Molecular Linkage Map Research Articles

Genetic Loci Mining and Candidate Gene Analysis for Determining Fatty Acid Composition in Rice

Fatty acid composition and its proportions are critical to the nutritional value and storage quality of rice (Oryza sativa L.) as the third major nutrient component in this staple food. This study involved crossing an indica rice variety, Huazhan (HZ), as the male parent, with a japonica variety, Nekken2, as the female parent, to produce the F1 generation. Subsequently, a population of 120 recombinant inbred lines (RILs) was developed through multiple generations of self-breeding. By utilizing a high-density molecular genetic linkage map and phenotypic data of four fatty acid components, we identified a total of 14 quantitative trait loci (QTLs) related to fatty acid composition across chromosomes 1, 3, 4, 6, 8, and 9. These included two QTLs for C14 content, three for C16:0 content, six for C18:1 content, and three for C18:2 content. Notably, the QTL qCOPT4.2 exhibited a high LOD score of 5.22. Within QTL intervals, genes such as OsACX3 and SLG affecting grain length were identified. The expression of candidate genes within these intervals was assessed and further analyzed by using quantitative real-time PCR. Genes such as LOC_Os01g15000, LOC_Os04g47120, LOC_Os04g49194, LOC_Os06g22080, LOC_Os06g23870, LOC_Os06g24704, LOC_Os06g30780, LOC_Os08g44840, and LOC_Os09g36860 were found to regulate fatty acid synthesis or metabolic pathways, potentially enhancing fatty acid content in rice. These QTLs are indispensable for breeding rice varieties with improved fatty acid profiles, offering new genetic resources for enhancing the nutritional and storage qualities of rice.

Construction of Genetic Map and QTL Mapping for Seed Size and Quality Traits in Soybean (Glycine max L.).

Soybean (Glycine max L.) is the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean yield and quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) mapping for yield and quality traits, as well as for the identification of mining-related candidate genes, is of great significance for the molecular breeding and understanding the genetic mechanism. In this study, 186 individual plants of the F2 generation derived from crosses between Changjiangchun 2 and Yushuxian 2 were selected as the mapping population to construct a molecular genetic linkage map. A genetic map containing 445 SSR markers with an average distance of 5.3 cM and a total length of 2375.6 cM was obtained. Based on constructed genetic map, 11 traits including hundred-seed weight (HSW), seed length (SL), seed width (SW), seed length-to-width ratio (SLW), oil content (OIL), protein content (PRO), oleic acid (OA), linoleic acid (LA), linolenic acid (LNA), palmitic acid (PA), stearic acid (SA) of yield and quality were detected by the multiple- d size traits and 113 QTLs related to quality were detected by the multiple QTL model (MQM) mapping method across generations F2, F2:3, F2:4, and F2:5. A total of 71 QTLs related to seed size traits and 113 QTLs related to quality traits were obtained in four generations. With those QTLs, 19 clusters for seed size traits and 20 QTL clusters for quality traits were summarized. Two promising clusters, one related to seed size traits and the other to quality traits, have been identified. The cluster associated with seed size traits spans from position 27876712 to 29009783 on Chromosome 16, while the cluster linked to quality traits spans from position 12575403 to 13875138 on Chromosome 6. Within these intervals, a reference genome of William82 was used for gene searching. A total of 36 candidate genes that may be involved in the regulation of soybean seed size and quality were screened by gene functional annotation and GO enrichment analysis. The results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean.

Construction of a genetic map and QTL mapping of seed size traits in soybean.

Soybean seed size and seed shape traits are closely related to plant yield and appearance quality. In this study, 186 individual plants of the F2 generation derived from crosses between Changjiang Chun 2 and JiYu 166 were selected as the mapping population to construct a molecular genetic linkage map, and the phenotypic data of hundred-grain weight, seed length, seed width, and seed length-to-width ratio of soybean under three generations of F2 single plants and F2:3 and F2:4 lines were combined to detect the QTL (quantitative trait loci) for the corresponding traits by ICIM mapping. A soybean genetic map containing 455 markers with an average distance of 6.15cM and a total length of 2799.2cM was obtained. Forty-nine QTLs related to the hundred-grain weight, seed length, seed width, and seed length-to-width ratio of soybean were obtained under three environmental conditions. A total of 10 QTLs were detected in more than two environments with a phenotypic variation of over 10%. Twelve QTL clusters were identified on chromosomes 1, 2, 5, 6, 8, 13, 18, and 19, with the majority of the overlapping intervals for hundred-grain weight and seed width. These results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean seed weight and seed shape. Eighteen candidate genes that may be involved in the regulation of soybean seed size were screened by gene functional annotation and GO enrichment analysis.

A physical map of traits of agronomic importance based on potato and tomato genome sequences.

Potato, tomato, pepper, and eggplant are worldwide important crop and vegetable species of the Solanaceae family. Molecular linkage maps of these plants have been constructed and used to map qualitative and quantitative traits of agronomic importance. This research has been undertaken with the vision to identify the molecular basis of agronomic characters on the one hand, and on the other hand, to assist the selection of improved varieties in breeding programs by providing DNA-based markers that are diagnostic for specific agronomic characters. Since 2011, whole genome sequences of tomato and potato became available in public databases. They were used to combine the results of several hundred mapping and map-based cloning studies of phenotypic characters between 1988 and 2022 in physical maps of the twelve tomato and potato chromosomes. The traits evaluated were qualitative and quantitative resistance to pathogenic oomycetes, fungi, bacteria, viruses, nematodes, and insects. Furthermore, quantitative trait loci for yield and sugar content of tomato fruits and potato tubers and maturity or earliness were physically mapped. Cloned genes for pathogen resistance, a few genes underlying quantitative trait loci for yield, sugar content, and maturity, and several hundred candidate genes for these traits were included in the physical maps. The comparison between the physical chromosome maps revealed, in addition to known intrachromosomal inversions, several additional inversions and translocations between the otherwise highly collinear tomato and potato genomes. The integration of the positional information from independent mapping studies revealed the colocalization of qualitative and quantitative loci for resistance to different types of pathogens, called resistance hotspots, suggesting a similar molecular basis. Synteny between potato and tomato with respect to genomic positions of quantitative trait loci was frequently observed, indicating eventual similarity between the underlying genes.

Construction of a High-Density Genetic Linkage Map Based on Bin Markers and Mapping of QTLs Associated with Fruit Size in Jujube (Ziziphus jujuba Mill.)

Jujube (Ziziphus jujuba Mill.) is a fruit tree that is gaining increasing importance in drought-affected regions worldwide. The fruit size is an important quantitative agronomic trait that affects not only the fruit yield and attractiveness but also consumer preference. Genetic enhancement of fruit appearance is a fundamental goal of jujube breeding programs. The genetic control of jujube fruit size traits is highly quantitative, and development of high-density genetic maps can facilitate fine mapping of quantitative trait loci (QTLs) and gene identification. However, studies regarding the construction of high-density molecular linkage maps and identification of quantitative trait loci (QTLs) targeting fruit size in jujube are limited. In this study, we performed whole-genome resequencing of the jujube cultivars “JMS2” and “Xing16” and their 165 F1 progenies to identify genome-wide single-nucleotide polymorphism (SNP) markers and constructed a high-density bin map of jujube that can be used to assist in the selection of multiple traits in jujube breeding. This analysis yielded a total of 116,312 SNPs and a genetic bin map of 2398 bin markers spanning 1074.33 cM with an average adjacent interval of 0.45 cM. A quantitative genetic analysis identified 15 QTLs related to fruit size and the observed phenotypic variation associated with a single QTL ranged from 9.5 to 13.3%. Through the screening of overlapping and stable QTL regions, we identified 113 candidate genes related to fruit size. These genes were ascertained to be involved in cell division, cell wall metabolism, synthesis of phytohormones (ABA, IAA, and auxin), and encoding of enzymes and transcription factors. These candidate genomic regions will facilitate marker-assisted breeding of fruits with different sizes and shapes and lay a foundation for future breeding and manipulation of fruit size and shape in jujube.

Omics technologies towards sesame improvement: a review.

Genetic improvement of sesame (Sesamum indicum L.), one of the most important oilseed crops providing edible oil, proteins, minerals, and vitamins, is important to ensure a balanced diet for the growing world population. Increasing yield, seed protein, oil, minerals, and vitamins is urgently needed to meet the global demand. The production and productivity of sesame is very low due to various biotic and abiotic stresses. Therefore, various efforts have been made to combat these constraints and increase the production and productivity of sesame through conventional breeding. However, less attention has been paid to the genetic improvement of the crop through modern biotechnological methods, leaving it lagging behind other oilseed crops. Recently, however, the scenario has changed as sesame research has entered the era of "omics" and has made significant progress. Therefore, the purpose of this paper is to provide an overview of the progress made by omics research in improving sesame. This review presents a number of efforts that have been made over past decade using omics technologies to improve various traits of sesame, including seed composition, yield, and biotic and abiotic resistant varieties. It summarizes the advances in genetic improvement of sesame using omics technologies, such as germplasm development (web-based functional databases and germplasm resources), gene discovery (molecular markers and genetic linkage map construction), proteomics, transcriptomics, and metabolomics that have been carried out in the last decade. In conclusion, this review highlights future directions that may be important for omics-assisted breeding in sesame genetic improvement.

Genetic analysis and QTL mapping of aroma volatile compounds in the apple progeny 'Fuji' × 'Cripps Pink'.

Aroma is an essential trait for apple fruit quality, but the understanding of biochemical mechanisms underlying aroma formation is still limited. To better characterize and assess the genetic potential for improving aroma quality for breeding, many efforts have been paid to map quantitative trait loci (QTLs) using a saturated molecular linkage map. In the present study, aroma profiles in ripe fruit of F1 population between 'Fuji' and 'Cripps Pink' were evaluated by gas chromatography-mass spectrometry (GC-MS) over 2019 and 2020 years, and the genetics of volatile compounds were dissected. In total, 38 volatile compounds were identified in 'Fuji' × 'Cripps Pink' population, including 23 esters, 3 alcohols, 7 aldehydes and 5 others. With the combination of aroma phenotypic data and constructed genetic linkage map, 87 QTLs were detected for 15 volatile compounds on 14 linkage groups (LGs). Among them, a set of QTLs associated with ester production identified and confirmed on LG 6. A candidate gene MdAAT6 in the QTL mapping interval was detected. Over-expression of MdAAT6 in tomato and apple fruits showed significantly higher esters accumulation compared to the control, indicating it was critical for the ester production. Our results give light on the mode of inheritance of the apple volatilome and provide new insights for apple flavor improvement in the future.

Map-based cloning and functional analysis revealed ABCC2 is responsible for Cry1Ac toxin resistance in Bombyx mori.

Bt toxins are parasporal crystals produced by Bacillus thuringiensis (Bt).They have specific killing activity against various insects and have been widely used to control agricultural pests. However, their widespread use has developed the resistance of many target insects. To maintain the sustainable use of Bt products, the resistance mechanism of insects to Bt toxins must be fully clarified. In this study, Bt-resistant and Bt-susceptible silkworm strains were used to construct genetic populations, and the genetic pattern of silkworm resistance to Cry1Ac toxin was determined. Sequence-tagged sitemolecular marker technology was used to finely map the resistance gene and to draw a molecular genetic linkage map, and the two closest markers were T1590 and T1581, indicating the resistance gene located in the 155 kb genetic region. After analyzing the sequence of the predicted gene in the genetic region, an ATP binding cassette transporter (ABCC2) was identified as the candidate gene. Molecular modeling and protein-protein docking result showed that a tyrosine insertion in the mutant ABCC2 might be responsible for the interaction between Cry1Ac and ABCC2. Moreover, CRISPR/Cas9-mediated genome editing technology was used to knockout ABCC2 gene. The homozygous mutant ABCC2 silkworm was resistant to Cry1Ac toxin, which indicated ABCC2 is the key gene that controls silkworm resistance to Cry1Ac toxin. The results have laid the foundation for elucidating the molecular resistance mechanism of silkworms to Cry1Ac toxin and could provide a theoretical basis for the biological control of lepidopteran pests.

The First Genetic Linkage Map of Winged Bean [Psophocarpus tetragonolobus (L.) DC.] and QTL Mapping for Flower-, Pod-, and Seed-Related Traits.

Winged bean [Psophocarpus tetragonolobus (L.) DC.] (2n = 2× = 18) is a tropical legume crop with multipurpose usages. Recently, the winged bean has regained attention from scientists as a food protein source. Currently, there is no breeding program for winged bean cultivars. All winged bean cultivars are landraces or selections from landraces. Molecular markers and genetic linkage maps are pre-requisites for molecular plant breeding. The aim of this study was to develop a high-density linkage map and identify quantitative trait loci (QTLs) for pod and seed-related traits of the winged bean. An F2 population of 86 plants was developed from a cross between winged bean accessions W054 and TPT9 showing contrasting pod length, and pod, flower and seed colors. A genetic linkage map of 1384 single nucleotide polymorphism (SNP) markers generated from restriction site-associated DNA sequencing was constructed. The map resolved nine haploid chromosomes of the winged bean and spanned the cumulative length of 4552.8 cM with the number of SNPs per linkage ranging from 36 to 218 with an average of 153.78. QTL analysis in the F2 population revealed 31 QTLs controlling pod length, pod color, pod anthocyanin content, flower color, and seed color. The number of QTLs per trait varied between 1 (seed length) to 7 (banner color). Interestingly, the major QTLs for pod color, anthocyanin content, and calyx color, and for seed color and flower wing color were located at the same position. The high-density linkage map QTLs reported in this study will be useful for molecular breeding of winged beans.

Drug repositioning to combat COVID-19 using artificial intelligence system

Although months have passed since WHO declared COVID-19 a global pandemic, only a limited number of clinically effective drugs are available, and the development of drugs to treat COVID-19 has become an urgent issue worldwide. The pace of new research on COVID-19 is extremely high and it is impossible to read every report. In order to tackle these problems, we leveraged our artificial intelligence (AI) system, Concept Encoder, to accelerate the process of drug repositioning. Concept Encoder is a patented AI system based on natural language processing technology and by deeply learning papers on COVID-19, the system identified a large group of genes implicated in COVID-19 pathogenesis. The AI system then generated a molecular linkage map for COVID-19, connecting the genes by learning the molecular relationship comprehensively. By thoroughly reviewing the resulting map and list of the genes with rankings, we found potential key players for disease progression and existing drugs that might improve COVID-19 survival. Here, we focus on potential targets and discuss the perspective of our approach.

Quantitative trait locus mapping of five significant quality traits such as crude protein content of tetraploid hybrid crested wheatgrass in multiple environments

AbstractAgropyron is an important germplasm material of the genetic improvement for Gramineae forage and Triticeae crops. In the present research, in order to determine the stable and major quantitative trait loci (QTLs) controlling five significant quality traits, a total of 115 individuals from F2 segregation population of tetraploid hybrid crested wheatgrass and their parents were used as materials. On the basis of the ultra‐high density molecular genetic linkage map of tetraploid crested wheatgrass constructed with single nucleotide polymorphism (SNP) markers, we first determined QTLs for the phenotypic data of five quality traits in three different environments (Hohhot‐2018, Hohhot‐2019 and Tongliao‐2019) in 2 years (2018 and 2019) by Map QTL 6.0 software. The results showed that a total of 28 QTLs controlling quality traits of wheatgrass were located on 11 linkages (LGs), including LG1, LG2, LG3, LG4, LG6, LG7, LG8, LG9, LG12, LG13 and LG14. Among them, there were two QTLs for crude protein content (CPC), four QTLs for water‐soluble carbohydrate content (WSCC), 12 QTLs for starch content (SC), five QTLs for phosphorus content (PC) and five QTLs for calcium content (CC), which accounted for 10.1% to 21.6% of the phenotypic variation and all were major QTLs of genetic contribution rate >10%. However, only six stable QTLs were detected at least in two environments and in the mean environment data, including one for CPC (qCpc4‐1), one for WSCC (qWscc4‐2), two for SC (qSc1‐2, qSc9‐12), one for PC (qPc4‐4) and one for CC (qCc4‐2). These QTLs determining five traits would provide a theoretical basis for further fine mapping and the molecular marker‐assisted selection of elite gene in tetraploid crested wheatgrass.

Genomics and Marker-Assisted Improvement of Vegetable Crops

Vegetables are an integral part of the human diet worldwide. Traditional breeding approaches have been used extensively to develop new cultivars of vegetables with desirable characteristics, including resistance/tolerance to biotic and abiotic stresses, high yield, and an elevated content of compounds beneficial to human health. The technological progress since the early 1980s has revolutionized our ability to study and manipulate genetic variation in crop plants. The development of high-throughput sequencing platforms and accompanying analytical methods have led to sequencing and assembly of a large number of plant genomes, construction of dense and ultra-dense molecular linkage maps, identification of structural variants, and application of molecular markers in breeding programs. Linkage mapping and genome-wide association mapping studies have been used to identify chromosomal locations of genes and QTLs associated with plant phenotypic variations important for crop improvement. This review provides up-to-date information on the status of genomics and marker-assisted improvement of vegetable crops with the focus on tomato, pepper, eggplant, lettuce, spinach, cucumber, and chicory. For each vegetable crop, we present the most recent information on genetic resources, mapping populations, genetic maps, genome sequences, mapped genes and QTLs, the status of marker-assisted selection and genomic selection, and discuss future research prospects and application of novel techniques and approaches.

Multi-Environment Quantitative Trait Loci Mapping for Grain Iron and Zinc Content Using Bi-parental Recombinant Inbred Line Mapping Population in Pearl Millet.

Pearl millet is a climate-resilient, nutritious crop with low input requirements that could provide economic returns in marginal agro-ecologies. In this study, we report quantitative trait loci (QTLs) for iron (Fe) and zinc (Zn) content from three distinct production environments. We generated a genetic linkage map using 210 F6 recombinant inbred line (RIL) population derived from the (PPMI 683 × PPMI 627) cross using genome-wide simple sequence repeats (SSRs). The molecular linkage map (seven linkage groups) of 151 loci was 3,273.1 cM length (Kosambi). The content of grain Fe in the RIL population ranged between 36 and 114 mg/Kg, and that of Zn from 20 to 106 mg/Kg across the 3 years (2014–2016) at over the three locations (Delhi, Dharwad, and Jodhpur). QTL analysis revealed a total of 22 QTLs for grain Fe and Zn, of which 14 were for Fe and eight were for Zn on three consecutive years at all locations. The observed phenotypic variance (R2) explained by different QTLs for grain Fe and Zn content ranged from 2.85 (QGFe.E3.2014–2016_Q3) to 19.66% (QGFe.E1.2014–2016_Q3) and from 2.93 (QGZn.E3.2014–2016_Q3) to 25. 95% (QGZn.E1.2014–2016_Q1), respectively. Two constitutive expressing QTLs for both Fe and Zn co-mapped in this population, one on LG 2 and second one on LG 3. Inside the QTLs candidate genes such as Ferritin gene, Al3+ Transporter, K+ Transporters, Zn2+ transporters and Mg2+ transporters were identified using bioinformatics approaches. The identified QTLs and candidate genes could be useful in pearl millet population improvement programs, seed, restorer parents, and marker-assisted selection programs.

Mapping of QTLs controlling epicotyl length in adzuki bean (Vigna angularis).

Epicotyl length (ECL) of adzuki bean (Vigna angularis) affects the efficiency of mechanized weeding and harvest. The present study investigated the genetic factors controlling ECL. An F2 population derived from a cross between the breeding line ‘Tokei1121’ (T1121, long epicotyls) and the cultivar ‘Erimo167’ (common epicotyls) was phenotyped for ECL and genotyped using simple sequence repeats (SSRs) and single-nucleotide polymorphism (SNP) markers. A molecular linkage map was generated and fifty-two segregating markers, including 27 SSRs and 25 SNPs, were located on seven linkage groups (LGs) at a LOD threshold value of 3.0. Four quantitative trait loci (QTLs) for ECL, with LOD scores of 4.0, 3.4, 4.8 and 6.4, were identified on LGs 2, 4, 7 and 10, respectively; together, these four QTLs accounted for 49.3% of the phenotypic variance. The segregation patterns observed in F5 residual heterozygous lines at qECL10 revealed that a single recessive gene derived from T1121 contributed to the longer ECL phenotype. Using five insertion and deletion markers, this gene was fine mapped to a ~255 kb region near the end of LG10. These findings will facilitate marker-assisted selection for breeding in the adzuki bean and contribute to an understanding of the mechanisms associated with epicotyl elongation.

Drug repositioning to combat COVID-19 using artificial intelligence system

Although months have passed since WHO declared COVID-19 a global pandemic, only a limited number of clinically effective drugs are available, and the development of drugs to treat COVID-19 has become an urgent issue worldwide. The pace of new research on COVID-19 is extremely high and it is impossible to read every report. In order to tackle these problems, we leveraged our artificial intelligence (AI) system, Concept Encoder, to accelerate the process of drug repositioning. The Concept Encoder is a patented AI system based on natural language processing technology and by deep learning papers on COVID-19, the system identified a large group of genes implicated in COVID-19 pathogenesis. The AI system then generated a molecular linkage map for COVID-19, connecting the genes by deep learning the molecular relationship. By thoroughly reviewing the resulting map and list of the genes with rankings, we found potential key players for disease progression and existing drugs that might improve COVID-19 survival. Here, we focus on potential targets and discuss the perspective of our approach.

Identification of quantitative trait loci underlying resistance of soybean to Fusarium graminearum

AbstractFusarium graminearum could cause serious yield loss of soybean. Host resistance could offer an economical and effective way to control F. graminearum. The aims of this study were to identify and confirm quantitative trait loci (QTLs) underlying resistance to F. graminearum, and to analyse the genetic effects of pyramid resistance QTL on resistance level. A total of 140 F2:14 recombinant inbred lines (RILs) were constructed via the cross between 'Hefeng 25' (moderate resistance to F. graminearum) and 'Conrad' (resistance to F. graminearum). The molecular genetic linkage map was constructed based on 164 simple sequence repeat (SSR) markers. A total of seven QTLs underlying F. graminearum resistance, located on six chromosomes, were identified. Among these seven identified QTLs, beneficial allele of qFG‐1, qFG‐2 and qFG‐3 derived from 'Hefeng 25' and beneficial allele of qFG‐4, qFG‐5, qFG‐6, qFG‐7 derived from 'Conrad'. Of these seven identified QTLs, qFG‐1, qFG‐3, qFG‐4 and qFG‐5 were novel for F. graminearum resistance. Four pairs of QTLs with significant epistatic effects were found. The accumulation of resistance QTL was positively correlated with decreases in disease severity index, which was valuable for improving efficiency of marker‐assistant breeding in F. graminearum resistance.

FLOWERING LOCUS T, GIGANTEA, SEPALLATA, and FRIGIDA homologs are candidate genes involved in white lupin (Lupinus albus L.) early flowering

White lupin (Lupinus albus L.) is a legume plant rich in seed protein and appreciated in crop rotation due to improvement of soil structure and fertility. Primitive white lupin accessions are late flowering unless subjected to cold period during seed germination. It is an undesirable trait in spring-based agriculture. Moreover, white lupin is very susceptible to anthracnose, and the only known resistant lines are late-flowering landraces from Ethiopia. Tracking of early flowering during white lupin breeding has been challenging for many years due to the lack of knowledge on underlying genes and limited molecular resources. To address this issue, we performed genomic and genetic analysis of white lupin germplasm differing by time to flowering, including mapping population derived from Kiev Mutant (early flowering, anthracnose susceptible) and P27174 (late flowering, anthracnose resistant). Thirty six flowering induction pathway genes were subjected to molecular marker development and linkage mapping. Markers representing 24 homologs were localized in 17 linkage groups. Four quantitative trait loci (QTLs) of flowering time, consistent across field and greenhouse experiments, were localized in three linkage groups. Three QTLs absolutely co-localized with GIGANTEA, FLOWERING LOCUS T, and SEPALLATA 3 gene–based markers whereas one neighbored the FRIGIDA 3 marker by 3.6 cM. Analysis of narrow-leafed lupin genome regions highly syntenic to these QTLs highlighted these homologs as candidate genes for early flowering. Molecular markers developed in the present study should have facilitated the issue of tracking late-flowering alleles in further white lupin breeding approaches involving primitive Ethiopian germplasm.

Construction of a high density genetic map of an interspecific cross of Capsicum chinense and Capsicum annuum and QTL analysis of floral traits

The yield of pepper plants (Capsicum spp.) is their most important trait and is affected by the flower number and flowering time. Capsicum annuum produces a single flower per node and has an early flowering habit. By contrast, Capsicum chinense yields multiple flowers per node and has a late flowering character. However, the genetic mechanism underlying the control of these floral traits remains largely unknown. In this study, 150 F2 populations from an interspecific cross between the inbred lines 740 (C. chinense) and CA1 (C. annuum) and their parents were used to construct a molecular genetic linkage map using the specific length amplified fragment sequencing (SLAF-seq) technique. This linkage map, spanning 1,586.78 cM in length, contained 9,038 markers on 12 chromosomes, with a mean marker distance of 0.18 cM. Phenotypic data on the flowering time and flower number per node were collected over multiple years, and QTL analysis identified 6 QTLs for the flowering time and flower number per node by composite interval mapping (CIM) and genome-wide composite interval mapping (GCIM) methods at least in two environments. The candidate genes within the major QTL were predicted. In the major flowering time QTL, the candidate gene Capana02g000700, which encodes the homeotic protein APETALA2, was identified. Quantitative reverse-transcription PCR (qRT-PCR) analysis indicated that its expression level in 740 was higher than that in CA1. Gene expression analysis indicated that the expression of Capana02g000700 was significantly upregulated in flowers, and many floral development-related genes were found to be coexpressed with Capana02g000700, supporting the function of this gene in association with flowering time in C. chinense and C. annuum species.

Mapping QTL controlling agronomic traits in a doubled haploid population of winter oilseed rape (Brassica napus L.)

Identification of superior alleles for agronomic traits in genetic resources of oilseed rape (Brassica napus L.) would be useful for improving the performance of locally adapted cultivars in Iran. The objective of the present work was to analyse the genetic variation and inheritance of important agronomic traits in a doubled haploid population derived from a cross between two German oilseed rape cultivars, Sansibar and Oase. Field experiments were performed in 2016-2017 with 200 doubled haploid lines and the parental genotypes applying an alpha-lattice design with two replicates. Phenological traits were recorded during the cultivation period and at maturity, seed yield, yield components and seed quality traits were determined. Significant genetic variation was found in most of the traits and heritabilities ranged from medium (48.5%) for days to end of flowering to high (92.6%) for oil content. A molecular marker linkage map was used to map 36 QTL for different traits on 17 linkage groups. Between three and four QTL were identified for each seed yield, seed weight, oil and protein content. Some of the plant material and positive QTL alleles identified for agronomic traits may be useful for improving those characters in locally adapted cultivars in Iran.

Construction of a highly saturated Genetic Map for Vitis by Next-generation Restriction Site-associated DNA Sequencing

BackgroundHigh-saturate molecular linkage maps are an important tool in studies on plant molecular biology and assisted breeding. Development of a large set of single nucleotide polymorphisms (SNPs) via next-generation sequencing (NGS)-based methods, restriction-site associated DNA sequencing (RAD-seq), and the generation of a highly saturated genetic map help improve fine mapping of quantitative trait loci (QTL).ResultsWe generated a highly saturated genetic map to identify significant traits in two elite grape cultivars and 176 F1 plants. In total, 1,426,967 high-quality restriction site-associated DNA tags were detected; 51,365, 23,683, and 70,061 markers were assessed in 19 linkage groups (LGs) for the maternal, paternal, and integrated maps, respectively. Our map was highly saturated in terms of marker density and average “Gap ≤ 5 cM” percentage.ConclusionsIn this study, RAD-seq of 176 F1 plants and their parents yielded 8,481,484 SNPs and 1,646,131 InDel markers, of which 65,229 and 4832, respectively, were used to construct a highly saturated genetic map for grapevine. This map is expected to facilitate genetic studies on grapevine, including an evaluation of grapevine and deciphering the genetic basis of economically and agronomically important traits. Our findings provide basic essential genetic data the grapevine genetic research community, which will lead to improvements in grapevine breeding.