| Abstract Detail
Comparative Genomics/Transcriptomics Bhattarai, Akriti [1], Wegrzyn, Jill [2]. Identifying and Classifying Potential Disease Resistance Genes in White Pines. The white pines comprise the subsection Strobus of the genus Pinus, with species native to North and Central America, Europe, and Asia. They are susceptible to a devastating disease known as white pine blister rust (WPBR) caused by the fungus Cronartium ribicola. Native to Asia, this pathogen was introduced to North America in the early 1900s through the nursery trade, first impacting eastern white pine and later spreading west throughout the native range of North American white pines. Major resistance loci (Cr1 to Cr4) have been identified in four North American species (Pinus lambertiana, P. strobiformis, P. flexilis, P. monticola). Candidate genes for these loci have been categorized as NLRs, which consist of an N-terminal domain, nucleotide-binding domain (NB-ARC), and leucine-rich repeat domain (LRR). NLRs are also candidates for quantitative resistance through loci contributing partial resistance, and these associated genes can be identified through their characteristic domains. Existing transcriptomic resources (Illumina RNA-Seq reads sourced from NCBI) for 22 species were reassembled de-novo using Trinity, SOAPdenovo-Trans, and rnaSPADES before frame selection with Evigene. All transcriptomes were required to have a BUSCO completeness of at least 80% to ensure more complete resources for protein domain analysis. InterProScan and RGAugury were used for protein domain analysis while NLR-Annotator was used to scan the coding sequences for NLR-associated motifs. Combining the results of these methods, a total of 6427 potential NLRs were identified in the white pines, ranging from 177 to 581 per species. InterProScan and RGAugury identified roughly double the total number of NLRs than NLR-Annotator, however, the total number of complete NLRs was similar across the three methods. The identified domains and motifs were used to annotate potential NLRs and classify them into subfamilies based on their N-terminal domain. The TNLs comprised the largest subfamily, followed by RNLs and then CNLs. Compared to the European and American species of white pines, the Asian species has the highest average number of RNLs. Complete NB-ARC domain sequences were extracted from the NLRs and OrthoFinder was used to identify orthologous groups. The orthogroups separated by NLR subfamilies, and the three largest orthogroups contained the TNLs, RNLs, and CNLs, respectively. The identified NLRs were also compared to candidate genes for the major resistance loci Cr1 and Cr2. The final set of identified NLR genes will provide a catalog for the exploration of genes related to quantitative resistance and allow for a more comprehensive evaluation of potential disease resistance genes.
1 - University Of Connecticut, Ecology And Evolutionary Biology , 2152 Hillside Road, Unit 3046, Gant 401W, Storrs, CT, 06269, United States
2 - University Of Connecticut, EEB, 67 N. Eagleville Road, Unit 3124, Storrs, CT, 06269, United States
Keywords:
Transcriptomics
disease resistance.
Presentation Type: Poster
Number: PGT004
Abstract ID:707
Candidate for Awards:None |
