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

Dissecting genomic regions and underlying candidate genes in groundnut MAGIC population for drought tolerance

BACKGROUND

Groundnut is mainly grown in the semi-arid tropic (SAT) regions worldwide, where abiotic stress like drought is persistent. However, a major research gap exists regarding exploring the genetic and genomic underpinnings of tolerance to drought. In this study, a multi-parent advanced generation inter-cross (MAGIC) population was developed and evaluated for five seasons at two locations for three consecutive years (2018-19, 2019-20 and 2020-21) under drought stress and normal environments.

RESULTS

Phenotyping data of drought tolerance related traits, combined with the high-quality 10,556 polymorphic SNPs, were used to perform multi-locus model genome-wide association study (GWAS) analysis. We identified 37 significant marker-trait associations (MTAs) (Bonferroni-corrected) accounting, 0.91- 9.82% of the phenotypic variance. Intriguingly, 26 significant MTAs overlap on four chromosomes (Ah03, Ah07, Ah10 and Ah18) (harboring 70% of MTAs), indicating genomic hotspot regions governing drought tolerance traits. Furthermore, important candidate genes associated with leaf senescence (NAC transcription factor), flowering (B3 domain-containing transcription factor, Ulp1 protease family, and Ankyrin repeat-containing protein), involved in chlorophyll biosynthesis (FAR1 DNA-binding domain protein), stomatal regulation (Rop guanine nucleotide exchange factor; Galacturonosyltransferases), and associated with yield traits (Fasciclin-like arabinogalactan protein 11 and Fasciclin-like arabinogalactan protein 21) were found in the vicinity of significant MTAs genomic regions.

CONCLUSION

The findings of our investigation have the potential to provide a basis for significant MTAs validation, gene discovery and development of functional markers, which could be employed in genomics-assisted breeding to develop climate-resilient groundnut varieties.

Optimizing Peanut (Arachis hypogaea L.) Production: Genetic Insights, Climate Adaptation, and Efficient Management Practices: Systematic Review

Peanut production plays a crucial role in global food security, particularly in developing countries, where it provides essential nutrition and income. This paper examines the optimization of peanut production through genetic advancements, climate adaptation strategies, and sustainable practices. The primary objective is to increase yields by addressing challenges related to climate change, pests, and resource constraints. Globally, peanut production is hindered by rising temperatures, irregular rainfall, and declining soil quality, impacting both yield and quality. Developing countries, especially in Africa and Asia, face additional challenges, such as limited access to advanced agricultural technologies, inadequate infrastructure, and insufficient support for smallholder farmers. The vital issues include genetic vulnerabilities to pests, climate stress, and inefficient water use. Recent genetic research has provided insights into breeding more resilient, drought-resistant varieties, offering hope for improving yields, despite environmental challenges. The adoption of climate adaptation strategies, precision farming, and integrated pest management is essential for boosting productivity. These, along with optimized irrigation and nutrient management, have significantly impacted peanut production in resource-limited settings. Additionally, drought-resistant varieties have proven crucial, enabling farmers to increase resilience and yields in areas facing climate stress. In conclusion, optimizing peanut production requires continued investment in genetic advancements, infrastructure, and sustainable practices. Future efforts should focus on improving climate adaptation and sustainable farming techniques for long-term success.

Early exposure to phosphorus starvation induces genetically determined responses in Sorghum bicolor roots

KEY MESSAGE

We identified novel physiological and genetic responses to phosphorus starvation in sorghum diversity lines that augment current knowledge of breeding for climate-smart crops in Europe. Phosphorus (P) deficiency and finite P reserves for fertilizer production pose a threat to future global crop production. Understanding root system architecture (RSA) plasticity is central to breeding for P-efficient crops. Sorghum is regarded as a P-efficient and climate-smart crop with strong adaptability to different climatic regions of the world. Here we investigated early genetic responses of sorghum RSA to P deficiency in order to identified genotypes with interesting root phenotypes and responses under low P. A diverse set of sorghum lines (n = 285) was genotyped using DarTSeq generating 12,472 quality genome wide single-nucleotide polymorphisms. Root phenotyping was conducted in a paper-based hydroponic rhizotron system under controlled greenhouse conditions with low and optimal P nutrition, using 16 RSA traits to describe genetic and phenotypic variability at two time points. Genotypic and phenotypic P-response variations were observed for multiple root traits at 21 and 42 days after germination with high broad sense heritability (0.38-0.76). The classification of traits revealed four distinct sorghum RSA types, with genotypes clustering separately under both low and optimal P conditions, suggesting genetic control of root responses to P availability. Association studies identified quantitative trait loci in chromosomes Sb02, Sb03, Sb04, Sb06 and Sb09 linked with genes potentially involved in P transport and stress responses. The genetic dissection of key factors underlying RSA responses to P deficiency could enable early identification of P-efficient sorghum genotypes. Genotypes with interesting RSA traits for low P environments will be incorporated into current sorghum breeding programs for later growth stages and field-based evaluations.

The groundnut improvement network for Africa (GINA) germplasm collection: a unique genetic resource for breeding and gene discovery

Cultivated peanut or groundnut (Arachis hypogaea L.) is a grain legume grown in many developing countries by smallholder farmers for food, feed, and/or income. The speciation of the cultivated species, that involved polyploidization followed by domestication, greatly reduced its variability at the DNA level. Mobilizing peanut diversity is a prerequisite for any breeding program for overcoming the main constraints that plague production and for increasing yield in farmer fields. In this study, the Groundnut Improvement Network for Africa assembled a collection of 1,049 peanut breeding lines, varieties, and landraces from 9 countries in Africa. The collection was genotyped with the Axiom_Arachis2 48K SNP array and 8,229 polymorphic single nucleotide polymorphism (SNP) markers were used to analyze the genetic structure of this collection and quantify the level of genetic diversity in each breeding program. A supervised model was developed using dapc to unambiguously assign 542, 35, and 172 genotypes to the Spanish, Valencia, and Virginia market types, respectively. Distance-based clustering of the collection showed a clear grouping structure according to subspecies and market types, with 73% of the genotypes classified as fastigiata and 27% as hypogaea subspecies. Using STRUCTURE, the global structuration was confirmed and showed that, at a minimum membership of 0.8, 76% of the varieties that were not assigned by dapc were actually admixed. This was particularly the case of most of the genotype of the Valencia subgroup that exhibited admixed genetic heritage. The results also showed that the geographic origin (i.e. East, Southern, and West Africa) did not strongly explain the genetic structure. The gene diversity managed by each breeding program, measured by the expected heterozygosity, ranged from 0.25 to 0.39, with the Niger breeding program having the lowest diversity mainly because only lines that belong to the fastigiata subspecies are used in this program. Finally, we developed a core collection composed of 300 accessions based on breeding traits and genetic diversity. This collection, which is composed of 205 genotypes of fastigiata subspecies (158 Spanish and 47 Valencia) and 95 genotypes of hypogaea subspecies (all Virginia), improves the genetic diversity of each individual breeding program and is, therefore, a unique resource for allele mining and breeding.

Development and evaluation of the utility of GenoBaits Peanut 40K for a peanut MAGIC population

Population and genotype data are essential for genetic mapping. The multi-parent advanced generation intercross (MAGIC) population is a permanent mapping population used for precisely mapping quantitative trait loci. Moreover, genotyping-by-target sequencing (GBTS) is a robust high-throughput genotyping technology characterized by its low cost, flexibility, and limited requirements for information management and support. In this study, an 8-way MAGIC population was constructed using eight elite founder lines. In addition, GenoBaits Peanut 40K was developed and utilized for the constructed MAGIC population. A subset (297 lines) of the MAGIC population at the S2 stage was genotyped using GenoBaits Peanut 40K. Furthermore, these lines and the eight parents were analyzed in terms of pod length, width, area, and perimeter. A total of 27 single nucleotide polymorphisms (SNPs) were revealed to be significantly associated with peanut pod size-related traits according to a genome-wide association study. The GenoBaits Peanut 40K provided herein and the constructed MAGIC population will be applicable for future research to identify the key genes responsible for important peanut traits.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01417-w.