Localization of the Rf3 restorer-of-fertility gene for maize S-type cytoplasmic male sterility

Title from PDF of title page (University of Missouri--Columbia, viewed on April 23, 2014).The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.VitaMaize S-type cytoplasmic male sterility (CMS-S) is a maternally inherited trait that prevents pollen grains from developing to maturity. CMS-S is associated with the high levels of a novel mitochondrial transcript, orf355/orf77. Cleavage of this RNA, mediated by the nuclear restorer Rf3, reverses the sterility. Rf3 was previously mapped on the long arm of chromosome 2. The goals of this research were to fine-map the locus and to identify Rf3 using a candidate gene approach. Genotyping of nearisogenic lines (NILs) mapped Rf3 to a 1.98 Mb region of 2L. Six candidate genes, all predicted to code for mitochondrially targeted pentatricopeptide repeat proteins (PPR), were PCR-amplified, sequenced, and compared from multiple Rf3-containing NILs and non-restoring rf3 inbreds. One PPR-Rf3 candidate gene had two consistent differences between multiple restoring and non-restoring lines. Gene expression in pre-emergent tassels from the fertility-restored and non-restored plants was compared. Within the 3 Mb region surrounding Rf3, 9 genes were differentially expressed between restoring and non-restoring lines, including genes that could code for an ATP-binding protein, an ATPase, and four PPR proteins. Although Rf3 has not yet been identified, this study has revealed five promising candidates.Includes bibliographical reference

The development and use of a molecular model for soybean maturity groups

Abstract Background Achieving appropriate maturity in a target environment is essential to maximizing crop yield potential. In soybean [Glycine max (L.) Merr.], the time to maturity is largely dependent on developmental response to dark periods. Once the critical photoperiod is reached, flowering is initiated and reproductive development proceeds. Therefore, soybean adaptation has been attributed to genetic changes and natural or artificial selection to optimize plant development in specific, narrow latitudinal ranges. In North America, these regions have been classified into twelve maturity groups (MG), with lower MG being shorter season than higher MG. Growing soybean lines not adapted to a particular environment typically results in poor growth and significant yield reductions. The objective of this study was to develop a molecular model for soybean maturity based on the alleles underlying the major maturity loci: E1, E2, and E3. Results We determined the allelic variation and diversity of the E maturity genes in a large collection of soybean landraces, North American ancestors, Chinese cultivars, North American cultivars or expired Plant Variety Protection lines, and private-company lines. The E gene status of accessions in the USDA Soybean Germplasm Collection with SoySNP50K Beadchip data was also predicted. We determined the E allelic combinations needed to adapt soybean to different MGs in the United States (US) and discovered a strong signal of selection for E genotypes released in North America, particularly the US and Canada. Conclusions The E gene maturity model proposed will enable plant breeders to more effectively transfer traits into different MGs and increase the overall efficiency of soybean breeding in the US and Canada. The powerful yet simple selection strategy for increasing soybean breeding efficiency can be used alone or to directly enhance genomic prediction/selection schemes. The results also revealed previously unrecognized aspects of artificial selection in soybean imposed by soybean breeders based on geography that highlights the need for plant breeding that is optimized for specific environments

Major Soybean Maturity Gene Haplotypes Revealed by SNPViz Analysis of 72 Sequenced Soybean Genomes

<div><p>In this Genomics Era, vast amounts of next-generation sequencing data have become publicly available for multiple genomes across hundreds of species. Analyses of these large-scale datasets can become cumbersome, especially when comparing nucleotide polymorphisms across many samples within a dataset and among different datasets or organisms. To facilitate the exploration of allelic variation and diversity, we have developed and deployed an in-house computer software to categorize and visualize these haplotypes. The SNPViz software enables users to analyze region-specific haplotypes from single nucleotide polymorphism (SNP) datasets for different sequenced genomes. The examination of allelic variation and diversity of important soybean [<i>Glycine max</i> (L.) Merr.] flowering time and maturity genes may provide additional insight into flowering time regulation and enhance researchers' ability to target soybean breeding for particular environments. For this study, we utilized two available soybean genomic datasets for a total of 72 soybean genotypes encompassing cultivars, landraces, and the wild species <i>Glycine soja</i>. The major soybean maturity genes <i>E1</i>, <i>E2</i>, <i>E3</i>, and <i>E4</i> along with the <i>Dt1</i> gene for plant growth architecture were analyzed in an effort to determine the number of major haplotypes for each gene, to evaluate the consistency of the haplotypes with characterized variant alleles, and to identify evidence of artificial selection. The results indicated classification of a small number of predominant haplogroups for each gene and important insights into possible allelic diversity for each gene within the context of known causative mutations. The software has both a stand-alone and web-based version and can be used to analyze other genes, examine additional soybean datasets, and view similar genome sequence and SNP datasets from other species.</p></div

Haplotype analysis of the <i>Dt1</i> gene region.

<p>The SNPViz clustering pictorial displayed the SNPs in an 8.6-kb region on chromosome 19, which included Glyma19g37890. Nucleotide polymorphisms were examined in A) the wild (black) and cultivated (red) lines from the Chinese collection and B) the NAM parents (blue). Details about the SNPViz clustering pictorial were described in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094150#pone-0094150-g001" target="_blank">Figure 1</a> legend.</p

Reported polymorphic alleles of major maturity genes with reference to the Williams 82 sequence.

1<p>Uppercase allele designations indicate the dominant functional versions of the gene. In each case, the recessive mutant version of the gene is earlier flowering and maturing than the functional dominant version of the gene. The Williams 82 genome contains an earlier maturing missense version of <i>E1</i> (<i>e1-as</i>; T15R compared to the wild-type functional <i>E1</i>) <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094150#pone.0094150-Xia1" target="_blank">[5]</a>. Allele names are taken or modified from the published descriptions for clarity.</p>2<p>The underlined alleles were identified and described in the literature but were not present in the two datasets used for this analysis.</p>3<p>Although the Williams 82 <i>E3</i> allele is considered functional, it was shown to contain an insertion in intron three consisting of transposable element-like sequences when compared to other functional <i>E3</i> alleles without the insertion in intron 3 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094150#pone.0094150-Watanabe2" target="_blank">[7]</a>. We herein denote the <i>E3</i> from Williams 82 as <i>E3</i> and the equivalently functional shorter <i>E3</i> allele as <i>E3 (short)</i>.</p

Maturity and growth determinate genotypes for wild soybean.

1<p><i>E3</i> and <i>E4</i> genotypes are not shown because the causative SNP was not identified in the data.</p

Haplotype analysis of the <i>E1</i> gene region.

<p>The SNPViz clustering pictorial displayed the SNPs in a 7.8-kb region on chromosome six, which included Glyma06g23026. UPGMA grouped samples by calculating their sequence identity to the reference, Williams 82. Each soybean line was represented by a column with nucleotides only shown for the reference. All base positions that are identical to the reference are white, those that are different are black, and positions with no data or missing data are gray. Since an annotation file was included in this analysis, the gene locations, DNA strand, and exon start and end site are shown to the right of SNP position. Nucleotide polymorphisms were examined in A) the wild (black) and cultivated (red) lines from the Chinese collection and B) the NAM parents (blue).</p

Maturity and growth determinate genotypes for the 41 NAM parents.

1<p>The <i>E4</i> genotype is not shown because the causative SNP was not identified in the data.</p>2<p>DNA was unavailable for <i>E3/e3</i> genotyping.</p

Haplotype analysis of the <i>E4</i> gene region.

<p>The SNPViz clustering pictorial displayed the SNPs in a 12.6-kb region on chromosome 20, which included Glyma20g22160. Nucleotide polymorphisms were examined in A) the wild (black) and cultivated (red) lines from the Chinese collection and B) the NAM parents (blue). Details about the SNPViz clustering pictorial were described in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0094150#pone-0094150-g001" target="_blank">Figure 1</a> legend.</p

Major flowering time/maturity genes present in the Williams 82 reference sequence and positions used around those genes for haplotype analysis.

1<p>Gene location based on the Williams 82 reference sequence Glyma1.1.</p>2<p>Gene location based on the Williams 82 reference sequence Glyma1.0.</p