NGSEP3: accurate variant calling across species and sequencing protocols

Rapid evolutionary tuning of endospore quantity versus quality trade-off via a phase-variable contingency locus

The UV resistance of bacterial endospores is an important quality supporting their survival in inhospitable environments and therefore constitutes an essential driver of the ecological success of spore-forming bacteria. Nevertheless, the variability and evolvability of this trait are poorly understood. In this study, directed evolution and genetics approaches revealed that the Bacillus cereus pdaA gene (encoding the endospore-specific peptidoglycan-N-acetylmuramic acid deacetylase) serves as a contingency locus in which the expansion and contraction of short tandem repeats can readily compromise (PdaAOFF) or restore (PdaAON) the pdaA open reading frame. Compared with B. cereus populations in the PdaAON state, populations in the PdaAOFF state produced a lower yield of viable endospores but endowed them with vastly increased UV resistance. Moreover, selection pressures based on either quantity (i.e., yield of viable endospores) or quality (i.e., UV resistance of viable endospores) aspects could readily shift populations between PdaAON and PdaAOFF states, respectively. Bioinformatic analysis also revealed that pdaA homologs within the Bacillus and Clostridium genera are often equipped with several short tandem repeat regions, suggesting a wider implementation of the pdaA-mediated phase variability in other sporeformers as well. These results for the first time reveal (1) pdaA as a phase-variable contingency locus in the adaptive evolution of endospore properties and (2) bet-hedging between what appears to be a quantity versus quality trade-off in endospore crops.

Genetic study of Camelina sativa oilseed crop and selection of a new variety by the bulk method

Camelina sativa, commonly referred to as camelina or false flax, has emerged as a promising cover crop with the potential to mitigate climate change-a pressing global challenge that demands urgent and sustainable solutions. Belonging to the Brassicaceae family and native to Europe and Central Asia, camelina is an oilseed crop known for its resilience in diverse climates, including arid and semi-arid regions, making it adaptable to various environments. A breeding program started from a study of six winter varieties and five spring varieties of camelina is described: these genetic materials were characterized by SSRs molecular markers and by GBS technique. Molecular data clearly showed all spring varieties were genetically similar and distinguishable from the winter varieties, which, in turn, clustered together. Using molecular data, parental varieties belonging to the two different clusters were selected to generate new genetic variability. The new variety obtained, selected through the bulk method based on three parameters: yield, earliness, and weight of 1000 seeds, has allowed the generation of the new genetic material provisionally named C1244. Chemical characterization was performed (bromatological and glucosinolates analysis) to better describe C1244 in comparison with benchmark varieties. The new variety exhibited early maturity, similar to spring varieties, making this genetic material promising for use in intercropping systems, a high weight of 1000 seeds (1.46 g) which improves and facilitates seeding/harvesting operations and a high oil content (33.62%) akin to winter varieties making it valuable for human and animal food purposes.

A revisited history of cacao domestication in pre-Columbian times revealed by archaeogenomic approaches

Humans have a long history of transporting and trading plants, contributing to the evolution of domesticated plants. Theobroma cacao originated in the Neotropics from South America. However, little is known about its domestication and use in these regions. In this study, ceramic residues from a large sample of pre-Columbian cultures from South and Central America were analyzed using archaeogenomic and biochemical approaches. Here we show, for the first time, the widespread use of cacao in South America out of its native Amazonian area of origin, extending back 5000 years, likely supported by cultural interactions between the Amazon and the Pacific coast. We observed that strong genetic mixing between geographically distant cacao populations occurred as early as the middle Holocene, in South America, driven by humans, favoring the adaptation of T. cacao to new environments. This complex history of cacao domestication is the basis of today's cacao tree populations and its knowledge can help us better manage their genetic resources.

A high-density linkage map construction in guava (Psidium guajava L.) using genotyping by sequencing and identification of QTLs for leaf, peel, and pulp color in an intervarietal mapping population

Psidium guajava L. is an important fruit crop in the tropical and subtropical regions of the world. The advanced breeding methods are not employed for important commercial traits like peel and pulp color, seed hardiness, fruit size, etc., due to the scarcity of genome-wide molecular markers and high-density linkage maps. In this study, we employed single-nucleotide polymorphism (SNP) markers and identified quantitative trait loci (QTL) regions that are associated with color traits of leaf, peel, and pulp in the guava intervarietal mapping population. The mapping population was developed from the contrasting genotypes of fruit and leaf color. Variations in color among the segregating hybrids were recorded both visually and using a Color reader. A high-density linkage map of guava was constructed using the SNP markers from genotyping by sequencing (GBS) of 150 hybrid individuals of the cross 'Arka Poorna' (green) x 'Purple Local' (purple). The integrated linkage map consisted of 1426 SNPs mapped on 11 linkage groups (LG), spanning a total distance of around 730 cM with an average of 129.6 markers per LG. Through QTL analysis for color traits, a minor QTL region was identified for visually scored leaf color and peel color on LG1, whereas a major QTL was detected for pulp color in LG4. The Hunter color values (L* and, a*) also had major QTLs with overlapping marker intervals for leaf and peel colors, establishing the association of SNP markers to the trait. The QTLs harbored genes and transcription factors involved in lycopene and anthocyanin pigment biosynthesis. This is the first report of a high-density linkage map based on SNP markers in guava and QTL mapping for color characters in leaf, fruit peel and pulp. The genotyping information generated in this study can aid in genetic engineering and marker-assisted breeding in guava.

Genome-wide association and genomic prediction for iron and zinc concentration and iron bioavailability in a collection of yellow dry beans

Dry bean is a nutrient-dense food targeted in biofortification programs to increase seed iron and zinc levels. The underlying assumption of breeding for higher mineral content is that enhanced iron and zinc levels will deliver health benefits to the consumers of these biofortified foods. This study characterized a diversity panel of 275 genotypes comprising the Yellow Bean Collection (YBC) for seed Fe and Zn concentration, Fe bioavailability (FeBio), and seed yield across 2 years in two field locations. The genetic architecture of each trait was elucidated via genome-wide association studies (GWAS) and the efficacy of genomic prediction (GP) was assessed. Moreover, 82 yellow breeding lines were evaluated for seed Fe and Zn concentrations as well as seed yield, serving as a prediction set for GP models. Large phenotypic variability was identified in all traits evaluated, and variations of up to 2.8 and 13.7-fold were observed for Fe concentration and FeBio, respectively. Prediction accuracies in the YBC ranged from a low of 0.12 for Fe concentration, to a high of 0.72 for FeBio, and an accuracy improvement of 0.03 was observed when a QTN, identified through GWAS, was used as a fixed effect for FeBio. This study provides evidence of the lack of correlation between FeBio estimated in vitro and Fe concentration and highlights the potential of GP in accurately predicting FeBio in yellow beans, offering a cost-effective alternative to the traditional assessment of using Caco2 cell methodologies.

The evolutionary history of three Baracoffea species from western Madagascar revealed by chloroplast and nuclear genomes

The wild species of the Coffea genus present a very wide morphological, genetic, and biochemical diversity. Wild species are recognized more resistant to diseases, pests, and environmental variations than the two species currently cultivated worldwide: C. arabica (Arabica) and C. canephora (Robusta). Consequently, wild species are now considered as a crucial resource for adapting cultivated coffee trees to climate change. Within the Coffea genus, 79 wild species are native to the Indian Ocean islands of Comoros, Mayotte, Mauritius, Réunion and Madagascar, out of a total of 141 taxa worldwide. Among them, a group of 9 species called "Baracoffea" are particularly atypical in their morphology and adaptation to the sandy soils of the dry deciduous forests of western Madagascar. Here, we have attempted to shed light on the evolutionary history of three Baracoffea species: C. ambongensis, C. boinensis and C. bissetiae by analyzing their chloroplast and nuclear genomes. We assembled the complete chloroplast genomes de novo and extracted 28,800 SNP (Single Nucleotide Polymorphism) markers from the nuclear genomes. These data were used for phylogenetic analysis of Baracoffea with Coffea species from Madagascar and Africa. Our new data support the monophyletic origin of Baracoffea within the Coffea of Madagascar, but also reveal a divergence with a sister clade of four species: C. augagneurii, C. ratsimamangae, C. pervilleana and C. Mcphersonii (also called C. vohemarensis), belonging to the Subterminal botanical series and living in dry or humid forests of northern Madagascar. Based on a bioclimatic analysis, our work suggests that Baracoffea may have diverged from a group of Malagasy Coffea from northern Madagascar and adapted to the specific dry climate and low rainfall of western Madagascar. The genomic data generated in the course of this work will contribute to the understanding of the adaptation mechanisms of these particularly singular species.

Whole-genome resequencing-based characterization of a durum wheat landrace showing similarity to 'Senatore Cappelli'

Durum wheat (Triticum turgidum spp. durum) is a major cereal adopted since antiquity to feed humans. Due to its use, dating back several millennia, this species features a wide genetic diversity and landraces are considered important repositories of gene pools which constitute invaluable tools for breeders. The aim of this work is to provide a first characterization of a wheat landrace, referred to as 'TB2018', that was collected in the Apulia region (Southern Italy). 'TB2018' revealed, through visual inspection, characters reminiscent of the traditional variety 'Senatore Cappelli', while exhibiting a distinctive trait, i.e., reduced stature. Indeed, the comparison with a set of Italian durum wheat cultivars conducted in this study, in which 24 CPVO plant descriptors were adopted, placed the 'TB2018' landrace in proximity to the 'Senatore Cappelli' cultivar. In addition, the close similarity between the two genotypes was confirmed by the analysis of the seed protein pattern. A relative reduction was detected for 'TB2018' root elongation in the early stages of plant growth. The 'TB2018' genome sequence, obtained through low-coverage resequencing and comparison to the reference 'Svevo' cultivar is also reported in this study, followed by a genome-wide comparison against 259 durum wheat accessions that placed 'TB2018' close to the 'Cappelli' reference. Hundreds of genes putatively affected by variants that possess Gene Ontology descriptors were detected, among which some were shown to be putatively linked to the morphological traits that distinguish 'TB2018' from 'Senatore Cappelli', Overall, this study poses the basis for a possible exploitation of 'TB2018' per se in cultivation or as a source of alternative alleles in the breeding of traditional cultivars. This work also presents a genomic methodology that exploits the information contained in a low-depth, whole-genome sequence to derive genotypic data useful for cross-platform (chip data) comparisons.

Metabolic and transcriptomic study of pennycress natural variation identifies targets for oil improvement

Pennycress (Thlaspi arvense L.), a member of the Brassicaceae family, produces seed oil high in erucic acid, suitable for biodiesel and aviation fuel. Although pennycress, a winter annual, could be grown as a dedicated bioenergy crop, an increase in its seed oil content is required to improve its economic competitiveness. The success of crop improvement relies upon finding the right combination of biomarkers and targets, and the best genetic engineering and/or breeding strategies. In this work, we combined biomass composition with metabolomic and transcriptomic studies of developing embryos from 22 pennycress natural variants to identify targets for oil improvement. The selected accession collection presented diverse levels of fatty acids at maturity ranging from 29% to 41%. Pearson correlation analyses, weighted gene co-expression network analysis and biomarker identifications were used as complementary approaches to detect associations between metabolite level or gene expression and oil content at maturity. The results indicated that improving seed oil content can lead to a concomitant increase in the proportion of erucic acid without affecting the weight of embryos. Processes, such as carbon partitioning towards the chloroplast, lipid metabolism, photosynthesis, and a tight control of nitrogen availability, were found to be key for oil improvement in pennycress. Besides identifying specific targets, our results also provide guidance regarding the best timing for their modification, early or middle maturation. Thus, this work lays out promising strategies, specific for pennycress, to accelerate the successful development of lines with increased seed oil content for biofuel applications.

Selection signatures and population dynamics of transposable elements in lima bean

The domestication process in lima bean (Phaseolus lunatus L.) involves two independent events, within the Mesoamerican and Andean gene pools. This makes lima bean an excellent model to understand convergent evolution. The mechanisms of adaptation followed by Mesoamerican and Andean landraces are largely unknown. Genes related to these adaptations can be selected by identification of selective sweeps within gene pools. Previous genetic analyses in lima bean have relied on Single Nucleotide Polymorphism (SNP) loci, and have ignored transposable elements (TEs). Here we show the analysis of whole-genome sequencing data from 61 lima bean accessions to characterize a genomic variation database including TEs and SNPs, to associate selective sweeps with variable TEs and to predict candidate domestication genes. A small percentage of genes under selection are shared among gene pools, suggesting that domestication followed different genetic avenues in both gene pools. About 75% of TEs are located close to genes, which shows their potential to affect gene functions. The genetic structure inferred from variable TEs is consistent with that obtained from SNP markers, suggesting that TE dynamics can be related to the demographic history of wild and domesticated lima bean and its adaptive processes, in particular selection processes during domestication.

Interspecific common bean population derived from Phaseolus acutifolius using a bridging genotype demonstrate useful adaptation to heat tolerance

Common bean (Phaseolus vulgaris L.) is an important legume crop worldwide and is a major nutrient source in the tropics. Common bean reproductive development is strongly affected by heat stress, particularly overnight temperatures above 20°C. The desert Tepary bean (Phaseolus acutifolius A. Gray) offers a promising source of adaptative genes due to its natural acclimation to arid conditions. Hybridization between both species is challenging, requiring in vitro embryo rescue and multiple backcrossing cycles to restore fertility. This labor-intensive process constrains developing mapping populations necessary for studying heat tolerance. Here we show the development of an interspecific mapping population using a novel technique based on a bridging genotype derived from P. vulgaris, P. Acutifolius and P. parvifolius named VAP1 and is compatible with both common and tepary bean. The population was based on two wild P. acutifolius accessions, repeatedly crossed with Mesoamerican elite common bush bean breeding lines. The population was genotyped through genotyping-by-sequencing and evaluated for heat tolerance by genome-wide association studies. We found that the population harbored 59.8% introgressions from wild tepary, but also genetic regions from Phaseolus parvifolius, a relative represented in some early bridging crosses. We found 27 significative quantitative trait loci, nine located inside tepary introgressed segments exhibiting allelic effects that reduced seed weight, and increased the number of empty pods, seeds per pod, stem production and yield under high temperature conditions. Our results demonstrate that the bridging genotype VAP1 can intercross common bean with tepary bean and positively influence the physiology of derived interspecific lines, which displayed useful variance for heat tolerance.

New algorithms for accurate and efficient de novo genome assembly from long DNA sequencing reads

Building de novo genome assemblies for complex genomes is possible thanks to long-read DNA sequencing technologies. However, maximizing the quality of assemblies based on long reads is a challenging task that requires the development of specialized data analysis techniques. We present new algorithms for assembling long DNA sequencing reads from haploid and diploid organisms. The assembly algorithm builds an undirected graph with two vertices for each read based on minimizers selected by a hash function derived from the k-mer distribution. Statistics collected during the graph construction are used as features to build layout paths by selecting edges, ranked by a likelihood function. For diploid samples, we integrated a reimplementation of the ReFHap algorithm to perform molecular phasing. We ran the implemented algorithms on PacBio HiFi and Nanopore sequencing data taken from haploid and diploid samples of different species. Our algorithms showed competitive accuracy and computational efficiency, compared with other currently used software. We expect that this new development will be useful for researchers building genome assemblies for different species.

Genetic analysis of resistance to bean leaf crumple virus identifies a candidate LRR-RLK gene

Bean leaf crumple virus (BLCrV) is a novel begomovirus (family Geminiviridae, genus Begomovirus) infecting common bean (Phaseolus vulgaris L.), threatening bean production in Latin America. Genetic resistance is required to ensure yield stability and reduce the use of insecticides, yet the available resistance sources are limited. In this study, three common bean populations containing a total of 558 genotypes were evaluated in different yield and BLCrV resistance trials under natural infection in the field. A genome-wide association study identified the locus BLC7.1 on chromosome Pv07 at 3.31 Mbp, explaining 8 to 16% of the phenotypic variation for BLCrV resistance. In comparison, whole-genome regression models explained 51 to 78% of the variation and identified the same region on Pv07 to confer resistance. The most significantly associated markers were located within the gene model Phvul.007G040400, which encodes a leucine-rich repeat receptor-like kinase subfamily III member and is likely to be involved in the innate immune response against the virus. The allelic diversity within this gene revealed five different haplotype groups, one of which was significantly associated with BLCrV resistance. As the same genome region was previously reported to be associated with resistance against other geminiviruses affecting common bean, our study highlights the role of previous breeding efforts for virus resistance in the accumulation of positive alleles against newly emerging viruses. In addition, we provide novel diagnostic single-nucleotide polymorphism markers for marker-assisted selection to exploit BLC7.1 for breeding against geminivirus diseases in one of the most important food crops worldwide.

Multiple domestication events explain the origin of Gossypium hirsutum landraces in Mexico

Several Mesoamerican crops constitute wild-to-domesticated complexes generated by multiple initial domestication events, and continuous gene flow among crop populations and between these populations and their wild relatives. It has been suggested that the domestication of cotton (Gossypium hirsutum) started in the northwest of the Yucatán Peninsula, from where it spread to other regions inside and outside of Mexico. We tested this hypothesis by assembling chloroplast genomes of 23 wild, landraces, and breeding lines (transgene-introgressed and conventional). The phylogenetic analysis showed that the evolutionary history of cotton in Mexico involves multiple events of introgression and genetic divergence. From this, we conclude that Mexican landraces arose from multiple wild populations. Our results also revealed that their structural and functional chloroplast organizations had been preserved. However, genetic diversity decreases as a consequence of domestication, mainly in transgene-introgressed (TI) individuals (π = 0.00020, 0.00001, 0.00016, 0, and 0, of wild, TI-wild, landraces, TI-landraces, and breeding lines, respectively). We identified homologous regions that differentiate wild from domesticated plants and indicate a relationship among the samples. A decrease in genetic diversity associated with transgene introgression in cotton was identified for the first time, and our outcomes are therefore relevant to both biosecurity and agrobiodiversity conservation.

xAtlas: scalable small variant calling across heterogeneous next-generation sequencing experiments

BACKGROUND

The growing volume and heterogeneity of next-generation sequencing (NGS) data complicate the further optimization of identifying DNA variation, especially considering that curated high-confidence variant call sets frequently used to validate these methods are generally developed from the analysis of comparatively small and homogeneous sample sets.

FINDINGS

We have developed xAtlas, a single-sample variant caller for single-nucleotide variants (SNVs) and small insertions and deletions (indels) in NGS data. xAtlas features rapid runtimes, support for CRAM and gVCF file formats, and retraining capabilities. xAtlas reports SNVs with 99.11% recall and 98.43% precision across a reference HG002 sample at 60× whole-genome coverage in less than 2 CPU hours. Applying xAtlas to 3,202 samples at 30× whole-genome coverage from the 1000 Genomes Project achieves an average runtime of 1.7 hours per sample and a clear separation of the individual populations in principal component analysis across called SNVs.

CONCLUSIONS

xAtlas is a fast, lightweight, and accurate SNV and small indel calling method. Source code for xAtlas is available under a BSD 3-clause license at https://github.com/jfarek/xatlas.

Large genomic introgression blocks of Phaseolus parvifolius Freytag bean into the common bean enhance the crossability between tepary and common beans

The production of the common bean (Phaseolus vulgaris L.), one of the most important sources of protein and minerals and one of the most consumed grain legumes globally, is highly affected by heat and drought constraints. In contrast, the tepary bean (Phaseolus acutifolius A. Gray), a common bean-related species, is adapted to hot and dry climates. Hybridization to introduce complex traits from the tepary bean into the common bean has been challenging, as embryo rescue is required. In this study, we report three novel interspecific lines that were obtained by crossing lines from prior common bean × tepary bean hybridization with Phaseolus parvifolius Freytag in order to increase the male gametic diversity to facilitate interspecific crosses. These interspecific lines enhanced the crossability of the common bean and tepary bean species while avoiding the embryo rescue process. Crossing these three interspecific lines with tepary beans resulted in 12-fold more hybrid plants than crossing traditional common beans with tepary beans. Whole-genome sequencing analysis of these three interspecific lines shows large introgressions of genomic regions corresponding to P. parvifolius on chromosomes that presumably contribute to reproductive barriers between both species. The development of these lines opens up the possibility of increasing the introgression of desirable tepary bean traits into the common bean to address constraints driven by climate change.

Genetic Determinants of Fiber-Associated Traits in Flax Identified by Omics Data Integration

In this paper, we explore potential genetic factors in control of flax phenotypes associated with fiber by mining a collection of 306 flax accessions from the Federal Research Centre of the Bast Fiber Crops, Torzhok, Russia. In total, 11 traits were assessed in the course of 3 successive years. A genome-wide association study was performed for each phenotype independently using six different single-locus models implemented in the GAPIT3 R package. Moreover, we applied a multivariate linear mixed model implemented in the GEMMA package to account for trait correlations and potential pleiotropic effects of polymorphisms. The analyses revealed a number of genomic variants associated with different fiber traits, implying the complex and polygenic control. All stable variants demonstrate a statistically significant allelic effect across all 3 years of the experiment. We tested the validity of the predicted variants using gene expression data available for the flax fiber studies. The results shed new light on the processes and pathways associated with the complex fiber traits, while the pinpointed candidate genes may be further used for marker-assisted selection.

Improving Association Studies and Genomic Predictions for Climbing Beans With Data From Bush Bean Populations

Common bean (Phaseolus vulgaris L.) has two major origins of domestication, Andean and Mesoamerican, which contribute to the high diversity of growth type, pod and seed characteristics. The climbing growth habit is associated with increased days to flowering (DF), seed iron concentration (SdFe), nitrogen fixation, and yield. However, breeding efforts in climbing beans have been limited and independent from bush type beans. To advance climbing bean breeding, we carried out genome-wide association studies and genomic predictions using 1,869 common bean lines belonging to five breeding panels representing both gene pools and all growth types. The phenotypic data were collected from 17 field trials and were complemented with 16 previously published trials. Overall, 38 significant marker-trait associations were identified for growth habit, 14 for DF, 13 for 100 seed weight, three for SdFe, and one for yield. Except for DF, the results suggest a common genetic basis for traits across all panels and growth types. Seven QTL associated with growth habits were confirmed from earlier studies and four plausible candidate genes for SdFe and 100 seed weight were newly identified. Furthermore, the genomic prediction accuracy for SdFe and yield in climbing beans improved up to 8.8% when bush-type bean lines were included in the training population. In conclusion, a large population from different gene pools and growth types across multiple breeding panels increased the power of genomic analyses and provides a solid and diverse germplasm base for genetic improvement of common bean.

Natural variation and improved genome annotation of the emerging biofuel crop field pennycress (Thlaspi arvense)

The Brassicaceae family comprises more than 3,700 species with a diversity of phenotypic characteristics, including seed oil content and composition. Recently, the global interest in Thlaspi arvense L. (pennycress) has grown as the seed oil composition makes it a suitable source for biodiesel and aviation fuel production. However, many wild traits of this species need to be domesticated to make pennycress ideal for cultivation. Molecular breeding and engineering efforts require the availability of an accurate genome sequence of the species. Here, we describe pennycress genome annotation improvements, using a combination of long- and short-read transcriptome data obtained from RNA derived from embryos of 22 accessions, in addition to public genome and gene expression information. Our analysis identified 27,213 protein-coding genes, as well as on average 6,188 biallelic SNPs. In addition, we used the identified SNPs to evaluate the population structure of our accessions. The data from this analysis support that the accession Ames 32872, originally from Armenia, is highly divergent from the other accessions, while the accessions originating from Canada and the United States cluster together. When we evaluated the likely signatures of natural selection from alternative SNPs, we found 7 candidate genes under likely recent positive selection. These genes are enriched with functions related to amino acid metabolism and lipid biosynthesis and highlight possible future targets for crop improvement efforts in pennycress.

Deciphering the Association among Pathogenicity, Production and Polymorphisms of Capsule/Melanin in Clinical Isolates of Cryptococcus neoformans var. grubii VNI

Background: Cryptococcus neoformans is an opportunistic fungal pathogen that can cause meningitis in immunocompromised individuals. The objective of this work was to study the relationship between the phenotypes and genotypes of isolates of clinical origin from different cities in Colombia. Methods: Genome classification of 29 clinical isolates of C. neoformans var. grubii was performed using multilocus sequence typing (MLST), and genomic sequencing was used to genotype protein-coding genes. Pathogenicity was assessed in a larval model, and melanin production and capsule size were evaluated in vitro and in vivo. Results: Eleven MLST sequence types (STs) were found, the most frequent being ST69 (n = 9), ST2, ST93, and ST377 (each with n = 4). In the 29 isolates, different levels of pigmentation, capsule size and pathogenicity were observed. Isolates classified as highly pathogenic showed a tendency to exhibit larger increases in capsule size. In the analysis of polymorphisms, 48 non-synonymous variants located in the predicted functional domains of 39 genes were found to be associated with capsule size change, melanin, or pathogenicity. Conclusions: No clear patterns were found in the analysis of the phenotype and genotype of Cryptococcus. However, the data suggest that the increase in capsule size is a key variable for the differentiation of pathogenic isolates, regardless of the method used for its induction.

Genetic Correlation Between Fe and Zn Biofortification and Yield Components in a Common Bean (Phaseolus vulgaris L.)

Common bean (Phaseolus vulgaris L.) is the most important legume for direct human consumption worldwide. It is a rich and relatively inexpensive source of proteins and micronutrients, especially iron and zinc. Bean is a target for biofortification to develop new cultivars with high Fe/Zn levels that help to ameliorate malnutrition mainly in developing countries. A strong negative phenotypic correlation between Fe/Zn concentration and yield is usually reported, posing a significant challenge for breeders. The objective of this study was to investigate the genetic relationship between Fe/Zn. We used Quantitative Trait Loci (QTLs) mapping and Genome-Wide Association Studies (GWAS) analysis in three bi-parental populations that included biofortified parents, identifying genomic regions associated with yield and micromineral accumulation. Significant negative correlations were observed between agronomic traits (pod harvest index, PHI; pod number, PdN; seed number, SdN; 100 seed weight, 100SdW; and seed per pod, Sd/Pd) and micronutrient concentration traits (SdFe and SdZn), especially between pod harvest index (PHI) and SdFe and SdZn. PHI presented a higher correlation with SdN than PdN. Seventy-nine QTLs were identified for the three populations: 14 for SdFe, 12 for SdZn, 13 for PHI, 11 for SdN, 14 for PdN, 6 for 100SdW, and 9 for Sd/Pd. Twenty-three hotspot regions were identified in which several QTLs were co-located, of which 13 hotpots displayed QTL of opposite effect for yield components and Fe/Zn accumulation. In contrast, eight QTLs for SdFe and six QTLs for SdZn were observed that segregated independently of QTL of yield components. The selection of these QTLs will enable enhanced levels of Fe/Zn and will not affect the yield performance of new cultivars focused on biofortification.

The Genetic Landscape of Fiber Flax

Genetic diversity in a breeding program is essential to overcome modern-day environmental challenges faced by humanity and produce robust, resilient crop cultivars with improved agronomic characteristics, as well as to trace crop domestication history. Flax (Linum usitatissimum), one of the first crops domesticated by mankind, has been traditionally cultivated for fiber as well as for medicinal purposes and as a nutritional product. The origins of fiber flax are hidden in the mists of time and can be hypothetically traced back to either the Indo-Afghan region or Fertile Crescent. To shed new light on fiber flax genetic diversity and breeding history, in this study, we presented a comprehensive analysis of the core collection of flax (306 accessions) of different morphotypes and geographic origins maintained by the Russian Federal Research Center for Bast Fiber Crops. We observed significant population differentiation between oilseed and fiber morphotypes, as well as mapped genomic regions affected by recent breeding efforts. We also sought to unravel the origins of kryazhs, Russian heritage landraces, and their genetic relatedness to modern fiber flax cultivars. For the first time, our results provide strong genetic evidence in favor of the hypothesis on kryazh's mixed origin from both the Indo-Afghan diversity center and Fertile Crescent. Finally, we showed predominant contribution from Russian landraces and kryazhs into the ancestry of modern fiber flax varieties. Taken together, these findings may have practical implications on the development of new improved flax varieties with desirable traits that give farmers greater choice in crop management and meet the aspirations of breeders.

Genomic Regions Associated with Fusarium Wilt Resistance in Flax

Modern flax cultivars are susceptible to many diseases; arguably, the most economically damaging of these is the Fusarium wilt fungal disease. Over the past decades international flax breeding initiatives resulted in the development of resistant cultivars. However, much remains to be learned about the mechanisms of resistance to Fusarium infection in flax. As a first step to uncover the genetic factors associated with resistance to Fusarium wilt disease, we performed a genome-wide association study (GWAS) using 297 accessions from the collection of the Federal Research Centre of the Bast Fiber Crops, Torzhok, Russia. These genotypes were infected with a highly pathogenic Fusarium oxysporum f.sp. lini MI39 strain; the wilt symptoms were documented in the course of three successive years. Six different single-locus models implemented in GAPIT3 R package were applied to a selected subset of 72,526 SNPs. A total of 15 QTNs (Quantitative Trait Nucleotides) were detected during at least two years of observation, while eight QTNs were found during all three years of the experiment. Of these, ten QTNs occupied a region of 640 Kb at the start of chromosome 1, while the remaining QTNs mapped to chromosomes 8, 11 and 13. All stable QTNs demonstrate a statistically significant allelic effect across 3 years of the experiment. Importantly, several QTNs spanned regions that harbored genes involved in the pathogen recognition and plant immunity response, including the KIP1-like protein (Lus10025717) and NBS-LRR protein (Lus10025852). Our results provide novel insights into the genetic architecture of flax resistance to Fusarium wilt and pinpoint potential candidate genes for further in-depth studies.

A whole genome duplication drives the genome evolution of Phytophthora betacei, a closely related species to Phytophthora infestans

BACKGROUND

Pathogens of the genus Phytophthora are the etiological agents of many devastating diseases in several high-value crops and forestry species such as potato, tomato, cocoa, and oak, among many others. Phytophthora betacei is a recently described species that causes late blight almost exclusively in tree tomatoes, and it is closely related to Phytophthora infestans that causes the disease in potato crops and other Solanaceae. This study reports the assembly and annotation of the genomes of P. betacei P8084, the first of its species, and P. infestans RC1-10, a Colombian strain from the EC-1 lineage, using long-read SMRT sequencing technology.

RESULTS

Our results show that P. betacei has the largest sequenced genome size of the Phytophthora genus so far with 270 Mb. A moderate transposable element invasion and a whole genome duplication likely explain its genome size expansion when compared to P. infestans, whereas P. infestans RC1-10 has expanded its genome under the activity of transposable elements. The high diversity and abundance (in terms of copy number) of classified and unclassified transposable elements in P. infestans RC1-10 relative to P. betacei bears testimony of the power of long-read technologies to discover novel repetitive elements in the genomes of organisms. Our data also provides support for the phylogenetic placement of P. betacei as a standalone species and as a sister group of P. infestans. Finally, we found no evidence to support the idea that the genome of P. betacei P8084 follows the same gene-dense/gense-sparse architecture proposed for P. infestans and other filamentous plant pathogens.

CONCLUSIONS

This study provides the first genome-wide picture of P. betacei and expands the genomic resources available for P. infestans. This is a contribution towards the understanding of the genome biology and evolutionary history of Phytophthora species belonging to the subclade 1c.

Phylogenomic analysis and Mycobacterium tuberculosis antibiotic resistance prediction by whole-genome sequencing from clinical isolates of Caldas, Colombia

Mycobacterium tuberculosis (M. tuberculosis) was the pathogen responsible for the highest number of deaths from infectious diseases in the world, before the arrival of the COVID-19 pandemic. Whole genome sequencing (WGS) has contributed to the understanding of genetic diversity, the mechanisms involved in drug resistance and the transmission dynamics of this pathogen. The object of this study is to use WGS for the epidemiological and molecular characterization of M. tuberculosis clinical strains from Chinchiná, Caldas, a small town in Colombia with a high incidence of TB. Sputum samples were obtained during the first semester of 2020 from six patients and cultured in solid Löwenstein-Jensen medium. DNA extraction was obtained from positive culture samples and WGS was performed with the Illumina HiSeq 2500 platform for subsequent bioinformatic analysis. M. tuberculosis isolates were typified as Euro-American lineage 4 with a predominance of the Harlem and LAM sublineages. All samples were proven sensitive to antituberculosis drugs by genomic analysis, although no phenotype antimicrobial tests were performed on the samples, unreported mutations were identified that could require further analysis. The present study provides preliminary data for the construction of a genomic database line and the follow-up of lineages in this region.

Understanding the metabolome and metagenome as extended phenotypes: The next frontier in macroalgae domestication and improvement

"Omics" techniques (including genomics, transcriptomics, metabolomics, proteomics, and metagenomics) have been employed with huge success in the improvement of agricultural crops. As marine aquaculture of macroalgae expands globally, biologists are working to domesticate species of macroalgae by applying these techniques tested in agriculture to wild macroalgae species. Metabolomics has revealed metabolites and pathways that influence agriculturally relevant traits in crops, allowing for informed crop crossing schemes and genomic improvement strategies that would be pivotal to inform selection on macroalgae for domestication. Advances in metagenomics have improved understanding of host-symbiont interactions and the potential for microbial organisms to improve crop outcomes. There is much room in the field of macroalgal biology for further research toward improvement of macroalgae cultivars in aquaculture using metabolomic and metagenomic analyses. To this end, this review discusses the application and necessary expansion of the omics tool kit for macroalgae domestication as we move to enhance seaweed farming worldwide.

Robust and efficient software for reference-free genomic diversity analysis of genotyping-by-sequencing data on diploid and polyploid species

Genotyping-by-sequencing (GBS) is a widely used and cost-effective technique for obtaining large numbers of genetic markers from populations by sequencing regions adjacent to restriction cut sites. Although a standard reference-based pipeline can be followed to analyse GBS reads, a reference genome is still not available for a large number of species. Hence, reference-free approaches are required to generate the genetic variability information that can be obtained from a GBS experiment. Unfortunately, available tools to perform de novo analysis of GBS reads face issues of usability, accuracy and performance. Furthermore, few available tools are suitable for analysing data sets from polyploid species. In this manuscript, we describe a novel algorithm to perform reference-free variant detection and genotyping from GBS reads. Nonexact searches on a dynamic hash table of consensus sequences allow for efficient read clustering and sorting. This algorithm was integrated in the Next Generation Sequencing Experience Platform (NGSEP) to integrate the state-of-the-art variant detector already implemented in this tool. We performed benchmark experiments with three different empirical data sets of plants and animals with different population structures and ploidies, and sequenced with different GBS protocols at different read depths. These experiments show that NGSEP has comparable and in some cases better accuracy and always better computational efficiency compared to existing solutions. We expect that this new development will be useful for many research groups conducting population genetic studies in a wide variety of species.

MultiGWAS: An integrative tool for Genome Wide Association Studies in tetraploid organisms

The genome-wide association studies (GWASs) are essential to determine the genetic bases of either ecological or economic phenotypic variation across individuals within populations of the model and nonmodel organisms. For this research question, the GWAS replication testing different parameters and models to validate the results' reproducibility is common. However, straightforward methodologies that manage both replication and tetraploid data are still missing. To solve this problem, we designed the MultiGWAS, a tool that does GWAS for diploid and tetraploid organisms by executing in parallel four software packages, two designed for polyploid data (GWASpoly and SHEsis) and two designed for diploid data (GAPIT and TASSEL). MultiGWAS has several advantages. It runs either in the command line or in a graphical interface; it manages different genotype formats, including VCF. Moreover, it allows control for population structure, relatedness, and several quality control checks on genotype data. Besides, MultiGWAS can test for additive and dominant gene action models, and, through a proprietary scoring function, select the best model to report its associations. Finally, it generates several reports that facilitate identifying false associations from both the significant and the best-ranked association Single Nucleotide Polymorphisms (SNPs) among the four software packages. We tested MultiGWAS with public tetraploid potato data for tuber shape and several simulated data under both additive and dominant models. These tests demonstrated that MultiGWAS is better at detecting reliable associations than using each of the four software packages individually. Moreover, the parallel analysis of polyploid and diploid software that only offers MultiGWAS demonstrates its utility in understanding the best genetic model behind the SNP association in tetraploid organisms. Therefore, MultiGWAS probed to be an excellent alternative for wrapping GWAS replication in diploid and tetraploid organisms in a single analysis environment.

Using RNA-seq to characterize pollen-stigma interactions for pollination studies

Insects are essential for the reproduction of pollinator-dependent crops and contribute to the pollination of 87% of wild plants and 75% of the world’s food crops. Understanding pollen flow dynamics between plants and pollinators is thus essential to manage and conserve wild plants and ensure yields are maximized in food crops. However, the determination of pollen transfer in the field is complex and laborious. We developed a field experiment in a pollinator-dependent crop and used high throughput RNA sequencing (RNA-seq) to quantify pollen flow by measuring changes in gene expression between pollination treatments across different apple (Malus domestica Borkh.) cultivars. We tested three potential molecular indicators of successful pollination and validated these results with field data by observing single and multiple visits by honey bees (Apis mellifera) to apple flowers and measured fruit set in a commercial apple orchard. The first indicator of successful outcrossing was revealed via differential gene expression in the cross-pollination treatments after 6 h. The second indicator of successful outcrossing was revealed by the expression of specific genes related to pollen tube formation and defense response at three different time intervals in the stigma and the style following cross-pollination (i.e. after 6, 24, and 48 h). Finally, genotyping variants specific to donor pollen could be detected in cross-pollination treatments, providing a third indicator of successful outcrossing. Field data indicated that one or five flower visits by honey bees were insufficient and at least 10 honey bee flower visits were required to achieve a 25% probability of fruit set under orchard conditions. By combining the genotyping data, the differential expression analysis, and the traditional fruit set field experiments, it was possible to evaluate the pollination effectiveness of honey bee visits under orchards conditions. This is the first time that pollen-stigma-style mRNA expression analysis has been conducted after a pollinator visit (honey bee) to a plant (in vivo apple flowers). This study provides evidence that mRNA sequencing can be used to address complex questions related to stigma–pollen interactions over time in pollination ecology.

Genetic Analyses and Genomic Predictions of Root Rot Resistance in Common Bean Across Trials and Populations

Root rot in common bean is a disease that causes serious damage to grain production, particularly in the upland areas of Eastern and Central Africa where significant losses occur in susceptible bean varieties. Pythium spp. and Fusarium spp. are among the soil pathogens causing the disease. In this study, a panel of 228 lines, named RR for root rot disease, was developed and evaluated in the greenhouse for Pythium myriotylum and in a root rot naturally infected field trial for plant vigor, number of plants germinated, and seed weight. The results showed positive and significant correlations between greenhouse and field evaluations, as well as high heritability (0.71-0.94) of evaluated traits. In GWAS analysis no consistent significant marker trait associations for root rot disease traits were observed, indicating the absence of major resistance genes. However, genomic prediction accuracy was found to be high for Pythium, plant vigor and related traits. In addition, good predictions of field phenotypes were obtained using the greenhouse derived data as a training population and vice versa. Genomic predictions were evaluated across and within further published data sets on root rots in other panels. Pythium and Fusarium evaluations carried out in Uganda on the Andean Diversity Panel showed good predictive ability for the root rot response in the RR panel. Genomic prediction is shown to be a promising method to estimate tolerance to Pythium, Fusarium and root rot related traits, indicating a quantitative resistance mechanism. Quantitative analyses could be applied to other disease-related traits to capture more genetic diversity with genetic models.

A Genomic Blueprint of Flax Fungal Parasite Fusarium oxysporum f. sp. lini

Fusarium wilt of flax is an aggressive disease caused by the soil-borne fungal pathogen Fusarium oxysporum f. sp. lini. It is a challenging pathogen presenting a constant threat to flax production industry worldwide. Previously, we reported chromosome-level assemblies of 5 highly pathogenic F. oxysporum f. sp. lini strains. We sought to characterize the genomic architecture of the fungus and outline evolutionary mechanisms shaping the pathogen genome. Here, we reveal the complex multi-compartmentalized genome organization and uncover its diverse evolutionary dynamics, which boosts genetic diversity and facilitates host adaptation. In addition, our results suggest that host of functions implicated in the life cycle of mobile genetic elements are main contributors to dissimilarity between proteomes of different Fusaria. Finally, our experiments demonstrate that mobile genetics elements are expressed in planta upon infection, alluding to their role in pathogenicity. On the whole, these results pave the way for further in-depth studies of evolutionary forces shaping the host–pathogen interaction.

Comprehensive genomic resources related to domestication and crop improvement traits in Lima bean

Lima bean (Phaseolus lunatus L.), one of the five domesticated Phaseolus bean crops, shows a wide range of ecological adaptations along its distribution range from Mexico to Argentina. These adaptations make it a promising crop for improving food security under predicted scenarios of climate change in Latin America and elsewhere. In this work, we combine long and short read sequencing technologies with a dense genetic map from a biparental population to obtain the chromosome-level genome assembly for Lima bean. Annotation of 28,326 gene models show high diversity among 1917 genes with conserved domains related to disease resistance. Structural comparison across 22,180 orthologs with common bean reveals high genome synteny and five large intrachromosomal rearrangements. Population genomic analyses show that wild Lima bean is organized into six clusters with mostly non-overlapping distributions and that Mesomerican landraces can be further subdivided into three subclusters. RNA-seq data reveal 4275 differentially expressed genes, which can be related to pod dehiscence and seed development. We expect the resources presented here to serve as a solid basis to achieve a comprehensive view of the degree of convergent evolution of Phaseolus species under domestication and provide tools and information for breeding for climate change resiliency.

Niche specificity influences gene flow across fine-scale habitat mosaics in Succulent Karoo plants

While the tempo of diversification in biodiversity hotspots has received much attention, the spatial scale of diversification has often been overlooked. Addressing this deficiency requires understanding the drivers of population divergence and the spatial scales at which they operate in species-rich clades and ecosystems. South Africa's Succulent Karoo (SK) hotspot provides an excellent system for such research, being both compact (ca. 110,000 km² ) and home to spectacular in-situ radiations, such as the ruschioid Aizoaceae. Here we use GBS to document genetic structure in two co-occurring ruschioid species, at both coarse (>10 km) and fine (<500 m) spatial scales. Where Ruschia burtoniae shows strong between-population genetic differentiation and no gene flow, Conophytum calculus shows weak differentiation, with high levels of admixture suggesting recent or ongoing gene flow. Community analysis and transplant experiments reveal that R. burtoniae occupies a narrow, low-pH edaphic niche, and at scales of a few hundred metres, areas of elevated genetic turnover correspond to patches of edaphically unsuitable habitat. In contrast, C. calculus occupies a broader niche and exhibits isolation-by-distance without a habitat effect. We suggest that edaphic specialisation, coupled with highly restricted seed and pollen dispersal in heterogeneous landscapes, has played a major role in driving rapid diversification at small spatial scales in this system. However, the contrasting patterns in our study species show that these factors do not influence all organisms uniformly, being strongly modulated by lineage-specific traits that influence both the spatial scale of gene flow and habitat specificity.

Using single-plant-omics in the field to link maize genes to functions and phenotypes

Most of our current knowledge on plant molecular biology is based on experiments in controlled laboratory environments. However, translating this knowledge from the laboratory to the field is often not straightforward, in part because field growth conditions are very different from laboratory conditions. Here, we test a new experimental design to unravel the molecular wiring of plants and study gene-phenotype relationships directly in the field. We molecularly profiled a set of individual maize plants of the same inbred background grown in the same field and used the resulting data to predict the phenotypes of individual plants and the function of maize genes. We show that the field transcriptomes of individual plants contain as much information on maize gene function as traditional laboratory-generated transcriptomes of pooled plant samples subject to controlled perturbations. Moreover, we show that field-generated transcriptome and metabolome data can be used to quantitatively predict individual plant phenotypes. Our results show that profiling individual plants in the field is a promising experimental design that could help narrow the lab-field gap.

Genetic mapping for agronomic traits in a MAGIC population of common bean (Phaseolus vulgaris L.) under drought conditions

BACKGROUND

Common bean is an important staple crop in the tropics of Africa, Asia and the Americas. Particularly smallholder farmers rely on bean as a source for calories, protein and micronutrients. Drought is a major production constraint for common bean, a situation that will be aggravated with current climate change scenarios. In this context, new tools designed to understand the genetic basis governing the phenotypic responses to abiotic stress are required to improve transfer of desirable traits into cultivated beans.

RESULTS

A multiparent advanced generation intercross (MAGIC) population of common bean was generated from eight Mesoamerican breeding lines representing the phenotypic and genotypic diversity of the CIAT Mesoamerican breeding program. This population was assessed under drought conditions in two field trials for yield, 100 seed weight, iron and zinc accumulation, phenology and pod harvest index. Transgressive segregation was observed for most of these traits. Yield was positively correlated with yield components and pod harvest index (PHI), and negative correlations were found with phenology traits and micromineral contents. Founder haplotypes in the population were identified using Genotyping by Sequencing (GBS). No major population structure was observed in the population. Whole Genome Sequencing (WGS) data from the founder lines was used to impute genotyping data for GWAS. Genetic mapping was carried out with two methods, using association mapping with GWAS, and linkage mapping with haplotype-based interval screening. Thirteen high confidence QTL were identified using both methods and several QTL hotspots were found controlling multiple traits. A major QTL hotspot located on chromosome Pv01 for phenology traits and yield was identified. Further hotspots affecting several traits were observed on chromosomes Pv03 and Pv08. A major QTL for seed Fe content was contributed by MIB778, the founder line with highest micromineral accumulation. Based on imputed WGS data, candidate genes are reported for the identified major QTL, and sequence changes were identified that could cause the phenotypic variation.

CONCLUSIONS

This work demonstrates the importance of this common bean MAGIC population for genetic mapping of agronomic traits, to identify trait associations for molecular breeding tool design and as a new genetic resource for the bean research community.

Genomic Variability of Phytophthora palmivora Isolates from Different Oil Palm Cultivation Regions in Colombia

Palm oil is the most consumed vegetable oil globally, and Colombia is the largest palm oil producer in South America and fourth worldwide. However, oil palm plantations in Colombia are affected by bud rot disease caused by the oomycete Phytophthora palmivora, leading to significant economic losses. Infection processes by plant pathogens involve the secretion of effector molecules, which alter the functioning or structure of host cells. Current long-read sequencing technologies provide the information needed to produce high-quality genome assemblies, enabling a comprehensive annotation of effectors. Here, we describe the development of genomic resources for P. palmivora, including a high-quality genome assembly based on long and short-read sequencing data, intraspecies variability for 12 isolates from different oil palm cultivation regions in Colombia, and a catalog of over 1,000 candidate effector proteins. A total of 45,416 genes were annotated from the new genome assembled in 2,322 contigs adding to 165.5 Mbp, which represents an improvement of two times more gene models, 33 times better contiguity, and 11 times less fragmentation compared with currently available genomic resources for the species. Analysis of nucleotide evolution in paralogs suggests a recent whole-genome duplication event. Genetic differences were identified among isolates showing variable virulence levels. We expect that these novel genomic resources contribute to the characterization of the species and the understanding of the interaction of P. palmivora with oil palm and could be further exploited as tools for the development of effective strategies for disease control.

Genomic Prediction of Agronomic Traits in Common Bean (Phaseolus vulgaris L.) Under Environmental Stress

In plant and animal breeding, genomic prediction models are established to select new lines based on genomic data, without the need for laborious phenotyping. Prediction models can be trained on recent or historic phenotypic data and increasingly available genotypic data. This enables the adoption of genomic selection also in under-used legume crops such as common bean. Beans are an important staple food in the tropics and mainly grown by smallholders under limiting environmental conditions such as drought or low soil fertility. Therefore, genotype-by-environment interactions (G × E) are an important consideration when developing new bean varieties. However, G × E are often not considered in genomic prediction models nor are these models implemented in current bean breeding programs. Here we show the prediction abilities of four agronomic traits in common bean under various environmental stresses based on twelve field trials. The dataset includes 481 elite breeding lines characterized by 5,820 SNP markers. Prediction abilities over all twelve trials ranged between 0.6 and 0.8 for yield and days to maturity, respectively, predicting new lines into new seasons. In all four evaluated traits, the prediction abilities reached about 50-80% of the maximum accuracies given by phenotypic correlations and heritability. Predictions under drought and low phosphorus stress were up to 10 and 20% improved when G × E were included in the model, respectively. Our results demonstrate the potential of genomic selection to increase the genetic gain in common bean breeding. Prediction abilities improved when more phenotypic data was available and G × E could be accounted for. Furthermore, the developed models allowed us to predict genotypic performance under different environmental stresses. This will be a key factor in the development of common bean varieties adapted to future challenging conditions.

Genetic Architecture and Genomic Prediction of Cooking Time in Common Bean (Phaseolus vulgaris L.)

Cooking time of the common bean is an important trait for consumer preference, with implications for nutrition, health, and environment. For efficient germplasm improvement, breeders need more information on the genetics to identify fast cooking sources with good agronomic properties and molecular breeding tools. In this study, we investigated a broad genetic variation among tropical germplasm from both Andean and Mesoamerican genepools. Four populations were evaluated for cooking time (CKT), water absorption capacity (WAC), and seed weight (SdW): a bi-parental RIL population (DxG), an eight-parental Mesoamerican MAGIC population, an Andean (VEF), and a Mesoamerican (MIP) breeding line panel. A total of 922 lines were evaluated in this study. Significant genetic variation was found in all populations with high heritabilities, ranging from 0.64 to 0.89 for CKT. CKT was related to the color of the seed coat, with the white colored seeds being the ones that cooked the fastest. Marker trait associations were investigated by QTL analysis and GWAS, resulting in the identification of 10 QTL. In populations with Andean germplasm, an inverse correlation of CKT and WAC, and also a QTL on Pv03 that inversely controls CKT and WAC (CKT3.2/WAC3.1) were observed. WAC7.1 was found in both Mesoamerican populations. QTL only explained a small part of the variance, and phenotypic distributions support a more quantitative mode of inheritance. For this reason, we evaluated how genomic prediction (GP) models can capture the genetic variation. GP accuracies for CKT varied, ranging from good results for the MAGIC population (0.55) to lower accuracies in the MIP panel (0.22). The phenotypic characterization of parental material will allow for the cooking time trait to be implemented in the active germplasm improvement programs. Molecular breeding tools can be developed to employ marker-assisted selection or genomic selection, which looks to be a promising tool in some populations to increase the efficiency of breeding activities.