Association genetics of complex traits in plants

A protocol for increased throughput phenotyping of plant resistance to the pollen beetle

BACKGROUND

Improving crop resistance to insect herbivores is a major research objective in breeding programs. Although genomic technologies have increased the speed at which large populations can be genotyped, breeding programs still suffer from phenotyping constraints. The pollen beetle (Brassicogethes aeneus) is a major pest of oilseed rape for which no resistant cultivar is available to date, but previous studies have highlighted the potential of white mustard as a source of resistance and introgression of this resistance appears to be a promising strategy. Here we present a phenotyping protocol allowing mid-throughput (i.e., increased throughput compared to current methods) acquisition of resistance data, which could then be used for genetic mapping of QTLs.

RESULTS

Contrasted white mustard genotypes were selected from an initial field screening and then evaluated for their resistance under controlled conditions using a standard phenotyping method on entire plants. We then upgraded this protocol for mid-throughput phenotyping, by testing two alternative methods. We found that phenotyping on detached buds did not provide the same resistance contrasts as observed with the standard protocol, in contrast to the phenotyping protocol with miniaturized plants. This protocol was then tested on a large panel composed of hundreds of plants. A significant variation in resistance among genotypes was observed, which validates the large-scale application of this new phenotyping protocol.

CONCLUSION

The combination of this mid-throughput phenotyping protocol and white mustard as a source of resistance against the pollen beetle offers a promising avenue for breeding programs aiming to improve oilseed rape resistance. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Allelic variations of WAK106-E2Fa-DPb1-UGT74E2 module regulate fibre properties in Populus tomentosa

Wood formation, intricately linked to the carbohydrate metabolism pathway, underpins the capacity of trees to produce renewable resources and offer vital ecosystem services. Despite their importance, the genetic regulatory mechanisms governing wood fibre properties in woody plants remain enigmatic. In this study, we identified a pivotal module comprising 158 high-priority core genes implicated in wood formation, drawing upon tissue-specific gene expression profiles from 22 Populus samples. Initially, we conducted a module-based association study in a natural population of 435 Populus tomentosa, pinpointing PtoDPb1 as the key gene contributing to wood formation through the carbohydrate metabolic pathway. Overexpressing PtoDPb1 led to a 52.91% surge in cellulose content, a reduction of 14.34% in fibre length, and an increment of 38.21% in fibre width in transgenic poplar. Moreover, by integrating co-expression patterns, RNA-sequencing analysis, and expression quantitative trait nucleotide (eQTN) mapping, we identified a PtoDPb1-mediated genetic module of PtoWAK106-PtoDPb1-PtoE2Fa-PtoUGT74E2 responsible for fibre properties in Populus. Additionally, we discovered the two PtoDPb1 haplotypes that influenced protein interaction efficiency between PtoE2Fa-PtoDPb1 and PtoDPb1-PtoWAK106, respectively. The transcriptional activation activity of the PtoE2Fa-PtoDPb1 haplotype-1 complex on the promoter of PtoUGT74E2 surpassed that of the PtoE2Fa-PtoDPb1 haplotype-2 complex. Taken together, our findings provide novel insights into the regulatory mechanisms of fibre properties in Populus, orchestrated by PtoDPb1, and offer a practical module for expediting genetic breeding in woody plants via molecular design.

Strong prevalence of light regime-specific QTL in Arabidopsis detected using automated high-throughput phenotyping in fluctuating or constant light

Plants have evolved and adapted under dynamic environmental conditions, particularly to fluctuating light, but plant research has often focused on constant growth conditions. To quantitatively asses the adaptation to fluctuating light, a panel of 384 natural Arabidopsis thaliana accessions was analyzed in two parallel independent experiments under fluctuating and constant light conditions in an automated high-throughput phenotyping system upgraded with supplemental LEDs. While the integrated daily photosynthetically active radiation was the same under both light regimes, plants in fluctuating light conditions accumulated significantly less biomass and had lower leaf area during their measured vegetative growth than plants in constant light. A total of 282 image-derived architectural and/or color-related traits at six common time points, and 77 photosynthesis-related traits from one common time point were used to assess their associations with genome-wide natural variation for both light regimes. Out of the 3000 significant marker-trait associations (MTAs) detected, only 183 (6.1%) were common for fluctuating and constant light conditions. The prevalence of light regime-specific QTL indicates a complex adaptation. Genes in linkage disequilibrium with fluctuating light-specific MTAs with an adjusted repeatability value >0.5 were filtered for gene ontology terms containing "photo" or "light", yielding 15 selected candidates. The candidate genes are involved in photoprotection, PSII maintenance and repair, maintenance of linear electron flow, photorespiration, phytochrome signaling, and cell wall expansion, providing a promising starting point for further investigations into the response of Arabidopsis thaliana to fluctuating light conditions.

Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize

Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype-phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies.

Genetic control of flowering time and fruit yield in citron watermelon

Flowering time and fruit yield are important traits in watermelon crop improvement. There is limited information on the inheritance and genomic loci underlying flowering time and yield performance, especially in citron watermelon. A total of 125 citron watermelon accessions were evaluated in field trials over two growing seasons for days to male and female flowers, fruit count, fruit weight, and fruit yield. The germplasm was genotyped with more than two million single-nucleotide polymorphism (SNP) markers generated via whole-genome resequencing. Trait mapping was conducted using a genome-wide association study (GWAS). Broad-sense heritability for all traits ranged from moderate to high, indicating that genetic improvement through breeding and selection is feasible. Significant marker-trait associations were uncovered for days to female flower (chromosomes Ca04, Ca05, Ca08, and Ca09), fruit count (on Ca02, Ca03, and Ca05), fruit weight (on Ca02, Ca06, Ca08, Ca10, and Ca11), and fruit yield on chromosomes Ca05, Ca07, and Ca09. The phenotypic variation explained by the significant SNPs ranged from 1.6 to 25.4, highlighting the complex genetic architecture of the evaluated traits. Candidate genes relevant to flowering time and fruit yield component traits were uncovered on chromosomes Ca02, Ca04, Ca05, Ca06, Ca09, and Ca11. These results lay a foundation for marker-assisted trait introgression of flowering time and fruit yield component traits in watermelons.

A Large-Scale Candidate-Gene Association Mapping for Drought Tolerance and Agronomic Traits in Sugarcane

Dissection of the genetic loci controlling drought tolerance traits with a complex genetic inheritance is important for drought-tolerant sugarcane improvement. In this study, we conducted a large-scale candidate gene association study of 649 candidate genes in a sugarcane diversity panel to identify genetic variants underlying agronomic traits and drought tolerance indices evaluated in plant cane and ratoon cane under water-stressed (WS) and non-stressed (NS) environments. We identified 197 significant marker-trait associations (MTAs) in 141 candidate genes associated with 18 evaluated traits with the Bonferroni correction threshold (α = 0.05). Out of the total, 95 MTAs in 78 candidate genes and 62 MTAs in 58 candidate genes were detected under NS and WS conditions, respectively. Most MTAs were found only in specific water regimes and crop seasons. These MTAs explained 7.93-30.52% of phenotypic variation. Association mapping results revealed that 34, 59, and 104 MTAs involved physiological and molecular adaptation, phytohormone metabolism, and drought-inducible genes. They identified 19 pleiotropic genes associated with more than one trait and many genes related to drought tolerance indices. The genetic and genomic resources identified in this study will enable the combining of yield-related traits and sugar-related traits with agronomic value to optimize the yield of sugarcane cultivars grown under drought-stressed and non-stressed environments.

Combining multiplex gene editing and doubled haploid technology in maize

A major advantage of using CRISPR/Cas9 for gene editing is multiplexing, that is, the simultaneous targeting of many genes. However, primary transformants typically contain hetero-allelic mutations or are genetic mosaic, while genetically stable lines that are homozygous are desired for functional analysis. Currently, a dedicated and labor-intensive effort is required to obtain such higher-order mutants through several generations of genetic crosses and genotyping. We describe the design and validation of a rapid and efficient strategy to produce lines of genetically identical plants carrying various combinations of homozygous edits, suitable for replicated analysis of phenotypical differences. This approach was achieved by combining highly multiplex gene editing in Zea mays (maize) with in vivo haploid induction and efficient in vitro generation of doubled haploid plants using embryo rescue doubling. By combining three CRISPR/Cas9 constructs that target in total 36 genes potentially involved in leaf growth, we generated an array of homozygous lines with various combinations of edits within three generations. Several genotypes show a reproducible 10% increase in leaf size, including a septuple mutant combination. We anticipate that our strategy will facilitate the study of gene families via multiplex CRISPR mutagenesis and the identification of allele combinations to improve quantitative crop traits.

Genetic markers and tree properties predicting wood biorefining potential in aspen (Populus tremula) bioenergy feedstock

BACKGROUND

Wood represents the majority of the biomass on land and constitutes a renewable source of biofuels and other bioproducts. However, wood is recalcitrant to bioconversion, raising a need for feedstock improvement in production of, for instance, biofuels. We investigated the properties of wood that affect bioconversion, as well as the underlying genetics, to help identify superior tree feedstocks for biorefining.

RESULTS

We recorded 65 wood-related and growth traits in a population of 113 natural aspen genotypes from Sweden ( https://doi.org/10.5061/dryad.gtht76hrd ). These traits included three growth and field performance traits, 20 traits for wood chemical composition, 17 traits for wood anatomy and structure, and 25 wood saccharification traits as indicators of bioconversion potential. Glucose release after saccharification with acidic pretreatment correlated positively with tree stem height and diameter and the carbohydrate content of the wood, and negatively with the content of lignin and the hemicellulose sugar units. Most of these traits displayed extensive natural variation within the aspen population and high broad-sense heritability, supporting their potential in genetic improvement of feedstocks towards improved bioconversion. Finally, a genome-wide association study (GWAS) revealed 13 genetic loci for saccharification yield (on a whole-tree-biomass basis), with six of them intersecting with associations for either height or stem diameter of the trees.

CONCLUSIONS

The simple growth traits of stem height and diameter were identified as good predictors of wood saccharification yield in aspen trees. GWAS elucidated the underlying genetics, revealing putative genetic markers for bioconversion of bioenergy tree feedstocks.

Genome-wide association mapping for component traits of drought tolerance in dry beans (Phaseolus vulgaris L.)

Understanding the genetic basis of traits of economic importance under drought stressed and well-watered conditions is important in enhancing genetic gains in dry beans (Phaseolus vulgaris L.). This research aims to: (i) identify markers associated with agronomic and physiological traits for drought tolerance and (ii) identify drought-related putative candidate genes within the mapped genomic regions. An andean and middle-american diversity panel (AMDP) comprising of 185 genotypes was screened in the field under drought stressed and well-watered conditions for two successive seasons. Agronomic and physiological traits, viz., days to 50% flowering (DFW), plant height (PH), days to physiological maturity (DPM), grain yield (GYD), 100-seed weight (SW), leaf temperature (LT), leaf chlorophyll content (LCC) and stomatal conductance (SC) were phenotyped. Principal component and association analysis were conducted using the filtered 9370 Diversity Arrays Technology sequencing (DArTseq) markers. The mean PH, GYD, SW, DPM, LCC and SC of the panel was reduced by 12.1, 29.6, 10.3, 12.6, 28.5 and 62.0%, respectively under drought stressed conditions. Population structure analysis revealed two sub-populations, which corresponded to the andean and middle-american gene pools. Markers explained 0.08-0.10, 0.22-0.23, 0.29-0.32, 0.43-0.44, 0.65-0.66 and 0.69-0.70 of the total phenotypic variability (R2) for SC, LT, PH, GYD, SW and DFW, respectively under drought stressed conditions. For well-watered conditions, R2 varied from 0.08 (LT) to 0.70 (DPM). Overall, 68 significant (p < 10-03) marker-trait associations (MTAs) and 22 putative candidate genes were identified across drought stressed and well-watered conditions. Most of the identified genes had known biological functions related to regulating the response to drought stress. The findings provide new insights into the genetic architecture of drought stress tolerance in common bean. The findings also provide potential candidate SNPs and putative genes that can be utilized in gene discovery and marker-assisted breeding for drought tolerance after validation.

Genetic association of toxin production in the dinoflagellate Alexandrium minutum

Dinoflagellates of the genus Alexandrium are responsible for harmful algal blooms and produce paralytic shellfish toxins (PSTs). Their very large and complex genomes make it challenging to identify the genes responsible for toxin synthesis. A family-based genomic association study was developed to determine the inheritance of toxin production in Alexandrium minutum and identify genomic regions linked to this production. We show that the ability to produce toxins is inheritable in a Mendelian way, while the heritability of the toxin profile is more complex. We developed the first dinoflagellate genetic linkage map. Using this map, several major results were obtained: 1. A genomic region related to the ability to produce toxins was identified. 2. This region does not contain any polymorphic sxt genes, known to be involved in toxin production in cyanobacteria. 3. The sxt genes, known to be present in a single cluster in cyanobacteria, are scattered on different linkage groups in A. minutum. 4. The expression of two sxt genes not assigned to any linkage group, sxtI and sxtG, may be regulated by the genomic region related to the ability to produce toxins. Our results provide new insights into the organization of toxicity-related genes in A. minutum, suggesting a dissociated genetic mechanism for the production of the different analogues and the ability to produce toxins. However, most of the newly identified genes remain unannotated. This study therefore proposes new candidate genes to be further explored to understand how dinoflagellates synthesize their toxins.

Prioritized candidate causal haplotype blocks in plant genome-wide association studies

Genome wide association studies (GWAS) can play an essential role in understanding genetic basis of complex traits in plants and animals. Conventional SNP-based linear mixed models (LMM) that marginally test single nucleotide polymorphisms (SNPs) have successfully identified many loci with major and minor effects in many GWAS. In plant, the relatively small population size in GWAS and the high genetic diversity found in many plant species can impede mapping efforts on complex traits. Here we present a novel haplotype-based trait fine-mapping framework, HapFM, to supplement current GWAS methods. HapFM uses genotype data to partition the genome into haplotype blocks, identifies haplotype clusters within each block, and then performs genome-wide haplotype fine-mapping to prioritize the candidate causal haplotype blocks of trait. We benchmarked HapFM, GEMMA, BSLMM, GMMAT, and BLINK in both simulated and real plant GWAS datasets. HapFM consistently resulted in higher mapping power than the other GWAS methods in high polygenicity simulation setting. Moreover, it resulted in smaller mapping intervals, especially in regions of high LD, achieved by prioritizing small candidate causal blocks in the larger haplotype blocks. In the Arabidopsis flowering time (FT10) datasets, HapFM identified four novel loci compared to GEMMA’s results, and the average mapping interval of HapFM was 9.6 times smaller than that of GEMMA. In conclusion, HapFM is tailored for plant GWAS to result in high mapping power on complex traits and improved on mapping resolution to facilitate crop improvement.

Genome-wide association studies (GWAS) are commonly used in human and plant studies to identify genetic variants responsible for the phenotype of interest and provide foundations for studying disease mechanisms and crop improvement. Most GWAS models are developed and optimized using human datasets. However, the difference between human and plant datasets essentially limits their applications in plant studies, especially when mapping complex traits such as drought resistance and yield. In this study, we present a novel GWAS method, HapFM, tailored for plant datasets to overcome the difficulties of many conventional GWAS methods. HapFM resulted in higher statistical power than conventional GWAS methods for mapping complex traits in our simulation and real dataset analyses. In addition, HapFM reduced the mapping interval by prioritizing candidate causal regions in the genome, which benefits the downstream experimental studies. Last but not least, HapFM can incorporate biological annotations to increase statistical power further. Overall, HapFM balances statistical power, result interpretability, and downstream experimental verifiability.

Transcriptome and association mapping revealed functional genes respond to drought stress in Populus

Drought frequency and severity are exacerbated by global climate change, which could compromise forest ecosystems. However, there have been minimal efforts to systematically investigate the genetic basis of the response to drought stress in perennial trees. Here, we implemented a systems genetics approach that combines co-expression analysis, association genetics, and expression quantitative trait nucleotide (eQTN) mapping to construct an allelic genetic regulatory network comprising four key regulators (PtoeIF-2B, PtoABF3, PtoPSB33, and PtoLHCA4) under drought stress conditions. Furthermore, Hap_01PtoeIF-2B, a superior haplotype associated with the net photosynthesis, was revealed through allelic frequency and haplotype analysis. In total, 75 candidate genes related to drought stress were identified through transcriptome analyses of five Populus cultivars (P. tremula × P. alba, P. nigra, P. simonii, P. trichocarpa, and P. tomentosa). Through association mapping, we detected 92 unique SNPs from 38 genes and 104 epistatic gene pairs that were associated with six drought-related traits by association mapping. eQTN mapping unravels drought stress-related gene loci that were significantly associated with the expression levels of candidate genes for drought stress. In summary, we have developed an integrated strategy for dissecting a complex genetic network, which facilitates an integrated population genomics approach that can assess the effects of environmental threats.

Dissecting the Genetic Architecture of Phenology Affecting Adaptation of Spring Bread Wheat Genotypes to the Major Wheat-Producing Zones in India

Spring bread wheat adaptation to diverse environments is supported by various traits such as phenology and plant architecture. A large-scale genome-wide association study (GWAS) was designed to investigate and dissect the genetic architecture of phenology affecting adaptation. It used 48 datasets from 4,680 spring wheat lines. For 8 years (2014-2021), these lines were evaluated for days to heading (DH) and maturity (DM) at three sites: Jabalpur, Ludhiana, and Samastipur (Pusa), which represent the three major Indian wheat-producing zones: the Central Zone (CZ), North-Western Plain Zone (NWPZ), and North-Eastern Plain Zone (NEPZ), respectively. Ludhiana had the highest mean DH of 103.8 days and DM of 148.6 days, whereas Jabalpur had the lowest mean DH of 77.7 days and DM of 121.6 days. We identified 119 markers significantly associated with DH and DM on chromosomes 5B (76), 2B (18), 7D (10), 4D (8), 5A (1), 6B (4), 7B (1), and 3D (1). Our results clearly indicated the importance of the photoperiod-associated gene (Ppd-B1) for adaptation to the NWPZ and the Vrn-B1 gene for adaptation to the NEPZ and CZ. A maximum variation of 21.1 and 14% was explained by markers 2B_56134146 and 5B_574145576 linked to the Ppd-B1 and Vrn-B1 genes, respectively, indicating their significant role in regulating DH and DM. The results provide important insights into the genomic regions associated with the two phenological traits that influence adaptation to the major wheat-producing zones in India.

Genome-Wide Association Analysis of Resistance to Pseudoperonospora cubensis in Citron Watermelon

Cultivated sweet watermelon (Citrullus lanatus) is an important vegetable crop for millions of people around the world. There are limited sources of resistance to economically important diseases within C. lanatus, whereas C. amarus has a reservoir of traits that can be exploited to improve C. lanatus for resistance to biotic and abiotic stresses. Cucurbit downy mildew (CDM), caused by Pseudoperonospora cubensis, is an emerging threat to watermelon production. We screened 122 C. amarus accessions for resistance to CDM over two tests (environments). The accessions were genotyped by whole-genome resequencing to generate 2,126,759 single nucleotide polymorphic (SNP) markers. A genome-wide association study was deployed to uncover marker-trait associations and identify candidate genes underlying resistance to CDM. Our results indicate the presence of wide phenotypic variability (1.1 to 57.8%) for leaf area infection, representing a 50.7-fold variation for CDM resistance across the C. amarus germplasm collection. Broad-sense heritability estimate was 0.55, implying the presence of moderate genetic effects for resistance to CDM. The peak SNP markers associated with resistance to P. cubensis were located on chromosomes Ca03, Ca05, Ca07, and Ca11. The significant SNP markers accounted for up to 30% of the phenotypic variation and were associated with promising candidate genes encoding leucine-rich repeat receptor-like protein kinase and the WRKY transcription factor. This information will be useful in understanding the genetic architecture of the P. cubensis-Citrullus spp. patho-system as well as development of resources for genomics-assisted breeding for resistance to CDM in watermelon.

Trends of genetic changes uncovered by Env- and Eigen-GWAS in wheat and barley

Variety age and population structure detect novel QTL for yield and adaptation in wheat and barley without the need to phenotype. The process of crop breeding over the last century has delivered new varieties with increased genetic gains, resulting in higher crop performance and yield. However, in many cases, the alleles and genomic regions underpinning this success remain unknown. This is partly due to the difficulty of generating sufficient phenotypic data on large numbers of historical varieties to enable such analyses. Here we demonstrate the ability to circumvent such bottlenecks by identifying genomic regions selected over 100 years of crop breeding using age of a variety as a surrogate for yield. Rather than collecting phenotype data, we deployed 'environmental genome-wide association scans' (EnvGWAS) based on variety age in two of the world's most important crops, wheat and barley, and detected strong signals of selection across both genomes. EnvGWAS identified 16 genomic regions in barley and 10 in wheat with contrasting patterns between spring and winter types of the two crops. To further examine changes in genome structure, we used the genomic relationship matrix of the genotypic data to derive eigenvectors for analysis in EigenGWAS. This detected seven major chromosomal introgressions that contributed to adaptation in wheat. EigenGWAS and EnvGWAS based on variety age avoid costly phenotyping and facilitate the identification of genomic tracts that have been under selection during breeding. Our results demonstrate the potential of using historical cultivar collections coupled with genomic data to identify chromosomal regions under selection and may help guide future plant breeding strategies to maximise the rate of genetic gain and adaptation.

Genome-Wide Association Study of Soybean Germplasm Derived From Canadian × Chinese Crosses to Mine for Novel Alleles to Improve Seed Yield and Seed Quality Traits

Genome-wide association study (GWAS) has emerged in the past decade as a viable tool for identifying beneficial alleles from a genomic diversity panel. In an ongoing effort to improve soybean [Glycine max (L.) Merr.], which is the third largest field crop in Canada, a GWAS was conducted to identify novel alleles underlying seed yield and seed quality and agronomic traits. The genomic panel consisted of 200 genotypes including lines derived from several generations of bi-parental crosses between modern Canadian × Chinese cultivars (CD-CH). The genomic diversity panel was field evaluated at two field locations in Ontario in 2019 and 2020. Genotyping-by-sequencing (GBS) was conducted and yielded almost 32 K high-quality SNPs. GWAS was conducted using Fixed and random model Circulating Probability Unification (FarmCPU) model on the following traits: seed yield, seed protein concentration, seed oil concentration, plant height, 100 seed weight, days to maturity, and lodging score that allowed to identify five QTL regions controlling seed yield and seed oil and protein content. A candidate gene search identified a putative gene for each of the three traits. The results of this GWAS study provide insight into potentially valuable genetic resources residing in Chinese modern cultivars that breeders may use to further improve soybean seed yield and seed quality traits.

Targeted re-sequencing and genome-wide association analysis for wood property traits in breeding population of Eucalyptus tereticornis × E. grandis

Globally, Eucalyptus plantations occupy 22 million ha area and is one of the preferred hardwood species due to their short rotation, rapid growth, adaptability and wood properties. In this study, we present results of GWAS in parents and 100 hybrids of Eucalyptus tereticornis × E. grandis using 762 genes presumably involved in wood formation. Comparative analysis between parents predicted 32,202 polymorphic SNPs with high average read depth of 269-562× per individual per nucleotide. Seventeen wood related traits were phenotyped across three diverse environments and GWAS was conducted using 13,610 SNPs. A total of 45 SNP-trait associations were predicted across two locations. Seven large effect markers were identified which explained more than 80% of phenotypic variation for fibre area. This study has provided an array of candidate genes which may govern fibre morphology in this genus and has predicted potential SNPs which can guide future breeding programs in tropical Eucalyptus.

Genome Wide Association Mapping of Root Traits in the Andean Genepool of Common Bean (Phaseolus vulgaris L.) Grown With and Without Aluminum Toxicity

Common bean is one of the most important grain legumes for human diets but is produced on marginal lands with unfavorable soil conditions; among which Aluminum (Al) toxicity is a serious and widespread problem. Under low pH, stable forms of Al dissolve into the soil solution and as phytotoxic ions inhibit the growth and function of roots through injury to the root apex. This results in a smaller root system that detrimentally effects yield. The goal of this study was to evaluate 227 genotypes from an Andean diversity panel (ADP) of common bean and determine the level of Al toxicity tolerance and candidate genes for this abiotic stress tolerance through root trait analysis and marker association studies. Plants were grown as seedlings in hydroponic tanks at a pH of 4.5 with a treatment of high Al concentration (50 μM) compared to a control (0 μM). The roots were harvested and scanned to determine average root diameter, root volume, root surface area, number of root links, number of root tips, and total root length. Percent reduction or increase was calculated for each trait by comparing treatments. Genome wide association study (GWAS) was conducted by testing phenotypic data against single nucleotide polymorphism (SNP) marker genotyping data for the panel. Principal components and a kinship matrix were included in the mixed linear model to correct for population structure. Analyses of variance indicated the presence of significant difference between genotypes. The heritability of traits ranged from 0.67 to 0.92 in Al-treated and reached similar values in non-treated plants. GWAS revealed significant associations between root traits and genetic markers on chromosomes Pv01, Pv04, Pv05, Pv06, and Pv11 with some SNPs contributing to more than one trait. Candidate genes near these loci were analyzed to explain the detected association and included an Al activated malate transporter gene and a multidrug and toxic compound extrusion gene. This study showed that polygenic inheritance was critical to aluminum toxicity tolerance in common beans roots. Candidate genes found suggested that exudation of malate and citrate as organic acids would be important for Al tolerance. Possible cross-talk between mechanisms of aluminum tolerance and resistance to other abiotic stresses are discussed.

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.

Variation in non-target traits in genetically modified hybrid aspens does not exceed natural variation

Genetically modified hybrid aspens (Populus tremula L. x P. tremuloides Michx.), selected for increased growth under controlled conditions, have been grown in highly replicated field trials to evaluate how the target trait (growth) translated to natural conditions. Moreover, the variation was compared among genotypes of ecologically important non-target traits: number of shoots, bud set, pathogen infection, amount of insect herbivory, composition of the insect herbivore community and flower bud induction. This variation was compared with the variation in a population of randomly selected natural accessions of P. tremula grown in common garden trials, to estimate how the "unintended variation" present in transgenic trees, which in the future may be commercialized, compares with natural variation. The natural variation in the traits was found to be typically significantly greater. The data suggest that when authorities evaluate the potential risks associated with a field experiment or commercial introduction of transgenic trees, risk evaluation should focus on target traits and that unintentional variation in non-target traits is of less concern.

GWAS Mediated Elucidation of Heterosis for Metric Traits in Cotton (Gossypium hirsutum L.) Across Multiple Environments

For about a century, plant breeding has widely exploited the heterosis phenomenon-often considered as hybrid vigor-to increase agricultural productivity. The ensuing F₁ hybrids can substantially outperform their progenitors due to heterozygous combinations that mitigate deleterious mutations occurring in each genome. However, only fragmented knowledge is available concerning the underlying genes and processes that foster heterosis. Although cotton is among the highly valued crops, its improvement programs that involve the exploitation of heterosis are still limited in terms of significant accomplishments to make it broadly applicable in different agro-ecological zones. Here, F₁ hybrids were derived from mating a diverse Upland Cotton germplasm with commercially valuable cultivars in the Line × Tester fashion and evaluated across multiple environments for 10 measurable traits. These traits were dissected into five different heterosis types and specific combining ability (SCA). Subsequent genome-wide predictions along-with association analyses uncovered a set of 298 highly significant key single nucleotide polymorphisms (SNPs)/Quantitative Trait Nucleotides (QTNs) and 271 heterotic Quantitative Trait Nucleotides (hQTNs) related to agronomic and fiber quality traits. The integration of a genome wide association study with RNA-sequence analysis yielded 275 candidate genes in the vicinity of key SNPs/QTNs. Fiber micronaire (MIC) and lint percentage (LP) had the maximum number of associated genes, i.e., each with 45 related to QTNs/hQTNs. A total of 54 putative candidate genes were identified in association with HETEROSIS of quoted traits. The novel players in the heterosis mechanism highlighted in this study may prove to be scientifically and biologically important for cotton biologists, and for those breeders engaged in cotton fiber and yield improvement programs.

Genome-Wide Association Study of Local Thai Indica Rice Seedlings Exposed to Excessive Iron

Excess soluble iron in acidic soil is an unfavorable environment that can reduce rice production. To better understand the tolerance mechanism and identify genetic loci associated with iron toxicity (FT) tolerance in a highly diverse indica Thai rice population, a genome-wide association study (GWAS) was performed using genotyping by sequencing and six phenotypic data (leaf bronzing score (LBS), chlorophyll content, shoot height, root length, shoot biomass, and root dry weight) under both normal and FT conditions. LBS showed a high negative correlation with the ratio of chlorophyll content and shoot biomass, indicating the FT-tolerant accessions can regulate cellular homeostasis when encountering stress. Sixteen significant single nucleotide polymorphisms (SNPs) were identified by association mapping. Validation of candidate SNP using other FT-tolerant accessions revealed that SNP:2_21262165 might be associated with tolerance to FT; therefore, it could be used for SNP marker development. Among the candidate genes controlling FT tolerance, RAR1 encodes an innate immune responsive protein that links to cellular redox homeostasis via interacting with abiotic stress-responsive Hsp90. Future research may apply the knowledge obtained from this study in the molecular breeding program to develop FT-tolerant rice varieties.

A candidate gene association analysis identifies SNPs potentially involved in drought tolerance in European beech (Fagus sylvatica L.)

Studies of genetic variation underlying traits related to drought tolerance in forest trees are of great importance for understanding their adaptive potential under a climate change scenario. In this study, using a candidate gene approach, associations between SNPs and drought related traits were assessed in saplings of European beech (Fagus sylvatica L.) representing trees growing along steep precipitation gradients. The saplings were subjected to experimentally controlled drought treatments. Response of the saplings was assessed by the evaluation of stem diameter growth (SDG) and the chlorophyll fluorescence parameters FV/FM, PIabs, and PItot. The evaluation showed that saplings from xeric sites were less affected by the drought treatment. Five SNPs (7.14%) in three candidate genes were significantly associated with the evaluated traits; saplings with particular genotypes at these SNPs showed better performance under the drought treatment. The SNPs were located in the cytosolic class I small heat-shock protein, CTR/DRE binding transcription factor, and isocitrate dehydrogenase genes and explained 5.8-13.4% of the phenotypic variance. These findings provide insight into the genetic basis of traits related to drought tolerance in European beech and could support the development of forest conservation management strategies under future climatic conditions.

Genome-Wide Association Study of Root and Shoot Related Traits in Spring Soybean (Glycine max L.) at Seedling Stages Using SLAF-Seq

Root systems can display variable genetic architectures leading to nutrient foraging or improving abiotic stress tolerance. Breeding for new soybean varieties with efficient root systems has tremendous potential in enhancing resource use efficiency and plant adaptation for challenging climates. In this study, root related traits were analyzed in a panel of 260 spring soybean with genome-wide association study (GWAS). Genotyping was done with specific locus amplified fragment sequencing (SLAF-seq), and five GWAS models (GLM, MLM, CMLM, FaST-LMM, and EMMAX) were used for analysis. A total of 179,960 highly consistent SNP markers distributed over the entire genome with an inter-marker distance of 2.36 kb was used for GWAS analysis. Overall, 27 significant SNPs with a phenotypic contribution ranging from 20 to 72% and distributed on chromosomes 2, 6, 8, 9, 13, 16 and 18 were identified and two of them were found to be associated with multiple root-related traits. Based on the linkage disequilibrium (LD) distance of 9.5 kb for the different chromosomes, 11 root and shoot regulating genes were detected based on LD region of a maximum 55-bp and phenotypic contribution greater than 22%. Expression analysis revealed an association between expression levels of those genes and the degree of root branching number. The current study provides new insights into the genetic architecture of soybean roots, and the underlying SNPs/genes could be critical for future breeding of high-efficient root system in soybean.

Genetic Effects and Expression Patterns of the Nitrate Transporter (NRT) Gene Family in Populus tomentosa

Nitrate is an important source of nitrogen for poplar trees. The nitrate transporter (NRT) gene family is generally responsible for nitrate absorption and distribution. However, few analyses of the genetic effects and expression patterns of NRT family members have been conducted in woody plants. Here, using poplar as a model, we identified and characterized 98 members of the PtoNRT gene family. We calculated the phylogenetic and evolutionary relationships of the PtoNRT family and identified poplar-specific NRT genes and their expression patterns. To construct a core triple genetic network (association - gene expression - phenotype) for leaf nitrogen content, a candidate gene family association study, weighted gene co-expression network analysis (WGCNA), and mapping of expression quantitative trait nucleotides (eQTNs) were combined, using data from 435 unrelated Populus. tomentosa individuals. PtoNRT genes exhibited distinct expression patterns between twelve tissues, circadian rhythm points, and stress responses. The association study showed that genotype combinations of allelic variations of three PtoNRT genes had a strong effect on leaf nitrogen content. WGCNA produced two co-expression modules containing PtoNRT genes. We also found that four PtoNRT genes defined thousands of eQTL signals. WGCNA and eQTL provided comprehensive analysis of poplar nitrogen-related regulatory factors, including MYB17 and WRKY21. NRT genes were found to be regulated by five plant hormones, among which abscisic acid was the main regulator. Our study provides new insights into the NRT gene family in poplar and enables the exploitation of novel genetic factors to improve the nitrate use efficiency of trees.

Evolutionary network genomics of wood formation in a phylogenetic survey of angiosperm forest trees

Wood formation was present in early angiosperms, but has been highly modified through evolution to generate the anatomical diversity seen in extant angiosperm lineages. In this project, we modeled changes in gene coexpression relationships associated with the evolution of wood formation in a phylogenetic survey of 13 angiosperm tree species. Gravitropic stimulation was used as an experimental treatment to alter wood formation and also perturb gene expression. Gene transcript abundances were determined using RNA sequencing of developing wood tissues from upright trees, and from the top (tension wood) and bottom (opposite wood) tissues of gravistimulated trees. A network-based approach was employed to align gene coexpression networks across species based on orthologous relationships. A large-scale, multilayer network was modeled that identified both lineage-specific gene coexpression modules and modules conserved across multiple species. Functional annotation and analysis of modules identified specific regulatory processes associated with conserved modules, including regulation of hormones, protein phosphorylation, meristem development and epigenetic processes. Our results provide novel insights into the evolution and development of wood formation, and demonstrate the ability to identify biological processes and genes important for the evolution of a foundational trait in nonmodel, undomesticated forest trees.

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.

Designing a Mini-Core Collection Effectively Representing 3004 Diverse Rice Accessions

Genetic diversity provides the foundation for plant breeding and genetic research. Over 3000 rice genomes were recently sequenced as part of the 3K Rice Genome (3KRG) Project. We added four additional Indian rice accessions to create a panel of 3004 accessions. However, such a large collection of germplasm is difficult to preserve and evaluate. The construction of core and mini-core collections is an efficient method for the management of genetic resources. In this study, we developed a mini-core comprising 520 accessions that captured most of the SNPs and represented all of the phenotypes and geographic regions from the original panel. The mini-core was validated using different statistical analyses and contained representatives from all major rice groups, including japonica, indica, aus/boro, and aromatic/basmati. Genome-wide association analyses of the mini-core panel efficiently reproduced the marker-trait associations identified in the original panel. Haplotype analysis validated the utility of the mini-core panel. In the current era with many ongoing large-scale sequencing projects, such a strategy for mini-core design should be useful in many crops. The rice mini-core collection developed in this study would be valuable for agronomic trait evaluation and useful for rice improvement via marker-assisted molecular breeding.

Identification of resistance loci in Chinese and Canadian canola/rapeseed varieties against Leptosphaeria maculans based on genome-wide association studies

Background

The fungal pathogen Leptosphaeria maculans (Lm). causes blackleg disease on canola/rapeseed in many parts of the world. It is important to use resistant cultivars to manage the disease and minimize yield losses. In this study, twenty-two Lm isolates were used to identify resistance genes in a collection of 243 canola/rapeseed (Brassica napus L.) accessions from Canada and China. These Lm isolates carry different compliments of avirulence genes, and the investigation was based on a genome-wide association study (GWAS) and genotype-by-sequencing (GBS).

Results

Using the CROP-SNP pipeline, a total of 81,471 variants, including 78,632 SNPs and 2839 InDels, were identified. The GWAS was performed using TASSEL 5.0 with GLM + Q model. Thirty-two and 13 SNPs were identified from the Canadian and Chinese accessions, respectively, tightly associated with blackleg resistance with P values < 1 × 10^− 4. These SNP loci were distributed on chromosomes A03, A05, A08, A09, C01, C04, C05, and C07, with the majority of them on A08 followed by A09 and A03. The significant SNPs identified on A08 were all located in a 2010-kb region and associated with resistance to 12 of the 22 Lm isolates. Furthermore, 25 resistance gene analogues (RGAs) were identified in these regions, including two nucleotide binding site (NBS) domain proteins, fourteen RLKs, three RLPs and six TM-CCs. These RGAs can be the potential candidate genes for blackleg resistance.

Conclusion

This study provides insights into potentially new genomic regions for discovery of additional blackleg resistance genes. The identified regions associated with blackleg resistance in the germplasm collection may also contribute directly to the development of canola varieties with novel resistance genes against blackleg of canola.

Genome-wide association mapping reveals loci for shelf life and developmental rate of lettuce

KEY MESSAGE

Two major QTL, one for shelf life that corresponds to qSL4 and one, qDEV7, for developmental rate, were identified. Associated markers will be useful in breeding for improved fresh-cut lettuce. Fresh-cut lettuce in packaged salad can have short shelf life, and visible deterioration may start within a week after processing. Yield and developmental rate are an important aspect of lettuce production. Genetic diversity and genome-wide association studies (GWAS) were performed on 493 accessions with the genotypic data of 4615 high-quality single nucleotide polymorphism markers. Population structure (Q), principal component (PC), and phylogenetic analyses displayed genetic relationships associated with lettuce types and geographic distribution. Data for shelf life, yield, developmental rate, and their stability indices were used for statistical analysis, and GWAS was performed by general and mixed linear models. The genetic relationship among the individuals was incorporated into the models using kinship matrix, PC, and Q. Broad-sense heritability (H2) across environments was 0.43 for shelf life, 0.36 for yield, and 0.60 for developmental rate. There was a negative correlation between yield and developmental rate. Significant marker-trait association (SMTA) was detected for shelf life on chromosome 4. The most significant quantitative trait locus (QTL,  qSL4, P = 2.23E-17) explained 24% of the total phenotypic variation (R2). The major QTL for developmental rate was detected on chromosome 7 (qDEV7, P = 2.43E-16, R2 = 17%), while additional QTLs with smaller effect were found in all chromosomes. No SMTA was detected for yield. The study identified lettuce accessions with extended and stable shelf life, stable yield, and desirable developmental rate. Molecular markers closely linked to traits can be applied for selection of preferable genotypes and for identification of genes associated with these traits.

Genomics-assisted breeding for pigeonpea improvement

The review outlines advances in pigeonpea genomics, breeding and seed delivery systems to achieve yield gains at farmers' field. Pigeonpea is a nutritious and stress-tolerant grain legume crop of tropical and subtropical regions. Decades of breeding efforts in pigeonpea have resulted in development of a number of high-yielding cultivars. Of late, the development of CMS-based hybrid technology has allowed the exploitation of heterosis for yield enhancement in this crop. Despite these positive developments, the actual on-farm yield of pigeonpea is still well below its potential productivity. Growing needs for high and sustainable pigeonpea yields motivate scientists to improve the breeding efficiency to deliver a steady stream of cultivars that will provide yield benefits under both ideal and stressed environments. To achieve this objective in the shortest possible time, it is imperative that various crop breeding activities are integrated with appropriate new genomics technologies. In this context, the last decade has seen a remarkable rise in the generation of important genomic resources such as genome-wide markers, high-throughput genotyping assays, saturated genome maps, marker/gene-trait associations, whole-genome sequence and germplasm resequencing data. In some cases, marker/gene-trait associations are being employed in pigeonpea breeding programs to improve the valuable yield and market-preferred traits. Embracing new breeding tools like genomic selection and speed breeding is likely to improve genetic gains. Breeding high-yielding pigeonpea cultivars with key adaptation traits also calls for a renewed focus on systematic selection and utilization of targeted genetic resources. Of equal importance is to overcome the difficulties being faced by seed industry to take the new cultivars to the doorstep of farmers.

Photons to food: genetic improvement of cereal crop photosynthesis

Photosynthesis has become a major trait of interest for cereal yield improvement as breeders appear to have reached the theoretical genetic limit for harvest index, the mass of grain as a proportion of crop biomass. Yield improvements afforded by the adoption of green revolution dwarfing genes to wheat and rice are becoming exhausted, and improvements in biomass and radiation use efficiency are now sought in these crops. Exploring genetic diversity in photosynthesis is now possible using high-throughput techniques, and low-cost genotyping facilitates discovery of the genetic architecture underlying this variation. Photosynthetic traits have been shown to be highly heritable, and significant variation is present for these traits in available germplasm. This offers hope that breeding for improved photosynthesis and radiation use efficiency in cereal crops is tractable and a useful shorter term adjunct to genetic and genome engineering to boost yield potential.

Genome-Wide Association Study Identifies Single Nucleotide Polymorphism Markers Associated with Mycelial Growth (at 15, 20, and 25°C), Mefenoxam Resistance, and Mating Type in Phytophthora infestans

Phenotypic diversity among individuals defines the potential for evolutionary selection in a species. Phytophthora infestans epidemics are generally thought to be favored by moderate to low temperatures, but temperatures in many locations worldwide are expected to rise as a result of global climate change. Thus, we investigated variation among individuals of P. infestans for relative growth at different temperatures. Isolates of P. infestans came from three collections: (i) individual genotypes recently dominant in the United States, (ii) recently collected individuals from Central Mexico, and (iii) progeny of a recent sexual recombination event in the northeastern United States. In general, these isolates had optimal mycelial growth rates at 15 or 20°C. However, two individuals from Central Mexico grew better at higher temperatures than did most others and two individuals grew relatively less at higher temperatures than did most others. The isolates were also assessed for mefenoxam sensitivity and mating type. Each collection contained individuals of diverse sensitivities to mefenoxam and individuals of the A1 and A2 mating type. We then searched for genomic regions associated with phenotypic diversity using genotyping-by-sequencing. We found one single nucleotide polymorphism (SNP) associated with variability in mycelial growth at 20°C, two associated with variability in mycelial growth at 25°C, two associated with sensitivity to mefenoxam, and one associated with mating type. Interestingly, the SNPs associated with mefenoxam sensitivity were found in a gene-sparse region, whereas the SNPs associated with growth at the two temperatures and mating type were found both at more gene-dense regions.

Genetic dissection of the gene coexpression network underlying photosynthesis in Populus

Photosynthesis is a key reaction that ultimately generates the carbohydrates needed to form woody tissues in trees. However, the genetic regulatory network of protein-encoding genes (PEGs) and regulatory noncoding RNAs (ncRNAs), including microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), underlying the photosynthetic pathway is unknown. Here, we integrated data from coexpression analysis, association studies (additive, dominance and epistasis), and expression quantitative trait nucleotide (eQTN) mapping to dissect the causal variants and genetic interaction network underlying photosynthesis in Populus. We initially used 30 PEGs, 6 miRNAs and 12 lncRNAs to construct a coexpression network based on the tissue-specific gene expression profiles of 15 Populus samples. Then, we performed association studies using a natural population of 435 unrelated Populus tomentosa individuals, and identified 72 significant associations (P ≤ 0.001, q ≤ 0.05) with diverse additive and dominance patterns underlying photosynthesis-related traits. Analysis of epistasis and eQTNs revealed that the complex genetic interactions in the coexpression network contribute to phenotypes at various levels. Finally, we demonstrated that heterologously expressing the most highly linked gene (PtoPsbX1) in this network significantly improved photosynthesis in Arabidopsis thaliana, pointing to the functional role of PtoPsbX1 in the photosynthetic pathway. This study provides an integrated strategy for dissecting a complex genetic interaction network, which should accelerate marker-assisted breeding efforts to genetically improve woody plants.

Variance heterogeneity genome-wide mapping for cadmium in bread wheat reveals novel genomic loci and epistatic interactions

Genome-wide association mapping identifies quantitative trait loci (QTL) that influence the mean differences between the marker genotypes for a given trait. While most loci influence the mean value of a trait, certain loci, known as variance heterogeneity QTL (vQTL) determine the variability of the trait instead of the mean trait value (mQTL). In the present study, we performed a variance heterogeneity genome-wide association study (vGWAS) for grain cadmium (Cd) concentration in bread wheat. We used double generalized linear model and hierarchical generalized linear model to identify vQTL associated with grain Cd. We identified novel vQTL regions on chromosomes 2A and 2B that contribute to the Cd variation and loci that affect both mean and variance heterogeneity (mvQTL) on chromosome 5A. In addition, our results demonstrated the presence of epistatic interactions between vQTL and mvQTL, which could explain variance heterogeneity. Overall, we provide novel insights into the genetic architecture of grain Cd concentration and report the first application of vGWAS in wheat. Moreover, our findings indicated that epistasis is an important mechanism underlying natural variation for grain Cd concentration.

A genome-wide association study uncovers consistent quantitative trait loci for resistance to Verticillium wilt and Fusarium wilt race 4 in the US Upland cotton

A high-resolution GWAS detected consistent QTL for resistance to Verticillium wilt and Fusarium wilt race 4 in 376 U.S. Upland cotton accessions based on six independent replicated greenhouse tests. Verticillium wilt (VW, caused by Verticillium dahliae Kleb.) and Fusarium wilt (FOV, caused by Fusarium oxysporum f.sp. vasinfectum Atk. Sny & Hans) are the most important soil-borne fungal diseases in cotton. To augment and refine resistance quantitative trait loci (QTL), we conducted a genome-wide association study (GWAS) using high-density genotyping with the CottonSNP63K array. Resistance of 376 US Upland cotton accessions to a defoliating VW and virulent FOV4 was evaluated in four and two independent replicated greenhouse tests, respectively. A total of 15 and 13 QTL for VW and FOV4 resistances were anchored by 30 (on five chromosomes) and 56 (on six chromosomes) significant single nucleotide polymorphic (SNPs) markers, respectively. QTL on c8, c10, c16, and c21 were consistent in two or more tests for VW resistance, while two QTL on c8 and c14 were consistent for FOV4 resistance in two tests. Two QTL clusters on c16 and c19 were observed for both VW and FOV4 resistance, suggesting that these genomic regions may harbor genes in response to both diseases. Using BLAST search against the sequenced TM-1 genome, 30 and 35 candidate genes were identified on four QTL for VW resistance and on three QTL for FOV4 resistance, respectively. These genomic regions were rich in NBS-LRR genes presented in clusters. The results create opportunities for further studies to determine the correlations of field resistance with these QTL, molecular examinations of VW and FOV4 resistances, marker-assisted selection (MAS) and eventual cloning of QTL for disease resistance in cotton.

Genome-Wide Association Study of Wood Anatomical and Morphological Traits in Populus trichocarpa

To understand the genetic mechanisms underlying wood anatomical and morphological traits in Populus trichocarpa, we used 869 unrelated genotypes from a common garden in Clatskanie, Oregon that were previously collected from across the distribution range in western North America. Using GEMMA mixed model analysis, we tested for the association of 25 phenotypic traits and nine multitrait combinations with 6.741 million SNPs covering the entire genome. Broad-sense trait heritabilities ranged from 0.117 to 0.477. Most traits were significantly correlated with geoclimatic variables suggesting a role of climate and geography in shaping the variation of this species. Fifty-seven SNPs from single trait GWAS and 11 SNPs from multitrait GWAS passed an FDR threshold of 0.05, leading to the identification of eight and seven nearby candidate genes, respectively. The percentage of phenotypic variance explained (PVE) by the significant SNPs for both single and multitrait GWAS ranged from 0.01% to 6.18%. To further evaluate the potential roles of candidate genes, we used a multi-omic network containing five additional data sets, including leaf and wood metabolite GWAS layers and coexpression and comethylation networks. We also performed a functional enrichment analysis on coexpression nearest neighbors for each gene model identified by the wood anatomical and morphological trait GWAS analyses. Genes affecting cell wall composition and transport related genes were enriched in wood anatomy and stomatal density trait networks. Signaling and metabolism related genes were also common in networks for stomatal density. For leaf morphology traits (leaf dry and wet weight) the networks were significantly enriched for GO terms related to photosynthetic processes as well as cellular homeostasis. The identified genes provide further insights into the genetic control of these traits, which are important determinants of the suitability and sustainability of improved genotypes for lignocellulosic biofuel production.

Genome-Wide Association Study and QTL Meta-Analysis Identified Novel Genomic Loci Controlling Potassium Use Efficiency and Agronomic Traits in Bread Wheat

Potassium use efficiency, a complex trait, directly impacts the yield potential of crop plants. Low potassium efficiency leads to a high use of fertilizers, which is not only farmer unfriendly but also deteriorates the environment. Genome-wide association studies (GWAS) are widely used to dissect complex traits. However, most studies use single-locus one-dimensional GWAS models which do not provide true information about complex traits that are controlled by multiple loci. Here, both single-locus GWAS (MLM) and multi-locus GWAS (pLARmEB, FASTmrMLM, mrMLM, FASTmrEMMA) models were used with genotyping from 90 K Infinium SNP array and phenotype derived from four normal and potassium-stress environments, which identified 534 significant marker-trait associations (MTA) for agronomic and potassium related traits: pLARmEB = 279, FASTmrMLM = 213, mrMLM = 35, MLM = 6, FASTmrEMMA = 1. Further screening of these MTA led to the detection of eleven stable loci: q1A, q1D, q2B-1, q2B-2, q2D, q4D, q5B-1, q5B-2, q5B-3, q6D, and q7A. Moreover, Meta-QTL (MQTL) analysis of four independent QTL studies for potassium deficiency in bread wheat located 16 MQTL on 13 chromosomes. One locus identified in this study (q5B-1) colocalized with an MQTL (MQTL_{_11} ), while the other ten loci were novel associations. Gene ontology of these loci identified 20 putative candidate genes encoding functional proteins involved in key pathways related to stress tolerance, sugar metabolism, and nutrient transport. These findings provide potential targets for breeding potassium stress resistant wheat cultivars and advocate the advantages of multi-locus GWAS models for studying complex traits.

Genome-Wide Correlation of 36 Agronomic Traits in the 287 Pepper (Capsicum) Accessions Obtained from the SLAF-seq-Based GWAS

There are many agronomic traits of pepper (Capsicum L.) with abundant phenotypes that can benefit pepper growth. Using specific-locus amplified fragment sequencing (SLAF-seq), a genome-wide association study (GWAS) of 36 agronomic traits was carried out for 287 representative pepper accessions. To ensure the accuracy and reliability of the GWAS results, we analyzed the genetic diversity, distribution of labels (SLAF tags and single nucleotide polymorphisms (SNPs)) and population differentiation and determined the optimal statistical model. In our study, 1487 SNPs were highly significantly associated with 26 agronomic traits, and 2126 candidate genes were detected in the 100-kb region up- and down-stream near these SNPs. Furthermore, 13 major association peaks were identified for 11 key agronomic traits. Then we examined the correlations among the 36 agronomic traits and analyzed SNP distribution and found 37 SNP polymerization regions (total size: 264.69 Mbp) that could be selected areas in pepper breeding. We found that the stronger the correlation between the two traits, the greater the possibility of them being in more than one polymerization region, suggesting that they may be linked or that one pleiotropic gene controls them. These results provide a theoretical foundation for future multi-trait pyramid breeding of pepper. Finally, we found that the GWAS signals were highly consistent with those from the nuclear restorer-of-fertility (Rf) gene for cytoplasmic male sterility (CMS), verifying their reliability. We further identified Capana06g002967 and Capana06g002969 as Rf candidate genes by functional annotation and expression analysis, which provided a reference for the study of cytoplasmic male sterility in Capsicum.

To clean or not to clean phenotypic datasets for outlier plants in genetic analyses?

Based on case studies, we discuss the extent to which genome-wide association studies (GWAS) are affected by outlier plants, i.e. those deviating from the expected distribution on a multi-criteria basis. Using a raw dataset consisting of daily measurements of leaf area, biomass, and plant height for thousands of plants, we tested three different cleaning methods for their effects on genetic analyses. No-cleaning resulted in the highest number of dubious quantitative trait loci, especially at loci with highly unbalanced allelic frequencies. A trade-off was identified between the risk of false-positives (with no-cleaning and/or a low threshold for minor allele frequency) and the risk of missing interesting rare alleles. Cleaning can lower the risk of the latter by making it possible to choose a higher threshold in GWAS.

Genetic architecture of maize chlorotic mottle virus and maize lethal necrosis through GWAS, linkage analysis and genomic prediction in tropical maize germplasm

KEY MESSAGE

Analysis of the genetic architecture of MCMV and MLN resistance in maize doubled-haploid populations revealed QTLs with major effects on chromosomes 3 and 6 that were consistent across genetic backgrounds and environments. Two major-effect QTLs, qMCMV3-108/qMLN3-108 and qMCMV6-17/qMLN6-17, were identified as conferring resistance to both MCMV and MLN. Maize lethal necrosis (MLN) is a serious threat to the food security of maize-growing smallholders in sub-Saharan Africa. The ability of the maize chlorotic mottle virus (MCMV) to interact with other members of the Potyviridae causes severe yield losses in the form of MLN. The objective of the present study was to gain insights and validate the genetic architecture of resistance to MCMV and MLN in maize. We applied linkage mapping to three doubled-haploid populations and a genome-wide association study (GWAS) on 380 diverse maize lines. For all the populations, phenotypic variation for MCMV and MLN was significant, and heritability was moderate to high. Linkage mapping revealed 13 quantitative trait loci (QTLs) for MCMV resistance and 12 QTLs conferring MLN resistance. One major-effect QTL, qMCMV3-108/qMLN3-108, was consistent across populations for both MCMV and MLN resistance. Joint linkage association mapping (JLAM) revealed 18 and 21 main-effect QTLs for MCMV and MLN resistance, respectively. Another major-effect QTL, qMCMV6-17/qMLN6-17, was detected for both MCMV and MLN resistance. The GWAS revealed a total of 54 SNPs (MCMV-13 and MLN-41) significantly associated (P ≤ 5.60 × 10-05) with MCMV and MLN resistance. Most of the GWAS-identified SNPs were within or adjacent to the QTLs detected through linkage mapping. The prediction accuracy for within populations as well as the combined populations is promising; however, the accuracy was low across populations. Overall, MCMV resistance is controlled by a few major and many minor-effect loci and seems more complex than the genetic architecture for MLN resistance.

Transcription factors involved in the regulatory networks governing the Calvin-Benson-Bassham cycle

Transcription factors (TFs) play crucial roles in the regulation of photosynthesis; elucidating these roles will facilitate our understanding of photosynthesis and thus accelerate its improvement for enhancing crop yield. Promoter analysis of 52 nuclear-encoded Populus tomentosa Carr. genes involved in the Calvin-Benson-Bassham (CBB) cycle revealed 706 motifs and 326 potentially interacting TFs. A backward elimination random forest (BWERF) algorithm reduced the number of TFs to 40, involved in a three-layer gene regulatory network (GRN) including 46 photosynthesis genes (bottom layer), 25 TFs (second layer) and 15 TFs (top layer). Phenotype-genotype association identified 248 single-nucleotide polymorphisms (SNPs) within 72 genes associated with 11 photosynthesis traits. Of the regulatory pairs identified by the BWERF (202 pairs), 77 TF-target combinations harbored SNPs associated with the same trait, supporting similar mechanisms of phenotype modulation. We used expression quantitative trait nucleotide (eQTN) analysis to identify causal SNPs affecting gene expression, identifying 1851 eQTN signals for 50 eGenes (genes whose expressions are regulated by eQTNs). Distribution patterns identified 14 eQTNs from seven TFs associated with eight expression levels of their downstream targets (defined in the GRN), whereas seven TF-target pairs were also identified by phenotype-genotype associations. To further validate the roles of TFs at the metabolic level, we selected 6764 SNPs from 55 genes (identified by GRN-association or GRN-eQTN pairs or both) for metabolic association, identifying variants within 10 TFs affecting metabolic processes underlying the CBB cycle. Our study provides new insights into the photosynthesis pathway in poplar and may facilitate understanding of processes underlying photosynthesis improvement.

Linking plant genes to insect communities: Identifying the genetic bases of plant traits and community composition

Community genetics aims to understand the effects of intraspecific genetic variation on community composition and diversity, thereby connecting community ecology with evolutionary biology. Thus far, research has shown that plant genetics can underlie variation in the composition of associated communities (e.g., insects, lichen and endophytes), and those communities can therefore be considered as extended phenotypes. This work, however, has been conducted primarily at the plant genotype level and has not identified the key underlying genes. To address this gap, we used genome-wide association mapping with a population of 445 aspen (Populus tremuloides) genets to identify the genes governing variation in plant traits (defence chemistry, bud phenology, leaf morphology, growth) and insect community composition. We found 49 significant SNP associations in 13 Populus genes that are correlated with chemical defence compounds and insect community traits. Most notably, we identified an early nodulin-like protein that was associated with insect community diversity and the abundance of interacting foundation species (ants and aphids). These findings support the concept that particular plant traits are the mechanistic link between plant genes and the composition of associated insect communities. In putting the "genes" into "genes to ecosystems ecology", this work enhances understanding of the molecular genetic mechanisms that underlie plant-insect associations and the consequences thereof for the structure of ecological communities.

Multitrait genome-wide association analysis of Populus trichocarpa identifies key polymorphisms controlling morphological and physiological traits

Genome-wide association studies (GWAS) have great promise for identifying the loci that contribute to adaptive variation, but the complex genetic architecture of many quantitative traits presents a substantial challenge. We measured 14 morphological and physiological traits and identified single nucleotide polymorphism (SNP)-phenotype associations in a Populus trichocarpa population distributed from California, USA to British Columbia, Canada. We used whole-genome resequencing data of 882 trees with more than 6.78 million SNPs, coupled with multitrait association to detect polymorphisms with potentially pleiotropic effects. Candidate genes were validated with functional data. Broad-sense heritability (H² ) ranged from 0.30 to 0.56 for morphological traits and 0.08 to 0.36 for physiological traits. In total, 4 and 20 gene models were detected using the single-trait and multitrait association methods, respectively. Several of these associations were corroborated by additional lines of evidence, including co-expression networks, metabolite analyses, and direct confirmation of gene function through RNAi. Multitrait association identified many more significant associations than single-trait association, potentially revealing pleiotropic effects of individual genes. This approach can be particularly useful for challenging physiological traits such as water-use efficiency or complex traits such as leaf morphology, for which we were able to identify credible candidate genes by combining multitrait association with gene co-expression and co-methylation data.

A new genomic tool for walnut (Juglans regia L.): development and validation of the high-density Axiom™ J. regia 700K SNP genotyping array

Over the last 20 years, global production of Persian walnut (Juglans regia L.) has grown enormously, likely reflecting increased consumption due to its numerous benefits to human health. However, advances in genome-wide association (GWA) studies and genomic selection (GS) for agronomically important traits in walnut remain limited due to the lack of powerful genomic tools. Here, we present the development and validation of a high-density 700K single nucleotide polymorphism (SNP) array in Persian walnut. Over 609K high-quality SNPs have been thoroughly selected from a set of 9.6 m genome-wide variants, previously identified from the high-depth re-sequencing of 27 founders of the Walnut Improvement Program (WIP) of University of California, Davis. To validate the effectiveness of the array, we genotyped a collection of 1284 walnut trees, including 1167 progeny of 48 WIP families and 26 walnut cultivars. More than half of the SNPs (55.7%) fell in the highest quality class of 'Poly High Resolution' (PHR) polymorphisms, which were used to assess the WIP pedigree integrity. We identified 151 new parent-offspring relationships, all confirmed with the Mendelian inheritance test. In addition, we explored the genetic variability among cultivars of different origin, revealing how the varieties from Europe and California were differentiated from Asian accessions. Both the reconstruction of the WIP pedigree and population structure analysis confirmed the effectiveness of the Applied Biosystems™ Axiom™ J. regia 700K SNP array, which initiates a novel genomic and advanced phase in walnut genetics and breeding.

Genetic analyses of nitrogen assimilation enzymes in Brassica juncea (L.) Czern & Coss

Nitrogen (N) is a critical input for plant growth and development. A better understanding of N uptake and utilization is important to develop plant breeding strategies for improving nitrogen use efficiency (NUE). With that objective in mind, we assayed a SNP-genotyped association panel comprising 92 inbred lines for the activities of nitrate reductase (NR), nitrite reductase (NIR), glutamine synthetase (GS) and glutamate synthase (GOGAT). All these enzymes are associated with N assimilation. The experiments were carried out at two levels of N application: no added N (N₀) and agrnomically recommened dose (100 kg/ha) of N application (N₁₀₀). Genome wide association studies (GWAS) helped to identify several marker-trait associations (MTAs), involving chromosomes A01, A06, A08, B02, B04, B05 and B08. These explained high phenotypic variation (up to 32%). Annotation of the genomic region(s) in or around significant SNPs allowed prediction of genes encoding high affinity nitrate transporters, glutamine synthetase 1.3, myb-like transcription factor family protein, bidirectional amino acid transporter 1, auxin signaling F-box 3 and oxidoreductases. This is the first attempt to use GWAS for identification of enzyme QTLs to explain variation for nitrogen assimilation enzymes in Brassica juncea.

Development of a highly efficient Axiom™ 70 K SNP array for Pyrus and evaluation for high-density mapping and germplasm characterization

Background

Both a source of diversity and the development of genomic tools, such as reference genomes and molecular markers, are equally important to enable faster progress in plant breeding. Pear (Pyrus spp.) lags far behind other fruit and nut crops in terms of employment of available genetic resources for new cultivar development. To address this gap, we designed a high-density, high-efficiency and robust single nucleotide polymorphism (SNP) array for pear, with the main objectives of conducting genetic diversity and genome-wide association studies.

Results

By applying a two-step design process, which consisted of the construction of a first ‘draft’ array for the screening of a small subset of samples, we were able to identify the most robust and informative SNPs to include in the Applied Biosystems™ Axiom™ Pear 70 K Genotyping Array, currently the densest SNP array for pear. Preliminary evaluation of this 70 K array in 1416 diverse pear accessions from the USDA National Clonal Germplasm Repository (NCGR) in Corvallis, OR identified 66,616 SNPs (93% of all the tiled SNPs) as high quality and polymorphic (PolyHighResolution). We further used the Axiom Pear 70 K Genotyping Array to construct high-density linkage maps in a bi-parental population, and to make a direct comparison with available genotyping-by-sequencing (GBS) data, which suggested that the SNP array is a more robust method of screening for SNPs than restriction enzyme reduced representation sequence-based genotyping.

Conclusions

The Axiom Pear 70 K Genotyping Array, with its high efficiency in a widely diverse panel of Pyrus species and cultivars, represents a valuable resource for a multitude of molecular studies in pear. The characterization of the USDA-NCGR collection with this array will provide important information for pear geneticists and breeders, as well as for the optimization of conservation strategies for Pyrus.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5712-3) contains supplementary material, which is available to authorized users.

Identification and characterization of metabolite quantitative trait loci in tomato leaves and comparison with those reported for fruits and seeds

INTRODUCTION

To date, most studies of natural variation and metabolite quantitative trait loci (mQTL) in tomato have focused on fruit metabolism, leaving aside the identification of genomic regions involved in the regulation of leaf metabolism.

OBJECTIVE

This study was conducted to identify leaf mQTL in tomato and to assess the association of leaf metabolites and physiological traits with the metabolite levels from other tissues.

METHODS

The analysis of components of leaf metabolism was performed by phenotypying 76 tomato ILs with chromosome segments of the wild species Solanum pennellii in the genetic background of a cultivated tomato (S. lycopersicum) variety M82. The plants were cultivated in two different environments in independent years and samples were harvested from mature leaves of non-flowering plants at the middle of the light period. The non-targeted metabolite profiling was obtained by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). With the data set obtained in this study and already published metabolomics data from seed and fruit, we performed QTL mapping, heritability and correlation analyses.

RESULTS

Changes in metabolite contents were evident in the ILs that are potentially important with respect to stress responses and plant physiology. By analyzing the obtained data, we identified 42 positive and 76 negative mQTL involved in carbon and nitrogen metabolism.

CONCLUSIONS

Overall, these findings allowed the identification of S. lycopersicum genome regions involved in the regulation of leaf primary carbon and nitrogen metabolism, as well as the association of leaf metabolites with metabolites from seeds and fruits.