Genetic Map Research Articles

High-resolution genetic map and SNP chip for molecular breeding in Panax ginseng, a tetraploid medicinal plant

Abstract Ginseng (Panax ginseng) renowned as the king of medicinal plants. Ginseng grows slowly under shade conditions, requiring at least four years to produce a limited number of seeds. Molecular breeding of ginseng faces challenges due to its the tetraploid genome and the absence of an efficient molecular marker system. To overcome these obstacles, we adopted genotyping-by-sequencing to delve into genetic mapping and survey genetic diversity. We constructed a comprehensive genetic map comprising 24 linkage groups, each corresponding to one of the 24 chromosomes in the ginseng genome, based on 1216 non-redundant SNPs obtained from an F2 mapping population. Additionally, 431 103 SNPs were identified from 119 diverse ginseng genotypes. From these, 192 informative subgenome-specific single copy SNPs were selected to develop a SNP chip. The SNP chip was used to genotype a large ginseng collection, encompassing registered cultivars, breeding lines, wild-simulated ginseng, and wild ginseng from various countries and regions. We evaluated the utility of the assay for molecular breeding with 919 ginseng genotypes. This breeder-friendly SNP chip promises versatility, enabling purity assessments of seeds and products, the authentication of species and cultivars, and the determination of homozygosity and homogeneity rates for breeding lines. Genotype data for 1200 ginseng genotypes are now stored in our database. This SNP chip lays the foundation for a molecular breeding in ginseng and will facilitate the breeding process in this medicinal crop.

Comparing Apples and Oranges: Advances in Disease Resistance Breeding of Woody Perennial Fruit Crops.

Apple and citrus are perennial tree fruit crops that are vital for nutritional security and agricultural economy and to achieve the Sustainable Development Goals of the United Nations. Apple scab and fire blight, along with Huanglongbing, canker, and tristeza virus, stand out as their most notorious diseases and annually destabilize fruit supply. An environmentally sound approach to managing these diseases is improving tree resistance through breeding and biotechnology. Perennial fruit tree germplasm collections are distributed globally and offer untapped potential as sources of resistance. However, long juvenility, specific pollination and flowering habits, and extensive outcrossing hinder apple and citrus breeding. Advances in breeding approaches include trans- and cis-genesis, genome editing, and rapid-cycle breeding, which, in addition to conventional crossbreeding, can all facilitate accelerated integration of resistance into elite germplasm. In addition, the global pool of available sources of resistance can be characterized by the existing genetic mapping and gene expression studies for accurate discovery of associated loci, genes, and markers to efficiently include these sources in breeding efforts. We discuss and propose a multitude of approaches to overcome the challenges of breeding for resistance in woody perennials and outline a technical path to reduce the time required for the ultimate deployment of disease-resistant cultivars.

QTL Mapping of Fiber- and Seed-Related Traits in Chromosome Segment Substitution Lines Derived from Gossypium hirsutum × Gossypium darwinii.

A narrow genetic basis limits further the improvement of modern Gossypium hirsutum cultivar. The abundant genetic diversity of wild species provides available resources to solve this dilemma. In the present study, a chromosome segment substitution line (CSSL) population including 553 individuals was established using G. darwinii accession 5-7 as the donor parent and G. hirsutum cultivar CCRI35 as the recipient parent. After constructing a high-density genetic map with the BC1 population, the genotype and phenotype of the CSSL population were investigated. A total of 235 QTLs, including 104 QTLs for fiber-related traits and 132 QTLs for seed-related traits, were identified from four environments. Among these QTLs, twenty-seven QTLs were identified in two or more environments, and twenty-five QTL clusters consisted of 114 QTLs. Moreover, we identified three candidate genes for three stable QTLs, including GH_A01G1096 (ARF5) and GH_A10G0141 (PDF2) for lint percentage, and GH_D01G0047 (KCS4) for seed index or oil content. These results pave way for understanding the molecular regulatory mechanism of fiber and seed development and would provide valuable information for marker-assisted genetic improvement in cotton.

Fine genetic mapping and transcriptomic analysis revealed major gene modulating the clear stripe margin pattern of watermelon peel.

The peel stripe margin pattern is one of the most important quality traits of watermelon. In this study, two contrasted watermelon lines [slb line (P1) with a clear peel stripe margin pattern and GWAS-38 line (P2) with a blurred peel stripe margin pattern] were crossed, and biparental F2 mapping populations were developed. Genetic segregation analysis revealed that a single recessive gene is modulating the main-effect genetic locus (Clcsm) of the clear stripe margin pattern of peel. Bulked segregant analysis-based sequencing (BSA-Seq) and fine genetic mapping exposed the delimited Clcsm locus to a 19.686-kb interval on chromosome 6, and the Cla97C06G126680 gene encoding the MYB transcription factor family was identified. The gene mutation analysis showed that two non-synonymous single-nucleotide polymorphism (nsSNP) sites [Chr6:28438793 (A-T) and Chr6:28438845 (A-C)] contribute to the clear peel stripe margin pattern, and quantitative real-time polymerase chain reaction (qRT-PCR) also showed a higher expression trend in the slb line than in the GWAS-38 line. Further, comparative transcriptomic analysis identified major differentially expressed genes (DEGs) in three developmental periods [4, 12, and 20 days after pollination (DAP)] of both parental lines. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses indicated highly enriched DEGs involved in metabolic processes and catalytic activity. A total of 44 transcription factor families and candidate genes belonging to the ARR-B transcription factor family are believed to regulate the clear stripe margin trait of watermelon peel. The gene structure, sequence polymorphism, and expression trends depicted significant differences in the peel stripe margin pattern of both parental lines. The ClMYB36 gene showed a higher expression trend for regulating the clear peel stripe margin of the slb line, and the ClAPRR5 gene depicted a higher expression for modulating the blurred peel stripe margin in the GWAS-38 line. Overall, our fine genetic mapping and transcriptomic analysis revealed candidate genes differentiating the clear and blurred peel stripe patterns of watermelon fruit.

Genetic mapping and molecular marker development for white flesh color in tomato.

Fruit color significantly influences the quality of horticultural crops, which affects phytochemical diversity and consumer preferences. Despite its importance, the genetic basis of the white-colored fruit in tomatoes remains poorly understood. In this study, we demonstrate that white-fleshed tomato varieties accumulate fewer carotenoids than yellow-fleshed varieties. We developed various segregating populations by hybridizing red, yellow, and white fruit tomato cultivars. Genetic analysis revealed that the white fruit color trait is controlled by a single gene that dominates both red and yellow fruits. Bulk segregant RNA sequencing provided a preliminary map of a 3.17 Mb region on chromosome 3 associated with the white color trait. Based on kompetitive allele-specific PCR (KASP) markers, we narrowed the candidate gene region to 819 kb. Within this region, we identified a 4906-bp sequence absence variation near Phytoene Synthase 1 (SlPSY1) specific to white-colored tomatoes. Genotyping of the progeny and natural populations using a single nucleotide polymorphism adjacent to this absence of variation confirmed its key role in white fruit formation. Collectively, our findings provide insights into white fruit trait formation in tomatoes, enabling tomato breeders to precisely introduce white fruit traits for commercial exploitation.

Recombination fraction in pre-recombinant inbred lines (PRERIL) - revisiting a century old problem in genetics

BackgroundTraditional recombinant inbred lines (RILs) are generated from repeated self-fertilization or brother-sister mating from the F1 hybrid of two inbred parents. Compared with the F2 population, RILs cumulate more crossovers between loci and thus increase the number of recombinants, resulting in an increased resolution of genetic mapping. Since they are inbred to the isogenic stage, another consequence of the heterozygosity reduction is the increased genetic variance and thus the increased power of QTL detection. Self-fertilization is the primary form of developing RILs in plants. Brother-sister mating is another way to develop RILs but in small laboratory animals. To ensure that the RILs have at least 98% of homozygosity, we need about seven generations of self-fertilization or 20 generations of brother-sister mating. Prior to homozygosity, these lines are called pre-recombinant inbred lines (PRERIL). Phenotypic values of traits in PRERILs are often collected but not used in QTL mapping. To perform QTL mapping in PRERILs, we need the recombination fraction between two markers at generation t for t < 7 (selfing) or t < 20 (brother-sister mating) so that the genotypes of QTL flanked by the markers can be inferred.ResultsIn this study, we developed formulas to calculate the recombination fractions of PRERILs at generation t in self-fertilization, brother-sister mating, and random mating. In contrast to existing works in this topic, we used computer code to construct the transition matrix to form the Markov chain of genotype array between consecutive generations, the so-called recurrent equations.ConclusionsWe provide R functions to calculate the recombination fraction using the newly developed recurrent equations of ordered genotype array. With the recurrent equations and the R code, users can perform QTL mapping in PRERILs. Substantial time and effort can be saved compared with QTL mapping in RILs.

QTL mapping for branch- and leaf-related traits with a high-density SNP genetic map in litchi (Litchi chinensis Sonn.)

Litchi (Litchi chinensis Sonn.), an important fruit tree in tropical and subtropical regions, possesses substantial economic value. The branch- and leaf-related traits of litchi have a significant impact on litchi yield and quality. However, due to limitations such as the density of the genetic linkage map, there have been few studies on mapping QTLs of branch- and leaf-related traits. In this study, a high-density genetic map was constructed by next-generation sequencing (NGS) using an F1 population of 264 progenies, derived from the cross between the cultivars ‘Sanyuehong’ and ‘Ziniangxi’. A total of 2574 high-quality BINs (binomial intervals) were obtained, and a genetic linkage map was constructed with a total length of 1753.3 cM and an average marker distance of 0.68 cM. With the genetic map and the phenotyping of single leaf length (SLL), single leaf width (SLW), leaf shape index (LSI), weight of specific leaf (WSL), petiole length (PL) and compound leaf length (CLL) measured in three seasons, 11, 9, 9, 10, 9 and 12 QTLs were detected for SLL, SLW, WSL, LSI, PL and CLL traits, respectively. Among these QTLs, five QTLs were consistently detected in two seasons and 12 pleiotropic QTLs were identified for at least two traits. These findings will provide new insights for the gene cloning for branch- and leaf-related traits as well as marker-assisted selection (MAS).

Rmg10, a Novel Wheat Blast Resistance Gene Derived from Aegilops tauschii.

Wheat blast, caused by Pyricularia oryzae (syn. Magnaporthe oryzae) pathotype Triticum (MoT), is a devastating disease that can result in up to 100% yield loss in affected fields. To find new resistance genes against wheat blast, we screened 199 accessions of Aegilops tauschii, the D genome progenitor of common wheat (Triticum aestivum), by seedling inoculation assays with Brazilian MoT isolate Br48 and found 14 resistant accessions. A synthetic hexaploid wheat line (Ldn/KU-2097) derived from a cross between the T. turgidum 'Langdon' (Ldn) and resistant A. tauschii accession KU-2097 exhibited resistance in seedlings and spikes against Br48. In an F2 population derived from 'Chinese Spring' × Ldn/KU-2097, resistant and susceptible individuals segregated in a 3:1 ratio, suggesting that the resistance from KU-2097 is controlled by a single dominant gene. We designated this gene Rmg10. Genetic mapping using an F2:3 population from the same cross mapped the RMG10 locus to the short arm of chromosome 2D. Rmg10 was ineffective against Bangladesh isolates but effective against Brazilian isolates. Field tests in Bolivia showed increased spike resistance in a synthetic octaploid wheat line produced from a cross between common wheat cultivar 'Gladius' and KU-2097. These results suggest that Rmg10 would be beneficial in farmers' fields in South America.

Development and application of the GenoBaits WheatSNP16K array to accelerate wheat genetic research and breeding

Single-nucleotide polymorphisms (SNPs) are widely used as molecular markers for constructing genetic linkage maps in wheat. Compared with available SNP-based genotyping platforms, a genotyping by target sequencing (GBTS) system with capture-in-solution (liquid chip) technology has become the favored genotyping technology because it is less demanding and more cost effective, flexible, and user-friendly. In this study, a new GenoBaits WheatSNP16K (GBW16K) GBTS array was designed using datasets generated by the wheat 660K SNP array and resequencing platforms in our previous studies. The GBW16K array contains 14 868 target SNP regions that are evenly distributed across the wheat genome, and 37 669 SNPs in these regions can be identified in a diversity panel consisting of 239 wheat accessions from around the world. Principal component and neighbor-joining analyses using the called SNPs are consistent with the pedigree information and geographic distributions or ecological environments of the accessions. For the GBW16K marker panel, the average genetic diversity among the 239 accessions is 0.270, which is sufficient for linkage map construction and preliminary mapping of targeted genes or quantitative trait loci (QTLs). A genetic linkage map, constructed using the GBW16K array-based genotyping of a recombinant inbred line population derived from a cross of the CIMMYT wheat line Yaco“S” and the Chinese landrace Mingxian169, enables the identification of Yr27, Yr30, and QYr.nwafu-2BL.4 for adult-plant resistance to stripe rust from Yaco“S” and of Yr18 from Mingxian169. QYr.nwafu-2BL.4 is different from any previously reported gene/QTL. Three haplotypes and six candidate genes have been identified for QYr.nwafu-2BL.4 on the basis of haplotype analysis, micro-collinearity, gene annotation, RNA sequencing, and SNP data. This array provides a new tool for wheat genetic analysis and breeding studies and for achieving durable control of wheat stripe rust.

Inheritance and QTL mapping identified multi-effects loci for fatty acid related traits in peanut (Arachis hypogaea L.)

Peanut (Arachis hypogaea L.) is an important oil and edible protein crop. The fatty acid composition not only influences the quality of peanut oil but also impacts flavor, shelf life, and consumer health. Peanut oil comprises approximately 80% oleic acid (C18:1) and linoleic acid (C18:2), 10% palmitic acid (C16:0), and the remaining 10% includes stearic acid (C18:0), arachidic acid (C20:0), gadoleic acid (C20:1), behenic acid (C22:0), and lignoceric acid (C24:0). To unravel the genetic foundation of fatty acid content and delve into QTL localization, we utilized high-density SNP microarrays for genotyping the RIL population of ‘SunOleic 97R’ × ‘NC94022’. A genetic linkage map was constructed with 3141 SNP markers, covering a total genetic distance of 3051.81 cM. We identified 60 quantitative trait loci (QTLs) associated with fatty acids which distributed in 11 linkage group, with phenotypic variance explained (PVE) ranging from 1.37% to 44.92%. Notably, the QTL qFAT_A05.1 and qFAT_A08.1 are multiple-effect loci contributing to various fatty acid compositions. Moreover, we identified 15 haplotypes for the QTL qFAT_A05.1 and qFAT_A08.1 through genotyping 178 peanut germplasms. Haplotypes analysis in natural population confirmed the closely relationship of the QTLs with the content of oil, oleic acid, lignoceric acid, palmitic acid and behenic acid. This study serves as a valuable reference for selecting improved peanut genotypes with superior oil quality and desirable fatty acid composition.

86 - Genetic mapping of insulin sensitivity identifies alpha-defensin peptides as modulators of murine metabolic health

86 - Genetic mapping of insulin sensitivity identifies alpha-defensin peptides as modulators of murine metabolic health

QTL mapping of maize plant height based on a population of doubled haploid lines using UAV LiDAR high-throughput phenotyping data

Maize (Zea mays L.) is a globally significant crop that plays a crucial role in feeding the growing global population. Among its various traits, plant height is particularly important as it affects yield, lodging resistance, ecological adaptability, and other important factors. Traditional methods for measuring plant height often lack cost-efficiency and accuracy. In this study, we employed a light detection and ranging (LiDAR) sensor mounted on an unmanned aerial vehicle (UAV) to collect point cloud data from 270 doubled haploid (DH) lines. This innovative application of UAV-based LiDAR technology was explored for high-throughput phenotyping in maize breeding. We constructed high-density genetic maps and assessed plant height at both single-plant and row scales across multiple developmental stages and genetic backgrounds. Our findings revealed that for many varieties and small areas, single-plant-scale estimation accuracy was superior to row-scale estimation, with an R2 of 0.67 versus 0.56 and an RMSE of 0.12 m vs. 0.17 m, respectively. Two high-density genetic maps were constructed based on SNP markers. In Sanya and Xinxiang, the F1DH and F2DH populations identified 12 and 20 QTLs (quantitative trait loci) for plant height, respectively. The study successfully identified and validated QTLs associated with plant height, revealing novel genetic loci and candidate genes. This research highlights the potential of UAV-based remote sensing to advance precision agriculture by enabling efficient, large-scale phenotyping and gene discovery in maize breeding programs.

Characterization and Genetic Mapping of Resistance to Cotton–Melon Aphid (Aphis gossypii) in Cucumber

Characterization and Genetic Mapping of Resistance to Cotton–Melon Aphid (<scp><i>Aphis gossypii</i></scp>) in Cucumber

Linkage Mapping and Discovery of Candidate Genes for Drought Tolerance in Rice During the Vegetative Growth Period

Drought is a major abiotic stress affecting crop yields. Mapping quantitative trait loci (QTLs) and mining genes for drought tolerance in rice are important for identifying gene functions and targets for molecular breeding. Here, we performed linkage analysis of drought tolerance using a recombinant inbred line population derived from Jileng 1 (drought sensitive) and Milyang 23 (drought tolerant). An ultra-high-density genetic map, previously constructed by our research team using genotype data from whole-genome sequencing, was used in combination with phenotypic data for rice grown under drought stress conditions in the field in 2017–2019. Thirty-nine QTLs related to leaf rolling index and leaf withering degree were identified, and QTLs were found on all chromosomes except chromosomes 6, 10, and 11. qLWD4-1 was detected after 32 days and 46 days of drought stress in 2017 and explained 7.07–8.19% of the phenotypic variation. Two loci, qLRI2-2 and qLWD4-2, were identified after 29, 42, and 57 days of drought stress in 2018. These loci explained 10.59–17.04% and 5.14–5.71% of the phenotypic variation, respectively. There were 281 genes within the QTL interval. Through gene functional annotation and expression analysis, two candidate genes, Os04g0574600 and OsCHR731, were found. Quantitative reverse transcription PCR analysis showed that the expression levels of these genes were significantly higher under drought stress than under normal conditions, indicating positive regulation. Notably, Os04g0574600 was a newly discovered drought tolerance gene. Haplotype analysis showed that the RIL population carried two haplotypes (Hap1 and Hap2) of both genes. Lines carrying Hap2 exhibited significantly or extremely stronger drought tolerance than those carrying Hap1, indicating that Hap2 is an excellent haplotype. Among rice germplasm resources, there were two and three haplotypes of Os04g0574600 and OsCHR731, respectively. A high proportion of local rice resources in Sichuan, Yunnan, Anhui, Guangdong and Fujian provinces had Hap of both genes. In wild rice, 50% of accessions contained Hap1 of Os04g0574600 and 50% carried Hap4; 13.51%, 59.46% and 27.03% of wild rice accessions contained Hap1, Hap2, and Hap3, respectively. Hap2 of Os04g0574600 was found in more indica rice resources than in japonica rice. Therefore, Hap2 has more potential for utilization in future drought tolerance breeding of japonica rice.

HASCH - A high-throughput amplicon-based SNP-platform for medicinal cannabis and industrial hemp genotyping applications

BackgroundCannabis sativa is seeing a global resurgence as a food, fiber and medicinal crop for industrial hemp and medicinal Cannabis industries respectively. However, a widespread moratorium on the use and research of C. sativa throughout most of the 20th century has seen the development of improved cultivars for specific end uses lag behind that of conventional crops. While C. sativa research and development has seen significant investments in the recent past, resulting in a suite of publicly available genomic resources and tools, a versatile and cost-effective mid-density genotyping platform for applied purposes in breeding and pre-breeding is lacking. Here we report on a first mid-density fixed-target SNP platform for C. sativa.ResultsThe High-throughput Amplicon-based SNP-platform for medicinal Cannabis and industrial Hemp (HASCH) was designed using a combination of filtering and Integer Linear Programming on publicly available whole-genome sequencing and RNA sequencing data, supplemented with in-house generated genotyping-by-sequencing (GBS) data. HASCH contains 1,504 genome-wide targets of high call rate (97% mean) and even distribution across the genome, designed to be highly informative (> 0.3 minor allele frequency) across both medicinal cannabis and industrial hemp gene pools. Average numbers of mismatch SNP between any two accessions were 251 for medicinal cannabis (N = 116) and 272 for industrial hemp (N = 87). Comparing HASCH data with corresponding GBS data on a collection of diverse C. sativa accessions demonstrated high concordance and resulted in comparable phylogenies and genetic distance matrices. Using HASCH on a segregating F2 population derived from a cross between a tetrahydrocannabinol (THC)-dominant and a cannabidiol (CBD)-dominant accession resulted in a genetic map consisting of 310 markers, comprising 10 linkage groups and a total size of 582.7 cM. Quantitative Trait Locus (QTL) mapping identified a major QTL for CBD content on chromosome 7, consistent with previous findings.ConclusionHASCH constitutes a versatile, easy to use and cost-effective genotyping solution for the rapidly growing Cannabis research community. It provides consistent genetic fingerprints of 1504 SNPs with wide applicability genetic resource management, quantitative genetics and breeding.

Improving complex agronomic and domestication traits in the perennial grain crop intermediate wheatgrass with genetic mapping and genomic prediction.

The perennial grass Thinopyrum intermedium (intermediate wheatgrass [IWG]) is being domesticated as a food crop. With a deep root system and high biomass, IWG can help reduce soil and water erosion and limit nutrient runoff. As a novel grain crop undergoing domestication, IWG lags in yield, seed size, and other agronomic traits compared to annual grains. Better characterization of trait variation and identification of genetic markers associated with loci controlling the traits could help in further improving this crop. The University of Minnesota's Cycle 5 IWG breeding population of 595 spaced plants was evaluated at two locations in 2021 and 2022 for agronomic traits plant height, grain yield, and spike weight, and domestication traits shatter resistance, free grain threshing, and seed size. Pairwise trait correlations were weak to moderate with the highest correlation observed between seed size and height (0.41). Broad-sense trait heritabilities were high (0.68-0.77) except for spike weight (0.49) and yield (0.44). Association mapping using 24,284 genome-wide single nucleotide polymorphism markers identified 30 main quantitative trait loci (QTLs) across all environments and 32 QTL-by-environment interactions (QTE) at each environment. The genomic prediction model significantly improved predictions when parents were used in the training set and significant QTLs and QTEs used as covariates. Seed size was the best predicted trait with model predictive ability (r) of 0.72; yield was predicted moderately well (r=0.45). We expect this discovery of significant genomic loci and mostly high trait predictions from genomic prediction models to help improve future IWG breeding populations.

Prediction of additive genetic variances of descendants for complex families based on Mendelian sampling variances.

The ability to predict the outcome of selection and mating decisions enables breeders to make strategically better selection decisions. To improve genetic progress, those individuals need to be selected whose offspring can be expected to show high genetic variance next to high breeding values. Previously published approaches enable to predict the variance of descendants of two future generations for up to 4 founding haplotypes, or 2 outbred individuals, based on phased genotypes, allele effects and recombination frequencies. The purpose of this study was to develop a general approach for the analytical calculation of the genetic variance in any future generation. The core development is an equation for the prediction of the variance of double haploid lines, under the assumption of no selection and negligible drift, stemming from an arbitrary number of founder haplotypes. This double haploid variance can be decomposed into gametic Mendelian sampling variances (MSV) of ancestors of the double haploid lines allowing usage for non-double haploid genotypes which enables application in animal breeding programs as well as in plant breeding programs. Together with the breeding values of the founders, the gametic MSV may be used in new selection criteria. We present our idea of such a criterion that describes the genetic level of selected individuals in four generations. Since breeding programs do select, the assumption made for predicting variances is clearly violated which decreases the accuracy of predicted gametic MSV caused by changes in allele frequency and linkage disequilibrium. Despite violating the assumption, we found high predictive correlations of our criterion to the true genetic level which was obtained by means of simulation for the "corn" and "cattle" genome models tested in this study (0.90 and 0.97). In practice, the genotype phases, genetic map and allele effects all need to be estimated meaning inaccuracies in their estimation will lead to inaccurate variance prediction. Investigation of variance prediction accuracy when input parameters are estimated was not part of this study.

Multiple Localization Analysis of the Major QTL-sfw 2.2 for Controlling Single Fruit Weight Traits in Melon Based on SLAF Sequencing.

Cucumis melo is an annual dicotyledonous trailing herb. It is fruity, cool, and refreshing to eat and is widely loved by consumers worldwide. The single fruit weight is an important factor affecting the yield, and thus the income and economic benefits, of melon crops. In this study, to identify the main QTLs (quantitative trait locus) controlling the single fruit weight of melon and thereby identify candidate genes controlling this trait, specific-locus amplified fragment sequencing (SLAF) analysis was performed on the offspring of female 1244 plants crossed with male MS-5 plants. A total of 115 individual plants in the melon F2 population were analyzed to construct a genetic linkage map with a total map distance of 1383.88 cM by the group in the early stages of the project, which was divided into 12 linkage groups with a total of 10,596 SLAF markers spaced at an average genetic distance of 0.13 cM. A total of six QTLs controlling single fruit weight (sfw loci) were detected. Seven pairs of markers with polymorphisms were obtained by screening candidate intervals from the SLAF data. The primary QTL sfw2.2 was further studied in 300 F2:3 family lines grown in 2020 and 2021, respectively, a positioning sfw2.2 between the markers CY Indel 11 and CY Indel 16, between 18,568,142 and 18,704,724 on chromosome 2. This interval contained 136.58 kb and included three genes with functional annotations, MELO3C029673, MELO3C029669, and MELO3C029674. Gene expression information for different fruit development stages was obtained from 1244 and MS-5 fruits on the 15d, 25d, and 35d after pollination, and qRT-PCR (quantitative reverse transcription-PCR) indicated that the expression of the MELO3C029669 gene significantly differed between the parents during the three periods. The gene sequences between the parents of MELO3C029669 were analyzed and compared, a base mutation was found to occur in the intronic interval between the parents of the gene, from A-G. Phylogenetic evolutionary tree analysis revealed that the candidate gene MELO3C029669 is most closely related to Pisum sativum Fimbrin-5 variant 2 and most distantly related to Cucumis melo var. makuwa. Therefore, it was hypothesized that MELO3C029669 is the primary major locus controlling single fruit weight in melon. These results not only provide a theoretical basis for further studies to find genes with functions in melon single fruit weight but also lay the foundation for accelerating breakthroughs and innovations in melon breeding.

Independent genetic factors control floret number and spikelet number in Triticum turgidum ssp.

Wheat grain yield is a complex trait resulting from a trade-off among many distinct components. During wheat evolution, domestication events and then modern breeding have strongly increased the yield potential of wheat plants, by enhancing spike fertility. To address the genetic bases of spike fertility in terms of spikelet number per spike and floret number per spikelet, a population of 110 recombinant inbred lines (RILS) obtained crossing a Triticum turgidum ssp. durum cultivar (Latino) and a T. dicoccum accession (MG5323) was exploited. Being a modern durum and a semi-domesticated genotype, respectively, the two parents differ for spike architecture and fertility, and thus the corresponding RIL population is the ideal genetic material to dissect genetic bases of yield components. The RIL population was phenotyped in four environments. Using a high-density SNP genetic map and taking advantage of several genome sequencing available for Triticeae, a total of 94 QTLs were identified for the eight traits considered; these QTLs were further reduced to 17 groups, based on their genetic and physical co-location. QTLs controlling floret number per spikelet and spikelet number per spike mapped in non-overlapping chromosomal regions, suggesting that independent genetic factors determine these fertility-related traits. The physical intervals of QTL groups were considered for possible co-location with known genes functionally involved in spike fertility traits and with yield-related QTLs previously mapped in tetraploid wheat. The most interesting result concerns a QTL group on chromosome 5B, associated with spikelet number per spike, since it could host genes still uncharacterized for their association to spike fertility. Finally, we identified two different regions where the trade-off between fertility related traits and kernel weight is overcome. Further analyses of these regions could pave the way for a future identification of new genetic loci contributing to fertility traits essential for yield improvement in durum wheat.

Identification and Mapping of QTLs for Adult Plant Resistance in Wheat Line XK502.

Stripe rust is a serious wheat disease occurring worldwide. At present, the most effective way to control it is to grow resistant cultivars. In this study, a population of 221 recombinant inbred lines (RILs) derived via single-seed descent from a hybrid of a susceptible wheat line, SY95-71, and a resistant line, XK502, was tested in three crop seasons from 2022 to 2024 in five environments. A genetic linkage map was constructed using 12,577 single-nucleotide polymorphisms (SNPs). Based on the phenotypic data of infection severity and the linkage map, five quantitative trait loci (QTL) for adult plant resistance (APR) were detected using the inclusive composite interval mapping (ICIM) method. These five loci are QYrxk502.swust-1BL, QYrxk502.swust-2BL, QYrxk502.swust-3AS, QYrxk502.swust-3BS, and QYrxk502.swust-7BS, explaining 5.67-19.64%, 9.63-36.74%, 9.58-11.30%, 9.76-23.98%, and 8.02-12.41% of the phenotypic variation, respectively. All these QTL originated from the resistant parent XK502. By comparison with the locations of known stripe rust resistance genes, three of the detected QTL, QYrxk502.swust-3AS, QYrxk502.swust-3BS, and QYrxk502.swust-7BS, may harbor new, unidentified genes. From among the tested RILs, 16 lines were selected with good field stripe rust resistance and acceptable agronomic traits for inclusion in breeding programs.