A MAGIC population-based genome-wide association study reveals functional association of GhRBB1_A07 gene with superior fiber quality in cotton

Genome-wide association study of fiber quality traits in US upland cotton (Gossypium hirsutum L.)

KEY MESSAGE

A GWAS in an elite diversity panel, evaluated across 10 environments, identified genomic regions regulating six fiber quality traits, facilitating genomics-assisted breeding and gene discovery in upland cotton. In this study, an elite diversity panel of 348 upland cotton accessions was evaluated in 10 environments across the US Cotton Belt and genotyped with the cottonSNP63K array, for a genome-wide association study of six fiber quality traits. All fiber quality traits, upper half mean length (UHML: mm), fiber strength (FS: g tex-1), fiber uniformity (FU: %), fiber elongation (FE: %), micronaire (MIC) and short fiber content (SFC: %), showed high broad-sense heritability (> 60%). All traits except FE showed high genomic heritability. UHML, FS and FU were all positively correlated with each other and negatively correlated with FE, MIC and SFC. GWAS of these six traits identified 380 significant marker-trait associations (MTAs) including 143 MTAs on 30 genomic regions. These 30 genomic regions included MTAs identified in at least three environments, and 23 of them were novel associations. Phenotypic variation explained for the MTAs in these 30 genomic regions ranged from 6.68 to 11.42%. Most of the fiber quality-associated genomic regions were mapped in the D-subgenome. Further, this study confirmed the pleiotropic region on chromosome D11 (UHML, FS and FU) and identified novel co-localized regions on D04 (FU, SFC), D05 (UHML, FU, and D06 UHML, FU). Marker haplotype analysis identified superior combinations of fiber quality-associated genomic regions with high trait values (UHML = 32.34 mm; FS = 32.73 g tex-1; FE = 6.75%). Genomic analyses of traits, haplotype combinations and candidate gene information described in the current study could help leverage genetic diversity for targeted genetic improvement and gene discovery for fiber quality traits in cotton.

Unraveling the genetic and molecular basis of heat stress in cotton

Human activities and climate change have resulted in frequent and intense weather fluctuations, leading to diverse abiotic stresses on crops which hampers greatly their metabolic activities. Heat stress, a prevalent abiotic factor, significantly influences cotton plant biological activities resulting in reducing yield and production. We must deepen our understanding of how plants respond to heat stress across various dimensions, encompassing genes, RNAs, proteins, metabolites for effective cotton breeding. Multi-omics methods, primarily genomics, transcriptomics, proteomics, metabolomics, and phenomics, proves instrumental in studying cotton's responses to abiotic stresses. Integrating genomics, transcriptomics, proteomics, and metabolomic is imperative for our better understanding regarding genetics and molecular basis of heat tolerance in cotton. The current review explores fundamental omics techniques, covering genomics, transcriptomics, proteomics, and metabolomics, to highlight the progress made in cotton omics research.

Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea

Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013-14 and 2014-15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas.

Genome-wide association study of fiber yield-related traits uncovers the novel genomic regions and candidate genes in Indian upland cotton (Gossypium hirsutum L.)

Upland cotton (Gossypium hirsutum L.) is a major fiber crop that is cultivated worldwide and has significant economic importance. India harbors the largest area for cotton cultivation, but its fiber yield is still compromised and ranks 22nd in terms of productivity. Genetic improvement of cotton fiber yield traits is one of the major goals of cotton breeding, but the understanding of the genetic architecture underlying cotton fiber yield traits remains limited and unclear. To better decipher the genetic variation associated with fiber yield traits, we conducted a comprehensive genome-wide association mapping study using 117 Indian cotton germplasm for six yield-related traits. To accomplish this, we generated 2,41,086 high-quality single nucleotide polymorphism (SNP) markers using genotyping-by-sequencing (GBS) methods. Population structure, PCA, kinship, and phylogenetic analyses divided the germplasm into two sub-populations, showing weak relatedness among the germplasms. Through association analysis, 205 SNPs and 134 QTLs were identified to be significantly associated with the six fiber yield traits. In total, 39 novel QTLs were identified in the current study, whereas 95 QTLs overlapped with existing public domain data in a comparative analysis. Eight QTLs, qGhBN_SCY_D6-1, qGhBN_SCY_D6-2, qGhBN_SCY_D6-3, qGhSI_LI_A5, qGhLI_SI_A13, qGhLI_SI_D9, qGhBW_SCY_A10, and qGhLP_BN_A8 were identified. Gene annotation of these fiber yield QTLs revealed 2,509 unique genes. These genes were predominantly enriched for different biological processes, such as plant cell wall synthesis, nutrient metabolism, and vegetative growth development in the gene ontology (GO) enrichment study. Furthermore, gene expression analysis using RNAseq data from 12 diverse cotton tissues identified 40 candidate genes (23 stable and 17 novel genes) to be transcriptionally active in different stages of fiber, ovule, and seed development. These findings have revealed a rich tapestry of genetic elements, including SNPs, QTLs, and candidate genes, and may have a high potential for improving fiber yield in future breeding programs for Indian cotton.

Discovering useful genetic variation in the seed parent gene pool for sorghum improvement

Multi-parent populations contain valuable genetic material for dissecting complex, quantitative traits and provide a unique opportunity to capture multi-allelic variation compared to the biparental populations. A multi-parent advanced generation inter-cross (MAGIC) B-line (MBL) population composed of 708 F6 recombinant inbred lines (RILs), was recently developed from four diverse founders. These selected founders strategically represented the four most prevalent botanical races (kafir, guinea, durra, and caudatum) to capture a significant source of genetic variation to study the quantitative traits in grain sorghum [Sorghum bicolor (L.) Moench]. MBL was phenotyped at two field locations for seven yield-influencing traits: panicle type (PT), days to anthesis (DTA), plant height (PH), grain yield (GY), 1000-grain weight (TGW), tiller number per meter (TN) and yield per panicle (YPP). High phenotypic variation was observed for all the quantitative traits, with broad-sense heritabilities ranging from 0.34 (TN) to 0.84 (PH). The entire population was genotyped using Diversity Arrays Technology (DArTseq), and 8,800 single nucleotide polymorphisms (SNPs) were generated. A set of polymorphic, quality-filtered markers (3,751 SNPs) and phenotypic data were used for genome-wide association studies (GWAS). We identified 52 marker-trait associations (MTAs) for the seven traits using BLUPs generated from replicated plots in two locations. We also identified desirable allelic combinations based on the plant height loci (Dw1, Dw2, and Dw3), which influences yield related traits. Additionally, two novel MTAs were identified each on Chr1 and Chr7 for yield traits independent of dwarfing genes. We further performed a multi-variate adaptive shrinkage analysis and 15 MTAs with pleiotropic effect were identified. The five best performing MBL progenies were selected carrying desirable allelic combinations. Since the MBL population was designed to capture significant diversity for maintainer line (B-line) accessions, these progenies can serve as valuable resources to develop superior sorghum hybrids after validation of their general combining abilities via crossing with elite pollinators. Further, newly identified desirable allelic combinations can be used to enrich the maintainer germplasm lines through marker-assisted backcross breeding.

A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane

The sugarcane ratooning ability (RA) is the most important target trait for breeders seeking to enhance the profitability of sugarcane production by reducing the planting cost. Understanding the genetics governing the RA could help breeders by identifying molecular markers that could be used for genomics-assisted breeding (GAB). A replicated field trial was conducted for three crop cycles (plant cane, first ratoon, and second ratoon) using 432 sugarcane clones and used for conducting genome-wide association and genomic prediction of five sugar and yield component traits of the RA. The RA traits for economic index (EI), stalk population (SP), stalk weight (SW), tonns of cane per hectare (TCH), and tonns of sucrose per hectare (TSH) were estimated from the yield and sugar data. A total of six putative quantitative trait loci and eight nonredundant single-nucleotide polymorphism (SNP) markers were associated with all five tested RA traits and appear to be unique. Seven putative candidate genes were colocated with significant SNPs associated with the five RA traits. The genomic prediction accuracies for those tested traits were moderate and ranged from 0.21 to 0.36. However, the models fitting fixed effects for the most significant associated markers for each respective trait did not give any advantages over the standard models without fixed effects. As a result of this study, more robust markers could be used in the future for clone selection in sugarcane, potentially helping resolve the genetic control of the RA in sugarcane.

Identifying genomic regions determining shoot and root traits related to nitrogen uptake efficiency in a multiparent advanced generation intercross (MAGIC) winter wheat population in a high-throughput phenotyping facility

In the context of a continuously increasing human population that needs to be fed, with environmental protection in mind, nitrogen use efficiency (NUE) improvement is becoming very important. To understand the natural variation of traits linked to nitrogen uptake efficiency (UPE), one component of NUE, the multiparent advanced generation intercross (MAGIC) winter wheat population WM-800 was phenotyped under two contrasting nitrogen (N) levels in a high-throughput phenotyping facility for six weeks. Three biomass-related, three root-related, and two reflectance-related traits were measured weekly under each treatment. Subsequently, the population was genetically analysed using a total of 13,060 polymorphic haplotypes and singular SNPs for a genome-wide association study (GWAS). In total, we detected 543 quantitative trait loci (QTL) across all time points and traits, which were pooled into 42 stable QTL (sQTL; present in at least three of the six weeks). Besides Rht-B1 and Rht-D1, candidate genes playing a role in gibberellic acid-regulated growth and nitrate transporter genes from the NPF gene family, like NRT 1.1, were linked to sQTL. Two novel sQTL on chromosomes 5 A and 6D showed pleiotropic effects on several traits. The high number of N-specific sQTL indicates that selection for UPE is useful specifically under N-limited conditions.

Genome-wide association mapping for LLS resistance in a MAGIC population of groundnut (Arachis hypogaea L.)

The identified 30 functional nucleotide polymorphisms or genic SNP markers would offer essential information for marker-assisted breeding in groundnut. A genome-wide association study (GWAS) on component traits of LLS resistance in an eight-way multiparent advance generation intercross (MAGIC) population of groundnut in the field and in a light chamber (controlled conditions) was performed via an Affymetrix 48 K single-nucleotide polymorphism (SNP) 'Axiom Arachis' array. Multiparental populations with high-density genotyping enable the detection of novel alleles. In total, five quantitative trait loci (QTLs) with marker - log10(p value) scores ranging from 4.25 to 13.77 for the incubation period (IP) and six QTLs with marker - log10(p value) scores ranging from 4.33 to 10.79 for the latent period (LP) were identified across the A- and B-subgenomes. A total of 62 markers‒trait associations (MTAs) were identified across the A- and B-subgenomes. Markers for LLS scores and the area under the disease progression curve (AUDPC) recorded for plants in the light chamber and under field conditions presented - log10 (p value) scores ranging from 4.22 to 27.30. The highest number of MTAs (six) was identified on chromosomes A05, B07 and B09. Out of a total of 73 MTAs, 37 and 36 MTAs were detected in subgenomes A and B, respectively. Taken together, these results suggest that both subgenomes have equal potential genomic regions contributing to LLS resistance. A total of 30 functional nucleotide polymorphisms or genic SNP markers were detected, among which eight genes were found to encode leucine-rich repeat (LRR) receptor-like protein kinases and putative disease resistance proteins. These important SNPs can be used in breeding programmes for the development of cultivars with improved disease resistance.

Genomic confirmation of Gossypium barbadense introgression into G. hirsutum and a subsequent MAGIC population

Introgression of superior fiber traits from Pima cotton (Gossypium barbadense, GB) into high yield Upland cotton (G. hirsutum) has been a breeding objective for many years in a few breeding programs in the world. However, progress has been very slow due to introgression barriers resulting from whole genome hybridization between the two species. To minimize such barriers, chromosome substitution lines (CS-B) from Pima cotton 3-79 in an Upland cotton cultivar TM-1 were developed. A multiparent advanced generation inter-cross (MAGIC) population consisting of 180 recombinant inbred lines (RILs) was subsequently made using the 18 CS-B lines and three Upland cotton cultivars as parents. In this research, we sequenced the whole genomes of the 21 parents and 180 RILs to examine the G. barbadense introgression. Of the 18 CS-B lines, 11 contained the target GB chromosome or chromosome segment, two contained more than two GB chromosomes, and five did not have the expected introgression. Residual introgression in non-target chromosomes was prevalent in all CS-B lines. A clear structure existed in the MAGIC population and the 180 RILs were distributed into three groups, i.e., high, moderate, and low GB introgression. Large blocks of GB chromosome introgression were still present in some RILs after five cycles of random-mating, an indication of recombination suppression or other unknown reasons present in the population. Identity by descent analysis revealed that the MAGIC RILs contained less introgression than expected. This research presents an insight on understanding the complex problems of introgression between cotton species.

Flame resistant cotton lines generated by synergistic epistasis in a MAGIC population

Textiles made from cotton fibers are flammable and thus often include flame retardant additives for consumer safety. Transgressive segregation in multi-parent populations facilitates new combinations of alleles of genes and can result in traits that are superior to those of any of the parents. A screen of 257 recombinant inbred lines from a multi-parent advanced generation intercross (MAGIC) population for naturally enhance flame retardance (FR) was conducted. All eleven parents, like all conventional white fiber cotton cultivars produce flammable fabric. MAGIC recombinant inbred lines (RILs) that produced fibers with significantly lower heat release capacities (HRC) as measured by microscale combustion calorimetry (MCC) were identified and the stability of the phenotypes of the outliers were confirmed when the RILs were grown at an additional location. Of the textiles fabricated from the five superior RILs, four exhibited the novel characteristic of inherent flame resistance. When exposed to open flame by standard 45° incline flammability testing, these four fabrics self-extinguished. To determine the genetic architecture of this novel trait, linkage, epistatic and multi-locus genome wide association studies (GWAS) were conducted with 473k SNPs identified by whole genome sequencing (WGS). Transcriptomes of developing fiber cells from select RILs were sequenced (RNAseq). Together, these data provide insight into the genetic mechanism of the unexpected emergence of flame-resistant cotton by transgressive segregation in a breeding program. The incorporation of this trait into global cotton germplasm by breeding has the potential to greatly reduce the costs and impacts of flame-retardant chemicals.

Natural variation of GhSI7 increases seed index in cotton

qSI07.1, a major QTL for seed index in cotton, was fine-mapped to a 17.45-kb region, and the candidate gene GhSI7 was verified in transgenic plants. Improving production to meet human needs is a vital objective in cotton breeding. The yield-related trait seed index is a complex quantitative trait, but few candidate genes for seed index have been characterized. Here, a major QTL for seed index qSI07.1 was fine-mapped to a 17.45-kb region by linkage analysis and substitutional mapping. Only GhSI7, encoding the transcriptional regulator STERILE APETALA, was contained in the candidate region. Association test and genetic analysis indicated that an 845-bp-deletion in its intron was responsible for the seed index variation. Origin analysis revealed that this variation was unique in Gossypium hirsutum and originated from race accessions. Overexpression of GhSI7 (haplotype 2) significantly increased the seed index and organ size in cotton plants. Our findings provided a diagnostic marker for breeding and selecting cotton varieties with high seed index, and laid a foundation for further studies to understand the molecular mechanism of cotton seed morphogenesis.

SoyMAGIC: An Unprecedented Platform for Genetic Studies and Breeding Activities in Soybean

Multi-Parent Advanced Generation Inter-Cross (MAGIC) populations are emerging genetic platforms for high-resolution and fine mapping of quantitative traits, such as agronomic and seed composition traits in soybean (Glycine max L.). We have established an eight-parent MAGIC population, comprising 721 recombinant inbred lines (RILs), through conical inter-mating of eight soybean lines. The parental lines were genetically diverse elite cultivars carrying different agronomic and seed composition characteristics, including amino acids and fatty acids, as well as oil and protein concentrations. This study aimed to introduce soybean MAGIC (SoyMAGIC) population as an unprecedented platform for genotypic and phenotypic investigation of agronomic and seed quality traits in soybean. The RILs were evaluated for important seed composition traits using replicated field trials during 2020 and 2021. To measure the seed composition traits, near-infrared reflectance (NIR) was employed. The RILs were genotyped using genotyping-by-sequencing (GBS) method to decipher the genome and discover single-nucleotide polymorphic (SNP) markers among the RILs. A high-density linkage map was constructed through inclusive composite interval mapping (ICIM). The linkage map was 3,770.75 cM in length and contained 12,007 SNP markers. Chromosomes 11 and 18 were recorded as the shortest and longest linkage groups with 71.01 and 341.15 cM in length, respectively. Observed transgressive segregation of the selected traits and higher recombination frequency across the genome confirmed the capability of MAGIC population in reshuffling the diversity in the soybean genome among the RILs. The assessment of haplotype blocks indicated an uneven distribution of the parents' genomes in RILs, suggesting cryptic influence against or in favor of certain parental genomes. The SoyMAGIC population is a recombined genetic material that will accelerate further genomic studies and the development of soybean cultivars with improved seed quality traits through the development and implementation of reliable molecular-based toolkits.

A GWAS identified a major QTL for resistance to Fusarium wilt (Fusarium oxysporum f. sp. vasinfectum) race 4 in a MAGIC population of Upland cotton and a meta-analysis of QTLs for Fusarium wilt resistance

A major QTL conferring resistance to Fusarium wilt race 4 in a narrow region of chromosome D02 was identified in a MAGIC population of 550 RILs of Upland cotton. Numerous studies have been conducted to investigate the genetic basis of Fusarium wilt (FW, caused by Fusarium oxysporum f. sp. vasinfectum, FOV) resistance using bi-parental and association mapping populations in cotton. In this study, a multi-parent advanced generation inter-cross (MAGIC) population of 550 recombinant inbred lines (RILs), together with their 11 Upland cotton (Gossypium hirsutum) parents, was used to identify QTLs for FOV race 4 (FOV4) resistance. Among the parents, Acala Ultima, M-240 RNR, and Stoneville 474 were the most resistant, while Deltapine Acala 90, Coker 315, and Stoneville 825 were the most susceptible. Twenty-two MAGIC lines were consistently resistant to FOV4. Through a genome-wide association study (GWAS) based on 473,516 polymorphic SNPs, a major FOV4 resistance QTL within a narrow region on chromosomes D02 was detected, allowing identification of 14 candidate genes. Additionally, a meta-analysis of 133 published FW resistance QTLs showed a D subgenome and individual chromosome bias and no correlation between homeologous chromosome pairs. This study represents the first GWAS study using a largest genetic population and the most comprehensive meta-analysis for FW resistance in cotton. The results illustrated that 550 lines were not enough for high resolution mapping to pinpoint a candidate gene, and experimental errors in phenotyping cotton for FW resistance further compromised the accuracy and precision in QTL localization and identification of candidate genes. This study identified FOV4-resistant parents and MAGIC lines, and the first major QTL for FOV4 resistance in Upland cotton, providing useful information for developing FOV4-resistant cultivars and further genomic studies towards identification of causal genes for FOV4 resistance in cotton.

Genomic and GWAS analyses demonstrate phylogenomic relationships of Gossypium barbadense in China and selection for fibre length, lint percentage and Fusarium wilt resistance

Sea Island cotton (Gossypium barbadense) is the source of the world's finest fibre quality cotton, yet relatively little is understood about genetic variations among diverse germplasms, genes underlying important traits and the effects of pedigree selection. Here, we resequenced 336 G. barbadense accessions and identified 16 million SNPs. Phylogenetic and population structure analyses revealed two major gene pools and a third admixed subgroup derived from geographical dissemination and interbreeding. We conducted a genome-wide association study (GWAS) of 15 traits including fibre quality, yield, disease resistance, maturity and plant architecture. The highest number of associated loci was for fibre quality, followed by disease resistance and yield. Using gene expression analyses and VIGS transgenic experiments, we confirmed the roles of five candidate genes regulating four key traits, that is disease resistance, fibre length, fibre strength and lint percentage. Geographical and temporal considerations demonstrated selection for the superior fibre quality (fibre length and fibre strength), and high lint percentage in improving G. barbadense in China. Pedigree selection breeding increased Fusarium wilt disease resistance and separately improved fibre quality and yield. Our work provides a foundation for understanding genomic variation and selective breeding of Sea Island cotton.

The Pivotal Role of Major Chromosomes of Sub-Genomes A and D in Fiber Quality Traits of Cotton

Lack of precise information about the candidate genes involved in a complex quantitative trait is a major obstacle in the cotton fiber quality improvement, and thus, overall genetic gain in conventional phenotypic selection is low. Recent molecular interventions and advancements in genome sequencing have led to the development of high-throughput molecular markers, quantitative trait locus (QTL) fine mapping, and single nucleotide polymorphisms (SNPs). These advanced tools have resolved the existing bottlenecks in trait-specific breeding. This review demonstrates the significance of chromosomes 3, 7, 9, 11, and 12 of sub-genomes A and D carrying candidate genes for fiber quality. However, chromosome 7 carrying SNPs for stable and potent QTLs related to fiber quality provides great insights for fiber quality-targeted research. This information can be validated by marker-assisted selection (MAS) and transgene in Arabidopsis and subsequently in cotton.

New genomic regions associated with white mold resistance in dry bean using a MAGIC population

Dry bean (Phaseolus vulgaris L.) production in many regions is threatened by white mold (WM) [Sclerotinia sclerotiorum (Lib.) de Bary]. Seed yield losses can be up to 100% under conditions favorable for the pathogen. The low heritability, polygenic inheritance, and cumbersome screening protocols make it difficult to breed for improved genetic resistance. Some progress in understanding genetic resistance and germplasm improvement has been accomplished, but cultivars with high levels of resistance are yet to be released. A WM multiparent advanced generation inter-cross (MAGIC) population (n = 1060) was developed to facilitate mapping and breeding efforts. A seedling straw test screening method provided a quick assay to phenotype the population for response to WM isolate 1980. Nineteen MAGIC lines were identified with improved resistance. For genome-wide association studies (GWAS), the data was transformed into three phenotypic distributions-quantitative, polynomial, and binomial-and coupled with ∼52,000 single-nucleotide polymorphisms (SNPs). The three phenotypic distributions identified 30 significant genomic intervals [-log₁₀ (P value) ≥ 3.0]. However, across distributions, four new genomic regions as well as two regions previously reported were found to be associated with resistance. Cumulative R² values were 57% for binomial distribution using 13 genomic intervals, 41% for polynomial using eight intervals, and 40% for quantitative using 11 intervals. New resistant germplasm as well as new genomic regions associated with resistance are now available for further investigation.

Genome-wide association study for seedling biomass-related traits in Gossypium arboreum L

BACKGROUND

Seedling stage plant biomass is usually used as an auxiliary trait to study plant growth and development or stress adversities. However, few molecular markers and candidate genes of seedling biomass-related traits were found in cotton.

RESULT

Here, we collected 215 Gossypium arboreum accessions, and investigated 11 seedling biomass-related traits including the fresh weight, dry weight, water content, and root shoot ratio. A genome-wide association study (GWAS) utilizing 142,5003 high-quality SNPs identified 83 significant associations and 69 putative candidate genes. Furthermore, the transcriptome profile of the candidate genes emphasized higher expression of Ga03G1298, Ga09G2054, Ga10G1342, Ga11G0096, and Ga11G2490 in four representative cotton accessions. The relative expression levels of those five genes were further verified by qRT-PCR.

CONCLUSIONS

The significant SNPs, candidate genes identified in this study are expected to lay a foundation for studying the molecular mechanism for early biomass development and related traits in Asian cotton.

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.

Genetic Correlation Between Fe and Zn Biofortification and Yield Components in a Common Bean (Phaseolus vulgaris L.)

Common bean (Phaseolus vulgaris L.) is the most important legume for direct human consumption worldwide. It is a rich and relatively inexpensive source of proteins and micronutrients, especially iron and zinc. Bean is a target for biofortification to develop new cultivars with high Fe/Zn levels that help to ameliorate malnutrition mainly in developing countries. A strong negative phenotypic correlation between Fe/Zn concentration and yield is usually reported, posing a significant challenge for breeders. The objective of this study was to investigate the genetic relationship between Fe/Zn. We used Quantitative Trait Loci (QTLs) mapping and Genome-Wide Association Studies (GWAS) analysis in three bi-parental populations that included biofortified parents, identifying genomic regions associated with yield and micromineral accumulation. Significant negative correlations were observed between agronomic traits (pod harvest index, PHI; pod number, PdN; seed number, SdN; 100 seed weight, 100SdW; and seed per pod, Sd/Pd) and micronutrient concentration traits (SdFe and SdZn), especially between pod harvest index (PHI) and SdFe and SdZn. PHI presented a higher correlation with SdN than PdN. Seventy-nine QTLs were identified for the three populations: 14 for SdFe, 12 for SdZn, 13 for PHI, 11 for SdN, 14 for PdN, 6 for 100SdW, and 9 for Sd/Pd. Twenty-three hotspot regions were identified in which several QTLs were co-located, of which 13 hotpots displayed QTL of opposite effect for yield components and Fe/Zn accumulation. In contrast, eight QTLs for SdFe and six QTLs for SdZn were observed that segregated independently of QTL of yield components. The selection of these QTLs will enable enhanced levels of Fe/Zn and will not affect the yield performance of new cultivars focused on biofortification.

Genome-wide association mapping for agronomic traits in an 8-way Upland cotton MAGIC population by SLAF-seq

One sub-MAGIC population was genotyped using SLAF-seq, and QTLs and candidate genes for agronomic traits were identified in Upland cotton. The agronomic traits of Upland cotton have serious impacts on cotton production, as well as economic benefits. To discover the genetic basis of important agronomic traits in Upland cotton, a subset MAGIC (multi-parent advanced generation inter-cross) population containing 372 lines (SMLs) was selected from an 8-way MAGIC population with 960 lines. The 372 lines and 8 parents were phenotyped in six environments and deeply genotyped by SLAF-seq with 60,495 polymorphic SNPs. The genetic diversity indexes of all SNPs were 0.324 and 0.362 for the parents and MAGIC lines, respectively. The LD decay distance of the SMLs was 600 kb (r² = 0.1). Genome-wide association mapping was performed using 60,495 SNPs and the phenotypic data of the SMLs, and 177 SNPs were identified to be significantly associated with 9 stable agronomic traits in multiple environments. The identified SNPs were divided into 117 QTLs (quantitative trait loci) by LD decay distance, explaining 5.44% to 31.64% of the phenotypic variation. Among the 117 QTLs, 3 QTLs were stable in multiple environments, and 11 QTL regions were proven to have pleiotropism associated with multiple traits. Within QTL regions, 154 genes were preferentially expressed in correlated tissues, and 8 genes with known functions were identified as priori candidate genes. Two genes, GhACT1 and GhGASL3, reported to have clear functions, were, respectively, located in qFE-A05-4 and qFE-D04-3, two stable QTLs for FE. This study revealed the genetic basis of important agronomic traits of Upland cotton, and the results will facilitate molecular breeding in cotton.

Using chlorate as an analogue to nitrate to identify candidate genes for nitrogen use efficiency in barley

Nitrogen (N) is one of the most important macronutrients for crop growth and development. Large amounts of N fertilizers are applied exogenously to improve grain yield and quality, which has led to environmental pollution and high cost of production. Therefore, improvement of N use efficiency (NUE) is a very important aspect for sustainable agriculture. Here, a pilot experiment was firstly conducted with a set of barley genotypes with confirmed NUE to validate the fast NUE screening, using chlorate as an analogue to nitrate. High NUE genotypes were susceptible to chlorate-induced toxicity whereas the low NUE genotypes were tolerant. A total of 180 barley RILs derived from four parents (Compass, GrangeR, Lockyer and La Trobe) were further screened for NUE. Leaf chlorosis induced by chlorate toxicity was the key parameter observed which was later related to low-N tolerance of the RILs. There was a distinct variation in chlorate susceptibility of the RILs with leaf chlorosis in the oldest leaf ranging from 10 to 80%. A genome-wide association study (GWAS) identified 9 significant marker-trait associations (MTAs) conferring high chlorate sensitivity on chromosomes 2H (2), 3H (1), 4H (4), 5H (1) and Un (1). Genes flanking with these markers were retrieved as potential targets for genetic improvement of NUE. Genes encoding Ferredoxin 3, leucine-rich receptor-like protein kinase family protein and receptor kinase are responsive to N stress. MTA4H5468 which exhibits concordance with high NUE phenotype can further be explored under different genetic backgrounds and successfully applied in marker-assisted selection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01239-8.

Evaluation and genome-wide association study of resistance to bacterial blight race 18 in U.S. Upland cotton germplasm

Bacterial blight (BB), caused by Xanthomonas citri pv. malvacearum (Xcm), is a destructive disease to cotton production in many countries. In the U.S., Xcm race 18 is the most virulent and widespread race and can cause serious yield losses. Planting BB-resistant cotton cultivars is the most effective method of controlling this disease. In this study, 335 U.S. Upland cotton accessions were evaluated for resistance to race 18 using artificial inoculations by scratching cotyledons on an individual plant basis in a greenhouse. The analysis of variance detected significant genotypic variation in disease incidence, and 50 accessions were resistant including 38 lines with no symptoms on either cotyledons or true leaves. Many of the resistant lines were developed in the MAR (multi-adversity resistance) breeding program at Texas A&M University, whereas others were developed before race 18 was first reported in the U.S. in 1973, suggesting a broad base of resistance to race 18. A genome-wide association study (GWAS) based on 26,301 single nucleotide polymorphic (SNP) markers detected 11 quantitative trait loci (QTL) anchored by 79 SNPs, including three QTL on each of the three chromosomes A01, A05 and D02, and one QTL on each of D08 and D10. This study has identified a set of obsolete Upland germplasm with resistance to race 18 and specific chromosomal regions delineated by SNPs for resistance. The results will assist in breeding cotton for BB resistance and facilitate further genomic studies in fine mapping resistance genes to enhance the understanding of the genetic basis of BB resistance in cotton.

Haplotype analysis from unmanned aerial vehicle imagery of rice MAGIC population for the trait dissection of biomass and plant architecture

Unmanned aerial vehicles (UAVs) are popular tools for high-throughput phenotyping of crops in the field. However, their use for evaluation of individual lines is limited in crop breeding because research on what the UAV image data represent is still developing. Here, we investigated the connection between shoot biomass of rice plants and the vegetation fraction (VF) estimated from high-resolution orthomosaic images taken by a UAV 10 m above a field during the vegetative stage. Haplotype-based genome-wide association studies of multi-parental advanced generation inter-cross (MAGIC) lines revealed four quantitative trait loci (QTLs) for VF. VF was correlated with shoot biomass, but the haplotype effect on VF was better correlated with that on shoot biomass at these QTLs. Further genetic characterization revealed the relationships between these QTLs and plant spreading habit, final shoot biomass and panicle weight. Thus, genetic analysis using high-throughput phenotyping data derived from low-altitude, high-resolution UAV images during early stages of rice growing in the field provides insights into plant growth, architecture, final biomass, and yield.

Identification of hub genes through co-expression network of major QTLs of fiber length and strength traits in multiple RIL populations of cotton

The present study demonstrated a de novo correlation among fiber quality genes in multiple RIL populations including sGK9708 × 0-153, LMY22 × LY343 and Lumianyan28 × Xinluzao24. The current study was conducted to identify the major common QTLs including fiber length and strength, and to identify the co-expression networks of fiber length and strength QTLs harbored genes to target the hub genes. The RNA-seq data of sGK9708 × 0-153 population highlighted 50 and 48 candidate genes of fiber length and fiber strength QTLs. A total of 29 and 21 hub genes were identified in fiber length and strength co-expression network modules. The absolute values of correlation coefficient close to 1 resulted highly positive correlation among hub genes. Results also suggested that the gene correlation significantly influence the gene expression at different fiber development stages. These results might provide useful reference for further experiments in multiple RIL populations and suggest potential candidate genes for functional studies in cotton.

The cellulose synthase (CesA) gene family in four Gossypium species: phylogenetics, sequence variation and gene expression in relation to fiber quality in Upland cotton

Cellulose synthases (CesAs) are multi-subunit enzymes found on the plasma membrane of plant cells and play a pivotal role in cellulose production. The cotton fiber is mainly composed of cellulose, and the genetic relationships between CesA genes and cotton fiber yield and quality are not fully understood. Through a phylogenetic analysis, the CesA gene family in diploid Gossypium arboreum and Gossypium raimondii, as well as tetraploid Gossypium hirsutum ('TM-1') and Gossypium barbadense ('Hai-7124' and '3-79'), was divided into 6 groups and 15 sub-groups, with each group containing two to five homologous genes. Most CesA genes in the four species are highly collinear. Among the five cotton genomes, 440 and 1929 single nucleotide polymorphisms (SNPs) in the CesA gene family were identified in exons and introns, respectively, including 174 SNPs resulting in amino acid changes. In total, 484 homeologous SNPs between the A and D genomes were identified in diploids, while 142 SNPs were detected between the two tetraploids, with 32 and 82 SNPs existing within G. hirsutum and G. barbadense, respectively. Additionally, 74 quantitative trait loci near 18 GhCesA genes were associated with fiber quality. One to four GhCesA genes were differentially expressed (DE) in ovules at 0 and 3 days post anthesis (DPA) between two backcross inbred lines having different fiber lengths, but no DE genes were identified between these lines in developing fibers at 10 DPA. Twenty-seven SNPs in above DE CesA genes were detected among seven cotton lines, including one SNP in Ghi_A08G03061 that was detected in four G. hirsutum genotypes. This study provides the first comprehensive characterization of the cotton CesA gene family, which may play important roles in determining cotton fiber quality.

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.

Association Mapping in Plants

Quantitative trait loci mapping has become a common practice in crop plants and can be accomplished using either biparental populations following interval mapping or natural populations following the approach of association mapping. Because of its ability to use the natural diversity and to search for functional variants in a broader germplasm, association mapping is becoming popular among researchers. An overview of the different steps involved in association mapping in plants is provided in this chapter.

Genetic Diversity, QTL Mapping, and Marker-Assisted Selection Technology in Cotton (Gossypium spp.)

Cotton genetic resources contain diverse economically important traits that can be used widely in breeding approaches to create of high-yielding elite cultivars with superior fiber quality and adapted to biotic and abiotic stresses. Nevertheless, the creation of new cultivars using conventional breeding methods is limited by the cost and proved to be time consuming process, also requires a space to make field observations and measurements. Decoding genomes of cotton species greatly facilitated generating large-scale high-throughput DNA markers and identification of QTLs that allows confirmation of candidate genes, and use them in marker-assisted selection (MAS)-based breeding programs. With the advances of quantitative trait loci (QTL) mapping and genome-wide-association study approaches, DNA markers associated with valuable traits significantly accelerate breeding processes by replacing the selection with a phenotype to the selection at the DNA or gene level. In this review, we discuss the evolution and genetic diversity of cotton Gossypium genus, molecular markers and their types, genetic mapping and QTL analysis, application, and perspectives of MAS-based approaches in cotton breeding.

Bin-based genome-wide association studies reveal superior alleles for improvement of appearance quality using a 4-way MAGIC population in rice

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4-way Multiparental population covered the limitations of the biparental structure.

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The combination of SNP and bin-GWAS showed a powerful tool for QTL mapping.

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qPGWC8.2 harbored a novel predicted gene for rice chalkiness quality.

Introduction

The multiparental population provides us the chance to identify superior alleles controlling a trait for genetic improvement. Genome wide association studies at bin level (bin-GWAS) are expected to be more power in QTL mapping than GWAS at SNP level (SNP-GWAS).

Objectives

This study is to estimate genetic effects of QTL conferring grain appearance quality in rice by SNP-GWAS and bin-GWAS, compare their power in QTL mapping and identify the superior alleles of all detected QTL from 4 parents for genetic improvement.

Methods

A 4-way MAGIC population and its four founders were cultivated in two environments to dissect the genetic basis of rice grain appearance quality. Both SNP-GWAS and bin-GWAS were conducted for QTL mapping. Multiple comparison among 4 parental bin/alleles was used to identify the superior alleles.

Results

A total of 16 and 20 QTL associated with grain appearance quality were identified by SNP- and bin-GWAS, respectively. A minor chalkiness QTL qPGWC8.2/qDEC8 was assigned to a 30-kb genomic region, in which OsMH_08T0121900 is the potential candidate gene because its encoded protein, glucan endo-1,3-beta-glucosidase precursor is involved in the starch and sucrose metabolism pathway. The superior parental alleles for GS3, GL3.1, GW5, GW7, and Chalk5 and two QTLs were almost carried by the high-quality parents Cypress and Yuejingsimiao (YJSM), while the poor-quality parent Guichao-2 (GC2) always carried the inferior alleles. The top five recombinant inbred lines with the highest quality of grain shape and chalkiness traits all carried gene combinations of superior alleles.

Conclusions

Both SNP- and bin-GWAS methods are encouraged for joint QTL mapping with MAGIC population. qPGWC8.2/qDEC8 is a novel candidate gene strongly associated with chalkiness. The superior alleles of GS3, GW5, GL3.1, GW7, Chalk5 and qPGWC8.2 were identified, and the pyramiding of these superior alleles is helpful to improve rice appearance quality.

You Had Me at "MAGIC"!: Four Barley MAGIC Populations Reveal Novel Resistance QTL for Powdery Mildew

Blumeria graminis f. sp. hordei (Bgh), the causal agent of barley powdery mildew (PM), is one of the most important barley leaf diseases and is prevalent in most barley growing regions. Infection decreases grain quality and yields on average by 30%. Multi-parent advanced generation inter-cross (MAGIC) populations combine the advantages of bi-parental and association panels and offer the opportunity to incorporate exotic alleles into adapted material. Here, four barley MAGIC populations consisting of six to eight founders were tested for PM resistance in field trials in Denmark. Principle component and STRUCTURE analysis showed the populations were unstructured and genome-wide linkage disequilibrium (LD) decay varied between 14 and 38 Mbp. Genome-wide association studies (GWAS) identified 11 regions associated with PM resistance located on chromosomes 1H, 2H, 3H, 4H, 5H and 7H, of which three regions are putatively novel resistance quantitative trait locus/loci (QTL). For all regions high-confidence candidate genes were identified that are predicted to be involved in pathogen defense. Haplotype analysis of the significant SNPs revealed new allele combinations not present in the founders and associated with high resistance levels.

Genome-wide dissection of hybridization for fiber quality- and yield-related traits in upland cotton

An evaluation of combining ability can facilitate the selection of suitable parents and superior F₁ hybrids for hybrid cotton breeding, although the molecular genetic basis of combining ability has not been fully characterized. In the present study, 282 female parents were crossed with four male parents in accordance with the North Carolina II mating scheme to generate 1128 hybrids. The parental lines were genotyped based on restriction site-associated DNA sequencing and 306 814 filtered single nucleotide polymorphisms were used for genome-wide association analysis involving the phenotypes, general combining ability (GCA) values, and specific combining ability values of eight fiber quality- and yield-related traits. The main results were: (i) all parents could be clustered into five subgroups based on population structure analyses and the GCA performance of the female parents had significant differences between subgroups; (ii) 20 accessions with a top 5% GCA value for more than one trait were identified as elite parents for hybrid cotton breeding; (iii) 120 significant single nucleotide polymorphisms, clustered into 66 quantitative trait loci, such as the previously reported Gh_A07G1769 and GhHOX3 genes, were found to be significantly associated with GCA; and (iv) identified quantitative trait loci for GCA had a cumulative effect on GCA of the accessions. Overall, our results suggest that pyramiding the favorable loci for GCA may improve the efficiency of hybrid cotton breeding.

Genetic mapping for agronomic traits in a MAGIC population of common bean (Phaseolus vulgaris L.) under drought conditions

BACKGROUND

Common bean is an important staple crop in the tropics of Africa, Asia and the Americas. Particularly smallholder farmers rely on bean as a source for calories, protein and micronutrients. Drought is a major production constraint for common bean, a situation that will be aggravated with current climate change scenarios. In this context, new tools designed to understand the genetic basis governing the phenotypic responses to abiotic stress are required to improve transfer of desirable traits into cultivated beans.

RESULTS

A multiparent advanced generation intercross (MAGIC) population of common bean was generated from eight Mesoamerican breeding lines representing the phenotypic and genotypic diversity of the CIAT Mesoamerican breeding program. This population was assessed under drought conditions in two field trials for yield, 100 seed weight, iron and zinc accumulation, phenology and pod harvest index. Transgressive segregation was observed for most of these traits. Yield was positively correlated with yield components and pod harvest index (PHI), and negative correlations were found with phenology traits and micromineral contents. Founder haplotypes in the population were identified using Genotyping by Sequencing (GBS). No major population structure was observed in the population. Whole Genome Sequencing (WGS) data from the founder lines was used to impute genotyping data for GWAS. Genetic mapping was carried out with two methods, using association mapping with GWAS, and linkage mapping with haplotype-based interval screening. Thirteen high confidence QTL were identified using both methods and several QTL hotspots were found controlling multiple traits. A major QTL hotspot located on chromosome Pv01 for phenology traits and yield was identified. Further hotspots affecting several traits were observed on chromosomes Pv03 and Pv08. A major QTL for seed Fe content was contributed by MIB778, the founder line with highest micromineral accumulation. Based on imputed WGS data, candidate genes are reported for the identified major QTL, and sequence changes were identified that could cause the phenotypic variation.

CONCLUSIONS

This work demonstrates the importance of this common bean MAGIC population for genetic mapping of agronomic traits, to identify trait associations for molecular breeding tool design and as a new genetic resource for the bean research community.

Elucidation of sequence polymorphism in fuzzless-seed cotton lines

Most commercially produced cotton cultivars have two types of fibers on the seed coat, short fuzz and long lint. Lint fiber is used in the textile industry, while fuzz is considered an undesirable trait. Both types of fibers are believed to be controlled by the same regulators; however, their mechanisms of actions are still obscure. Cotton fiber mutants provide an excellent system to study the genes that regulate fiber development. Here we described four uncharacterized and three previously reported cotton mutants with fuzzless seed phenotypes. To evaluate whether or not the genes previously associated with fuzzless seed phenotypes have mutations we sequenced whole genomic DNA of seven mutants and wild type varieties. We identified multiple polymorphic changes among the tested genes. Non-synonymous SNPs in the coding region of the MML3-A gene was common in the six mutant lines tested in this study, showing both dominant and recessive fuzzless phenotypes. We have mapped the locus of the causative mutation for one of the uncharacterized fuzzless lines using an F₂ population that originated from a cross between the dominant fuzzless mutant and a wild type. Further, we have clarified the current knowledge about the causative n₂ mutations by analyzing the sequence data and previously reported mapping data. The key genes and possible mechanisms of fiber differentiation are discussed in this study.

Genetic architecture of agronomic and quality traits in a nested association mapping population of spring wheat

Germplasm collections are rich sources of genetic variation to improve crops for many valuable traits. Nested association mapping (NAM) populations can overcome the limitations of genome-wide association studies (GWAS) in germplasm collections by reducing the effect of population structure. We exploited the genetic diversity of the USDA-ARS wheat (Triticum aestivum L.) core collection by developing the Spring Wheat Multiparent Introgression Population (SWMIP). To develop this population, twenty-five core parents were crossed and backcrossed to the Minnesota spring wheat cultivar RB07. The NAM population and 26 founder parents were genotyped using genotyping-by-sequencing and phenotyped for heading date, height, test weight, and grain protein content. After quality control, 20,312 markers with physical map positions were generated for 2,038 recombinant inbred lines (RILs). The number of RILs in each family varied between 58 and 96. Three GWAS models were utilized for quantitative trait loci (QTL) detection and accounted for known family stratification, genetic kinship, and both covariates. GWAS was performed on the whole population and also by bootstrap sampling of an equal number of RILs from each family. Greater power of QTL detection was achieved by treating families equally through bootstrapping. In total 16, 15, 12, and 13 marker-trait associations (MTAs) were identified for heading date, height, test weight, and grain protein content, respectively. Some of these MTAs were coincident with major genes known to control the traits, but others were novel and contributed by the wheat core parents. The SWMIP will be a valuable source of genetic variation for spring wheat breeding.

GWAS reveals consistent QTL for drought and salt tolerance in a MAGIC population of 550 lines derived from intermating of 11 Upland cotton (Gossypium hirsutum) parents

Cotton is grown in arid and semi-arid regions where abiotic stresses such as drought and salt are prevalent. There is a lack of studies that simultaneously address the genetic and genomic basis of tolerance to drought and salt stress. In this study, a multi-parent advanced generation inter-cross (MAGIC) population of 550 recombinant inbred lines (RILs) together with their 11 Upland cotton parents with a total of 473,516 polymorphic SNP markers was used to identify quantitative trait loci (QTL) for drought tolerance (DT) and salt tolerance (ST) at the seedling stage based on two replicated greenhouse tests. Transgressive segregation occurred in the MAGIC-RILs, indicating that tolerant and sensitive alleles recombined for tolerance to the abiotic stress during the intermating process for the population development. A total of 20 QTL were detected for DT including 13 and 7 QTL based on plant height (PH) and dry shoot weight (DSW), respectively; and 23 QTL were detected for ST including 12 and 11 QTL for PH and DSW, respectively. There were several chromosomes with QTL clusters for abiotic stress tolerance including four QTL on chromosome A13 and three QTL on A01 for DT, and four QTL on D08 and three QTL on A11 for ST. Nine QTL (21% of the 43 QTL) detected were in common between DT and ST, indicating a common genetic basis for DT and ST. The narrow chromosomal regions for most of the QTL detected in this study allowed identification of 53 candidate genes associated with responses to salt and drought stress and abiotic stimulus. The QTL identified for both DT and ST have significantly augmented the repertoire of QTL for abiotic stress tolerance that can be used for marker-assisted selection to develop cultivars with resilience to drought and/or salt and further genomic studies towards the identification of drought and salt tolerance genes in cotton.

The Dawn of the Age of Multi-Parent MAGIC Populations in Plant Breeding: Novel Powerful Next-Generation Resources for Genetic Analysis and Selection of Recombinant Elite Material

The compelling need to increase global agricultural production requires new breeding approaches that facilitate exploiting the diversity available in the plant genetic resources. Multi-parent advanced generation inter-cross (MAGIC) populations are large sets of recombinant inbred lines (RILs) that are a genetic mosaic of multiple founder parents. MAGIC populations display emerging features over experimental bi-parental and germplasm populations in combining significant levels of genetic recombination, a lack of genetic structure, and high genetic and phenotypic diversity. The development of MAGIC populations can be performed using “funnel” or “diallel” cross-designs, which are of great relevance choosing appropriate parents and defining optimal population sizes. Significant advances in specific software development are facilitating the genetic analysis of the complex genetic constitutions of MAGIC populations. Despite the complexity and the resources required in their development, due to their potential and interest for breeding, the number of MAGIC populations available and under development is continuously growing, with 45 MAGIC populations in different crops being reported here. Though cereals are by far the crop group where more MAGIC populations have been developed, MAGIC populations have also started to become available in other crop groups. The results obtained so far demonstrate that MAGIC populations are a very powerful tool for the dissection of complex traits, as well as a resource for the selection of recombinant elite breeding material and cultivars. In addition, some new MAGIC approaches that can make significant contributions to breeding, such as the development of inter-specific MAGIC populations, the development of MAGIC-like populations in crops where pure lines are not available, and the establishment of strategies for the straightforward incorporation of MAGIC materials in breeding pipelines, have barely been explored. The evidence that is already available indicates that MAGIC populations will play a major role in the coming years in allowing for impressive gains in plant breeding for developing new generations of dramatically improved cultivars.

Genetic structure, gene flow pattern, and association analysis of superior germplasm resources in domesticated upland cotton (Gossypium hirsutum L.)

Gene flow patterns and the genetic structure of domesticated crops like cotton are not well understood. Furthermore, marker-assisted breeding of cotton has lagged far behind that of other major crops because the loci associated with cotton traits such as fiber yield and quality have scarcely been identified. In this study, we used 19 microsatellites to first determine the population genetic structure and patterns of gene flow of superior germplasm resources in upland cotton. We then used association analysis to identify which markers were associated with 15 agronomic traits (including ten yield and five fiber quality traits). The results showed that the upland cotton accessions have low levels of genetic diversity (polymorphism information content = 0.427), although extensive gene flow occurred among different ecological and geographic regions. Bayesian clustering analysis indicated that the cotton resources used in this study did not belong to obvious geographic populations, which may be the consequence of a single source of domestication followed by frequent genetic introgression mediated by human transference. A total of 82 maker-trait associations were examined in association analysis and the related ratios for phenotypic variations ranged from 3.04% to 47.14%. Interestingly, nine SSR markers were detected in more than one environmental condition. In addition, 14 SSR markers were co-associated with two or more different traits. It was noteworthy that NAU4860 and NAU5077 markers detected at least in two environments were simultaneously associated with three fiber quality traits (uniformity index, specific breaking strength and micronaire value). In conclusion, these findings provide new insights into the population structure and genetic exchange pattern of cultivated cotton accessions. The quantitative trait loci of domesticated cotton identified will also be very useful for improvement of yield and fiber quality of cotton in molecular breeding programs.

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

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

Genetic Architecture and Genomic Prediction of Cooking Time in Common Bean (Phaseolus vulgaris L.)

Cooking time of the common bean is an important trait for consumer preference, with implications for nutrition, health, and environment. For efficient germplasm improvement, breeders need more information on the genetics to identify fast cooking sources with good agronomic properties and molecular breeding tools. In this study, we investigated a broad genetic variation among tropical germplasm from both Andean and Mesoamerican genepools. Four populations were evaluated for cooking time (CKT), water absorption capacity (WAC), and seed weight (SdW): a bi-parental RIL population (DxG), an eight-parental Mesoamerican MAGIC population, an Andean (VEF), and a Mesoamerican (MIP) breeding line panel. A total of 922 lines were evaluated in this study. Significant genetic variation was found in all populations with high heritabilities, ranging from 0.64 to 0.89 for CKT. CKT was related to the color of the seed coat, with the white colored seeds being the ones that cooked the fastest. Marker trait associations were investigated by QTL analysis and GWAS, resulting in the identification of 10 QTL. In populations with Andean germplasm, an inverse correlation of CKT and WAC, and also a QTL on Pv03 that inversely controls CKT and WAC (CKT3.2/WAC3.1) were observed. WAC7.1 was found in both Mesoamerican populations. QTL only explained a small part of the variance, and phenotypic distributions support a more quantitative mode of inheritance. For this reason, we evaluated how genomic prediction (GP) models can capture the genetic variation. GP accuracies for CKT varied, ranging from good results for the MAGIC population (0.55) to lower accuracies in the MIP panel (0.22). The phenotypic characterization of parental material will allow for the cooking time trait to be implemented in the active germplasm improvement programs. Molecular breeding tools can be developed to employ marker-assisted selection or genomic selection, which looks to be a promising tool in some populations to increase the efficiency of breeding activities.

Identification of genomewide single-nucleotide polymorphisms associated with presummer, summer and autumn bolls in upland cotton

Presummer, summer, and autumn bolls (PSB, SB and AB, respectively) in cotton are related to both maturity and yield. Therefore, studying their genetic basis is important for breeding purposes. In this study, we developed an association analysis panel consisting of 169 upland cotton accessions. The panel was phenotyped for PSB, SB and AB across four environments and genotyped using a Cotton SNP80K array. Single-nucleotide polymorphisms (SNPs) associated with these three traits were identified by a genomewide association study. A total of 53,848 high-quality SNPs were screened, and 91 significant trait-associated SNPs were detected. Of the 91 SNPs 33 were associated with PSB, 21 with SB and 37 with AB. Three SNPs for PSB (TM10410, TM13158 and TM21762) and five for AB (TM13730, TM13733, TM13834, TM29666 and TM43214) were repeatedly detected in two environments or by two methods. These eight SNPs exhibited high phenotypic variation of more than 10%, thus allowing their use formarker-assisted selection. The candidate genes for target traits were also identified. These findings provide a theoretical basis for the improvement of early maturity and yield in cotton breeding programmes.

HaploBlocker: Creation of Subgroup-Specific Haplotype Blocks and Libraries

The concept of haplotype blocks has been shown to be useful in genetics. Fields of application range from the detection of regions under positive selection to statistical methods that make use of dimension reduction. We propose a novel approach ("HaploBlocker") for defining and inferring haplotype blocks that focuses on linkage instead of the commonly used population-wide measures of linkage disequilibrium. We define a haplotype block as a sequence of genetic markers that has a predefined minimum frequency in the population, and only haplotypes with a similar sequence of markers are considered to carry that block, effectively screening a dataset for group-wise identity-by-descent. From these haplotype blocks, we construct a haplotype library that represents a large proportion of genetic variability with a limited number of blocks. Our method is implemented in the associated R-package HaploBlocker, and provides flexibility not only to optimize the structure of the obtained haplotype library for subsequent analyses, but also to handle datasets of different marker density and genetic diversity. By using haplotype blocks instead of single nucleotide polymorphisms (SNPs), local epistatic interactions can be naturally modeled, and the reduced number of parameters enables a wide variety of new methods for further genomic analyses such as genomic prediction and the detection of selection signatures. We illustrate our methodology with a dataset comprising 501 doubled haploid lines in a European maize landrace genotyped at 501,124 SNPs. With the suggested approach, we identified 2991 haplotype blocks with an average length of 2685 SNPs that together represent 94% of the dataset.

QTLs for Resistance to Fusarium Ear Rot in a Multiparent Advanced Generation Intercross (MAGIC) Maize Population

Alternative approaches to linkage and association mapping using inbred panels may allow further insights into loci involved in resistance to Fusarium ear rot and lead to the discovery of suitable markers for breeding programs. Here, the suitability of a maize multiparent advanced-generation intercross population for detecting quantitative trait loci (QTLs) associated with Fusarium ear rot resistance was evaluated and found to be valuable in uncovering genomic regions containing resistance-associated loci in temperate materials. In total, 13 putative minor QTLs were located over all of the chromosomes, except chromosome 5, and frequencies of favorable alleles for resistance to Fusarium ear rot were, in general, high. These findings corroborated the quantitative characteristic of resistance to Fusarium ear rot in which many loci have small additive effects. Present and previous results indicate that crucial regions such as 210 to 220 Mb in chromosome 3 and 166 to 173 Mb in chromosome 7 (B73-RefGen-v2) contain QTLs for Fusarium ear rot resistance and fumonisin content.

A novel variant of Gh_D02G0276 is required for root-knot nematode resistance on chromosome 14 (D02) in Upland cotton

MAGIC population sequencing and virus-induced gene silencing identify Gh_D02G0276 as a novel root-knot nematode resistance gene on chromosome 14 in Upland cotton. The southern root-knot nematode [RKN; Meloidogyne incognita (Kofoid & White)] remains the primary yield-limiting biotic stress to Upland cotton (Gossypium hirsutum L.) throughout the southeastern USA. While useful genetic markers have been developed for two major RKN resistance loci on chromosomes 11 (A11) and 14 (D02), these markers are not completely effective because the causative genes have not been identified. Here, we sequenced 550 recombinant inbred lines (RILs) from a multi-parent advanced generation intercross (MAGIC) population to identify five RILs that had informative recombinations near the D02-RKN resistance locus. The RKN resistance phenotypes of these five RILs narrowed the D02-RKN locus to a 30-kb region with four candidate genes. We conducted virus-induced gene silencing (VIGS) on each of these genes and found that Gh_D02G0276 was required for suppression of RKN egg production conferred by the Chr. D02 resistance gene. The resistant lines all possessed an allele of Gh_D02G0276 that showed non-synonymous mutations and was prematurely truncated. Furthermore, a Gh_D02G0276-specific marker for the resistance allele variant was able to identify RKN-resistant germplasm from a collection of 367 cotton accessions. The Gh_D02G0276 peptide shares similarity with domesticated hAT-like transposases with additional novel N- and C-terminal domains that resemble the target of known RKN effector molecules and a prokaryotic motif, respectively. The truncation in the resistance allele results in a loss of a plant nuclear gene-specific C-terminal motif, potentially rendering this domain antigenic due to its high homology with bacterial proteins. The conclusive identification of this RKN resistance gene opens new avenues for understanding plant resistance mechanisms to RKN as well as opportunities to develop more efficient marker-assisted selection in cotton breeding programs.

Whole genome sequencing of a MAGIC population identified genomic loci and candidate genes for major fiber quality traits in upland cotton (Gossypium hirsutum L.)

Significant associations between candidate genes and six major cotton fiber quality traits were identified in a MAGIC population using GWAS and whole genome sequencing. Upland cotton (Gossypium hirsutum L.) is the world's major renewable source of fibers for textiles. To identify causative genetic variants that influence the major agronomic measures of cotton fiber quality, which are used to set discount or premium prices on each bale of cotton in the USA, we measured six fiber phenotypes from twelve environments, across three locations and 7 years. Our 550 recombinant inbred lines were derived from a multi-parent advanced generation intercross population and were whole-genome-sequenced at 3× coverage, along with the eleven parental cultivars at 20× coverage. The segregation of 473,517 single nucleotide polymorphisms (SNPs) in this population, including 7506 non-synonymous mutations, was combined with phenotypic data to identify seven highly significant fiber quality loci. At these loci, we found fourteen genes with non-synonymous SNPs. Among these loci, some had simple additive effects, while others were only important in a subset of the population. We observed additive effects for elongation and micronaire, when the three most significant loci for each trait were examined. In an informative subset where the major multi-trait locus on chromosome A07:72-Mb was fixed, we unmasked the identity of another significant fiber strength locus in gene Gh_D13G1792 on chromosome D13. The micronaire phenotype only revealed one highly significant genetic locus at one environmental location, demonstrating a significant genetic by environment component. These loci and candidate causative variant alleles will be useful to cotton breeders for marker-assisted selection with minimal linkage drag and potential biotechnological applications.

Genetic and transcriptomic dissection of the fiber length trait from a cotton (Gossypium hirsutum L.) MAGIC population

BACKGROUND

Improving cotton fiber length without reducing yield is one of the major goals of cotton breeding. However, genetic improvement of cotton fiber length by breeding has been a challenge due to the narrow genetic diversity of modern cotton cultivars and negative correlations between fiber quality and yield traits. A multi-parent advanced generation inter-cross (MAGIC) population developed through random mating provides an excellent genetic resource that allows quantitative trait loci (QTL) and causal genes to be identified.

RESULTS

An Upland cotton MAGIC population, consisting of 550 recombinant inbred lines (RILs) derived from eleven different cultivars, was used to identify fiber length QTLs and potential genes that contribute to longer fibers. A genome wide association study (GWAS) identified a cluster of single nucleotide polymorphisms (SNPs) on chromosome (Chr.) D11 that is significantly associated with fiber length. Further evaluation of the Chr. D11 genomic region among lines of the MAGIC population detected that 90% of RILs have a D11 haplotype similar to the reference TM-1 genome (D11-ref), whereas 10% of RILs inherited an alternative haplotype from one of the parents (D11-alt). The average length of fibers of D11-alt RILs was significantly shorter compared to D11-ref RILs, suggesting that alleles in the D11-alt haplotype contributed to the inferior fiber quality. RNAseq analysis of the longest and shortest fiber length RILs from D11-ref and D11-alt populations identified 949 significantly differentially expressed genes (DEGs). Gene set enrichment analysis revealed that different functional categories of genes were over-represented during fiber elongation between the four selected RILs. We found 12 genes possessing non-synonymous SNPs (nsSNPs) significantly associated with the fiber length, and three that were highly significant and were clustered at D11:24-Mb, including D11G1928, D11G1929 and D11G1931.

CONCLUSION

The results of this study provide insights into molecular aspects of genetic variation in fiber length and suggests candidate genes for genetic manipulation for cotton improvement.

Genetic and transcriptomic dissection of the fiber length trait from a cotton (Gossypium hirsutum L.) MAGIC population

Background

Improving cotton fiber length without reducing yield is one of the major goals of cotton breeding. However, genetic improvement of cotton fiber length by breeding has been a challenge due to the narrow genetic diversity of modern cotton cultivars and negative correlations between fiber quality and yield traits. A multi-parent advanced generation inter-cross (MAGIC) population developed through random mating provides an excellent genetic resource that allows quantitative trait loci (QTL) and causal genes to be identified.

Results

An Upland cotton MAGIC population, consisting of 550 recombinant inbred lines (RILs) derived from eleven different cultivars, was used to identify fiber length QTLs and potential genes that contribute to longer fibers. A genome wide association study (GWAS) identified a cluster of single nucleotide polymorphisms (SNPs) on chromosome (Chr.) D11 that is significantly associated with fiber length. Further evaluation of the Chr. D11 genomic region among lines of the MAGIC population detected that 90% of RILs have a D11 haplotype similar to the reference TM-1 genome (D11-ref), whereas 10% of RILs inherited an alternative haplotype from one of the parents (D11-alt). The average length of fibers of D11-alt RILs was significantly shorter compared to D11-ref RILs, suggesting that alleles in the D11-alt haplotype contributed to the inferior fiber quality. RNAseq analysis of the longest and shortest fiber length RILs from D11-ref and D11-alt populations identified 949 significantly differentially expressed genes (DEGs). Gene set enrichment analysis revealed that different functional categories of genes were over-represented during fiber elongation between the four selected RILs. We found 12 genes possessing non-synonymous SNPs (nsSNPs) significantly associated with the fiber length, and three that were highly significant and were clustered at D11:24-Mb, including D11G1928, D11G1929 and D11G1931.

Conclusion

The results of this study provide insights into molecular aspects of genetic variation in fiber length and suggests candidate genes for genetic manipulation for cotton improvement.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5427-5) contains supplementary material, which is available to authorized users.

Metabolic GWAS-based dissection of genetic bases underlying the diversity of plant metabolism

Plants have served as sources providing humans with metabolites for food and nutrition, biomaterials for living, and treatment for pain and disease. Plants produce a huge array of metabolites, with an immense diversity at both the population and individual levels. Dissection of the genetic bases for metabolic diversity has attracted increasing research attention. The concept of genome-wide association study (GWAS) was extended to studies on the diversity of plant metabolome that benefitted from the development of mass-spectrometry-based analytical systems and genome sequencing technologies. Metabolic genome-wide association study (mGWAS) is one of the most powerful tools for global identification of genetic determinants for diversity of plant metabolism. Recently, mGWAS has been performed for various species with continuous improvements, providing deeper insights into the genetic bases of metabolic diversity. In this review, we discuss fully the achievements to date and remaining challenges that are associated with both mGWAS and mGWAS-based multi-dimensional analysis. We begin with a summary of GWAS and its development based on statistical methods and populations. As variation in targeted traits is essential for GWAS, we review metabolic diversity and its rise at both the population and individual levels. Subsequently, the application of mGWAS for plants and its corresponding achievements are fully discussed. We address the current knowledge on mGWAS-based multi-dimensional analysis and emerging insights into the diversity of metabolism.

Discovery of QTL Alleles for Grain Shape in the Japan-MAGIC Rice Population Using Haplotype Information

A majority of traits are determined by multiple quantitative trait loci (QTL) that can have pleiotropic effects. A multi-parent advanced generation inter-cross (MAGIC) population is well suited for genetically analyzing the effects of multiple QTL on traits of interest because it contains a higher number of QTL alleles than a biparental population. We previously produced the JAPAN-MAGIC (JAM) population, derived from eight rice (Oryza sativa L.) cultivars with high yield and biomass in Japan, and developed the method of genome-wide association study (GWAS) using haplotype information on the JAM lines. This method was effective for identifying major genes such as Waxy for eating quality and Sd1 for culm length. Here, we show that haplotype-based GWAS is also effective for the evaluation of multiple QTL with small effects on rice grain shape in the JAM lines. Although both the haplotype- and SNP-based GWAS identified multiple QTL for grain length and width, the sum of the estimated trait values of each allele for the QTL detected by haplotype-based GWAS had higher correlation with observed values than those detected by SNP-based GWAS, indicating high-accuracy QTL detection in the haplotype-based GWAS. Furthermore, the study revealed pleiotropic effects of some QTL regions in regulation of grain shape, suggesting that the haplotype-based GWAS using the JAM lines is an effective means to evaluate the main and side effects of haplotypes at each QTL. Information on the pleiotropic effects of haplotypes on various traits will be useful for designing ideal lines in a breeding program.