plethora of different and well-adapted models has been developed, but only little attention has been payed to the development of different and similarly well-adapted learning principles. Only recently it was noticed that discriminative learning principles can be superior over generative ones in diverse bioinformatics applications, too.</p> <p>Results</p> <p>Here, we propose a generalization of generative and discriminative learning principles containing the maximum likelihood, maximum a posteriori, maximum conditional likelihood, maximum supervised posterior, generative-discriminative trade-off, and penalized generative-discriminative trade-off learning principles as special cases, and we illustrate its efficacy for the recognition of vertebrate transcription factor binding sites.</p> <p>Conclusions</p> <p>We find that the proposed learning principle helps to improve the recognition of transcription factor binding sites, enabling better computational approaches for extracting as much information as possible from valuable wet-lab data. We make all implementations available in the open-source library Jstacs so that this learning principle can be easily applied to other classification problems in the field of genome and epigenome analysis.</p
High Resolution Mapping of RphMBR1012 Conferring Resistance to Puccinia hordei in Barley (Hordeum vulgare L.)
Isolation of disease resistance genes in barley was hampered by the large genome size, but has become easy due to the availability of the reference genome sequence. During the last years, many genomic resources, e.g., the Illumina 9K iSelect, the 50K Infinium arrays, the Barley Genome Zipper, POPSEQ, and genotyping by sequencing (GBS), were developed that enable enhanced gene isolation in combination with the barley genome sequence. In the present study, we developed a fine map of the barley leaf rust resistance gene RphMBR1012. 537 segmental homozygous recombinant inbred lines (RILs) derived from 4775 F2-plants were used to construct a high-resolution mapping population (HRMP). The Barley Genome Zipper, the 9K iSelect chip, the 50K Infinium chip and GBS were used to develop 56 molecular markers located in the target interval of 8 cM. This interval was narrowed down to about 0.07 cM corresponding to 0.44 Mb of the barley reference genome. Eleven low-confidence and 18 high-confidence genes were identified in this interval. Five of these are putative disease resistance genes and were subjected to allele-specific sequencing. In addition, comparison of the genetic map and the reference genome revealed an inversion of 1.34 Mb located distally to the resistance locus. In conclusion, the barley reference sequence and the respective gene annotation delivered detailed information about the physical size of the target interval, the genes located in the target interval and facilitated the efficient development of molecular markers for marker-assisted selection for RphMBR1012
Detection and Identification of Genome Editing in Plants: Challenges and Opportunities
Conventional genetic engineering techniques generate modifications in the genome via stable integration of DNA elements which do not occur naturally in this combination. Therefore, the resulting organisms and (most) products thereof can unambiguously be identified with event-specific PCR-based methods targeting the insertion site. New breeding techniques such as genome editing diversify the toolbox to generate genetic variability in plants. Several of these techniques can introduce single nucleotide changes without integrating foreign DNA and thereby generate organisms with intended phenotypes. Consequently, such organisms and products thereof might be indistinguishable from naturally occurring or conventionally bred counterparts with established analytical tools. The modifications can entirely resemble random mutations regardless of being spontaneous or induced chemically or via irradiation. Therefore, if an identification of these organisms or products thereof is demanded, a new challenge will arise for (official) seed, food, and feed testing laboratories and enforcement institutions. For detailed consideration, we distinguish between the detection of sequence alterations – regardless of their origin – the identification of the process that generated a specific modification and the identification of a genotype, i.e., an organism produced by genome editing carrying a specific genetic alteration in a known background. This article briefly reviews the existing and upcoming detection and identification strategies (including the use of bioinformatics and statistical approaches) in particular for plants developed with genome editing techniques
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