Evidence map›Paper›PMID 39081164›Full record

ArticleThe plant genome2024

Integrated meta-QTL and in silico transcriptome assessment pinpoint major genomic regions responsible for spike length in wheat (Triticum aestivum L.).

Changgang Yang, Xueting Zhang, Shihong Wang, Na Liu

Abstract read
In one paragraph

Article in The plant genome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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3 · Its place in the literature

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5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Changgang YangWheat Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, China.ORCID https://orcid.org/0000-0002-9307-8936
Xueting ZhangWheat Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, China.
Shihong WangWheat Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, China.
Na LiuWheat Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou, China.

Funding

Agricultural Science and Technology Innovation Program of Gansu Academy of Agricultural Sciences 2021GAAS37Lanzhou Talent Innovation and Entrepreneurship Project 2022-RC-69National Key Research and Development Program of China 2022YFD1200903National Natural Science Foundation Project 32360446National Natural Science Foundation Project 32360505
6 · The paper itself

Abstract

Spike length (SL) is one of the major contributors to wheat yield. Uncovering major genetic regions affecting SL is an integral part of elucidating the genetic basis of wheat yield traits and goes further pivotal for marker-assisted selection breeding. A genome-wide meta-quantitative trait locus (MQTL) analysis of wheat SL resulted in the refinement of 48 MQTLs using 227 initial QTLs retrieved from previous studies published over the past decades. The average confidence interval (CI) of these MQTLs amounted to a 5.16-fold reduction compared to the mean CI of the initial QTLs. As many as 2240 putative candidate genes (CGs) were identified from the MQTL intervals using transcriptomics data in silico of wheat, of which 58 CGs were identified based on wheat-rice homology analysis. For the key CG affecting SL, a functional kompetitive allele-specific PCR (KASP) marker, TaPP2C-3B-KASP, was developed to distinguish TaPP2C-3B-Hap I and TaPP2C-3B-Hap II based on the single nucleotide polymorphism at the 272 bp (A/G). The frequency of the elite allelic variation TaPP2C-3B-Hap II with high SL remained relatively stable at about 49.62% from the 1960s to 1990s. Integration of MQTL analysis and in silico transcriptome data led to a significant increase in the reliability of CGs for the genetic regulation of wheat SL, and the haplotype analysis for key CGs TaPP2C-3B of SL provided insights into the biological function of the TaPP2C-3B gene.

Indexed as

Quantitative Trait LociTranscriptomeTriticumChromosome MappingComputer SimulationGenome, PlantPolymorphism, Single Nucleotide

Identifiers

PMID39081164
PMCPMC12807425

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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.