Penghao Wang

A chromosome conformation capture ordered sequence of the barley genome

Cereal grasses of the Triticeae tribe have been the major food source in temperate regions since the dawn of agriculture. Their large genomes are characterized by a high content of repetitive elements and large pericentromeric regions that are virtually devoid of meiotic recombination. Here we present a high-quality reference genome assembly for barley (Hordeum vulgare L.). We use chromosome conformation capture mapping to derive the linear order of sequences across the pericentromeric space and to investigate the spatial organization of chromatin in the nucleus at megabase resolution. The composition of genes and repetitive elements differs between distal and proximal regions. Gene family analyses reveal lineage-specific duplications of genes involved in the transport of nutrients to developing seeds and the mobilization of carbohydrates in grains. We demonstrate the importance of the barley reference sequence for breeding by inspecting the genomic partitioning of sequence variation in modern elite germplasm, highlighting regions vulnerable to genetic erosion.

Transcriptome and Allele Specificity Associated with a 3BL Locus for Fusarium Crown Rot Resistance in Bread Wheat

Fusarium pathogens cause two major diseases in cereals, Fusarium crown rot (FCR) and head blight (FHB). A large-effect locus conferring resistance to FCR disease was previously located to chromosome arm 3BL (designated as Qcrs-3B) and several independent sets of near isogenic lines (NILs) have been developed for this locus. In this study, five sets of the NILs were used to examine transcriptional changes associated with the Qcrs-3B locus and to identify genes linked to the resistance locus as a step towards the isolation of the causative gene(s). Of the differentially expressed genes (DEGs) detected between the NILs, 12.7% was located on the single chromosome 3B. Of the expressed genes containing SNP (SNP-EGs) detected, 23.5% was mapped to this chromosome. Several of the DEGs and SNP-EGs are known to be involved in host-pathogen interactions, and a large number of the DEGs were among those detected for FHB in previous studies. Of the DEGs detected, 22 were mapped in the Qcrs-3B interval and they included eight which were detected in the resistant isolines only. The enrichment of DEG, and not necessarily those containing SNPs between the resistant and susceptible isolines, around the Qcrs-3B locus is suggestive of local regulation of this region by the resistance allele. Functions for 13 of these DEGs are known. Of the SNP-EGs, 28 were mapped in the Qcrs-3B interval and biological functions for 16 of them are known. These results provide insights into responses regulated by the 3BL locus and identify a tractable number of target genes for fine mapping and functional testing to identify the causative gene(s) at this QTL.

Assembly and transfer of tripartite integrative and conjugative genetic elements

Significance Integrative and conjugative elements (ICEs) are one of the most prevalent but least-characterized families of mobile genetic elements in bacteria. We identified a family of ICEs that exists as three separate parts integrated within the single chromosomes of symbiotic mesorhizobia. These “tripartite ICEs,” through a series of chromosomal recombinations mediated by integrase proteins, assemble into a single circular ICE. Following transfer to nonsymbiotic mesorhizobia, tripartite ICEs integrate and disassemble into three parts in the recipient genome and exconjugant mesorhizobia gain the ability to form a symbiosis with legumes. These discoveries expand our appreciation of the potential for gene transfer in bacteria and demonstrate how mobile genetic elements can dramatically manipulate the bacterial genome. Integrative and conjugative elements (ICEs) are ubiquitous mobile genetic elements present as “genomic islands” within bacterial chromosomes. Symbiosis islands are ICEs that convert nonsymbiotic mesorhizobia into symbionts of legumes. Here we report the discovery of symbiosis ICEs that exist as three separate chromosomal regions when integrated in their hosts, but through recombination assemble as a single circular ICE for conjugative transfer. Whole-genome comparisons revealed exconjugants derived from nonsymbiotic mesorhizobia received three separate chromosomal regions from the donor Mesorhizobium ciceri WSM1271. The three regions were each bordered by two nonhomologous integrase attachment (att) sites, which together comprised three homologous pairs of attL and attR sites. Sequential recombination between each attL and attR pair produced corresponding attP and attB sites and joined the three fragments to produce a single circular ICE, ICEMcSym1271. A plasmid carrying the three attP sites was used to recreate the process of tripartite ICE integration and to confirm the role of integrase genes intS, intM, and intG in this process. Nine additional tripartite ICEs were identified in diverse mesorhizobia and transfer was demonstrated for three of them. The transfer of tripartite ICEs to nonsymbiotic mesorhizobia explains the evolution of competitive but suboptimal N2-fixing strains found in Western Australian soils. The unheralded existence of tripartite ICEs raises the possibility that multipartite elements reside in other organisms, but have been overlooked because of their unusual biology. These discoveries reveal mechanisms by which integrases dramatically manipulate bacterial genomes to allow cotransfer of disparate chromosomal regions.

Protein signatures correspond to survival outcomes of AJCC stage III melanoma patients

Outcomes for melanoma patients with stage III disease differ widely even within the same subcategory. Molecular signatures that more accurately predict prognosis are needed to stratify patients according to risk. Proteomic analyses were used to identify differentially abundant proteins in extracts of surgically excised samples from patients with stage IIIc melanoma lymph node metastases. Analysis of samples from patients with poor (n = 14, <1 yr) and good (n = 19, >4 yr) survival outcomes identified 84 proteins that were differentially abundant between prognostic groups. Subsequent selected reaction monitoring analysis verified 21 proteins as potential biomarkers for survival. Poor prognosis patients are characterized by increased levels of proteins involved in protein metabolism, nucleic acid metabolism, angiogenesis, deregulation of cellular energetics and methylation processes, and decreased levels of proteins involved in apoptosis and immune response. These proteins are able to classify stage IIIc patients into prognostic subgroups (P < 0.02). This is the first report of potential prognostic markers from stage III melanoma using proteomic analyses. Validation of these protein markers in larger patient cohorts should define protein signatures that enable better stratification of stage III melanoma patients.

Improving X!Tandem on Peptide Identification from Mass Spectrometry by Self-Boosted Percolator

A critical component in mass spectrometry (MS)-based proteomics is an accurate protein identification procedure. Database search algorithms commonly generate a list of peptide-spectrum matches (PSMs). The validity of these PSMs is critical for downstream analysis since proteins that are present in the sample are inferred from those PSMs. A variety of postprocessing algorithms have been proposed to validate and filter PSMs. Among them, the most popular ones include a semi-supervised learning (SSL) approach known as Percolator and an empirical modeling approach known as PeptideProphet. However, they are predominantly designed for commercial database search algorithms, i.e., SEQUEST and MASCOT. Therefore, it is highly desirable to extend and optimize those PSM postprocessing algorithms for open source database search algorithms such as X!Tandem. In this paper, we propose a Self-boosted Percolator for postprocessing X!Tandem search results. We find that the SSL algorithm utilized by Percolator depends heavily on the initial ranking of PSMs. Starting with a poor PSM ranking list may cause Percolator to perform suboptimally. By implementing Percolator in a cascade learning manner, we can progressively improve the performance through multiple boost runs, enabling many more PSM identifications without sacrificing false discovery rate (FDR).

Deep Sequencing of the Fruit Transcriptome and Lipid Accumulation in a Non-Seed Tissue of Chinese Tallow, a Potential Biofuel Crop.

Chinese tallow (Triadica sebifera) is a valuable oilseed-producing tree that can grow in a variety of conditions without competing for food production, and is a promising biofuel feedstock candidate. The fruits are unique in that they contain both saturated and unsaturated fat present in the tallow and seed layer, respectively. The tallow layer is poorly studied and is considered only as an external fatty deposition secreted from the seed. In this study we show that tallow is in fact a non-seed cellular tissue capable of triglyceride synthesis. Knowledge of lipid synthesis and storage mechanisms in tissues other than seed is limited but essential to generate oil-rich biomass crops. Here, we describe the annotated transcriptome assembly generated from the fruit coat, tallow and seed tissues of Chinese tallow. The final assembly was functionally annotated, allowing for the identification of candidate genes and reconstruction of lipid pathways. A tallow tissue-specific paralog for the transcription factor gene WRINKLED1 (WRI1) and lipid droplet-associated protein genes, distinct from those expressed in seed tissue, were found to be active in tallow, underpinning the mode of oil synthesis and packaging in this tissue. Our data have established an excellent knowledge base that can provide genetic and biochemical insights for engineering non-seed tissues to accumulate large amounts of oil. In addition to the large data set of annotated transcripts, the study also provides gene-based simple sequence repeat and single nucleotide polymorphism markers.

A dynamic wavelet-based algorithm for pre-processing tandem mass spectrometry data

MOTIVATION Mass spectrometry (MS)-based proteomics is one of the most commonly used research techniques for identifying and characterizing proteins in biological and medical research. The identification of a protein is the critical first step in elucidating its biological function. Successful protein identification depends on various interrelated factors, including effective analysis of MS data generated in a proteomic experiment. This analysis comprises several stages, often combined in a pipeline or workflow. The first component of the analysis is known as spectra pre-processing. In this component, the raw data generated by the mass spectrometer is processed to eliminate noise and identify the mass-to-charge ratio (m/z) and intensity for the peaks in the spectrum corresponding to the presence of certain peptides or peptide fragments. Since all downstream analyses depend on the pre-processed data, effective pre-processing is critical to protein identification and characterization. There is a critical need for more robust pre-processing algorithms that perform well on tandem mass spectra under a variety of different conditions and can be easily integrated into sophisticated data analysis pipelines for practical wet-lab applications. RESULT We have developed a new pre-processing algorithm. Based on wavelet theory, our method uses a dynamic peak model to identify peaks. It is designed to be easily integrated into a complete proteomic analysis workflow. We compared the method with other available algorithms using a reference library of raw MS and tandem MS spectra with known protein composition information. Our pre-processing algorithm results in the identification of significantly more peptides and proteins in the downstream analysis for a given false discovery rate. AVAILABILITY Software available at: http://www.maths.usyd.edu.au/u/penghao/index.html.

Demethylase Inhibitor Fungicide Resistance in Pyrenophora teres f. sp. teres Associated with Target Site Modification and Inducible Overexpression of Cyp51

Pyrenophora teres f. sp. teres is the cause of net form of net blotch (NFNB), an economically important foliar disease in barley (Hordeum vulgare). Net and spot forms of net blotch are widely controlled using site-specific systemic fungicides. Although resistance to succinate dehydrogenase inhibitors and quinone outside inhibitors has been addressed before in net blotches, mechanisms controlling demethylation inhibitor resistance have not yet been reported at the molecular level. Here we report the isolation of strains of NFNB in Australia since 2013 resistant to a range of demethylase inhibitor fungicides. Cyp51A:KO103-A1, an allele with the mutation F489L, corresponding to the archetype F495I in Aspergillus fumigatus, was only present in resistant strains and was correlated with resistance factors to various demethylase inhibitors ranging from 1.1 for epoxiconazole to 31.7 for prochloraz. Structural in silico modeling of the sensitive and resistant CYP51A proteins docked with different demethylase inhibitor fungicides showed how the interaction of F489L within the heme cavity produced a localized constriction of the region adjacent to the docking site that is predicted to result in lower binding affinities. Resistant strains also displayed enhanced induced expression of the two Cyp51A paralogs and of Cyp51B genes. While Cyp51B was found to be constitutively expressed in the absence of fungicide, Cyp51A was only detected at extremely low levels. Under fungicide induction, expression of Cyp51B, Cyp51A2, and Cyp51A1 was shown to be 1.6-, 3,- and 5.3-fold higher, respectively in the resistant isolate compared to the wild type. These increased levels of expression were not supported by changes in the promoters of any of the three genes. The implications of these findings on demethylase inhibitor activity will require current net blotch management strategies to be reconsidered in order to avoid the development of further resistance and preserve the lifespan of fungicides in use.

Mass spectrometry-based protein identification by integrating de novo sequencing with database searching.

BackgroundMass spectrometry-based protein identification is a very challenging task. The main identification approaches include de novo sequencing and database searching. Both approaches have shortcomings, so an integrative approach has been developed. The integrative approach firstly infers partial peptide sequences, known as tags, directly from tandem spectra through de novo sequencing, and then puts these sequences into a database search to see if a close peptide match can be found. However the current implementation of this integrative approach has several limitations. Firstly, simplistic de novo sequencing is applied and only very short sequence tags are used. Secondly, most integrative methods apply an algorithm similar to BLAST to search for exact sequence matches and do not accommodate sequence errors well. Thirdly, by applying these methods the integrated de novo sequencing makes a limited contribution to the scoring model which is still largely based on database searching.ResultsWe have developed a new integrative protein identification method which can integrate de novo sequencing more efficiently into database searching. Evaluated on large real datasets, our method outperforms popular identification methods.

Differential gene expression profiling after conditional Müller-cell ablation in a novel transgenic model.

PURPOSE Müller cells, the principal glial cells in the mammalian retina, play an important role in the maintenance of retinal homeostasis. Recent reports suggest that Müller-cell dysfunction may contribute to the pathogenesis of retinal diseases such as idiopathic macular telangiectasia type 2. In the present study, we used microarray to compare retinae isolated from transgenic mice in which the Müller cells of adult mice retinae can be selectively ablated with control mice. METHODS Retinae were isolated 1 week, 1 month, and 3 months after tamoxifen-induced selective Müller-cell ablation and microarray were performed with Affymatrix microarrays. Differentially expressed (DE) genes, temporal trends of DE genes, and pathway analysis were conducted. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to validate the results. RESULTS Strong upregulation of mRNA of proteins involved in gliosis, apoptosis, and neurotrophism was found 1 week after ablation and their related pathways such as the apoptotic and Jak/Stat pathways were identified. Three months after induced Müller-cell ablation, Müller-cell metabolic pathways and vasculopathy-related pathways such as genes involved in glycolysis and tight junctions were downregulated. qRT-PCR analysis showed consistent expression trends of selected genes. CONCLUSIONS The results were generally consistent with the previous morphologic findings in this model, in which photoreceptor degeneration soon after Müller-cell ablation, accompanied by blood-retinal barrier breakdown and subsequent retinal neovascularization were reported. These results are consistent with a significant contribution of Müller-cell dysfunction on retinal neuronal injury and vascular pathology at the mRNA level.