Dataset Information

QTL Mapping of Genome Regions Controlling Manganese Uptake in Lentil Seed.

ABSTRACT: This study evaluated Mn concentration in the seeds of 120 RILs of lentil developed from the cross "CDC Redberry" × "ILL7502". Micronutrient analysis using atomic absorption spectrometry indicated mean seed manganese (Mn) concentrations ranging from 8.5 to 26.8 mg/kg, based on replicated field trials grown at three locations in Turkey in 2012 and 2013. A linkage map of lentil was constructed and consisted of seven linkage groups with 5,385 DNA markers. The total map length was 973.1 cM, with an average distance between markers of 0.18 cM. A total of 6 QTL for Mn concentration were identified using composite interval mapping (CIM). All QTL were statistically significant and explained 15.3-24.1% of the phenotypic variation, with LOD scores ranging from 3.00 to 4.42. The high-density genetic map reported in this study will increase fundamental knowledge of the genome structure of lentil, and will be the basis for the development of micronutrient-enriched lentil genotypes to support biofortification efforts.

SUBMITTER: Ates D

PROVIDER: S-EPMC5940135 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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QTL Mapping of Genome Regions Controlling Manganese Uptake in Lentil Seed.

Ates Duygu D Aldemir Secil S Yagmur Bulent B Kahraman Abdullah A Ozkan Hakan H Vandenberg Albert A Tanyolac Muhammed Bahattin MB

G3 (Bethesda, Md.) 20180504 5

This study evaluated Mn concentration in the seeds of 120 RILs of lentil developed from the cross "CDC Redberry" × "ILL7502". Micronutrient analysis using atomic absorption spectrometry indicated mean seed manganese (Mn) concentrations ranging from 8.5 to 26.8 mg/kg, based on replicated field trials grown at three locations in Turkey in 2012 and 2013. A linkage map of lentil was constructed and consisted of seven linkage groups with 5,385 DNA markers. The total map length was 973.1 cM, with an a ...[more]

PMID: 29588380

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Project description:BackgroundSeed aging in soybean is a serious challenge for agronomic production and germplasm preservation. However, its genetic basis remains largely unclear in soybean. Unraveling the genetic mechanism involved in seed aging, and enhancing seed storability is an imperative goal for soybean breeding. The aim of this study is to identify quantitative trait loci (QTLs) using high-density genetic linkage maps of soybean for seed storability. In this regard, two recombinant inbred line (RIL) populations derived from Zhengyanghuangdou × Meng 8206 (ZM6) and Linhefenqingdou × Meng 8206 (LM6) crosses were evaluated for three seed-germination related traits viz., germination rate (GR), normal seedling length (SL) and normal seedling fresh weight (FW) under natural and artificial aging conditions to map QTLs for seed storability.ResultsA total of 34 QTLs, including 13 QTLs for GR, 11 QTLs for SL and 10 QTLs for FW, were identified on 11 chromosomes with the phenotypic variation ranged from 7.30 to 23.16% under both aging conditions. All these QTLs were novel, and 21 of these QTLs were clustered in five QTL-rich regions on four different chromosomes viz., Chr3, Chr5, Chr17 &Chr18, among them the highest concentration of seven and six QTLs were found in "QTL hotspot A" (Chr17) and "QTL hotspot B" (Chr5), respectively. Furthermore, QTLs within all the five QTL clusters are linked to at least two studied traits, which is also supported by highly significant correlation between the three germination-related traits. QTLs for seed-germination related traits in "QTL hotspot B" were found in both RIL populations and aging conditions, and also QTLs underlying "QTL hotspot A" are identified in both RIL populations under artificial aging condition. These are the stable genomic regions governing the inheritance of seed storability in soybean, and will be the main focus for soybean breeders.ConclusionThis study uncovers the genetic basis of seed storability in soybean. The newly identified QTLs provides valuable information, and will be main targets for fine mapping, candidate gene identification and marker-assisted breeding. Hence, the present study is the first report for the comprehensive and detailed investigation of genetic architecture of seed storability in soybean.

Project description:Melon (Cucumis melo L.) seed germination significantly affects its economic value. Cultivation of melon varieties with high germination ability and seedling vigor is beneficial in large-scale melon propagation. In this study, two melon genotypes differing in their germination ability, P5 with low and P10 with high germination ability, were used to identify the optimal seed germination conditions by evaluating different water immersion times and germination temperatures. The germination rate of the P5 and P10 parental genotypes and their segregating population, consisting of 358 F2:3 families, were evaluated for 2 years to identify their genetic basis. QTL analysis was performed on a high-density genetic map constructed using specific-locus amplified fragment sequencing (SLAF-seq). The germination rate of F1 and F2 populations treated with water immersion for 8 h at 28°C and measured at 48 h showed a normal distribution Genetic mapping carried out using the high-density genetic map revealed eight QTLs in chromosomes 2, 4, 5, 6, and 8 that control melon seed germination, of which 2020/2021-qsg5.1 was consistently significant in both years of experimentation. qsg5.1 explained 15.13% of the phenotypic variance with a LOD of 4.1. To fine map the candidate region of qsg5.1, eight cleaved amplified polymorphism sequence (CAPS) markers were used to construct a genetic map with another 421 F2 individual fruits. The major QTL qsg5.1 was located between SNP53 and SNP54 within a 55.96 Kb interval containing four genes. qRT-PCR gene expression analysis of the candidate genes showed that MELO3C031219.2 (Phosphorus transporter PHO-5) exhibited a significant difference in gene expression between the parental lines at 24, 32, and 48 h after germination, potentially being the underlying gene controlling melon seed germination. These results provide a theoretical basis for the molecular mechanisms controlling melon seed germination and can practically contribute to further improving germination to increase the propagation efficiency of commercial melon cultivars.

Project description:BackgroundThe serovars Enteritidis and Typhimurium of the Gram-negative bacterium Salmonella enterica are significant causes of human food poisoning. Fowl carrying these bacteria often show no clinical disease, with detection only established post-mortem. Increased resistance to the carrier state in commercial poultry could be a way to improve food safety by reducing the spread of these bacteria in poultry flocks. Previous studies identified QTLs for both resistance to carrier state and resistance to Salmonella colonization in the same White Leghorn inbred lines. Until now, none of the QTLs identified was common to the two types of resistance. All these analyses were performed using the F2 inbred or backcross option of the QTLExpress software based on linear regression. In the present study, QTL analysis was achieved using Maximum Likelihood with QTLMap software, in order to test the effect of the QTL analysis method on QTL detection. We analyzed the same phenotypic and genotypic data as those used in previous studies, which were collected on 378 animals genotyped with 480 genome-wide SNP markers. To enrich these data, we added eleven SNP markers located within QTLs controlling resistance to colonization and we looked for potential candidate genes co-localizing with QTLs.ResultsIn our case the QTL analysis method had an important impact on QTL detection. We were able to identify new genomic regions controlling resistance to carrier-state, in particular by testing the existence of two segregating QTLs. But some of the previously identified QTLs were not confirmed. Interestingly, two QTLs were detected on chromosomes 2 and 3, close to the locations of the major QTLs controlling resistance to colonization and to candidate genes involved in the immune response identified in other, independent studies.ConclusionsDue to the lack of stability of the QTLs detected, we suggest that interesting regions for further studies are those that were identified in several independent studies, which is the case of the QTL regions on chromosomes 2 and 3, involved in resistance to both Salmonella colonization and carrier state. These observations provide evidence of common genes controlling S. Typhimurium colonization and S. Enteritidis carrier-state in chickens.

Dataset Information

QTL Mapping of Genome Regions Controlling Manganese Uptake in Lentil Seed.

Publications

QTL Mapping of Genome Regions Controlling Manganese Uptake in Lentil Seed.

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