Genome resources of four distinct pathogenic races within Fusarium oxysporum f. sp. vasinfectum that cause vascular wilt disease of cotton

Whole Genome Sequence (WGS) based identifications are being increasingly used by regulatory and public health agencies to facilitate the detection, investigation, and control of pathogens and pests. Fusarium oxysporum f. sp. vasinfectum (FOV) is a significant vascular wilt pathogen of cultivated cotton, and consists of several pathogenic races that are not each other’s closest phylogenetic relatives. We have developed WGS assemblies for isolates of race 1 (FOV1), race 4 (FOV4), race 5 (FOV5), and race 8 (FOV8) using a combination of Nanopore (MinION) and Illumina sequencing technology (Mi-Seq). This resulted in assembled contigs with more than 100X coverage for each of the FOV races and estimated genome sizes of FOV1 52 Mb, FOV4 68 Mb, FOV5 68 Mb and FOV8 55 Mb. The AUGUSTUS gene prediction program predicted 16,263 genes in FOV1, 20,259 genes in FOV4, 20,375 genes in FOV5 and 16,615 genes in FOV8. We were able to identify 525 genes unique to FOV1, 570 unique to FOV4, 1242 unique to FOV5 and 383 unique to FOV8. We expect that these findings will help in comparative genomics, and in the identification of unique genes as candidate targets for diagnostic marker and methods development to permit rapid differentiation of FOV subgroups.

ASPic-GeneID: A Lightweight Pipeline for Gene Prediction and Alternative Isoforms Detection

New genomes are being sequenced at an increasingly rapid rate, far outpacing the rate at which manual gene annotation can be performed. Automated genome annotation is thus necessitated by this growth in genome projects; however, full-fledged annotation systems are usually home-grown and customized to a particular genome. There is thus a renewed need for accurateab initiogene prediction methods. However, it is apparent that fullyab initiomethods fall short of the required level of sensitivity and specificity for a quality annotation. Evidence in the form of expressed sequences gives the single biggest improvement in accuracy when used to inform gene predictions. Here, we present a lightweight pipeline for first-pass gene prediction on newly sequenced genomes. The two main components are ASPic, a program that derives highly accurate, albeit not necessarily complete, EST-based transcript annotations from EST alignments, and GeneID, a standard gene prediction program, which we have modified to take as evidence intron annotations. The introns output by ASPic CDS predictions is given to GeneID to constrain the exon-chaining process and produce predictions consistent with the underlying EST alignments. The pipeline was successfully tested on the entireC. elegansgenome and the 44 ENCODE human pilot regions.

Narrowing and genomic annotation of the commonly deleted region of the 5q− syndrome

The 5q− syndrome is the most distinct of the myelodysplastic syndromes, and the molecular basis for this disorder remains unknown. We describe the narrowing of the common deleted region (CDR) of the 5q− syndrome to the approximately 1.5-megabases interval at 5q32 flanked by D5S413 and theGLRA1 gene. The Ensembl gene prediction program has been used for the complete genomic annotation of the CDR. The CDR is gene rich and contains 24 known genes and 16 novel (predicted) genes. Of 40 genes in the CDR, 33 are expressed in CD34+ cells and, therefore, represent candidate genes since they are expressed within the hematopoietic stem/progenitor cell compartment. A number of the genes assigned to the CDR represent good candidates for the 5q− syndrome, including MEGF1, G3BP, and several of the novel gene predictions. These data now afford a comprehensive mutational/expression analysis of all candidate genes assigned to the CDR.