Genomic insights into the genetic signatures of selection and seed trait loci in cultivated peanut

Combining Hyperspectral Techniques and Genome-Wide Association Studies to Predict Peanut Seed Vigor and Explore Associated Genetic Loci

Seed vigor significantly affects peanut breeding and agricultural yield by influencing seed germination and seedling growth and development. Traditional vigor testing methods are inadequate for modern high-throughput assays. Although hyperspectral technology shows potential for monitoring various crop traits, its application in predicting peanut seed vigor is still limited. This study developed and validated a method that combines hyperspectral technology with genome-wide association studies (GWAS) to achieve high-throughput detection of seed vigor and identify related functional genes. Hyperspectral phenotyping data and physiological indices from different peanut seed populations were used as input data to construct models using machine learning regression algorithms to accurately monitor changes in vigor. Model-predicted phenotypic data from 191 peanut varieties were used in GWAS, gene-based association studies, and haplotype analyses to screen for functional genes. Real-time fluorescence quantitative PCR (qPCR) was used to analyze the expression of functional genes in three high-vigor and three low-vigor germplasms. The results indicated that the random forest and support vector machine models provided effective phenotypic data. We identified Arahy.VMLN7L and Arahy.7XWF6F, with Arahy.VMLN7L negatively regulating seed vigor and Arahy.7XWF6F positively regulating it, suggesting distinct regulatory mechanisms. This study confirms that GWAS based on hyperspectral phenotyping reveals genetic relationships in seed vigor levels, offering novel insights and directions for future peanut breeding, accelerating genetic improvements, and boosting agricultural yields. This approach can be extended to monitor and explore germplasms and other key variables in various crops.

Genome-wide association analysis reveal candidate genes and haplotypes related to root weight in cucumber (Cucumis sativus L.)

Background

The plant root system is critical for the absorption of water and nutrients, and have a direct influence on growth and yield. In cucumber, a globally consumed crop, the molecular mechanism of root development remains unclear, and this has implications for developing stress tolerant varieties. This study sought to determine the genetic patterns and related genes of cucumber root weight. A core cucumber germplasms population was used to do the GWAS analysis in three environments.

Results

Here, we investigated four root-weight related traits including root fresh weight (RFW), root dry weight (RDW), ratio of root dry weight to root fresh weight (RDFW) and the comprehensive evaluation index, D-value of root weight (DRW) deduced based on the above three traits for the core germplasm of the cucumber global repository. According to the D-value, we identified 21 and 16 accessions with light and heavy-root, respectively. We also found that the East Asian ecotype accessions had significantly heavier root than other three ecotypes. The genome-wide association study (GWAS) for these four traits reveals that 4 of 10 significant loci (gDRW3.1, gDRW3.2, gDRW4.1 and gDRW5.1) were repeatedly detected for at least two traits. Further haplotype and expression analysis for protein-coding genes positioned within these 4 loci between light and heavy-root accessions predicted five candidate genes (i.e., Csa3G132020 and Csa3G132520 both encoding F-box protein PP2-B1 for gDRW3.1, Csa3G629240 encoding a B-cell receptor-associated protein for gDRW3.2, Csa4G499330 encodes a GTP binding protein for gDRW4.1, and Csa5G286040 encodes a proteinase inhibitor for gDRW5.1).

Conclusions

We conducted a systematic analysis of the root genetic basis and characteristics of cucumber core germplasms population. We detected four novel loci, which regulate the root weight in cucumber. Our study provides valuable candidate genes and haplotypes for the improvement of root system in cucumber breeding.

Designing future peanut: the power of genomics-assisted breeding

KEY MESSAGE

Integrating GAB methods with high-throughput phenotyping, genome editing, and speed breeding hold great potential in designing future smart peanut cultivars to meet market and food supply demands. Cultivated peanut (Arachis hypogaea L.), a legume crop greatly valued for its nourishing food, cooking oil, and fodder, is extensively grown worldwide. Despite decades of classical breeding efforts, the actual on-farm yield of peanut remains below its potential productivity due to the complicated interplay of genotype, environment, and management factors, as well as their intricate interactions. Integrating modern genomics tools into crop breeding is necessary to fast-track breeding efficiency and rapid progress. When combined with speed breeding methods, this integration can substantially accelerate the breeding process, leading to faster access of improved varieties to farmers. Availability of high-quality reference genomes for wild diploid progenitors and cultivated peanuts has accelerated the process of gene/quantitative locus discovery, developing markers and genotyping assays as well as a few molecular breeding products with improved resistance and oil quality. The use of new breeding tools, e.g., genomic selection, haplotype-based breeding, speed breeding, high-throughput phenotyping, and genome editing, is probable to boost genetic gains in peanut. Moreover, renewed attention to efficient selection and exploitation of targeted genetic resources is also needed to design high-quality and high-yielding peanut cultivars with main adaptation attributes. In this context, the combination of genomics-assisted breeding (GAB), genome editing, and speed breeding hold great potential in designing future improved peanut cultivars to meet market and food supply demands.

A genomic variation map provides insights into peanut diversity in China and associations with 28 agronomic traits

Peanut (Arachis hypogaea L.) is an important allotetraploid oil and food legume crop. China is one of the world's largest peanut producers and consumers. However, genomic variations underlying the migration and divergence of peanuts in China remain unclear. Here we reported a genome-wide variation map based on the resequencing of 390 peanut accessions, suggesting that peanuts might have been introduced into southern and northern China separately, forming two cultivation centers. Selective sweep analysis highlights asymmetric selection between the two subgenomes during peanut improvement. A classical pedigree from South China offers a context for the examination of the impact of artificial selection on peanut genome. Genome-wide association studies identified 22,309 significant associations with 28 agronomic traits, including candidate genes for plant architecture and oil biosynthesis. Our findings shed light on peanut migration and diversity in China and provide valuable genomic resources for peanut improvement.

Mapping Quantitative Trait Loci (QTLs) for Hundred-Pod and Hundred-Seed Weight under Seven Environments in a Recombinant Inbred Line Population of Cultivated Peanut (Arachis hypogaea L.)

The cultivated peanut (Arachis hypogaea L.) is a significant oil and cash crop globally. Hundred-pod and -seed weight are important components for peanut yield. To unravel the genetic basis of hundred-pod weight (HPW) and hundred-seed weight (HSW), in the current study, a recombinant inbred line (RIL) population with 188 individuals was developed from a cross between JH5 (JH5, large pod and seed weight) and M130 (small pod and seed weight), and was utilized to identify QTLs for HPW and HSW. An integrated genetic linkage map was constructed by using SSR, AhTE, SRAP, TRAP and SNP markers. This map consisted of 3130 genetic markers, which were assigned to 20 chromosomes, and covered 1998.95 cM with an average distance 0.64 cM. On this basis, 31 QTLs for HPW and HSW were located on seven chromosomes, with each QTL accounting for 3.7-10.8% of phenotypic variance explained (PVE). Among these, seven QTLs were detected under multiple environments, and two major QTLs were found on B04 and B08. Notably, a QTL hotspot on chromosome A08 contained seven QTLs over a 2.74 cM genetic interval with an 0.36 Mb physical map, including 18 candidate genes. Of these, Arahy.D52S1Z, Arahy.IBM9RL, Arahy.W18Y25, Arahy.CPLC2W and Arahy.14EF4H might play a role in modulating peanut pod and seed weight. These findings could facilitate further research into the genetic mechanisms influencing pod and seed weight in cultivated peanut.

Genome-Wide Analysis of the SNARE Family in Cultivated Peanut (Arachis hypogaea L.) Reveals That Some Members Are Involved in Stress Responses

The superfamily of soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins mediates membrane fusion during vesicular transport between endosomes and the plasma membrane in eukaryotic cells, playing a vital role in plant development and responses to biotic and abiotic stresses. Peanut (Arachis hypogaea L.) is a major oilseed crop worldwide that produces pods below ground, which is rare in flowering plants. To date, however, there has been no systematic study of SNARE family proteins in peanut. In this study, we identified 129 putative SNARE genes from cultivated peanut (A. hypogaea) and 127 from wild peanut (63 from Arachis duranensis, 64 from Arachis ipaensis). We sorted the encoded proteins into five subgroups (Qa-, Qb-, Qc-, Qb+c- and R-SNARE) based on their phylogenetic relationships with Arabidopsis SNAREs. The genes were unevenly distributed on all 20 chromosomes, exhibiting a high rate of homolog retention from their two ancestors. We identified cis-acting elements associated with development, biotic and abiotic stresses in the promoters of peanut SNARE genes. Transcriptomic data showed that expression of SNARE genes is tissue-specific and stress inducible. We hypothesize that AhVTI13b plays an important role in the storage of lipid proteins, while AhSYP122a, AhSNAP33a and AhVAMP721a might play an important role in development and stress responses. Furthermore, we showed that three AhSNARE genes (AhSYP122a, AhSNAP33a and AhVAMP721) enhance cold and NaCl tolerance in yeast (Saccharomyces cerevisiae), especially AhSNAP33a. This systematic study provides valuable information about the functional characteristics of AhSNARE genes in the development and regulation of abiotic stress responses in peanut.

Genome-wide association studies reveal novel loci for resistance to groundnut rosette disease in the African core groundnut collection

KEY MESSAGE

We identified markers associated with GRD resistance after screening an Africa-wide core collection across three seasons in Uganda Groundnut is cultivated in several African countries where it is a major source of food, feed and income. One of the major constraints to groundnut production in Africa is groundnut rosette disease (GRD), which is caused by a complex of three agents: groundnut rosette assistor luteovirus, groundnut rosette umbravirus and its satellite RNA. Despite several years of breeding for GRD resistance, the genetics of the disease is not fully understood. The objective of the current study was to use the African core collection to establish the level of genetic variation in their response to GRD, and to map genomic regions responsible for the observed resistance. The African groundnut core genotypes were screened across two GRD hotspot locations in Uganda (Nakabango and Serere) for 3 seasons. The Area Under Disease Progress Curve combined with 7523 high quality SNPs were analyzed to establish marker-trait associations (MTAs). Genome-Wide Association Studies based on Enriched Compressed Mixed Linear Model detected 32 MTAs at Nakabango: 21 on chromosome A04, 10 on B04 and 1 on B08. Two of the significant markers were localised on the exons of a putative TIR-NBS-LRR disease resistance gene on chromosome A04. Our results suggest the likely involvement of major genes in the resistance to GRD but will need to be further validated with more comprehensive phenotypic and genotypic datasets. The markers identified in the current study will be developed into routine assays and validated for future genomics-assisted selection for GRD resistance in groundnut.

The Key to the Future Lies in the Past: Insights from Grain Legume Domestication and Improvement Should Inform Future Breeding Strategies

Crop domestication is a co-evolutionary process that has rendered plants and animals significantly dependent on human interventions for survival and propagation. Grain legumes have played an important role in the development of Neolithic agriculture some 12,000 years ago. Despite being early companions of cereals in the origin and evolution of agriculture, the understanding of grain legume domestication has lagged behind that of cereals. Adapting plants for human use has resulted in distinct morpho-physiological changes between the wild ancestors and domesticates, and this distinction has been the focus of several studies aimed at understanding the domestication process and the genetic diversity bottlenecks created. Growing evidence from research on archeological remains, combined with genetic analysis and the geographical distribution of wild forms, has improved the resolution of the process of domestication, diversification and crop improvement. In this review, we summarize the significance of legume wild relatives as reservoirs of novel genetic variation for crop breeding programs. We describe key legume features, which evolved in response to anthropogenic activities. Here, we highlight how whole genome sequencing and incorporation of omics-level data have expanded our capacity to monitor the genetic changes accompanying these processes. Finally, we present our perspective on alternative routes centered on de novo domestication and re-domestication to impart significant agronomic advances of novel crops over existing commodities. A finely resolved domestication history of grain legumes will uncover future breeding targets to develop modern cultivars enriched with alleles that improve yield, quality and stress tolerance.

Genome-Wide Characterization of Ascorbate Peroxidase Gene Family in Peanut (Arachis hypogea L.) Revealed Their Crucial Role in Growth and Multiple Stress Tolerance

Ascorbate peroxidase (APX), an important antioxidant enzyme, plays a significant role in ROS scavenging by catalyzing the decrease of hydrogen peroxide under various environmental stresses. Nevertheless, information about the APX gene family and their evolutionary and functional attributes in peanut (Arachis hypogea L.) was not reported. Therefore, a comprehensive genome-wide study was performed to discover the APX genes in cultivated peanut genome. This study identified 166 AhAPX genes in the peanut genome, classified into 11 main groups. The gene duplication analysis showed that AhAPX genes had experienced segmental duplications and purifying selection pressure. Gene structure and motif investigation indicated that most of the AhAPX genes exhibited a comparatively well-preserved exon-intron pattern and motif configuration contained by the identical group. We discovered five phytohormones-, six abiotic stress-, and five growth and development-related cis-elements in the promoter regions of AhAPX. Fourteen putative ah-miRNAs from 12 families were identified, targeting 33 AhAPX genes. Furthermore, we identified 3,257 transcription factors from 38 families (including AP2, ARF, B3, bHLH, bZIP, ERF, MYB, NAC, WRKY, etc.) in 162 AhAPX genes. Gene ontology and KEGG enrichment analysis confirm the role of AhAPX genes in oxidoreductase activity, catalytic activity, cell junction, cellular response to stimulus and detoxification, biosynthesis of metabolites, and phenylpropanoid metabolism. Based on transcriptome datasets, some genes such as AhAPX4/7/17/77/82/86/130/133 and AhAPX160 showed significantly higher expression in diverse tissues/organs, i.e., flower, leaf, stem, roots, peg, testa, and cotyledon. Likewise, only a few genes, including AhAPX4/17/19/55/59/82/101/102/137 and AhAPX140, were significantly upregulated under abiotic (drought and cold), and phytohormones (ethylene, abscisic acid, paclobutrazol, brassinolide, and salicylic acid) treatments. qRT-PCR-based expression profiling presented the parallel expression trends as generated from transcriptome datasets. Our discoveries gave new visions into the evolution of APX genes and provided a base for further functional examinations of the AhAPX genes in peanut breeding programs.

Genetic characterization of flowering and phytochrome genes in peanut (Arachis hypogaea L.) for early maturity

BACKGROUND

Peanut (Arachis hypogaea L.) production and cropping pattern is highly influenced by the climatic factors including temperature and rain pattern fluctuations. It is one of the most important cash crop in the rain fed areas of Pakistan and its production, under changing climatic conditions, that can be improved by developing short duration varieties. The present study was based on the molecular characterization of the maturity associated gene families in the peanut under two light conditions.

METHODS AND RESULTS

Genomic analysis based on the in silico study of important gene families for early maturity associated attributes like flowering time, their pattern, duration and photoperiodism was done for a comprehensive mapping of maturity related genes. Phytochromes genes Phy A, Phy B and Phy E and flowering genes FT2a, Ft5a and COL2 were selected for in silico characterization for protein based analysis including Multiple Sequence Alignment (MSA), and Neighbor Joining (NJ) tree. MSA and NJ trees of the peanut with Arabidopsis thaliana and Glycine max showed a clear picture of the phylogenetic relationship on the basis of selected gene proteins. Expression profile of phytochrome and flowering genes revealed that photoperiod conditions i.e. short and long days, have great influence on the Phy A, Phy B and Phy E, Ft2a, FT5a and COL2 gene expression pattern. In current study, the relative expression of all studied genes was found higher in short day light condition at flower initiation stage of the plants than in the long light day condition with exception of COL2 gene protein.

CONCLUSIONS

The molecular characterization based on the in silico study of the particular genes and qPCR based gene expression profiling of the selected genes provided an evidence of the role of these genes and their comparative analysis under two photoperiodic conditions.