Marker-based estimation of heritability in immortal populations

Dissecting the genetic basis of resistance to Soil-borne cereal mosaic virus (SBCMV) in durum wheat by bi-parental mapping and GWAS

Soil-borne cereal mosaic virus (SBCMV), the causative agent of wheat mosaic, is a Furovirus challenging wheat production all over Europe. Differently from bread wheat, durum wheat shows greater susceptibility and stronger yield penalties, so identification and genetic characterization of resistance sources are major targets for durum genetics and breeding. The Sbm1 locus providing high level of resistance to SBCMV was mapped in bread wheat to the 5DL chromosome arm (Bass in Genome 49:1140-1148, 2006). This excluded the direct use of Sbm1 for durum wheat improvement. Only one major QTL has been mapped in durum wheat, namely QSbm.ubo-2B, on the 2BS chromosome region coincident with Sbm2, already known in bread wheat as reported (Bayles in HGCA Project Report, 2007). Therefore, QSbm.ubo-2B = Sbm2 is considered a pillar for growing durum in SBCMV-affected areas. Herein, we report the fine mapping of Sbm2 based on bi-parental mapping and GWAS, using the Infinium 90 K SNP array and high-throughput KASP®. Fine mapping pointed out a critical haploblock of 3.2 Mb defined by concatenated SNPs successfully converted to high-throughput KASP® markers coded as KUBO. The combination of KUBO-27, wPt-2106-ASO/HRM, KUBO-29, and KUBO-1 allows unequivocal tracing of the Sbm2-resistant haplotype. The interval harbors 52 high- and 41 low-confidence genes, encoding 17 cytochrome p450, three receptor kinases, two defensins, and three NBS-LRR genes. These results pave the way for Sbm2 positional cloning. Importantly, the development of Sbm2 haplotype tagging KASP® provides a valuable case study for improving efficacy of the European variety testing system and, ultimately, the decision-making process related to varietal characterization and choice.

Genotyping-by-sequencing-based high-resolution mapping reveals a single candidate gene for the grapevine veraison locus Ver1

Veraison marks the transition from berry growth to berry ripening and is a crucial phenological stage in grapevine (Vitis vinifera): the berries become soft and begin to accumulate sugars, aromatic substances, and, in red cultivars, anthocyanins for pigmentation, while the organic acid levels begin to decrease. These changes determine the potential quality of wine. However, rising global temperatures lead to earlier flowering and ripening, which strongly influence wine quality. Here, we combined genotyping-by-sequencing with a bioinformatics pipeline on ∼150 F1 genotypes derived from a cross between the early ripening variety "Calardis Musqué" and the late-ripening variety "Villard Blanc". Starting from 20,410 haplotype-based markers, we generated a high-density genetic map and performed a quantitative trait locus analysis based on phenotypic datasets evaluated over 20 yrs. Through locus-specific marker enrichment and recombinant screening of ∼1,000 additional genotypes, we refined the originally postulated 5-mb veraison locus, Ver1, on chromosome 16 to only 112 kb, allowing us to pinpoint the ethylene response factor VviERF027 (VCost.v3 gene ID: Vitvi16g00942, CRIBIv1 gene ID: VIT_16s0100g00400) as veraison candidate gene. Furthermore, the early veraison allele could be traced back to a clonal "Pinot" variant first mentioned in the seventeenth century. "Pinot Precoce Noir" passed this allele over "Madeleine Royale" to the maternal grandparent "Bacchus Weiss" and, ultimately, to the maternal parent "Calardis Musqué". Our findings are crucial for ripening time control, thereby improving wine quality, and for breeding grapevines adjusted to climate change scenarios that have a major impact on agro-ecosystems in altering crop plant phenology.

Systems genetic analysis of lignin biosynthesis in Populus tremula

The genetic control underlying natural variation in lignin content and composition in trees is not fully understood. We performed a systems genetic analysis to uncover the genetic regulation of lignin biosynthesis in a natural 'SwAsp' population of aspen (Populus tremula) trees. We analyzed gene expression by RNA sequencing (RNA-seq) in differentiating xylem tissues, and lignin content and composition using Pyrolysis-GC-MS in mature wood of 268 trees from 99 genotypes. Abundant variation was observed for lignin content and composition, and genome-wide association study identified proteins in the pentose phosphate pathway and arabinogalactan protein glycosylation among the top-ranked genes that are associated with these traits. Variation in gene expression and the associated genetic polymorphism was revealed through the identification of 312 705 local and 292 003 distant expression quantitative trait loci (eQTL). A co-expression network analysis suggested modularization of lignin biosynthesis and novel functions for the lignin-biosynthetic CINNAMYL ALCOHOL DEHYDROGENASE 2 and CAFFEOYL-CoA O-METHYLTRANSFERASE 3. PHENYLALANINE AMMONIA LYASE 3 was co-expressed with HOMEOBOX PROTEIN 5 (HB5), and the role of HB5 in stimulating lignification was demonstrated in transgenic trees. The systems genetic approach allowed linking natural variation in lignin biosynthesis to trees´ responses to external cues such as mechanical stimulus and nutrient availability.

Improving wheat grain composition for human health by constructing a QTL atlas for essential minerals

Wheat is an important source of minerals for human nutrition and increasing grain mineral content can contribute to reducing mineral deficiencies. Here, we identify QTLs for mineral micronutrients in grain of wheat by determining the contents of six minerals in a total of eleven sample sets of three biparental populations from crosses between A.E. Watkins landraces and cv. Paragon. Twenty-three of the QTLs are mapped in two or more sample sets, with LOD scores above five in at least one set with the increasing alleles for sixteen of the QTLs being present in the landraces and seven in Paragon. Of these QTLs, the number for each mineral varies between three and five and they are located on 14 of the 21 chromosomes, with clusters on chromosomes 5A (four), 6A (three), and 7A (three). The gene content within 5 megabases of DNA on either side of the marker for the QTL with the highest LOD score is determined and the gene responsible for the strongest QTL (chromosome 5A for Ca) identified as an ATPase transporter gene (TraesCS5A02G543300) using mutagenesis. The identification of these QTLs, together with associated SNP markers and candidate genes, will facilitate the improvement of grain nutritional quality.

Linking genetic markers and crop model parameters using neural networks to enhance genomic prediction of integrative traits

Introduction

Predicting the performance (yield or other integrative traits) of cultivated plants is complex because it involves not only estimating the genetic value of the candidates to selection, the interactions between the genotype and the environment (GxE) but also the epistatic interactions between genomic regions for a given trait, and the interactions between the traits contributing to the integrative trait. Classical Genomic Prediction (GP) models mostly account for additive effects and are not suitable to estimate non-additive effects such as epistasis. Therefore, the use of machine learning and deep learning methods has been previously proposed to model those non-linear effects.

Methods

In this study, we propose a type of Artificial Neural Network (ANN) called Convolutional Neural Network (CNN) and compare it to two classical GP regression methods for their ability to predict an integrative trait of sorghum: aboveground fresh weight accumulation. We also suggest that the use of a crop growth model (CGM) can enhance predictions of integrative traits by decomposing them into more heritable intermediate traits.

Results

The results show that CNN outperformed both LASSO and Bayes C methods in accuracy, suggesting that CNN are better suited to predict integrative traits. Furthermore, the predictive ability of the combined CGM-GP approach surpassed that of GP without the CGM integration, irrespective of the regression method used.

Discussion

These results are consistent with recent works aiming to develop Genome-to-Phenotype models and advocate for the use of non-linear prediction methods, and the use of combined CGM-GP to enhance the prediction of crop performances.

Integrating GWAS with a gene co-expression network better prioritizes candidate genes associated with root metaxylem phenes in maize

Root metaxylems are phenotypically diverse structures whose function is particularly important under drought stress. Significant research has dissected the genetic machinery underlying metaxylem phenotypes in dicots, but that of monocots are relatively underexplored. In maize (Zea mays), a robust pipeline integrated a genome-wide association study (GWAS) of root metaxylem phenes under well-watered and water-stress conditions with a gene co-expression network to prioritize the strongest gene candidates. We identified 244 candidate genes by GWAS, of which 103 reside in gene co-expression modules most relevant to xylem development. Several candidate genes may be involved in biosynthetic processes related to the cell wall, hormone signaling, oxidative stress responses, and drought responses. Of those, six gene candidates were detected in multiple root metaxylem phenes in both well-watered and water-stress conditions. We posit that candidate genes that are more essential to network function based on gene co-expression (i.e., hubs or bottlenecks) should be prioritized and classify 33 essential genes for further investigation. Our study demonstrates a new strategy for identifying promising gene candidates and presents several gene candidates that may enhance our understanding of vascular development and responses to drought in cereals.

Mapping of flumioxazin tolerance in a snap bean diversity panel leads to the discovery of a master genomic region controlling multiple stress resistance genes

Introduction

Effective weed management tools are crucial for maintaining the profitable production of snap bean (Phaseolus vulgaris L.). Preemergence herbicides help the crop to gain a size advantage over the weeds, but the few preemergence herbicides registered in snap bean have poor waterhemp (Amaranthus tuberculatus) control, a major pest in snap bean production. Waterhemp and other difficult-to-control weeds can be managed by flumioxazin, an herbicide that inhibits protoporphyrinogen oxidase (PPO). However, there is limited knowledge about crop tolerance to this herbicide. We aimed to quantify the degree of snap bean tolerance to flumioxazin and explore the underlying mechanisms.

Methods

We investigated the genetic basis of herbicide tolerance using genome-wide association mapping approach utilizing field-collected data from a snap bean diversity panel, combined with gene expression data of cultivars with contrasting response. The response to a preemergence application of flumioxazin was measured by assessing plant population density and shoot biomass variables.

Results

Snap bean tolerance to flumioxazin is associated with a single genomic location in chromosome 02. Tolerance is influenced by several factors, including those that are indirectly affected by seed size/weight and those that directly impact the herbicide's metabolism and protect the cell from reactive oxygen species-induced damage. Transcriptional profiling and co-expression network analysis identified biological pathways likely involved in flumioxazin tolerance, including oxidoreductase processes and programmed cell death. Transcriptional regulation of genes involved in those processes is possibly orchestrated by a transcription factor located in the region identified in the GWAS analysis. Several entries belonging to the Romano class, including Bush Romano 350, Roma II, and Romano Purpiat presented high levels of tolerance in this study. The alleles identified in the diversity panel that condition snap bean tolerance to flumioxazin shed light on a novel mechanism of herbicide tolerance and can be used in crop improvement.

Fatty Acids in Dry Beans (Phaseolus vulgaris L.): A Contribution to Their Analysis and the Characterization of a Diversity Panel

Dry bean (Phaseolus vulgaris L.) is a crop of high nutritional interest widespread throughout the world. This research had two objectives. On the one hand, the development and validation of an analytical method to quantify fatty acids in dry beans based on the extraction and derivatization in a single step and later quantification by gas chromatography. On the other, its application to characterize the fatty acid content in a diversity panel consisting of 172 lines. The method was successfully validated in terms of accuracy, precision and robustness. Among the 14 fatty acids that constitute the fatty acid profile of dry bean, the most quantitatively important were linolenic acid, the major fatty acid in all cases, with an average value of 6.7 mg/g, followed by linoleic acid (3.9 mg/g), palmitic acid (2.9 mg/g) and oleic acid (1.5 mg/g). The concentrations of fatty acids in dry bean were influenced by the gene pool, with the Mesoamerican gene pool showing a higher content of palmitic, stearic, linoleic and linolenic acids and the Andean gene pool a higher level of cis-vaccenic acid. Also, the expression of fatty acid content showed high heritability. The information generated constitutes a robust database of interest in food technology, nutrition and breeding programs.

The genomic basis of nitrogen utilization efficiency and trait plasticity to improve nutrient stress tolerance in cultivated sunflower

Maintaining crop productivity is challenging as population growth, climate change, and increasing fertilizer costs necessitate expanding crop production to poorer lands whilst reducing inputs. Enhancing crops' nutrient use efficiency is thus an important goal, but requires a better understanding of related traits and their genetic basis. We investigated variation in low nutrient stress tolerance in a diverse panel of cultivated sunflower genotypes grown under high and low nutrient conditions, assessing relative growth rate (RGR) as performance. We assessed variation in traits related to nitrogen utilization efficiency (NUtE), mass allocation, and leaf elemental content. Across genotypes, nutrient limitation generally reduced RGR. Moreover, there was a negative correlation between vigor (RGR in control) and decline in RGR in response to stress. Given this trade-off, we focused on nutrient stress tolerance independent of vigor. This tolerance metric correlated with the change in NUtE, plasticity for a suite of morphological traits, and leaf element content. Genome-wide associations revealed regions associated with variation and plasticity in multiple traits, including two regions with seemingly additive effects on NUtE change. Our results demonstrate potential avenues for improving sunflower nutrient stress tolerance independent of vigor, and highlight specific traits and genomic regions that could play a role in enhancing tolerance.

Characterization of adaptation mechanisms in sorghum using a multireference back-cross nested association mapping design and envirotyping

Identifying the genetic factors impacting the adaptation of crops to environmental conditions is of key interest for conservation and selection purposes. It can be achieved using population genomics, and evolutionary or quantitative genetics. Here we present a sorghum multireference back-cross nested association mapping population composed of 3,901 lines produced by crossing 24 diverse parents to 3 elite parents from West and Central Africa-back-cross nested association mapping. The population was phenotyped in environments characterized by differences in photoperiod, rainfall pattern, temperature levels, and soil fertility. To integrate the multiparental and multi-environmental dimension of our data we proposed a new approach for quantitative trait loci (QTL) detection and parental effect estimation. We extended our model to estimate QTL effect sensitivity to environmental covariates, which facilitated the integration of envirotyping data. Our models allowed spatial projections of the QTL effects in agro-ecologies of interest. We utilized this strategy to analyze the genetic architecture of flowering time and plant height, which represents key adaptation mechanisms in environments like West Africa. Our results allowed a better characterization of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod-sensitive and the region of possible candidate gene Elf3 being photoperiod-insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology-dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the West and Central Africa-back-cross nested association mapping and the presented analytical approach constitute unique resources to better understand adaptation in sorghum with direct application to develop climate-smart varieties.

Genome-wide association analysis reveals genes controlling an antagonistic effect of biotic and osmotic stress on Arabidopsis thaliana growth

While the response of Arabidopsis thaliana to drought, herbivory or fungal infection has been well-examined, the consequences of exposure to a series of such (a)biotic stresses are not well studied. This work reports on the genetic mechanisms underlying the Arabidopsis response to single osmotic stress, and to combinatorial stress, either fungal infection using Botrytis cinerea or herbivory using Pieris rapae caterpillars followed by an osmotic stress treatment. Several small-effect genetic loci associated with rosette dry weight (DW), rosette water content (WC), and the projected rosette leaf area in response to combinatorial stress were mapped using univariate and multi-environment genome-wide association approaches. A single-nucleotide polymorphism (SNP) associated with DROUGHT-INDUCED 19 (DI19) was identified by both approaches, supporting its potential involvement in the response to combinatorial stress. Several SNPs were found to be in linkage disequilibrium with known stress-responsive genes such as PEROXIDASE 34 (PRX34), BASIC LEUCINE ZIPPER 25 (bZIP25), RESISTANCE METHYLATED GENE 1 (RMG1) and WHITE RUST RESISTANCE 4 (WRR4). An antagonistic effect between biotic and osmotic stress was found for prx34 and arf4 mutants, which suggests PRX34 and ARF4 play an important role in the response to the combinatorial stress.

Genome-Wide Association Studies Prioritize Genes Controlling Seed Size and Reproductive Period Length in Soybean

Hundred-seed weight (HSW) and reproductive period length (RPL) are two major agronomic traits critical for soybean production and adaptation. However, both traits are quantitatively controlled by multiple genes that have yet to be comprehensively elucidated due to the lack of major genes; thereby, the genetic basis is largely unknown. In the present study, we conducted comprehensive genome-wide association analyses (GWAS) of HSW and RPL with multiple sets of accessions that were phenotyped across different environments. The large-scale analysis led to the identification of sixty-one and seventy-four significant QTLs for HSW and RPL, respectively. An ortholog-based search analysis prioritized the most promising candidate genes for the QTLs, including nine genes (TTG2, BZR1, BRI1, ANT, KLU, EOD1/BB, GPA1, ABA2, and ABI5) for HSW QTLs and nine genes (such as AGL8, AGL9, TOC1, and COL4) and six known soybean flowering time genes (E2, E3, E4, Tof11, Tof12, and FT2b) for RPL QTLs. We also demonstrated that some QTLs were targeted during domestication to drive the artificial selection of both traits towards human-favored traits. Local adaptation likely contributes to the increased genomic diversity of the QTLs underlying RPL. The results provide additional insight into the genetic basis of HSW and RPL and prioritize a valuable resource of candidate genes that merits further investigation to reveal the complex molecular mechanism and facilitate soybean improvement.

Genetic control of pod morphological traits and pod edibility in a common bean RIL population

KEY MESSAGE

QTL mapping, association analysis, and colocation study with previously reported QTL revealed three main regions controlling pod morphological traits and two loci for edible pod characteristics on the common bean chromosomes Pv01 and Pv06. Bean pod phenotype is a complex characteristic defined by the combination of different traits that determine the potential use of a genotype as a snap bean. In this study, the TUM RIL population derived from a cross between 'TU' (dry) and 'Musica' (snap) was used to investigate the genetic control of pod phenotype. The character was dissected into pod morphological traits (PMTs) and edible pod characteristics (EPC). The results revealed 35 QTL for PMTs located on seven chromosomes, suggesting a strong QTL colocation on chromosomes Pv01 and Pv06. Some QTL were colocated with previously reported QTL, leading to the mapping of 15 consensus regions associated with bean PMTs. Analysis of EPC of cooked beans revealed that two major loci with epistatic effect, located on chromosomes Pv01 and Pv06, are involved in the genetic control of this trait. An association study using a subset of the Spanish Diversity Panel (snap vs. non-snap) detected 23 genomic regions, with three regions being mapped at a position similar to those of two loci identified in the TUM population. The results demonstrated the relevant roles of Pv01 and Pv06 in the modulation of bean pod phenotype. Gene ontology enrichment analysis revealed a significant overrepresentation of genes regulating the phenylpropanoid metabolic process and auxin response in regions associated with PMTs and EPC, respectively. Both biological functions converged in the lignin biosynthetic pathway, suggesting the key role of the pathway in the genetic control of bean pod phenotype.

Metabolome plasticity in 241 Arabidopsis thaliana accessions reveals evolutionary cold adaptation processes

Acclimation and adaptation of metabolism to a changing environment are key processes for plant survival and reproductive success. In the present study, 241 natural accessions of Arabidopsis (Arabidopsis thaliana) were grown under two different temperature regimes, 16 °C and 6 °C, and growth parameters were recorded, together with metabolite profiles, to investigate the natural genome × environment effects on metabolome variation. The plasticity of metabolism, which was captured by metabolic distance measures, varied considerably between accessions. Both relative growth rates and metabolic distances were predictable by the underlying natural genetic variation of accessions. Applying machine learning methods, climatic variables of the original growth habitats were tested for their predictive power of natural metabolic variation among accessions. We found specifically habitat temperature during the first quarter of the year to be the best predictor of the plasticity of primary metabolism, indicating habitat temperature as the causal driver of evolutionary cold adaptation processes. Analyses of epigenome- and genome-wide associations revealed accession-specific differential DNA-methylation levels as potentially linked to the metabolome and identified FUMARASE2 as strongly associated with cold adaptation in Arabidopsis accessions. These findings were supported by calculations of the biochemical Jacobian matrix based on variance and covariance of metabolomics data, which revealed that growth under low temperatures most substantially affects the accession-specific plasticity of fumarate and sugar metabolism. Our findings indicate that the plasticity of metabolic regulation is predictable from the genome and epigenome and driven evolutionarily by Arabidopsis growth habitats.

Genetic Mapping of Genotype-by-Ploidy Effects in Arabidopsis thaliana

Plants can express different phenotypic responses following polyploidization, but ploidy-dependent phenotypic variation has so far not been assigned to specific genetic factors. To map such effects, segregating populations at different ploidy levels are required. The availability of an efficient haploid inducer line in Arabidopsis thaliana allows for the rapid development of large populations of segregating haploid offspring. Because Arabidopsis haploids can be self-fertilised to give rise to homozygous doubled haploids, the same genotypes can be phenotyped at both the haploid and diploid ploidy level. Here, we compared the phenotypes of recombinant haploid and diploid offspring derived from a cross between two late flowering accessions to map genotype × ploidy (G × P) interactions. Ploidy-specific quantitative trait loci (QTLs) were detected at both ploidy levels. This implies that mapping power will increase when phenotypic measurements of monoploids are included in QTL analyses. A multi-trait analysis further revealed pleiotropic effects for a number of the ploidy-specific QTLs as well as opposite effects at different ploidy levels for general QTLs. Taken together, we provide evidence of genetic variation between different Arabidopsis accessions being causal for dissimilarities in phenotypic responses to altered ploidy levels, revealing a G × P effect. Additionally, by investigating a population derived from late flowering accessions, we revealed a major vernalisation-specific QTL for variation in flowering time, countering the historical bias of research in early flowering accessions.

Genetic Mapping of the Root Mycobiota in Rice and its Role in Drought Tolerance

BACKGROUND

Rice is the second most produced crop worldwide, but is highly susceptible to drought. Micro-organisms can potentially alleviate the effects of drought. The aim of the present study was to unravel the genetic factors involved in the rice-microbe interaction, and whether genetics play a role in rice drought tolerance. For this purpose, the composition of the root mycobiota was characterized in 296 rice accessions (Oryza sativa L. subsp. indica) under control and drought conditions. Genome wide association mapping (GWAS) resulted in the identification of ten significant (LOD > 4) single nucleotide polymorphisms (SNPs) associated with six root-associated fungi: Ceratosphaeria spp., Cladosporium spp., Boudiera spp., Chaetomium spp., and with a few fungi from the Rhizophydiales order. Four SNPs associated with fungi-mediated drought tolerance were also found. Genes located around those SNPs, such as a DEFENSIN-LIKE (DEFL) protein, EXOCYST TETHERING COMPLEX (EXO70), RAPID ALKALINIZATION FACTOR-LIKE (RALFL) protein, peroxidase and xylosyltransferase, have been shown to be involved in pathogen defense, abiotic stress responses and cell wall remodeling processes. Our study shows that rice genetics affects the recruitment of fungi, and that some fungi affect yield under drought. We identified candidate target genes for breeding to improve rice-fungal interactions and hence drought tolerance.

Genome-wide association study reveals WRKY42 as a novel plant transcription factor that influences oviposition preference of Pieris butterflies

Insect herbivores are amongst the most destructive plant pests, damaging both naturally occurring and domesticated plants. As sessile organisms, plants make use of structural and chemical barriers to counteract herbivores. However, over 75% of herbivorous insect species are well adapted to their host's defenses and these specialists are generally difficult to ward off. By actively antagonizing the number of insect eggs deposited on plants, future damage by the herbivore's offspring can be limited. Therefore, it is important to understand which plant traits influence attractiveness for oviposition, especially for specialist insects that are well adapted to their host plants. In this study, we investigated the oviposition preference of Pieris butterflies (Lepidoptera: Pieridae) by offering them the choice between 350 different naturally occurring Arabidopsis accessions. Using a genome-wide association study of the oviposition data and subsequent fine mapping with full genome sequences of 164 accessions, we identified WRKY42 and AOC1 as candidate genes that are associated with the oviposition preference observed for Pieris butterflies. Host plant choice assays with Arabidopsis genotypes impaired in WRKY42 or AOC1 function confirmed a clear role for WRKY42 in oviposition preference of female Pieris butterflies, while for AOC1 the effect was mild. In contrast, WRKY42-impaired plants, which were preferred for oviposition by butterflies, negatively impacted offspring performance. These findings exemplify that plant genotype can have opposite effects on oviposition preference and caterpillar performance. This knowledge can be used for breeding trap crops or crops that are unattractive for oviposition by pest insects.

Unraveling the genetics underlying micronutrient signatures of diversity panel present in brown rice through genome-ionome linkages

Rice (Oryza sativa) is an important staple crop to address the Hidden Hunger problem not only in Asia but also in Africa where rice is fast becoming an important source of calories. The brown rice (whole grain with bran) is known to be more nutritious due to elevated mineral composition. The genetics underlying brown rice ionome (sum total of such mineral composition) remains largely unexplored. Hence, we conducted a comprehensive study to dissect the genetic architecture of the brown rice ionome. We used genome-wide association studies, gene set analysis, and targeted association analysis for 12 micronutrients in the brown rice grains. A diverse panel of 300 resequenced indica accessions, with more than 1.02 million single nucleotide polymorphisms, was used. We identified 109 candidate genes with 5-20% phenotypic variation explained for the 12 micronutrients and identified epistatic interactions with multiple micronutrients. Pooling all candidate genes per micronutrient exhibited phenotypic variation explained values ranging from 11% to almost 40%. The key donor lines with larger concentrations for most of the micronutrients possessed superior alleles, which were absent in the breeding lines. Through gene regulatory networks we identified enriched functional pathways for central regulators that were detected as key candidate genes through genome-wide association studies. This study provided important insights on the ionome variations in rice, on the genetic basis of the genome-ionome relationships and on the molecular mechanisms underlying micronutrient signatures.

Genomic heritability and correlation between carcass traits in Japanese Black cattle evaluated under different ceilings of relatedness among individuals

The investigation of carcass traits to produce meat with high efficiency has been in focus on Japanese Black cattle since 1972. To implement a successful breeding program in carcass production, a comprehensive understanding of genetic characteristics and relationships between the traits is of paramount importance. In this study, genomic heritability and genomic correlation between carcass traits, including carcass weight (CW), rib eye area (REA), rib thickness (RT), subcutaneous fat thickness (SFT), yield rate (YI), and beef marbling score (BMS) were estimated using the genomic data of 9,850 Japanese Black cattle (4,142 heifers and 5,708 steers). In addition, we investigated the effect of genetic relatedness degree on the estimation of genetic parameters of carcass traits in sub-populations created based on different GRM-cutoff values. Genome-based restricted maximum likelihood (GREML) analysis was applied to estimate genetic parameters. Using all animal data, the heritability values for carcass traits were estimated as moderate to relatively high magnitude, ranging from 0.338 to 0.509 with standard errors, ranging from 0.014 to 0.015. The genetic correlations were obtained low and negative between SFT and REA [-0.198 (0.034)] and between SFT and BMS [-0.096 (0.033)] traits, and high and negative between SFT and YI [-0.634 (0.022)]. REA trait was genetically highly correlated with YI and BMS [0.811 (0.012) and 0.625 (0.022), respectively]. In sub-populations created based on the genetic-relatedness ceiling, the heritability estimates ranged from 0.212 (0.131) to 0.647 (0.066). At the genetic-relatedness ceiling of 0.15, the correlation values between most traits with low genomic correlation were overestimated while the correlations between the traits with relatively moderate to high correlations, ranging from 0.380 to 0.811, were underestimated. The values were steady at the ceilings of 0.30-0.95 (sample size of 5,443-9,850) for most of the highly correlated traits. The results demonstrated that there is considerable genetic variation and also favorable genomic correlations between carcass traits. Therefore, the genetic improvement for the traits can be simultaneously attained through genomic selection. In addition, we observed that depending on the degree of relationship between individuals and sample size, the genomic heritability and correlation estimates for carcass traits may be different.

Novel candidate loci for morpho-agronomic and seed quality traits detected by targeted genotyping-by-sequencing in common bean

Phaseolus vulgaris L., known as common bean, is one of the most important grain legumes cultivated around the world for its immature pods and dry seeds, which are rich in protein and micronutrients. Common bean offers a cheap food and protein sources to ameliorate food shortage and malnutrition around the world. However, the genetic basis of most important traits in common bean remains unknown. This study aimed at identifying QTL and candidate gene models underlying twenty-six agronomically important traits in common bean. For this, we assembled and phenotyped a diversity panel of 200 P. vulgaris genotypes in the greenhouse, comprising determinate bushy, determinate climbing and indeterminate climbing beans. The panel included dry beans and snap beans from different breeding programmes, elite lines and landraces from around the world with a major focus on accessions of African, European and South American origin. The panel was genotyped using a cost-conscious targeted genotyping-by-sequencing (GBS) platform to take advantage of highly polymorphic SNPs detected in previous studies and in diverse germplasm. The detected single nucleotide polymorphisms (SNPs) were applied in marker-trait analysis and revealed sixty-two quantitative trait loci (QTL) significantly associated with sixteen traits. Gene model identification via a similarity-based approach implicated major candidate gene models underlying the QTL associated with ten traits including, flowering, yield, seed quality, pod and seed characteristics. Our study revealed six QTL for pod shattering including three new QTL potentially useful for breeding. However, the panel was evaluated in a single greenhouse environment and the findings should be corroborated by evaluations across different field environments. Some of the detected QTL and a number of candidate gene models only elucidate the understanding of the genetic nature of these traits and provide the basis for further studies. Finally, the study showed the possibility of using a limited number of SNPs in performing marker-trait association in common bean by applying a highly scalable targeted GBS approach. This targeted GBS approach is a cost-efficient strategy for assessment of the genetic basis of complex traits and can enable geneticists and breeders to identify novel loci and targets for marker-assisted breeding more efficiently.

Natural variation in root suberization is associated with local environment in Arabidopsis thaliana

Genetic signature of climate adaptation has been widely recognized across the genome of many organisms; however, the eco-physiological basis for linking genomic polymorphisms with local adaptations remains largely unexplored. Using a panel of 218 world-wide Arabidopsis accessions, we characterized the natural variation in root suberization by quantifying 16 suberin monomers. We explored the associations between suberization traits and 126 climate variables. We conducted genome-wide association analysis and integrated previous genotype-environment association (GEA) to identify the genetic bases underlying suberization variation and their involvements in climate adaptation. Root suberin content displays extensive variation across Arabidopsis populations and significantly correlates with local moisture gradients and soil characteristics. Specifically, enhanced suberization is associated with drier environments, higher soil cation-exchange capacity, and lower soil pH; higher proportional levels of very-long-chain suberin is negatively correlated with moisture availability, lower soil gravel content, and higher soil silt fraction. We identified 94 putative causal loci and experimentally proved that GPAT6 is involved in C16 suberin biosynthesis. Highly significant associations between the putative genes and environmental variables were observed. Roots appear highly responsive to environmental heterogeneity via regulation of suberization, especially the suberin composition. The patterns of suberization-environment correlation and the suberin-related GEA fit the expectations of local adaptation for the polygenic suberization trait.

Genomic regions associate with major axes of variation driven by gas exchange and leaf construction traits in cultivated sunflower (Helianthus annuus L.)

Stomata and leaf veins play an essential role in transpiration and the movement of water throughout leaves. These traits are thus thought to play a key role in the adaptation of plants to drought and a better understanding of the genetic basis of their variation and coordination could inform efforts to improve drought tolerance. Here, we explore patterns of variation and covariation in leaf anatomical traits and analyze their genetic architecture via genome-wide association (GWA) analyses in cultivated sunflower (Helianthus annuus L.). Traits related to stomatal density and morphology as well as lower-order veins were manually measured from digital images while the density of minor veins was estimated using a novel deep learning approach. Leaf, stomatal, and vein traits exhibited numerous significant correlations that generally followed expectations based on functional relationships. Correlated suites of traits could further be separated along three major principal component (PC) axes that were heavily influenced by variation in traits related to gas exchange, leaf hydraulics, and leaf construction. While there was limited evidence of colocalization when individual traits were subjected to GWA analyses, major multivariate PC axes that were most strongly influenced by several traits related to gas exchange or leaf construction did exhibit significant genomic associations. These results provide insight into the genetic basis of leaf trait covariation and showcase potential targets for future efforts aimed at modifying leaf anatomical traits in sunflower.

Chromosome 3A harbors several pleiotropic and stable drought-responsive alleles for photosynthetic efficiency selected through wheat breeding

Water deficit is the most severe stress factor in crop production threatening global food security. In this study, we evaluated the genetic variation in photosynthetic traits among 200 wheat cultivars evaluated under drought and rainfed conditions. Significant genotypic, treatments, and their interaction effects were detected for chlorophyll content and chlorophyll fluorescence parameters. Drought stress reduced the effective quantum yield of photosystem II (YII) from the anthesis growth stage on. Leaf chlorophyll content measured at anthesis growth stages was significantly correlated with YII and non-photochemical quenching under drought conditions, suggesting that high throughput chlorophyll content screening can serve as a good indicator of plant drought tolerance status in wheat. Breeding significantly increased the photosynthetic efficiency as newer released genotypes had higher YII and chlorophyll content than the older ones. GWAS identified a stable drought-responsive QTL on chromosome 3A for YII, while under rainfed conditions, it detected another QTL on chromosome 7A for chlorophyll content across both growing seasons. Molecular analysis revealed that the associated alleles of AX-158576783 (515.889 Mbp) on 3A co-segregates with the NADH-ubiquinone oxidoreductase (TraesCS3A02G287600) gene involved in ATP synthesis coupled electron transport and is proximal to WKRY transcription factor locus. This allele on 3A has been positively selected through breeding and has contributed to increasing the grain yield.

Genetic architecture of fusarium head blight disease resistance and associated traits in Nordic spring wheat

This study identified a significant number of QTL that are associated with FHB disease resistance in NMBU spring wheat panel by conducting genome-wide association study. Fusarium head blight (FHB) is a widely known devastating disease of wheat caused by Fusarium graminearum and other Fusarium species. FHB resistance is quantitative, highly complex and divided into several resistance types. Quantitative trait loci (QTL) that are effective against several of the resistance types give valuable contributions to resistance breeding. A spring wheat panel of 300 cultivars and breeding lines of Nordic and exotic origins was tested in artificially inoculated field trials and subjected to visual FHB assessment in the years 2013-2015, 2019 and 2020. Deoxynivalenol (DON) content was measured on harvested grain samples, and anther extrusion (AE) was assessed in separate trials. Principal component analysis based on 35 and 25 K SNP arrays revealed the existence of two subgroups, dividing the panel into European and exotic lines. We employed a genome-wide association study to detect QTL associated with FHB traits and identify marker-trait associations that consistently influenced FHB resistance. A total of thirteen QTL were identified showing consistent effects across FHB resistance traits and environments. Haplotype analysis revealed a highly significant QTL on 7A, Qfhb.nmbu.7A.2, which was further validated on an independent set of breeding lines. Breeder-friendly KASP markers were developed for this QTL that can be used in marker-assisted selection. The lines in the wheat panel harbored from zero to five resistance alleles, and allele stacking showed that resistance can be significantly increased by combining several of these resistance alleles. This information enhances breeders´ possibilities for genomic prediction and to breed cultivars with improved FHB resistance.

Genetic basis of the lobedness degree in tomato fruit morphology

Fruit shape is a key trait in tomato (Solanum lycopersicum L.). Since most studies focused on proximo-distal fruit morphology, we hypothesized that unknown QTLs for medio-lateral direction ones could be found analysing segregating populations where major shape genes are fixed. We examined the diversity of fruit morphology in medio-lateral direction; defined divergent traits in cultivars carrying identical genetic constitution at LC and FAS genes; and identified QTLs for lobedness degree (LD) by a QTL-seq approach. We found that LC and FAS genes were not enough to explain LD variability in a large tomato collection. Then, we derived F₂ populations crossing cultivars divergent for LD where LC and FAS were fixed (Yellow Stuffer x Heinz 1439 [F₂YSxH] and Voyage x Old Brooks [F₂VxOB]). By QTL-seq we identified a QTL for LD on chromosome 8 in both F₂, which was validated in F₂YSxH by interval mapping accounting for ~ 17% of the variability. Other two QTLs located on chromosomes 6 and 11 with epistasis explained ~ 61% of the variability in the F₂VxOB. In conclusion, three novel QTLs with major effect for LD (ld6, ld8, and ld11) were identified through the study of diversity and genetic segregation in intraspecific tomato crosses.

Dissecting the Genetic Architecture of Carbon Partitioning in Sorghum Using Multiscale Phenotypes

Carbon partitioning in plants may be viewed as a dynamic process composed of the many interactions between sources and sinks. The accumulation and distribution of fixed carbon is not dictated simply by the sink strength and number but is dependent upon the source, pathways, and interactions of the system. As such, the study of carbon partitioning through perturbations to the system or through focus on individual traits may fail to produce actionable developments or a comprehensive understanding of the mechanisms underlying this complex process. Using the recently published sorghum carbon-partitioning panel, we collected both macroscale phenotypic characteristics such as plant height, above-ground biomass, and dry weight along with microscale compositional traits to deconvolute the carbon-partitioning pathways in this multipurpose crop. Multivariate analyses of traits resulted in the identification of numerous loci associated with several distinct carbon-partitioning traits, which putatively regulate sugar content, manganese homeostasis, and nitrate transportation. Using a multivariate adaptive shrinkage approach, we identified several loci associated with multiple traits suggesting that pleiotropic and/or interactive effects may positively influence multiple carbon-partitioning traits, or these overlaps may represent molecular switches mediating basal carbon allocating or partitioning networks. Conversely, we also identify a carbon tradeoff where reduced lignin content is associated with increased sugar content. The results presented here support previous studies demonstrating the convoluted nature of carbon partitioning in sorghum and emphasize the importance of taking a holistic approach to the study of carbon partitioning by utilizing multiscale phenotypes.

The genetic architecture underlying body-size traits plasticity over different temperatures and developmental stages in Caenorhabditis elegans

Most ectotherms obey the temperature-size rule, meaning they grow larger in a colder environment. This raises the question of how the interplay between genes and temperature affects the body size of ectotherms. Despite the growing body of literature on the physiological life-history and molecular genetic mechanism underlying the temperature-size rule, the overall genetic architecture orchestrating this complex phenotype is not yet fully understood. One approach to identify genetic regulators of complex phenotypes is quantitative trait locus (QTL) mapping. Here, we explore the genetic architecture of body-size phenotypes, and plasticity of body-size phenotypes at different temperatures using Caenorhabditis elegans as a model ectotherm. We used 40 recombinant inbred lines (RILs) derived from N2 and CB4856, which were reared at four different temperatures (16, 20, 24, and 26 °C) and measured at two developmental stages (L4 and adult). The animals were measured for body length, width at vulva, body volume, length/width ratio, and seven other body-size traits. The genetically diverse RILs varied in their body-size phenotypes with heritabilities ranging from 0.0 to 0.99. We detected 18 QTL underlying the body-size traits across all treatment combinations, with the majority clustering on Chromosome X. We hypothesize that the Chromosome X QTL could result from a known pleiotropic regulator-npr-1-known to affect the body size of C. elegans through behavioral changes. We also found five plasticity QTL of body-size traits where three colocalized with body-size QTL. In conclusion, our findings shed more light on multiple loci affecting body-size plasticity and the possibility of co-regulation of traits and traits plasticity by the same loci under different environments.

Disaggregation of Ploidy, Gender, and Genotype Effects on Wood and Fiber Traits in a Diploid and Triploid Hybrid Poplar Family

Triploid breeding based on unilateral sexual polyploidization is an effective approach for genetic improvement of Populus, which can integrate heterosis and ploidy vigor in an elite variety. However, the phenotypic divergence of unselected allotriploids with the same cross-combination remains poorly understood, and the contributions of ploidy, gender, and genotype effects on phenotypic variation are still unclear. In this study, wood and fiber traits, including basic density (BD), lignin content (LC), fiber length (FL), fiber width (FW), and fiber length/width (FL/W), were measured based on a 10-year-old clonal trial, including full-sib diploid and triploid hybrids of (Populus pseudo-simonii × P. nigra 'Zheyin3#') × P. × beijingensis, and contributions of ploidy, gender, and genotype effects on the variation of these traits, were disaggregated to enhance our understanding of triploid breeding. We found a significant phenotypic variation for all measured traits among genotypes. All the wood and fiber traits studied here underwent strong clonal responses with high repeatabilities (0.55-0.76). The Pearson's correlation analyses based on the best linear unbiased predictors (BLUPs) revealed that BD was significantly positively correlated with FL (r = 0.65, p = 0.030), suggesting that BD could be improved together with FL during triploid breeding. The FL of the triploids was significantly larger than that of the diploids (p < 0.001), suggesting that ploidy strongly affected the variation of FL traits. The difference between females and males was not significant for any measured trait, implying that gender might not be a major factor for variation in these traits. Further analyses of variance components showed that genotype dominantly contributed to the variation of BD, LC, and FW traits (with 54, 62, and 53% contributions, respectively) and ploidy contributed strongly to variation in FL and FL/W (77 and 50%, respectively). The genetic coefficient of variation (CVG) of triploids for each trait was low, suggesting that it is necessary to produce many triploids for selection or to use different Populus species as parents. Our findings provide new insights into the genetic effects of ploidy, gender, and genotype on wood and fiber traits within a full-sib poplar family, enhancing the understanding of the triploid breeding program of Populus.

Genome-Wide Association Study Reveals Marker Trait Associations (MTA) for Waterlogging-Triggered Adventitious Roots and Aerenchyma Formation in Barley

Waterlogging is an environmental stress, which severely affects barley growth and development. Limited availability of oxygen in the root zone negatively affects the metabolism of the whole plant. Adventitious roots (AR) and root cortical aerenchyma (RCA) formation are the most important adaptive traits that contribute to a plant's ability to survive in waterlogged soil conditions. This study used a genome-wide association (GWAS) approach using 18,132 single nucleotide polymorphisms (SNPs) in a panel of 697 barley genotypes to reveal marker trait associations (MTA) conferring the above adaptive traits. Experiments were conducted over two consecutive years in tanks filled with soil and then validated in field experiments. GWAS analysis was conducted using general linear models (GLM), mixed linear models (MLM), and fixed and random model circulating probability unification models (FarmCPU model), with the FarmCPU showing to be the best suited model. Six and five significant (approximately -log₁₀ (p) ≥ 5.5) MTA were identified for AR and RCA formation under waterlogged conditions, respectively. The highest -log₁₀ (p) MTA for adventitious root and aerenchyma formation were approximately 9 and 8 on chromosome 2H and 4H, respectively. The combination of different MTA showed to be more effective in forming RCA and producing more AR under waterlogging stress. Genes from major facilitator superfamily (MFS) transporter and leucine-rich repeat (LRR) families for AR formation, and ethylene responsive factor (ERF) family genes and potassium transporter family genes for RCA formation were the potential candidate genes involved under waterlogging conditions. Several genotypes, which performed consistently well under different conditions, can be used in breeding programs to develop waterlogging-tolerant varieties.

Genomic prediction models for traits differing in heritability for soybean, rice, and maize

BACKGROUND

Genomic selection is a powerful tool in plant breeding. By building a prediction model using a training set with markers and phenotypes, genomic estimated breeding values (GEBVs) can be used as predictions of breeding values in a target set with only genotype data. There is, however, limited information on how prediction accuracy of genomic prediction can be optimized. The objective of this study was to evaluate the performance of 11 genomic prediction models across species in terms of prediction accuracy for two traits with different heritabilities using several subsets of markers and training population proportions. Species studied were maize (Zea mays, L.), soybean (Glycine max, L.), and rice (Oryza sativa, L.), which vary in linkage disequilibrium (LD) decay rates and have contrasting genetic architectures.

RESULTS

Correlations between observed and predicted GEBVs were determined via cross validation for three training-to-testing proportions (90:10, 70:30, and 50:50). Maize, which has the shortest extent of LD, showed the highest prediction accuracy. Amongst all the models tested, Bayes B performed better than or equal to all other models for each trait in all the three crops. Traits with higher broad-sense and narrow-sense heritabilities were associated with higher prediction accuracy. When subsets of markers were selected based on LD, the accuracy was similar to that observed from the complete set of markers. However, prediction accuracies were significantly improved when using a subset of total markers that were significant at P ≤ 0.05 or P ≤ 0.10. As expected, exclusion of QTL-associated markers in the model reduced prediction accuracy. Prediction accuracy varied among different training population proportions.

CONCLUSIONS

We conclude that prediction accuracy for genomic selection can be improved by using the Bayes B model with a subset of significant markers and by selecting the training population based on narrow sense heritability.

Estimating heritability using family-pooled phenotypic and genotypic data: a simulation study applied to aquaculture

Estimating heritability based on individual phenotypic and genotypic measurements can be expensive and labour-intensive in commercial aquaculture breeding. Here, the feasibility of estimating heritability using within-family means of phenotypes and allelic frequencies was investigated. Different numbers of full-sib families and family sizes across ten generations with phenotypic and genotypic information on 10 K SNPs were analysed in ten replicates. Three scenarios, representing differing numbers of pools per family (one, two and five) were considered. The results showed that using one pool per family did not reliably estimate the heritability of family means. Using simulation parameters appropriate for aquaculture, at least 200 families of 60 progeny per family divided equally in two pools per family was required to estimate the heritability of family means effectively. Although application of five pools generated more within- and between- family relationships, it reduced the number of individuals per pool and increased within-family residual variation, hence, decreased the heritability of family means. Moreover, increasing the size of pools resulted in increasing the heritability of family means towards one. In addition, heritability of family mean estimates were higher than family heritabilities obtained from Falconer’s formula due to lower intraclass correlation estimate compared to the coefficient of relationship.

Genomic Selection for Wheat Blast in a Diversity Panel, Breeding Panel and Full-Sibs Panel

Wheat blast is an emerging threat to wheat production, due to its recent migration to South Asia and Sub-Saharan Africa. Because genomic selection (GS) has emerged as a promising breeding strategy, the key objective of this study was to evaluate it for wheat blast phenotyped at precision phenotyping platforms in Quirusillas (Bolivia), Okinawa (Bolivia) and Jashore (Bangladesh) using three panels: (i) a diversity panel comprising 172 diverse spring wheat genotypes, (ii) a breeding panel comprising 248 elite breeding lines, and (iii) a full-sibs panel comprising 298 full-sibs. We evaluated two genomic prediction models (the genomic best linear unbiased prediction or GBLUP model and the Bayes B model) and compared the genomic prediction accuracies with accuracies from a fixed effects model (with selected blast-associated markers as fixed effects), a GBLUP + fixed effects model and a pedigree relationships-based model (ABLUP). On average, across all the panels and environments analyzed, the GBLUP + fixed effects model (0.63 ± 0.13) and the fixed effects model (0.62 ± 0.13) gave the highest prediction accuracies, followed by the Bayes B (0.59 ± 0.11), GBLUP (0.55 ± 0.1), and ABLUP (0.48 ± 0.06) models. The high prediction accuracies from the fixed effects model resulted from the markers tagging the 2NS translocation that had a large effect on blast in all the panels. This implies that in environments where the 2NS translocation-based blast resistance is effective, genotyping one to few markers tagging the translocation is sufficient to predict the blast response and genome-wide markers may not be needed. We also observed that marker-assisted selection (MAS) based on a few blast-associated markers outperformed GS as it selected the highest mean percentage (88.5%) of lines also selected by phenotypic selection and discarded the highest mean percentage of lines (91.8%) also discarded by phenotypic selection, across all panels. In conclusion, while this study demonstrates that MAS might be a powerful strategy to select for the 2NS translocation-based blast resistance, we emphasize that further efforts to use genomic tools to identify non-2NS translocation-based blast resistance are critical.

Genetic control of arbuscular mycorrhizal colonization by Rhizophagus intraradices in Helianthus annuus (L.)

Plant symbiosis with arbuscular mycorrhizal (AM) fungi provides many benefits, including increased nutrient uptake, drought tolerance, and belowground pathogen resistance. To develop a better understanding of the genetic architecture of mycorrhizal symbiosis, we conducted a genome-wide association study (GWAS) of this plant-fungal interaction in cultivated sunflower. A diversity panel of cultivated sunflower (Helianthus annuus L.) was phenotyped for root colonization under inoculation with the AM fungus Rhizophagus intraradices. Using a mixed linear model approach with a high-density genetic map, we identified genomic regions that are likely associated with R. intraradices colonization in sunflower. Additionally, we used a set of twelve diverse lines to assess the effect that inoculation with R. intraradices has on dried shoot biomass and macronutrient uptake. Colonization among lines in the mapping panel ranged from 0-70% and was not correlated with mycorrhizal growth response, shoot phosphorus response, or shoot potassium response among the Core 12 lines. Association mapping yielded three single-nucleotide polymorphisms (SNPs) that were significantly associated with R. intraradices colonization. This is the first study to use GWAS to identify genomic regions associated with AM colonization in an Asterid eudicot species. Three genes of interest identified from the regions containing these SNPs are likely related to plant defense.

Predicting Fusarium Head Blight Resistance for Advanced Trials in a Soft Red Winter Wheat Breeding Program With Genomic Selection

Many studies have evaluated the effectiveness of genomic selection (GS) using cross-validation within training populations; however, few have looked at its performance for forward prediction within a breeding program. The objectives for this study were to compare the performance of naïve GS (NGS) models without covariates and multi-trait GS (MTGS) models by predicting two years of F_{4: 7} advanced breeding lines for three Fusarium head blight (FHB) resistance traits, deoxynivalenol (DON) accumulation, Fusarium damaged kernels (FDK), and severity (SEV) in soft red winter wheat and comparing predictions with phenotypic performance over two years of selection based on selection accuracy and response to selection. On average, for DON, the NGS model correctly selected 69.2% of elite genotypes, while the MTGS model correctly selected 70.1% of elite genotypes compared with 33.0% based on phenotypic selection from the advanced generation. During the 2018 breeding cycle, GS models had the greatest response to selection for DON, FDK, and SEV compared with phenotypic selection. The MTGS model performed better than NGS during the 2019 breeding cycle for all three traits, whereas NGS outperformed MTGS during the 2018 breeding cycle for all traits except for SEV. Overall, GS models were comparable, if not better than phenotypic selection for FHB resistance traits. This is particularly helpful when adverse environmental conditions prohibit accurate phenotyping. This study also shows that MTGS models can be effective for forward prediction when there are strong correlations between traits of interest and covariates in both training and validation populations.

Integrating genomics and multivariate evolutionary quantitative genetics: a case study of constraints on sexual selection in Drosophila serrata

In evolutionary quantitative genetics, the genetic variance-covariance matrix, G, and the vector of directional selection gradients, β, are key parameters for predicting multivariate selection responses and genetic constraints. Historically, investigations of G and β have not overlapped with those dissecting the genetic basis of quantitative traits. Thus, it remains unknown whether these parameters reflect pleiotropic effects at individual loci. Here, we integrate multivariate genome-wide association study (GWAS) with G and β estimation in a well-studied system of multivariate constraint: sexual selection on male cuticular hydrocarbons (CHCs) in Drosophila serrata. In a panel of wild-derived re-sequenced lines, we augment genome-based restricted maximum likelihood to estimate G alongside multivariate single nucleotide polymorphism (SNP) effects, detecting 532 significant associations from 1 652 276 SNPs. Constraint was evident, with β lying in a direction of G with low evolvability. Interestingly, minor frequency alleles typically increased male CHC-attractiveness suggesting opposing natural selection on β. SNP effects were significantly misaligned with the major eigenvector of G, gmax, but well aligned to the second and third eigenvectors g2 and g3. We discuss potential factors leading to these varied results including multivariate stabilizing selection and mutational bias. Our framework may be useful as researchers increasingly access genomic methods to study multivariate selection responses in wild populations.

The genetics of gene expression in a Caenorhabditis elegans multiparental recombinant inbred line population

Studying genetic variation of gene expression provides a powerful way to unravel the molecular components underlying complex traits. Expression quantitative trait locus (eQTL) studies have been performed in several different model species, yet most of these linkage studies have been based on the genetic segregation of two parental alleles. Recently, we developed a multiparental segregating population of 200 recombinant inbred lines (mpRILs) derived from four wild isolates (JU1511, JU1926, JU1931, and JU1941) in the nematode Caenorhabditis elegans. We used RNA-seq to investigate how multiple alleles affect gene expression in these mpRILs. We found 1789 genes differentially expressed between the parental lines. Transgression, expression beyond any of the parental lines in the mpRILs, was found for 7896 genes. For expression QTL mapping almost 9000 SNPs were available. By combining these SNPs and the RNA-seq profiles of the mpRILs, we detected almost 6800 eQTLs. Most trans-eQTLs (63%) co-locate in six newly identified trans-bands. The trans-eQTLs found in previous two-parental allele eQTL experiments and this study showed some overlap (17.5-46.8%), highlighting on the one hand that a large group of genes is affected by polymorphic regulators across populations and conditions, on the other hand, it shows that the mpRIL population allows identification of novel gene expression regulatory loci. Taken together, the analysis of our mpRIL population provides a more refined insight into C. elegans complex trait genetics and eQTLs in general, as well as a starting point to further test and develop advanced statistical models for detection of multiallelic eQTLs and systems genetics studying the genotype-phenotype relationship.

Genetic Regulation of Vessel Morphology in Populus

During secondary growth, forest trees can modify the anatomy of the wood produced by the vascular cambium in response to environmental conditions. Notably, the trees of the model angiosperm genus, Populus, reduce the risk of cavitation and hydraulic failure under water stress by producing water-conducting vessel elements with narrow lumens, which are more numerous and more interconnected with each other. Here, we determined the genetic architecture of vessel traits affecting hydraulic physiology and resilience to water stress. Vessel traits were measured for clonally replicated genotypes of a unique Populus deltoides x nigra population carrying genomically defined insertions and deletions that create gene dosage variation. We found significant phenotypic variation for all traits measured (mean vessel diameter, height-corrected mean vessel diameter, vessel frequency, height-corrected vessel frequency, vessel grouping index, and mean vessel circularity), and that all traits were under genetic control and showed moderate heritability values, ranging from 0.32 to 0.53. Whole-genome scans of correlations between gene dosage and phenotypic traits identified quantitative trait loci for tree height, mean vessel diameter, height-corrected mean vessel diameter, height-corrected vessel frequency, and vessel grouping index. Our results demonstrate that vessel traits affecting hydraulic physiology are under genetic control, and both pleiotropic and trait-specific quantitative trait loci are found for these traits.

Host genetic control of natural killer cell diversity revealed in the Collaborative Cross

Natural killer (NK) cells are innate effectors armed with cytotoxic and cytokine-secreting capacities whose spontaneous antitumor activity is key to numerous immunotherapeutic strategies. However, current mouse models fail to mirror the extensive immune system variation that exists in the human population which may impact on NK cell-based therapies. We performed a comprehensive profiling of NK cells in the Collaborative Cross (CC), a collection of novel recombinant inbred mouse strains whose genetic diversity matches that of humans, thereby providing a unique and highly diverse small animal model for the study of immune variation. We demonstrate that NK cells from CC strains displayed a breadth of phenotypic and functional variation reminiscent of that reported for humans with regards to cell numbers, key marker expression, and functional capacities. We took advantage of the vast genetic diversity of the CC and identified nine genomic loci through quantitative trait locus mapping driving these phenotypic variations. SNP haplotype patterns and variant effect analyses identified candidate genes associated with lung NK cell numbers, frequencies of CD94⁺ NK cells, and expression levels of NKp46. Thus, we demonstrate that the CC represents an outstanding resource to study NK cell diversity and its regulation by host genetics.

Potential of rice landraces with strong culms as genetic resources for improving lodging resistance against super typhoons

It is generally believed that rice landraces with long culms are susceptible to lodging, and have not been utilized for breeding to improve lodging resistance. However, little is known about the structural culm strength of landraces and their beneficial genetic loci. Therefore, in this study, genome-wide association studies (GWAS) were performed using a rice population panel including Japanese rice landraces to identify beneficial loci associated with strong culms. As a result, the landraces were found to have higher structural culm strength and greater diversity than the breeding varieties. Genetic loci associated with strong culms were identified, and it was demonstrated that haplotypes with positive effects of those loci were present in a high proportion of these landraces. These results indicated that the utilization of the strong culm-associated loci present in Japanese rice landraces may further improve the lodging resistance of modern breeding varieties that have relied on semi-dwarfism.

Quantification of spatial metal accumulation patterns in Noccaea caerulescens by X-ray fluorescence image processing for genetic studies

BACKGROUND

Hyperaccumulation of trace elements is a rare trait among plants which is being investigated to advance our understanding of the regulation of metal accumulation and applications in phytotechnologies. Noccaea caerulescens (Brassicaceae) is an intensively studied hyperaccumulator model plant capable of attaining extremely high tissue concentrations of zinc and nickel with substantial genetic variation at the population-level. Micro-X-ray Fluorescence spectroscopy (µXRF) mapping is a sensitive high-resolution technique to obtain information of the spatial distribution of the plant metallome in hydrated samples. We used laboratory-based µXRF to characterize a collection of 86 genetically diverse Noccaea caerulescens accessions from across Europe. We developed an image-processing method to segment different plant substructures in the µXRF images. We introduced the concentration quotient (CQ) to quantify spatial patterns of metal accumulation and linked that to genetic variation.

RESULTS

Image processing resulted in automated segmentation of µXRF plant images into petiole, leaf margin, leaf interveinal and leaf vasculature substructures. The harmonic means of recall and precision (F1 score) were 0.79, 0.80, 0.67, and 0.68, respectively. Spatial metal accumulation as determined by CQ is highly heritable in Noccaea caerulescens for all substructures, with broad-sense heritability (H²) ranging from 76 to 92%, and correlates only weakly with other heritable traits. Insertion of noise into the image segmentation algorithm barely decreases heritability scores of CQ for the segmented substructures, illustrating the robustness of the trait and the quantification method. Very low heritability was found for CQ if randomly generated substructures were compared, validating the approach.

CONCLUSIONS

A strategy for segmenting µXRF images of Noccaea caerulescens is proposed and the concentration quotient is developed to provide a quantitative measure of metal accumulation pattern, which can be used to determine genetic variation for such pattern. The metric is robust to segmentation error and provides reliable H² estimates. This strategy provides an avenue for quantifying XRF data for analysis of the genetics of metal distribution patterns in plants and the subsequent discovery of new genes that regulate metal homeostasis and sequestration in plants.

The genetic basis of adaptation in phenology in an introduced population of Black Cottonwood (Populus trichocarpa, Torr. & Gray)

BACKGROUND

Entering and exiting winter dormancy present important trade-offs between growth and survival at northern latitudes. Many forest trees display local adaptation across latitude in traits associated with these phenology transitions. Transfers of a species outside its native range introduce the species to novel combinations of environmental conditions potentially requiring different combinations of alleles to optimize growth and survival. In this study, we performed genome wide association analyses and a selection scan in a P. trichocarpa mapping population derived from crossings between clones collected across the native range and introduced into Sweden. GWAS analyses were performed using phenotypic data collected across two field seasons and in a controlled phytotron experiment.

RESULTS

We uncovered 584 putative candidate genes associated with spring and autumn phenology traits as well as with growth. Many regions harboring variation significantly associated with the initiation of leaf shed and leaf autumn coloring appeared to have been evolving under positive selection in the native environments of P. trichocarpa. A comparison between the candidate genes identified with results from earlier GWAS analyses performed in the native environment found a smaller overlap for spring phenology traits than for autumn phenology traits, aligning well with earlier observations that spring phenology transitions have a more complex genetic basis than autumn phenology transitions.

CONCLUSIONS

In a small and structured introduced population of P. trichocarpa, we find complex genetic architectures underlying all phenology and growth traits, and identify multiple putative candidate genes despite the limitations of the study population.

Variation of Morphological, Agronomic and Chemical Composition Traits of Local Hazelnuts Collected in Northern Spain

Hazelnut is a traditional crop in northern Spain, where it grows wild as well as being cultivated. A field collection of 41 local and 17 non-local accessions, including 15 well-known cultivars, was established at SERIDA in Villaviciosa, Spain. Here, phenotypic variation was documented for phenological and morphological traits and chemical composition. A large degree of variation for most morphological and phenological traits, except nut maturity date, was revealed. Estimates of broad-sense heritability were high (>0.75) for most of the assessed characters, except for the first male bloom date (0.65), male and female flowering periods (0.40, 0.31), kernel weight (0.69), and kernel percentage (0.33). Local accessions produced smaller nuts and kernels than well-known cultivars but with higher kernel percentage. Limited overlapping between the male and female flowering periods (dychogamy) was observed, except for 'Forcinas 1', 'Forcinas 2', and 'Morell'. The local accessions generally exhibited significantly later male and female flowering compared with the reference cultivars. The local materials showed similar nutritional values to those reported previously for hazelnut. Moreover, the local accessions presented average values similar to the non-local accessions for total fat, ash and carbohydrate contents, as well as energy value, but their protein contents were lower. Their oils were rich in functional compounds, such as unsaturated fatty acids (average: 90.1%), tocopherols (514 mg/kg) and squalene (294.3 mg/kg). A hierarchical clustering on principal components analysis grouped the accessions and differentiated eight local accessions from the rest, including the landrace 'Casina'. This finding provides potential new cultivars, as well as sources of desirable traits, for European hazelnut breeding programs.

Chromosomal characteristics of salt stress heritable gene expression in the rice genome

BACKGROUND

Gene expression is potentially an important heritable quantitative trait that mediates between genetic variation and higher-level complex phenotypes through time and condition-dependent regulatory interactions. Therefore, we sought to explore both the genomic and condition-specific characteristics of gene expression heritability within the context of chromosomal structure.

RESULTS

Heritability was estimated for biological gene expression using a diverse, 84-line, Oryza sativa (rice) population under optimal and salt-stressed conditions. Overall, 5936 genes were found to have heritable expression regardless of condition and 1377 genes were found to have heritable expression only during salt stress. These genes with salt-specific heritable expression are enriched for functional terms associated with response to stimulus and transcription factor activity. Additionally, we discovered that highly and lowly expressed genes, and genes with heritable expression are distributed differently along the chromosomes in patterns that follow previously identified high-throughput chromosomal conformation capture (Hi-C) A/B chromatin compartments. Furthermore, multiple genomic hot-spots enriched for genes with salt-specific heritability were identified on chromosomes 1, 4, 6, and 8. These hotspots were found to contain genes functionally enriched for transcriptional regulation and overlaps with a previously identified major QTL for salt-tolerance in rice.

CONCLUSIONS

Investigating the heritability of traits, and in-particular gene expression traits, is important towards developing a basic understanding of how regulatory networks behave across a population. This work provides insights into spatial patterns of heritable gene expression at the chromosomal level.

Punctuated Loci on Chromosome IV Determine Natural Variation in Orsay Virus Susceptibility of Caenorhabditis elegans Strains Bristol N2 and Hawaiian CB4856

Host-pathogen interactions play a major role in evolutionary selection and shape natural genetic variation. The genetically distinct Caenorhabditis elegans strains, Bristol N2 and Hawaiian CB4856, are differentially susceptible to the Orsay virus (OrV). Here, we report the dissection of the genetic architecture of susceptibility to OrV infection. We compare OrV infection in the relatively resistant wild-type CB4856 strain to the more susceptible canonical N2 strain. To gain insight into the genetic architecture of viral susceptibility, 52 fully sequenced recombinant inbred lines (CB4856 × N2 RILs) were exposed to OrV. This led to the identification of two loci on chromosome IV associated with OrV resistance. To verify the two loci and gain additional insight into the genetic architecture controlling virus infection, introgression lines (ILs) that together cover chromosome IV, were exposed to OrV. Of the 27 ILs used, 17 had an CB4856 introgression in an N2 background, and 10 had an N2 introgression in a CB4856 background. Infection of the ILs confirmed and fine-mapped the locus underlying variation in OrV susceptibility, and we found that a single nucleotide polymorphism in cul-6 may contribute to the difference in OrV susceptibility between N2 and CB4856. An allele swap experiment showed the strain CB4856 became as susceptible as the N2 strain by having an N2 cul-6 allele, although having the CB4856 cul-6 allele did not increase resistance in N2. In addition, we found that multiple strains with nonoverlapping introgressions showed a distinct infection phenotype from the parental strain, indicating that there are punctuated locations on chromosome IV determining OrV susceptibility. Thus, our findings reveal the genetic complexity of OrV susceptibility in C. elegans and suggest that viral susceptibility is governed by multiple genes.IMPORTANCE Genetic variation determines the viral susceptibility of hosts. Yet, pinpointing which genetic variants determine viral susceptibility remains challenging. Here, we have exploited the genetic tractability of the model organism Caenorhabditis elegans to dissect the genetic architecture of Orsay virus infection. Our results provide novel insight into natural determinants of Orsay virus infection.

Genome-wide association coupled gene to gene interaction studies unveil novel epistatic targets among major effect loci impacting rice grain chalkiness

Rice varieties whose quality is graded as excellent have a lower percent grain chalkiness (PGC) of two per cent and below with higher whole grain yields upon milling, leading to higher economic returns for farmers. We have conducted a genome-wide association study (GWAS) using a combined population panel of indica and japonica rice varieties, and identified a total of 746 single nucleotide polymorphisms (SNPs) that were strongly associated with the chalk phenotype, covered 78 Quantitative Trait Loci (QTL) regions. Among them, 21 were high-value QTLs, as they explained at least 10 % of the phenotypic variance for PGC. A combined epistasis and GWAS was applied to dissect the genetics of the complex chalkiness trait, and its regulatory cascades were validated using gene regulatory networks. Promising novel epistatic interactions were found between the loci of chromosomes 6 (PGC6.1) and 7 (PGC7.8) that contributed to lower PGC. Based on haplotype mining only a few modern rice varieties confounded with a lower chalkiness, and they possess several PGC QTLs. The importance of PGC6.1 was validated through multi-parent advanced generation intercrosses and several low-chalk lines possessing superior haplotypes were identified. The results of this investigation have deciphered the underlying genetic networks that can reduce PGC to 2%, and will thus support future breeding programs to improve the grain quality of elite genetic material with high-yielding potentials.

GWAS of pod morphological and color characters in common bean

BACKGROUND

Common bean (Phaseolus vulgaris L.) is an important legume species which can be consumed as immature pods and dry seeds after re-hydration and cooking. Many genes and QTL, and epistatic interactions among them, condition pod morphological traits. However, not all them have been mapped or validated nor candidate genes proposed. We sought to investigate the genomic regions conditioning pod morphological and color characters through GWAS.

RESULTS

Single and multi-locus genome wide association analysis was used to investigate pod traits for a set of 301 bean lines of the Spanish Diversity Panel (SDP). The SDP was genotyped with 32,812 SNPs obtained from Genotyping by Sequencing. The panel was grown in two seasons and phenotypic data were recorded for 17 fresh pods traits grouped in four pod characters: pod length, pod cross-section, pod color, and number of seeds per pod. In all, 23 QTL for pod length, 6 for cross-section, 18 for pod color, 6 for number of seeds per pod and 9 associated to two or more pod characters were detected. Most QTL were located in the telomeric region of chromosomes Pv01, Pv02, Pv04, Pv08, Pv09 and Pv10. Eighteen detected QTL co-localized with 28 previously reported QTL. Twenty-one potential candidate genes involving developmental processes were detected underlying 11 QTL for pod morphological characters, four of them homologous to A. thaliana genes FIS2, SPL10, TTG2 and AML4 affecting silique size. Eight potential candidate genes involved in pigment synthesis, were found underlying five QTL for pod color.

CONCLUSIONS

GWAS for pod morphological and color characters in the bean Spanish Diversity Panel revealed 62 QTL, 18 co-localized with previously reported QTL, and 16 QTL were underlain by 25 candidate genes. Overall 44 new QTL identified and 18 existing QTL contribute to a better understanding of the complex inheritance of pod size and color traits in common bean and open the opportunity for future validation works.

Selection for functional performance in the evolution of cuticle hardening mechanisms in insects

Calcified tissues have repeatedly evolved in many animal lineages and show a tremendous diversity of forms and functions. The cuticle of many insects is enriched with elements other than Calcium, a strategy of hardening that is taxonomically widespread but apparently poorly variable among clades. Here, we investigate the evolutionary potential of the enrichment with metals in insect cuticle at different biological levels. We combined experimental evidence of Zinc content variation in the mandibles of a target species (Chorthippus cazurroi [Bolívar]) with phylogenetic comparative analyses among grasshopper species. We found that mandibular Zinc content was repeatable among related individuals and was associated with an indicator of fitness, so there was potential for adaptive variation. Among species, Zinc enrichment evolved as a consequence of environmental and dietary influences on the physical function of the jaw (cutting and chewing), suggesting a role of natural selection in environmental fit. However, there were also important within and transgenerational environmental sources of similarity among individuals. These environmental influences, along with the tight relationship with biomechanics, may limit the potential for diversification of this hardening mechanism. This work provides novel insights into the diversification of biological structures and the link between evolutionary capacity and intra- and interspecific variation.

Lessons from a GWAS study of a wheat pre-breeding program: pyramiding resistance alleles to Fusarium crown rot

Much has been published on QTL detection for complex traits using bi-parental and multi-parental crosses (linkage analysis) or diversity panels (GWAS studies). While successful for detection, transferability of results to real applications has proven more difficult. Here, we combined a QTL detection approach using a pre-breeding populations which utilized intensive phenotypic selection for the target trait across multiple plant generations, combined with rapid generation turnover (i.e. "speed breeding") to allow cycling of multiple plant generations each year. The reasoning is that QTL mapping information would complement the selection process by identifying the genome regions under selection within the relevant germplasm. Questions to answer were the location of the genomic regions determining response to selection and the origin of the favourable alleles within the pedigree. We used data from a pre-breeding program that aimed at pyramiding different resistance sources to Fusarium crown rot into elite (but susceptible) wheat backgrounds. The population resulted from a complex backcrossing scheme involving multiple resistance donors and multiple elite backgrounds, akin to a MAGIC population (985 genotypes in total, with founders, and two major offspring layers within the pedigree). A significant increase in the resistance level was observed (i.e. a positive response to selection) after the selection process, and 17 regions significantly associated with that response were identified using a GWAS approach. Those regions included known QTL as well as potentially novel regions contributing resistance to Fusarium crown rot. In addition, we were able to trace back the sources of the favourable alleles for each QTL. We demonstrate that QTL detection using breeding populations under selection for the target trait can identify QTL controlling the target trait and that the frequency of the favourable alleles was increased as a response to selection, thereby validating the QTL detected. This is a valuable opportunistic approach that can provide QTL information that is more easily transferred to breeding applications.

Transcriptome-wide analysis of introgression-resistant regions reveals genetic divergence genes under positive selection in Populus trichocarpa

Comparing gene expression patterns and genetic polymorphisms between populations is of central importance for understanding the origin and maintenance of biodiversity. Based on population-specific gene expression levels and allele frequency differences, we sought to identify population divergence (PD) genes across the introgression-resistant genomic regions of Populus trichocarpa. Genes containing highly diverged loci [i.e., genetic divergence (GD)] or showing expression divergence (ED) between populations were widely distributed in the genome and substantially enriched in functional categories related to stress responses, disease resistance, timing of flowering, cell cycle regulation, plant growth, and development. Nine genomic regions showing evidence of strong positive selection were overlapped with GD genes, which had significant differences between Oregon (a southernmost peripheral deme) and the other demes. However, we did not find evidence that genes under positive selection show an enrichment for ED. PD genes and genes under selection pertained to the same gene classes, such as SERINE/CYSTEINE PROTEASE, ABC TRANSPORTER, GLYCOSYLTRANSFERASE and other transferases. Our analysis also revealed that GD genes were polymorphic within the species (41.9 ± 3.66 biallelic variants per gene), as previously reported in herbaceous plants. By contrast, ED genes contained less genetic variants (10.73 ± 1.14) and were likely highly expressed. In addition, we found that trans- rather than cis-acting variants considerably contribute to the evolution of >90% PD genes. Overall, this study elucidates that cohorts of PD genes agree with the general attributes of known speciation genes and GD genes will provide substrates for positive selection to operate on.

Prior Biological Knowledge Improves Genomic Prediction of Growth-Related Traits in Arabidopsis thaliana

Prediction of growth-related complex traits is highly important for crop breeding. Photosynthesis efficiency and biomass are direct indicators of overall plant performance and therefore even minor improvements in these traits can result in significant breeding gains. Crop breeding for complex traits has been revolutionized by technological developments in genomics and phenomics. Capitalizing on the growing availability of genomics data, genome-wide marker-based prediction models allow for efficient selection of the best parents for the next generation without the need for phenotypic information. Until now such models mostly predict the phenotype directly from the genotype and fail to make use of relevant biological knowledge. It is an open question to what extent the use of such biological knowledge is beneficial for improving genomic prediction accuracy and reliability. In this study, we explored the use of publicly available biological information for genomic prediction of photosynthetic light use efficiency (Φ PSII ) and projected leaf area (PLA) in Arabidopsis thaliana. To explore the use of various types of knowledge, we mapped genomic polymorphisms to Gene Ontology (GO) terms and transcriptomics-based gene clusters, and applied these in a Genomic Feature Best Linear Unbiased Predictor (GFBLUP) model, which is an extension to the traditional Genomic BLUP (GBLUP) benchmark. Our results suggest that incorporation of prior biological knowledge can improve genomic prediction accuracy for both Φ PSII and PLA. The improvement achieved depends on the trait, type of knowledge and trait heritability. Moreover, transcriptomics offers complementary evidence to the Gene Ontology for improvement when used to define functional groups of genes. In conclusion, prior knowledge about trait-specific groups of genes can be directly translated into improved genomic prediction.