Reference genes for quantitative reverse transcription-polymerase chain reaction expression studies in wild and cultivated peanut

<p>Abstract</p> <p>Background</p> <p>Wild peanut species (<it>Arachis </it>spp.) are a rich source of new alleles for peanut improvement. Plant transcriptome analysis under specific experimental conditions helps the understanding of cellular processes related, for instance, to development, stress response, and crop yield. The validation of these studies has been generally accomplished by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) which requires normalization of mRNA levels among samples. This can be achieved by comparing the expression ratio between a gene of interest and a reference gene which is constitutively expressed. Nowadays there is a lack of appropriate reference genes for both wild and cultivated <it>Arachis</it>. The identification of such genes would allow a consistent analysis of qRT-PCR data and speed up candidate gene validation in peanut.</p> <p>Results</p> <p>A set of ten reference genes were analyzed in four <it>Arachis </it>species (<it>A. magna</it>; <it>A. duranensis</it>; <it>A. stenosperma </it>and <it>A. hypogaea</it>) subjected to biotic (root-knot nematode and leaf spot fungus) and abiotic (drought) stresses, in two distinct plant organs (roots and leaves). By the use of three programs (GeNorm, NormFinder and BestKeeper) and taking into account the entire dataset, five of these ten genes, <it>ACT1 </it>(actin depolymerizing factor-like protein), <it>UBI1 </it>(polyubiquitin), <it>GAPDH </it>(glyceraldehyde-3-phosphate dehydrogenase), <it>60S </it>(60S ribosomal protein L10) and <it>UBI2 </it>(ubiquitin/ribosomal protein S27a) emerged as top reference genes, with their stability varying in eight subsets. The former three genes were the most stable across all species, organs and treatments studied.</p> <p>Conclusions</p> <p>This first in-depth study of reference genes validation in wild <it>Arachis </it>species will allow the use of specific combinations of secure and stable reference genes in qRT-PCR assays. The use of these appropriate references characterized here should improve the accuracy and reliability of gene expression analysis in both wild and cultivated Arachis and contribute for the better understanding of gene expression in, for instance, stress tolerance/resistance mechanisms in plants.</p

Genome-based trait prediction in multi- environment breeding trials in groundnut

Genomic selection (GS) can be an efficient and cost-effective breeding approach which captures both small- and large-effect genetic factors and therefore promises to achieve higher genetic gains for complex traits such as yield and oil content in groundnut. A training population was constituted with 340 elite lines followed by genotyping with 58 K ‘Axiom_Arachis’ SNP array and phenotyping for key agronomic traits at three locations in India. Four GS models were tested using three different random cross-validation schemes (CV0, CV1 and CV2). These models are: (1) model 1 (M1 = E + L) which includes the main effects of environment (E) and line (L); (2) model 2 (M2 = E + L + G) which includes the main effects of markers (G) in addition to E and L; (3) model 3 (M3 = E + L + G + GE), a naïve interaction model; and (4) model 4 (E + L + G + LE + GE), a naïve and informed interaction model. Prediction accuracy estimated for four models indicated clear advantage of the inclusion of marker information which was reflected in better prediction accuracy achieved with models M2, M3 and M4 as compared to M1 model. High prediction accuracies (> 0.600) were observed for days to 50% flowering, days to maturity, hundred seed weight, oleic acid, rust@90 days, rust@105 days and late leaf spot@90 days, while medium prediction accuracies (0.400–0.600) were obtained for pods/plant, shelling %, and total yield/plant. Assessment of comparative prediction accuracy for different GS models to perform selection for untested genotypes, and unobserved and unevaluated environments provided greater insights on potential application of GS breeding in groundnut

A QTL study on late leaf spot and rust revealed one major QTL for molecular breeding for rust resistance in groundnut (Arachis hypogaea L.)

Late leaf spot (LLS) and rust are two major foliar diseases of groundnut (Arachis hypogaea L.) that often occur together leading to 50–70% yield loss in the crop. A total of 268 recombinant inbred lines of a mapping population TAG 24 × GPBD 4 segregating for LLS and rust were used to undertake quantitative trait locus (QTL) analysis. Phenotyping of the population was carried out under artificial disease epiphytotics. Positive correlations between different stages, high to very high heritability and independent nature of inheritance between both the diseases were observed. Parental genotypes were screened with 1,089 simple sequence repeat (SSR) markers, of which 67 (6.15%) were found polymorphic. Segregation data obtained for these markers facilitated development of partial linkage map (14 linkage groups) with 56 SSR loci. Composite interval mapping (CIM) undertaken on genotyping and phenotyping data yielded 11 QTLs for LLS (explaining 1.70–6.50% phenotypic variation) in three environments and 12 QTLs for rust (explaining 1.70–55.20% phenotypic variation). Interestingly a major QTL associated with rust (QTLrust01), contributing 6.90–55.20% variation, was identified by both CIM and single marker analysis (SMA). A candidate SSR marker (IPAHM 103) linked with this QTL was validated using a wide range of resistant/susceptible breeding lines as well as progeny lines of another mapping population (TG 26 × GPBD 4). Therefore, this marker should be useful for introgressing the major QTL for rust in desired lines/varieties of groundnut through marker-assisted backcrossing

A genome-wide identification and comparative analysis of the lentil MLO genes

Revista electrónica on linePowdery mildew is a widespread fungal plant disease that can cause significant losses in many crops. Some MLO genes (Mildew resistance locus O) have proved to confer a durable resistance to powdery mildew in several species. Resistance granted by the MLO gene family members has prompted an increasing interest in characterizing these genes and implementing their use in plant breeding. Lentil (Lens culinaris Medik.) is a widely grown food legume almost exclusively consumed as dry seed with an average world production of 4.5 million tons. Powdery mildew causes severe losses on certain lentil cultivars under particular environmental conditions. Data mining of the lentil CDC Redberry draft genome allowed to identify up to 15 gene sequences with homology to known MLO genes, designated as LcMLOs. Further characterization of these gene sequences and their deduced protein sequences demonstrated conformity with key MLO protein characteristics such as the presence of transmembrane and calmodulin binding domains, as well as that of other conserved motifs. Phylogenetic and other comparative analyses revealed that LcMLO1 and LcMLO3 are the most likely gene orthologs related to powdery mildew response in other species, sharing a high similarity with other known resistance genes of dicot species, such as pea PsMLO1 and Medicago truncatula MtMLO1 and MtMLO3. Sets of primers were designed as tools to PCR amplify the genomic sequences of LcMLO1 and LcMLO3, also to screen lentil germplasm in search of resistance mutants. Primers were used to obtain the complete sequences of these two genes in all of the six wild lentil relatives. Respective to each gene, all Lens sequences shared a high similarity. Likewise, we used these primers to screen a working collection of 58 cultivated and 23 wild lentil accessions in search of length polymorphisms present in these two genes. All these data widen the insights on this gene family and can be useful for breeding programs in lentil and close related species.S