Abstract: Next-Generation Sequencing (NGS) methods have revolutionized various aspects of genomics including transcriptome analysis. Digital expression analysis is all set to replace analog expression analysis that uses microarray chips through their cost-effectiveness, reproducibility, accuracy, and speed. The last 2 years have seen a surge in the development of statistical methods and software tools for analysis and visualization of NGS data. Large amounts of NGS data are available for pathogenic fungi and oomycetes. As the analysis results start pouring in, it brings about a paradigm shift in the understanding of host pathogen interactions with discovery of new transcripts, splice variants, mutations, regulatory elements, and epigenetic controls. Here we describe the core technology of the new sequencing platforms, the methodology of data analysis, and different aspects of applications.
Abstract: The genome of the soybean pathogen Phytophthora sojae contains nearly 400 genes encoding candidate effector proteins carrying the host cell entry motif RXLR-dEER. Here, we report a broad survey of the transcription, variation, and functions of a large sample of the P. sojae candidate effectors. Forty-five (12%) effector genes showed high levels of polymorphism among P. sojae isolates and significant evidence for positive selection. Of 169 effectors tested, most could suppress programmed cell death triggered by BAX, effectors, and/or the PAMP INF1, while several triggered cell death themselves. Among the most strongly expressed effectors, one immediate-early class was highly expressed even prior to infection and was further induced 2- to 10-fold following infection. A second early class, including several that triggered cell death, was weakly expressed prior to infection but induced 20- to 120-fold during the first 12 h of infection. The most strongly expressed immediate-early effectors could suppress the cell death triggered by several early effectors, and most early effectors could suppress INF1-triggered cell death, suggesting the two classes of effectors may target different functional branches of the defense response. In support of this hypothesis, misexpression of key immediate-early and early effectors severely reduced the virulence of P. sojae transformants.
Abstract: Few quantitative trait loci (QTL) have been mapped for the expression of partial resistance to Phytophthora sojae in soybean and very little is known about the molecular mechanisms that contribute to this trait. Therefore, the objectives of this study were to identify additional QTL conferring resistance to P. sojae and to identify candidate genes that may contribute to this form of defense. QTL on chromosomes 12, 13, 14, 17, and 19, each explaining 4 to 7% of the phenotypic variation, were identified using 186 RILs from a cross of the partially resistant cultivar ‘Conrad’ and susceptible cultivar ‘Sloan’ through composite interval mapping. Microarray analysis identified genes with significant differences in transcript abundances between Conrad and Sloan, both constitutively and following inoculation. Of these genes, 55 mapped to the five QTL regions. Ten genes encoded proteins with unknown functions, while the others encode proteins related to defense or physiological traits. Seventeen genes within the genomic region that encompass the QTL were selected and their transcript abundance was confirmed by quantitative reverse transcription polymerase chain reaction (qRT-PCR). These results suggest a complex QTL-mediated resistance network. This study will contribute to soybean resistance breeding by providing additional QTL for marker-assisted selection as well as a list of candidate genes which may be manipulated to confer resistance.
Abstract: Soybean mosaic virus (SMV) is a prevalent virus infecting soybean (Glycine max L. Merr) worldwide. The incorporation of Rsv4, conferring resistance to all currently known strains in the United States, can assist in creating durable virus resistance in soybean. Additionally, lines heterozygous at the Rsv4 locus often express a late susceptible phenotype, showing symptoms only in mid to late vegetative growth. In this study the whole-genome shotgun sequence (WGS) of soybean was utilized for fine mapping and examining potential Rsv4 gene candidates in two populations. Six markers, designed from the WGS, were used to localize Rsv4 in the same, 1.3-cM region in both mapping populations, a physical interval of less than 100 kb on chromosome 2. This region contained no sequences previously related to virus resistance, namely nucleotide binding site-leucine rich repeat gene sequences or eukaryotic translation initiation factors. Instead, sequence analysis revealed several predicted transcription factors and unknown protein products. We conclude that Rsv4 likely belongs to a new class of resistance genes that interfere with viral infection and cell-to-cell movement, and delay vascular movement.
Abstract: Many oomycete and fungal plant pathogens are obligate biotrophs, which extract nutrients only from living plant tissue and cannot grow apart from their hosts. Although these pathogens cause substantial crop losses, little is known about the molecular basis or evolution of obligate biotrophy. Here, we report the genome sequence of the oomycete Hyaloperonospora arabidopsidis (Hpa), an obligate biotroph and natural pathogen of Arabidopsis thaliana. In comparison with genomes of related, hemibiotrophic Phytophthora species, the Hpa genome exhibits dramatic reductions in genes encoding (i) RXLR effectors and other secreted pathogenicity proteins, (ii) enzymes for assimilation of inorganic nitrogen and sulfur, and (iii) proteins associated with zoospore formation and motility. These attributes comprise a genomic signature of evolution toward obligate biotrophy.
Abstract: Pythium ultimum is a ubiquitous oomycete plant pathogen responsible for a variety of diseases on a broad range of crop and ornamental species.
Abstract: High throughput methods, such as high density oligonucleotide microarray measurements of mRNA levels, are popular and critical to genome scale analysis and systems biology. However understanding the results of these analyses and in particular understanding the very wide range of levels of transcriptional changes observed is still a significant challenge. Many researchers still use an arbitrary cut off such as two-fold in order to identify changes that may be biologically significant. We have used a very large-scale microarray experiment involving 72 biological replicates to analyze the response of soybean plants to infection by the pathogen Phytophthora sojae and to analyze transcriptional modulation as a result of genotypic variation.
Abstract: Pathogens secrete effector molecules that facilitate the infection of their hosts. A number of effectors identified in plant pathogenic Phytophthora species possess N-terminal motifs (RXLR-dEER) required for targeting these effectors into host cells. Here, we bioinformatically identify >370 candidate effector genes in each of the genomes of P. sojae and P. ramorum. A single superfamily, termed avirulence homolog (Avh) genes, accounts for most of the effectors. The Avh proteins show extensive sequence divergence but are all related and likely evolved from a common ancestor by rapid duplication and divergence. More than half of the Avh proteins contain conserved C-terminal motifs (termed W, Y, and L) that are usually arranged as a module that can be repeated up to eight times. The Avh genes belong to the most rapidly evolving part of the genome, and they are nearly always located at synteny breakpoints. The superfamily includes all experimentally identified oomycete effector and avirulence genes, and its rapid pace of evolution is consistent with a role for Avh proteins in interaction with plant hosts.
Abstract: Oomycete plant pathogens such as Phytophthora species and downy mildews cause destructive diseases in an enormous variety of crop plant species as well as forests and native ecosystems. These pathogens are most closely related to algae in the kingdom Stramenopiles, and hence have evolved plant pathogenicity independently of other plant pathogens such as fungi. We have used bioinformatic analysis of genome sequences and EST collections, together with functional genomics to identify plant and pathogen genes that may be key players in the interaction between the soybean pathogen Phytophthora sojae and its host. In P. sojae, we have identified many rapidly diversifying gene families that encode potential pathogenicity factors including protein toxins, and a class of proteins (avirulence or effector proteins) that appear to have the ability to penetrate plant cells. Transcriptomic analysis of quantitative or multigenic resistance against P. sojae in soybean has revealed that there are widespread adjustments in host gene expression in response to infection, and that some responses are unique to particular resistant cultivars. These observations lay the foundation for dissecting the interplay between pathogen and host genes during infection at a whole-genome level.
Abstract: Six unique expressed sequence tag (EST) libraries were generated from four developmental stages of Phytophthora sojae P6497. RNA was extracted from mycelia, swimming zoospores, germinating cysts, and soybean (Glycine max (L.) Merr.) cv. Harosoy tissues heavily infected with P. sojae. Three libraries were created from mycelia growing on defined medium, complex medium, and nutrient-limited medium. The 26,943 high-quality sequences obtained clustered into 7,863 unigenes composed of 2,845 contigs and 5,018 singletons. The total number of P. sojae unigenes matching sequences in the genome assembly was 7,412 (94%). Of these unigenes, 7,088 (90%) matched gene models predicted from the P. sojae sequence assembly, but only 2,047 (26%) matched P. ramorum gene models. Analysis of EST frequency from different growth conditions and morphological stages revealed genes that were specific to or highly represented in particular growth conditions and life stages. Additionally, our results indicate that, during infection, the pathogen derives most of its carbon and energy via glycolysis of sugars in the plant. Sequences identified with putative roles in pathogenesis included avirulence homologs possessing the RxLR motif, elicitins, and hydrolytic enzymes. This large collection of P. sojae ESTs will serve as a valuable public genomic resource.
Abstract: In all, 238 and 155 transfer (t)RNA genes were predicted from the genomes of Phytophthora sojae and P. ramorum, respectively. After omitting pseudogenes and undetermined types of tRNA genes, there remained 208 P. sojae tRNA genes and 140 P. ramorum tRNA genes. There were 45 types of tRNA genes, with distinct anticodons, in each species. Fourteen common anticodon types of tRNAs are missing altogether from the genome in the two species; however, these appear to be compensated by wobbling of other tRNA anticodons in a manner which is tied to the codon bias in Phytophthora genes. The most abundant tRNA class was arginine in both P. sojae and P. ramorum. A codon usage table was generated for these two organisms from a total of 9,803,525 codons in P. sojae and 7,496,598 codons in P. ramorum. The most abundant codon type detected from the codon usage tables was GAG (encoding glutamic acid), whereas the most numerous tRNA gene had a methionine anticodon (CAT). The correlation between the frequencies of tRNA genes and the codon frequencies in protein-coding genes was very low (0.12 in P. sojae and 0.19 in P. ramorum); however, the correlation between amino acid tRNA gene frequency and the corresponding amino acid codon frequency in P. sojae and P. ramorum was substantially higher (0.53 in P. sojae and 0.77 in P. ramorum). The codon usage frequencies of P. sojae and P ramorum were very strongly correlated (0.99), as were tRNA gene frequencies (0.77). Approximately 60% of orthologous tRNA gene pairs in P sojae and P. ramorum are located in regions that have conserved synteny in the two species.
Abstract: The VBI Microbial Database (VMD) is a database system designed to host a range of microbial genome sequences. At present, the database contains genome sequence and annotation data of two plant pathogens Phytophthora sojae and Phytophthora ramorum. With the completion of the draft genome sequences of these pathogens in collaboration with the DOE Joint Genome Institute (JGI), we have created this resource to make the sequences publicly available. The genome sequences (95 MB for P.sojae and 65 MB for P.ramorum) were annotated with approximately 19,000 and approximately 16,000 gene models, respectively. We used two different statistical methods to validate these gene models, Fickett's and a log-likelihood method. Functional annotation of the gene models is based on results from BlastX and InterProScan screens. From the InterProScan results, we could assign putative functions to 17,694 genes in P.sojae and 14,700 genes in P.ramorum. We created an easy-to-use genome browser to view the genome sequence data, which opens to detailed annotation pages for each gene model. A community annotation interface is available for registered community members to add or edit annotations. There are approximately 1600 gene models for P.sojae and approximately 700 models for P.ramorum that have already been manually curated. A toolkit is provided as an additional resource for users to perform a variety of sequence analysis jobs. The database is publicly available at http://phytophthora.vbi.vt.edu/.
Abstract: Draft genome sequences have been determined for the soybean pathogen Phytophthora sojae and the sudden oak death pathogen Phytophthora ramorum. Oömycetes such as these Phytophthora species share the kingdom Stramenopila with photosynthetic algae such as diatoms, and the presence of many Phytophthora genes of probable phototroph origin supports a photosynthetic ancestry for the stramenopiles. Comparison of the two species' genomes reveals a rapid expansion and diversification of many protein families associated with plant infection such as hydrolases, ABC transporters, protein toxins, proteinase inhibitors, and, in particular, a superfamily of 700 proteins with similarity to known oömycete avirulence genes.
Abstract: Phytophthora spp. are serious pathogens that threaten numerous cultivated crops, trees, and natural vegetation worldwide. The soybean pathogen P. sojae has been developed as a model oomycete. Here, we report a bacterial artificial chromosome (BAC)-based, integrated physical map of the P. sojae genome. We constructed two BAC libraries, digested 8,681 BACs with seven restriction enzymes, end labeled the digested fragments with four dyes, and analyzed them with capillary electrophoresis. Fifteen data sets were constructed from the fingerprints, using individual dyes and all possible combinations, and were evaluated for contig assembly. In all, 257 contigs were assembled from the XhoI data set, collectively spanning approximately 132 Mb in physical length. The BAC contigs were integrated with the draft genome sequence of P. sojae by end sequencing a total of 1,440 BACs that formed a minimal tiling path. This enabled the 257 contigs of the BAC map to be merged with 207 sequence scaffolds to form an integrated map consisting of 79 superscaffolds. The map represents the first genome-wide physical map of a Phytophthora sp. and provides a valuable resource for genomics and molecular biology research in P. sojae and other Phytophthora spp. In one illustration of this value, we have placed the 350 members of a superfamily of putative pathogenicity effector genes onto the map, revealing extensive clustering of these genes.
