New Strategies and Tools in Quantitative Genetics: How to Go from the Phenotype to the Genotype

Multiomics Analyses Reveal the Dual Role of Flavonoids in Pigmentation and Abiotic Stress Tolerance of Soybean Seeds

The color of the seed coat has great diversity and is regarded as a biomarker of metabolic variations. Here we isolated a soybean variant (BLK) from a population of recombinant inbred lines with a black seed coat, while its sibling plants have yellow seed coats (YL). The BLK and YL plants showed no obvious differences in vegetative growth and seed weight. However, the BLK seeds had higher anthocyanins and flavonoids level and showed tolerance to various abiotic stresses including herbicide, oxidation, salt, and alkalinity during germination. Integrated metabolomic and transcriptomic analyses revealed that the upregulation of biosynthetic genes probably contributed to the overaccumulation of flavonoids in BLK seeds. The transient expression of those biosynthetic genes in soybean root hairs increased the levels of total flavonoids or anthocyanins. Our study revealed the molecular basis of flavonoid accumulation in soybean seeds, leveraging genetic engineering for both nutritious and stress-tolerant soybean germplasm.

Whole genome scanning of a Mediterranean basin hotspot collection provides new insights into olive tree biodiversity and biology

Olive tree (Olea europaea L. subsp. europaea var. europaea) is one of the most important species of the Mediterranean region and one of the most ancient species domesticated. The availability of whole genome assemblies and annotations of olive tree cultivars and oleaster (O. europaea subsp. europaea var. sylvestris) has contributed to a better understanding of genetic and genomic differences between olive tree cultivars. However, compared to other plant species there is still a lack of genomic resources for olive tree populations that span the entire Mediterranean region. In the present study we developed the most complete genomic variation map and the most comprehensive catalog/resource of molecular variation to date for 89 olive tree genotypes originating from the entire Mediterranean basin, revealing the genetic diversity of this commercially significant crop tree and explaining the divergence/similarity among different variants. Additionally, the monumental ancient tree 'Throuba Naxos' was studied to characterize the potential origin or routes of olive tree domestication. Several candidate genes known to be associated with key agronomic traits, including olive oil quality and fruit yield, were uncovered by a selective sweep scan to be under selection pressure on all olive tree chromosomes. To further exploit the genomic and phenotypic resources obtained from the current work, genome-wide association analyses were performed for 23 morphological and two agronomic traits. Significant associations were detected for eight traits that provide valuable candidates for fruit tree breeding and for deeper understanding of olive tree biology.

QTG-Miner aids rapid dissection of the genetic base of tassel branch number in maize

Genetic dissection of agronomic traits is important for crop improvement and global food security. Phenotypic variation of tassel branch number (TBN), a major breeding target, is controlled by many quantitative trait loci (QTLs). The lack of large-scale QTL cloning methodology constrains the systematic dissection of TBN, which hinders modern maize breeding. Here, we devise QTG-Miner, a multi-omics data-based technique for large-scale and rapid cloning of quantitative trait genes (QTGs) in maize. Using QTG-Miner, we clone and verify seven genes underlying seven TBN QTLs. Compared to conventional methods, QTG-Miner performs well for both major- and minor-effect TBN QTLs. Selection analysis indicates that a substantial number of genes and network modules have been subjected to selection during maize improvement. Selection signatures are significantly enriched in multiple biological pathways between female heterotic groups and male heterotic groups. In summary, QTG-Miner provides a large-scale approach for rapid cloning of QTGs in crops and dissects the genetic base of TBN for further maize breeding.

Artificial selection reveals complex genetic architecture of shoot branching and its response to nitrate supply in Arabidopsis

Quantitative traits may be controlled by many loci, many alleles at each locus, and subject to genotype-by-environment interactions, making them difficult to map. One example of such a complex trait is shoot branching in the model plant Arabidopsis, and its plasticity in response to nitrate. Here, we use artificial selection under contrasting nitrate supplies to dissect the genetic architecture of this complex trait, where loci identified by association mapping failed to explain heritability estimates. We found a consistent response to selection for high branching, with correlated responses in other traits such as plasticity and flowering time. Genome-wide scans for selection and simulations suggest that at least tens of loci control this trait, with a distinct genetic architecture between low and high nitrate treatments. While signals of selection could be detected in the populations selected for high branching on low nitrate, there was very little overlap in the regions selected in three independent populations. Thus the regulatory network controlling shoot branching can be tuned in different ways to give similar phenotypes.

Investigating the genetic components of tuber bruising in a breeding population of tetraploid potatoes

BACKGROUND

Tuber bruising in tetraploid potatoes (Solanum tuberosum) is a trait of economic importance, as it affects tubers' fitness for sale. Understanding the genetic components affecting tuber bruising is a key step in developing potato lines with increased resistance to bruising. As the tetraploid setting renders genetic analyses more complex, there is still much to learn about this complex phenotype. Here, we used capture sequencing data on a panel of half-sibling populations from a breeding programme to perform a genome-wide association analysis (GWAS) for tuber bruising. In addition, we collected transcriptomic data to enrich the GWAS results. However, there is currently no satisfactory method to represent both GWAS and transcriptomics analysis results in a single visualisation and to compare them with existing knowledge about the biological system under study.

RESULTS

When investigating population structure, we found that the STRUCTURE algorithm yielded greater insights than discriminant analysis of principal components (DAPC). Importantly, we found that markers with the highest (though non-significant) association scores were consistent with previous findings on tuber bruising. In addition, new genomic regions were found to be associated with tuber bruising. The GWAS results were backed by the transcriptomics differential expression analysis. The differential expression notably highlighted for the first time the role of two genes involved in cellular strength and mechanical force sensing in tuber resistance to bruising. We proposed a new visualisation, the HIDECAN plot, to integrate the results from the genomics and transcriptomics analyses, along with previous knowledge about genomic regions and candidate genes associated with the trait.

CONCLUSION

This study offers a unique genome-wide exploration of the genetic components of tuber bruising. The role of genetic components affecting cellular strength and resistance to physical force, as well as mechanosensing mechanisms, was highlighted for the first time in the context of tuber bruising. We showcase the usefulness of genomic data from breeding programmes in identifying genomic regions whose association with the trait of interest merit further investigation. We demonstrate how confidence in these discoveries and their biological relevance can be increased by integrating results from transcriptomics analyses. The newly proposed visualisation provides a clear framework to summarise of both genomics and transcriptomics analyses, and places them in the context of previous knowledge on the trait of interest.

Rapid identification of a major locus qPRL-C06 affecting primary root length in Brassica napus by QTL-seq

BACKGROUND AND AIMS

Brassica napus is one of the most important oilseed crops worldwide. Seed yield of B. napus significantly correlates with the primary root length (PRL). The aims of this study were to identify quantitative trait loci (QTLs) for PRL in B. napus.

METHODS

QTL-seq and conventional QTL mapping were jointly used to detect QTLs associated with PRL in a B. napus double haploid (DH) population derived from a cross between 'Tapidor' and 'Ningyou 7'. The identified major locus was confirmed and resolved by an association panel of B. napus and an advanced backcross population. RNA-seq analysis of two long-PRL lines (Tapidor and TN20) and two short-PRL lines (Ningyou 7 and TN77) was performed to identify differentially expressed genes in the primary root underlying the target QTLs.

KEY RESULTS

A total of 20 QTLs impacting PRL in B. napus grown at a low phosphorus (P) supply were found by QTL-seq. Eight out of ten QTLs affecting PRL at a low P supply discovered by conventional QTL mapping could be detected by QTL-seq. The locus qPRL-C06 identified by QTL-seq was repeatedly detected at both an optimal P supply and a low P supply by conventional QTL mapping. This major constitutive QTL was further confirmed by regional association mapping. qPRL-C06 was delimited to a 0.77 Mb genomic region on chromosome C06 using an advanced backcross population. A total of 36 candidate genes within qPRL-C06 were identified that showed variations in coding sequences and/or exhibited significant differences in mRNA abundances in primary root between the long-PRL and short-PRL lines, including five genes involved in phytohormone biosynthesis and signaling.

CONCLUSIONS

These results both demonstrate the power of the QTL-seq in rapid QTL detection for root traits and will contribute to marker-assisted selective breeding of B. napus cultivars with increased PRL.

Marginal leaf galls on Pliocene leaves from India indicate mutualistic behavior between Ipomoea plants and Eriophyidae mites

We report a new type of fossil margin galls arranged in a linear series on dicot leaf impressions from the latest Neogene (Pliocene) sediments of the Chotanagpur Plateau, Jharkhand, eastern India. We collected ca. 1500 impression and compression leaf fossils, of which 1080 samples bear arthropod damage referable to 37 different damage types (DT) in the 'Guide to Insect (and Other) Damage Types in Compressed Plant Fossils'. A few leaf samples identified as Ipomoea L. (Convolvulaceae) have specific margin galls that do not match any galling DT previously described. This type of galling is characterized by small, linearly arranged, irregular, sessile, sub-globose, solitary, indehiscent, solid pouch-galls with irregular ostioles. The probable damage inducers of the present galling of the foliar margin might be members of Eriophyidae (Acari). The new type of gall suggests that marginal gall-inducing mites on leaves of Ipomoea did not change their host preference at the genus level since the Pliocene. The development of marginal leaf galling in Ipomoea is linked to extrafloral nectaries that do not offer protection against arthropod galling but indirectly protect the plant against herbivory from large mammals.

Heritability and gene functions associated with sclerotia formation of Rhizoctonia solani AG-7 using whole genome sequencing and genome-wide association study

Sclerotia are specialized fungal structures formed by pigmented and aggregated hyphae, which can survive under unfavourable environmental conditions and serve as the primary inocula for several phytopathogenic fungi including Rhizoctonia solani. Among 154 R. solani anastomosis group 7 (AG-7) isolates collected in fields, the sclerotia-forming capability regarding sclerotia number and sclerotia size varied in the fungal population, but the genetic makeup of these phenotypes remained unclear. As limited studies have focused on the genomics of R. solani AG-7 and the population genetics of sclerotia formation, this study completed the whole genome sequencing and gene prediction of R. solani AG-7 using the Oxford NanoPore and Illumina RNA sequencing. Meanwhile, a high-throughput image-based method was established to quantify the sclerotia-forming capability, and the phenotypic correlation between sclerotia number and sclerotia size was low. A genome-wide association study identified three and five significant SNPs associated with sclerotia number and size in distinct genomic regions, respectively. Of these significant SNPs, two and four showed significant differences in the phenotypic mean separation for sclerotia number and sclerotia size, respectively. Gene ontology enrichment analysis focusing on the linkage disequilibrium blocks of significant SNPs identified more categories related to oxidative stress for sclerotia number, and more categories related to cell development, signalling and metabolism for sclerotia size. These results indicated that different genetic mechanisms may underlie these two phenotypes. Moreover, the heritability of sclerotia number and sclerotia size were estimated for the first time to be 0.92 and 0.31, respectively. This study provides new insights into the heritability and gene functions related to the development of sclerotia number and sclerotia size, which could provide additional knowledge to reduce fungal residues in fields and achieve sustainable disease management.

A genome-wide association study identifies novel players in Na and Fe homeostasis in Arabidopsis thaliana under alkaline-salinity stress

In nature, multiple stress factors occur simultaneously. The screening of natural diversity panels and subsequent Genome-Wide Association Studies (GWAS) is a powerful approach to identify genetic components of various stress responses. Here, the nutritional status variation of a set of 270 natural accessions of Arabidopsis thaliana grown on a natural saline-carbonated soil is evaluated. We report significant natural variation on leaf Na (LNa) and Fe (LFe) concentrations in the studied accessions. Allelic variation in the NINJA and YUC8 genes is associated with LNa diversity, and variation in the ALA3 is associated with LFe diversity. The allelic variation detected in these three genes leads to changes in their mRNA expression and correlates with plant differential growth performance when plants are exposed to alkaline salinity treatment under hydroponic conditions. We propose that YUC8 and NINJA expression patters regulate auxin and jasmonic signaling pathways affecting plant tolerance to alkaline salinity. Finally, we describe an impairment in growth and leaf Fe acquisition associated with differences in root expression of ALA3, encoding a phospholipid translocase active in plasma membrane and the trans Golgi network which directly interacts with proteins essential for the trafficking of PIN auxin transporters, reinforcing the role of phytohormonal processes in regulating ion homeostasis under alkaline salinity.

Integrating plant and fungal quantitative genetics to improve the ecological and agricultural applications of mycorrhizal symbioses

Finding and targeting genes that quantitatively contribute to agricultural and ecological processes progresses food production and conservation efforts. Typically, quantitative genetic approaches link variants in a single organism's genome with a trait of interest. Recently, genome-to-genome mapping has found genome variants interacting between species to produce the result of a multiorganism (including multikingdom) interaction. These were plant and bacterial pathogen genome interactions; plant-fungal coquantitative genetics have not yet been applied. Plant-mycorrhizae symbioses exist across most biomes, for a majority of land plants, including crop plants, and manipulate many traits from single organisms to ecosystems for which knowing the genetic basis would be useful. The availability of Rhizophagus irregularis mycorrhizal isolates, with genomic information, makes dual-genome methods with beneficial mutualists accessible and imminent.

DeepBSA: A deep-learning algorithm improves bulked segregant analysis for dissecting complex traits

Bulked segregant analysis (BSA) is a rapid, cost-effective method for mapping mutations and quantitative trait loci (QTLs) in animals and plants based on high-throughput sequencing. However, the algorithms currently used for BSA have not been systematically evaluated and are complex and fallible to operate. We developed a BSA method driven by deep learning, DeepBSA, for QTL mapping and functional gene cloning. DeepBSA is compatible with a variable number of bulked pools and performed well with various simulated and real datasets in both animals and plants. DeepBSA outperformed all other algorithms when comparing absolute bias and signal-to-noise ratio. Moreover, we applied DeepBSA to an F₂ segregating maize population of 7160 individuals and uncovered five candidate QTLs, including three well-known plant-height genes. Finally, we developed a user-friendly graphical user interface for DeepBSA, by integrating five widely used BSA algorithms and our two newly developed algorithms, that is easy to operate and can quickly map QTLs and functional genes. The DeepBSA software is freely available to non-commercial users at http://zeasystemsbio.hzau.edu.cn/tools.html and https://github.com/lizhao007/DeepBSA.

Study of genetic variation and its association with tensile strength among bamboo species through whole genome resequencing

Moso bamboo (Phyllostachys edulis) is a versatile plant species that is widely used as a construction material by many low-income countries due to the lack of major construction materials such as steel and reinforced concrete. It is also widely used in China. Bamboo is an economically sustainable material that behaves exceptionally in natural disasters such as earthquakes and it can offer viable solutions for contemporary engineering challenges. Despite bamboo's potential in the engineering sector, biological features such as its long generation time, its large genome size, and its polyploidy are constraining factors for genetic and genomic studies that potentially can assist the breeding efforts. This study re-sequenced 8 Phyllostachys species and 18 natural accessions of Ph. edulis, generating a large set of functionally annotated molecular markers (Single Nucleotide Polymorphisms (SNPs) and InDels) providing key genomic resource information. Moreover, all this genomic information was used to carry out a preliminary genome-wide association analysis and several candidate genes were identified to be correlated with a mechanical property that is of high interest to structural engineers: its tensile strength normal to its fibers (i.e., splitting).

Genetics as a key to improving crop photosynthesis

Since the basic biochemical mechanisms of photosynthesis are remarkably conserved among plant species, genetic modification approaches have so far been the main route to improve the photosynthetic performance of crops. Yet, phenotypic variation observed in wild species and between varieties of crop species implies there is standing natural genetic variation for photosynthesis, offering a largely unexplored resource to use for breeding crops with improved photosynthesis and higher yields. The reason this has not yet been explored is that the variation probably involves thousands of genes, each contributing only a little to photosynthesis, making them hard to identify without proper phenotyping and genetic tools. This is changing, though, and increasingly studies report on quantitative trait loci for photosynthetic phenotypes. So far, hardly any of these quantitative trait loci have been used in marker assisted breeding or genomic selection approaches to improve crop photosynthesis and yield, and hardly ever have the underlying causal genes been identified. We propose to take the genetics of photosynthesis to a higher level, and identify the genes and alleles nature has used for millions of years to tune photosynthesis to be in line with local environmental conditions. We will need to determine the physiological function of the genes and alleles, and design novel strategies to use this knowledge to improve crop photosynthesis through conventional plant breeding, based on readily available crop plant germplasm. In this work, we present and discuss the genetic methods needed to reveal natural genetic variation, and elaborate on how to apply this to improve crop photosynthesis.

Genomic interrogation of a MAGIC population highlights genetic factors controlling fiber quality traits in cotton

Cotton (Gossypium hirsutum L.) fiber is the most important resource of natural and renewable fiber for the textile industry. However, the understanding of genetic components and their genome-wide interactions controlling fiber quality remains fragmentary. Here, we sequenced a multiple-parent advanced-generation inter-cross (MAGIC) population, consisting of 550 individuals created by inter-crossing 11 founders, and established a mosaic genome map through tracing the origin of haplotypes that share identity-by-descent (IBD). We performed two complementary GWAS methods—SNP-based GWAS (sGWAS) and IBD-based haplotype GWAS (hGWAS). A total of 25 sQTLs and 14 hQTLs related to cotton fiber quality were identified, of which 26 were novel QTLs. Two major QTLs detected by both GWAS methods were responsible for fiber strength and length. The gene Ghir_D11G020400 (GhZF14) encoding the MATE efflux family protein was identified as a novel candidate gene for fiber length. Beyond the additive QTLs, we detected prevalent epistatic interactions that contributed to the genetics of fiber quality, pinpointing another layer for trait variance. This study provides new targets for future molecular design breeding of superior fiber quality.

Wang and colleagues use a complementary GWAS approach to identify genetic loci associated with cotton fiber quality. Using a multiparent advanced-generation inter-cross population, 26 new QTLs related to cotton fiber quality were found.

Mapping of dwarfing QTL of Ari1327, a semi-dwarf mutant of upland cotton

BACKGROUND

Upland Cotton (Gossypium hirsutum L.) has few cotton varieties suitable for mechanical harvesting. The plant height of the cultivar is one of the key features that need to modify. Hence, this study was planned to locate the QTL for plant height in a 60Co γ treated upland cotton semi-dwarf mutant Ari1327.

RESULTS

Interestingly, bulk segregant analysis (BSA) and genotyping by sequencing (GBS) methods exhibited that candidate QTL was co-located in the region of 5.80-9.66 Mb at D01 chromosome in two F2 populations. Using three InDel markers to genotype a population of 1241 individuals confirmed that the offspring's phenotype is consistent with the genotype. Comparative analysis of RNA-seq between the mutant and wild variety exhibited that Gh_D01G0592 was identified as the source of dwarfness from 200 genes. In addition, it was also revealed that the appropriate use of partial separation markers in QTL mapping can escalate linkage information.

CONCLUSIONS

Overwhelmingly, the results will provide the basis to reveal the function of candidate genes and the utilization of excellent dwarf genetic resources in the future.

Complex adaptive architecture underlies adaptation to quantitative host resistance in a fungal plant pathogen

Plant pathogens often adapt to plant genetic resistance so characterization of the architecture underlying such an adaptation is required to understand the adaptive potential of pathogen populations. Erosion of banana quantitative resistance to a major leaf disease caused by polygenic adaptation of the causal agent, the fungus Pseudocercospora fijiensis, was recently identified in the northern Caribbean region. Genome scan and quantitative genetics approaches were combined to investigate the adaptive architecture underlying this adaptation. Thirty-two genomic regions showing host selection footprints were identified by pool sequencing of isolates collected from seven plantation pairs of two cultivars with different levels of quantitative resistance. Individual sequencing and phenotyping of isolates from one pair revealed significant and variable levels of correlation between haplotypes in 17 of these regions with a quantitative trait of pathogenicity (the diseased leaf area). The multilocus pattern of haplotypes detected in the 17 regions was found to be highly variable across all the population pairs studied. These results suggest complex adaptive architecture underlying plant pathogen adaptation to quantitative resistance with a polygenic basis, redundancy, and a low level of parallel evolution between pathogen populations. Candidate genes involved in quantitative pathogenicity and host adaptation of P. fijiensis were identified in genomic regions by combining annotation analysis with available biological data.

Unraveling Cuticle Formation, Structure, and Properties by Using Tomato Genetic Diversity

The tomato (Solanum lycopersicum) fruit has a thick, astomatous cuticle that has become a model for the study of cuticle formation, structure, and properties in plants. Tomato is also a major horticultural crop and a long-standing model for research in genetics, fruit development, and disease resistance. As a result, a wealth of genetic resources and genomic tools have been established, including collections of natural and artificially induced genetic diversity, introgression lines of genome fragments from wild relatives, high-quality genome sequences, phenotype and gene expression databases, and efficient methods for genetic transformation and editing of target genes. This mini-review reports the considerable progresses made in recent years in our understanding of cuticle by using and generating genetic diversity for cuticle-associated traits in tomato. These include the synthesis of the main cuticle components (cutin and waxes), their role in the structure and properties of the cuticle, their interaction with other cell wall polymers as well as the regulation of cuticle formation. It also addresses the opportunities offered by the untapped germplasm diversity available in tomato and the current strategies available to exploit them.

Genetic basis of kernel starch content decoded in a maize multi-parent population

Starch is the most abundant storage carbohydrate in maize kernels and provides calories for humans and other animals as well as raw materials for various industrial applications. Decoding the genetic basis of natural variation in kernel starch content is needed to manipulate starch quantity and quality via molecular breeding to meet future needs. Here, we identified 50 unique single quantitative trait loci (QTLs) for starch content with 18 novel QTLs via single linkage mapping, joint linkage mapping and a genome-wide association study in a multi-parent population containing six recombinant inbred line populations. Only five QTLs explained over 10% of phenotypic variation in single populations. In addition to a few large-effect and many small-effect additive QTLs, limited pairs of epistatic QTLs also contributed to the genetic basis of the variation in kernel starch content. A regional association study identified five non-starch-pathway genes that were the causal candidate genes underlying the identified QTLs for starch content. The pathway-driven analysis identified ZmTPS9, which encodes a trehalose-6-phosphate synthase in the trehalose pathway, as the causal gene for the QTL qSTA4-2, which was detected by all three statistical analyses. Knockout of ZmTPS9 increased kernel starch content and, in turn, kernel weight in maize, suggesting potential applications for ZmTPS9 in maize starch and yield improvement. These findings extend our knowledge about the genetic basis of starch content in maize kernels and provide valuable information for maize genetic improvement of starch quantity and quality.

The identification of grain size genes by RapMap reveals directional selection during rice domestication

Cloning quantitative trait locus (QTL) is time consuming and laborious, which hinders the understanding of natural variation and genetic diversity. Here, we introduce RapMap, a method for rapid multi-QTL mapping by employing F2 gradient populations (F2GPs) constructed by minor-phenotypic-difference accessions. The co-segregation standard of the single-locus genetic models ensures simultaneous integration of a three-in-one framework in RapMap i.e. detecting a real QTL, confirming its effect, and obtaining its near-isogenic line-like line (NIL-LL). We demonstrate the feasibility of RapMap by cloning eight rice grain-size genes using 15 F2GPs in three years. These genes explain a total of 75% of grain shape variation. Allele frequency analysis of these genes using a large germplasm collection reveals directional selection of the slender and long grains in indica rice domestication. In addition, major grain-size genes have been strongly selected during rice domestication. We think application of RapMap in crops will accelerate gene discovery and genomic breeding.

The genetic architecture of leaf stable carbon isotope composition in Zea mays and the effect of transpiration efficiency on leaf elemental accumulation

With increased demand on freshwater resources for agriculture, it is imperative that more water-use efficient crops are developed. Leaf stable carbon isotope composition, δ13C, is a proxy for transpiration efficiency and a possible tool for breeders, but the underlying mechanisms effecting δ13C in C4 plants are not known. It has been suggested that differences in specific leaf area (SLA), which potentially reflects variation in internal CO2 diffusion, can impact leaf δ13C. Furthermore, although it is known that water movement is important for elemental uptake, it is not clear how manipulation of transpiration for increased water-use efficiency may impact nutrient accumulation. Here, we characterize the genetic architecture of leaf δ13C and test its relationship to SLA and the ionome in five populations of maize. Five significant QTL for leaf δ13C were identified, including novel QTL as well as some that were identified previously in maize kernels. One of the QTL regions contains an Erecta-like gene, the ortholog of which has been shown to regulate transpiration efficiency and leaf δ13C in Arabidopsis. QTL for δ13C were located in the same general chromosome region, but slightly shifted, when comparing data from two different years. Our data does not support a relationship between δ13C and SLA, and of the 19 elements analyzed, only a weak correlation between molybdenum and δ13C was detected. Together these data add to the genetic understanding of leaf δ13C in maize and suggest that improvements to plant water use may be possible without significantly influencing elemental homeostasis.

ABA Metabolism and Homeostasis in Seed Dormancy and Germination

Abscisic acid (ABA) is a key hormone that promotes dormancy during seed development on the mother plant and after seed dispersal participates in the control of dormancy release and germination in response to environmental signals. The modulation of ABA endogenous levels is largely achieved by fine-tuning, in the different seed tissues, hormone synthesis by cleavage of carotenoid precursors and inactivation by 8'-hydroxylation. In this review, we provide an overview of the current knowledge on ABA metabolism in developing and germinating seeds; notably, how environmental signals such as light, temperature and nitrate control seed dormancy through the adjustment of hormone levels. A number of regulatory factors have been recently identified which functional relationships with major transcription factors, such as ABA INSENSITIVE3 (ABI3), ABI4 and ABI5, have an essential role in the control of seed ABA levels. The increasing importance of epigenetic mechanisms in the regulation of ABA metabolism gene expression is also described. In the last section, we give an overview of natural variations of ABA metabolism genes and their effects on seed germination, which could be useful both in future studies to better understand the regulation of ABA metabolism and to identify candidates as breeding materials for improving germination properties.

Genome-wide association study of multiple traits linked to heat tolerance in emmer-derived hexaploid wheat genotypes

Heat stress tolerance in plants is a complex trait controlled by multiple genes of minor effect which are influenced by the environment and this makes breeding and selection complicated. Emmer wheat (Triticum dicoccon Schrank) carries valuable diversity that can be used to improve the heat tolerance of modern bread wheat. A diverse set of emmer-based genotypes was developed by crossing emmer wheat with hexaploid wheat. These materials, along with their hexaploid recurrent parents and commercial cultivars, were evaluated at optimum (E1) and heat stressed (E2) sowing times in the field for three consecutive years (2014-2016). The material was genotyped using the Infinium iSelect SNP 90K SNP Assay. The phenotypic data were combined across years within each sowing time and best linear unbiased estimators calculated for each genotype in each environment. These estimates were used for GWAS analysis. Significant phenotypic and genotypic variation was observed for all traits. A total of 125 and 142 marker-trait associations (MTAs) were identified in E1 and E2, respectively. The highest number of MTAs were observed on the A genome (106), followed by the B (105) and D (56) genomes. MTAs with pleiotropic effects within and across the environments were observed. Many of the MTAs found were reported previously for various traits, and a few significant MTAs under heat stress were new and linked to emmer genome. Genomic regions identified on chromosomes 2B and 3A had a significant positive impact on grain yield under stress with a 7% allelic effect. Genomic regions on chromosomes 1A and 4B contributed 11% and 9% of the variation for thousand kernel weight (TKW) under heat stress respectively. Following fine mapping, these regions could be used for marker-assisted selection to improve heat tolerance in wheat.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01222-3.

Natural variation in temperature-modulated immunity uncovers transcription factor bHLH059 as a thermoresponsive regulator in Arabidopsis thaliana

Temperature impacts plant immunity and growth but how temperature intersects with endogenous pathways to shape natural variation remains unclear. Here we uncover variation between Arabidopsis thaliana natural accessions in response to two non-stress temperatures (22°C and 16°C) affecting accumulation of the thermoresponsive stress hormone salicylic acid (SA) and plant growth. Analysis of differentially responding A. thaliana accessions shows that pre-existing SA provides a benefit in limiting infection by Pseudomonas syringae pathovar tomato DC3000 bacteria at both temperatures. Several A. thaliana genotypes display a capacity to mitigate negative effects of high SA on growth, indicating within-species plasticity in SA—growth tradeoffs. An association study of temperature x SA variation, followed by physiological and immunity phenotyping of mutant and over-expression lines, identifies the transcription factor bHLH059 as a temperature-responsive SA immunity regulator. Here we reveal previously untapped diversity in plant responses to temperature and a way forward in understanding the genetic architecture of plant adaptation to changing environments.

Temperature has a profound effect on plant innate immune responses but little is known about the mechanisms underlying natural variation in transmission of temperature signals to defence pathways. Much of our understanding of temperature effects on plant immunity and tradeoffs between activated defences and growth has come from analysis of the common Arabidopsis thaliana genetic accession, Col-0. Here we examine A. thaliana genetic variation in response to temperature (within the non-stress range—22 ^oC and 16 ^oC) at the level of accumulation of the thermoresponsive biotic stress hormone salicylic acid (SA), bacterial pathogen resistance, and plant biomass. From analysis of 105 genetically diverse A. thaliana accessions we uncover plasticity in temperature-modulated SA homeostasis and in the relationship between SA levels and plant growth. We find that high SA amounts prior to infection provide a robust benefit of enhancing bacterial resistance. In some accessions this benefit comes without compromised plant growth, suggestive of altered defence–growth tradeoffs. Based on a temperature x SA association study we identify the transcription factor gene, bHLH059, and show that it has features of a temperature-sensitive immunity regulator that are unrelated to PIF4, a known thermosensitive coordinator of immunity and growth.

Almond diversity and homozygosity define structure, kinship, inbreeding, and linkage disequilibrium in cultivated germplasm, and reveal genomic associations with nut and seed weight

Almond [Prunus dulcis Miller (D.A. Webb)] is the main tree nut species worldwide. Here, genotyping-by-sequencing (GBS) was applied to 149 almond cultivars from the ex situ collections of the Italian Council for Agricultural Research (CREA) and the Spanish National Research Council (CSIC), leading to the detection of 93,119 single-nucleotide polymorphisms (SNPs). The study of population structure outlined four distinct genetic groups and highlighted diversification between the Mediterranean and Californian gene pools. Data on SNP diversity and runs of homozygosity (ROHs) allowed the definition of kinship, inbreeding, and linkage disequilibrium (LD) decay in almond cultivated germplasm. Four-year phenotypic observations, gathered on 98 cultivars of the CREA collection, were used to perform a genome-wide association study (GWAS) and, for the first time in a crop species, homozygosity mapping (HM), resulting in the identification of genomic associations with nut, shell, and seed weight. Both GWAS and HM suggested that loci controlling nut and seed weight are mostly independent. Overall, this study provides insights on the almond cultivation history and delivers information of major interest for almond genetics and breeding. In a broader perspective, our results encourage the use of ROHs in crop science to estimate inbreeding, choose parental combinations minimizing the risk of inbreeding depression, and identify genomic footprints of selection for specific traits.

A large-scale genomic association analysis identifies the candidate causal genes conferring stripe rust resistance under multiple field environments

The incorporation of resistance genes into wheat commercial varieties is the ideal strategy to combat stripe or yellow rust (YR). In a search for novel resistance genes, we performed a large-scale genomic association analysis with high-density 660K single nucleotide polymorphism (SNP) arrays to determine the genetic components of YR resistance in 411 spring wheat lines. Following quality control, 371 972 SNPs were screened, covering over 50% of the high-confidence annotated gene space. Nineteen stable genomic regions harbouring 292 significant SNPs were associated with adult-plant YR resistance across nine environments. Of these, 14 SNPs were localized in the proximity of known loci widely used in breeding. Obvious candidate SNP variants were identified in certain confidence intervals, such as the cloned gene Yr18 and the major locus on chromosome 2BL, despite a large extent of linkage disequilibrium. The number of causal SNP variants was refined using an independent validation panel and consideration of the estimated functional importance of each nucleotide polymorphism. Interestingly, four natural polymorphisms causing amino acid changes in the gene TraesCS2B01G513100 that encodes a serine/threonine protein kinase (STPK) were significantly involved in YR responses. Gene expression and mutation analysis confirmed that STPK played an important role in YR resistance. PCR markers were developed to identify the favourable TraesCS2B01G513100 haplotype for marker-assisted breeding. These results demonstrate that high-resolution SNP-based GWAS enables the rapid identification of putative resistance genes and can be used to improve the efficiency of marker-assisted selection in wheat disease resistance breeding.

Wild and Domestic Differences in Plant Development and Responses to Water Deficit in Cicer

There is growing interest in widening the genetic diversity of domestic crops using wild relatives to break linkage drag and/or introduce new adaptive traits, particularly in narrow crops such as chickpea. To this end, it is important to understand wild and domestic adaptive differences to develop greater insight into how wild traits can be exploited for crop improvement. Here, we study wild and domestic Cicer development and water-use over the lifecycle, measuring responses to reproductive water deficit, a key Mediterranean selection pressure, using mini-lysimeters (33 L round pots) in common gardens under contrasting water regimes. Wild and domestic Cicer were consistently separated by later phenology, greater water extraction and lower water use efficiency (WUE) and harvest index in the former, and much greater yield-responsiveness in the latter. Throughout the lifecycle, there was greater vegetative investment in wild, and greater reproductive investment in domestic Cicer, reflected in root and harvest indices, rates of leaf area, and pod growth. Domestic WUE was consistently greater than wild, suggesting differences in water-use regulation and partitioning. Large wild-domestic differences revealed in this study are indicative of evolution under contrasting selection pressures. Cicer domestication has selected for early phenology, greater early vigor, and reproductive efficiency, attributes well-suited to a time-delimited production system, where the crop is protected from grazing, disease, and competition, circumstances that do not pertain in the wild. Wild Cicer attributes are more competitive: higher peak rates of leaf area growth, greater ad libitum water-use, and extraction under terminal drought associated with greater vegetative dry matter allocation, leading to a lower reproductive capacity and efficiency than in domestic chickpea. These traits strengthen competitive capacity throughout the growing season and are likely to facilitate recovery from grazing, two significant selection pressures faced by wild, rather than domesticated Cicer. While increased water extraction may be useful for improving chickpea drought tolerance, this trait must be evaluated independently of the other associated wild traits. To this end, the wild-domestic populations have been developed.

Identification of Genes Conferring Plant Salt Tolerance using GWAS: Current Success and Perspectives

An understanding of the molecular mechanisms that underlie plant salt tolerance is important for both economic and scientific interests. Genome-wide association study (GWAS) is a promising approach to pinpoint genes that confer plant salt tolerance. With the advancement of supporting technology and methodology, GWAS has enabled the discovery of genes that play central roles in regulating plant salt tolerance in the past decade. Here, I highlight recent successful GWAS work in unveiling the molecular factors underlying plant salt tolerance and discuss the concerns and opportunities in conducting such experiments. It is anticipated that GWAS will be increasingly successful in the identification of key genes that are useful for crop improvement.

Specialized phenolic compounds in seeds: structures, functions, and regulations

Plants produce a huge diversity of specialized metabolites (SM) throughout their life cycle that play important physiological and ecological functions. SM can protect plants and seeds against diseases, predators, and abiotic stresses, or support their interactions with beneficial or symbiotic organisms. They also have strong impacts on human nutrition and health. Despite this importance, the biosynthesis and biological functions of most of the SM remain elusive and their diversity and/or quantity have been reduced in most crops during domestication. Seeds present a large number of SM that are important for their physiological, agronomic, nutritional or industrial qualities and hence, provide interesting models for both studying biosynthesis and producing large amounts of specialized metabolites. For instance, phenolics are abundant and widely distributed in seeds. More specifically, flavonoid pathway has been instrumental for understanding environmental or developmental regulations of specialized metabolic pathways, at the molecular and cellular levels. Here, we summarize current knowledge on seed phenolics as model, and discuss how recent progresses in omics approaches could help to further characterize their diversity, regulations, and the underlying molecular mechanisms involved.

A Brassica napus Reductase Gene Dissected by Associative Transcriptomics Enhances Plant Adaption to Freezing Stress

Cold treatment (vernalization) is required for winter crops such as rapeseed (Brassica napus L.). However, excessive exposure to low temperature (LT) in winter is also a stress for the semi-winter, early-flowering rapeseed varieties widely cultivated in China. Photosynthetic efficiency is one of the key determinants, and thus a good indicator for LT tolerance in plants. So far, the genetic basis underlying photosynthetic efficiency is poorly understood in rapeseed. Here the current study used Associative Transcriptomics to identify genetic loci controlling photosynthetic gas exchange parameters in a diversity panel comprising 123 accessions. A total of 201 significant Single Nucleotide Polymorphisms (SNPs) and 147 Gene Expression Markers (GEMs) were detected, leading to the identification of 22 candidate genes. Of these, Cab026133.1, an ortholog of the Arabidopsis gene AT2G29300.2 encoding a tropinone reductase (BnTR1), was further confirmed to be closely linked to transpiration rate. Ectopic expressing BnTR1 in Arabidopsis plants significantly increased the transpiration rate and enhanced LT tolerance under freezing conditions. Also, a much higher level of alkaloids content was observed in the transgenic Arabidopsis plants, which could help protect against LT stress. Together, the current study showed that AT is an effective approach for dissecting LT tolerance trait in rapeseed and that BnTR1 is a good target gene for the genetic improvement of LT tolerance in plant.

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.

A systematic analysis of apple root resistance traits to Pythium ultimum infection and the underpinned molecular regulations of defense activation

Apple replant disease (ARD), caused by a pathogen complex, significantly impacts apple orchard establishment. The molecular regulation on ARD resistance has not been investigated until recently. A systematic phenotyping effort and a series of transcriptomic analyses were performed to uncover the underpinned molecular mechanism of apple root resistance to P. ultimum, a representative member in ARD pathogen complex. Genotype-specific plant survival rates and biomass reduction corresponded with microscopic features of necrosis progression patterns along the infected root. The presence of defined boundaries separating healthy and necrotic sections likely caused delayed necrosis expansion in roots of resistant genotypes compared with swift necrosis progression and profuse hyphae growth along infected roots of susceptible genotypes. Comprehensive datasets from a series of transcriptome analyses generated the first panoramic view of genome-wide transcriptional networks of defense activation between resistant and susceptible apple roots. Earlier and stronger molecular defense activation, such as pathogen perception and hormone signaling, may differentiate resistance from susceptibility in apple root. Delayed and interrupted activation of multiple defense pathways could have led to an inadequate resistance response. Using the panel of apple rootstock germplasm with defined resistant and susceptible phenotypes, selected candidate genes are being investigated by transgenic manipulation including CRISPR/Cas9 tools for their specific roles during apple root defense toward P. ultimum infection. Individual apple genes with validated functions regulating root resistance responses can be exploited for developing molecular tools for accurate and efficient incorporation of resistance traits into new apple rootstocks.

Fine mapping and gene cloning in the post-NGS era: advances and prospects

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.

Exploration of the Yield Potential of Mesoamerican Wild Common Beans From Contrasting Eco-Geographic Regions by Nested Recombinant Inbred Populations

Genetic analyses and utilization of wild genetic variation for crop improvement in common bean (Phaseolus vulgaris L.) have been hampered by yield evaluation difficulties, identification of advantageous variation, and linkage drag. The lack of adaptation to cultivation conditions and the existence of highly structured populations make association mapping of diversity panels not optimal. Joint linkage mapping of nested populations avoids the later constraint, while populations crossed with a common domesticated parent allow the evaluation of wild variation within a more adapted background. Three domesticated by wild backcrossed-inbred-line populations (BC₁S₄) were developed using three wild accessions representing the full range of rainfall of the Mesoamerican wild bean distribution crossed to the elite drought tolerant domesticated parent SEA 5. These populations were evaluated under field conditions in three environments, two fully irrigated trials in two seasons and a simulated terminal drought in the second season. The goal was to test if these populations responded differently to drought stress and contained progenies with higher yield than SEA 5, not only under drought but also under water-watered conditions. Results revealed that the two populations derived from wild parents of the lower rainfall regions produced lines with higher yield compared to the domesticated parent in the three environments, i.e., both in the drought-stressed environment and in the well-watered treatments. Several progeny lines produced yields, which on average over the three environments were 20% higher than the SEA 5 yield. Twenty QTLs for yield were identified in 13 unique regions on eight of the 11 chromosomes of common bean. Five of these regions showed at least one wild allele that increased yield over the domesticated parent. The variation explained by these QTLs ranged from 0.6 to 5.4% of the total variation and the additive effects ranged from -164 to 277 kg ha^-1, with evidence suggesting allelic series for some QTLs. Our results underscore the potential of wild variation, especially from drought-stressed regions, for bean crop improvement as well the identification of regions for efficient marker-assisted introgression.

Genetic dissection of thousand-seed weight and fine mapping of cqSW.A03-2 via linkage and association analysis in rapeseed (Brassica napus L.)

KEY MESSAGE: cqSW.A03-2, one of the six identified quantitative trait loci associated with thousand-seed weight in rapeseed, is mapped to a 61.6-kb region on chromosome A03 and corresponds to the candidate gene BnaA03G37960D. Seed weight is an important factor that determines the seed yield of oilseed rape (Brassica napus L.). To elucidate the genetic mechanism of thousand-seed weight (TSW), quantitative trait locus (QTL) mapping was conducted using a double haploid population derived from the cross between an elite line ZY50 and a pol cytoplasmic male sterility restorer line 7-5. The genetic basis of TSW was dissected into six major QTLs. One major QTL denoted as cqSW.A03-2, which explained 8.46-13.70% of the phenotypic variation, was detected across multiple environments. To uncover the genetic basis of cqSW.A03-2, a set of near-isogenic lines were developed. Based on the test of self-pollinated progenies, cqSW.A03-2 was identified as a single Mendelian factor and the ZY50 allele at cqSW.A03-2 showed a positive effect on TSW. Fine mapping delimited the cqSW.A03-2 locus into a 61.6-kb region, and 18 genes within this region were predicted. Candidate gene association analysis and expression analysis indicated that a histidine kinase gene (BnaA03G37960D) is likely to be the candidate gene for the cqSW.A03-2 locus. Our results may contribute to a better understanding of the molecular mechanism of seed weight regulation and promote the breeding program for yield improvement in rapeseed.

Characterization of four polymorphic genes controlling red leaf colour in lettuce that have undergone disruptive selection since domestication

Anthocyanins protect plants from biotic and abiotic stressors and provide great health benefits to consumers. In this study, we cloned four genes (Red Lettuce Leaves 1 to 4: RLL1 to RLL4) that contribute to colour variations in lettuce. The RLL1 gene encodes a bHLH transcription factor, and a 5-bp deletion in some cultivars abolishes its function to activate the anthocyanin biosynthesis pathway. The RLL2 gene encodes an R2R3-MYB transcription factor, which was derived from a duplication followed by mutations in its promoter region. The RLL3 gene encodes an R2-MYB transcription factor, which down-regulates anthocyanin biosynthesis through competing with RLL2 for interaction with RLL1; a mis-sense mutation compromises the capacity of RLL3 to bind RLL1. The RLL4 gene encodes a WD-40 transcription factor, homologous to the RUP genes suppressing the UV-B signal transduction pathway in Arabidopsis; a mis-sense mutation in rll4 attenuates its suppressing function, leading to a high concentration of anthocyanins. Sequence analysis of the RLL1-RLL4 genes from wild and cultivated lettuce showed that their function-changing mutations occurred after domestication. The mutations in rll1 disrupt anthocyanin biosynthesis, while the mutations in RLL2, rll3 and rll4 activate anthocyanin biosynthesis, showing disruptive selection for leaf colour during domestication of lettuce. The characterization of multiple polymorphic genes in this study provides the necessary molecular resources for the rational breeding of lettuce cultivars with distinct levels of red pigments and green cultivars with high levels of health-promoting flavonoids.

CUBIC: an atlas of genetic architecture promises directed maize improvement

BACKGROUND

Identifying genotype-phenotype links and causative genes from quantitative trait loci (QTL) is challenging for complex agronomically important traits. To accelerate maize gene discovery and breeding, we present the Complete-diallel design plus Unbalanced Breeding-like Inter-Cross (CUBIC) population, consisting of 1404 individuals created by extensively inter-crossing 24 widely used Chinese maize founders.

RESULTS

Hundreds of QTL for 23 agronomic traits are uncovered with 14 million high-quality SNPs and a high-resolution identity-by-descent map, which account for an average of 75% of the heritability for each trait. We find epistasis contributes to phenotypic variance widely. Integrative cross-population analysis and cross-omics mapping allow effective and rapid discovery of underlying genes, validated here with a case study on leaf width.

CONCLUSIONS

Through the integration of experimental genetics and genomics, our study provides useful resources and gene mining strategies to explore complex quantitative traits.

Genomic biosurveillance of forest invasive alien enemies: A story written in code

The world's forests face unprecedented threats from invasive insects and pathogens that can cause large irreversible damage to the ecosystems. This threatens the world's capacity to provide long-term fiber supply and ecosystem services that range from carbon storage, nutrient cycling, and water and air purification, to soil preservation and maintenance of wildlife habitat. Reducing the threat of forest invasive alien species requires vigilant biosurveillance, the process of gathering, integrating, interpreting, and communicating essential information about pest and pathogen threats to achieve early detection and warning and to enable better decision-making. This process is challenging due to the diversity of invasive pests and pathogens that need to be identified, the diverse pathways of introduction, and the difficulty in assessing the risk of establishment. Genomics can provide powerful new solutions to biosurveillance. The process of invasion is a story written in four chapters: transport, introduction, establishment, and spread. The series of processes that lead to a successful invasion can leave behind a DNA signature that tells the story of an invasion. This signature can help us understand the dynamic, multistep process of invasion and inform management of current and future introductions. This review describes current and future application of genomic tools and pipelines that will provide accurate identification of pests and pathogens, assign outbreak or survey samples to putative sources to identify pathways of spread, and assess risk based on traits that impact the outbreak outcome.

Trait mapping in diverse arthropods by bulked segregant analysis

Bulked segregant analysis (BSA) is a cross-based method for genetic mapping in sexually reproducing organisms. The method's use of bulked (pooled) samples markedly reduces the genotyping effort associated with traditional linkage mapping studies. Further, it can be applied to species with life histories or physical attributes (as for micro-insects) that render genetic mapping with other methods impractical. Recent studies in both insects and mites have revealed that advanced BSA experimental designs can resolve causal loci to narrow genomic intervals, facilitating follow-up investigations. As high-quality genomes become more widely available, BSA methods are poised to become an increasingly important tool for the rapid mapping of both monogenic and polygenic traits in diverse arthropod species.

A Genetic Dissection of Natural Variation for Stomatal Abundance Traits in Arabidopsis

Stomatal abundance varies widely across natural populations of Arabidopsis thaliana, and presumably affects plant performance because it influences water and CO2 exchange with the atmosphere and thence photosynthesis and transpiration. In order to determine the genetic basis of this natural variation, we have analyzed a recombinant inbred line (RIL) population derived from the wild accession Ll-0 and the reference strain Landsberg erecta (Ler), which show low and high stomatal abundance, respectively. Quantitative trait locus (QTL) analyses of stomatal index, stomatal density, and pavement cell density measured in the adaxial cotyledon epidermis, identified five loci. Three of the genomic regions affect all traits and were named MID (Modulator of Cell Index and Density) 1 to 3. MID2 is a large-effect QTL overlapping with ERECTA (ER), the er-1 allele from Ler increasing all trait values. Additional analyses of natural and induced loss-of-function er mutations in different genetic backgrounds revealed that ER dysfunctions have differential and opposite effects on the stomatal index in adaxial and abaxial cotyledon epidermis and confirmed that ER is the gene underlying MID2. Ll-0 alleles at MID1 and MID3 displayed moderate and positive effects on the various traits. Furthermore, detailed developmental studies tracking primary and satellite stomatal lineages show that MID3-Ll-0 allele promotes the spacing divisions that initiate satellite lineages, while the ER allele limits them. Finally, expression analyses suggest that ER and MID3 modulate satellization through partly different regulatory pathways. Our characterization of MID3 indicates that genetic modulation of satellization contributes to the variation for stomatal abundance in natural populations, and subsequently that this trait might be involved in plant adaptation.

Natural variation in Arabidopsis shoot branching plasticity in response to nitrate supply affects fitness

The capacity of organisms to tune their development in response to environmental cues is pervasive in nature. This phenotypic plasticity is particularly striking in plants, enabled by their modular and continuous development. A good example is the activation of lateral shoot branches in Arabidopsis, which develop from axillary meristems at the base of leaves. The activity and elongation of lateral shoots depends on the integration of many signals both external (e.g. light, nutrient supply) and internal (e.g. the phytohormones auxin, strigolactone and cytokinin). Here, we characterise natural variation in plasticity of shoot branching in response to nitrate supply using two diverse panels of Arabidopsis lines. We find extensive variation in nitrate sensitivity across these lines, suggesting a genetic basis for variation in branching plasticity. High plasticity is associated with extreme branching phenotypes such that lines with the most branches on high nitrate have the fewest under nitrate deficient conditions. Conversely, low plasticity is associated with a constitutively moderate level of branching. Furthermore, variation in plasticity is associated with alternative life histories with the low plasticity lines flowering significantly earlier than high plasticity lines. In Arabidopsis, branching is highly correlated with fruit yield, and thus low plasticity lines produce more fruit than high plasticity lines under nitrate deficient conditions, whereas highly plastic lines produce more fruit under high nitrate conditions. Low and high plasticity, associated with early and late flowering respectively, can therefore be interpreted alternative escape vs mitigate strategies to low N environments. The genetic architecture of these traits appears to be highly complex, with only a small proportion of the estimated genetic variance detected in association mapping.

Phenotyping Thermal Responses of Yeasts and Yeast-like Microorganisms at the Individual and Population Levels: Proof-of-Concept, Development and Application of an Experimental Framework to a Plant Pathogen

Deciphering the responses of microbial populations to spatiotemporal changes in their thermal environment is instrumental in improving our understanding of their eco-evolutionary dynamics. Recent studies have shown that current phenotyping protocols do not adequately address all dimensions of phenotype expression. Therefore, these methods can give biased assessments of sensitivity to temperature, leading to misunderstandings concerning the ecological processes underlying thermal plasticity. We describe here a new robust and versatile experimental framework for the accurate investigation of thermal performance and phenotypic diversity in yeasts and yeast-like microorganisms, at the individual and population levels. In addition to proof-of-concept, the application of this framework to the fungal wheat pathogen Zymoseptoria tritici resulted in detailed characterisations for this yeast-like microorganism of (i) the patterns of temperature-dependent changes in performance for four fitness traits; (ii) the consistency in thermal sensitivity rankings of strains between in planta and in vitro growth assessments; (iii) significant interindividual variation in thermal responses, with four principal thermotypes detected in a sample of 66 strains; and (iv) the ecological consequences of this diversity for population-level processes through pairwise competition experiments highlighting temperature-dependent outcomes. These findings extend our knowledge and ability to quantify and categorise the phenotypic heterogeneity of thermal responses. As such, they lay the foundations for further studies elucidating local adaptation patterns and the effects of temperature variations on eco-evolutionary and epidemiological processes.

High-Throughput Field-Phenotyping Tools for Plant Breeding and Precision Agriculture

High-throughput field phenotyping has garnered major attention in recent years leading to the development of several new protocols for recording various plant traits of interest. Phenotyping of plants for breeding and for precision agriculture have different requirements due to different sizes of the plots and fields, differing purposes and the urgency of the action required after phenotyping. While in plant breeding phenotyping is done on several thousand small plots mainly to evaluate them for various traits, in plant cultivation, phenotyping is done in large fields to detect the occurrence of plant stresses and weeds at an early stage. The aim of this review is to highlight how various high-throughput phenotyping methods are used for plant breeding and farming and the key differences in the applications of such methods. Thus, various techniques for plant phenotyping are presented together with applications of these techniques for breeding and cultivation. Several examples from the literature using these techniques are summarized and the key technical aspects are highlighted.

Duplication of a domestication locus neutralized a cryptic variant that caused a breeding barrier in tomato

Genome editing technologies are being widely adopted in plant breeding¹. However, a looming challenge of engineering desirable genetic variation in diverse genotypes is poor predictability of phenotypic outcomes due to unforeseen interactions with pre-existing cryptic mutations^2-4. In tomato, breeding with a classical MADS-box gene mutation that improves harvesting by eliminating fruit stem abscission frequently results in excessive inflorescence branching, flowering and reduced fertility due to interaction with a cryptic variant that causes partial mis-splicing in a homologous gene^5-8. Here, we show that a recently evolved tandem duplication carrying the second-site variant achieves a threshold of functional transcripts to suppress branching, enabling breeders to neutralize negative epistasis on yield. By dissecting the dosage mechanisms by which this structural variant restored normal flowering and fertility, we devised strategies that use CRISPR-Cas9 genome editing to predictably improve harvesting. Our findings highlight the under-appreciated impact of epistasis in targeted trait breeding and underscore the need for a deeper characterization of cryptic variation to enable the full potential of genome editing in agriculture.

The complex genetic architecture of shoot growth natural variation in Arabidopsis thaliana

One of the main outcomes of quantitative genetics approaches to natural variation is to reveal the genetic architecture underlying the phenotypic space. Complex genetic architectures are described as including numerous loci (or alleles) with small-effect and/or low-frequency in the populations, interactions with the genetic background, environment or age. Linkage or association mapping strategies will be more or less sensitive to this complexity, so that we still have an unclear picture of its extent. By combining high-throughput phenotyping under two environmental conditions with classical QTL mapping approaches in multiple Arabidopsis thaliana segregating populations as well as advanced near isogenic lines construction and survey, we have attempted to improve our understanding of quantitative phenotypic variation. Integrative traits such as those related to vegetative growth used in this work (highlighting either cumulative growth, growth rate or morphology) all showed complex and dynamic genetic architecture with respect to the segregating population and condition. The more resolutive our mapping approach, the more complexity we uncover, with several instances of QTLs visible in near isogenic lines but not detected with the initial QTL mapping, indicating that our phenotyping accuracy was less limiting than the mapping resolution with respect to the underlying genetic architecture. In an ultimate approach to resolve this complexity, we intensified our phenotyping effort to target specifically a 3Mb-region known to segregate for a major quantitative trait gene, using a series of selected lines recombined every 100kb. We discovered that at least 3 other independent QTLs had remained hidden in this region, some with trait- or condition-specific effects, or opposite allelic effects. If we were to extrapolate the figures obtained on this specific region in this particular cross to the genome- and species-scale, we would predict hundreds of causative loci of detectable phenotypic effect controlling these growth-related phenotypes.

Kernel size-related genes revealed by an integrated eQTL analysis during early maize kernel development

In maize, kernel traits strongly impact overall grain yields, and it is known that sophisticated spatiotemporal programs of gene expression coordinate kernel development, so advancing our knowledge of kernel development can help efforts to improve grain yields. Here, using phenotype, genotype and transcriptomics data of maize kernels at 5 and 15 days after pollination (DAP) for a large association mapping panel, we employed multiple quantitative genetics approaches-genome-wide association studies (GWAS) as well as expression quantitative trait loci (eQTL) and quantitative trait transcript (QTT) analyses-to gain insights about molecular genetic basis of kernel development in maize. This resulted in the identification of 137 putative kernel length-related genes at 5 DAP, of which 43 are located in previously reported QTL regions. Strikingly, we identified an eQTL that overlaps the locus encoding a maize homolog of the recently described m⁶ A methylation reader protein ECT2 from Arabidopsis; this putative ^epi eQTL is associated with 53 genes and may represent a master epi-transcriptomic regulator of kernel development. Notably, among the genes associated with this ^epi eQTL, 10 are for the main storage proteins in the maize endosperm (zeins) and two are known regulators of zein expression or endosperm development (Opaque2 and ZmICE1). Collectively, beyond cataloging and characterizing genomic attributes of a large number of eQTL associated with kernel development in maize, our study highlights how an eQTL approach can bolster the impact of both GWAS and QTT studies and can drive insights about the basic biology of plants.

Cumulative and different genetic effects contributed to yield heterosis using maternal and paternal backcross populations in Upland cotton

Heterosis has been utilized in commercial production, but the heterosis mechanism has remained vague. Hybrid cotton is suitable to dissect the heterosis mechanism. In order to explore the genetic basis of heterosis in Upland cotton, we generated paternal and maternal backcross (BC/P and BC/M) populations. Data for yield and yield-component traits were collected over 2 years in three replicated BC/P field trials and four replicated BC/M field trials. At single-locus level, 26 and 27 QTLs were identified in BC/P and BC/M populations, respectively. Six QTLs shared in both BC populations. A total of 27 heterotic loci were detected. Partial dominant and over-dominant QTLs mainly determined yield heterosis in the BC/P and BC/M populations. QTLs for different traits displayed varied genetic effects in two BC populations. Eleven heterotic loci overlapped with QTLs but no common heterotic locus was detected in both BC populations. We resolved the 333 kb (48 genes) and 516 kb (25 genes) physical intervals based on 16 QTL clusters and 35 common QTLs, respectively, in more than one environment or population. We also identified 189 epistatic QTLs and a number of QTL × environment interactions in two BC populations and the corresponding MPH datasets. The results indicated that cumulative effects contributed to yield heterosis in Upland cotton, including epistasis, QTL × environment interaction, additive, partial dominance and over-dominance.

Rapid gene cloning in cereals

The large and complex genomes of many cereals hindered cloning efforts in the past. Advances in genomics now allow the rapid cloning of genes from humanity's most valuable crops. The past two decades were characterized by a genomics revolution that entailed profound changes to crop research, plant breeding, and agriculture. Today, high-quality reference sequences are available for all major cereal crop species. Large resequencing and pan-genome projects start to reveal a more comprehensive picture of the genetic makeup and the diversity among domesticated cereals and their wild relatives. These technological advancements will have a dramatic effect on dissecting genotype-phenotype associations and on gene cloning. In this review, we will highlight the status of the genomic resources available for various cereal crops and we will discuss their implications for gene cloning. A particular focus will be given to the cereal species barley and wheat, which are characterized by very large and complex genomes that have been inaccessible to rapid gene cloning until recently. With the advancements in genomics and the development of several rapid gene-cloning methods, it has now become feasible to tackle the cloning of most agriculturally important genes, even in wheat and barley.

Converging phenomics and genomics to study natural variation in plant photosynthetic efficiency

In recent years developments in plant phenomic approaches and facilities have gradually caught up with genomic approaches. An opportunity lies ahead to dissect complex, quantitative traits when both genotype and phenotype can be assessed at a high level of detail. This is especially true for the study of natural variation in photosynthetic efficiency, for which forward genetics studies have yielded only a little progress in our understanding of the genetic layout of the trait. High-throughput phenotyping, primarily from chlorophyll fluorescence imaging, should help to dissect the genetics of photosynthesis at the different levels of both plant physiology and development. Specific emphasis should be directed towards understanding the acclimation of the photosynthetic machinery in fluctuating environments, which may be crucial for the identification of genetic variation for relevant traits in food crops. Facilities should preferably be designed to accommodate phenotyping of photosynthesis-related traits in such environments. The use of forward genetics to study the genetic architecture of photosynthesis is likely to lead to the discovery of novel traits and/or genes that may be targeted in breeding or bio-engineering approaches to improve crop photosynthetic efficiency. In the near future, big data approaches will play a pivotal role in data processing and streamlining the phenotype-to-gene identification pipeline.

Computer vision-based phenotyping for improvement of plant productivity: a machine learning perspective

Employing computer vision to extract useful information from images and videos is becoming a key technique for identifying phenotypic changes in plants. Here, we review the emerging aspects of computer vision for automated plant phenotyping. Recent advances in image analysis empowered by machine learning-based techniques, including convolutional neural network-based modeling, have expanded their application to assist high-throughput plant phenotyping. Combinatorial use of multiple sensors to acquire various spectra has allowed us to noninvasively obtain a series of datasets, including those related to the development and physiological responses of plants throughout their life. Automated phenotyping platforms accelerate the elucidation of gene functions associated with traits in model plants under controlled conditions. Remote sensing techniques with image collection platforms, such as unmanned vehicles and tractors, are also emerging for large-scale field phenotyping for crop breeding and precision agriculture. Computer vision-based phenotyping will play significant roles in both the nowcasting and forecasting of plant traits through modeling of genotype/phenotype relationships.