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Sequence diversity in coding regions of candidate genes in the glycoalkaloid biosynthetic pathway of wild potato species.

Manrique-Carpintero NC, Tokuhisa JG, Ginzberg I, Holliday JA, Veilleux RE - G3 (Bethesda) (2013)

Bottom Line: More polymorphisms were found in introns than exons and in genes of secondary compared to primary metabolism.Although no significant deviation from neutrality was found, dN/dS ratios < 1 and negative values of Tajima's D test suggested purifying selection and genetic hitchhiking in the gene fragments.These results can be used to evaluate SGA accumulation in segregating or association mapping populations.

View Article: PubMed Central - PubMed

Affiliation: Department of Horticulture, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061.

ABSTRACT
Natural variation in five candidate genes of the steroidal glycoalkaloid (SGA) metabolic pathway and whole-genome single nucleotide polymorphism (SNP) genotyping were studied in six wild [Solanum chacoense (chc 80-1), S. commersonii, S. demissum, S. sparsipilum, S. spegazzinii, S. stoloniferum] and cultivated S. tuberosum Group Phureja (phu DH) potato species with contrasting levels of SGAs. Amplicons were sequenced for five candidate genes: 3-hydroxy-3-methylglutaryl coenzyme A reductase 1 and 2 (HMG1, HMG2) and 2.3-squalene epoxidase (SQE) of primary metabolism, and solanidine galactosyltransferase (SGT1), and glucosyltransferase (SGT2) of secondary metabolism. SNPs (n = 337) producing 354 variations were detected within 3.7 kb of sequenced DNA. More polymorphisms were found in introns than exons and in genes of secondary compared to primary metabolism. Although no significant deviation from neutrality was found, dN/dS ratios < 1 and negative values of Tajima's D test suggested purifying selection and genetic hitchhiking in the gene fragments. In addition, patterns of dN/dS ratios across the SGA pathway suggested constraint by natural selection. Comparison of nucleotide diversity estimates and dN/dS ratios showed stronger selective constraints for genes of primary rather than secondary metabolism. SNPs (n = 24) with an exclusive genotype for either phu DH (low SGA) or chc 80-1 (high SGA) were identified for HMG2, SQE, SGT1 and SGT2. The SolCAP 8303 Illumina Potato SNP chip genotyping revealed eight informative SNPs on six pseudochromosomes, with homozygous and heterozygous genotypes that discriminated high, intermediate and low levels of SGA accumulation. These results can be used to evaluate SGA accumulation in segregating or association mapping populations.

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Predicted protein structure modifications resulting from amino acid changes and indel polymorphisms in phu DH and chc 80-1 allelic sequences of SGT2. The three aa indel in phu DH in the red colloidal is the most evident modifications beside the other four aa changes that differentiate both sequences.
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fig2: Predicted protein structure modifications resulting from amino acid changes and indel polymorphisms in phu DH and chc 80-1 allelic sequences of SGT2. The three aa indel in phu DH in the red colloidal is the most evident modifications beside the other four aa changes that differentiate both sequences.

Mentions: To determine potential associations between informative SNPs and SGA accumulation in the potato accessions, we conducted ANOVAs on the logarithm of averages of total SGA levels estimated per accession using allelic variants for SNPs identified in exons of candidate gene fragments as the source of variation (Table 7). Then haplotype clusters were built per SNP genotype, their accessions and total SGA levels, to identify clusters holding mainly low or high SGA accessions within a single SNP genotype. Since the significant SNPs identified by ANOVA were the most likely to be informative, we analyzed them first and used their pattern to identify other informative SNPs. For HMG1, 19 polymorphic SNPs were in our potato species, none of which was statistically significant for association with SGA accumulation, nor was there a SNP genotype cluster associated with high or low SGA accessions. From the 20 polymorphic SNPs in HMG2 a set of three nonsynonymous SNPs could explain different levels of SGA accumulation. HMG2_snp_202 was an informative SNP identified by ANOVA (P < 0.001*), which separated phu DH, which did not produce SGAs from the other individuals. The different alleles of HMG2_snp_202 would be expected to code for either serine, a polar amino acid, or alanine, a nonpolar amino acid. HMG2_snp_128 and 199 separated the highest SGA producer, chc 80-1, from the other samples, with codons specifying either arginine/lysine (both polar) or alanine/serine, with different polarity. One SNP (SQE_snp_220) of 22 that were polymorphic in SQE was potentially associated with SGA accumulation (P < 0.001*). This SNP is nonsynonymous, specifying a change from lysine to glutamine, both polar amino acids, and separated phu DH from the other samples. SGT1 had 106 polymorphic SNPs and for 11 the SGA accumulation levels showed significant differences among SNP genotypes with P < 0.006. Seven were nonsynonymous, specifying amino acids with similar polarity, and four were synonymous. The 11 SNPs (SGT1_snp_171, 210, 249, 250, 255, 408, 415, 435, 612, 666, and 714) were mainly heterozygous in phu DH and homozygous for all other individuals, with the exception of two that were also heterozygous in 1-2 other individuals. Three SNPs (SGT1_snp_210, 256, and 549) that were heterozygous for the greatest SGA producer, chc 80-1, separated it from all other individuals. SNP SGT1_snp_210 was detected by ANOVA, whereas the other two were found during the cluster analysis. All of them were nonsynonymous, specifying amino acids changes of similar polarity, lysine by asparagine, aspartic acid by glutamic acid and different polarity, and glycine by arginine (SGT1_snp_256). In SGT2 there were 53 polymorphic SNPs, and seven were putatively associated with SGA accumulation. We observed only two homozygous genotypes for six of these SNPs in our germplasm panel, whereas there were four possible different homozygotes for SGT2_snp_264. Four of these SNPs were nonsynonymous and three synonymous; two of the nonsynonymous changed from polar to non-polar and the other two kept same the polarity. Four SNPs (SGT2_snp_126, 264, 396 and 404) with an exclusive genotype for phu DH separated it from other accessions. These SNPs were detected by ANOVA, two were synonymous and two nonsynonymous specifying changes of glutamine by histidine and serine by leucine. Four SNPs (SGT2_snp_10, 11, 76 and 404) exhibited a specific genotype for chc 80-1. Two produced amino acid changes in chc 80-1 from glutamic acid to tryptophan and valine to isoleucine, and two were synonymous. A comparison of protein models of SGT2 using either the chc or phu amplicons to specify aa from positions 197-385 and the S. tuberosum aa profile to complete the 482 aa protein yielded models with different secondary structure (Figure 2). In general the SNPs at candidate genes did not cluster accessions with similar levels of SGA accumulation, but were able to discriminate no synthesis in phu DH and the greatest accumulator of SGAs, chc 80-1. Some of these informative SNPs can be used as tag SNPs to screen segregating populations.


Sequence diversity in coding regions of candidate genes in the glycoalkaloid biosynthetic pathway of wild potato species.

Manrique-Carpintero NC, Tokuhisa JG, Ginzberg I, Holliday JA, Veilleux RE - G3 (Bethesda) (2013)

Predicted protein structure modifications resulting from amino acid changes and indel polymorphisms in phu DH and chc 80-1 allelic sequences of SGT2. The three aa indel in phu DH in the red colloidal is the most evident modifications beside the other four aa changes that differentiate both sequences.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3755908&req=5

fig2: Predicted protein structure modifications resulting from amino acid changes and indel polymorphisms in phu DH and chc 80-1 allelic sequences of SGT2. The three aa indel in phu DH in the red colloidal is the most evident modifications beside the other four aa changes that differentiate both sequences.
Mentions: To determine potential associations between informative SNPs and SGA accumulation in the potato accessions, we conducted ANOVAs on the logarithm of averages of total SGA levels estimated per accession using allelic variants for SNPs identified in exons of candidate gene fragments as the source of variation (Table 7). Then haplotype clusters were built per SNP genotype, their accessions and total SGA levels, to identify clusters holding mainly low or high SGA accessions within a single SNP genotype. Since the significant SNPs identified by ANOVA were the most likely to be informative, we analyzed them first and used their pattern to identify other informative SNPs. For HMG1, 19 polymorphic SNPs were in our potato species, none of which was statistically significant for association with SGA accumulation, nor was there a SNP genotype cluster associated with high or low SGA accessions. From the 20 polymorphic SNPs in HMG2 a set of three nonsynonymous SNPs could explain different levels of SGA accumulation. HMG2_snp_202 was an informative SNP identified by ANOVA (P < 0.001*), which separated phu DH, which did not produce SGAs from the other individuals. The different alleles of HMG2_snp_202 would be expected to code for either serine, a polar amino acid, or alanine, a nonpolar amino acid. HMG2_snp_128 and 199 separated the highest SGA producer, chc 80-1, from the other samples, with codons specifying either arginine/lysine (both polar) or alanine/serine, with different polarity. One SNP (SQE_snp_220) of 22 that were polymorphic in SQE was potentially associated with SGA accumulation (P < 0.001*). This SNP is nonsynonymous, specifying a change from lysine to glutamine, both polar amino acids, and separated phu DH from the other samples. SGT1 had 106 polymorphic SNPs and for 11 the SGA accumulation levels showed significant differences among SNP genotypes with P < 0.006. Seven were nonsynonymous, specifying amino acids with similar polarity, and four were synonymous. The 11 SNPs (SGT1_snp_171, 210, 249, 250, 255, 408, 415, 435, 612, 666, and 714) were mainly heterozygous in phu DH and homozygous for all other individuals, with the exception of two that were also heterozygous in 1-2 other individuals. Three SNPs (SGT1_snp_210, 256, and 549) that were heterozygous for the greatest SGA producer, chc 80-1, separated it from all other individuals. SNP SGT1_snp_210 was detected by ANOVA, whereas the other two were found during the cluster analysis. All of them were nonsynonymous, specifying amino acids changes of similar polarity, lysine by asparagine, aspartic acid by glutamic acid and different polarity, and glycine by arginine (SGT1_snp_256). In SGT2 there were 53 polymorphic SNPs, and seven were putatively associated with SGA accumulation. We observed only two homozygous genotypes for six of these SNPs in our germplasm panel, whereas there were four possible different homozygotes for SGT2_snp_264. Four of these SNPs were nonsynonymous and three synonymous; two of the nonsynonymous changed from polar to non-polar and the other two kept same the polarity. Four SNPs (SGT2_snp_126, 264, 396 and 404) with an exclusive genotype for phu DH separated it from other accessions. These SNPs were detected by ANOVA, two were synonymous and two nonsynonymous specifying changes of glutamine by histidine and serine by leucine. Four SNPs (SGT2_snp_10, 11, 76 and 404) exhibited a specific genotype for chc 80-1. Two produced amino acid changes in chc 80-1 from glutamic acid to tryptophan and valine to isoleucine, and two were synonymous. A comparison of protein models of SGT2 using either the chc or phu amplicons to specify aa from positions 197-385 and the S. tuberosum aa profile to complete the 482 aa protein yielded models with different secondary structure (Figure 2). In general the SNPs at candidate genes did not cluster accessions with similar levels of SGA accumulation, but were able to discriminate no synthesis in phu DH and the greatest accumulator of SGAs, chc 80-1. Some of these informative SNPs can be used as tag SNPs to screen segregating populations.

Bottom Line: More polymorphisms were found in introns than exons and in genes of secondary compared to primary metabolism.Although no significant deviation from neutrality was found, dN/dS ratios < 1 and negative values of Tajima's D test suggested purifying selection and genetic hitchhiking in the gene fragments.These results can be used to evaluate SGA accumulation in segregating or association mapping populations.

View Article: PubMed Central - PubMed

Affiliation: Department of Horticulture, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061.

ABSTRACT
Natural variation in five candidate genes of the steroidal glycoalkaloid (SGA) metabolic pathway and whole-genome single nucleotide polymorphism (SNP) genotyping were studied in six wild [Solanum chacoense (chc 80-1), S. commersonii, S. demissum, S. sparsipilum, S. spegazzinii, S. stoloniferum] and cultivated S. tuberosum Group Phureja (phu DH) potato species with contrasting levels of SGAs. Amplicons were sequenced for five candidate genes: 3-hydroxy-3-methylglutaryl coenzyme A reductase 1 and 2 (HMG1, HMG2) and 2.3-squalene epoxidase (SQE) of primary metabolism, and solanidine galactosyltransferase (SGT1), and glucosyltransferase (SGT2) of secondary metabolism. SNPs (n = 337) producing 354 variations were detected within 3.7 kb of sequenced DNA. More polymorphisms were found in introns than exons and in genes of secondary compared to primary metabolism. Although no significant deviation from neutrality was found, dN/dS ratios < 1 and negative values of Tajima's D test suggested purifying selection and genetic hitchhiking in the gene fragments. In addition, patterns of dN/dS ratios across the SGA pathway suggested constraint by natural selection. Comparison of nucleotide diversity estimates and dN/dS ratios showed stronger selective constraints for genes of primary rather than secondary metabolism. SNPs (n = 24) with an exclusive genotype for either phu DH (low SGA) or chc 80-1 (high SGA) were identified for HMG2, SQE, SGT1 and SGT2. The SolCAP 8303 Illumina Potato SNP chip genotyping revealed eight informative SNPs on six pseudochromosomes, with homozygous and heterozygous genotypes that discriminated high, intermediate and low levels of SGA accumulation. These results can be used to evaluate SGA accumulation in segregating or association mapping populations.

Show MeSH