40
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Relationship, evolutionary fate and function of two maize co-orthologs of rice GW2 associated with kernel size and weight

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          In rice, the GW2 gene, found on chromosome 2, controls grain width and weight. Two homologs of this gene, ZmGW2-CHR4 and ZmGW2-CHR5, have been found in maize. In this study, we investigated the relationship, evolutionary fate and putative function of these two maize genes.

          Results

          The two genes are located on duplicated maize chromosomal regions that show co-orthologous relationships with the rice region containing GW2. ZmGW2-CHR5 is more closely related to the sorghum counterpart than to ZmGW2-CHR4. Sequence comparisons between the two genes in eight diverse maize inbred lines revealed that the functional protein domain of both genes is completely conserved, with no non-synonymous polymorphisms identified. This suggests that both genes may have conserved functions, a hypothesis that was further confirmed through linkage, association, and expression analyses. Linkage analysis showed that ZmGW2-CHR4 is located within a consistent quantitative trait locus (QTL) for one-hundred kernel weight (HKW). Association analysis with a diverse panel of 121 maize inbred lines identified one single nucleotide polymorphism (SNP) in the promoter region of ZmGW2-CHR4 that was significantly associated with kernel width (KW) and HKW across all three field experiments examined in this study. SNPs or insertion/deletion polymorphisms (InDels) in other regions of ZmGW2-CHR4 and ZmGW2-CHR5 were also found to be significantly associated with at least one of the four yield-related traits (kernel length (KL), kernel thickness (KT), KW and HKW). None of the polymorphisms in either maize gene are similar to each other or to the 1 bp InDel causing phenotypic variation in rice. Expression levels of both maize genes vary over ear and kernel developmental stages, and the expression level of ZmGW2-CHR4 is significantly negatively correlated with KW.

          Conclusions

          The sequence, linkage, association and expression analyses collectively showed that the two maize genes represent chromosomal duplicates, both of which function to control some of the phenotypic variation for kernel size and weight in maize, as does their counterpart in rice. However, the different polymorphisms identified in the two maize genes and in the rice gene indicate that they may cause phenotypic variation through different mechanisms.

          Related collections

          Most cited references46

          • Record: found
          • Abstract: not found
          • Article: not found

          MEGA3: Integrated software for Molecular Evolutionary Genetics Analysis and sequence alignment.

          S. KUMAR (2004)
          With its theoretical basis firmly established in molecular evolutionary and population genetics, the comparative DNA and protein sequence analysis plays a central role in reconstructing the evolutionary histories of species and multigene families, estimating rates of molecular evolution, and inferring the nature and extent of selective forces shaping the evolution of genes and genomes. The scope of these investigations has now expanded greatly owing to the development of high-throughput sequencing techniques and novel statistical and computational methods. These methods require easy-to-use computer programs. One such effort has been to produce Molecular Evolutionary Genetics Analysis (MEGA) software, with its focus on facilitating the exploration and analysis of the DNA and protein sequence variation from an evolutionary perspective. Currently in its third major release, MEGA3 contains facilities for automatic and manual sequence alignment, web-based mining of databases, inference of the phylogenetic trees, estimation of evolutionary distances and testing evolutionary hypotheses. This paper provides an overview of the statistical methods, computational tools, and visual exploration modules for data input and the results obtainable in MEGA.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            A draft sequence of the rice genome (Oryza sativa L. ssp. indica).

            J. Yu (2002)
            We have produced a draft sequence of the rice genome for the most widely cultivated subspecies in China, Oryza sativa L. ssp. indica, by whole-genome shotgun sequencing. The genome was 466 megabases in size, with an estimated 46,022 to 55,615 genes. Functional coverage in the assembled sequences was 92.0%. About 42.2% of the genome was in exact 20-nucleotide oligomer repeats, and most of the transposons were in the intergenic regions between genes. Although 80.6% of predicted Arabidopsis thaliana genes had a homolog in rice, only 49.4% of predicted rice genes had a homolog in A. thaliana. The large proportion of rice genes with no recognizable homologs is due to a gradient in the GC content of rice coding sequences.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Cytokinin oxidase regulates rice grain production.

              Most agriculturally important traits are regulated by genes known as quantitative trait loci (QTLs) derived from natural allelic variations. We here show that a QTL that increases grain productivity in rice, Gn1a, is a gene for cytokinin oxidase/dehydrogenase (OsCKX2), an enzyme that degrades the phytohormone cytokinin. Reduced expression of OsCKX2 causes cytokinin accumulation in inflorescence meristems and increases the number of reproductive organs, resulting in enhanced grain yield. QTL pyramiding to combine loci for grain number and plant height in the same genetic background generated lines exhibiting both beneficial traits. These results provide a strategy for tailormade crop improvement.
                Bookmark

                Author and article information

                Journal
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central
                1471-2229
                2010
                14 July 2010
                : 10
                : 143
                Affiliations
                [1 ]National Maize Improvement Center of China, Key Laboratory of Crop Genomics and Genetic Improvement (Ministry of Agriculture), China Agricultural University, 100193 Beijing, China
                [2 ]USDA-ARS Corn Host Plant Resistance Research Unit Box 9555 Mississippi State, MS 39762
                [3 ]College of Agriculture, Xinjiang Agricultural University, Urumqi, 830052 Xinjiang, China
                [4 ]International Maize and Wheat Improvement Center (CIMMYT), Apdo. Postal 6-641, 06600 Mexico, D.F., Mexico
                Article
                1471-2229-10-143
                10.1186/1471-2229-10-143
                3017803
                20626916
                2102f22e-960a-4027-8cf3-4927cee8e7f2
                Copyright ©2010 Li et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 31 January 2010
                : 14 July 2010
                Categories
                Research Article

                Plant science & Botany
                Plant science & Botany

                Comments

                Comment on this article