Comparisons of sampling methods for assessing intra- and inter-accession genetic diversity in three rice species using genotyping by sequencing

Challenges and Opportunities in the Sustainable Improvement of Carrot Production

From an agricultural perspective, carrots are a significant tap root vegetable crop in the Apiaceae family because of their nutritional value, health advantages, and economic importance. The edible part of a carrot, known as the storage root, contains various beneficial compounds, such as carotenoids, anthocyanins, dietary fiber, vitamins, and other nutrients. It has a crucial role in human nutrition as a significant vegetable and raw material in the nutraceutical, food, and pharmaceutical industries. The cultivation of carrot fields is susceptible to a wide range of biotic and abiotic hazards, which can significantly damage the plants' health and decrease yield and quality. Scientific research mostly focuses on important biotic stressors, including pests, such as nematodes and carrot flies, as well as diseases, such as cavity spots, crown or cottony rot, black rot, and leaf blight, caused by bacteria, fungi, and oomycetes. The emerging challenges in the field include gaining a comprehensive understanding of the interaction between hosts and pathogens in the carrot-pathogen system, identifying the elements that contribute to disease development, expanding knowledge of systemic treatments, exploring host resistance mechanisms, developing integrated control programs, and enhancing resistance through breeding approaches. In fact, the primary carrot-growing regions in tropical and subtropical climates are experiencing abiotic pressures, such as drought, salinity, and heat stress, which limit carrot production. This review provides an extensive, up-to-date overview of the literature on biotic and abiotic factors for enhanced and sustainable carrot production, considering the use of different technologies for the shelf-life extension of carrots. Therefore, it addresses the current issues in the carrot production chain, opening new perspectives for the exploration of carrots both as a food commodity and as a source of natural compounds.

Sampling strategies for genotyping common bean (Phaseolus vulgaris L.) Genebank accessions with DArTseq: a comparison of single plants, multiple plants, and DNA pools

Introduction

Genotyping large-scale gene bank collections requires an appropriate sampling strategy to represent the diversity within and between accessions.

Methods

A panel of 44 common bean (Phaseolus vulgaris L.) landraces from the Alliance Bioversity and The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) gene bank was genotyped with DArTseq using three sampling strategies: a single plant per accession, 25 individual plants per accession jointly analyzed after genotyping (in silico-pool), and by pooling tissue from 25 individual plants per accession (seq-pool). Sampling strategies were compared to assess the technical aspects of the samples, the marker information content, and the genetic composition of the panel.

Results

The seq-pool strategy resulted in more consistent DNA libraries for quality and call rate, although with fewer polymorphic markers (6,142 single-nucleotide polymorphisms) than the in silico-pool (14,074) or the single plant sets (6,555). Estimates of allele frequencies by seq-pool and in silico-pool genotyping were consistent, but the results suggest that the difference between pools depends on population heterogeneity. Principal coordinate analysis, hierarchical clustering, and the estimation of admixture coefficients derived from a single plant, in silico-pool, and seq-pool successfully identified the well-known structure of Andean and Mesoamerican gene pools of P. vulgaris across all datasets.

Conclusion

In conclusion, seq-pool proved to be a viable approach for characterizing common bean germplasm compared to genotyping individual plants separately by balancing genotyping effort and costs. This study provides insights and serves as a valuable guide for gene bank researchers embarking on genotyping initiatives to characterize their collections. It aids curators in effectively managing the collections and facilitates marker-trait association studies, enabling the identification of candidate markers for key traits.

Maize dispersal patterns associated with different types of endosperm and migration of indigenous groups in lowland South America

BACKGROUND AND AIMS

The lowlands of South America appear to be remarkably important in the evolutionary history of maize, due to new evidence that suggests that maize dispersed from Mexico and arrived in this region in a state of partial domestication. This study aimed to identify dispersal patterns of maize genetic diversity in this part of the continent.

METHODS

A total of 170 maize accessions were characterized with 4398 single nucleotide polymorphisms (SNPs) and analysed to determine if maize dispersal was associated with types of endosperm and indigenous language families.

KEY RESULTS

Four genetic groups were identified in the discriminant analysis of principal components and five groups in the cluster analysis (neighbour-joining method). The groups were structured according to the predominance of endosperm types (popcorn, floury, flint/semi-flint). Spatial principal component analysis of genetic variation suggests different dispersal patterns for each endosperm type and can be associated with hypotheses of expansions of different indigenous groups.

CONCLUSIONS

From a possible origin in Southwestern Amazonia, different maize dispersal routes emerged: (1) towards Northern Amazonia, which continued towards the Caatinga and south-eastern Atlantic Forest (Floury); (2) towards Southern Brazil, passing through the Cerrado and Southern Atlantic Forest reaching the Pampa region (Floury); and (3) along the Atlantic Coast, following Tupi movements originating from two separate expansions: one (Tupinamba) from north to south, and the other (Guarani) in the opposite direction, from south to north (flint, floury and popcorn).

Evaluation of gene flow and genetic diversity in rice accessions across Kurdistan region-iraq using SSR markers

BACKGROUND

In recent years, farmers have complained that the only way to obtain seeds is to select plants that show good performance under local climate conditions in the region. This study aimed to investigate the diversity of rice accessions grown in the region to build a breeding program. METHODS AND RESULTS: A total of 62 accessions of rice from farmers and research stations were collected from the Kurdistan region, including short-grain and long-grain types, for molecular genetics and diversity analysis. In this study, 37 polymorphic simple sequence repeat (SSR) markers were selected with several molecular genetics software programs. The results show that these SSR markers are very effective for this investigation, generating a total of 152 observed alleles (Na), 75.166 Effective number of alleles (Ne) and an average of 4.1 and 2.03 alleles per locus, respectively. The average polymorphic information content (PIC) per locus was recorded as 0.404. The research presented here confirms two subpopulations, japonica (C1 and C2) and indica (C3), based on molecular genetics data analysis. Analysis of molecular variance revealed that the 72% variance was due to the variation among populations and 28% within the population.

CONCLUSIONS

Altogether, these results indicate that there is very low gene flow. These results show the importance of the study of genetic diversity and relationships for starting breeding and improvement programs for rice in the Kurdistan region.

The INCREASE project: Intelligent Collections of food-legume genetic resources for European agrofood systems

Food legumes are crucial for all agriculture-related societal challenges, including climate change mitigation, agrobiodiversity conservation, sustainable agriculture, food security and human health. The transition to plant-based diets, largely based on food legumes, could present major opportunities for adaptation and mitigation, generating significant co-benefits for human health. The characterization, maintenance and exploitation of food-legume genetic resources, to date largely unexploited, form the core development of both sustainable agriculture and a healthy food system. INCREASE will implement, on chickpea (Cicer arietinum), common bean (Phaseolus vulgaris), lentil (Lens culinaris) and lupin (Lupinus albus and L. mutabilis), a new approach to conserve, manage and characterize genetic resources. Intelligent Collections, consisting of nested core collections composed of single-seed descent-purified accessions (i.e., inbred lines), will be developed, exploiting germplasm available both from genebanks and on-farm and subjected to different levels of genotypic and phenotypic characterization. Phenotyping and gene discovery activities will meet, via a participatory approach, the needs of various actors, including breeders, scientists, farmers and agri-food and non-food industries, exploiting also the power of massive metabolomics and transcriptomics and of artificial intelligence and smart tools. Moreover, INCREASE will test, with a citizen science experiment, an innovative system of conservation and use of genetic resources based on a decentralized approach for data management and dynamic conservation. By promoting the use of food legumes, improving their quality, adaptation and yield and boosting the competitiveness of the agriculture and food sector, the INCREASE strategy will have a major impact on economy and society and represents a case study of integrative and participatory approaches towards conservation and exploitation of crop genetic resources.

Development and validation of diagnostic SNP markers for quality control genotyping in a collection of four rice (Oryza) species

Morphological identification of closely related rice species, particularly those in the Oryza AA genome group, presents major challenges and often results in cases of misidentification. Recent work by this group identified diagnostic single nucleotide polymorphic (SNP) markers specific for several rice species and subspecies based on DArTseq next-generation sequencing technology ("DArTseq"). These SNPs can be used for quality control (QC) analysis in rice breeding and germplasm maintenance programs. Here, we present the DArTseq-based diagnostic SNPs converted into Kompetitive allele-specific PCR (KASPar or KASP) assays and validation data for a subset of them; these can be used for low-cost routine genotyping quality control (QC) analysis. Of the 224 species/subspecies' diagnostic SNPs tested, 158 of them produced working KASP assays, a conversion success rate of 70%. Two validation experiments were run with 87 of the 158 SNP markers to ensure that the assays amplified, were polymorphic, and distinguished the five species/subspecies tested. Based on these validation test results, we recommend a panel of 36 SNP markers that clearly delineate O. barthii, O. glaberrima, O. longistaminata, O. sativa spp. indica and japonica. The KASP assays provide a flexible, rapid turnaround and cost-effective tool to facilitate germplasm curation and management of these four Oryza AA genome species across multiple genebanks.

Patterns of Genetic Variation in a Soybean Germplasm Collection as Characterized with Genotyping-by-Sequencing

Genomic characterization is playing an increasing role in plant germplasm conservation and utilization, as it can provide higher resolution with genome-wide SNP markers than before to identify and analyze genetic variation. A genotyping-by-sequencing technique was applied to genotype 541 soybean accessions conserved at Plant Gene Resources of Canada and 30 soybean cultivars and breeding lines developed by the Ottawa soybean breeding program of Agriculture and Agri-Food Canada. The sequencing generated an average of 952,074 raw sequence reads per sample. SNP calling identified 43,891 SNPs across 20 soybean chromosomes and 69 scaffolds with variable levels of missing values. Based on 19,898 SNPs with up to 50% missing values, three distinct genetic groups were found in the assayed samples. These groups were a mixture of the samples that originated from different countries and the samples of known maturity groups. The samples that originated from Canada were clustered into all three distinct groups, but 30 Ottawa breeding lines fell into two groups only. Based on the average pairwise dissimilarity estimates, 40 samples with the most genetic distinctness were identified from three genetic groups with diverse sample origin and known maturity. Additionally, 40 samples with the highest genetic redundancy were detected and they consisted of different sample origins and maturity groups, largely from one genetic group. Moreover, some genetically duplicated samples were identified, but the overall level of genetic duplication was relatively low in the collection. These findings are useful for soybean germplasm management and utilization.

Deciphering the Genetic Diversity of Landraces With High-Throughput SNP Genotyping of DNA Bulks: Methodology and Application to the Maize 50k Array

Genebanks harbor original landraces carrying many original favorable alleles for mitigating biotic and abiotic stresses. Their genetic diversity remains, however, poorly characterized due to their large within genetic diversity. We developed a high-throughput, cheap and labor saving DNA bulk approach based on single-nucleotide polymorphism (SNP) Illumina Infinium HD array to genotype landraces. Samples were gathered for each landrace by mixing equal weights from young leaves, from which DNA was extracted. We then estimated allelic frequencies in each DNA bulk based on fluorescent intensity ratio (FIR) between two alleles at each SNP using a two step-approach. We first tested either whether the DNA bulk was monomorphic or polymorphic according to the two FIR distributions of individuals homozygous for allele A or B, respectively. If the DNA bulk was polymorphic, we estimated its allelic frequency by using a predictive equation calibrated on FIR from DNA bulks with known allelic frequencies. Our approach: (i) gives accurate allelic frequency estimations that are highly reproducible across laboratories, (ii) protects against false detection of allele fixation within landraces. We estimated allelic frequencies of 23,412 SNPs in 156 landraces representing American and European maize diversity. Modified Roger's genetic Distance between 156 landraces estimated from 23,412 SNPs and 17 simple sequence repeats using the same DNA bulks were highly correlated, suggesting that the ascertainment bias is low. Our approach is affordable, easy to implement and does not require specific bioinformatics support and laboratory equipment, and therefore should be highly relevant for large-scale characterization of genebanks for a wide range of species.