Transcriptome analysis of the fungal pathogen Fusarium oxysporum f. sp. medicaginis during colonisation of resistant and susceptible Medicago truncatula hosts identifies differential pathogenicity profiles and novel candidate effectors

Abstract

BackgroundPathogenic members of the Fusarium oxysporum species complex are responsible for vascular wilt disease on many important crops including legumes, where they can be one of the most destructive disease causing necrotrophic fungi. We previously developed a model legume-infecting pathosystem based on the reference legume Medicago truncatula and a pathogenic F. oxysporum forma specialis (f. sp.) medicaginis (Fom). To dissect the molecular pathogenicity arsenal used by this root-infecting pathogen, we sequenced its transcriptome during infection of a susceptible and resistant host accession.ResultsHigh coverage RNA-Seq of Fom infected root samples harvested from susceptible (DZA315) or resistant (A17) M. truncatula seedlings at early or later stages of infection (2 or 7 days post infection (dpi)) and from vegetative (in vitro) samples facilitated the identification of unique and overlapping sets of in planta differentially expressed genes. This included enrichment, particularly in DZA315 in planta up-regulated datasets, for proteins associated with sugar, protein and plant cell wall metabolism, membrane transport, nutrient uptake and oxidative processes. Genes encoding effector-like proteins were identified, including homologues of the F. oxysporum f. sp. lycopersici Secreted In Xylem (SIX) proteins, and several novel candidate effectors based on predicted secretion, small protein size and high in-planta induced expression. The majority of the effector candidates contain no known protein domains but do share high similarity to predicted proteins predominantly from other F. oxysporum ff. spp. as well as other Fusaria (F. solani, F. fujikori, F. verticilloides, F. graminearum and F. pseudograminearum), and from another wilt pathogen of the same class, a Verticillium species. Overall, this suggests these novel effector candidates may play important roles in Fusaria and wilt pathogen virulence.ConclusionCombining high coverage in planta RNA-Seq with knowledge of fungal pathogenicity protein features facilitated the identification of differentially expressed pathogenicity associated genes and novel effector candidates expressed during infection of a resistant or susceptible M. truncatula host. The knowledge from this first in depth in planta transcriptome sequencing of any F. oxysporum ff. spp. pathogenic on legumes will facilitate the dissection of Fusarium wilt pathogenicity mechanisms on many important legume crops.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3192-2) contains supplementary material, which is available to authorized users.

Transcriptome analysis of the plant pathogen Sclerotinia sclerotiorum interaction with resistant and susceptible canola (Brassica napus) lines

“…Gene Sscle_07g055350 was 4.4 -fold down-regulated (l2fc -2.13) at T1, followed by 9 -fold upregulation (l2fc 3.18) at T2. A similar expression pattern (up-regulation only at late infection) was observed by Seifbarghi et al [35] and Guyon et al [110] during infection of canola and soybean [34] by S. sclerotiorum and by Thatcher et al [119] during Fusarium oxysporum and Medicago truncatula interaction. SsSSVP1, another characterized S. sclerotiorum virulence factor, is a small cysteine rich secreted protein essential for full virulence.…”

Divergent and convergent modes of interaction between wheat and Puccinia graminis f. sp. tritici isolates revealed by the comparative gene co-expression network and genome analyses

“…The development of fungi was also associated with the increase in the transmembrane transport (Fig. 3) that was also demonstrated for Fusarium oxysporum during the colonization of Medicago truncatula host [49]. We have identified 7 clusters in the RKQQC dataset and 8 clusters in the MCCFC dataset enriched for the fungal genes encoding candidate effectors with the secretion signal peptides (Fig.…”

Comparison of gene co-networks analysis provide a systems view of rice (Oryza sativa L.) response to Tilletia horrida infection

“…horrida biomass in rice kernels was quantified based on the abundance 18S rRNA of T . horrida relative to that of rice [ 10 ]. Primers used for qRT-PCR are listed in S1 Table .…”