Evidence map›Paper›PMID 35257240›Full record

ArticleMolecular genetics and genomics : MGG2022

Identification of potential MTAs and candidate genes for juice quality- and yield-related traits in Saccharum clones: a genome-wide association and comparative genomic study.

Shanmugavel Senthilkumar, K K Vinod, Selvaraj Parthiban, Prathima Thirugnanasambandam, Thalambedu Lakshmi Pathy, Nandita Banerjee, Thelakat Sasikumar Sarath Padmanabhan, P Govindaraj

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Article in Molecular genetics and genomics : MGG, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.3field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Combination of GWAS and FMolecular genetics and genomics : MGG · 2023
    Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Shanmugavel SenthilkumarDivision of Crop Improvement, ICAR-Sugarcane Breeding Institute, Coimbatore, Tamil Nadu, 641007, India.
K K VinodDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
Selvaraj ParthibanDivision of Crop Improvement, ICAR-Sugarcane Breeding Institute, Coimbatore, Tamil Nadu, 641007, India.
Prathima ThirugnanasambandamDivision of Crop Improvement, ICAR-Sugarcane Breeding Institute, Coimbatore, Tamil Nadu, 641007, India.
Thalambedu Lakshmi PathyDivision of Crop Improvement, ICAR-Sugarcane Breeding Institute, Coimbatore, Tamil Nadu, 641007, India.
Nandita BanerjeeDivision of Crop Improvement, ICAR-Indian Institute of Sugarcane Research, Lucknow, Uttar Pradesh, 226002, India.
Thelakat Sasikumar Sarath PadmanabhanDivision of Crop Improvement, ICAR-Sugarcane Breeding Institute, Coimbatore, Tamil Nadu, 641007, India.
P GovindarajDivision of Crop Improvement, ICAR-Sugarcane Breeding Institute, Coimbatore, Tamil Nadu, 641007, India. govindsbi1912@gmail.com.ORCID http://orcid.org/0000-0002-2389-0953
Sugarcane Breeding Institute · INIndian Agricultural Research Institute · INIndian Institute of Sugarcane Research · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sugarcane is an economically important commercial crop which provides raw material for the production of sugar, jaggery, bioethanol, biomass and other by-products. Sugarcane breeding till today heavily relies on conventional breeding approaches which is time consuming, laborious and costly. Integration of marker-assisted selection (MAS) in sugarcane genetic improvement programs for difficult to select traits like sucrose content, resistance to pests and diseases and tolerance to abiotic stresses will accelerate varietal development. In the present study, association mapping approach was used to identify QTLs and genes associated with sucrose and other important yield-contributing traits. A mapping panel of 110 diverse sugarcane genotypes and 148 microsatellite primers were used for structured association mapping study. An optimal subpopulation number (ΔK) of 5 was identified by structure analysis. GWAS analysis using TASSEL identified a total of 110 MTAs which were localized into 27 QTLs by GLM and MLM (Q + K, PC + K) approaches. Among the 24 QTLs sequenced, 12 were able to identify potential candidate genes, viz., starch branching enzyme, starch synthase 4, sugar transporters and G3P-DH related to carbohydrate metabolism and hormone pathway-related genes ethylene insensitive 3-like 1, reversion to ethylene sensitive1-like, and auxin response factor associated to juice quality- and yield-related traits. Six markers, NKS 5_185, SCB 270_144, SCB 370_256, NKS 46_176 and UGSM 648_245, associated with juice quality traits and marker SMC31CUQ_304 associated with NMC were validated and identified as significantly associated to the traits by one-way ANOVA analysis. In conclusion, 24 potential QTLs identified in the present study could be used in sugarcane breeding programs after further validation in larger population. The candidate genes from carbohydrate and hormone response pathway presented in this study could be manipulated with genome editing approaches to further improve sugarcane crop.

Indexed as

SaccharumClone CellsEthylenesGenome-Wide Association StudyGenomicsHormonesPemetrexedPlant BreedingSucroseSugarsEthylenesHormonesPemetrexedSucroseSugarsAssociation mappingComparative genomicsGLMMLMSucrose

Identifiers

PMID35257240
OpenAlexW4220821096

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.