Linkage analysis in WE x SA cross.

<p><b>A.</b> LOD plot from linkage analysis using a nonparametric model for all traits with at least a single QTL. QTLs for the corresponding phenotype are: QTL1, Serine and Threonine; QTL2, Glutamic Acid; QTL3, Lysine and Tryptophane; QTL4, Phenylalanine and Tyrosine; QTL5, Aspartate and Glutamate; QTL6, Ammonium and Lysine; QTL7, Lysine; QTL8, Histidine; QTL9, Isoleucine, Serine, Tyrosine, Glutamine and Threonine; QTL10, Phenylalanine and Tyrosine. <b>B.</b> Amino Acid consumption levels in segregants carrying either WE or SA alleles for QTL XIII.527 underlying Isoleucine, Serine, Tyrosine, Glutamine and Threonine variation.</p

A Principal Component Analysis of ammonium and amino acid consumption variation across segregants.

<p>Repartition of the 14 amino acids and ammonium are shown on the PC1 and PC2 axis. PC1 explains 40% of the variation, while PC2 17%. Amino acids, Red: Non-polar, Blue: Polar uncharged side chain, Black: Polar positively charged side chain, Purple: Polar negatively charged side chain, Green: Aromatic.</p

Reciprocal hemizygosity analysis on <i>GHD2</i> and <i>GLT1</i> underlying consumption variation for Aspartic and Glutamic acid.

<p><b>A.</b> The hybrid hemizygote strains consumption levels (mg/L) for SA and WE <i>GDH2</i> reciprocal hemizygotes. <b>B.</b> Similarly, <i>GLT1</i> reciprocal hemizygosity assay. (*), (**) and (***) represents a significant statistical difference between the hemizygote strains for the same gene using ANOVA tests <i>P</i><0.05, <i>P</i><0.01 and <i>P</i><0.001 respectively. Δ/WE denotes hemizygotes carrying the WE allele, while SA/Δdenotes hemizygotes carrying the SA allele.</p

Consumption levels in parental strains and F1 hybrids of each nitrogen source.

<p>Amount of nitrogen source consumed (mg/L), the relative percentage respect to the initial amount, its relative contribution to the total amount of nitrogen consumed and ANOVA statistical analysis in parental and F1 hybrid strains are shown. R1 and R2 represent each individual replicate, % Initial refers to the amount consumed respect to the initial amount provided and % YAN refers to the amount consumed respect to the total nitrogen provided. Av = average.</p

Additional file 2 of Intravitreal allogeneic mesenchymal stem cells: a non-randomized phase II clinical trial for acute non-arteritic optic neuropathy

Additional file 2. Supplementary Table T1. Follow-up Schedul

Additional file 1 of Intravitreal allogeneic mesenchymal stem cells: a non-randomized phase II clinical trial for acute non-arteritic optic neuropathy

Additional file 1. TREND flow diagram

Table_1_Integration of Genetic and Cytogenetic Maps and Identification of Sex Chromosome in Garden Asparagus (Asparagus officinalis L.).pdf

<p>A genetic linkage map of dioecious garden asparagus (Asparagus officinalis L., 2n = 2x = 20) was constructed using F₁ population, simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers. In total, 1376 SNPs and 27 SSRs were used for genetic mapping. Two resulting parental maps contained 907 and 678 markers spanning 1947 and 1814 cM, for female and male parent, respectively, over ten linkage groups representing ten haploid chromosomes of the species. With the aim to anchor the ten genetic linkage groups to individual chromosomes and develop a tool to facilitate genome analysis and gene cloning, we have optimized a protocol for flow cytometric chromosome analysis and sorting in asparagus. The analysis of DAPI-stained suspensions of intact mitotic chromosomes by flow cytometry resulted in histograms of relative fluorescence intensity (flow karyotypes) comprising eight major peaks. The analysis of chromosome morphology and localization of 5S and 45S rDNA by FISH on flow-sorted chromosomes, revealed that four chromosomes (IV, V, VI, VIII) could be discriminated and sorted. Seventy-two SSR markers were used to characterize chromosome content of individual peaks on the flow karyotype. Out of them, 27 were included in the genetic linkage map and anchored genetic linkage groups to chromosomes. The sex determining locus was located on LG5, which was associated with peak V representing a chromosome with 5S rDNA locus. The results obtained in this study will support asparagus improvement by facilitating targeted marker development and gene isolation using flow-sorted chromosomes.</p

Image_1_Integration of Genetic and Cytogenetic Maps and Identification of Sex Chromosome in Garden Asparagus (Asparagus officinalis L.).pdf

<p>A genetic linkage map of dioecious garden asparagus (Asparagus officinalis L., 2n = 2x = 20) was constructed using F₁ population, simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers. In total, 1376 SNPs and 27 SSRs were used for genetic mapping. Two resulting parental maps contained 907 and 678 markers spanning 1947 and 1814 cM, for female and male parent, respectively, over ten linkage groups representing ten haploid chromosomes of the species. With the aim to anchor the ten genetic linkage groups to individual chromosomes and develop a tool to facilitate genome analysis and gene cloning, we have optimized a protocol for flow cytometric chromosome analysis and sorting in asparagus. The analysis of DAPI-stained suspensions of intact mitotic chromosomes by flow cytometry resulted in histograms of relative fluorescence intensity (flow karyotypes) comprising eight major peaks. The analysis of chromosome morphology and localization of 5S and 45S rDNA by FISH on flow-sorted chromosomes, revealed that four chromosomes (IV, V, VI, VIII) could be discriminated and sorted. Seventy-two SSR markers were used to characterize chromosome content of individual peaks on the flow karyotype. Out of them, 27 were included in the genetic linkage map and anchored genetic linkage groups to chromosomes. The sex determining locus was located on LG5, which was associated with peak V representing a chromosome with 5S rDNA locus. The results obtained in this study will support asparagus improvement by facilitating targeted marker development and gene isolation using flow-sorted chromosomes.</p

Table_4_GPD1 and ADH3 Natural Variants Underlie Glycerol Yield Differences in Wine Fermentation.XLSX

<p>Glycerol is one of the most important by-products of alcohol fermentation, and depending on its concentration it can contribute to wine flavor intensity and aroma volatility. Here, we evaluated the potential of utilizing the natural genetic variation of non-coding regions in budding yeast to identify allelic variants that could modulate glycerol phenotype during wine fermentation. For this we utilized four Saccharomyces cerevisiae strains (WE - Wine/European, SA – Sake, NA – North American, and WA – West African), which were previously profiled for genome-wide Allele Specific Expression (ASE) levels. The glycerol yields under Synthetic Wine Must (SWM) fermentations differed significantly between strains; WA produced the highest glycerol yields while SA produced the lowest yields. Subsequently, from our ASE database, we identified two candidate genes involved in alcoholic fermentation pathways, ADH3 and GPD1, exhibiting significant expression differences between strains. A reciprocal hemizygosity assay demonstrated that hemizygotes expressing GPD1^WA, GPD1^SA, ADH3^WA and ADH3^SA alleles had significantly greater glycerol yields compared to GPD1^WE and ADH3^WE. We further analyzed the gene expression profiles for each GPD1 variant under SWM, demonstrating that the expression of GPD1^WE occurred earlier and was greater compared to the other alleles. This result indicates that the level, timing, and condition of expression differ between regulatory regions in the various genetic backgrounds. Furthermore, promoter allele swapping demonstrated that these allele expression patterns were transposable across genetic backgrounds; however, glycerol yields did not differ between wild type and modified strains, suggesting a strong trans effect on GPD1 gene expression. In this line, Gpd1 protein levels in parental strains, particularly Gpd1p^WE, did not necessarily correlate with gene expression differences, but rather with glycerol yield where low Gpd1p^WE levels were detected. This suggests that GPD1^WE is influenced by recessive negative post-transcriptional regulation which is absent in the other genetic backgrounds. This dissection of regulatory mechanisms in GPD1 allelic variants demonstrates the potential to exploit natural alleles to improve glycerol production in wine fermentation and highlights the difficulties of trait improvement due to alternative trans-regulation and gene-gene interactions in the different genetic background.</p

Table_1_GPD1 and ADH3 Natural Variants Underlie Glycerol Yield Differences in Wine Fermentation.XLSX

<p>Glycerol is one of the most important by-products of alcohol fermentation, and depending on its concentration it can contribute to wine flavor intensity and aroma volatility. Here, we evaluated the potential of utilizing the natural genetic variation of non-coding regions in budding yeast to identify allelic variants that could modulate glycerol phenotype during wine fermentation. For this we utilized four Saccharomyces cerevisiae strains (WE - Wine/European, SA – Sake, NA – North American, and WA – West African), which were previously profiled for genome-wide Allele Specific Expression (ASE) levels. The glycerol yields under Synthetic Wine Must (SWM) fermentations differed significantly between strains; WA produced the highest glycerol yields while SA produced the lowest yields. Subsequently, from our ASE database, we identified two candidate genes involved in alcoholic fermentation pathways, ADH3 and GPD1, exhibiting significant expression differences between strains. A reciprocal hemizygosity assay demonstrated that hemizygotes expressing GPD1^WA, GPD1^SA, ADH3^WA and ADH3^SA alleles had significantly greater glycerol yields compared to GPD1^WE and ADH3^WE. We further analyzed the gene expression profiles for each GPD1 variant under SWM, demonstrating that the expression of GPD1^WE occurred earlier and was greater compared to the other alleles. This result indicates that the level, timing, and condition of expression differ between regulatory regions in the various genetic backgrounds. Furthermore, promoter allele swapping demonstrated that these allele expression patterns were transposable across genetic backgrounds; however, glycerol yields did not differ between wild type and modified strains, suggesting a strong trans effect on GPD1 gene expression. In this line, Gpd1 protein levels in parental strains, particularly Gpd1p^WE, did not necessarily correlate with gene expression differences, but rather with glycerol yield where low Gpd1p^WE levels were detected. This suggests that GPD1^WE is influenced by recessive negative post-transcriptional regulation which is absent in the other genetic backgrounds. This dissection of regulatory mechanisms in GPD1 allelic variants demonstrates the potential to exploit natural alleles to improve glycerol production in wine fermentation and highlights the difficulties of trait improvement due to alternative trans-regulation and gene-gene interactions in the different genetic background.</p