Flowering time variation association enrichment LOD scores comparison in different curation categories.

<p>1: maize flowering time orthologs; 2: maize leaf genes (in Feng <i>et </i><i>al</i>. 2010); 3: maize miRNA target leaf genes; 4: biosynthetic process (GO:0009058); 5: developmental process (GO:0032502); 6: enzyme regulator activity (GO:0030234); 7: growth (GO:0040007); 8: negative regulation of response to stimulus (GO:0048585); 9: positive regulation of response to stimulus (GO:0050729) and 10: transcription regulator activity (GO:0030528). GO terms in 6 and 10 are from molecular function GO terms, while the rest of the GO terms come from biological process.</p

Maize flowering time priori candidate genes.

<p>Maize flowering time priori candidate genes are identified via enrichment of GWAS associations; and, the annotations are taken from their orthologous relationship to <i>Arabidopsis</i> genes.</p

The distribution of allelic effects in maize days-to-silk associations. The unit of allelic effect is in day(s).

<p>The distribution of allelic effects in maize days-to-silk associations. The unit of allelic effect is in day(s).</p

The comparison of estimated linkage block sizes with perfect linkage (<i>r²</i> = 1), high linkage (1><i>r²</i>≥0.8), intermediate linkage (1><i>r²</i>≥0.6 and 0.4) and low linkage (1><i>r²</i>≥0.2).

<p>The comparison of estimated linkage block sizes with perfect linkage (<i>r²</i> = 1), high linkage (1><i>r²</i>≥0.8), intermediate linkage (1><i>r²</i>≥0.6 and 0.4) and low linkage (1><i>r²</i>≥0.2).</p

Averaged positive and negative allelic effects and their standard deviations in tropical versus temperate NAM populations.

<p>Averaged positive and negative allelic effects and their standard deviations in tropical versus temperate NAM populations.</p

Maize flowering time related homologs, resulted from the comparison between <i>Arabidopsis</i> and maize genes by Compara pipeline.

<p>Maize flowering time related homologs, resulted from the comparison between <i>Arabidopsis</i> and maize genes by Compara pipeline.</p

SNPs, GWAS associations, flowering time homologs and gene density on maize chromosome 3.

<p>In (a), the top panel shows the days-to-silk GWAS signals; blue triangles are the positive QTLs, the red are negative ones and the light blue ones at the bottom indicative of insignificant SNPs that did not pass RMIP test. SNP density along the chromosome is in grey bars in the background and significance level of RIMP scores is in the axis on the left. The gene density, calculated from the number of maize gene in every 200K bp, are in the lower panel, while the black triangles on the bottom of the density distribution mark the positions of maize flowering time homologs. Two dashed vertical lines indicate the positions of the examples in two top enriched flowering time maize homologs. (b) The enrichment of maize flowering time priori candidate: GRMZM2G115960. In this case, the co-localizing significant QTLs found in GWAS are all within the linkage block of the <i>a priori</i> candidate. (c) The enrichment of maize flowering time priori candidate: GRMZM2G365688. Three (solid red dots) of 6 significantly QTLs reside within linkage block of <i>a priori</i> candidate; the 3 unfilled red dots outside of the dashed red lines are significant, but unlinked, GWAS associations, while black dots being maize Hapmap 1 SNPs.</p

The distribution of association QTLs across NAM families.

<p>NAM GWAS associations identify a few cases of family specific QTL, while QTL found in previous joint-linkage analysis are mostly shared by 7 or 8 families.</p

131021 Genomics assisted ancestry deconvolution in grape

Genome-wide SNP data for grapevine samples (Vitis) used for ancestry estimation. Sample IDs for individuals used as ancestral populations and interspecific hybrids. Scripts used for simulating interspecific hybrids using the genotype data

Genomics Assisted Ancestry Deconvolution in Grape

<div><p>The genus <i>Vitis</i> (the grapevine) is a group of highly diverse, diploid woody perennial vines consisting of approximately 60 species from across the northern hemisphere. It is the world’s most valuable horticultural crop with ~8 million hectares planted, most of which is processed into wine. To gain insights into the use of wild <i>Vitis</i> species during the past century of interspecific grape breeding and to provide a foundation for marker-assisted breeding programmes, we present a principal components analysis (PCA) based ancestry estimation method to calculate admixture proportions of hybrid grapes in the United States Department of Agriculture grape germplasm collection using genome-wide polymorphism data. We find that grape breeders have backcrossed to both the domesticated <i>V. vinifera</i> and wild <i>Vitis</i> species and that reasonably accurate genome-wide ancestry estimation can be performed on interspecific <i>Vitis</i> hybrids using a panel of fewer than 50 ancestry informative markers (AIMs). We compare measures of ancestry informativeness used in selecting SNP panels for two-way admixture estimation, and verify the accuracy of our method on simulated populations of admixed offspring. Our method of ancestry deconvolution provides a first step towards selection at the seed or seedling stage for desirable admixture profiles, which will facilitate marker-assisted breeding that aims to introgress traits from wild <i>Vitis</i> species while retaining the desirable characteristics of elite <i>V. vinifera</i> cultivars. </p> </div