Evidence map›Paper›PMID 42919024›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2027

Development of SNPs for Crop Improvement.

Shouvik Gorai, Afridi Mondal, Md Imtiyaz, Bandela Chandana, Subhasis Samanta, V Umesh Kumar, Soham Hazra, Anirban Maji

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2027. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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.

Shouvik GoraiDepartment of Genetics and Plant Breeding, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, West Bengal, India.
Afridi MondalDepartment of Genetics and Plant Breeding, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, West Bengal, India.
Md ImtiyazDepartment of Genetics and Plant Breeding, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, West Bengal, India.
Bandela ChandanaDepartment of Genetics and Plant Breeding, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, West Bengal, India.
Subhasis SamantaDepartment of Genetics and Plant Breeding, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, West Bengal, India.
V Umesh KumarDepartment of Genetics and Plant Breeding, Sri Konda Laxman Telangana Horticultural University, Telangana, India.
Soham HazraDepartment of Agriculture, Brainware University, Barasat, West Bengal, India.
Anirban MajiDepartment of Genetics and Plant Breeding, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, West Bengal, India. anigpbr@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-nucleotide polymorphisms (SNPs) represent the most abundant form of genetic variation in crop genomes and serve as highly informative molecular markers for modern breeding programs. Advances in next-generation sequencing technologies have enabled rapid and high-throughput SNP discovery across diverse crop species, including those with large and complex genomes. Reliable SNP development requires an integrated workflow encompassing germplasm selection, high-quality DNA isolation, library preparation, sequencing, sequence data processing, variant calling, stringent filtering, annotation, and experimental validation. This chapter presents a stepwise methodological framework for SNP discovery and validation tailored for crop improvement applications. The described protocols emphasize reproducibility, data quality, and scalability to support downstream analyses such as genetic diversity assessment, association mapping, marker-assisted selection, and genomic prediction.

Indexed as

Crops, AgriculturalPlant BreedingPolymorphism, Single NucleotideGenetic MarkersGenome, PlantGenomicsHigh-Throughput Nucleotide SequencingSequence Analysis, DNAGenetic MarkersCrop genomicsGenomic selectionMolecular markersNext-generation sequencingSingle nucleotide polymorphismSNP discoveryVariant calling

Identifiers

PMID42919024

What OpenQuestion holds

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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.