Literature DB >> 27898771

Dissection of Genetic Factors underlying Wheat Kernel Shape and Size in an Elite × Nonadapted Cross using a High Density SNP Linkage Map.

Ajay Kumar, E E Mantovani, R Seetan, A Soltani, M Echeverry-Solarte, S Jain, S Simsek, D Doehlert, M S Alamri, E M Elias, S F Kianian, M Mergoum.   

Abstract

Wheat kernel shape and size has been under selection since early domestication. Kernel morphology is a major consideration in wheat breeding, as it impacts grain yield and quality. A population of 160 recombinant inbred lines (RIL), developed using an elite (ND 705) and a nonadapted genotype (PI 414566), was extensively phenotyped in replicated field trials and genotyped using Infinium iSelect 90K assay to gain insight into the genetic architecture of kernel shape and size. A high density genetic map consisting of 10,172 single nucleotide polymorphism (SNP) markers, with an average marker density of 0.39 cM/marker, identified a total of 29 genomic regions associated with six grain shape and size traits; ∼80% of these regions were associated with multiple traits. The analyses showed that kernel length (KL) and width (KW) are genetically independent, while a large number (∼59%) of the quantitative trait loci (QTL) for kernel shape traits were in common with genomic regions associated with kernel size traits. The most significant QTL was identified on chromosome 4B, and could be an ortholog of major rice grain size and shape gene or . Major and stable loci also were identified on the homeologous regions of Group 5 chromosomes, and in the regions of (6A) and (7A) genes. Both parental genotypes contributed equivalent positive QTL alleles, suggesting that the nonadapted germplasm has a great potential for enhancing the gene pool for grain shape and size. This study provides new knowledge on the genetic dissection of kernel morphology, with a much higher resolution, which may aid further improvement in wheat yield and quality using genomic tools.
Copyright © 2016 Crop Science Society of America.

Entities:  

Mesh:

Year:  2016        PMID: 27898771     DOI: 10.3835/plantgenome2015.09.0081

Source DB:  PubMed          Journal:  Plant Genome        ISSN: 1940-3372            Impact factor:   4.089


  28 in total

1.  QTL mapping for some grain traits in bread wheat (Triticum aestivum L.).

Authors:  Supriya Kumari; Vandana Jaiswal; Vinod Kumar Mishra; Rajneesh Paliwal; Harindra Singh Balyan; Pushpendra Kumar Gupta
Journal:  Physiol Mol Biol Plants       Date:  2018-06-01

2.  Genomic Regions From an Iranian Landrace Increase Kernel Size in Durum Wheat.

Authors:  Francesca Desiderio; Leila Zarei; Stefania Licciardello; Kianoosh Cheghamirza; Ezatollah Farshadfar; Nino Virzi; Fabiola Sciacca; Paolo Bagnaresi; Raffaella Battaglia; Davide Guerra; Massimo Palumbo; Luigi Cattivelli; Elisabetta Mazzucotelli
Journal:  Front Plant Sci       Date:  2019-04-18       Impact factor: 5.753

3.  Relationship between QTL for grain shape, grain weight, test weight, milling yield, and plant height in the spring wheat cross RL4452/'AC Domain'.

Authors:  Adrian L Cabral; Mark C Jordan; Gary Larson; Daryl J Somers; D Gavin Humphreys; Curt A McCartney
Journal:  PLoS One       Date:  2018-01-22       Impact factor: 3.240

4.  Genotyping-by-Sequencing Derived High-Density Linkage Map and its Application to QTL Mapping of Flag Leaf Traits in Bread Wheat.

Authors:  Waseem Hussain; P Stephen Baenziger; Vikas Belamkar; Mary J Guttieri; Jorge P Venegas; Amanda Easterly; Ahmed Sallam; Jesse Poland
Journal:  Sci Rep       Date:  2017-11-27       Impact factor: 4.379

5.  Effect of Co-segregating Markers on High-Density Genetic Maps and Prediction of Map Expansion Using Machine Learning Algorithms.

Authors:  Amidou N'Diaye; Jemanesh K Haile; D Brian Fowler; Karim Ammar; Curtis J Pozniak
Journal:  Front Plant Sci       Date:  2017-08-23       Impact factor: 5.753

6.  Global QTL Analysis Identifies Genomic Regions on Chromosomes 4A and 4B Harboring Stable Loci for Yield-Related Traits Across Different Environments in Wheat (Triticum aestivum L.).

Authors:  Panfeng Guan; Lahu Lu; Lijia Jia; Muhammad Rezaul Kabir; Jinbo Zhang; Tianyu Lan; Yue Zhao; Mingming Xin; Zhaorong Hu; Yingyin Yao; Zhongfu Ni; Qixin Sun; Huiru Peng
Journal:  Front Plant Sci       Date:  2018-04-25       Impact factor: 5.753

7.  Identification and Validation of a New Source of Low Grain Cadmium Accumulation in Durum Wheat.

Authors:  Atena Oladzad-Abbasabadi; Ajay Kumar; Seyed Pirseyedi; Evan Salsman; Marina Dobrydina; Roshan Sharma Poudel; Wesam A AbuHammad; Shiaoman Chao; Justin D Faris; Elias M Elias
Journal:  G3 (Bethesda)       Date:  2018-03-02       Impact factor: 3.154

8.  Identification of Main-Effect and Environmental Interaction QTL and Their Candidate Genes for Drought Tolerance in a Wheat RIL Population Between Two Elite Spring Cultivars.

Authors:  S M Hisam Al Rabbi; Ajay Kumar; Sepehr Mohajeri Naraghi; Suraj Sapkota; Mohammed S Alamri; Elias M Elias; Shahryar Kianian; Raed Seetan; Ali Missaoui; Shyam Solanki; Mohamed Mergoum
Journal:  Front Genet       Date:  2021-06-17       Impact factor: 4.599

9.  Utilization of a Wheat50K SNP Microarray-Derived High-Density Genetic Map for QTL Mapping of Plant Height and Grain Traits in Wheat.

Authors:  Dongyun Lv; Chuanliang Zhang; Rui Yv; Jianxin Yao; Jianhui Wu; Xiaopeng Song; Juntao Jian; Pengbo Song; Zeyuan Zhang; Dejun Han; Daojie Sun
Journal:  Plants (Basel)       Date:  2021-06-08

10.  Ubiquitin-related genes are differentially expressed in isogenic lines contrasting for pericarp cell size and grain weight in hexaploid wheat.

Authors:  Jemima Brinton; James Simmonds; Cristobal Uauy
Journal:  BMC Plant Biol       Date:  2018-01-25       Impact factor: 4.215

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.