Integrated meta-analysis and transcriptomics pinpoint genomic loci and novel candidate genes associated with submergence tolerance in rice.

BACKGROUND: Due to rising costs, water shortages, and labour shortages, farmers across the globe now prefer a direct seeding approach. However, submergence stress remains a major bottleneck limiting the success of this approach in rice cultivation. The merger of accumulated rice genetic resources provides an opportunity to detect key genomic loci and candidate genes that influence the flooding tolerance of rice. RESULTS: In the present study, a whole-genome meta-analysis was conducted on 120 quantitative trait loci (QTL) obtained from 16 independent QTL studies reported from 2004 to 2023. These QTL were confined to 18 meta-QTL (MQTL), and ten MQTL were successfully validated by independent genome-wide association studies from diverse natural populations. The mean confidence interval (CI) of the identified MQTL was 3.44 times narrower than the mean CI of the initial QTL. Moreover, four core MQTL loci with genetic distance less than 2 cM were obtained. By combining differentially expressed genes (DEG) from two transcriptome datasets with 858 candidate genes identified in the core MQTL regions, we found 38 common differentially expressed candidate genes (DECGs). In silico expression analysis of these DECGs led to the identification of 21 genes with high expression in embryo and coleoptile under submerged conditions. These DECGs encode proteins with known functions involved in submergence tolerance including WRKY, F-box, zinc fingers, glycosyltransferase, protein kinase, cytochrome P450, PP2C, hypoxia-responsive family, and DUF domain. By haplotype analysis, the 21 DECGs demonstrated distinct genetic differentiation and substantial genetic distance mainly between indica and japonica subspecies. Further, the MQTL7.1 was successfully validated using flanked marker S2329 on a set of genotypes with phenotypic variation. CONCLUSION: This study provides a new perspective on understanding the genetic basis of submergence tolerance in rice. The identified MQTL and novel candidate genes lay the foundation for marker-assisted breeding/engineering of flooding-tolerant cultivars conducive to direct seeding.

A meta-quantitative trait loci analysis identified consensus genomic regions and candidate genes associated with grain yield in rice.

Improving grain yield potential in rice is an important step toward addressing global food security challenges. The meta-QTL analysis offers stable and robust QTLs irrespective of the genetic background of mapping populations and phenotype environment and effectively narrows confidence intervals (CI) for candidate gene (CG) mining and marker-assisted selection improvement. To achieve these aims, a comprehensive bibliographic search for grain yield traits (spikelet fertility, number of grains per panicle, panicles number per plant, and 1000-grain weight) QTLs was conducted, and 462 QTLs were retrieved from 47 independent QTL research published between 2002 and 2022. QTL projection was performed using a reference map with a cumulative length of 2,945.67 cM, and MQTL analysis was conducted on 313 QTLs. Consequently, a total of 62 MQTLs were identified with reduced mean CI (up to 3.40 fold) compared to the mean CI of original QTLs. However, 10 of these MQTLs harbored at least six of the initial QTLs from diverse genetic backgrounds and environments and were considered the most stable and robust MQTLs. Also, MQTLs were compared with GWAS studies and resulted in the identification of 16 common significant loci modulating the evaluated traits. Gene annotation, gene ontology (GO) enrichment, and RNA-seq analyses of chromosome regions of the stable MQTLs detected 52 potential CGs including those that have been cloned in previous studies. These genes encode proteins known to be involved in regulating grain yield including cytochrome P450, zinc fingers, MADs-box, AP2/ERF domain, F-box, ubiquitin ligase domain protein, homeobox domain, DEAD-box ATP domain, and U-box domain. This study provides the framework for molecular dissection of grain yield in rice. Moreover, the MQTLs and CGs identified could be useful for fine mapping, gene cloning, and marker-assisted selection to improve rice productivity.

Unravelling consensus genomic regions conferring leaf rust resistance in wheat via meta-QTL analysis.

Leaf rust, caused by the fungus Puccinia triticina Erikss (Pt), is a destructive disease affecting wheat (Triticum aestivum L.) and a threat to food security. Developing resistant cultivars represents a useful method of disease control, and thus, understanding the genetic basis for leaf rust resistance is required. To this end, a comprehensive bibliographic search for leaf rust resistance quantitative trait loci (QTL) was performed, and 393 QTL were collected from 50 QTL mapping studies. Afterward, a consensus map with a total length of 4,567 cM consisting of different types of markers (simple sequence repeat [SSR], diversity arrays technology [DArT], chip-based single-nucleotide polymorphism [SNP] markers, and SNP markers from genotyping-by-sequencing) was used for QTL projection, and meta-QTL (MQTL) analysis was performed on 320 QTL. A total of 75 MQTL were discovered and refined to 15 high-confidence MQTL (hcmQTL). The candidate genes discovered within the hcmQTL interval were then checked for differential expression using data from three transcriptome studies, resulting in 92 differentially expressed genes (DEGs). The expression of these genes in various leaf tissues during wheat development was explored. This study provides insight into leaf rust resistance in wheat and thereby provides an avenue for developing resistant cultivars by incorporating the most important hcmQTL.

Amino acid transporter (AAT) gene family in foxtail millet (Setaria italica L.): widespread family expansion, functional differentiation, roles in quality formation and response to abiotic stresses.

BACKGROUND: Amino acid transporters (AATs) plays an essential roles in growth and development of plants, including amino acids long-range transport, seed germination, quality formation, responsiveness to pathogenic bacteria and abiotic stress by modulating the transmembrane transfer of amino acids. In this study, we performed a genome-wide screening to analyze the AAT genes in foxtail millet (Setaria italica L.), especially those associated with quality formation and abiotic stresses response. RESULTS: A total number of 94 AAT genes were identified and divided into 12 subfamilies by their sequence characteristics and phylogenetic relationship. A large number (58/94, 62%) of AAT genes in foxtail millet were expanded via gene duplication, involving 13 tandem and 12 segmental duplication events. Tandemly duplicated genes had a significant impact on their functional differentiation via sequence variation, structural variation and expression variation. Further comparison in multiple species showed that in addition to paralogous genes, the expression variations of the orthologous AAT genes also contributed to their functional differentiation. The transcriptomic comparison of two millet cultivars verified the direct contribution of the AAT genes such as SiAAP1, SiAAP8, and SiAUX2 in the formation of grain quality. In addition, the qRT-PCR analysis suggested that several AAT genes continuously responded to diverse abiotic stresses, such as SiATLb1, SiANT1. Finally, combined with the previous studies and analysis on sequence characteristics and expression patterns of AAT genes, the possible functions of the foxtail millet AAT genes were predicted. CONCLUSION: This study for the first time reported the evolutionary features, functional differentiation, roles in the quality formation and response to abiotic stresses of foxtail millet AAT gene family, thus providing a framework for further functional analysis of SiAAT genes, and also contributing to the applications of AAT genes in improving the quality and resistance to abiotic stresses of foxtail millet, and other cereal crops.

Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat.

KEY MESSAGE: Based on the large-scale integration of meta-QTL and Genome-Wide  Association Study, 76 high-confidence MQTL regions and 237 candidate genes that affected wheat yield and yield-related traits were discovered. Improving yield and yield-related traits are key goals in wheat breeding program. The integration of accumulated wheat genetic resources provides an opportunity to uncover important genomic regions and candidate genes that affect wheat yield. Here, a comprehensive meta-QTL analysis was conducted on 2230 QTL of yield-related traits obtained from 119 QTL studies. These QTL were refined into 145 meta-QTL (MQTL), and 89 MQTL were verified by GWAS with different natural populations. The average confidence interval (CI) of these MQTL was 2.92 times less than that of the initial QTL. Furthermore, 76 core MQTL regions with a physical distance less than 25 Mb were detected. Based on the homology analysis and expression patterns, 237 candidate genes in the MQTL involved in photoperiod response, grain development, multiple plant growth regulator pathways, carbon and nitrogen metabolism and spike and flower organ development were determined. A novel candidate gene TaKAO-4A was confirmed to be significantly associated with grain size, and a CAPS marker was developed based on its dominant haplotype. In summary, this study clarified a method based on the integration of meta-QTL, GWAS and homology comparison to reveal the genomic regions and candidate genes that affect important yield-related traits in wheat. This work will help to lay a foundation for the identification, transfer and aggregation of these important QTL or candidate genes in wheat high-yield breeding.

Phenylpropanoid Pathway Engineering: An Emerging Approach towards Plant Defense.

Pathogens hitting the plant cell wall is the first impetus that triggers the phenylpropanoid pathway for plant defense. The phenylpropanoid pathway bifurcates into the production of an enormous array of compounds based on the few intermediates of the shikimate pathway in response to cell wall breaches by pathogens. The whole metabolomic pathway is a complex network regulated by multiple gene families and it exhibits refined regulatory mechanisms at the transcriptional, post-transcriptional, and post-translational levels. The pathway genes are involved in the production of anti-microbial compounds as well as signaling molecules. The engineering in the metabolic pathway has led to a new plant defense system of which various mechanisms have been proposed including salicylic acid and antimicrobial mediated compounds. In recent years, some key players like phenylalanine ammonia lyases (PALs) from the phenylpropanoid pathway are proposed to have broad spectrum disease resistance (BSR) without yield penalties. Now we have more evidence than ever, yet little understanding about the pathway-based genes that orchestrate rapid, coordinated induction of phenylpropanoid defenses in response to microbial attack. It is not astonishing that mutants of pathway regulator genes can show conflicting results. Therefore, precise engineering of the pathway is an interesting strategy to aim at profitably tailored plants. Here, this review portrays the current progress and challenges for phenylpropanoid pathway-based resistance from the current prospective to provide a deeper understanding.