An RTM-GWAS procedure reveals the QTL alleles and candidate genes for three yield-related traits in upland cotton

Genome-wide genetic architecture for plant maturity and drought tolerance in diploid potatoes

Cultivated potato (Solanum tuberosum) is known to be highly susceptible to drought. With climate change and its frequent episodes of drought, potato growers will face increased challenges to achieving their yield goals. Currently, a high proportion of untapped potato germplasm remains within the diploid potato relatives, and the genetic architecture of the drought tolerance and maturity traits of diploid potatoes is still unknown. As such, a panel of 384 ethyl methanesulfonate-mutagenized diploid potato clones were evaluated for drought tolerance and plant maturity under field conditions. Genome-wide association studies (GWAS) were conducted to dissect the genetic architecture of the traits. The results obtained from the genetic structure analysis of the panel showed five main groups and seven subgroups. Using the Genome Association and Prediction Integrated Tool-mixed linear model GWAS statistical model, 34 and 17 significant quantitative trait nucleotides (QTNs) were found associated with maturity and drought traits, respectively. Chromosome 5 carried most of the QTNs, some of which were also detected by using the restricted two-stage multi-locus multi-allele-GWAS haploblock-based model, and two QTNs were found to be pleiotropic for both maturity and drought traits. Using the non-parametric U-test, one and three QTNs, with 5.13%-7.4% phenotypic variations explained, showed favorable allelic effects that increase the maturity and drought trait values. The quantitaive trait loci (QTLs)/QTNs associated with maturity and drought trait were found co-located in narrow (0.5-1 kb) genomic regions with 56 candidate genes playing roles in plant development and senescence and in abiotic stress responses. A total of 127 potato clones were found to be late maturing and tolerant to drought, while nine were early to moderate-late maturing and tolerant to drought. Taken together, the data show that the studied germplasm panel and the identified candidate genes are prime genetic resources for breeders and biologists in conventional breeding and targeted gene editing as climate adaptation tools.

Efficient identification of QTL for agronomic traits in foxtail millet (Setaria italica) using RTM- and MLM-GWAS

KEY MESSAGE

Eleven QTLs for agronomic traits were identified by RTM- and MLM-GWAS, putative candidate genes were predicted and two markers for grain weight were developed and validated. Foxtail millet (Setaria italica), the second most cultivated millet crop after pearl millet, is an important grain crop in arid regions. Seven agronomic traits of 408 diverse foxtail millet accessions from 15 provinces in China were evaluated in three environments. They were clustered into two divergent groups based on genotypic data using ADMIXTURE, which was highly consistent with their geographical distribution. Two models for genome-wide association studies (GWAS), namely restricted two-stage multi-locus multi-allele (RTM)-GWAS and mixed linear model (MLM)-GWAS, were used to dissect the genetic architecture of the agronomic traits based on 13,723 SNPs. Eleven quantitative trait loci (QTLs) for seven traits were identified using two models (RTM- and MLM-GWAS). Among them, five were considered stable QTLs that were identified in at least two environments using MLM-GWAS. One putative candidate gene (SETIT_006045mg, Chr4: 744,701-746,852) that can enhance grain weight per panicle was identified based on homologous gene comparison and gene expression analysis and was validated by haplotype analysis of 330 accessions with high-depth (10×) resequencing data (unpublished). In addition, homologous gene comparison and haplotype analysis identified one putative foxtail millet ortholog (SETIT_032906mg, Chr2: 5,020,600-5,029,771) with rice affecting the target traits. Two markers (cGWP6045 and kTGW2906) were developed and validated and can be used for marker-assisted selection of foxtail millet with high grain weight. The results provide a fundamental resource for foxtail millet genetic research and breeding and demonstrate the power of integrating RTM- and MLM-GWAS approaches as a complementary strategy for investigating complex traits in foxtail millet.

Genome-wide association study for boll weight in Gossypium hirsutum races

High yield has always been an essential target in almost all of the cotton breeding programs. Boll weight (BW) is a key component of cotton yield. Numerous linkage mapping and genome-wide association studies (GWAS) have been performed to understand the genetic mechanism of BW, but information on the markers/genes controlling BW remains limited. In this study, we conducted a GWAS for BW using 51,268 high-quality single-nucleotide polymorphisms (SNPs) and 189 Gossypium hirsutum accessions across five different environments. A total of 55 SNPs significantly associated with BW were detected, of which 29 and 26 were distributed in the A and D subgenomes, respectively. Five SNPs were simultaneously detected in two environments. For TM5655, TM8662, TM36371, and TM50258, the BW grouped by alleles of each SNP was significantly different. The ± 550 kb regions around these four key SNPs contained 262 genes. Of them, Gh_A02G1473, Gh_A10G1765, and Gh_A02G1442 were expressed highly at 0 to 1 days post-anthesis (dpa), - 3 to 0 dpa, and - 3 to 0 dpa in ovule of TM-1, respectively. They were presumed as the candidate genes for fiber cell differentiation, initiation, or elongation based on gene annotation of their homologs. Overall, these results supplemented valuable information for dissecting the genetic architecture of BW and might help to improve cotton yield through molecular marker-assisted selection breeding and molecular design breeding.

Integration of eQTL and machine learning to dissect causal genes with pleiotropic effects in genetic regulation networks of seed cotton yield

The dissection of a gene regulatory network (GRN) that complements the genome-wide association study (GWAS) locus and the crosstalk underlying multiple agronomical traits remains a major challenge. In this study, we generate 558 transcriptional profiles of lint-bearing ovules at one day post-anthesis from a selective core cotton germplasm, from which 12,207 expression quantitative trait loci (eQTLs) are identified. Sixty-six known phenotypic GWAS loci are colocalized with 1,090 eQTLs, forming 38 functional GRNs associated predominantly with seed yield. Of the eGenes, 34 exhibit pleiotropic effects. Combining the eQTLs within the seed yield GRNs significantly increases the portion of narrow-sense heritability. The extreme gradient boosting (XGBoost) machine learning approach is applied to predict seed cotton yield phenotypes on the basis of gene expression. Top-ranking eGenes (NF-YB3, FLA2, and GRDP1) derived with pleiotropic effects on yield traits are validated, along with their potential roles by correlation analysis, domestication selection analysis, and transgenic plants.

Genome-Wide Association Study of Lint Percentage in Gossypium hirsutum L. Races

Lint percentage is one of the most essential yield components and an important economic index for cotton planting. Improving lint percentage is an effective way to achieve high-yield in cotton breeding worldwide, especially upland cotton (Gossypium hirsutum L.). However, the genetic basis controlling lint percentage has not yet been systematically understood. Here, we performed a genome-wide association mapping for lint percentage using a natural population consisting of 189 G. hirsutum accessions (188 accessions of G. hirsutum races and one cultivar TM-1). The results showed that 274 single-nucleotide polymorphisms (SNPs) significantly associated with lint percentage were detected, and they were distributed on 24 chromosomes. Forty-five SNPs were detected at least by two models or at least in two environments, and their 5 Mb up- and downstream regions included 584 makers related to lint percentage identified in previous studies. In total, 11 out of 45 SNPs were detected at least in two environments, and their 550 Kb up- and downstream region contained 335 genes. Through RNA sequencing, gene annotation, qRT-PCR, protein-protein interaction analysis, the cis-elements of the promotor region, and related miRNA prediction, Gh_D12G0934 and Gh_A08G0526 were selected as key candidate genes for fiber initiation and elongation, respectively. These excavated SNPs and candidate genes could supplement marker and gene information for deciphering the genetic basis of lint percentage and facilitate high-yield breeding programs of G. hirsutum ultimately.

Lint percentage and boll weight QTLs in three excellent upland cotton (Gossypium hirsutum): ZR014121, CCRI60, and EZ60

BACKGROUND

Upland cotton (Gossypium hirsutum L.) is the most economically important species in the cotton genus (Gossypium spp.). Enhancing the cotton yield is a major goal in cotton breeding programs. Lint percentage (LP) and boll weight (BW) are the two most important components of cotton lint yield. The identification of stable and effective quantitative trait loci (QTLs) will aid the molecular breeding of cotton cultivars with high yield.

RESULTS

Genotyping by target sequencing (GBTS) and genome-wide association study (GWAS) with 3VmrMLM were used to identify LP and BW related QTLs from two recombinant inbred line (RIL) populations derived from high lint yield and fiber quality lines (ZR014121, CCRI60 and EZ60). The average call rate of a single locus was 94.35%, and the average call rate of an individual was 92.10% in GBTS. A total of 100 QTLs were identified; 22 of them were overlapping with the reported QTLs, and 78 were novel QTLs. Of the 100 QTLs, 51 QTLs were for LP, and they explained 0.29-9.96% of the phenotypic variation; 49 QTLs were for BW, and they explained 0.41-6.31% of the phenotypic variation. One QTL (qBW-E-A10-1, qBW-C-A10-1) was identified in both populations. Six key QTLs were identified in multiple-environments; three were for LP, and three were for BW. A total of 108 candidate genes were identified in the regions of the six key QTLs. Several candidate genes were positively related to the developments of LP and BW, such as genes involved in gene transcription, protein synthesis, calcium signaling, carbon metabolism, and biosynthesis of secondary metabolites. Seven major candidate genes were predicted to form a co-expression network. Six significantly highly expressed candidate genes of the six QTLs after anthesis were the key genes regulating LP and BW and affecting cotton yield formation.

CONCLUSIONS

A total of 100 stable QTLs for LP and BW in upland cotton were identified in this study; these QTLs could be used in cotton molecular breeding programs. Putative candidate genes of the six key QTLs were identified; this result provided clues for future studies on the mechanisms of LP and BW developments.

Genome-wide association study identifies GhSAL1 affects cold tolerance at the seedling emergence stage in upland cotton (Gossypium hirsutum L.)

Genomic analysis of upland cotton revealed that cold tolerance was associated with ecological distribution. GhSAL1 on chromosome D09 negatively regulated cold tolerance of upland cotton. Cotton can undergo low-temperature stress at the seedling emergence stage, which adversely affects growth and yield; however, the regulatory mechanism underlying cold tolerance remains nebulous. Here, we analyze the phenotypic and physiological parameters in 200 accessions from 5 ecological distributions under constant chilling (CC) and diurnal variation of chilling (DVC) stresses at the seedling emergence stage. All accessions were clustered into four groups, of which Group IV, with most germplasms from the northwest inland region (NIR), had better phenotypes than Groups I-III under the two kinds of chilling stresses. A total of 575 significantly associated single-nucleotide polymorphism (SNP) were identified, and 35 stable genetic quantitative trait loci (QTL) were obtained, of which 5 were associated with traits under CC and DVC stress, respectively, while the remaining 25 were co-associated. The accumulation of dry weight (DW) of seedling was associated with the flavonoid biosynthesis process regulated by Gh_A10G0500. The emergence rate (ER), DW, and total length of seedling (TL) under CC stress were associated with the SNPs variation of Gh_D09G0189 (GhSAL1). GhSAL1^HapB was the elite haplotype, which increased ER, DW, and TL by 19.04%, 11.26%, and 7.69%, respectively, compared with that of GhSAL1^HapA. The results of virus-induced gene silencing (VIGS) experiment and determination of metabolic substrate content preliminarily illustrated that GhSAL1 negatively regulated cotton cold tolerance through IP₃-Ca²⁺ signaling pathway. The elite haplotypes and candidate genes identified in this study could be used to improve cold tolerance at the seedling emergence stage in future upland cotton breeding.

Genome-Wide Association Studies (GWAS)

Most of the breeding targets are quantitative traits. In exploring the quantitative trait locus (QTL) system of a trait, linkage mapping was established using sparse polymerase chain reaction (PCR) markers. With the genome-wide sequencing technology advanced, genome-wide association study (GWAS) was developed for natural (germplasm) populations using dense genomic markers, which facilitates the identification of the complete QTL system with their multiple alleles on genomic locations. GWAS makes use of the linkage disequilibrium (LD) due to historical saturate recombination and high-density genomic markers to detect QTLs through statistical test for the association between molecular markers and phenotypes. However, due to inbreeding and mixture of source populations, the germplasm population often has complex and unknown structure, which leads to false positives/negatives in GWAS. Various GWAS methods have been proposed to reduce false positives/negatives, including those of the general linear model and the mixed linear model, which focused mainly on finding a handful of major QTLs under single-locus model for major gene cloning and could not detect directly the multiple alleles using bi-allelic single-nucleotide polymorphism (SNP) marker. As a relatively thorough detection of QTLs with their multiple alleles is required for germplasm population, the restricted two-stage multi-locus multi-allele GWAS (RTM-GWAS) procedure was proposed for identifying the QTL system with varying multiple alleles. From the RTM-GWAS results, a QTL-allele matrix is constructed as a compact form of the population genetic constitution, which can be further used for crop genetic and breeding studies, including major gene mining, population evolution, and breeding by genetic design.

Quantitative Trait Locus Mapping of Marsh Spot Disease Resistance in Cranberry Common Bean (Phaseolus vulgaris L.)

Common bean (Phaseolus vulgaris L.) is a food crop that is an important source of dietary proteins and carbohydrates. Marsh spot is a physiological disorder that diminishes seed quality in beans. Prior research suggested that this disease is likely caused by manganese (Mn) deficiency during seed development and that marsh spot resistance is controlled by at least four genes. In this study, genetic mapping was performed to identify quantitative trait loci (QTL) and the potential candidate genes associated with marsh spot resistance. All 138 recombinant inbred lines (RILs) from a bi-parental population were evaluated for marsh spot resistance during five years from 2015 to 2019 in sandy and heavy clay soils in Morden, Manitoba, Canada. The RILs were sequenced using a genotyping by sequencing approach. A total of 52,676 single nucleotide polymorphisms (SNPs) were identified and filtered to generate a high-quality set of 2066 SNPs for QTL mapping. A genetic map based on 1273 SNP markers distributed on 11 chromosomes and covering 1599 cm was constructed. A total of 12 stable and 4 environment-specific QTL were identified using additive effect models, and an additional two epistatic QTL interacting with two of the 16 QTL were identified using an epistasis model. Genome-wide scans of the candidate genes identified 13 metal transport-related candidate genes co-locating within six QTL regions. In particular, two QTL (QTL.3.1 and QTL.3.2) with the highest R2 values (21.8% and 24.5%, respectively) harbored several metal transport genes Phvul.003G086300, Phvul.003G092500, Phvul.003G104900, Phvul.003G099700, and Phvul.003G108900 in a large genomic region of 16.8–27.5 Mb on chromosome 3. These results advance the current understanding of the genetic mechanisms of marsh spot resistance in cranberry common bean and provide new genomic resources for use in genomics-assisted breeding and for candidate gene isolation and functional characterization.

Genome-Wide Association Study of Kernel Traits Using a 35K SNP Array in Bread Wheat (Triticum aestivum L.)

Kernel size and weight are crucial components of grain yield in wheat. Deciphering their genetic basis is essential for improving yield potential in wheat breeding. In this study, five kernel traits, including kernel length (KL), kernel width (KW), kernel diameter ratio (KDR), kernel perimeter (KP), and thousand-kernel weight (TKW), were evaluated in a panel consisting of 198 wheat accessions under six environments. Wheat accessions were genotyped using the 35K SNP iSelect chip array, resulting in a set of 13,228 polymorphic SNP markers that were used for genome-wide association study (GWAS). A total of 146 significant marker-trait associations (MTAs) were identified for five kernel traits on 21 chromosomes [-log₁₀(P) ≥ 3], which explained 5.91-15.02% of the phenotypic variation. Of these, 12 stable MTAs were identified in multiple environments, and six superior alleles showed positive effects on KL, KP, and KDR. Four potential candidate genes underlying the associated SNP markers were predicted for encoding ML protein, F-box protein, ethylene-responsive transcription factor, and 1,4-α-glucan branching enzyme. These genes were strongly expressed in grain development at different growth stages. The results will provide new insights into the genetic basis of kernel traits in wheat. The associated SNP markers and predicted candidate genes will facilitate marker-assisted selection in wheat breeding.

TIP41L, a putative candidate gene conferring both seed size and boll weight, was fine-mapped in an introgression line of Gossypium hirsutum-Gossypium arboreum

QTLs for yield-related traits in tetraploid cotton have been widely mapped, but QTLs introduced from diploid species into tetraploid cotton background remain uninvolved. Here, a stable introgression line with the traits of small boll and seed on Chr. A12, IL197 derived from Gossypium hirsutum (2n = AADD = 52) × Gossypium arboreum (2n = AA = 26), was employed to construct the F₂ and F₃ secondary populations for fine-mapping QTLs of yield-related traits. QTL analysis showed eight QTLs were detected for three traits, boll weight (BW), seed index (SI, one-hundred-seed weight in g), and lint percentage, with 3.94-28.13 % of the phenotypic variance explained. Of them, a stable major QTL, q(BW + SI)-A12-1 controlling both BW and SI and covering the shortest region in Chr. A12, was further narrowed into a 60.09 kb-interval through substitution mapping. Finally, five candidate genes were detected in the interval. The qRT-PCR analysis revealed only TIP41-like family protein (TIP41L) kept up-regulated expression and significantly lower in TM-1 than that in IL197 from -1 DPA to 15 DPA during cotton boll rapid developmental stage. Therefore, TIP41L gene is speculated as the most likely candidate gene. Comparative analysis with the other four allotetraploid species showed TIP41L gene was probably diverged after the formation of allotetraploid cotton, which may be selected and swept during domestication of modern upland cotton because small boll and seed are detrimental to fibre yield of cotton. This research would lay a solid foundation for further elucidating the molecular mechanism of cotton boll and seed development.

Inheritance, QTLs, and Candidate Genes of Lint Percentage in Upland Cotton

Cotton (Gossypium spp.) is an important natural fiber plant. Lint percentage (LP) is one of the most important determinants of cotton yield and is a typical quantitative trait with high variation and heritability. Many cotton LP genetic linkages and association maps have been reported. This work summarizes the inheritance, quantitative trait loci (QTLs), and candidate genes of LP to facilitate LP genetic study and molecular breeding. More than 1439 QTLs controlling LP have been reported. Excluding replicate QTLs, 417 unique QTLs have been identified on 26 chromosomes, including 243 QTLs identified at LOD >3. More than 60 are stable, major effective QTLs that can be used in marker-assisted selection (MAS). More than 90 candidate genes for LP have been reported. These genes encode MYB, HOX, NET, and other proteins, and most are preferentially expressed during fiber initiation and elongation. A putative molecular regulatory model of LP was constructed and provides the foundation for the genetic study and molecular breeding of LP.

Identification of yield-related genes through genome-wide association: case study of weeping forsythia, an emerging medicinal crop

KEY MESSAGE

This study identified candidate genes related to fruit yield for an emerging medicinal crop, weeping forsythia.

BACKGROUND

The genetic basis of crop yield is an agricultural research hotspot. Identifying the genes related to yield traits is the key to increase the yield. Weeping forsythia is an emerging medicinal crop that currently lacks excellent varieties. The genes related to fruit yield in weeping forsythia have not been identified.

OBJECTIVE

Thus, we aimed to screen the candidate genes related to fruit yield of weeping forsythia by using genome-wide association analysis.

METHODS

Here, 60 samples from the same field and source of weeping forsythia were collected to identify its yield-related candidate genes. Association analysis was performed on the variant loci and the traits related to yield, i.e., fruit length, width, thickness, and weight.

RESULTS

Results from admixture, neighbor-joining, and kinship matrix analyses supported the non-significant genetic differentiation of these samples. Significant association was found between 2 variant loci and fruit length, 8 loci and fruit width, 24 loci and fruit thickness, and 13 loci and fruit weight. Further search on the 20 kb up/downstream of these variant loci revealed 1 gene related to fruit length, 16 genes related to fruit width, 12 genes related to fruit thickness, and 13 genes related to fruit weight. Among which, 4 genes, namely, WRKY transcription factor 35, salicylic acid-binding protein, auxin response factor 6, and alpha-mannosidase were highly related to the fruit development of weeping forsythia.

CONCLUSION

This study identify four candidate genes related to fruit development, which will provide useful information for the subsequent molecular-assisted and genetic breeding of weeping forsythia.

Transcriptome Analysis of a Cotton Cultivar Provides Insights into the Differentially Expressed Genes Underlying Heightened Resistance to the Devastating Verticillium Wilt

Cotton is an important economic crop worldwide. Verticillium wilt (VW) caused by Verticillium dahliae (V. dahliae) is a serious disease in cotton, resulting in massive yield losses and decline of fiber quality. Breeding resistant cotton cultivars is an efficient but elaborate method to improve the resistance of cotton against V. dahliae infection. However, the functional mechanism of several excellent VW resistant cotton cultivars is poorly understood at present. In our current study, we carried out RNA-seq to discover the differentially expressed genes (DEGs) in the roots of susceptible cotton Gossypium hirsutum cultivar Junmian 1 (J1) and resistant cotton G.hirsutum cultivar Liaomian 38 (L38) upon Vd991 inoculation at two time points compared with the mock inoculated control plants. The potential function of DEGs uniquely expressed in J1 and L38 was also analyzed by GO enrichment and KEGG pathway associations. Most DEGs were assigned to resistance-related functions. In addition, resistance gene analogues (RGAs) were identified and analyzed for their role in the heightened resistance of the L38 cultivar against the devastating Vd991. In summary, we analyzed the regulatory network of genes in the resistant cotton cultivar L38 during V. dahliae infection, providing a novel and comprehensive insight into VW resistance in cotton.