194 research outputs found

    Metaplastic Carcinoma of the Left Breast with Extensive Chondroid Differentiation

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    Metaplastic breast carcinoma is very rare neoplasm which contains mixture of carcinomatous (epithelial) and sarcomatous (mesenchymal) elements in variable proportion. Metaplastic carcinoma with chondroid differentiation is even rarer. We report a case of metaplastic carcinoma with extensive chondroid differentiation as there is paucity of information regarding pathological features and clinical outcomes for these rare tumors. Tumor had characteristic definite areas of classic infiltrating duct carcinoma with abundant chondromyxoid matrix, focal areas of chondrosarcoma and cartilagenous metaplasia. Tumour cells were immunoreactive for S-100, ER, and PR. When pathologist encounter breast tumor with chondroid differentiation, careful gross sampling, histopathology and immunoreactivity for mesenchymal and epithelial component are most useful to differentiate metaplastic carcinoma from malignant phylloides tumors and malignant adenomyoepithelioma

    Study on Basic Mechanism of Reactive Armour

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    Two basic mechanisms which operate in the functioning of reactive armour are presented. Both the explosive effect and cutting of metal plates by a jet have been investigated. The angle of attack and the confinement of the explosive have been found most significant factors in reducing the penetrating power of the jet. The effect of detonating explosives has been investigated with radiography. Some of the significant effects, like detonation of explosive by the impact of the jet, expansion of covering plates, disturbance in coherence and reduction in the penetration of the jet have been observed. It is found that the jet penetration in a stack of mild steel plates is reduced to 30 per cent of its blank penetration in present set-ups. A theoretical model has been conceived to study the interaction of moving plates and the jet. The critical thickness and surface cut in plates have been calculated

    Characterization of heterosis and genomic prediction‐based establishment of heterotic patterns for developing better hybrids in pigeonpea

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    Whole-genome resequencing (WGRS) of 396 lines, consisting of 104 hybrid parental lines and 292 germplasm lines, were used to study the molecular basis of mid-parent heterosis (MPH) and to identify complementary heterotic patterns in pigeonpea [Cajanus cajan (L.) Millsp.] hybrids. The lines and hybrids were assessed for yield and yield-related traits in multiple environments. Our analysis showed positive MPH values in 78.6% of hybrids, confirming the potential of hybrid breeding in pigeonpea. By using genome-wide prediction and association mapping approaches, we identified 129 single nucleotide polymorphisms and 52 copy number variations with significant heterotic effects and also established a high-yielding heterotic pattern in pigeonpea. In summary, our study highlights the role of WGRS data in the study and use of heterosis in crops where hybrid breeding is expected to boost selection gain in order to ensure global food security

    Advances in Pigeonpea Genomics

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    Pigeonpea, a member of family Fabaceae, is one of the important food legumes cultivated in tropical and subtropical regions. Due to its inherent properties to withstand harsh environments, it plays a critical role in ensuring sustainability in the subsistence agriculture. Furthermore, plasticity in the maturity duration imparts it a greater adaptability in a variety of cropping systems. In the post genomics era, the importance of pigeonpea is further evident from the fact that pigeonpea has emerged as first non-industrial legume crop for which the whole genome sequence has been completed. It revealed 605.78 Mb of assembled and anchored sequence as against the predicted 833 Mb genome consequently representing 72.8 % of the whole genome. In order to perform genetic and genomic analysis various molecular markers like random amplified polymorphic DNA (RAPD), restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP), simple sequence repeat (SSR), diversity array technology (DArT), single feature polymorphism (SFP), and single nucleotide polymorphism (SNP) were employed. So far four transcriptome assemblies have been constructed and different sets of EST-SSRs were developed and validated in a panel of diverse pigeonpea genotypes. Extensive survey of BAC-end sequences (BESs) provided 3,072 BES-SSRs and all these BES-SSRs were further used for linkage analysis and trait mapping. To make the available linkage information more useful, six intra-specific genetic maps were joined together into a single consensus genetic map providing map positions to a total of 339 SSR markers at map coverage of 1,059 cM. However, earlier very few linkage maps were available in the crop because of non-availability of genomic resources. Several quantitative trait loci (QTLs) associated with traits of agronomic interest including QTLs for sterility mosaic disease, fertility restoration, plant type and earliness have been identified and validated. To strengthen the traditional breeding, plenty of genomics tools and technologies are now available for integration in regular pigeonpea breeding schemes. This article presents the progress made in the area of pigeonpea genomics and outlines its applications in crop breeding for pigeonpea improvement

    Genomics and breeding innovations for enhancing genetic gain for climate resilience and nutrition traits

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    Key message Integrating genomics technologies and breeding methods to tweak core parameters of the breeder’s equation could accelerate delivery of climate-resilient and nutrient rich crops for future food security. Abstract Accelerating genetic gain in crop improvement programs with respect to climate resilience and nutrition traits, and the realization of the improved gain in farmers’ fields require integration of several approaches. This article focuses on innovative approaches to address core components of the breeder’s equation. A prerequisite to enhancing genetic variance (σ2g) is the identification or creation of favorable alleles/haplotypes and their deployment for improving key traits. Novel alleles for new and existing target traits need to be accessed and added to the breeding population while maintaining genetic diversity. Selection intensity (i) in the breeding program can be improved by testing a larger population size, enabled by the statistical designs with minimal replications and high-throughput phenotyping. Selection priorities and criteria to select appropriate portion of the population too assume an important role. The most important component of breeder′s equation is heritability (h2). Heritability estimates depend on several factors including the size and the type of population and the statistical methods. The present article starts with a brief discussion on the potential ways to enhance σ2g in the population. We highlight statistical methods and experimental designs that could improve trait heritability estimation. We also offer a perspective on reducing the breeding cycle time (t), which could be achieved through the selection of appropriate parents, optimizing the breeding scheme, rapid fixation of target alleles, and combining speed breeding with breeding programs to optimize trials for release. Finally, we summarize knowledge from multiple disciplines for enhancing genetic gains for climate resilience and nutritional traits

    Toward the sequence-based breeding in legumes in the post-genome sequencing era

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    Efficiency of breeding programs of legume crops such as chickpea, pigeonpea and groundnut has been considerably improved over the past decade through deployment of modern genomic tools and technologies. For instance, next-generation sequencing technologies have facilitated availability of genome sequence assemblies, re-sequencing of several hundred lines, development of HapMaps, high-density genetic maps, a range of marker genotyping platforms and identification of markers associated with a number of agronomic traits in these legume crops. Although marker-assisted backcrossing and marker-assisted selection approaches have been used to develop superior lines in several cases, it is the need of the hour for continuous population improvement after every breeding cycle to accelerate genetic gain in the breeding programs. In this context, we propose a sequence-based breeding approach which includes use of independent or combination of parental selection, enhancing genetic diversity of breeding programs, forward breeding for early generation selection, and genomic selection using sequencing/genotyping technologies. Also, adoption of speed breeding technology by generating 4–6 generations per year will be contributing to accelerate genetic gain. While we see a huge potential of the sequence-based breeding to revolutionize crop improvement programs in these legumes, we anticipate several challenges especially associated with high-quality and precise phenotyping at affordable costs, data analysis and management related to improving breeding operation efficiency. Finally, integration of improved seed systems and better agronomic packages with the development of improved varieties by using sequence-based breeding will ensure higher genetic gains in farmers’ fields

    Development and Application of High-Density Axiom Cajanus SNP Array with 56K SNPs to Understand the Genome Architecture of Released Cultivars and Founder Genotypes

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    As one of the major outputs of next-generation sequencing (NGS), a large number of genome-wide single-nucleotide polymorphisms (SNPs) have been developed in pigeonpea [Cajanus cajan (L.) Huth.]. However, SNPs require a genotyping platform or assay to be used in different evolutionary studies or in crop improvement programs. Therefore, we developed an Axiom Cajanus SNP array with 56K SNPs uniformly distributed across the genome and assessed its utility in a genetic diversity study. From the whole-genome resequencing (WGRS) data on 104 pigeonpea lines, ∼2 million sequence variations (SNPs and insertion–deletions [InDels]) were identified, from which a subset of 56,512 unique and informative sequence variations were selected to develop the array. The Axiom Cajanus SNP array developed was used for genotyping 103 pigeonpea lines encompassing 63 cultivars released between 1960 and 2014 and 40 breeding, germplasm, and founder lines. Genotyping data thus generated on 103 pigeonpea lines provided 51,201 polymorphic SNPs and InDels. Genetic diversity analysis provided in-depth insights into the genetic architecture and trends in temporal diversity in pigeonpea cultivars. Therefore, the continuous use of the high-density Axiom Cajanus SNP array developed will accelerate high-resolution trait mapping, marker-assisted breeding, and genomic selection efforts in pigeonpea

    Genetic dissection of drought tolerance in chickpea (Cicer arietinum L.)

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    Chickpea (Cicer arietinum L.) is the second most important grain legume cultivated by resource poor farmers in the arid and semi-arid regions of the world. Drought is one of the major constraints leading up to 50 % production losses in chickpea. In order to dissect the complex nature of drought tolerance and to use genomics tools for enhancing yield of chickpea under drought conditions, two mapping populations—ICCRIL03 (ICC 4958 × ICC 1882) and ICCRIL04 (ICC 283 × ICC 8261) segregating for drought tolerance-related root traits were phenotyped for a total of 20 drought component traits in 1–7 seasons at 1–5 locations in India. Individual genetic maps comprising 241 loci and 168 loci for ICCRIL03 and ICCRIL04, respectively, and a consensus genetic map comprising 352 loci were constructed (http://cmap.icrisat.ac.in/cmap/sm/cp/varshney/). Analysis of extensive genotypic and precise phenotypic data revealed 45 robust main-effect QTLs (M-QTLs) explaining up to 58.20 % phenotypic variation and 973 epistatic QTLs (E-QTLs) explaining up to 92.19 % phenotypic variation for several target traits. Nine QTL clusters containing QTLs for several drought tolerance traits have been identified that can be targeted for molecular breeding. Among these clusters, one cluster harboring 48 % robust M-QTLs for 12 traits and explaining about 58.20 % phenotypic variation present on CaLG04 has been referred as “QTL-hotspot”. This genomic region contains seven SSR markers (ICCM0249, NCPGR127, TAA170, NCPGR21, TR11, GA24 and STMS11). Introgression of this region into elite cultivars is expected to enhance drought tolerance in chickpea
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