Identification of heterotic loci associated with grain yield and its components using two CSSL test populations in maize

Dissecting the Superior Drivers for the Simultaneous Improvement of Fiber Quality and Yield Under Drought Stress Via Genome-Wide Artificial Introgressions of Gossypium barbadense into Gossypium hirsutum

Global water scarcity and extreme weather intensify drought stress, significantly reducing cotton yield and quality worldwide. Drought treatments are conducted using a population of chromosome segment substitution lines generated from E22 (G. hirsutum) and 3-79 (G. barbadense) as parental lines either show superior yields or fiber quality under both control and drought conditions. Fourteen datasets, covering 4 yields and 4 quality traits, are compiled and assessed for drought resistance using the drought resistance coefficient (DRC) and membership function value of drought resistance (MFVD). Genome-wide association studies, linkage analysis, and bulked segregant analysis are combined to analyze the DR-related QTL. A total of 121 significant QTL are identified by DRC and MFVD of the 8 traits. CRISPR/Cas9 and virus-induced gene silencing techniques verified DRR1 and DRT1 as pivotal genes in regulating drought resistant of cotton, with hap3-79 exhibiting greater drought resistance than hapE22 concerning DRR1 and DRT1. Moreover, 14 markers with superior yield and fiber quality are selected for drought treatment. This study offers valuable insights into yield and fiber quality variations between G. hirsutum and G. barbadense amid drought, providing crucial theoretical and technological backing for developing cotton varieties resilient to drought, with high yield and superior fiber quality.

Introgression of Heterotic Genomic Segments from Brassica carinata into Brassica juncea for Enhancing Productivity

Interspecific hybridization resulted in the creation of B. juncea introgression lines (ILs) generated from B. carinata with increased productivity and adaptability. Forty ILs were crossed with their respective B. juncea recipient parents to generate introgression line hybrids (ILHs) and the common tester (SEJ 8) was used to generate test hybrids (THs). Mid-parent heterosis in ILHs and standard heterosis in THs were calculated for eight yield and yield-related traits. Heterotic genomic regions were dissected using ten ILs with significant mid-parent heterosis in ILHs and standard heterosis in THs for seed yield. A high level of heterosis for seed yield was contributed by 1000 seed weight (13.48%) in D31_ILHs and by total siliquae/plant (14.01%) and siliqua length (10.56%) in PM30_ILHs. The heterotic ILs of DRMRIJ 31 and Pusa Mustard 30 were examined using polymorphic SNPs between the parents, and a total of 254 and 335 introgressed heterotic segments were identified, respectively. This investigation discovered potential genes, viz., PUB10, glutathione S transferase, TT4, SGT, FLA3, AP2/ERF, SANT4, MYB, and UDP-glucosyl transferase 73B3 that were previously reported to regulate yield-related traits. The heterozygosity of the FLA3 gene significantly improved siliqua length and seeds per siliqua in ILHs of Pusa Mustard 30. This research proved that interspecific hybridization is an effective means of increasing the diversity of cultivated species by introducing new genetic variants and improving the level of heterosis.

Mapping of QTLs for Yield Traits Using F2:3:4 Populations Derived From Two Alien Introgression Lines Reveals qTGW8.1 as a Consistent QTL for Grain Weight From Oryza nivara

Wild introgressions play a crucial role in crop improvement by transferring important novel alleles and broadening allelic diversity of cultivated germplasm. In this study, two stable backcross alien introgression lines 166s and 14s derived from Swarn/Oryza nivara IRGC81848 were used as parents to generate populations to map quantitative trait loci (QTLs) for yield-related traits. Field evaluation of yield-related traits in F₂, F₃, and F₄ population was carried out in normal irrigated conditions during the wet season of 2015 and dry seasons of 2016 and 2018, respectively. Plant height, tiller number, productive tiller number, total dry matter, and harvest index showed a highly significant association to single plant yield in F₂, F₃, and F₄. In all, 21, 30, and 17 QTLs were identified in F₂, F_2:3, and F_2:4, respectively, for yield-related traits. QTLs qPH6.1 with 12.54% phenotypic variance (PV) in F₂, qPH1.1 with 13.01% PV, qTN6.1 with 10.08% PV in F_2:3, and qTGW6.1 with 15.19% PV in F_2:4 were identified as major effect QTLs. QTLs qSPY4.1 and qSPY6.1 were detected for grain yield in F₂ and F_2:3 with PV 8.5 and 6.7%, respectively. The trait enhancing alleles of QTLs qSPY4.1, qSPY6.1, qPH1.1, qTGW6.1, qTGW8.1, qGN4.1, and qTDM5.1 were from O. nivara. QTLs of the yield contributing traits were found clustered in the same chromosomal region. qTGW8.1 was identified in a 2.6 Mb region between RM3480 and RM3452 in all three generations with PV 6.1 to 9.8%. This stable and consistent qTGW8.1 allele from O. nivara can be fine mapped for identification of causal genes. From this population, lines C₂12, C₂124, C₂128, and C₂143 were identified with significantly higher SPY and C₂103, C₂116, and C₂117 had consistently higher thousand-grain weight values than both the parents and Swarna across the generations and are useful in gene discovery for target traits and further crop improvement.

Association mapping for general combining ability with yield, plant height and ear height using F1 population in maize

General combining ability (GCA) is an important index for inbred lines breeding of maize. To identify the genetic loci of GCA and associated agronomic traits, an association analysis with 195 SSRs was made in phenotypic traits of 240 F1 derived from 120 elite inbred lines containing current breeding resources of maize crossed with 2 testers (Zheng58 and Chang7-2) in two places in 2018. All of the 20 association loci detected for grain yield (GY), plant height (PH), ear height (EH) and GCA for the three traits in two places could explain a phenotypic variation range of 7.31%-9.29%. Among the 20 association loci, 9 (7.31%-9.04%) were associated with GY, 4 (7.22%-8.91%) were related to GCA of GY, 1 (7.56%) was associated with PH, and 3 (7.53%-8.96%) were related to EH. In addition, 3 loci (9.14%-9.29%) were associated with GCA of PH whereas no locus was identified for GCA of EH. In the comparison of the association loci detected in Baoding and Handan, interestingly, one locus (7.69% and 8.11%) was identified in both environments and one locus (7.52% and 7.82%) was identified for yield and GCA of yield. Therefore, the identification of GY-, PH-, EH- and GCA-related association loci could not only provide references for high yield breeding of maize, but also help us comprehend the relationships among GY, agricultural traits and GCA.

Heterotic quantitative trait loci analysis and genomic prediction of seedling biomass-related traits in maize triple testcross populations

BACKGROUND

Heterosis has been widely used in maize breeding. However, we know little about the heterotic quantitative trait loci and their roles in genomic prediction. In this study, we sought to identify heterotic quantitative trait loci for seedling biomass-related traits using triple testcross design and compare their prediction accuracies by fitting molecular markers and heterotic quantitative trait loci.

RESULTS

A triple testcross population comprised of 366 genotypes was constructed by crossing each of 122 intermated B73 × Mo17 genotypes with B73, Mo17, and B73 × Mo17. The mid-parent heterosis of seedling biomass-related traits involved in leaf length, leaf width, leaf area, and seedling dry weight displayed a large range, from less than 50 to ~ 150%. Relationships between heterosis of seedling biomass-related traits showed congruency with that between performances. Based on a linkage map comprised of 1631 markers, 14 augmented additive, two augmented dominance, and three dominance × additive epistatic quantitative trait loci for heterosis of seedling biomass-related traits were identified, with each individually explaining 4.1-20.5% of the phenotypic variation. All modes of gene action, i.e., additive, partially dominant, dominant, and overdominant modes were observed. In addition, ten additive × additive and six dominance × dominance epistatic interactions were identified. By implementing the general and special combining ability model, we found that prediction accuracy ranged from 0.29 for leaf length to 0.56 for leaf width. Different number of marker analysis showed that ~ 800 markers almost capture the largest prediction accuracies. When incorporating the heterotic quantitative trait loci into the model, we did not find the significant change of prediction accuracy, with only leaf length showing the marginal improvement by 1.7%.

CONCLUSIONS

Our results demonstrated that the triple testcross design is suitable for detecting heterotic quantitative trait loci and evaluating the prediction accuracy. Seedling leaf width can be used as the representative trait for seedling prediction. The heterotic quantitative trait loci are not necessary for genomic prediction of seedling biomass-related traits.

A combination of linkage mapping and GWAS brings new elements on the genetic basis of yield-related traits in maize across multiple environments

Using GWAS and QTL mapping identified 100 QTL and 138 SNPs, which control yield-related traits in maize. The candidate gene GRMZM2G098557 was further validated to regulate ear row number by using a segregation population. Understanding the genetic basis of yield-related traits contributes to the improvement of grain yield in maize. This study used an inter-mated B73 × Mo17 (IBM) Syn10 doubled-haploid (DH) population and an association panel to identify the genetic loci responsible for nine yield-related traits in maize. Using quantitative trait loci (QTL) mapping, 100 QTL influencing these traits were detected across different environments in the IBM Syn10 DH population, with 25 co-detected in multiple environments. Using a genome-wide association study (GWAS), 138 single-nucleotide polymorphisms (SNPs) were identified as correlated with these traits (P < 2.04E-06) in the association panel. Twenty-one pleiotropic QTL/SNPs were identified to control different traits in both populations. A combination of QTL mapping and GWAS uncovered eight significant SNPs (PZE-101097575, PZE-103169263, ZM011204-0763, PZE-104044017, PZE-104123110, SYN8062, PZE-108060911, and PZE-102043341) that were co-located within seven QTL confidence intervals. According to the eight co-localized SNPs by the two populations, 52 candidate genes were identified, among which the ear row number (ERN)-associated SNP SYN8062 was closely linked to SBP-transcription factor 7 (GRMZM2G098557). Several SBP-transcription factors were previously demonstrated to modulate maize ERN. We then validated the phenotypic effects of SYN8062 in the IBM Syn10 DH population, indicating that the ERN of the lines with the A-allele in SYN8062 was significantly (P < 0.05) larger than that of the lines with the G-allele in SYN8062 in each environment. These findings provide valuable information for understanding the genetic mechanisms of maize grain yield formation and for improving molecular marker-assisted selection for the high-yield breeding of maize.

Genome-wide identification and analysis of heterotic loci in three maize hybrids

Heterosis, or hybrid vigour, is a predominant phenomenon in plant genetics, serving as the basis of crop hybrid breeding, but the causative loci and genes underlying heterosis remain unclear in many crops. Here, we present a large-scale genetic analysis using 5360 offsprings from three elite maize hybrids, which identifies 628 loci underlying 19 yield-related traits with relatively high mapping resolutions. Heterotic pattern investigations of the 628 loci show that numerous loci, mostly with complete-incomplete dominance (the major one) or overdominance effects (the secondary one) for heterozygous genotypes and nearly equal proportion of advantageous alleles from both parental lines, are the major causes of strong heterosis in these hybrids. Follow-up studies for 17 heterotic loci in an independent experiment using 2225 F₂ individuals suggest most heterotic effects are roughly stable between environments with a small variation. Candidate gene analysis for one major heterotic locus (ub3) in maize implies that there may exist some common genes contributing to crop heterosis. These results provide a community resource for genetics studies in maize and new implications for heterosis in plants.

Identification of quantitative trait loci for kernel-related traits and the heterosis for these traits in maize (Zea mays L.)

Heterosis has been extensively applied for many traits during maize breeding, but there has been relatively little attention paid to the heterosis for kernel size. In this study, we evaluated a population of 301 recombinant inbred lines derived from a cross between 08-641 and YE478, as well as 298 hybrids from an immortalized F₂ (IF₂) population to detect quantitative trait loci (QTLs) for six kernel-related traits and the mid-parent heterosis (MPH) for these traits. A total of 100 QTLs, six pairs of loci with epistatic interactions, and five significant QTL × environment interactions were identified in both mapping populations. Seven QTLs accounted for over 10% of the phenotypic variation. Only four QTLs affected both the trait means and the MPH, suggesting the genetic mechanisms for kernel-related traits and the heterosis for kernel size are not completely independent. Moreover, more than half of the QTLs for each trait in the IF₂ population exhibited dominance, implying that dominance is more important than other genetic effects for the heterosis for kernel-related traits. Additionally, 20 QTL clusters comprising 46 QTLs were detected across ten chromosomes. Specific chromosomal regions (bins 2.03, 6.04-6.05, and 9.01-9.02) exhibited pleiotropy and congruency across diverse heterotic patterns in previous studies. These results may provide additional insights into the genetic basis for the MPH for kernel-related traits.

Genetic dissection of yield-related traits and mid-parent heterosis for those traits in maize (Zea mays L.)

BACKGROUND

Utilization of heterosis in maize could be critical in maize breeding for boosting grain yield. However, the genetic architecture of heterosis is not fully understood. To dissect the genetic basis of yield-related traits and heterosis in maize, 301 recombinant inbred lines derived from 08 to 641 × YE478 and 298 hybrids from the immortalized F₂ (IF₂) population were used to map quantitative trait loci (QTLs) for nine yield-related traits and mid-parent heterosis.

RESULTS

We observed 156 QTLs, 28 pairs of loci with epistatic interaction, and 10 significant QTL × environment interactions in the inbred and hybrid mapping populations. The high heterosis in F₁ and IF₂ populations for kernel weight per ear (KWPE), ear weight per ear (EWPE), and kernel number per row (KNPR) matched the high percentages of QTLs (over 50%) for those traits exhibiting overdominance, whereas a notable predominance of loci with dominance effects (more than 70%) was observed for traits that show low heterosis such as cob weight per ear (CWPE), rate of kernel production (RKP), ear length (EL), ear diameter (ED), cob diameter, and row number (RN). The environmentally stable QTL qRKP3-2 was identified across two mapping populations, while qKWPE9, affecting the trait mean and the mid-parent heterosis (MPH) level, explained over 18% of phenotypic variations. Nine QTLs, qEWPE9-1, qEWPE10-1, qCWPE6, qEL8, qED2-2, qRN10-1, qKWPE9, qKWPE10-1, and qRKP4-3, accounted for over 10% of phenotypic variation. In addition, QTL mapping identified 95 QTLs that were gathered together and integrated into 33 QTL clusters on 10 chromosomes.

CONCLUSIONS

The results revealed that (1) the inheritance of yield-related traits and MPH in the heterotic pattern improved Reid (PA) × Tem-tropic I (PB) is trait-dependent; (2) a large proportion of loci showed dominance effects, whereas overdominance also contributed to MPH for KNPR, EWPE, and KWPE; (3) marker-assisted selection for markers at genomic regions 1.09-1.11, 2.04, 3.08-3.09, and 10.04-10.05 contributed to hybrid performance per se and heterosis and were repeatedly reported in previous studies using different heterotic patterns is recommended.

Overdominance is the major genetic basis of lint yield heterosis in interspecific hybrids between G. hirsutum and G. barbadense

The genetic basis of heterosis has not been resolved for approximately a century, although the role of loci with overdominant (ODO) effects has continued to be discussed by biologists. In the present investigation, a proposed model was studied in Gossypium hirsutum L. introgression lines (ILs) harbouring a segment of G. barbadense. These introgressions were confirmed by a single marker of G. barbadense. These ILs contained 396 quantitative trait loci (QTLs) for 11 yield and non-yield traits that were recorded in the field on homozygous and heterozygous plants for 5 years. After comparing the different types of QTLs between the yield group and the non-yield group, it was found that the yield group had significantly higher ODO QTL ratios. Moreover, 16 ODO QTLs identified for 5 yield-related traits were consistently detected during 5 cotton growing seasons (2010-2011 and 2013-2015): 6 of 7 for boll weight, 3 of 11 for seed-cotton yield per plant, 4 of 17 for boll number, 2 of 13 for lint yield per plant and 1 of 11 for lint percentage. Therefore, we propose that overdominance is the major genetic basis of lint yield heterosis in interspecific hybrids between G. barbadense and G. hirsutum. These findings have important implications in cotton breeding in that the boll weight can be improved by utilizing ODO QTLs via heterosis; thus, the stagnant yield barrier can be smashed to achieve sustainable increases in cotton production. Additionally, this concept can be translated to other field crops for improving their yield potential.

Dissecting Heterosis During the Ear Inflorescence Development Stage in Maize via a Metabolomics-based Analysis

Heterosis can increase the yield of many crops and has been extensively applied in agriculture. In maize, female inflorescence architecture directly determines grain yield. Thus, exploring the relationship between early maize ear inflorescence development and heterosis regarding yield-related traits may be helpful for characterizing the molecular mechanisms underlying heterotic performance. In this study, we fine mapped the overdominant heterotic locus (hlEW2b), associated with ear width, in an approximately 1.98-Mb region based on analyses of chromosome segment substitution lines and the corresponding testcross population. Maize ear inflorescences at the floral meristem stage were collected from two inbred lines, one chromosome segment substitution line that carried hlEW2b (sub-CSSL₁₆), the receptor parent lx9801, and the Zheng58 × sub-CSSL₁₆ and Zheng58 × lx9801 hybrid lines. A total of 256 metabolites were identified, including 31 and 24 metabolites that were differentially accumulated between the two hybrid lines and between the two inbred lines, respectively. Most of these metabolites are involved in complex regulatory mechanisms important for maize ear development. For example, nucleotides are basic metabolites affecting cell composition and carbohydrate synthesis. Additionally, nicotinate and nicotinamide metabolism is important for photosynthesis, plant stress responses, and cell expansion. Moreover, flavonoid and phenolic metabolites regulate auxin transport and cell apoptosis. Meanwhile, phytohormone biosynthesis and distribution influence the cell cycle and cell proliferation. Our results revealed that changes in metabolite contents may affect the heterotic performance related to ear width and yield in maize hybrid lines. This study provides new clues in heterosis at the metabolomics level and implies that differentially accumulated metabolites made distinct contributions to the heterosis at an early stage of ear inflorescences development.

Heterotic loci identified for maize kernel traits in two chromosome segment substitution line test populations

Heterosis has been widely used to increase grain quality and yield, but its genetic mechanism remains unclear. In this study, the genetic basis of heterosis for four maize kernel traits was examined in two test populations constructed using a set of 184 chromosome segment substitution lines (CSSLs) and two inbred lines (Zheng58 and Xun9058) in two environments. 63 and 57 different heterotic loci (HL) were identified for four kernel traits in the CSSLs × Zheng58 and CSSLs × Xun9058 populations, respectively. Of these, nine HL and six HL were identified for four kernel traits in the CSSLs × Zheng58 and CSSLs × Xun9058 populations, at the two locations simultaneously. Comparative analysis of the HL for the four kernel traits identified only 21 HL in the two test populations simultaneously. These results showed that most HL for the four kernel traits differed between the two test populations. The common HL were important loci from the Reid × Tangsipingtou heterotic model, and could be used to predict hybrid performance in maize breeding.