Search Results (39)

Kernel row number (KRN) is a pivotal determinant for yield in maize breeding programs. However, the genetic basis underlying KRN remains largely elusive. To identify candidate genes regulating KRN, a population of 318 BC₄F₄ chromosomal segment substitution lines (CSSLs) was developed via backcrossing, with Baimaya (BMY) as the donor parent and B73 as the recurrent parent. Furthermore, a high-density genetic linkage map containing 2859 high-quality single-nucleotide polymorphism (SNP) markers was constructed for quantitative trait locus (QTL) mapping of KRN. Notably, 19 QTLs controlling KRN were detected across three environments and in the Best Linear Unbiased Prediction (BLUP) values; among these, a major-effect QTL (qKRN4.09-1) was consistently identified across all three environments and BLUP. Then, the integration of linkage mapping and transcriptome analysis of 5 mm immature ears from near-isogenic lines (NILs) uncovered a candidate gene, Zm00001eb205550. This gene exhibited significant downregulation in qKRN4.09-1^BMY, and two missense variants were detected between qKRN4.09-1^BMY and qKRN4.09-1^B73. Zm00001eb205550 exhibited preferential expression in developing ears. Moreover, the pyramiding of favorable alleles from the five stable QTLs significantly increased KRN in maize. These findings advance our genetic understanding of maize ear development and provide valuable genetic targets for improving KRN in maize breeding. Full article

Grain yield establishment is a complex progress and the genetic basis of one of the most important yield components, 100-kernel weight, remains largely unknown. Here, we employed a double haploid (DH) population containing 477 lines which was developed from a cross of two maize elite inbred lines, PHBA6 and Chang7-2, to identify quantitative trait loci (QTL) that related to 100-kernel weight. The phenotypes of the DH population were acquired over three years in two different locations, while the DH lines were genotyped by next-generation sequencing technology of massively parallel 3ʹ end RNA sequencing (MP3RNA-seq). Eventually, 28,874 SNPs from 436 DH lines were preserved after SNP calling and filtering and a genetic map with a length of 837 cM was constructed. Then, single environment QTL analysis was performed using the R/qtl program, and it was found that a total of 17 QTLs related to 100-kernel weight were identified and distributed across the whole genome except chromosomes 5 and 6. The total phenotypic variation explained by QTLs detected in three different environments (BJ2016, BJ2107, and HN2018) was 22.2%, 32.9%, and 51.38%, respectively. Among these QTLs, three of them were identified across different environments as environmentally stable QTLs and explained more than 10% of the phenotypic variance each. Together, the results provided in this study preliminarily revealed the genetic basis of 100-kernel weight and will enhance molecular breeding for key agronomic kernel-related traits in maize. Full article

Rice tillering is an important trait that is genetically and environmentally co-regulated. Nitorgen is one of the key nutrients affecting tillering, and straw return further affects tiller development by altering soil heterogeneity. In order to analyze the genetic regulation mechanism of rice tillering and its interactions with the environment, 124 recombinant inbred line (RIL) populations derived from two superior Peijiu lines, 9311 and PA64s, were used as materials in this study, and the dynamic tillering phenotypes were measured under three treatments (no nitrogen application, nitrogen application, and nitrogen + straw return) for two consecutive years. Using an existing genetic map, we conducted single-environment, multi-environment, and meta-QTL analyses to systematically identify tiller-related genetic loci and their environmental interactions. The main findings were as follows: (1) A total of 57 QTLs were identified in the single-environment QTL analysis, of which 44 were unreported new QTLs. Four QTLs showed temporal pleiotropy, ten QTLs contributed more than 10% to the phenotypes under the no-N treatment, and five QTLs contributed more than 10% under the straw return treatment. Among them, the phenotypic contribution of mks1-355 (qD1tn1-3) and mks1-352 (qD2TN1-2) both exceeded 40%. (2) Multi-environmental QTL analysis detected 15 QTLs. Of these, qmD1TN1 (mks1-356) showed no environmental interaction effect, while qmD1TN12 (mks12-267), qmD2TN1 (mks1-334), qmD2TN3-1 (mks3-105), and qmD5TN6 (mks6-71) exhibited antagonistic pleiotropy, suggesting that these QTL need to be considered for environmental specificity in breeding. (3) Meta-QTL analysis localized 52 MQTLs, of which MQTL3.1 and MQTL6.8 contained 82 and 59 candidate genes, respectively, and no reported tiller-related genes were found. (4) mks1-355 (qD1tn1-3), mks1-352 (qD2TN1-2), and mks1-356 (qmD1TN1) may be located in the same genetic locus, and their phenotypic contributions were more than 40%. These QTLs were detected stably for two consecutive years, and they may be the main effector QTLs in tillering that are less affected by the environment. Further analysis revealed that these QTLs corresponded to MQTL1.6, which contains 56 candidate genes. Of these, the expression level of OsSPL2 gene in the parental line 9311 was significantly higher than that of PA64s, and there were polymorphic differences in the coding region. It was hypothesized that OsSPL2 was the main effector gene of this QTL. This study provides important genetic resources for mining candidate genes related to tillering and nitrogen efficiency in rice and lays a theoretical foundation for directional breeding and molecular marker development in specific environments. Full article

Improving wheat yield is essential to meet the increasing demand for food production. This study aims to identify quantitative trait loci (QTL) associated with grain traits and plant height (PH) in winter wheat, using a recombinant inbred line (RIL) population derived from a cross between Zhongke 331 and Nongda 399. The RIL population was genotyped using the 16K GenoBaits Wheat single nucleotide polymorphism (SNP) array. A genetic linkage map was established, comprising 14,868 SNPs and spanning 3846.91 cM, with an average interval of 1.11 cM between markers. These SNPs were categorized into 3463 SNP bin markers, with 1653, 1508, and 302 located in the A, B, and D sub-genomes, respectively. QTL analysis for thousand-grain weight (TGW), grain length (GL), grain width (GW), and PH revealed 61 QTL influencing these traits across six environments. Loci qPH-4B.1 and qPH-4D.1 were consistently detected in five environments. QTL clusters with pleiotropic effects that regulate multiple grain traits were identified on chromosomes 4B and 4D. Furthermore, the combination of qPH-4B.1 and qPH-4D.1 resulted in a reduced plant height compared to the presence of either locus alone, indicating an additive effect between these loci. Full article

Fusarium head blight (FHB), caused by Fusarium graminearum, is a globally significant disease that severely impacts the yield and quality of wheat. Breeding resistant wheat varieties using resistance genes is the most cost-effective strategy for managing FHB, but few markers are available for marker-assisted selection (MAS) of resistance. In this study, we evaluated the resistance of a recombinant inbred line (RIL) population to FHB through single-floret inoculation in four field environments over two years. Combined with quantitative trait loci (QTL) detection through high-density genetic mapping based on wheat 50 K SNP arrays, we identified a total of 21 QTLs influencing FHB resistance. It is worth noting that QFhba-5D.2-1 was detected in two field environments as well as in the multi-environment trial (MET) analysis, explaining phenotypic variation ranging from 1.98% to 18.55%. We also pinpointed thirteen resistance genes within the QTL intervals on chromosomes 4A, 5D, 6B, and 7A associated with FHB defense mechanisms. Furthermore, we developed two Kompetitive Allele-Specific PCR (KASP) markers for the QFhba-5D.2-1 and QFhba-7A regions to validate their specificity within the RIL population. Subsequently, we validated the polymorphism of these two markers in 305 wheat germplasms and analyzed their effect on thousand kernel weight (TKW) and spike length (SL). These markers will accelerate the development of FHB-resistant wheat varieties through MAS, significantly reducing yield losses and strengthening food security. Full article

Maize is a critical crop for food, feed, and bioenergy worldwide. This study characterized the genetic diversity and population structure of 212 important inbred lines collected from the Southeast China breeding program using the Maize6H-60K single nucleotide polymorphism (SNP) array. To investigate the genetic architecture of plant height (PH) and ear height (EH), genome-wide association analysis (GWAS) was performed on this population in 2021 and 2022. Cluster analysis and population genetic structure analysis grouped the 212 maize inbred lines into 10 distinct categories. GWAS identified significant associations for PH, EH, and the EH/PH ratio. A total of 40 significant SNP (p < 8.55359 × 10⁻⁷) were detected, including nine associated with PH, with phenotypic variation explained (PVE) ranging from 3.42% to 25.92%. Additionally, 16 SNP were linked to EH, with PVE ranging from 2.49% to 38.49%, and 15 SNP were associated with the EH/PH ratio, showing PVE between 3.43% and 16.83%. Five stable SNP, identified across two or more environments, were further analyzed. Three of these SNP loci are reported for the first time in this study: two loci associated with the PH, AX-108020973, and AX-108022922, as well as one new locus, AX-108096437, which was significantly associated with the EH/PH ratio. Additionally, two other significant SNP (AX-247241325 and AX-108097244) were located within a 2 Mb range of previously identified QTL and/or related SNP. Within the 200 kb confidence intervals of these five stable SNP loci, 76 functionally annotated genes were identified. Further functional analysis indicated that 14 of these genes may play a role in regulating plant morphology, which is primarily involved in hormone synthesis, microtubule development, root growth, and cell division regulation. For instance, the homologous genes GRMZM2G375249 and GRMZM2G076029 in maize correspond to OsPEX1 in rice, a protein similar to extension proteins that are implicated in lignin biosynthesis, plant growth promotion, and the negative regulation of root growth through gibberellin-mediated pathways. The candidate gene corresponding to AX-108097244 is GRMZM2G464754; previous studies have reported its involvement in regulating EH in maize. These findings enhance the understanding of QTL associated with maize plant-type traits and provide a foundation for cloning PH, EH-related genes. Therefore, the results also support the development of functional markers for target genes and the breeding of improved maize varieties. Full article

Chilling injury during the germination stage (CIGS) of maize significantly hinders production, particularly in middle- and high-latitude regions, leading to slow germination, seed decay, and increased susceptibility to pathogens. This study dissects the genetic architecture of CIGS resistance expressed in terms of the relative germination rate (RGR) in maize through association mapping using genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs). A natural panel of 287 maize inbred lines was evaluated across multiple environments. The results revealed a broad-sense heritability of 0.68 for chilling tolerance, with 12 significant QTLs identified on chromosomes 1, 3, 5, 6, and 10. A genomic prediction analysis demonstrated that the rr-BLUP model outperformed other models in accuracy, achieving a moderate prediction accuracy of 0.44. This study highlights the potential of genomic selection (GS) to enhance chilling tolerance in maize, emphasizing the importance of training population size, marker density, and significant markers on prediction accuracy. These findings provide valuable insights for breeding programs aimed at improving chilling tolerance in maize. Full article

The oil content of maize kernels is essential to determine its nutritional and economic value. A multiparent population (MPP) consisting of five recombinant inbred line (RIL) subpopulations was developed to elucidate the genetic basis of the total oil content (TOC) in maize. The MPP used the subtropical maize inbred lines CML312 and CML384, along with the tropical maize inbred lines CML395, YML46, and YML32 as the female parents, and Ye107 as the male parent. A genome-wide association study (GWAS) was performed using 429 RILs of the multiparent population across three environments, employing 584,847 high-quality single nucleotide polymorphisms (SNPs). Furthermore, linkage analysis was performed in the five subpopulations to identify quantitative trait loci (QTL) linked to TOC in maize. Through QTL mapping and GWAS, 18 QTLs and 60 SNPs that were significantly associated with TOC were identified. Two novel candidate genes, Zm00001d029550 and Zm00001d029551, related to TOC in maize and located on chromosome 1 were reported, which have not been previously reported. These genes are involved in biosynthesis, lipid signal transduction, plant development and metabolism, and stress responses, potentially influencing maize TOC. Haplotype analysis of Zm00001d029550 and Zm00001d029551 revealed that Hap3 could be considered a superior haplotype for increasing TOC in maize. A co-located SNP (SNP-75791466) on chromosome 1, located 5648 bp and 11,951 bp downstream of the candidate genes Zm00001d029550 and Zm00001d029551, respectively, was found to be expressed in various maize tissues. The highest expression was observed in embryos after pollination, indicating that embryos are the main tissue for oil accumulation in maize. This study provides a theoretical basis for understanding the genetic mechanisms underlying maize TOC and developing high-quality, high-oil maize varieties. Full article

Soybean vegetable oil is an important source of the human diet. However, the analysis of the genetic mechanism leading to changes in soybean oil content is still incomplete. In this study, a total of 227 soybean materials were applied and analyzed by a genome-wide association study (GWAS). There are 44 quantitative trait nucleotides (QTNs) that were identified as associated with oil content. A total of six, four, and 34 significant QTN loci were identified in Xiangyang, Hulan, and Acheng, respectively. Of those, 26 QTNs overlapped with or were near the known oil content quantitative trait locus (QTL), and 18 new QTNs related to oil content were identified. A total of 594 genes were located near the peak single nucleotide polymorphism (SNP) from three tested environments. These candidate genes exhibited significant enrichment in tropane, piperidine, and pyridine alkaloid biosynthesiss (ko00960), ABC transporters (ko02010), photosynthesis-antenna proteins (ko00196), and betalain biosynthesis (ko00965). Combined with the GWAS and weighted gene co-expression network analysis (WGCNA), four candidate genes (Glyma.18G300100, Glyma.11G221100, Glyma.13G343300, and Glyma.02G166100) that may regulate oil content were identified. In addition, Glyma.18G300100 was divided into two main haplotypes in the studied accessions. The oil content of haplotype 1 is significantly lower than that of haplotype 2. Our research findings provide a theoretical basis for improving the regulatory mechanism of soybean oil content. Full article

Mercury (Hg) pollution not only poses a threat to the environment but also adversely affects the growth and development of plants, with potential repercussions for animals and humans through bioaccumulation in the food chain. Maize, a crucial source of food, industrial materials, and livestock feed, requires special attention in understanding the genetic factors influencing mercury accumulation. Developing maize varieties with low mercury accumulation is vital for both maize production and human health. In this study, a comprehensive genome-wide association study (GWAS) was conducted using an enlarged SNP panel comprising 1.25 million single nucleotide polymorphisms (SNPs) in 230 maize inbred lines across three environments. The analysis identified 111 significant SNPs within 78 quantitative trait loci (QTL), involving 169 candidate genes under the Q model. Compared to the previous study, the increased marker density and optimized statistical model led to the discovery of 74 additional QTL, demonstrating improved statistical power. Gene ontology (GO) enrichment analysis revealed that most genes participate in arsenate reduction and stress responses. Notably, GRMZM2G440968, which has been reported in previous studies, is associated with the significant SNP chr6.S_155668107 in axis tissue. It encodes a cysteine proteinase inhibitor, implying its potential role in mitigating mercury toxicity by inhibiting cysteine. Haplotype analyses provided further insights, indicating that lines carrying hap3 exhibited the lowest mercury content compared to other haplotypes. In summary, our study significantly enhances the statistical power of GWAS, identifying additional genes related to mercury accumulation and metabolism. These findings offer valuable insights into unraveling the genetic basis of mercury content in maize and contribute to the development of maize varieties with low mercury accumulation. Full article

Maize ear traits are an important component of yield, and the genetic basis of ear traits facilitates further yield improvement. In this study, a panel of 580 maize inbred lines were used as the study material, eight ear-related traits were measured through three years of planting, and whole genome sequencing was performed using the maize 40 K breeding chip based on genotyping by targeted sequencing (GBTS) technology. Five models were used to conduct a genome-wide association study (GWAS) on best linear unbiased estimate (BLUE) of ear traits to find the best model. The FarmCPU (Fixed and random model Circulating Probability Unification) model was the best model for this study; a total of 104 significant single nucleotide polymorphisms (SNPs) were detected, and 10 co-location SNPs were detected simultaneously in more than two environments. Through gene function annotation and prediction, a total of nine genes were identified as potentially associated with ear traits. Moreover, a total of 760 quantitative trait loci (QTL) associated with yield-related traits reported in 37 different articles were collected. Using the collected 760 QTL for meta-QTL analysis, a total of 41 MQTL (meta-QTL) associated with yield-related traits were identified, and 19 MQTL detected yield-related ear trait functional genes and candidate genes that have been reported in maize. Five significant SNPs detected by GWAS were located within these MQTL intervals, and another three significant SNPs were close to MQTL (less than 1 Mb). The results provide a theoretical reference for the analysis of the genetic basis of ear-related traits and the improvement of maize yield. Full article

Processing quality is an important economic wheat trait. The marker-assisted selection (MAS) method plays a vital role in accelerating genetic improvement of processing quality. In the present study, processing quality in a panel of 165 cultivars grown in four environments was evaluated by mixograph. An association mapping analysis using 90 K and 660 K single nucleotide polymorphism (SNP) arrays identified 24 loci in chromosomes 1A, 1B (4), 1D, 2A, 2B (2), 3A, 3B, 3D (2), 4A (3), 4B, 5D (2), 6A, 7B (2) and 7D (2), explaining 10.2–42.5% of the phenotypic variances. Totally, 15 loci were stably detected in two or more environments. Nine loci coincided with known genes or QTL, whereas the other fifteen were novel loci. Seven candidate genes encoded 3-ketoacyl-CoA synthase, lipoxygenase, pyridoxal phosphate-dependent decarboxylase, sucrose synthase 3 and a plant lipid transfer protein/Par allergen. SNPs significantly associated with processing quality and accessions with more favorable alleles can be used for marker-assisted selection. Full article

The recovery of Nero Lucano (NL) pigs in the Basilicata region (Southern Italy) started in 2001 with the collaboration of several public authorities in order to preserve native breeds that can play a significant economic role both due to their remarkable ability to adapt to difficult environments and the value of typical products from their area of origin. In this study, by using the Illumina Porcine SNP60 BeadChip, we compared the genetic structures of NL pigs reared in a single farm in two different periods separated by a time interval corresponding to at least three generations. The results showed an increase in the percentage of polymorphic loci, a decrease in the inbreeding coefficient calculated according to ROH genome coverage (F_ROH), a reduction in the number of ROH longer than 16 Mb and an increase in ROH with a length between 2 and 4 Mb, highlighting a picture of improved genetic variability. In addition, ROH island analysis in the two groups allowed us to identify five conserved regions, located on chromosomes 1, 4, 8, 14 and 15, containing genes involved in biological processes affecting immune response, reproduction and production traits. Only the conserved ROH island on chromosome 14 contains markers which, according to the literature, are associated with QTLs affecting thoracic vertebra number, teat number, gestation length, age at puberty and mean platelet volume. Full article

Kernel number per row (KNR) is an essential component of maize (Zea mays L.) grain yield (GY), and understanding its genetic mechanism is crucial to improve GY. In this study, two F₇ recombinant inbred line (RIL) populations were created using a temperate–tropical introgression line TML418 and a tropical inbred line CML312 as female parents and a backbone maize inbred line Ye107 as the common male parent. Bi-parental quantitative trait locus (QTL) mapping and genome-wide association analysis (GWAS) were then performed on 399 lines of the two maize RIL populations for KNR in two different environments using 4118 validated single nucleotide polymorphism (SNP) markers. This study aimed to: (1) detect molecular markers and/or the genomic regions associated with KNR; (2) identify the candidate genes controlling KNR; and (3) analyze whether the candidate genes are useful in improving GY. The authors reported a total of 7 QTLs tightly linked to KNR through bi-parental QTL mapping and identified 21 SNPs significantly associated with KNR through GWAS. Among these, a highly confident locus qKNR7-1 was detected at two locations, Dehong and Baoshan, with both mapping approaches. At this locus, three novel candidate genes (Zm00001d022202, Zm00001d022168, Zm00001d022169) were identified to be associated with KNR. These candidate genes were primarily involved in the processes related to compound metabolism, biosynthesis, protein modification, degradation, and denaturation, all of which were related to the inflorescence development affecting KNR. These three candidate genes were not reported previously and are considered new candidate genes for KNR. The progeny of the hybrid Ye107 × TML418 exhibited strong heterosis for KNR, which the authors believe might be related to qKNR7-1. This study provides a theoretical foundation for future research on the genetic mechanism underlying KNR in maize and the use of heterotic patterns to develop high-yielding hybrids. Full article

Synergetic elongation of mesocotyl and coleoptile are crucial in governing maize seedlings emergence, especially for the maize sown in deep soil. Studying the genomic regions controlling maize deep-sowing tolerance would aid the development of new varieties that are resistant to harsh conditions, such as drought and low temperature during seed germination. Using 346 F_2:3 maize population families from W64A × K12 cross at three sowing depths, we identified 33 quantitative trait loci (QTLs) for the emergence rate, mesocotyl, coleoptile, and seedling lengths via composite interval mapping (CIM). These loci explained 2.89% to 14.17% of phenotypic variation in a single environment, while 12 of 13 major QTLs were identified at two or more sowing environments. Among those, four major QTLs in Bin 1.09, Bin 4.08, Bin 6.01, and Bin 7.02 supported pleiotropy for multiple deep-sowing tolerant traits. Meta-analysis identified 17 meta-QTLs (MQTLs) based on 130 original QTLs from present and previous studies. RNA-Sequencing of mesocotyl and coleoptile in both parents (W64A and K12) at 3 cm and 20 cm sowing environments identified 50 candidate genes expressed differentially in all major QTLs and MQTLs regions: six involved in the circadian clock, 27 associated with phytohormones biosynthesis and signal transduction, seven controlled lignin biosynthesis, five regulated cell wall organization formation and stabilization, three were responsible for sucrose and starch metabolism, and two in the antioxidant enzyme system. These genes with highly interconnected networks may form a complex molecular mechanism of maize deep-sowing tolerance. Findings of this study will facilitate the construction of molecular modules for deep-sowing tolerance in maize. The major QTLs and MQTLs identified could be used in marker-assisted breeding to develop elite maize varieties. Full article