Recombinant Inbred Line Population Research Articles

Understanding genome structure facilitates the use of wild lentil germplasm for breeding: A case study with shattering loci.

Plant breeders are generally reluctant to cross elite crop cultivars with their wild relatives to introgress novel desirable traits due to associated negative traits such as pod shattering. This results in a genetic bottleneck that could be reduced through better understanding of the genomic locations of the gene(s) controlling this trait. We integrated information on parental genomes, pod shattering data from multiple environments, and high-density genetic linkage maps to identify pod shattering quantitative trait loci (QTLs) in three lentil interspecific recombinant inbred line populations. The broad-sense heritability on a multi-environment basis varied from 0.46 (in LR-70, Lens culinaris × Lens odemensis) to 0.77 (in LR-68, Lens orientalis × L. culinaris). Genetic linkage maps of the interspecific populations revealed reciprocal translocations of chromosomal segments that differed among the populations, and which were associated with reduced recombination. LR-68 had a 2-5 translocation, LR-70 had 1-5, 2-6, and 2-7 translocations, and LR-86 had a 2-7 translocation in one parent relative to the other. Segregation distortion was also observed for clusters of single nucleotide polymorphisms on multiple chromosomes per population, further affecting introgression. Two major QTL, on chromosomes 4 and 7, were repeatedly detected in the three populations and contain several candidate genes. These findings will be of significant value for lentil breeders to strategically access novel superior alleles while minimizing the genetic impact of pod shattering from wild parents.

Computer vision models enable mixed linear modeling to predict arbuscular mycorrhizal fungal colonization using fungal morphology

The presence of Arbuscular Mycorrhizal Fungi (AMF) in vascular land plant roots is one of the most ancient of symbioses supporting nitrogen and phosphorus exchange for photosynthetically derived carbon. Here we provide a multi-scale modeling approach to predict AMF colonization of a worldwide crop from a Recombinant Inbred Line (RIL) population derived from Sorghum bicolor and S. propinquum. The high-throughput phenotyping methods of fungal structures here rely on a Mask Region-based Convolutional Neural Network (Mask R-CNN) in computer vision for pixel-wise fungal structure segmentations and mixed linear models to explore the relations of AMF colonization, root niche, and fungal structure allocation. Models proposed capture over 95% of the variation in AMF colonization as a function of root niche and relative abundance of fungal structures in each plant. Arbuscule allocation is a significant predictor of AMF colonization among sibling plants. Arbuscules and extraradical hyphae implicated in nutrient exchange predict highest AMF colonization in the top root section. Our work demonstrates that deep learning can be used by the community for the high-throughput phenotyping of AMF in plant roots. Mixed linear modeling provides a framework for testing hypotheses about AMF colonization phenotypes as a function of root niche and fungal structure allocations.

Unraveling the genetic basis of superior traits in Gossypium barbadense: From phenotype to genotype

G. barbadense is renowned for its high-quality fiber and is highly regarded as a natural material in the textile industry. However, research on cotton has mainly focused on G. hirsutum, and progress in sea island cotton has been relatively slow. There was limited understanding of the genetic loci and transcriptional regulatory mechanisms of important traits, and the genetic basis for the development of superior traits remains unclear. In this study, a recombinant inbred line (RIL) population was constructed using two sea island cotton parents from different cotton regions. The phenotypic characteristics of the two parents and the RIL population, as well as the phenotypic correlations, heritability, and genetic models of the RIL population, were comprehensively analyzed. The RIL population was genotyped using whole-genome resequencing technology, and a high-density intraspecific linkage map was constructed, consisting of 5295 bin markers and a total genetic map distance of 2721.79 centimorgans (cM). Phenotypic data collected from five different environments were used to detect 169 quantitative trait loci (QTLs) using the composite interval mapping method. Among these QTLs, 30 were related to agronomic traits, 61 were related to yield traits, and 78 were related to fiber quality traits. Additionally, 17 QTL clusters were detected, and the additive effects of these clusters explained the correlation between different phenotypic traits. Candidate genes for stable QTLs related to agronomic and yield traits were identified through variant annotation and functional prediction. Two bin markers associated with lint percentage (LP) were validated as potential breeding markers. Furthermore, using RNA-seq data of cotton fiber from the RIL population parents, the dynamic changes in gene expression during different developmental stages of cotton fiber were revealed, and important differentially expressed genes in the secondary cell wall development and metabolism network of fibers were identified. Importantly, through the combined analysis of fiber trait QTLs and transcriptomes, eight candidate genes involved in regulating fiber quality traits were predicted, and the genetic basis of the excellent allele site qFL_D04_1 in the breeding history of Chinese sea island cotton was elucidated. In summary, this study provides new genetic resources and potential breeding markers for cotton variety improvement, valuable theoretical information for understanding the genetic basis of important traits in sea island cotton, and effectively promotes the development of cotton biotechnology breeding.

Mapping QTLs for adult-plant resistance to powdery mildew and stripe rust using a recombinant inbred line population derived from cross Qingxinmai × 041133

A recombinant inbred line (RIL) population derived from wheat landrace Qingxinmai and breeding line 041133 exhibited segregation in resistance to powdery mildew and stripe rust in five and three field tests, respectively. A 16K genotyping by target sequencing (GBTS) single-nucleotide polymorphism (SNP) array-based genetic linkage map was used to dissect the quantitative trait loci (QTLs) for disease resistance. Four and seven QTLs were identified for adult-plant resistance (APR) against powdery mildew and stripe rust. QPm.caas-1B and QPm.caas-5A on chromosomes 1B and 5A were responsible for the APR against powdery mildew in line 041133. QYr.caas-1B, QYr.caas-3B, QYr.caas-4B, QYr.caas-6B.1, QYr.caas-6B.2, and QYr.caas-7B detected on the five B-genome chromosomes of line 041133 conferred its APR to stripe rust. QPm.caas-1B and QYr.caas.1B were co-localized with the pleiotropic locus Lr46/Yr29/Sr58/Pm39/Ltn2. A Kompetitive Allele Specific Polymorphic (KASP) marker KASP_1B_668028290 was developed to trace QPm/Yr.caas.1B. Four lines pyramiding six major disease resistance loci, PmQ, Yr041133, QPm/Yr.caas-1B, QPm.caas-2B.1, QYr.caas-3B, and QPm.caas-6B, were developed. They displayed effective resistance against both powdery mildew and stripe rust at the seedling and adult-plant stages.

QTL Mapping of Yield-Related Traits in Tetraploid Wheat Based on Wheat55K SNP Array

To enhance the understanding of yield-related traits in tetraploid wheat, it is crucial to investigate and identify genes that govern superior yield characteristics. This study utilized the wheat55K single nucleotide polymorphism array to genotype a recombinant inbred line (RIL) population consisting of 120 lines developed through the crossbreeding of two tetraploid wheat varieties, Qin Hei-1 (QH-1) and Durum Wheat (DW). An investigation and analysis were conducted on 11 yield-related traits, including peduncle length (PL), neck length (NL), spike length (SL), flowering date (FD), heading date (HD), thousand-kernel weight (TKW), kernel area ratio (KAR), kernel circumference (KC), kernel length (KL), kernel width (KW), and kernel length–width ratio (KL-WR), over a period of three years in two locations, Yang Ling, Shaanxi, and Lin He, Inner Mongolia. The analysis identified nine stable loci among eight agronomic traits, named QSL.QD-1A.1, QNL.QD-4B.2, QPL.QD-4B.1, QFD.QD-2B, QHD.QD-2B.1, QHD.QD-4B, QKC.QD-4B.2, QKL-WR.QD-4B.6, and QKL.QD-4B.2. Among them, the additive effects of three QTLs, QSL.QD-1A.1, QNL.QD-4B.2, and QFD.QD-2B, were positive, indicating that the enhancing alleles at these loci were derived from the parent line QH-1. These three QTLs showed significant positive effects on the phenotypes of the population materials. Furthermore, potential functional genes were identified within the mapping intervals of QSL.QD-1A.1 and QNL.QD-4B.2, which regulate the development of spike length and neck length, respectively. These results provide potential QTLs and candidate genes, which broaden the genetic basis of agronomic traits related to yield, such as SL, NL, PL, and FD, and benefits for wheat breeding and improvement.

Fine-mapping and validation of the major quantitative trait locus QFlANG-4B for flag leaf angle in wheat.

This study precisely mapped and validated a quantitative trait locus (QTL) located on chromosome 4B for flag leaf angle in wheat. Flag leaf angle (FLANG) is closely related to crop architecture and yield. We previously identified the quantitative trait locus (QTL) QFLANG-4B for FLANG on chromosome 4B, located within a 14-cM interval flanked by the markers Xbarc20 and Xzyh357, using a mapping population of recombinant inbred lines (RILs) derived from a cross between Nongda3331 (ND3331) and Zang1817. In this study, we fine-mapped QFLANG-4B and validated its associated genetic effect. We developed a BC3F3 population using ND3331 as the recurrent parent through marker-assisted selection, as well as near-isogenic lines (NILs) by selfing BC3F3 plants carrying different heterozygous segments for the QFLANG-4B region. We obtained eight recombinant types for QFLANG-4B, narrowing its location down to a 5.3-Mb region. This region contained 76 predicted genes, 7 of which we considered to be likely candidate genes for QFLANG-4B. Marker and phenotypic analyses of individual plants from the secondary mapping populations and their progeny revealed that the FLANG of the ND3331 allele is significantly higher than that of the Zang1817 allele in multiple environments. These results not only provide a basis for the map-based cloning of QFLANG-4B, but also indicate that QFLANG-4B has great potential for marker-assisted selection in wheat breeding programs designed to improve plant architecture and yield.

Mapping of Leaf Rust Resistance Loci in Two Kenyan Wheats and Development of Linked Markers

Leaf rust caused by the pathogen Puccinia triticina (Pt) is a destructive fungal disease of wheat that occurs in almost all wheat-growing areas across the globe. Genetic resistance has proven to be the best solution to mitigate the disease. Wheat breeders are continuously seeking new diversified and durable sources of resistance to use in developing new varieties. We developed recombinant inbred line (RIL) populations from two leaf rust-resistant genotypes (Kenya Kudu and AUS12568) introduced from Kenya to identify and characterize resistance to Pt and to develop markers linked closely to the resistance that was found. Our studies detected four QTL conferring adult plant resistance (APR) to leaf rust. Two of these loci are associated with known genes, Lr46 and Lr68, residing on chromosomes 1B and 7B, respectively. The remaining two, QLrKK_2B and QLrAus12568_5A, contributed by Kenya Kudu and AUS12568 respectively, are putatively new loci for Pt resistance. Both QLrKK_2B and QLrAus12568_5A were found to interact additively with Lr46 in significantly reducing the disease severity at adult plant growth stages in the field. We further developed a suite of six closely linked markers within the QLrAus12568_5A locus and four within the QLrKK_2B region. Among these, markers sunKASP_522 and sunKASP_524, flanking QLrAus12568_5A, and sunKASP_536, distal to QLrKK_2B, were identified as the most closely linked and reliable for marker-assisted selection. The markers were validated on a selection of 64 Australian wheat varieties and found to be polymorphic and robust, allowing for clear allelic discrimination. The identified new loci and linked molecular markers will enable rapid adoption by breeders in developing wheat varieties carrying diversified and durable resistance to leaf rust.

Nitrate transporter protein NPF5.12 and major latex-like protein MLP6 are important defense factors against Verticillium longisporum.

Plant defense responses to the soil-borne fungus Verticillium longisporum causing stem stripe disease on oilseed rape (Brassica napus) are poorly understood. In this study, a population of recombinant inbred lines (RILs) using the Arabidopsis thaliana accessions Sei-0 and Can-0 was established. Composite interval mapping, transcriptome data and T-DNA mutant screening identified the NITRATE/PEPTIDE TRANSPORTER FAMILY 5.12 gene (AtNPF5.12) as being associated with disease susceptibility in Can-0. Coimmunoprecipitation revealed interaction between AtNPF5.12 and the MAJOR LATEX PROTEIN family member AtMLP6, and fluorescence microscopy confirmed interaction in the plasma membrane and endoplasmic reticulum. CRISPR/Cas9 technology was applied to mutate the NPF5.12 and MLP6 genes in B. napus. Elevated fungal growth in the npf5.12 mlp6 double mutant of both oilseed rape and Arabidopsis demonstrated their importance in defense against V. longisporum. Colonization of this fungus depends also on available nitrates in the host root. Accordingly, the negative effect of nitrate depletion on fungal growth was less pronounced in Atnpf5.12 plants with impaired nitrate transport. In addition, suberin staining revealed involvement of the NPF5.12 and MLP6 genes in suberin barrier formation. Together, these results demonstrate a dependency of multiple plant factors that lead to successful V. longisporum root infection.

Elucidating the phenotypic basis of multi-environment stability for fiber yield and quality traits of cotton (Gossypium hirsutum L.) using 498 recombinant inbred lines

Understanding genotype-environment interactions and trait relationships is pivotal for guiding breeding efforts aimed at stabilizing cotton varieties across diverse environments while boosting yield and fiber quality. The study aimed to assess genotypic variability and stability in 10 agronomic and fiber quality traits across four environments (Anyang in 2020 and 2021 and Weixian in 2020 and 2021) for three parental lines (ZR014121, CCRI60, and EZ60) and their corresponding 498 recombinant inbred lines (RILs) populations. The results indicated that the analysis of variance showed significant genotype and genotype-by-environment effects for all measured traits. Analysis of correlation revealed highly significant positive correlations between seed cotton yield and each of boll weight (r = 0.95), lint yield (r = 0.90), and between boll weight and lint yield (r = 0.90), while highly significant negative correlations were noticed between fiber maturity and fiber elongation (r = −0.52) and between fiber length and lint percentage (r = −0.38). Furthermore, the weighted average of absolute scores (WAASB) was calculated for each trait, revealing moderate to high stability for some yield traits and fiber quality parameters. Also, the multi-trait stability index (MTSI) applied to these RILs populations identified G13 as the most stable line (MTSI = 5.5) and S23 as the least stable (MTSI = 12.1). Selecting 25 RILs with the lowest MTSI values (5.5–6.47) revealed elite stable lines with favorable trait values, providing a valuable genetic resource for developing high-performance cotton cultivars in diverse environments.

An aldehyde dehydrogenase gene, GhALDH7B4_A06, positively regulates fiber strength in upland cotton (Gossypium hirsutum L.).

High fiber strength (FS) premium cotton has significant market demand. Consequently, enhancing FS is a major objective in breeding quality cotton. However, there is a notable lack of known functionally applicable genes that can be targeted for breeding. To address this issue, our study used specific length-amplified fragment sequencing combined with bulk segregant analysis to study FS trait in an F2 population. Subsequently, we integrated these results with previous quantitative trait locus mapping results regarding fiber quality, which used simple sequence repeat markers in F2, F2:3, and recombinant inbred line populations. We identified a stable quantitative trait locus qFSA06 associated with FS located on chromosome A06 (90.74-90.83 Mb). Within this interval, we cloned a gene, GhALDH7B4_A06, which harbored a critical mutation site in coding sequences that is distinct in the two parents of the tested cotton line. In the paternal parent Ji228, the gene is normal and referred to as GhALDH7B4_A06O; however, there is a nonsense mutation in the maternal parent Ji567 that results in premature termination of protein translation, and this gene is designated as truncated GhALDH7B4_A06S. Validation using recombinant inbred lines and gene expression analysis revealed that this mutation site is correlated with cotton FS. Virus-induced gene silencing of GhALDH7B4 in cotton caused significant decreases in FS and fiber micronaire. Conversely, GhALDH7B4_A06O overexpression in Arabidopsis boosted cell wall component contents in the stem. The findings of our study provide a candidate gene for improving cotton fiber quality through molecular breeding.

Identification of Quantitative Trait Loci Associated with Seed Quality Traits in Two Early-Maturing Soybean Populations

In Canada, soybean (Glycine max (L.) Merr.) is primarily cultivated in three provinces (Ontario, Quebec, and Manitoba). Canadian breeders want to expand the current cultivation range to more northern agro-environments by developing early-maturing elite lines while maintaining good seed quality traits. To examine quantitative trait loci (QTL) involved in 100-seed weight and seed protein, oil, and fatty acid (oleic, linolenic, and linoleic acids) contents, we generated an early-maturing recombinant inbred line population (QS15544RIL) and an F2:F3 (QS15524F2:F3) population adapted to cultivation zones MGs 00 and 000, and phenotyped them for three and one years, respectively. Using two mapping algorithms (Inclusive composite interval mapping and Genome-wide composite interval mapping), we identified a total of 12 major regions that were either associated with QS15544RIL (five loci), QS15524F2:F3 (four loci), or both (three loci) populations. Of the 12 identified regions, three (RIL_GM12, RIL_GM16, and F2_GM04.2) were not previously identified and might respectively serve as novel sources of regulation for oil content, seed weight, and oleic acid. For the RIL_GM05 locus, we identified two novel variants in Glyma.05G244100/MOTHER OF FT AND TFL1, a gene with a confirmed role in the regulation of oleic and linoleic acid contents. Two of the major loci (RIL_GM04 and RIL_GM16) associated with the 100-seed weight trait and one locus (F2_GM04.2) associated with oleic acid were found to be overlapping three loci (E8-r1, GM16:5,680,173-5,730,237, and E8-r2) involved in early-maturity and/or shorter pod-filling that were previously identified by our group, suggesting possible breeding bottlenecks due to linkage drag or pleiotropic effects.

QTL for the Kinematic Traits That Define the Arabidopsis Root Elongation Zone and Their Relationship to Gravitropism.

Cell expansion in a discrete region called the elongation zone drives root elongation. Analyzing time lapse images can quantify the expansion in kinematic terms as if it were fluid flow. We used horizontal microscopes to collect images from which custom software extracted the length of the elongation zone, the peak relative elemental growth rate (REGR) within it, the axial position of the REGR peak, and the root elongation rate. Automation enabled these kinematic traits to be measured in 1575 Arabidopsis seedlings representing 162 recombinant inbred lines (RILs) derived from a cross of Cvi and Ler ecotypes. We mapped ten quantitative trait loci (QTL), affecting the four kinematic traits. Three QTL affected two or more traits in these vertically oriented seedlings. We compared this genetic architecture with that previously determined for gravitropism using the same RIL population. The major QTL peaks for the kinematic traits did not overlap with the gravitropism QTL. Furthermore, no single kinematic trait correlated with quantitative descriptors of the gravitropism response curve across this population. In addition to mapping QTL for growth zone traits, this study showed that the size and shape of the elongation zone may vary widely without affecting the differential growth induced by gravity.

Effect of genotyping errors on linkage map construction based on repeated chip analysis of two recombinant inbred line populations in wheat (Triticum aestivum L.)

Linkage maps are essential for genetic mapping of phenotypic traits, gene map-based cloning, and marker-assisted selection in breeding applications. Construction of a high-quality saturated map requires high-quality genotypic data on a large number of molecular markers. Errors in genotyping cannot be completely avoided, no matter what platform is used. When genotyping error reaches a threshold level, it will seriously affect the accuracy of the constructed map and the reliability of consequent genetic studies. In this study, repeated genotyping of two recombinant inbred line (RIL) populations derived from crosses Yangxiaomai × Zhongyou 9507 and Jingshuang 16 × Bainong 64 was used to investigate the effect of genotyping errors on linkage map construction. Inconsistent data points between the two replications were regarded as genotyping errors, which were classified into three types. Genotyping errors were treated as missing values, and therefore the non-erroneous data set was generated. Firstly, linkage maps were constructed using the two replicates as well as the non-erroneous data set. Secondly, error correction methods implemented in software packages QTL IciMapping (EC) and Genotype-Corrector (GC) were applied to the two replicates. Linkage maps were therefore constructed based on the corrected genotypes and then compared with those from the non-erroneous data set. Simulation study was performed by considering different levels of genotyping errors to investigate the impact of errors and the accuracy of error correction methods. Results indicated that map length and marker order differed among the two replicates and the non-erroneous data sets in both RIL populations. For both actual and simulated populations, map length was expanded as the increase in error rate, and the correlation coefficient between linkage and physical maps became lower. Map quality can be improved by repeated genotyping and error correction algorithm. When it is impossible to genotype the whole mapping population repeatedly, 30% would be recommended in repeated genotyping. The EC method had a much lower false positive rate than did the GC method under different error rates. This study systematically expounded the impact of genotyping errors on linkage analysis, providing potential guidelines for improving the accuracy of linkage maps in the presence of genotyping errors.

QTL mapping for the flag leaf-related traits using RILs derived from Trititrigia germplasm line SN304 and wheat cultivar Yannong15 in multiple environments

BackgroundDeveloping and enriching genetic resources plays important role in the crop improvement. The flag leaf affects plant architecture and contributes to the grain yield of wheat (Triticum aestivum L.). The genetic improvement of flag leaf traits faces problems such as a limited genetic basis. Among the various genetic resources of wheat, Thinopyrum intermedium has been utilized as a valuable resource in genetic improvement due to its disease resistance, large spikes, large leaves, and multiple flowers. In this study, a recombinant inbred line (RIL) population was derived from common wheat Yannong15 and wheat-Th. intermedium introgression line SN304 was used to identify the quantitative trait loci (QTL) for flag leaf-related traits.ResultsQTL mapping was performed for flag leaf length (FLL), flag leaf width (FLW) and flag leaf area (FLA). A total of 77 QTLs were detected, and among these, 51 QTLs with positive alleles were contributed by SN304. Fourteen major QTLs for flag leaf traits were detected on chromosomes 2B, 3B, 4B, and 2D. Additionally, 28 QTLs and 8 QTLs for flag leaf-related traits were detected in low-phosphorus and drought environments, respectively. Based on major QTLs of positive alleles from SN304, we identified a pair of double-ended anchor primers mapped on chromosome 2B and amplified a specific band of Th. intermedium in SN304. Moreover, there was a major colocated QTL on chromosome 2B, called QFll/Flw/Fla-2B, which was delimited to a physical interval of approximately 2.9 Mb and contained 20 candidate genes. Through gene sequence and expression analysis, four candidate genes associated with flag leaf formation and growth in the QTL interval were identified.ConclusionThese results promote the fine mapping of QFll/Flw/Fla-2B, which have pleiotropic effects, and will facilitate the identification of candidate genes for flag leaf-related traits. Additionally, this work provides a theoretical basis for the application of Th. intermedium in wheat breeding.

Genetic mapping reveals the complex genetic architecture controlling slow canopy wilting in soybean

In soybean [Glycine max (L.) Merr.], drought stress is the leading cause of yield loss from abiotic stress in rain-fed US growing areas. Only 10% of the US soybean production is irrigated; therefore, plants must possess physiological mechanisms to tolerate drought stress. Slow canopy wilting is a physiological trait that is observed in a few exotic plant introductions (PIs) and may lead to yield improvement under drought stress. Canopy wilting of 130 recombinant inbred lines (RILs) derived from Hutcheson × PI 471938 grown under drought stress was visually evaluated and genotyped with the SoySNP6K BeadChip. Over four years, field evaluations of canopy wilting were conducted under rainfed conditions at three locations across the US (Georgia, Kansas, and North Carolina). Due to the variation in weather among locations and years, the phenotypic data were collected from seven environments. Substantial variation in canopy wilting was observed among the genotypes in the RIL population across environments. Three QTLs were identified for canopy wilting from the RIL population using composite interval mapping on chromosomes (Chrs) 2, 8, and 9 based on combined environmental analyses. These QTLs inherited the favorable alleles from PI 471938 and accounted for 11, 10, and 14% of phenotypic variation, respectively. A list of 106 candidate genes were narrowed down for these three QTLs based on the published information. The QTLs identified through this research can be used as targets for further investigation to understand the mechanisms of slow canopy wilting. These QTLs could be deployed to improve drought tolerance through a targeted selection of the genomic regions from PI 471938.

Promoter variations of ClERF1 gene determines flesh firmness in watermelon

BackgroundFlesh firmness is a critical factor that influences fruit storability, shelf-life and consumer’s preference as well. However, less is known about the key genetic factors that are associated with flesh firmness in fresh fruits like watermelon.ResultsIn this study, through bulk segregant analysis (BSA-seq), we identified a quantitative trait locus (QTL) that influenced variations in flesh firmness among recombinant inbred lines (RIL) developed from cross between the Citrullus mucosospermus accession ZJU152 with hard-flesh and Citrullus lanatus accession ZJU163 with soft-flesh. Fine mapping and sequence variations analyses revealed that ethylene-responsive factor 1 (ClERF1) was the most likely candidate gene for watermelon flesh firmness. Furthermore, several variations existed in the promoter region between ClERF1 of two parents, and significantly higher expressions of ClERF1 were found in hard-flesh ZJU152 compared with soft-flesh ZJU163 at key developmental stages. DUAL-LUC and GUS assays suggested much stronger promoter activity in ZJU152 over ZJU163. In addition, the kompetitive allele-specific PCR (KASP) genotyping datasets of RIL populations and germplasm accessions further supported ClERF1 as a possible candidate gene for fruit flesh firmness variability and the hard-flesh genotype might only exist in wild species C. mucosospermus. Through yeast one-hybrid (Y1H) and dual luciferase assay, we found that ClERF1 could directly bind to the promoters of auxin-responsive protein (ClAux/IAA) and exostosin family protein (ClEXT) and positively regulated their expressions influencing fruit ripening and cell wall biosynthesis.ConclusionsOur results indicate that ClERF1 encoding an ethylene-responsive factor 1 is associated with flesh firmness in watermelon and provide mechanistic insight into the regulation of flesh firmness, and the ClERF1 gene is potentially applicable to the molecular improvement of fruit-flesh firmness by design breeding.

QTL mapping and candidate gene analysis reveal two major loci regulating green leaf color in non-heading Chinese cabbage.

Two major-effect QTL GlcA07.1 and GlcA09.1 for green leaf color were fine mapped into 170.25kb and 191.41kb intervals on chromosomes A07 and A09, respectively, and were validated by transcriptome analysis. Non-heading Chinese cabbage (NHCC) is a leafy vegetable with a wide range of green colors. Understanding the genetic mechanism behind broad spectrum of green may facilitate the breeding of high-quality NHCC. Here, we used F2 and F7:8 recombination inbred line (RIL) population from a cross between Wutacai (dark-green) and Erqing (lime-green) to undertake the genetic analysis and quantitative trait locus (QTL) mapping in NHCC. The genetic investigation of the F2 population revealed that the variation of green leaf color was controlled by two recessive genes. Six pigments associated with green leaf color, including total chlorophyll, chlorophyll a, chlorophyll b, total carotenoids, lutein, and carotene were quantified and applied for QTL mapping in the RIL population. A total of 7 QTL were detected across the whole genome. Among them, two major-effect QTL were mapped on chromosomes A07 (GlcA07.1) and A09 (GlcA09.1) corresponding to two QTL identified in the F2 population. The QTL GlcA07.1 and GlcA09.1 were further fine mapped into 170.25kb and 191.41kb genomic regions, respectively. By comparing gene expression level and gene annotation, BraC07g023810 and BraC07g023970 were proposed as the best candidates for GlcA07.1, while BraC09g052220 and BraC09g052270 were suggested for GlcA09.1. Two InDel molecular markers (GlcA07.1-BcGUN4 and GlcA09.1-BcSG1) associated with BraC07gA023810 and BraC09g052220 were developed and could effectively identify leaf color in natural NHCC accessions, suggesting their potential for marker-assisted leaf color selection in NHCC breeding.

Genomic basis determining root system architecture in maize.

A total of 389 and 344 QTLs were identified by GWAS and QTL mapping explaining accumulatively 32.2-65.0% and 23.7-63.4% of phenotypic variation for 14 shoot-borne root traits using more than 1300 individuals across multiple field trails. Efficient nutrient and water acquisition from soils depends on the root system architecture (RSA). However, the genetic determinants underlying RSA in maize remain largely unexplored. In this study, we conducted a comprehensive genetic analysis for 14 shoot-borne root traits using 513 inbred lines and 800 individuals from four recombinant inbred line (RIL) populations at the mature stage across multiple field trails. Our analysis revealed substantial phenotypic variation for these 14 root traits, with a total of 389 and 344 QTLs identified through genome-wide association analysis (GWAS) and linkage analysis, respectively. These QTLs collectively explained 32.2-65.0% and 23.7-63.4% of the trait variation within each population. Several a priori candidate genes involved in auxin and cytokinin signaling pathways, such as IAA26, ARF2, LBD37 and CKX3, were found to co-localize with these loci. In addition, a total of 69 transcription factors (TFs) from 27 TF families (MYB, NAC, bZIP, bHLH and WRKY) were found for shoot-borne root traits. A total of 19 genes including PIN3, LBD15, IAA32, IAA38 and ARR12 and 19 GWAS signals were overlapped with selective sweeps. Further, significant additive effects were found for root traits, and pyramiding the favorable alleles could enhance maize root development. These findings could contribute to understand the genetic basis of root development and evolution, and provided an important genetic resource for the genetic improvement of root traits in maize.

Genetic insights into superior grain number traits: a QTL analysis of wheat-Agropyron cristatum derivative pubing3228

BackgroundAgropyron cristatum (L.) is a valuable genetic resource for expanding the genetic diversity of common wheat. Pubing3228, a novel wheat-A. cristatum hybrid germplasm, exhibits several desirable agricultural traits, including high grain number per spike (GNS). Understanding the genetic architecture of GNS in Pubing3228 is crucial for enhancing wheat yield. This study aims to analyze the specific genetic regions and alleles associated with high GNS in Pubing3228.MethodsThe study employed a recombination inbred line (RIL) population derived from a cross between Pubing3228 and Jing4839 to investigate the genetic regions and alleles linked to high GNS. Quantitative Trait Loci (QTL) analysis and candidate gene investigation were utilized to explore these traits.ResultsA total of 40 QTLs associated with GNS were identified across 16 chromosomes, accounting for 4.25–17.17% of the total phenotypic variation. Five QTLs (QGns.wa-1D, QGns.wa-5 A, QGns.wa-7Da.1, QGns.wa-7Da.2 and QGns.wa-7Da.3) accounter for over 10% of the phenotypic variation in at least two environments. Furthermore, 94.67% of the GNS QTL with positive effects originated from Pubing3228. Candidate gene analysis of stable QTLs identified 11 candidate genes for GNS, including a senescence-associated protein gene (TraesCS7D01G148000) linked to the most significant SNP (AX-108,748,734) on chromosome 7D, potentially involved in reallocating nutrients from senescing tissues to developing seeds.ConclusionThis study provides new insights into the genetic mechanisms underlying high GNS in Pubing3228, offering valuable resources for marker-assisted selection in wheat breeding to enhance yield.

Molecular mapping of the broad bean wilt virus 2 resistance locus bwvr in Capsicum annuum using BSR-seq

Key messageBulked segregant RNA seq of pools of pepper accessions that are susceptible or resistant to Broad bean wilt virus 2 identifies a gene that might confer resistance to this devastating pathogen.The single-stranded positive-sense RNA virus Broad bean wilt virus 2 (BBWV2) causes substantial damage to pepper (Capsicum annuum) cultivation. Here, we describe mapping the BBWV2 resistance locus bwvr using a F7:8 recombinant inbred line (RIL) population constructed by crossing the BBWV2-resistant pepper accession ‘SNU-C’ with the susceptible pepper accession ‘ECW30R.’ All F1 plants infected with the BBWV2 strain PAP1 were susceptible to the virus, and the RIL population showed a 1:1 ratio of resistance to susceptibility, indicating that this trait is controlled by a single recessive gene. To map bwvr, we performed bulked segregant RNA-seq (BSR-seq). We sequenced pools of resistant and susceptible lines from the RILs and aligned the reads to the high-quality ‘Dempsey’ reference genome to identify variants between the pools. This analysis identified 519,887 variants and selected the region from 245.9–250.8 Mb of the Dempsey reference genome as the quantitative trait locus region for bwvr. To finely map bwvr, we used newly designed high-resolution melting (HRM) and Kompetitive allele specific PCR (KASP) markers based on variants obtained from the BSR-seq reads and the PepperSNP16K array. Comparative analysis identified 11 SNU-C-specific SNPs within the bwvr locus. Using markers derived from these variants, we mapped the candidate bwvr locus to the region from 246.833–246.949 kb. SNU-C-specific variants clustered near DEM.v1.00035533 within the bwvr locus. DEM.v1.00035533 encodes the nitrate transporter NPF1.2 and contains a SNP within its 5′ untranslated region. The bwvr locus, which contains four genes including DEM.v1.00035533, could represent a valuable resource for global pepper breeding programs.