38 research outputs found
Integrated physical, genetic and genome map of chickpea (Cicer arietinum L.)
Physical map of chickpea was developed for the reference chickpea genotype (ICC 4958) using bacterial artificial chromosome (BAC) libraries targeting 71,094 clones (~12× coverage). High information content fingerprinting (HICF) of these clones gave high-quality fingerprinting data for 67,483 clones, and 1,174 contigs comprising 46,112 clones and 3,256 singletons were defined. In brief, 574 Mb genome size was assembled in 1,174 contigs with an average of 0.49 Mb per contig and 3,256 singletons represent 407 Mb genome. The physical map was linked with two genetic maps with the help of 245 BAC-end sequence (BES)-derived simple sequence repeat (SSR) markers. This allowed locating some of the BACs in the vicinity of some important quantitative trait loci (QTLs) for drought tolerance and reistance to Fusarium wilt and Ascochyta blight. In addition, fingerprinted contig (FPC) assembly was also integrated with the draft genome sequence of chickpea. As a result, ~965 BACs including 163 minimum tilling path (MTP) clones could be mapped on eight pseudo-molecules of chickpea forming 491 hypothetical contigs representing 54,013,992 bp (~54 Mb) of the draft genome. Comprehensive analysis of markers in abiotic and biotic stress tolerance QTL regions led to identification of 654, 306 and 23 genes in drought tolerance “QTL-hotspot” region, Ascochyta blight resistance QTL region and Fusarium wilt resistance QTL region, respectively. Integrated physical, genetic and genome map should provide a foundation for cloning and isolation of QTLs/genes for molecular dissection of traits as well as markers for molecular breeding for chickpea improvement
The GCP molecular marker toolkit, an instrument for use in breeding food security crops
Crop genetic resources carry variation useful for overcoming the challenges of modern agriculture. Molecular markers can facilitate the selection of agronomically important traits. The pervasiveness of genomics research has led to an overwhelming number of publications and databases, which are, nevertheless, scattered and hence often difficult for plant breeders to access, particularly those in developing countries. This situation separates them from developed countries, which have better endowed programs for developing varieties. To close this growing knowledge gap, we conducted an intensive literature review and consulted with more than 150 crop experts on the use of molecular markers in the breeding program of 19 food security crops. The result was a list of effectively used and highly reproducible sequence tagged site (STS), simple sequence repeat (SSR), single nucleotide polymorphism (SNP), and sequence characterized amplified region (SCAR) markers. However, only 12 food crops had molecular markers suitable for improvement. That is, marker-assisted selection is not yet used for Musa spp., coconut, lentils, millets, pigeonpea, sweet potato, and yam. For the other 12 crops, 214 molecular markers were found to be effectively used in association with 74 different traits. Results were compiled as the GCP Molecular Marker Toolkit, a free online tool that aims to promote the adoption of molecular approaches in breeding activities
Genomics-assisted breeding in four major pulse crops of developing countries: present status and prospects
The global population is continuously increasing and is expected to reach nine billion by 2050. This huge population pressure will lead to severe shortage of food, natural resources and arable land. Such an alarming situation is most likely to arise in developing countries due to increase in the proportion of people suffering from protein and micronutrient malnutrition. Pulses being a primary and affordable source of proteins and minerals play a key role in alleviating the protein calorie malnutrition, micronutrient deficiencies and other undernourishment-related issues. Additionally, pulses are a vital source of livelihood generation for millions of resource-poor farmers practising agriculture in the semi-arid and sub-tropical regions. Limited success achieved through conventional breeding so far in most of the pulse crops will not be enough to feed the ever increasing population. In this context, genomics-assisted breeding (GAB) holds promise in enhancing the genetic gains. Though pulses have long been considered as orphan crops, recent advances in the area of pulse genomics are noteworthy, e.g. discovery of genome-wide genetic markers, high-throughput genotyping and sequencing platforms, high-density genetic linkage/QTL maps and, more importantly, the availability of whole-genome sequence. With genome sequence in hand, there is a great scope to apply genome-wide methods for trait mapping using association studies and to choose desirable genotypes via genomic selection. It is anticipated that GAB will speed up the progress of genetic improvement of pulses, leading to the rapid development of cultivars with higher yield, enhanced stress tolerance and wider adaptability
Allelic relationships of flowering time genes in chickpea
Flowering time and crop duration are the most important traits for adaptation of chickpea (Cicer arietinum L.) to different agro-climatic conditions. Early flowering and early maturity enhance adaptation of chickpea to short season environments. This study was conducted to establish allelic relationships of the early flowering genes of ICC 16641, ICC 16644 and ICCV 96029 with three known early flowering genes, efl-1 (ICCV 2), ppd or efl-2 (ICC 5810), and efl-3 (BGD 132). In all cases, late flowering was dominant to early-flowering. The results indicated that the efl-1 gene identified from ICCV 2 was also present in ICCV 96029, which has ICCV 2 as one of the parents in its pedigree. ICC 16641 and ICC 16644 had a common early flowering gene which was not allelic to other reported early flowering genes. The new early flowering gene was designated efl-4. In most of the crosses, days to flowering was positively correlated with days to maturity, number of pods per plant, number of seeds per plant and seed yield per plant and negatively correlated or had no correlation with 100-seed weight. The double-pod trait improved grain yield per plant in the crosses where it delayed maturity. The information on allelic relationships of early flowering genes and their effects on yield and yield components will be useful in chickpea breeding for desired phenology
A genome-scale integrated approach aids in genetic dissection of complex flowering time trait in chickpea
A combinatorial approach of candidate gene-based association analysis and genome-wide association study (GWAS) integrated with QTL mapping, differential gene expression profiling and molecular haplotyping was deployed in the present study for quantitative dissection of complex flowering time trait in chickpea. Candidate gene-based association mapping in a flowering time association panel (92 diverse desi and kabuli accessions) was performed by employing the genotyping information of 5724 SNPs discovered from 82 known flowering chickpea gene orthologs of Arabidopsis and legumes as well as 832 gene-encoding transcripts that are differentially expressed during flower development in chickpea. GWAS using both genome-wide GBS- and candidate gene-based genotyping data of 30,129 SNPs in a structured population of 92 sequenced accessions (with 200–250 kb LD decay) detected eight maximum effect genomic SNP loci (genes) associated (34 % combined PVE) with flowering time. Six flowering time-associated major genomic loci harbouring five robust QTLs mapped on a high-resolution intra-specific genetic linkage map were validated (11.6–27.3 % PVE at 5.4–11.7 LOD) further by traditional QTL mapping. The flower-specific expression, including differential up- and down-regulation (>three folds) of eight flowering time-associated genes (including six genes validated by QTL mapping) especially in early flowering than late flowering contrasting chickpea accessions/mapping individuals during flower development was evident. The gene haplotype-based LD mapping discovered diverse novel natural allelic variants and haplotypes in eight genes with high trait association potential (41 % combined PVE) for flowering time differentiation in cultivated and wild chickpea. Taken together, eight potential known/candidate flowering time-regulating genes [efl1 (early flowering 1), FLD (Flowering locus D), GI (GIGANTEA), Myb (Myeloblastosis), SFH3 (SEC14-like 3), bZIP (basic-leucine zipper), bHLH (basic helix-loop-helix) and SBP (SQUAMOSA promoter binding protein)], including novel markers, QTLs, alleles and haplotypes delineated by aforesaid genome-wide integrated approach have potential for marker-assisted genetic improvement and unravelling the domestication pattern of flowering time in chickpea
Chickpea
The narrow genetic base of cultivated chickpea warrants systematic collection,
documentation and evaluation of chickpea germplasm and particularly wild
Cicer species for effective and efficient use in chickpea breeding programmes.
Limiting factors to crop production, possible solutions and ways to overcome
them, importance of wild relatives and barriers to alien gene introgression and
strategies to overcome them and traits for base broadening have been discussed.
It has been clearly demonstrated that resistance to major biotic and abiotic
stresses can be successfully introgressed from the primary gene pool
comprising progenitor species. However, many desirable traits including high
degree of resistance to multiple stresses that are present in the species
belonging to secondary and tertiary gene pools can also be introgressed by
using special techniques to overcome pre- and post-fertilization barriers.
Besides resistance to various biotic and abiotic stresses, the yield QTLs have
also been introgressed from wild Cicer species to cultivated varieties. Status
and importance of molecular markers, genome mapping and genomic tools
for chickpea improvement are elaborated. Because of major genes for various
biotic and abiotic stresses, the transfer of agronomically important traits into
elite cultivars has been made easy and practical through marker-assisted
selection and marker-assisted backcross. The usefulness of molecular markers
such as SSR and SNP for the construction of high-density genetic maps of
chickpea and for the identification of genes/QTLs for stress resistance, quality
and yield contributing traits has also been discussed
Suppression of the auxin response pathway enhances susceptibility to Phytophthora cinnamomi while phosphite-mediated resistance stimulates the auxin signalling pathway
Background
Phytophthora cinnamomi is a devastating pathogen worldwide and phosphite (Phi), an analogue of phosphate (Pi) is highly effective in the control of this pathogen. Phi also interferes with Pi starvation responses (PSR), of which auxin signalling is an integral component. In the current study, the involvement of Pi and the auxin signalling pathways in host and Phi-mediated resistance to P. cinnamomi was investigated by screening the Arabidopsis thaliana ecotype Col-0 and several mutants defective in PSR and the auxin response pathway for their susceptibility to this pathogen. The response to Phi treatment was also studied by monitoring its effect on Pi- and the auxin response pathways.
Results
Here we demonstrate that phr1-1 (phosphate starvation response 1), a mutant defective in response to Pi starvation was highly susceptible to P. cinnamomi compared to the parental background Col-0. Furthermore, the analysis of the Arabidopsis tir1-1 (transport inhibitor response 1) mutant, deficient in the auxin-stimulated SCF (Skp1 − Cullin − F-Box) ubiquitination pathway was also highly susceptible to P. cinnamomi and the susceptibility of the mutants rpn10 and pbe1 further supported a role for the 26S proteasome in resistance to P. cinnamomi. The role of auxin was also supported by a significant (P < 0.001) increase in susceptibility of blue lupin (Lupinus angustifolius) to P. cinnamomi following treatment with the inhibitor of auxin transport, TIBA (2,3,5-triiodobenzoic acid). Given the apparent involvement of auxin and PSR signalling in the resistance to P. cinnamomi, the possible involvement of these pathways in Phi mediated resistance was also investigated. Phi (especially at high concentrations) attenuates the response of some Pi starvation inducible genes such as AT4, AtACP5 and AtPT2 in Pi starved plants. However, Phi enhanced the transcript levels of PHR1 and the auxin responsive genes (AUX1, AXR1and AXR2), suppressed the primary root elongation, and increased root hair formation in plants with sufficient Pi.
Conclusions
The auxin response pathway, particularly auxin sensitivity and transport, plays an important role in resistance to P. cinnamomi in Arabidopsis, and phosphite-mediated resistance may in some part be through its effect on the stimulation of the PSR and auxin response pathways
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Use of variogram analysis to classify field peas with and without internal defects caused by weevil infestation
In this study, we acquired 72 (training data) and 30 (independent validation) high-spatial resolution (7 by 7 pixels per mm ) hyperspectral imaging data [240 spectral bands from 392 to 889 nm (spectral resolution = 2.1 nm)] from samples of field peas (Pisum sativum) with and without pea weevil (Bruchus pisorum) infestation. The reflectance data were analyzed with linear discriminant analysis (LDA) or either reflectance values only or of a combination of reflectance values and variogram parameters (derived from variogram analysis) from a single spectral band (782 nm). All examined classification models were assessed based on sensitivity (ability to positively detect infestation), specificity (ability to positively detect non-infestation), and accurate classification of 30 samples of independent validation data. Highest classification performance was obtained with a combination of reflectance values in two spectral bands (641 nm and 868 nm) and variogram parameters derived from 782 nm. This classification model was associated with a sensitivity of 94.7% and a specificity of 100%. In addition, all 30 independent validation data were accurately classified (100%). For comparison, traditional linear discriminant analyses of 108,351 reflectance profiles from individual pixels in the 72 samples or average reflectance profiles from the 72 samples classified the validation data with 84.0% and 83.3% accuracy, respectively. We are unaware of any reflectance-based classification system, which - based on reflectance data acquired in only three channels (spectral bands) - can provide this level of sensitivity and specificity and classification of independent validation data of internal defects in food products. Accurate and reliable classification of food objects based reflectance values in only a few spectral bands would likely imply low computer processing requirements and rapid data analysis. Thus, we believe that the current classification method may be useful for quality control systems of a wide range of food products. © 2013 Elsevier Ltd. All rights reserved.