WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Conference Object Conference Object Enabling the Quantitation of Post Translational Modifications(Springer Verlag, 2009) Allmer, Jens[No abstract available]Article Citation - WoS: 11Citation - Scopus: 14Categorization of Species Based on Their Micrornas Employing Sequence Motifs, Information-Theoretic Sequence Feature Extraction, and K-Mers(Springer Verlag, 2017) Yousef, Malik; Nigatu, Dawit; Levy, Dalit; Allmer, Jens; Henkel, WernerBackground: Diseases like cancer can manifest themselves through changes in protein abundance, and microRNAs (miRNAs) play a key role in the modulation of protein quantity. MicroRNAs are used throughout all kingdoms and have been shown to be exploited by viruses to modulate their host environment. Since the experimental detection of miRNAs is difficult, computational methods have been developed. Many such tools employ machine learning for pre-miRNA detection, and many features for miRNA parameterization have been proposed. To train machine learning models, negative data is of importance yet hard to come by; therefore, we recently started to employ pre-miRNAs from one species as positive data versus another species’ pre-miRNAs as negative examples based on sequence motifs and k-mers. Here, we introduce the additional usage of information-theoretic (IT) features. Results: Pre-miRNAs from one species were used as positive and another species’ pre-miRNAs as negative training data for machine learning. The categorization capability of IT and k-mer features was investigated. Both feature sets and their combinations yielded a very high accuracy, which is as good as the previously suggested sequence motif and k-mer based method. However, for obtaining a high performance, a sufficiently large phylogenetic distance between the species and sufficiently high number of pre-miRNAs in the training set is required. To examine the contribution of the IT and k-mer features, an information gain-based feature ranking was performed. Although the top 3 are IT features, 80% of the top 100 features are k-mers. The comparison of all three individual approaches (motifs, IT, and k-mers) shows that the distinction of species based on their pre-miRNAs k-mers are sufficient. Conclusions: IT sequence feature extraction enables the distinction among species and is less computationally expensive than motif calculations. However, since IT features need larger amounts of data to have enough statistics for producing highly accurate results, future categorization into species can be effectively done using k-mers only. The biological reasoning for this is the existence of a codon bias between species which can, at least, be observed in exonic miRNAs. Future work in this direction will be the ab initio detection of pre-miRNA. In addition, prediction of pre-miRNA from RNA-seq can be done.Article Citation - WoS: 20Citation - Scopus: 24Newly Developed Ssr Markers Reveal Genetic Diversity and Geographical Clustering in Spinach (spinacia Oleracea)(Springer Verlag, 2017) Göl, Şurhan; Göktay, Mehmet; Allmer, Jens; Doğanlar, Sami; Frary, AnneSpinach is a popular leafy green vegetable due to its nutritional composition. It contains high concentrations of vitamins A, E, C, and K, and folic acid. Development of genetic markers for spinach is important for diversity and breeding studies. In this work, Next Generation Sequencing (NGS) technology was used to develop genomic simple sequence repeat (SSR) markers. After cleaning and contig assembly, the sequence encompassed 2.5% of the 980 Mb spinach genome. The contigs were mined for SSRs. A total of 3852 SSRs were detected. Of these, 100 primer pairs were tested and 85% were found to yield clear, reproducible amplicons. These 85 markers were then applied to 48 spinach accessions from worldwide origins, resulting in 389 alleles with 89% polymorphism. The average gene diversity (GD) value of the markers (based on a GD calculation that ranges from 0 to 0.5) was 0.25. Our results demonstrated that the newly developed SSR markers are suitable for assessing genetic diversity and population structure of spinach germplasm. The markers also revealed clustering of the accessions based on geographical origin with clear separation of Far Eastern accessions which had the overall highest genetic diversity when compared with accessions from Persia, Turkey, Europe, and the USA. Thus, the SSR markers have good potential to provide valuable information for spinach breeding and germplasm management. Also they will be helpful for genome mapping and core collection establishment.Article Citation - WoS: 6Citation - Scopus: 5Development of Genomic Simple Sequence Repeat Markers in Faba Bean by Next-Generation Sequencing(Springer Verlag, 2017) Abuzayed, Mazen A.; Göktay, Mehmet; Allmer, Jens; Doğanlar, Sami; Frary, AnneFaba bean (Vicia faba L.) is an important food legume crop with a huge genome. Development of genetic markers for faba bean is important to study diversity and for molecular breeding. In this study, we used Next Generation Sequencing (NGS) technology for the development of genomic simple sequence repeat (SSR) markers. A total of 14,027,500 sequence reads were obtained comprising 4,208 Mb. From these reads, 56,063 contigs were assembled (16,367 Mb) and 2138 SSRs were identified. Mono and dinucleotides were the most abundant, accounting for 57.5 % and 20.9 % of all SSR repeats, respectively. A total of 430 primer pairs were designed from contigs larger than 350 nucleotides and 50 primers pairs were tested for validation of SSR locus amplification. Nearly all (96 %) of the markers were found to produce clear amplicons and to be reproducible. Thirty-nine SSR markers were then applied to 46 faba bean accessions from worldwide origins, resulting in 161 alleles with 87.5 % polymorphism, and an average of 4.1 alleles per marker. Gene diversity (GD) of the markers ranged from 0 to 0.48 with an average of 0.27. Testing of the markers showed that they were useful in determining genetic relationships and population structure in faba bean accessions.Article Citation - WoS: 27Citation - Scopus: 31Development of Genomic Simple Sequence Repeat Markers in Opium Poppy by Next-Generation Sequencing(Springer Verlag, 2014) Çelik, İbrahim; Gültekin, Visam; Allmer, Jens; Doğanlar, Sami; Frary, AnneOpium poppy (Papaver somniferum L.) is an important pharmaceutical crop with very few genetic marker resources. To expand these resources, we sequenced genomic DNA using pyrosequencing technology and examined the DNA sequences for simple sequence repeats (SSRs). A total of 1,244,412 sequence reads were obtained covering 474 Mb. Approximately half of the reads (52 %) were assembled into 166,724 contigs representing 105 Mb of the opium poppy genome. A total of 23,283 non-redundant SSRs were identified in 18,944 contigs (11.3 % of total contigs). Trinucleotide and tetranucleotide repeats were the most abundant SSR repeats, accounting for 49.0 and 27.9 % of all SSRs, respectively. The AAG/TTC repeat was the most abundant trinucleotide repeat, representing 19.7 % of trinucleotide repeats. Other SSR repeat types were AT-rich. A total of 23,126 primer pairs (98.7 % of total SSRs) were designed to amplify SSRs. Fifty-three genomic SSR markers were tested in 37 opium poppy accessions and seven Papaver species for determination of polymorphism and transferability. Intraspecific polymorphism information content (PIC) values of the genomic SSR markers were intermediate, with an average 0.17, while the interspecific average PIC value was slightly higher, 0.19. All markers showed at least 88 % transferability among related species. This study increases sequence coverage of the opium poppy genome by sevenfold and the number of opium poppy-specific SSR markers by sixfold. This is the first report of the development of genomic SSR markers in opium poppy, and the genomic SSR markers developed in this study will be useful in diversity, identification, mapping and breeding studies in opium poppy.Article Citation - WoS: 4Citation - Scopus: 12Existing Bioinformatics Tools for the Quantitation of Post-Translational Modifications(Springer Verlag, 2012) Allmer, JensMass spectrometry (MS)-based proteomics, by itself, is a vast and complex area encompassing various mass spectrometers, different spectra, and search result representations. When the aim is quantitation performed in different scanning modes at different MS levels, matters become additionally complex. Quantitation of post-translational modifications (PTM) represents the greatest challenge among these endeavors. Many different approaches to quantitation have been described and some of these can be directly applied to the quantitation of PTMs. The amount of data produced via MS, however, makes manual data interpretation impractical. Therefore, specialized software tools meet this challenge. Any software currently able to quantitate differentially labeled samples may theoretically be adapted to quantitate differential PTM expression among samples as well. Due to the heterogeneity of mass spectrometry-based proteomics; this review will focus on quantitation of PTM using liquid chromatography followed by one or more stages of mass spectrometry. Currently available free software, which either allow analysis of PTM or are easily adaptable for this purpose, is briefly reviewed in this paper. Selected studies, especially those related to phosphoproteomics, shall be used to highlight the current ability to quantitate PTMs. © Springer-Verlag 2010Article Citation - WoS: 1Citation - Scopus: 2Label-Free Quantitation, an Extension To 2db(Springer Verlag, 2010) Allmer, JensDetermining the differential expression of proteins under different conditions is of major importance in proteomics. Since mass spectrometry-based proteomics is often used to quantify proteins, several labelling strategies have been developed. While these are generally more precise than label-free quantitation approaches, they imply specifically designed experiments which also require knowledge about peptides that are expected to be measured and need to be modified. We recently designed the 2DB database which aids storage, analysis, and publication of data from mass spectrometric experiments to identify proteins. This database can aid identifying peptides which can be used for quantitation. Here an extension to the database application, named MSMAG, is presented which allows for more detailed analysis of the distribution of peptides and their associated proteins over the fractions of an experiment. Furthermore, given several biological samples in the database, label-free quantitation can be performed. Thus, interesting proteins, which may warrant further investigation, can be identified en passant while performing high-throughput proteomics studies. © 2009 Springer-Verlag.