Elucidating genetic diversity and association mapping to identify SSR markers linked to 100 seed weight in chickpea (Cicer arietinum L.)

Jha, Uday Chand; Jha, Rintu .; Thakro, Virevol .; Nayyar, Harsh .; Paul, Pronob J.; Tripathi, Shailesh .; Kumar, Yogesh; Mondal, Biswajit .; Srivastava, Avinash .; Singh, Narendra Pratap; Chaturvedi, Sushil K.; Parida, Swarup K.

doi:10.31742/ijgpb.82.2.8

Cited by 2 publications

(1 citation statement)

References 37 publications

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“…Plump and bold grains are preferred by grain mills and consumers of certain geographies (Ponce-Garcia et al 2017;Custodio et al 2019). Being a quantitative trait, TGW is controlled by multiple genes and warrants the use of quantitative trait loci (QTL) analysis to identify the genomic regions controlling it (Sun et al 2009;Li et al 2015;Jha et al 2022). Accurate phenotyping of TGW is crucial for capturing the phenotypic variation in the mapping populations with the minimum error to aid in QTL discovery.…”

Section: Introductionmentioning

confidence: 99%

Development of a novel image-based grain counting setup for thousand-grain weight estimation in wheat

Krishnan,

Kumar,

Kaur

et al. 2023

IJGPB

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Thousand-grain weight (TGW) is one of the major yield-contributing traits routinely used as a selection criterion by plant breeders. Itis also an important grain quality trait that determines milling yield. Accurate phenotyping of TGW is imperative to dissect its geneticsfor yield improvement. The traditional approach to TGW estimation involves manual grain counting and weighing, which is laborious,tedious and less accurate for large sample sizes. As an alternative, we propose a customized grain counting setup for accurate estimationof TGW in wheat by assembling a photo lighting tent and a smartphone for image acquisition of grain samples. A popular open-sourcesoftware, ‘imageJ’ was used to process the images to estimate the grain count. The counted grain samples were weighed to calculatethe TGW. The TGW estimate derived from the proposed grain counting setup displayed a high degree of correlation with the manuallyestimated TGW data (r = 0.99, p <0.05). It took significantly less time to count the grain samples using the proposed setup comparedto manual counting with better accuracy and minimal labor. The error rate in grain counting using the imaging-based setup was verylow (<1%) and 30 to 40 grain samples can be imaged per hour. This setup can be extended to estimate the TGW of different crops,excluding those having spherical seeds.

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Section: Introductionmentioning

confidence: 99%

Development of a novel image-based grain counting setup for thousand-grain weight estimation in wheat

Krishnan,

Kumar,

Kaur

et al. 2023

IJGPB

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Haplotypes of ATP-Binding Cassette CaABCC6 in Chickpea from Kazakhstan Are Associated with Salinity Tolerance and Leaf Necrosis via Oxidative Stress

Khassanova,

Jatayev,

Gabdola

et al. 2024

Biomolecules

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Salinity tolerance was studied in chickpea accessions from a germplasm collection and in cultivars from Kazakhstan. After NaCl treatment, significant differences were found between genotypes, which could be arranged into three groups. Those that performed poorest were found in group 1, comprising five ICC accessions with the lowest chlorophyll content, the highest leaf necrosis (LN), Na+ accumulation, malondialdehyde (MDA) content, and a low glutathione ratio GSH/GSSG. Two cultivars, Privo-1 and Tassay, representing group 2, were moderate in these traits, while the best performance was for group 3, containing two other cultivars, Krasnokutsky-123 and Looch, which were found to have mostly green plants and an exact opposite pattern of traits. Marker–trait association (MTA) between 6K DArT markers and four traits (LN, Na+, MDA, and GSH/GSSG) revealed the presence of four possible candidate genes in the chickpea genome that may be associated with the three groups. One gene, ATP-binding cassette, CaABCC6, was selected, and three haplotypes, A, D1, and D2, were identified in plants from the three groups. Two of the most salt-tolerant cultivars from group 3 were found to have haplotype D2 with a novel identified SNP. RT-qPCR analysis confirmed that this gene was strongly expressed after NaCl treatment in the parental- and breeding-line plants of haplotype D2. Mass spectrometry of seed proteins showed a higher accumulation of glutathione reductase and S-transferase, but not peroxidase, in the D2 haplotype. In conclusion, the CaABCC6 gene was hypothesized to be associated with a better response to oxidative stress via glutathione metabolism, while other candidate genes are likely involved in the control of chlorophyll content and Na+ accumulation.

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Elucidating genetic diversity and association mapping to identify SSR markers linked to 100 seed weight in chickpea (Cicer arietinum L.)

Cited by 2 publications

References 37 publications

Development of a novel image-based grain counting setup for thousand-grain weight estimation in wheat

Development of a novel image-based grain counting setup for thousand-grain weight estimation in wheat

Haplotypes of ATP-Binding Cassette CaABCC6 in Chickpea from Kazakhstan Are Associated with Salinity Tolerance and Leaf Necrosis via Oxidative Stress

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