Evidence map›Paper›PMID 26691201›Full record

ArticleBMC genomics2015

An ultra-high-density map as a community resource for discerning the genetic basis of quantitative traits in maize.

Hongjun Liu, Yongchao Niu, Pedro J Gonzalez-Portilla, Huangkai Zhou, Liya Wang, Tao Zuo, Cheng Qin, Shuaishuai Tai, Constantin Jansen, Yaou Shen and 6 more

Abstract read
In one paragraph

Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

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.

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

39 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Combined linkage mapping and association analysis reveal the genetic control of starch content in maize kernel.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Quantitative trait locus analysis of gray leaf spot resistance in the maize IBM Syn10 DH population.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
  8. A combination of QTL mapping and genome-wide association study revealed the key gene for husk number in maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. qTGW12a, a naturally varying QTL, regulates grain weight in rice.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021
    Article
  19. QTL Mapping for Leaf Area of Tea Plants (Frontiers in plant science · 2021
    Article
  20. Article
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

16 authors.

Hongjun LiuMaize Research Institute of Sichuan Agricultural University/Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture, 611130, Chengdu, China. lhj20305@163.com.
Yongchao NiuBGI-Shenzhen, Shenzhen, 518083, China. niuyongchao@tgs.org.cn.
Pedro J Gonzalez-PortillaDepartment of Agronomy, Iowa State University, Ames, IA, 50011, USA. pedrog@iastate.edu.
Huangkai ZhouBGI-Shenzhen, Shenzhen, 518083, China. zhouhuangkai@126.com.
Liya WangCold Spring Harbor Laboratory and USDA: USDA ARS NAA Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, 14853, Ithaca, NY, USA. wangli@cshl.edu.
Tao ZuoInterdepartmental Genetics Graduate Program, Iowa State University, Ames, 50011, USA. taozuo@iastate.edu.
Cheng QinMaize Research Institute of Sichuan Agricultural University/Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture, 611130, Chengdu, China. qincheng1001@163.com.
Shuaishuai TaiBGI-Shenzhen, Shenzhen, 518083, China. taishuaishuai@genomics.cn.
Constantin JansenDepartment of Agronomy, Iowa State University, Ames, IA, 50011, USA. jansenconstantin@googlemail.com.
Yaou ShenMaize Research Institute of Sichuan Agricultural University/Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture, 611130, Chengdu, China. shenyaou@aliyun.com.
Haijian LinMaize Research Institute of Sichuan Agricultural University/Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture, 611130, Chengdu, China. linhj521@gmail.com.
Michael LeeDepartment of Agronomy, Iowa State University, Ames, IA, 50011, USA. mlee@iastate.edu.
Doreen WareCold Spring Harbor Laboratory and USDA: USDA ARS NAA Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, 14853, Ithaca, NY, USA. ware@cshl.edu.
Zhiming ZhangMaize Research Institute of Sichuan Agricultural University/Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture, 611130, Chengdu, China. zzmmaize@gmail.com.
Thomas LübberstedtDepartment of Agronomy, Iowa State University, Ames, IA, 50011, USA. thomasl@iastate.edu.
Guangtang PanMaize Research Institute of Sichuan Agricultural University/Key Laboratory of Biology and Genetic Improvement of Maize in Southwest Region, Ministry of Agriculture, 611130, Chengdu, China. pangt@sicau.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo safeguard the food supply for the growing human population, it is important to understand and exploit the genetic basis of quantitative traits. Next-generation sequencing technology performs advantageously and effectively in genetic mapping and genome analysis of diverse genetic resources. Hence, we combined re-sequencing technology and a bin map strategy to construct an ultra-high-density bin map with thousands of bin markers to precisely map a quantitative trait locus.

resultsIn this study, we generated a linkage map containing 1,151,856 high quality SNPs between Mo17 and B73, which were verified in the maize intermated B73 × Mo17 (IBM) Syn10 population. This resource is an excellent complement to existing maize genetic maps available in an online database  (iPlant, http://data.maizecode.org/maize/qtl/syn10/ ). Moreover, in this population combined with the IBM Syn4 RIL population, we detected 135 QTLs for flowering time and plant height traits across the two populations. Eighteen known functional genes and twenty-five candidate genes for flowering time and plant height trait were fine-mapped into a 2.21-4.96 Mb interval. Map expansion and segregation distortion were also analyzed, and evidence for inadvertent selection of early flowering time in the process of mapping population development was observed. Furthermore, an updated integrated map with 1,151,856 high-quality SNPs, 2,916 traditional markers and 6,618 bin markers was constructed. The data were deposited into the iPlant Discovery Environment (DE), which provides a fundamental resource of genetic data for the maize genetic research community.

conclusionsOur findings provide basic essential genetic data for the maize genetic research community. An updated IBM Syn10 population and a reliable, verified high-quality SNP set between Mo17 and B73 will aid in future molecular breeding efforts.

Indexed as

Quantitative Trait LociChromosome MappingGenetic LinkageGenome, PlantPolymorphism, Single NucleotideSequence Analysis, DNAZea mays

Identifiers

PMID26691201
PMCPMC4687334

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.