Plants have developed effective mechanisms to recognize and respond to infections caused by pathogens. Plant resistance gene analogs (RGAs), as resistance (R) gene candidates, have conserved domains and motifs that play specific roles in pathogens’ resistance. Well-known RGAs are nucleotide binding site leucine rich repeats, receptor like kinases, and receptor like proteins. Others include pentatricopeptide repeats and apoplastic peroxidases. RGAs can be detected using bioinformatics tools based on their conserved structural features. Thousands of RGAs have been identified from sequenced plant genomes. High-density genome-wide RGA genetic maps are useful for designing diagnostic markers and identifying quantitative trait loci (QTL) or markers associated with plant disease resistance. This review focuses on recent advances in structures and mechanisms of RGAs, and their identification from sequenced genomes using bioinformatics tools. Applications in enhancing fine mapping and cloning of plant disease resistance genes are also discussed.

Sequencing, assembly, and annotation of the 26.5 Gbp hexaploid genome of coast redwood (Sequoia sempervirens) was completed leading toward discovery of genes related to climate adaptation and investigation of the origin of the hexaploid genome. Deep-coverage short-read Illumina sequencing data from haploid tissue from a single seed were combined with long-read Oxford Nanopore Technologies sequencing data from diploid needle tissue to create an initial assembly, which was then scaffolded using proximity ligation data to produce a highly contiguous final assembly, SESE 2.1, with a scaffold N50 size of 44.9 Mbp. The assembly included several scaffolds that span entire chromosome arms, confirmed by the presence of telomere and centromere sequences on the ends of the scaffolds. The structural annotation produced 118,906 genes with 113 containing introns that exceed 500 Kbp in length and one reaching 2 Mb. Nearly 19 Gbp of the genome represented repetitive content with the vast majority characterized as long terminal repeats, with a 2.9:1 ratio of Copia to Gypsy elements that may aid in gene expression control. Comparison of coast redwood to other conifers revealed species-specific expansions for a plethora of abiotic and biotic stress response genes, including those involved in fungal disease resistance, detoxification, and physical injury/structural remodeling and others supporting flavonoid biosynthesis. Analysis of multiple genes that exist in triplicate in coast redwood but only once in its diploid relative, giant sequoia, supports a previous hypothesis that the hexaploidy is the result of autopolyploidy rather than any hybridizations with separate but closely related conifer species.

Pseudogenes are paralogs generated from ancestral functional genes (parents) during genome evolution, which contain critical defects in their sequences, such as lacking a promoter, having a premature stop codon or frameshift mutations. Generally, pseudogenes are functionless, but recent evidence demonstrates that some of them have potential roles in regulation. The majority of pseudogenes are generated from functional progenitor genes either by gene duplication (duplicated pseudogenes) or retro-transposition (processed pseudogenes). Pseudogenes are primarily identified by comparison to their parent genes. Bioinformatics tools for pseudogene prediction have been developed, among which PseudoPipe, PSF and Shiu’s pipeline are publicly available. We compared these three tools using the well-annotated Arabidopsis thaliana genome and its known 924 pseudogenes as a test data set. PseudoPipe and Shiu’s pipeline identified ~80% of A. thaliana pseudogenes, of which 94% were shared, while PSF failed to generate adequate results. A need for improvement of the bioinformatics tools for pseudogene prediction accuracy in plant genomes was thus identified, with the ultimate goal of improving the quality of genome annotation in plants.

Dissecting the genomic basis of local adaptation is a major goal in evolutionary biology and conservation science. Rapid changes in the climate pose significant challenges to the survival of natural populations, and the genomic basis of long-generation plant species is still poorly understood. Here, we investigated genome-wide climate adaptation in giant sequoia and coast redwood, two iconic and ecologically important tree species. We used a combination of univariate and multivariate genotype–environment association methods and a selective sweep analysis using non-overlapping sliding windows. We identified genomic regions of potential adaptive importance, showing strong associations to moisture variables and mean annual temperature. Our results found a complex architecture of climate adaptation in the species, with genomic regions showing signatures of selective sweeps, polygenic adaptation, or a combination of both, suggesting recent or ongoing climate adaptation along moisture and temperature gradients in giant sequoia and coast redwood. The results of this study provide a first step toward identifying genomic regions of adaptive significance in the species and will provide information to guide management and conservation strategies that seek to maximize adaptive potential in the face of climate change.

Drought is a major limitation for survival and growth in plants. With more frequent and severe drought episodes occurring due to climate change, it is imperative to understand the genomic and physiological basis of drought tolerance to be able to predict how species will respond in the future. In this study, univariate and multitrait multivariate GWAS methods were used to identify candidate genes in two iconic and ecosystem-dominating species of the western US, coast redwood and giant sequoia, using ten drought-related physiological and anatomical traits and genome wide sequence-capture SNPs. Population level phenotypic variation was found in carbon isotope discrimination, osmotic pressure at full turgor, xylem hydraulic diameter and total area of transporting fibers in both species. Our study identified new 78 new marker x trait associations in coast redwood and six in giant sequoia, with genes involved in a range of metabolic, stress and signaling pathways, among other functions. This study contributes to a better understanding of the genomic basis of drought tolerance in long-generation conifers and helps guide current and future conservation efforts in the species.

Drought is a major limitation for survival and growth in plants. With more frequent and severe drought episodes occurring due to climate change, it is imperative to understand the genomic and physiological basis of drought tolerance to be able to predict how species will respond in the future. In this study, univariate and multitrait multivariate genome-wide association study methods were used to identify candidate genes in two iconic and ecosystem-dominating species of the western USA, coast redwood and giant sequoia, using 10 drought-related physiological and anatomical traits and genome-wide sequence-capture single nucleotide polymorphisms. Population-level phenotypic variation was found in carbon isotope discrimination, osmotic pressure at full turgor, xylem hydraulic diameter, and total area of transporting fibers in both species. Our study identified new 78 new marker 3 trait associations in coast redwood and six in giant sequoia, with genes involved in a range of metabolic, stress, and signaling pathways, among other functions. This study contributes to a better understanding of the genomic basis of drought tolerance in longgeneration conifers and helps guide current and future conservation efforts in the species.

Severe and frequent heat and drought events challenge the survival and development of long-generation trees. In this study, we investigated the genomic basis of heat tolerance, water use efficiency, and growth by performing genome-wide association studies in coastal Douglas-fir (Pseudotsuga menziesii) and intervarietal (menziesii x glauca) hybrid seedlings. GWAS results identified 32 candidate genes involved in primary and secondary metabolism, abiotic stress and signaling, among other functions. Water use efficiency (inferred from carbon isotope discrimination), photosynthetic capacity (inferred from %N), height, and heat tolerance (inferred from electrolyte leakage in a heat stress experiment) were significantly different among Douglas-fir families and varieties. High elevation seed sources had increased water use efficiency, which could be a result of higher photosynthetic capacity. Similarly, families with greater heat tolerance also had higher water use efficiency and slower growth, suggesting a conservative growth strategy. Intervarietal hybrids showed increased heat tolerance (lower electrolyte leakage at 50 oC and 55 oC) and higher water use efficiency compared to coastal families, suggesting hybridization might be a source of pre-adapted alleles to warming climates and should be considered for large-scale reforestation projects under increasingly arid conditions.

Stress tolerance in plants is a coordinated action of multiple stress response genes that also cross talk with other components of the stress signal transduction pathways. The expression and regulation of stress-induced genes are largely regulated by specific transcription factors, families of which have been reported in several plant species, such as Arabidopsis, rice and Populus. In sorghum, the majority of such factors remain unexplored. We used 2DE refined with MALDI-TOF techniques to analyze drought stress-induced proteins in sorghum. A total of 176 transcription factors from the MYB, AUX_ARF, bZIP, AP2 and WRKY families of drought-induced proteins were identified. We developed a method based on semantic similarity of gene ontology terms (GO terms) to identify the transcription factors. A threshold value (≥ 90%) was applied to retrieve total 1,493 transcription factors with high semantic similarity from selected plant species. It could be concluded that the identified transcription factors regulate their target proteins with endogenous signals and environmental cues, such as light, temperature and drought stress. The regulatory network and cis-acting elements of the identified transcription factors in distinct families are involved in responsiveness to auxin, abscisic acid, defense, stress and light. These responses may be highly important in the modulation of plant growth and development.