Genetic Properties of a Nested Association Mapping Population Constructed With Semi-Winter and Spring Oilseed Rapes

Quantitative trait locus mapping and identification of candidate genes for resistance to Verticillium wilt in four recombinant inbred line populations of Gossypium hirsutum

Improving resistance to Verticillium wilt is of great significance for achieving high and stable yields of Upland cotton (Gossypium hirsutum). To deeply understand the genetic basis of cotton resistance to Verticillium wilt, Verticillium wilt-resistant Upland Lumianyan 28 and four Verticillium wilt-susceptible Acala cotton cultivars were used to create four recombinant inbred line (RIL) populations of 469 families through nested hybridization. Phenotypic data collected in five stressful environments were used to select resistant and sensitive lines and create a mixed pool of extreme phenotypes for BSA-seq. A total of 8 QTLs associated with Verticillium wilt resistance were identified on 4 chromosomes, of which qVW-A12-5 was detected simultaneously in the RIL populations and in one of the RIL populations and was identified for the first time. According to the sequence comparison and transcriptome analysis of candidate genes in the QTL interval between parents and pools, 4 genes were identified in the qVW-A12-5 interval. qRT-PCR of parental and phenotypically extreme lines revealed that Gh_CPR30 was induced by and may be a candidate gene for resistance to Verticillium wilt in G. hirsutum. Furthermore, VIGS technology revealed that the disease severity index (DSI) of the Gh_CPR30-silenced plants was significantly higher than that of the control. These results indicate that the Gh_CPR30 gene plays an important role in the resistance of G. hirsutum to Verticillium wilt, and the study provides a molecular basis for analyzing the molecular mechanism underlying G. hirsutum resistance to Verticillium wilt.

BnGF14-2c Positively Regulates Flowering via the Vernalization Pathway in Semi-Winter Rapeseed

14-3-3s are general regulatory factors (GF14s or GRFs) involved in a variety of physiological regulations in plants, including the control of flowering time. However, there are poorly relevant reports in rapeseed so far. In this study, we identified a homologous 14-3-3 gene BnGF14-2c (AtGRF2_Like in Brassica napus) in rapeseed based on bioinformatic analysis by using the sequences of the flowering-related 14-3-3s in other plant species. Then, we found that overexpression of BnGF14-2c in the semi-winter rapeseed “93275” promoted flowering without vernalization. Moreover, both yeast two-hybrid and bimolecular fluorescence complementation analysis indicated that BnGF14-2c may interact with two vernalization-related flowering regulators BnFT.A02 and BnFLC.A10., respectively. qPCR analysis showed that the expression of BnFT (AtFT_Like) was increased and the expression of two selected vernalization-related genes were reduced in the overexpression transgenic plants. Further investigation on subcellular localization demonstrated that BnGF14-2c localized in the nucleus and cytoplasm. The results of RNA-seq analysis and GUS staining indicated that BnGF14-2c is ubiquitously expressed except for mature seed coat. In general, the interaction of 14-3-3 and FLC was firstly documented in this study, indicating BnGF14-2c may act as a positive regulator of flowering in rapeseed, which is worthy for more in-depth exploration.

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.

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.

Germplasm Resources and Strategy for Genetic Breeding of Lycium Species: A Review

Lycium species (goji), belonging to Solanaceae, are widely spread in the arid to semiarid environments of Eurasia, Africa, North and South America, among which most species have affinal drug and diet functions, resulting in their potential to be a superior healthy food. However, compared with other crop species, scientific research on breeding Lycium species lags behind. This review systematically introduces the present germplasm resources, cytological examination and molecular-assisted breeding progress in Lycium species. Introduction of the distribution of Lycium species around the world could facilitate germplasm collection for breeding. Karyotypes of different species could provide a feasibility analysis of fertility between species. The introduction of mapping technology has discussed strategies for quantitative trait locus (QTL) mapping in Lycium species according to different kinds of traits. Moreover, to extend the number of traits and standardize the protocols of trait detection, we also provide 1,145 potential traits (275 agronomic and 870 metabolic) in different organs based on different reference studies on Lycium, tomato and other Solanaceae species. Finally, perspectives on goji breeding research are discussed and concluded. This review will provide breeders with new insights into breeding Lycium species.

Exploiting High-Throughput Indoor Phenotyping to Characterize the Founders of a Structured B. napus Breeding Population

Phenotyping is considered a significant bottleneck impeding fast and efficient crop improvement. Similar to many crops, Brassica napus, an internationally important oilseed crop, suffers from low genetic diversity, and will require exploitation of diverse genetic resources to develop locally adapted, high yielding and stress resistant cultivars. A pilot study was completed to assess the feasibility of using indoor high-throughput phenotyping (HTP), semi-automated image processing, and machine learning to capture the phenotypic diversity of agronomically important traits in a diverse B. napus breeding population, SKBnNAM, introduced here for the first time. The experiment comprised 50 spring-type B. napus lines, grown and phenotyped in six replicates under two treatment conditions (control and drought) over 38 days in a LemnaTec Scanalyzer 3D facility. Growth traits including plant height, width, projected leaf area, and estimated biovolume were extracted and derived through processing of RGB and NIR images. Anthesis was automatically and accurately scored (97% accuracy) and the number of flowers per plant and day was approximated alongside relevant canopy traits (width, angle). Further, supervised machine learning was used to predict the total number of raceme branches from flower attributes with 91% accuracy (linear regression and Huber regression algorithms) and to identify mild drought stress, a complex trait which typically has to be empirically scored (0.85 area under the receiver operating characteristic curve, random forest classifier algorithm). The study demonstrates the potential of HTP, image processing and computer vision for effective characterization of agronomic trait diversity in B. napus, although limitations of the platform did create significant variation that limited the utility of the data. However, the results underscore the value of machine learning for phenotyping studies, particularly for complex traits such as drought stress resistance.

Genetic characterization of a Sorghum bicolor multiparent mapping population emphasizing carbon-partitioning dynamics

Sorghum bicolor, a photosynthetically efficient C₄ grass, represents an important source of grain, forage, fermentable sugars, and cellulosic fibers that can be utilized in myriad applications ranging from bioenergy to bioindustrial feedstocks. Sorghum’s efficient fixation of carbon per unit time per unit area per unit input has led to its classification as a preferred biomass crop highlighted by its designation as an advanced biofuel by the U.S. Department of Energy. Due to its extensive genetic diversity and worldwide colonization, sorghum has considerable diversity for a range of phenotypes influencing productivity, composition, and sink/source dynamics. To dissect the genetic basis of these key traits, we present a sorghum carbon-partitioning nested association mapping (NAM) population generated by crossing 11 diverse founder lines with Grassl as the single recurrent female. By exploiting existing variation among cellulosic, forage, sweet, and grain sorghum carbon partitioning regimes, the sorghum carbon-partitioning NAM population will allow the identification of important biomass-associated traits, elucidate the genetic architecture underlying carbon partitioning and improve our understanding of the genetic determinants affecting unique phenotypes within Poaceae. We contrast this NAM population with an existing grain population generated using Tx430 as the recurrent female. Genotypic data are assessed for quality by examining variant density, nucleotide diversity, linkage decay, and are validated using pericarp and testa phenotypes to map known genes affecting these phenotypes. We release the 11-family NAM population along with corresponding genomic data for use in genetic, genomic, and agronomic studies with a focus on carbon-partitioning regimes.

Genetic Dissection of Seedling Root System Architectural Traits in a Diverse Panel of Hexaploid Wheat through Multi-Locus Genome-Wide Association Mapping for Improving Drought Tolerance

Cultivars with efficient root systems play a major role in enhancing resource use efficiency, particularly water absorption, and thus in drought tolerance. In this study, a diverse wheat association panel of 136 wheat accessions including mini core subset was genotyped using Axiom 35k Breeders' Array to identify genomic regions associated with seedling stage root architecture and shoot traits using multi-locus genome-wide association studies (ML-GWAS). The association panel revealed a wide variation of 1.5- to 50-fold and were grouped into six clusters based on 15 traits. Six different ML-GWAS models revealed 456 significant quantitative trait nucleotides (QTNs) for various traits with phenotypic variance in the range of 0.12-38.60%. Of these, 87 QTNs were repeatedly detected by two or more models and were considered reliable genomic regions for the respective traits. Among these QTNs, eleven were associated with average diameter and nine each for second order lateral root number (SOLRN), root volume (RV) and root length density (RLD). A total of eleven genomic regions were pleiotropic and each controlled two or three traits. Some important candidate genes such as Formin homology 1, Ubiquitin-like domain superfamily and ATP-dependent 6-phosphofructokinase were identified from the associated genomic regions. The genomic regions/genes identified in this study could potentially be targeted for improving root traits and drought tolerance in wheat.

Development of an Aus-Derived Nested Association Mapping (Aus-NAM) Population in Rice

A genetic resource for studying genetic architecture of agronomic traits and environmental adaptation is essential for crop improvements. Here, we report the development of a rice nested association mapping population (aus-NAM) using 7 aus varieties as diversity donors and T65 as the common parent. Aus-NAM showed broad phenotypic variations. To test whether aus-NAM was useful for quantitative trait loci (QTL) mapping, known flowering genes (Ehd1, Hd1, and Ghd7) in rice were characterized using single-family QTL mapping, joint QTL mapping, and the methods based on genome-wide association study (GWAS). Ehd1 was detected in all the seven families and all the methods. On the other hand, Hd1 and Ghd7 were detected in some families, and joint QTL mapping and GWAS-based methods resulted in weaker and uncertain peaks. Overall, the high allelic variations in aus-NAM provide a valuable genetic resource for the rice community.

Bulked segregant analysis reveals candidate genes responsible for dwarf formation in woody oilseed crop castor bean

Plant dwarfism is a desirable agronomic trait in non-timber trees, but little is known about the physiological and molecular mechanism underlying dwarfism in woody plants. Castor bean (Ricinus communis) is a typical woody oilseed crop. We performed cytological observations within xylem, phloem and cambia tissues, revealing that divergent cell growth in all tissues might play a role in the dwarf phenotype in cultivated castor bean. Based on bulked segregant analyses for a F2 population generated from the crossing of a tall and a dwarf accession, we identified two QTLs associated with plant height, covering 325 candidate genes. One of these, Rc5NG4-1 encoding a putative IAA transport protein localized in the tonoplast was functionally characterized. A non-synonymous SNP (altering the amino acid sequence from Y to C at position 218) differentiated the tall and dwarf plants and we confirmed, through heterologous yeast transformation, that the IAA uptake capacities of Rc5NG4-1Y and Rc5NG4-1C were significantly different. This study provides insights into the physiological and molecular mechanisms of dwarfing in woody non-timber economically important plants, with potential to aid in the genetic breeding of castor bean and other related crops.

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.

High-throughput phenotyping accelerates the dissection of the dynamic genetic architecture of plant growth and yield improvement in rapeseed

Rapeseed is the second most important oil crop species and is widely cultivated worldwide. However, overcoming the 'phenotyping bottleneck' has remained a significant challenge. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In addition, it is important to explore the dynamic genetic architecture underlying rapeseed plant growth and its contribution to final yield. In this work, a high-throughput phenotyping facility was used to dynamically screen a rapeseed intervarietal substitution line population during two growing seasons. We developed an automatic image analysis pipeline to quantify 43 dynamic traits across multiple developmental stages, with 12 time points. The time-resolved i-traits could be extracted to reflect shoot growth and predict the final yield of rapeseed. Broad phenotypic variation and high heritability were observed for these i-traits across all developmental stages. A total of 337 and 599 QTLs were identified, with 33.5% and 36.1% consistent QTLs for each trait across all 12 time points in the two growing seasons, respectively. Moreover, the QTLs responsible for yield indicators colocalized with those of final yield, potentially providing a new mechanism of yield regulation. Our results indicate that high-throughput phenotyping can provide novel insights into the dynamic genetic architecture of rapeseed growth and final yield, which would be useful for future genetic improvements in rapeseed.

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.

Nested-association mapping (NAM)-based genetic dissection uncovers candidate genes for seed and pod weights in peanut (Arachis hypogaea)

Multiparental genetic mapping populations such as nested-association mapping (NAM) have great potential for investigating quantitative traits and associated genomic regions leading to rapid discovery of candidate genes and markers. To demonstrate the utility and power of this approach, two NAM populations, NAM_Tifrunner and NAM_Florida-07, were used for dissecting genetic control of 100-pod weight (PW) and 100-seed weight (SW) in peanut. Two high-density SNP-based genetic maps were constructed with 3341 loci and 2668 loci for NAM_Tifrunner and NAM_Florida-07, respectively. The quantitative trait locus (QTL) analysis identified 12 and 8 major effect QTLs for PW and SW, respectively, in NAM_Tifrunner, and 13 and 11 major effect QTLs for PW and SW, respectively, in NAM_Florida-07. Most of the QTLs associated with PW and SW were mapped on the chromosomes A05, A06, B05 and B06. A genomewide association study (GWAS) analysis identified 19 and 28 highly significant SNP-trait associations (STAs) in NAM_Tifrunner and 11 and 17 STAs in NAM_Florida-07 for PW and SW, respectively. These significant STAs were co-localized, suggesting that PW and SW are co-regulated by several candidate genes identified on chromosomes A05, A06, B05, and B06. This study demonstrates the utility of NAM population for genetic dissection of complex traits and performing high-resolution trait mapping in peanut.

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.

Maximising recombination across macadamia populations to generate linkage maps for genome anchoring

The Proteaceae genus Macadamia has a recent history of domestication as a commercial nut crop. We aimed to establish the first sequence-based haploid-correlated reference genetic linkage maps for this primarily outcrossing perennial tree crop, with marker density suitable for genome anchoring. Four first generation populations were used to maximise the segregation patterns available within full-sib, biparental and self-pollinated progeny. This allowed us to combine segregation data from overlapping subsets of >4,000 informative sequence-tagged markers to increase the effective coverage of the karyotype represented by the recombinant crossover events detected. All maps had 14 linkage groups, corresponding to the Macadamia haploid chromosome number, and enabled the anchoring and orientation of sequence scaffolds to construct a pseudo-chromosomal genome assembly for macadamia. Comparison of individual maps indicated a high level of congruence, with minor discrepancies satisfactorily resolved within the integrated maps. The combined set of maps significantly improved marker density and the proportion (70%) of the genome sequence assembly anchored. Overall, increasing our understanding of the genetic landscape and genome for this nut crop represents a substantial advance in macadamia genetics and genomics. The set of maps, large number of sequence-based markers and the reconstructed genome provide a toolkit to underpin future breeding that should help to extend the macadamia industry as well as provide resources for the long term conservation of natural populations in eastern Australia of this unique genus.

Eight high-quality genomes reveal pan-genome architecture and ecotype differentiation of Brassica napus

Rapeseed (Brassica napus) is the second most important oilseed crop in the world but the genetic diversity underlying its massive phenotypic variations remains largely unexplored. Here, we report the sequencing, de novo assembly and annotation of eight B. napus accessions. Using pan-genome comparative analysis, millions of small variations and 77.2-149.6 megabase presence and absence variations (PAVs) were identified. More than 9.4% of the genes contained large-effect mutations or structural variations. PAV-based genome-wide association study (PAV-GWAS) directly identified causal structural variations for silique length, seed weight and flowering time in a nested association mapping population with ZS11 (reference line) as the donor, which were not detected by single-nucleotide polymorphisms-based GWAS (SNP-GWAS), demonstrating that PAV-GWAS was complementary to SNP-GWAS in identifying associations to traits. Further analysis showed that PAVs in three FLOWERING LOCUS C genes were closely related to flowering time and ecotype differentiation. This study provides resources to support a better understanding of the genome architecture and acceleration of the genetic improvement of B. napus.