14 research outputs found
Additional file 12: of Genomic consequences of selection and genome-wide association mapping in soybean
The list of phenotypes used in this study and summary of tested environments. (DOCX 19 kb
Supplementary figures and files
<p><b>Supplementary Figure 1</b> </p><p>Distribution of polymorphic
markers of POP1 and POP2 on the Williams82 reference genome (Wm82.a1.v1.1)</p>
<p>Red: polymorphic markers of POP1.
Green: polymorphic markers of POP2. Yellow: polymorphic markers in both POP1
and POP2<b></b></p><p></p><p><b>Supplementary
Figure 2</b></p>
<p>High density genetic linkage map
of POP1</p>
<p><b>Supplementary
Figure 3</b></p>
<p>High density genetic linkage map
of POP2</p><p><b>Supplementary_Datafile_1 </b><br></p><p>Data for parental lines</p><p><b>Supplementary_Datafile_2</b><br></p><p>Genotypic data for POP1</p><p><b>Supplementary_Datafile_3</b><br></p><p>Phenotypic data for POP1</p><p><b>Supplementary_Datafile_4</b><br></p><p>Genotypic data for POP2</p><p><b>Supplementary_Datafile_5</b><br></p><p>Phenotypic data for POP2</p><p><b>Supplementary Table 1</b></p><p>Linkage groups of POP1 and POP2
constructed using SoySNP6K beadchip</p><p></p
El Diario de Pontevedra : periódico liberal: Ano LI Número 15272 - 1937 setembro 29
The significant loci associated with flowering time and related candidate genes. (DOCX 27Â kb
Phenotypic Characterization and Genetic Dissection of Growth Period Traits in Soybean (<i>Glycine max</i>) Using Association Mapping
<div><p>The growth period traits are important traits that affect soybean yield. The insights into the genetic basis of growth period traits can provide theoretical basis for cultivated area division, rational distribution, and molecular breeding for soybean varieties. In this study, genome-wide association analysis (GWAS) was exploited to detect the quantitative trait loci (QTL) for number of days to flowering (ETF), number of days from flowering to maturity (FTM), and number of days to maturity (ETM) using 4032 single nucleotide polymorphism (SNP) markers with 146 cultivars mainly from Northeast China. Results showed that abundant phenotypic variation was presented in the population, and variation explained by genotype, environment, and genotype by environment interaction were all significant for each trait. The whole accessions could be clearly clustered into two subpopulations based on their genetic relatedness, and accessions in the same group were almost from the same province. GWAS based on the unified mixed model identified 19 significant SNPs distributed on 11 soybean chromosomes, 12 of which can be consistently detected in both planting densities, and 5 of which were pleotropic QTL. Of 19 SNPs, 7 SNPs located in or close to the previously reported QTL or genes controlling growth period traits. The QTL identified with high resolution in this study will enrich our genomic understanding of growth period traits and could then be explored as genetic markers to be used in genomic applications in soybean breeding.</p></div
Descriptive statistics of best linear unbiased predictors (BLUPs) for three traits in two planting densities.
<p>Descriptive statistics of best linear unbiased predictors (BLUPs) for three traits in two planting densities.</p
Manhattan plot from Q+K model across three traits in high density.
<p>ETF is for trait of number of days to flowering; FTM is for trait of number of days from flowering to maturity; and ETM is for trait of number of days to maturity.</p
Genetic relatedness based on 4032 SNPs.
<p>A is for neighbor-joining tree; and B is for principle coordinate analysis (PCA). “W+Number” is the accession number.</p
Correlation coefficients between three growth period traits across the four locations.
<p>Correlation coefficients between three growth period traits across the four locations.</p