TeoNAM: A Nested Association Mapping Population for Domestication and Agronomic Trait Analysis in Maize

A regulatory network controlling developmental boundaries and meristem fates contributed to maize domestication

During domestication, early farmers selected different vegetative and reproductive traits, but identifying the causative loci has been hampered by their epistasis and functional redundancy. Using chromatin immunoprecipitation sequencing combined with genome-wide association analysis, we uncovered a developmental regulator that controls both types of trait while acting upstream of multiple domestication loci. tasselsheath4 (tsh4) is a new maize domestication gene that establishes developmental boundaries and specifies meristem fates despite not being expressed within them. TSH4 accomplishes this by using a double-negative feedback loop that targets and represses the very same microRNAs that negatively regulate it. TSH4 functions redundantly with a pair of homologs to positively regulate a suite of domestication loci while specifying the meristem that doubled seed yield in modern maize. TSH4 has a critical role in yield gain and helped generate ideal crop plant architecture, thus explaining why it was a major domestication target.

The construction of a maize-teosinte introgression population and quantitative trait loci analysis of their 21 agronomic traits

Teosinte is a progenitor species of maize (Zea mays ssp. mays) that retains a significant reservoir of genetic resources unaltered via the domestication process. To harness and explore the genetic reservoirs inherent in teosinte, we used the cultivated publicly inbred line H95 and wild species PI566673 (Zea mays ssp. mexicana) to develop a set of introgression lines (ILs), including 366 BC2F5 lines. Using these lines, 12481 high-quality polymorphic homozygous single nucleotide polymorphisms were converted into 2358 bin markers based on Genotyping by Target Sequencing technology. The homozygous introgression ratio in the ILs was approximately 12.1 % and the heterozygous introgression ratio was approximately 5.7 %. Based on the population phenotypic data across 21 important agronomic traits collected in Sanya and Beijing, 185 and 156 quantitative trait loci (QTLs) were detected in Sanya and Beijing, respectively, with 64 stable QTLs detected in both locations. We detected 12 QTL clusters spanning 10 chromosomes consisting of diverse QTLs related to yield traits such as grain size and weight. In addition, we identified useful materials in the ILs for further gene cloning of related variations. For example, some heterogeneous inbred families with superior genetic purity, shorter target heterozygotes, and some ILs exhibit clear morphological variation associated with plant growth, development, and domestication, manifesting traits such as white stalks, sharp seeds, and cob shattering. In conclusion, our results provide a robust foundation for delving into the genetic reservoirs of teosinte, presenting a wealth of genetic resources and offering insight into the genetic architecture underlying maize agronomic traits.

Natural variation of CT2 affects the embryo/kernel weight ratio in maize

Embryo size is a critical trait determining not only grain yield but also the nutrition of the maize kernel. Up to the present, only a few genes have been characterized affecting the maize embryo/kernel ratio. Here, we identify 63 genes significantly associated with maize embryo/kernel weight ratio using a genome-wide association study (GWAS). The peak GWAS signal shows that the natural variation in Zea mays COMPACT PLANT2 (CT2), encoding the heterotrimeric G protein α subunit, is significantly associated with the Embryo/Kernel Weight Ratio (EKWR). Further analyses show that a missense mutation of CT2 increases its enzyme activity and associates with EKWR. The function of CT2 on affecting embryo/kernel weight ratio is further validated by the characterization of two ct2 mutants, for which EKWR is significantly decreased. Subsequently, the key downstream genes of CT2 are identified by combining the differential expression analysis (DEG) of the ct2 mutant and quantitative trait transcript analysis in the GWAS population. In addition, the allele frequency spectrum shows that CT2 was under selective pressure during maize domestication. This study provides important genetic insights into the natural variation of maize embryo/kernel weight ratio, which could be applied in future maize breeding programs to improve grain yield and nutritional content.

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

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

Multi-omics-driven advances in the understanding of triacylglycerol biosynthesis in oil seeds

Vegetable oils are rich sources of polyunsaturated fatty acids and energy as well as valuable sources of human food, animal feed, and bioenergy. Triacylglycerols, which are comprised of three fatty acids attached to a glycerol backbone, are the main component of vegetable oils. Here, we review the development and application of multiple-level omics in major oilseeds and emphasize the progress in the analysis of the biological roles of key genes underlying seed oil content and quality in major oilseeds. Finally, we discuss future research directions in functional genomics research based on current omics and oil metabolic engineering strategies that aim to enhance seed oil content and quality, and specific fatty acids components according to either human health needs or industrial requirements.

Two teosintes made modern maize

The origins of maize were the topic of vigorous debate for nearly a century, but neither the current genetic model nor earlier archaeological models account for the totality of available data, and recent work has highlighted the potential contribution of a wild relative, Zea mays ssp. mexicana. Our population genetic analysis reveals that the origin of modern maize can be traced to an admixture between ancient maize and Zea mays ssp. mexicana in the highlands of Mexico some 4000 years after domestication began. We show that variation in admixture is a key component of maize diversity, both at individual loci and for additive genetic variation underlying agronomic traits. Our results clarify the origin of modern maize and raise new questions about the anthropogenic mechanisms underlying dispersal throughout the Americas.

Leveraging Single-Cell Populations to Uncover the Genetic Basis of Complex Traits

The ease and throughput of single-cell genomics have steadily improved, and its current trajectory suggests that surveying single-cell populations will become routine. We discuss the merger of quantitative genetics with single-cell genomics and emphasize how this synergizes with advantages intrinsic to plants. Single-cell population genomics provides increased detection resolution when mapping variants that control molecular traits, including gene expression or chromatin accessibility. Additionally, single-cell population genomics reveals the cell types in which variants act and, when combined with organism-level phenotype measurements, unveils which cellular contexts impact higher-order traits. Emerging technologies, notably multiomics, can facilitate the measurement of both genetic changes and genomic traits in single cells, enabling single-cell genetic experiments. The implementation of single-cell genetics will advance the investigation of the genetic architecture of complex molecular traits and provide new experimental paradigms to study eukaryotic genetics.

Data-driven approaches to improve water-use efficiency and drought resistance in crop plants

With the increasing population, there lies a pressing demand for food, feed and fibre, while the changing climatic conditions pose severe challenges for agricultural production worldwide. Water is the lifeline for crop production; thus, enhancing crop water-use efficiency (WUE) and improving drought resistance in crop varieties are crucial for overcoming these challenges. Genetically-driven improvements in yield, WUE and drought tolerance traits can buffer the worst effects of climate change on crop production in dry areas. While traditional crop breeding approaches have delivered impressive results in increasing yield, the methods remain time-consuming and are often limited by the existing allelic variation present in the germplasm. Significant advances in breeding and high-throughput omics technologies in parallel with smart agriculture practices have created avenues to dramatically speed up the process of trait improvement by leveraging the vast volumes of genomic and phenotypic data. For example, individual genome and pan-genome assemblies, along with transcriptomic, metabolomic and proteomic data from germplasm collections, characterised at phenotypic levels, could be utilised to identify marker-trait associations and superior haplotypes for crop genetic improvement. In addition, these omics approaches enable the identification of genes involved in pathways leading to the expression of a trait, thereby providing an understanding of the genetic, physiological and biochemical basis of trait variation. These data-driven gene discoveries and validation approaches are essential for crop improvement pipelines, including genomic breeding, speed breeding and gene editing. Herein, we provide an overview of prospects presented using big data-driven approaches (including artificial intelligence and machine learning) to harness new genetic gains for breeding programs and develop drought-tolerant crop varieties with favourable WUE and high-yield potential traits.

Green revolution to genome revolution: driving better resilient crops against environmental instability

Crop improvement programmes began with traditional breeding practices since the inception of agriculture. Farmers and plant breeders continue to use these strategies for crop improvement due to their broad application in modifying crop genetic compositions. Nonetheless, conventional breeding has significant downsides in regard to effort and time. Crop productivity seems to be hitting a plateau as a consequence of environmental issues and the scarcity of agricultural land. Therefore, continuous pursuit of advancement in crop improvement is essential. Recent technical innovations have resulted in a revolutionary shift in the pattern of breeding methods, leaning further towards molecular approaches. Among the promising approaches, marker-assisted selection, QTL mapping, omics-assisted breeding, genome-wide association studies and genome editing have lately gained prominence. Several governments have progressively relaxed their restrictions relating to genome editing. The present review highlights the evolutionary and revolutionary approaches that have been utilized for crop improvement in a bid to produce climate-resilient crops observing the consequence of climate change. Additionally, it will contribute to the comprehension of plant breeding succession so far. Investing in advanced sequencing technologies and bioinformatics will deepen our understanding of genetic variations and their functional implications, contributing to breakthroughs in crop improvement and biodiversity conservation.

The Genetic Structures and Molecular Mechanisms Underlying Ear Traits in Maize (Zea mays L.)

Maize (Zea mays L.) is one of the world's staple food crops. In order to feed the growing world population, improving maize yield is a top priority for breeding programs. Ear traits are important determinants of maize yield, and are mostly quantitatively inherited. To date, many studies relating to the genetic and molecular dissection of ear traits have been performed; therefore, we explored the genetic loci of the ear traits that were previously discovered in the genome-wide association study (GWAS) and quantitative trait locus (QTL) mapping studies, and refined 153 QTL and 85 quantitative trait nucleotide (QTN) clusters. Next, we shortlisted 19 common intervals (CIs) that can be detected simultaneously by both QTL mapping and GWAS, and 40 CIs that have pleiotropic effects on ear traits. Further, we predicted the best possible candidate genes from 71 QTL and 25 QTN clusters that could be valuable for maize yield improvement.

QTL mapping identifies novel major loci for kernel row number-associated ear fasciation, ear prolificacy and tillering in maize (Zea mays L.)

Maize ear fasciation originates from excessive or abnormal proliferation of the ear meristem and usually manifests as flattened multiple-tipped ear and/or disordered kernel arrangement. Ear prolificacy expresses as multiple ears per plant or per node. Both ear fasciation and prolificacy can affect grain yield. The genetic control of the two traits was studied using two recombinant inbred line populations (B73 × Lo1016 and Lo964 × Lo1016) with Lo1016 and Lo964 as donors of ear fasciation and prolificacy, respectively. Ear fasciation-related traits, number of kernel rows (KRN), ear prolificacy and number of tillers were phenotyped in multi-year field experiments. Ear fasciation traits and KRN showed relatively high heritability (h ² > 0.5) except ratio of ear diameters. For all ear fasciation-related traits, fasciation level positively correlated with KRN (0.30 ≤ r ≤ 0.68). Prolificacy and tillering were not correlated and their h ² ranged from 0.41 to 0.78. QTL mapping identified four QTLs for ear fasciation, on chromosomes 1 (two QTLs), 5 and 7, the latter two overlapping with QTLs for number of kernel rows. Notably, at these QTLs, the Lo1016 alleles increased both ear fasciation and KRN across populations, thus showing potential breeding applicability. Four and five non-overlapping QTLs were mapped for ear prolificacy and tillering, respectively. Two ear fasciation QTLs, qFas1.2 and qFas7, overlapped with fasciation QTLs mapped in other studies and spanned compact plant2 and ramosa1 candidate genes. Our study identified novel ear fasciation loci and alleles positively affecting grain yield components, and ear prolificacy and tillering loci which are unexpectedly still segregating in elite maize materials, contributing useful information for genomics-assisted breeding programs.

Identification of two new QTLs of maize (Zea mays L.) underlying kernel row number using the HNAU-NAM1 population

BACKGROUND

Maize kernel row number (KRN) is one of the most important yield traits and has changed greatly during maize domestication and selection. Elucidating the genetic basis of KRN will be helpful to improve grain yield in maize.

RESULTS

Here, we measured KRN in four environments using a nested association mapping (NAM) population named HNAU-NAM1 with 1,617 recombinant inbred lines (RILs) that were derived from 12 maize inbred lines with a common parent, GEMS41. Then, five consensus quantitative trait loci (QTLs) distributing on four chromosomes were identified in at least three environments along with the best linear unbiased prediction (BLUP) values by the joint linkage mapping (JLM) method. These QTLs were further validated by the separate linkage mapping (SLM) and genome-wide association study (GWAS) methods. Three KRN genes cloned through the QTL assay were found in three of the five consensus QTLs, including qKRN1.1, qKRN2.1 and qKRN4.1. Two new QTLs of KRN, qKRN4.2 and qKRN9.1, were also identified. On the basis of public RNA-seq and genome annotation data, five genes highly expressed in ear tissue were considered candidate genes contributing to KRN.

CONCLUSIONS

This study carried out a comprehensive analysis of the genetic architecture of KRN by using a new NAM population under multiple environments. The present results provide solid information for understanding the genetic components underlying KRN and candidate genes in qKRN4.2 and qKRN9.1. Single-nucleotide polymorphisms (SNPs) closely linked to qKRN4.2 and qKRN9.1 could be used to improve inbred yield during molecular breeding in maize.

Linkage Mapping Reveals QTL for Flowering Time-Related Traits under Multiple Abiotic Stress Conditions in Maize

Variation in flowering plays a major role in maize photoperiod adaptation during long-term domestication. It is of high value to investigate the genetic basis of maize flowering under a wide range of environmental conditions in order to overcome photoperiod sensitivity or enhance stress tolerance. A recombinant inbred line (RIL) population derived from a cross between Huangzaosi and Mo17, composed of 121 lines and genotyped by 8329 specifically developed markers, was field evaluated in two consecutive years under two planting densities (67,500 and 120,000 plants ha−1) and two water treatments (normal irrigation and drought stress at the flowering stage). The days to silking (DTS), days to anthesis (DTA), and anthesis to silking interval (ASI) were all evaluated. Within the RIL population, DTS and DTA expanded as planting density and water deficit increased. For DTA, DTS, ASI, and ASI-delay, a total of 22, 17, 21, and 11 QTLs were identified, respectively. More than two significant QTLs were identified in each of the nine chromosomal intervals. Under diverse conditions and locations, six QTLs (quantitative trait locus) for DTS and DTA were discovered in Chr. 8: 118.13–125.31 Mb. Three chromosome regions, Chr. 3: 196.14–199.89 Mb, Chr. 8: 169.02–172.46 Mb, and Chr. 9: 128.12–137.26 Mb, all had QTLs for ASI-delay under normal and stress conditions, suggesting their possible roles in stress tolerance enhancement. These QTL hotspots will promote early-maturing or multiple abiotic stress-tolerant maize breeding, as well as shed light on the development of maize varieties with a broad range of adaptations.

Linkage mapping combined with GWAS revealed the genetic structural relationship and candidate genes of maize flowering time-related traits

BACKGROUND

Flowering time is an important agronomic trait of crops and significantly affects plant adaptation and seed production. Flowering time varies greatly among maize (Zea mays) inbred lines, but the genetic basis of this variation is not well understood. Here, we report the comprehensive genetic architecture of six flowering time-related traits using a recombinant inbred line (RIL) population obtained from a cross between two maize genotypes, B73 and Abe2, and combined with genome-wide association studies to identify candidate genes that affect flowering time.

RESULTS

Our results indicate that these six traits showed extensive phenotypic variation and high heritability in the RIL population. The flowering time of this RIL population showed little correlation with the leaf number under different environmental conditions. A genetic linkage map was constructed by 10,114 polymorphic markers covering the whole maize genome, which was applied to QTL mapping for these traits, and identified a total of 82 QTLs that contain 13 flowering genes. Furthermore, a combined genome-wide association study and linkage mapping analysis revealed 17 new candidate genes associated with flowering time.

CONCLUSIONS

In the present study, by using genetic mapping and GWAS approaches with the RIL population, we revealed a list of genomic regions and candidate genes that were significantly associated with flowering time. This work provides an important resource for the breeding of flowering time traits in maize.

How Could the Use of Crop Wild Relatives in Breeding Increase the Adaptation of Crops to Marginal Environments?

Alongside the use of fertilizer and chemical control of weeds, pests, and diseases modern breeding has been very successful in generating cultivars that have increased agricultural production several fold in favorable environments. These typically homogeneous cultivars (either homozygous inbreds or hybrids derived from inbred parents) are bred under optimal field conditions and perform well when there is sufficient water and nutrients. However, such optimal conditions are rare globally; indeed, a large proportion of arable land could be considered marginal for agricultural production. Marginal agricultural land typically has poor fertility and/or shallow soil depth, is subject to soil erosion, and often occurs in semi-arid or saline environments. Moreover, these marginal environments are expected to expand with ongoing climate change and progressive degradation of soil and water resources globally. Crop wild relatives (CWRs), most often used in breeding as sources of biotic resistance, often also possess traits adapting them to marginal environments. Wild progenitors have been selected over the course of their evolutionary history to maintain their fitness under a diverse range of stresses. Conversely, modern breeding for broad adaptation has reduced genetic diversity and increased genetic vulnerability to biotic and abiotic challenges. There is potential to exploit genetic heterogeneity, as opposed to genetic uniformity, in breeding for the utilization of marginal lands. This review discusses the adaptive traits that could improve the performance of cultivars in marginal environments and breeding strategies to deploy them.

Using breeding and quantitative genetics to understand the C4 pathway

Reducing photorespiration in C3 crops could significantly increase rates of photosynthesis and yield. One method to achieve this would be to integrate C4 photosynthesis into C3 species. This objective is challenging as it involves engineering incompletely understood traits into C3 leaves, including complex changes to their biochemistry, cell biology, and anatomy. Quantitative genetics and selective breeding offer underexplored routes to identify regulators of these processes. We first review examples of natural intraspecific variation in C4 photosynthesis as well as the potential for hybridization between C3 and C4 species. We then discuss how quantitative genetic approaches including artificial selection and genome-wide association could be used to better understand the C4 syndrome and in so doing guide the engineering of the C4 pathway into C3 crops.

Genetic dissection of maize plant architecture using a novel nested association mapping population

The leaf angle (LA), plant height (PH), and ear height (EH) are key plant architectural traits influencing maize (Zea mays L.) yield. However, their genetic determinants have not yet been well-characterized. Here, we developed a maize advanced backcross-nested association mapping population in Henan Agricultural University (HNAU-NAM1) comprised of 1,625 BC₁ F₄ /BC₂ F₄ lines. These were obtained by crossing a diverse set of 12 representative inbred lines with the common GEMS41 line, which were then genotyped using the MaizeSNP9.4K array. Genetic diversity and phenotypic distribution analyses showed considerable levels of genetic variation. We obtained 18-88 quantitative trait loci (QTLs) associated with LA, PH, and EH by using three complementary mapping methods, named as separate linkage mapping, joint linkage mapping, and genome-wide association studies. Our analyses enabled the identification of ten QTL hot-spot regions associated with the three traits, which were distributed on nine different chromosomes. We further selected 13 major QTLs that were simultaneously detected by three methods and deduced the candidate genes, of which eight were not reported before. The newly constructed HNAU-NAM1 population in this study will further broaden our insights into understanding of genetic regulation of plant architecture, thus will help to improve maize yield and provide an invaluable resource for maize functional genomics and breeding research.

Population genomics of Zea species identifies selection signatures during maize domestication and adaptation

BACKGROUND

Maize (Zea mays L. ssp. mays) was domesticated from teosinte (Zea mays ssp. parviglumis) about 9000 years ago in southwestern Mexico and adapted to a range of environments worldwide. Researchers have depicted the maize domestication and adaptation processes over the past two decades, but efforts have been limited either in sample size or genetic diversity. To better understand these processes, we conducted a genome-wide survey of 982 maize inbred lines and 190 teosinte accessions using over 40,000 single-nucleotide polymorphism markers.

RESULTS

Population structure, principal component analysis, and phylogenetic trees all confirmed the evolutionary relationship between maize and teosinte, and determined the evolutionary lineage of all species within teosinte. Shared haplotype analysis showed similar levels of ancestral alleles from Zea mays ssp. parviglumis and Zea mays ssp. mexicana in maize. Scans for selection signatures identified 394 domestication sweeps by comparing wild and cultivated maize and 360 adaptation sweeps by comparing tropical and temperate maize. Permutation tests revealed that the public association signals for flowering time were highly enriched in the domestication and adaptation sweeps. Genome-wide association study identified 125 loci significantly associated with flowering-time traits, ten of which identified candidate genes that have undergone selection during maize adaptation.

CONCLUSIONS

In this study, we characterized the history of maize domestication and adaptation at the population genomic level and identified hundreds of domestication and adaptation sweeps. This study extends the molecular mechanism of maize domestication and adaptation, and provides resources for basic research and genetic improvement in maize.

The arches and spandrels of maize domestication, adaptation, and improvement

People living in the Balsas River basin in southwest México domesticated maize from the bushy grass teosinte. Nine thousand years later, in 2021, Ms. Deb Haaland - a member of the Pueblo of Laguna tribe of New Mexico - wore a dress adorned with a cornstalk when she was sworn in as the Secretary of Interior of the United States of America. This choice of garment highlights the importance of the coevolution of maize and the farmers who, through careful selection over thousands of years, domesticated maize and adapted the physiology and shoot architecture of maize to fit local environments and growth habits. Some traits such as tillering were directly selected on (arches), and others such as tassel size are the by-products (spandrels) of maize evolution. Here, we review current knowledge of the underlying cellular, developmental, physiological, and metabolic processes that were selected by farmers and breeders, which have positioned maize as a top global staple crop.

QTL Map of Early- and Late-Stage Perennial Regrowth in Zea diploperennis

Numerous climate change threats will necessitate a shift toward more sustainable agricultural practices during the 21st century. Conversion of annual crops to perennials that are capable of regrowing over multiple yearly growth cycles could help to facilitate this transition. Perennials can capture greater amounts of carbon and access more water and soil nutrients compared to annuals. In principle it should be possible to identify genes that confer perenniality from wild relatives and transfer them into existing breeding lines to create novel perennial crops. Two major loci controlling perennial regrowth in the maize relative Zea diploperennis were previously mapped to chromosome 2 (reg1) and chromosome 7 (reg2). Here we extend this work by mapping perennial regrowth in segregating populations involving Z. diploperennis and the maize inbreds P39 and Hp301 using QTL-seq and traditional QTL mapping approaches. The results confirmed the existence of a major perennial regrowth QTL on chromosome 2 (reg1). Although we did not observe the reg2 QTL in these populations, we discovered a third QTL on chromosome 8 which we named regrowth3 (reg3). The reg3 locus exerts its strongest effect late in the regrowth cycle. Neither reg1 nor reg3 overlapped with tiller number QTL scored in the same population, suggesting specific roles in the perennial phenotype. Our data, along with prior work, indicate that perennial regrowth in maize is conferred by relatively few major QTL.

Genome-wide association studies: assessing trait characteristics in model and crop plants

GWAS involves testing genetic variants across the genomes of many individuals of a population to identify genotype–phenotype association. It was initially developed and has proven highly successful in human disease genetics. In plants genome-wide association studies (GWAS) initially focused on single feature polymorphism and recombination and linkage disequilibrium but has now been embraced by a plethora of different disciplines with several thousand studies being published in model and crop species within the last decade or so. Here we will provide a comprehensive review of these studies providing cases studies on biotic resistance, abiotic tolerance, yield associated traits, and metabolic composition. We also detail current strategies of candidate gene validation as well as the functional study of haplotypes. Furthermore, we provide a critical evaluation of the GWAS strategy and its alternatives as well as future perspectives that are emerging with the emergence of pan-genomic datasets.

Development of an Australian Bread Wheat Nested Association Mapping Population, a New Genetic Diversity Resource for Breeding under Dry and Hot Climates

Genetic diversity, knowledge of the genetic architecture of the traits of interest and efficient means of transferring the desired genetic diversity into the relevant genetic background are prerequisites for plant breeding. Exotic germplasm is a rich source of genetic diversity; however, they harbor undesirable traits that limit their suitability for modern agriculture. Nested association mapping (NAM) populations are valuable genetic resources that enable incorporation of genetic diversity, dissection of complex traits and providing germplasm to breeding programs. We developed the OzNAM by crossing and backcrossing 73 diverse exotic parents to two Australian elite varieties Gladius and Scout. The NAM parents were genotyped using the iSelect wheat 90K Infinium SNP array, and the progeny were genotyped using a custom targeted genotyping-by-sequencing assay based on molecular inversion probes designed to target 12,179 SNPs chosen from the iSelect wheat 90K Infinium SNP array of the parents. In total, 3535 BC1F4:6 RILs from 125 families with 21 to 76 lines per family were genotyped and we found 4964 polymorphic and multi-allelic haplotype markers that spanned the whole genome. A subset of 530 lines from 28 families were evaluated in multi-environment trials over three years. To demonstrate the utility of the population in QTL mapping, we chose to map QTL for maturity and plant height using the RTM-GWAS approach and we identified novel and known QTL for maturity and plant height.

New genomic approaches for enhancing maize genetic improvement

Maize (Zea mays) is one of the most widely grown crops in the world, with an annual global production of over 1147 million tons. Genomics approaches are thought to be the best solution for accelerating yield improvement to meet the challenges of a growing population and global climate change. Here, we review current approaches to the exploration of novel genetic variation in genomes, DNA modifications, and transcription levels of cultivated maize, landraces, and wild relatives. We discuss applications of genetic engineering to maize yield improvement and highlight future directions for maize genomics studies.

Developmental genetics of maize vegetative shoot architecture

More than 1.1 billion tonnes of maize grain were harvested across 197 million hectares in 2019 (FAOSTAT 2020). The vast global productivity of maize is largely driven by denser planting practices, higher yield potential per area of land, and increased yield potential per plant. Shoot architecture, the three-dimensional structural arrangement of the above-ground plant body, is critical to maize grain yield and biomass. Structure of the shoot is integral to all aspects of modern agronomic practices. Here, the developmental genetics of the maize vegetative shoot is reviewed. Plant architecture is ultimately determined by meristem activity, developmental patterning, and growth. The following topics are discussed: shoot apical meristem, leaf architecture, axillary meristem and shoot branching, and intercalary meristem and stem activity. Where possible, classical and current studies in maize developmental genetics, as well as recent advances leveraged by "-omics" analyses, are highlighted within these sections.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01208-1.

A Multi-Locus Association Model Framework for Nested Association Mapping With Discriminating QTL Effects in Various Subpopulations

Nested association mapping (NAM) has been an invaluable approach for plant genetics community and can dissect the genetic architecture of complex traits. As the most popular NAM analysis strategy, joint multifamily mapping can combine all information from diverse genetic backgrounds and increase population size. However, it is influenced by the genetic heterogeneity of quantitative trait locus (QTL) across various subpopulations. Multi-locus association mapping has been proven to be powerful in many cases of QTL mapping and genome-wide association studies. Therefore, we developed a multi-locus association model of multiple families in the NAM population, which could discriminate the effects of QTLs in all subpopulations. A series of simulations with a real maize NAM genomic data were implemented. The results demonstrated that the new method improves the statistical power in QTL detection and the accuracy in QTL effect estimation. The new approach, along with single-family linkage mapping, was used to identify QTLs for three flowering time traits in the maize NAM population. As a result, most QTLs detected in single family linkage mapping were identified by the new method. In addition, the new method also mapped some new QTLs with small effects, although their functions need to be identified in the future.

Harnessing Knowledge from Maize and Rice Domestication for New Crop Breeding

Crop domestication has fundamentally altered the course of human history, causing a shift from hunter-gatherer to agricultural societies and stimulating the rise of modern civilization. A greater understanding of crop domestication would provide a theoretical basis for how we could improve current crops and develop new crops to deal with environmental challenges in a sustainable manner. Here, we provide a comprehensive summary of the similarities and differences in the domestication processes of maize and rice, two major staple food crops that feed the world. We propose that maize and rice might have evolved distinct genetic solutions toward domestication. Maize and rice domestication appears to be associated with distinct regulatory and evolutionary mechanisms. Rice domestication tended to select de novo, loss-of-function, coding variation, while maize domestication more frequently favored standing, gain-of-function, regulatory variation. At the gene network level, distinct genetic paths were used to acquire convergent phenotypes in maize and rice domestication, during which different central genes were utilized, orthologous genes played different evolutionary roles, and unique genes or regulatory modules were acquired for establishing new traits. Finally, we discuss how the knowledge gained from past domestication processes, together with emerging technologies, could be exploited to improve modern crop breeding and domesticate new crops to meet increasing human demands.

Multiparental Population in Crops: Methods of Development and Dissection of Genetic Traits

Multiparental populations are located midway between association mapping that relies on germplasm collections and classic linkage analysis, based upon biparental populations. They provide several key advantages such as the possibility to include a higher number of alleles and increased level of recombination with respect to biparental populations, and more equilibrated allelic frequencies than association mapping panels. Moreover, in these populations new allele's combinations arise from recombination that may reveal transgressive phenotypes and make them a useful pre-breeding material. Here we describe the strategies for working with multiparental populations, focusing on nested association mapping populations (NAM) and multiparent advanced generation intercross populations (MAGIC). We provide details from the selection of founders, population development, and characterization to the statistical methods for genetic mapping and quantitative trait detection.

Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding

Crop populations derived from experimental crosses enable the genetic dissection of complex traits and support modern plant breeding. Among these, multi-parent populations now play a central role. By mixing and recombining the genomes of multiple founders, multi-parent populations combine many commonly sought beneficial properties of genetic mapping populations. For example, they have high power and resolution for mapping quantitative trait loci, high genetic diversity and minimal population structure. Many multi-parent populations have been constructed in crop species, and their inbred germplasm and associated phenotypic and genotypic data serve as enduring resources. Their utility has grown from being a tool for mapping quantitative trait loci to a means of providing germplasm for breeding programmes. Genomics approaches, including de novo genome assemblies and gene annotations for the population founders, have allowed the imputation of rich sequence information into the descendent population, expanding the breadth of research and breeding applications of multi-parent populations. Here, we report recent successes from crop multi-parent populations in crops. We also propose an ideal genotypic, phenotypic and germplasm 'package' that multi-parent populations should feature to optimise their use as powerful community resources for crop research, development and breeding.

Genomic interventions for sustainable agriculture

Agricultural production faces a Herculean challenge to feed the increasing global population. Food production systems need to deliver more with finite land and water resources while exerting the least negative influence on the ecosystem. The unpredictability of climate change and consequent changes in pests/pathogens dynamics aggravate the enormity of the challenge. Crop improvement has made significant contributions towards food security, and breeding climate-smart cultivars are considered the most sustainable way to accelerate food production. However, a fundamental change is needed in the conventional breeding framework in order to respond adequately to the growing food demands. Progress in genomics has provided new concepts and tools that hold promise to make plant breeding procedures more precise and efficient. For instance, reference genome assemblies in combination with germplasm sequencing delineate breeding targets that could contribute to securing future food supply. In this review, we highlight key breakthroughs in plant genome sequencing and explain how the presence of these genome resources in combination with gene editing techniques has revolutionized the procedures of trait discovery and manipulation. Adoption of new approaches such as speed breeding, genomic selection and haplotype-based breeding could overcome several limitations of conventional breeding. We advocate that strengthening varietal release and seed distribution systems will play a more determining role in delivering genetic gains at farmer's field. A holistic approach outlined here would be crucial to deliver steady stream of climate-smart crop cultivars for sustainable agriculture.

dlf1 promotes floral transition by directly activating ZmMADS4 and ZmMADS67 in the maize shoot apex

The floral transition of the maize (Zea mays ssp. mays) shoot apical meristem determines leaf number and flowering time, which are key traits influencing local adaptation and yield potential. dlf1 (delayed flowering1) encodes a basic leucine zipper protein that interacts with the florigen ZCN8 to mediate floral induction in the shoot apex. However, the mechanism of how dlf1 promotes floral transition remains largely unknown. We demonstrate that dlf1 underlies qLB7-1, a quantitative trait locus controlling leaf number and flowering time that was identified in a BC₂ S₃ population derived from a cross between maize and its wild ancestor, teosinte (Zea mays ssp. parviglumis). Transcriptome sequencing and chromatin immunoprecipitation sequencing demonstrated that DLF1 binds the core promoter of two AP1/FUL subfamily MADS-box genes, ZmMADS4 and ZmMADS67, to activate their expression. Knocking out ZmMADS4 and ZmMADS67 both increased leaf number and delayed flowering, indicating that they promote the floral transition. Nucleotide diversity analysis revealed that dlf1 and ZmMADS67 were targeted by selection, suggesting that they may have played important roles in maize flowering time adaptation. We show that dlf1 promotes maize floral transition by directly activating ZmMADS4 and ZmMADS67 in the shoot apex, providing novel insights into the mechanism of maize floral transition.

Adaptive introgression from maize has facilitated the establishment of teosinte as a noxious weed in Europe

Global trade has considerably accelerated biological invasions. The annual tropical teosintes, the closest wild relatives of maize, were recently reported as new agricultural weeds in two European countries, Spain and France. Their prompt settlement under climatic conditions differing drastically from that of their native range indicates rapid genetic evolution. We performed a phenotypic comparison of French and Mexican teosintes under European conditions and showed that only the former could complete their life cycle during maize cropping season. To test the hypothesis that crop-to-wild introgression triggered such rapid adaptation, we used single nucleotide polymorphisms to characterize patterns of genetic variation in French, Spanish, and Mexican teosintes as well as in maize germplasm. We showed that both Spanish and French teosintes originated from Zea mays ssp. mexicana race "Chalco," a weedy teosinte from the Mexican highlands. However, introduced teosintes differed markedly from their Mexican source by elevated levels of genetic introgression from the high latitude Dent maize grown in Europe. We identified a clear signature of divergent selection in a region of chromosome 8 introgressed from maize and encompassing ZCN8, a major flowering time gene associated with adaptation to high latitudes. Moreover, herbicide assays and sequencing revealed that French teosintes have acquired herbicide resistance via the introgression of a mutant herbicide-target gene (ACC1) present in herbicide-resistant maize cultivars. Altogether, our results demonstrate that adaptive crop-to-wild introgression has triggered both rapid adaptation to a new climatic niche and acquisition of herbicide resistance, thereby fostering the establishment of an emerging noxious weed.

Ten Years of the Maize Nested Association Mapping Population: Impact, Limitations, and Future Directions

It has been just over a decade since the release of the maize (Zea mays) Nested Association Mapping (NAM) population. The NAM population has been and continues to be an invaluable resource for the maize genetics community and has yielded insights into the genetic architecture of complex traits. The parental lines have become some of the most well-characterized maize germplasm, and their de novo assemblies were recently made publicly available. As we enter an exciting new stage in maize genomics, this retrospective will summarize the design and intentions behind the NAM population; its application, the discoveries it has enabled, and its influence in other systems; and use the past decade of hindsight to consider whether and how it will remain useful in a new age of genomics.

The genetic architecture of the maize progenitor, teosinte, and how it was altered during maize domestication

The genetics of domestication has been extensively studied ever since the rediscovery of Mendel's law of inheritance and much has been learned about the genetic control of trait differences between crops and their ancestors. Here, we ask how domestication has altered genetic architecture by comparing the genetic architecture of 18 domestication traits in maize and its ancestor teosinte using matched populations. We observed a strongly reduced number of QTL for domestication traits in maize relative to teosinte, which is consistent with the previously reported depletion of additive variance by selection during domestication. We also observed more dominance in maize than teosinte, likely a consequence of selective removal of additive variants. We observed that large effect QTL have low minor allele frequency (MAF) in both maize and teosinte. Regions of the genome that are strongly differentiated between teosinte and maize (high FST) explain less quantitative variation in maize than teosinte, suggesting that, in these regions, allelic variants were brought to (or near) fixation during domestication. We also observed that genomic regions of high recombination explain a disproportionately large proportion of heritable variance both before and after domestication. Finally, we observed that about 75% of the additive variance in both teosinte and maize is "missing" in the sense that it cannot be ascribed to detectable QTL and only 25% of variance maps to specific QTL. This latter result suggests that morphological evolution during domestication is largely attributable to very large numbers of QTL of very small effect.

Nested association mapping of important agronomic traits in three interspecific soybean populations

KEY MESSAGE

Glycine soja germplasm can be used to successfully introduce new alleles with the potential to add valuable new genetic diversity to the current elite soybean gene pool. Given the demonstrated narrow genetic base of the US soybean production, it is essential to identify beneficial alleles from exotic germplasm, such as wild soybean, to enhance genetic gain for favorable traits. Nested association mapping (NAM) is an approach to population development that permits the comparison of allelic effects of the same QTL in multiple parents. Seed yield, plant maturity, plant height and plant lodging were evaluated in a NAM panel consisting of 392 recombinant inbred lines derived from three biparental interspecific soybean populations in eight environments during 2016 and 2017. Nested association mapping, combined with linkage mapping, identified three major QTL for plant maturity in chromosomes 6, 11 and 12 associated with alleles from wild soybean resulting in significant increases in days to maturity. A significant QTL for plant height was identified on chromosome 13 with the allele increasing plant height derived from wild soybean. A significant grain yield QTL was detected on chromosome 17, and the allele from Glycine soja had a positive effect of 166 kg ha-1; RIL's with the wild soybean allele yielded on average 6% more than the lines carrying the Glycine max allele. These findings demonstrate the usefulness and potential of alleles from wild soybean germplasm to enhance important agronomic traits in a soybean breeding program.