Novel global effector mining from the transcriptome of early life stages of the soybean cyst nematode Heterodera glycines

Abstract

Soybean cyst nematode (SCN) Heterodera glycines is an obligate parasite that relies on the secretion of effector proteins to manipulate host cellular processes that favor the formation of a feeding site within host roots to ensure its survival. The sequence complexity and co-evolutionary forces acting upon these effectors remain unknown. Here we generated a de novo transcriptome assembly representing the early life stages of SCN in both a compatible and an incompatible host interaction to facilitate global effector mining efforts in the absence of an available annotated SCN genome. We then employed a dual effector prediction strategy coupling a newly developed nematode effector prediction tool, N-Preffector, with a traditional secreted protein prediction pipeline to uncover a suite of novel effector candidates. Our analysis distinguished between effectors that co-evolve with the host genotype and those conserved by the pathogen to maintain a core function in parasitism and demonstrated that alternative splicing is one mechanism used to diversify the effector pool. In addition, we confirmed the presence of viral and microbial inhabitants with molecular sequence information. This transcriptome represents the most comprehensive whole-nematode sequence currently available for SCN and can be used as a tool for annotation of expected genome assemblies.

The genome of the soybean cyst nematode (Heterodera glycines) reveals complex patterns of duplications involved in the evolution of parasitism genes

“…To gain further insights into the prevalence of alternative splicing within known effector proteins, the 80 previously identified secreted effector proteins were associated with 371 transcripts. This differs from previous work where 395 transcripts were associated with the 80 effectors in a de-novo transcriptome approach [17]. The main types of alternatively spliced variants for the effector genes included 73 (19.7%) intron retention, 26 (7.0%) alternative 5' donor site, 25 (6.7%) alternative 3' acceptor site, 43 (11.6%) alternative transcription start site, 47 (12.7%) alternative transcription termination site, 4 (1.1%) single exon skipping, and 30 (8.1%) multiple exon skipping.…”

“…The most abundant alternative splicing events were intron retention (30%) and non-mediated decay (15%), with 70% of alternative splicing events changing open reading frame length ( Figure S3 & S4). In comparison, previous work utilizing a de novo transcriptome assembly approach discovered 71,093 genes with 147,910 (2.08 average) transcripts in H. glycines [17] thus demonstrating the importance of using an assembled genome as a part of the transcriptomics pipeline [18].…”

“…Briefly, SCN inbred population PA3 was grown on soybean cultivar Williams 82 or EXF63. Pre-parasitic second-stage juveniles and parasitic second stage juveniles were isolated from roots of resistant and susceptible cultivars at 5 days post-inoculation [17]. 100bp PE reads were aligned to the genome using HiSat2 [60].…”

“…The analysis of the global changes and effector specific effects in alternative splicing landscape was assessed following a recent de novo transcriptomics analysis of the H. glycines nematode effectors [17] Transcriptome annotation was constructed using 230 million RNA-Seq reads from both pre-parasitic and parasitic J2 H. glycines [17], 34,041 iso-seq reads from three life stages of both a virulent and an avirulent strain, and H. glycines ESTs in NCBI (35,796).…”

Endochondral ossification in hindlimbs during bufo gargarizans metamorphosis: A model of studying skeletal development in vertebrates

“…A limitation of our study was that just a single biological sample was used in the RNA‐seq. Also, it has been reported that the RNA‐seq was carried out only from a single biological sample in several researches (Geng et al, ; Liu et al, ; Gardner et al, ; Singh et al, ). In the present study, on the basis of RNA‐seq data, secondary and tertiary methods of analyses were used to validate the observed differences.…”