Characterization of <i>Ferredoxin-Dependent Glutamine-Oxoglutarate Amidotransferase (Fd-GOGAT)</i> Genes and Their Relationship with Grain Protein Content QTL in Wheat

<div><p>Background</p><p>In higher plants, inorganic nitrogen is assimilated via the glutamate synthase cycle or GS-GOGAT pathway. GOGAT enzyme occurs in two distinct forms that use NADH (NADH-GOGAT) or Fd (Fd-GOGAT) as electron carriers. The goal of the present study was to characterize wheat <i>Fd-GOGAT</i> genes and to assess the linkage with grain protein content (GPC), an important quantitative trait controlled by multiple genes.</p><p>Results</p><p>We report the complete genomic sequences of the three homoeologous A, B and D Fd-GOGAT genes from hexaploid wheat (<i>Triticum aestivum</i>) and their localization and characterization. The gene is comprised of 33 exons and 32 introns for all the three homoeologues genes. The three genes show the same exon/intron number and size, with the only exception of a series of indels in intronic regions. The partial sequence of the Fd-GOGAT gene located on A genome was determined in two durum wheat (<i>Triticum turgidum</i> ssp. <i>durum</i>) cvs Ciccio and Svevo, characterized by different grain protein content. Genomic differences allowed the gene mapping in the centromeric region of chromosome 2A. QTL analysis was conducted in the Svevo×Ciccio RIL mapping population, previously evaluated in 5 different environments. The study co-localized the <i>Fd-GOGAT-A</i> gene with the marker GWM-339, identifying a significant major QTL for GPC.</p><p>Conclusions</p><p>The wheat Fd-GOGAT genes are highly conserved; both among the three homoeologous hexaploid wheat genes and in comparison with other plants. In durum wheat, an association was shown between the <i>Fd-GOGAT</i> allele of cv Svevo with increasing GPC - potentially useful in breeding programs.</p></div

Phylogenetic tree of GOGAT polypeptides.

<p>The mature polypeptides for Fd- and NADH-GOGAT from a selection of plants an green algae were aligned with Clustal W and a nearest-neighbour tree generated with MEGA5. All three wheat homoeologues for Fd-GOGAT are in blue and red for the NADH-GOGAT version.</p

Diagrammatic representation of the structure of <i>Fd-GOGAT</i> genes.

<p>The three homoeologous Fd-GOGAT genes of wheat cv Chinese Spring are shown. Exons are numbered boxes. Coding sequences are colored, non-coding sequences are uncoloured boxes. Introns are intervening lines. Intron 1 is indicated by the dotted line.</p

Plant Fd-GOGAT amino acid sequences.

<p>Four monocot and two dicot Fd-GOGAT amino acid sequences for the mature protein are aligned with Clustal V: Wheat (A genome; present report), <i>Brachypodium</i> (BRADI1G19080), Rice (Os07g46460), Maize (NM_001112223), <i>Arabidopsis</i> (CP002688), Soybean. (AK245357).</p

Grain protein QTLs.

<p>LOD score scan on chromosome 2A for QTLs associated with grain protein content. The significant scan for QTLs for each environment: A) mean across environments; B) Foggia 2006; C) Gaudiano 2006. The position and the name of molecular markers are shown on the chromosome along the horizontal axis. The LOD score scan was obtained by ICIM with highlights the markers used as cofactors. LOD stands for logarithm of the odds (to the base 10). A LOD score of three or more is generally considered significant - a LOD score of three means the odds are a thousand to one in favour of genetic linkage.</p

<i>Fd-GOGAT-A1</i> specific primer name, sequence and PCR condition used for SNPs detection.

<p>Each PCR starts with 5 min at 94°C, followed by 35 cycles of 1 min denaturation at 94°C, 1 min annealing at the specific annealing T° reported above, and 2 min elongation at 72°C, and ends with a final elongation of 20 min at 72°C.</p

Additional file 1: of DHPLC technology for high-throughput detection of mutations in a durum wheat TILLING population

Supplemental file S1. β-LCY gene sequences. (DOCX 12 kb

Table_1_Meta-QTL analysis and candidate genes for quality traits, mineral content, and abiotic-related traits in wild emmer.xlsx

Wild emmer (Triticum turgidum ssp. dicoccoides) genotypes were studied for their high-nutritional value and good tolerance to various types of stress; for this reason, several QTL (quantitative trait loci) studies have been conducted to find favorable alleles to be introgressed into modern wheat cultivars. Given the complexity of the QTL nature, their interaction with the environment, and other QTLs, a small number of genotypes have been used in wheat breeding programs. Meta-QTL (MQTL) analysis helps to simplify the existing QTL information, identifying stable genomic regions and possible candidate genes for further allele introgression. The study aimed to identify stable QTL regions across different environmental conditions and genetic backgrounds using the QTL information of the past 14 years for different traits in wild emmer based upon 17 independent studies. A total of 41 traits were classified as quality traits (16), mineral composition traits (11), abiotic-related traits (13), and disease-related traits (1). The analysis revealed 852 QTLs distributed across all 14 chromosomes of wild emmer, with an average of 61 QTLs per chromosome. Quality traits had the highest number of QTLs (35%), followed by mineral content (33%), abiotic-related traits (28%), and disease-related traits (4%). Grain protein content (GPC) and thousand kernel weight (TKW) were associated with most of the QTLs detected. A total of 43 MQTLs were identified, simplifying the information, and reducing the average confidence interval (CI) from 22.6 to 4.78 cM. These MQTLs were associated with multiple traits across different categories. Nine candidate genes were identified for several stable MQTLs, potentially contributing to traits such as quality, mineral content, and abiotic stress resistance. These genes play essential roles in various plant processes, such as carbohydrate metabolism, nitrogen assimilation, cell wall biogenesis, and cell wall extensibility. Overall, this study underscores the importance of considering MQTL analysis in wheat breeding programs, as it identifies stable genomic regions associated with multiple traits, offering potential solutions for improving wheat varieties under diverse environmental conditions.</p

Image_2_Meta-QTL analysis and candidate genes for quality traits, mineral content, and abiotic-related traits in wild emmer.jpg

Wild emmer (Triticum turgidum ssp. dicoccoides) genotypes were studied for their high-nutritional value and good tolerance to various types of stress; for this reason, several QTL (quantitative trait loci) studies have been conducted to find favorable alleles to be introgressed into modern wheat cultivars. Given the complexity of the QTL nature, their interaction with the environment, and other QTLs, a small number of genotypes have been used in wheat breeding programs. Meta-QTL (MQTL) analysis helps to simplify the existing QTL information, identifying stable genomic regions and possible candidate genes for further allele introgression. The study aimed to identify stable QTL regions across different environmental conditions and genetic backgrounds using the QTL information of the past 14 years for different traits in wild emmer based upon 17 independent studies. A total of 41 traits were classified as quality traits (16), mineral composition traits (11), abiotic-related traits (13), and disease-related traits (1). The analysis revealed 852 QTLs distributed across all 14 chromosomes of wild emmer, with an average of 61 QTLs per chromosome. Quality traits had the highest number of QTLs (35%), followed by mineral content (33%), abiotic-related traits (28%), and disease-related traits (4%). Grain protein content (GPC) and thousand kernel weight (TKW) were associated with most of the QTLs detected. A total of 43 MQTLs were identified, simplifying the information, and reducing the average confidence interval (CI) from 22.6 to 4.78 cM. These MQTLs were associated with multiple traits across different categories. Nine candidate genes were identified for several stable MQTLs, potentially contributing to traits such as quality, mineral content, and abiotic stress resistance. These genes play essential roles in various plant processes, such as carbohydrate metabolism, nitrogen assimilation, cell wall biogenesis, and cell wall extensibility. Overall, this study underscores the importance of considering MQTL analysis in wheat breeding programs, as it identifies stable genomic regions associated with multiple traits, offering potential solutions for improving wheat varieties under diverse environmental conditions.</p

Marker trait association.

<p>Associated markers (with-Log10(P) ≥3) QTL for AX content detected by GWAS, using the Kinship matrix. Chromosome location and map position from Wang et al. (2014), -Log10(P) and SNP effect are reported for each SNP.</p