Evidence map›Paper›PMID 35971070›Full record

ArticleBMC genomics2022

Identification of two new QTLs of maize (Zea mays L.) underlying kernel row number using the HNAU-NAM1 population.

Xiaohong Fei, Yifei Wang, Yunxiao Zheng, Xiaomeng Shen, Lizhu E, Junqiang Ding, Jinsheng Lai, Weibin Song, Haiming Zhao

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

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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

12 citing papers in PubMed, 10 citations in OpenAlex.

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  3. Plants (Basel, Switzerland) · 2025
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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

9 authors at 2 institutions in 1 country.

Xiaohong FeiState Key Laboratory of Plant Physiology and Biochemistry, China Agricultural University, Beijing, 100193, People's Republic of China.
Yifei WangState Key Laboratory of Plant Physiology and Biochemistry, China Agricultural University, Beijing, 100193, People's Republic of China.
Yunxiao ZhengState Key Laboratory of Plant Physiology and Biochemistry, China Agricultural University, Beijing, 100193, People's Republic of China.
Xiaomeng ShenState Key Laboratory of Plant Physiology and Biochemistry, China Agricultural University, Beijing, 100193, People's Republic of China.
Lizhu EState Key Laboratory of Plant Physiology and Biochemistry, China Agricultural University, Beijing, 100193, People's Republic of China.
Junqiang DingState Key Laboratory of Wheat and Maize Crop Science and Center for Crop Genome Engineering, Henan Agricultural University, Zhengzhou, 450046, People's Republic of China.
Jinsheng LaiState Key Laboratory of Plant Physiology and Biochemistry, China Agricultural University, Beijing, 100193, People's Republic of China.
Weibin SongState Key Laboratory of Plant Physiology and Biochemistry, China Agricultural University, Beijing, 100193, People's Republic of China. songwb@cau.edu.cn.
Haiming ZhaoState Key Laboratory of Plant Physiology and Biochemistry, China Agricultural University, Beijing, 100193, People's Republic of China. haiming223@163.com.
China Agricultural University · CNHenan Agricultural University · CN

Funding

National Key R&D Program of China 2018YFA0901003National Key R&D Program of China 2021YFD1200700National Natural Science Foundation of China 31971957
6 · The paper itself

Abstract

backgroundMaize kernel row number (KRN) is one of the most important yield traits and has changed greatly during maize domestication and selection. Elucidating the genetic basis of KRN will be helpful to improve grain yield in maize.

resultsHere, we measured KRN in four environments using a nested association mapping (NAM) population named HNAU-NAM1 with 1,617 recombinant inbred lines (RILs) that were derived from 12 maize inbred lines with a common parent, GEMS41. Then, five consensus quantitative trait loci (QTLs) distributing on four chromosomes were identified in at least three environments along with the best linear unbiased prediction (BLUP) values by the joint linkage mapping (JLM) method. These QTLs were further validated by the separate linkage mapping (SLM) and genome-wide association study (GWAS) methods. Three KRN genes cloned through the QTL assay were found in three of the five consensus QTLs, including qKRN1.1, qKRN2.1 and qKRN4.1. Two new QTLs of KRN, qKRN4.2 and qKRN9.1, were also identified. On the basis of public RNA-seq and genome annotation data, five genes highly expressed in ear tissue were considered candidate genes contributing to KRN.

conclusionsThis study carried out a comprehensive analysis of the genetic architecture of KRN by using a new NAM population under multiple environments. The present results provide solid information for understanding the genetic components underlying KRN and candidate genes in qKRN4.2 and qKRN9.1. Single-nucleotide polymorphisms (SNPs) closely linked to qKRN4.2 and qKRN9.1 could be used to improve inbred yield during molecular breeding in maize.

Indexed as

Quantitative Trait LociZea maysChromosome MappingEdible GrainGenome-Wide Association StudyPhenotypeKernel row number (KRN)MaizeNested association mapping (NAM) populationQuantitative trait locus (QTL) mapping

Identifiers

PMID35971070
PMCPMC9380338
OpenAlexW4291903791

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LicenceCC BY
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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.