QTLs for iron concentration in seeds of the cultivated lentil (Lens culinaris Medic.) via genotyping by sequencing

Aldemir, Seçil; Ateş, Duygu; Temel, Hülya Yilmaz; Yağmur, Bülent; Alsaleh, Ahmad; Kahriman, Abdullah; Özkan, Hakan; Vandenberg, Albert; Tanyolaç, Muhammed Bahattin

doi:10.3906/tar-1610-33

Cited by 40 publications

(32 citation statements)

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“…Genetic markers such as DArT technology in context of micronutrients in lentil seeds have been used by Ates et al (2018) to construct a high-density linkage maps and to identify the associated QTLs using RILs and to assess the phenotypic variability in Mn, whereas Aldemir et al (2017) used a RIL population to locate QTLs for Fe using genotyping by sequencing technology. Molecular tagging of micronutrient-dense traits will lead to marker-assisted selection in breeding cycles.…”

Section: Discussionmentioning

confidence: 99%

“…It delivers improved genetic material to the national programs of developing countries to develop new improved cultivars. In Turkish environments, variability in micronutrients arising from landraces and genetic crosses derived lines has been reported in several studies based on dense genetic marker techniques (Karaköy et al, 2012;Aldemir et al, 2017;Ates et al, 2018). Its gene bank holds >11,000 accessions of diverse lentils collected from 72 countries (GRU, 2005), which are the key to genetic enhancement for micronutrients.…”

Section: Genotypic Variability and Genotype ´ Environment Interactionmentioning

confidence: 99%

“…Its gene bank holds >11,000 accessions of diverse lentils collected from 72 countries (GRU, 2005), which are the key to genetic enhancement for micronutrients. Aldemir et al (2017) observed that in a recombinant inbred line (RIL) population, Fe concentration in lentil seeds ranged from 37.2 to 175.7 mg kg −1 . These considerable variations in Fe and Zn contents suggest a scope for improvement in these traits (Sarker et al, 2018).…”

Section: Genotypic Variability and Genotype ´ Environment Interactionmentioning

confidence: 99%

“…These considerable variations in Fe and Zn contents suggest a scope for improvement in these traits (Sarker et al, 2018). In Turkish environments, variability in micronutrients arising from landraces and genetic crosses derived lines has been reported in several studies based on dense genetic marker techniques (Karaköy et al, 2012;Aldemir et al, 2017;Ates et al, 2018). In an evaluation of 39 landraces and seven cultivars collected from southeastern Turkey, substantial variability for eight micronutrients including Fe and Zn in an eastern Mediterranean climate was observed (Karaköy et al, 2012).…”

mentioning

confidence: 92%

“…In an evaluation of 39 landraces and seven cultivars collected from southeastern Turkey, substantial variability for eight micronutrients including Fe and Zn in an eastern Mediterranean climate was observed (Karaköy et al, 2012). Aldemir et al (2017) observed that in a recombinant inbred line (RIL) population, Fe concentration in lentil seeds ranged from 37.2 to 175.7 mg kg −1 . They also identified 21 QTL (quantitative trait locus) regions explaining 5.9 to 14.0% of phenotypic variation in Fe in lentil seeds and the location of the QTLs using genotyping by sequencing.…”

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confidence: 99%

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Genotypic Variability and Genotype × Environment Interaction for Iron and Zinc Content in Lentil under Nepalese Environments

et al. 2018

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To ascertain the variability in Fe and Zn concentrations in lentil (Lens culinaris Medikus ssp. culinaris) seeds, a set of 58 lentil genotypes were evaluated in randomized complete blocks at eight locations in Nepal during 2006 to 2012. Micronutrient contents of the seeds were analyzed. The mean Fe varied from 72.4 μg g−1 at Surkhet in 2009 to 98.2 μg g−1 at Rampur in 2012, and the mean Zn from 23.9 μg g−1 at Surkhet in 2012 to 85.1 μg g−1 at Parwanipur in 2009. The genotype effect and genotype × location interaction were significant for Fe (P = 0.01–0.03). For Zn, the genotype effect was significant (P = 0.008), and the genotype × location interaction was not (P = 0.46). The variance component estimates for the genotype × year interaction within locations were zero for both the minerals, indicating genotypic stability over the years. The best line for Fe was ILL7723 (81.0 μg g−1) and RL6 for Zn (56.2 μg g−1). The lines that were within the top 20% for high concentrations of both minerals were Barimasoor4, RL6, RL9, ILL8006, RL11, RL12, ILL9926, and ILL6819. The lowest concentrations of the minerals were found in Shital for Fe (74.2 μg g−1) and Black musuro for Zn (51.4 μg g−1). These results provide a useful foundation for the development of new lentil cultivars that have high mineral content and could be used to develop more nutritious varieties of lentil and reduce mineral element deficiencies in Nepal.

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Section: Discussionmentioning

confidence: 99%

Section: Genotypic Variability and Genotype ´ Environment Interactionmentioning

confidence: 99%

Section: Genotypic Variability and Genotype ´ Environment Interactionmentioning

confidence: 99%

mentioning

confidence: 92%

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confidence: 99%

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Genotypic Variability and Genotype × Environment Interaction for Iron and Zinc Content in Lentil under Nepalese Environments

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Recent Advances in Lentil Genetics, Genomics, and Molecular Breeding

Kumar

Gela

Gupta

et al. 2023

Lentils

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Genomics‐assisted lentil breeding: Current status and future strategies

et al. 2021

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Genomics‐assisted breeding has become a powerful tool to develop high‐yielding climate‐resilient varieties for adaptation to adverse environmental conditions such as heat and drought stresses. Previously, efforts have been made to develop genomic resources in lentil, leading to the development of many trait‐specific mapping populations, cores and mini‐cores, and single nucleotide polymorphism and simple sequence repeat markers. Molecular markers have been used in genetic diversity analyses and to clarify genetic relationships in lentil. However, availability of cost‐effective next‐generation sequencing and genotyping‐by‐sequencing technologies has provided unprecedented opportunities for advancing genetics research and breeding applications. For instance, it has become possible to assemble the large and complex genome, develop high‐density genetic maps for high‐resolution QTL mapping, and deploy genome‐wide association study in lentil. Furthermore, a range of cost‐effective marker genotyping platforms have been developed. These developments offer ample opportunities to modernize current breeding programs in lentil for accelerating genetic gains. This review discusses the current status and future possibilities of genomics‐assisted breeding to develop and deploy lentil cultivars suitable for changing climatic conditions.

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QTLs for iron concentration in seeds of the cultivated lentil (Lens culinaris Medic.) via genotyping by sequencing

Abstract: IntroductionLentil, Lens culinaris Medic., is an important cool season food legume in the old world. It is a self-pollinated, diploid (2n = 2x = 14) with a genome size of 4063 Mbp (Arumuganathan and Earl, 1991). The origin of cultivated lentil is the

Cited by 40 publications

References 91 publications

Genotypic Variability and Genotype × Environment Interaction for Iron and Zinc Content in Lentil under Nepalese Environments

Genotypic Variability and Genotype × Environment Interaction for Iron and Zinc Content in Lentil under Nepalese Environments

Recent Advances in Lentil Genetics, Genomics, and Molecular Breeding

Genomics‐assisted lentil breeding: Current status and future strategies

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