Mutations in the BRCA1 and BRCA2 genes profoundly increase the risk of developing breast and/or ovarian cancer among women. To explore the contribution of BRCA1 and BRCA2 mutations in the development of hereditary breast cancer among Indian women, we carried out mutation analysis of the BRCA1 and BRCA2 genes in 61 breast or ovarian cancer patients from south India with a positive family history of breast and/or ovarian cancer. Mutation analysis was carried out using conformation-sensitive gel electrophoresis (CSGE) followed by sequencing. Mutations were identified in 17 patients (28.0%); 15 (24.6%) had BRCA1 mutations and two (3.28%) had BRCA2 mutations. While no specific association between BRCA1 or BRCA2 mutations with cancer type was seen, mutations were more often seen in families with ovarian cancer. While 40% (4/10) and 30.8% (4/12) of families with ovarian or breast and ovarian cancer had mutations, only 23.1% (9/39) of families with breast cancer carried mutations in the BRCA1 and BRCA2 genes. In addition, while BRCA1 mutations were found in all age groups, BRCA2 mutations were found only in the age group of < or =40 years. Of the BRCA1 mutations, there were three novel mutations (295delCA; 4213T-->A; 5267T-->G) and three mutations that have been reported earlier. Interestingly, 185delAG, a BRCA1 mutation which occurs at a very high frequency in Ashkenazi Jews, was found at a frequency of 16.4% (10/61). There was one novel mutation (4866insT) and one reported mutation in BRCA2. Thus, our study emphasizes the importance of mutation screening in familial breast and/or ovarian cancers, and the potential implications of these findings in genetic counselling and preventive therapy.
Our current knowledge of recombination hot spot activity in mammalian systems implicates a role for both the primary DNA sequence and the nature of the chromatin domain around it. In mice, the only recombination hot spots mapped to date have been confined to a cluster within the major histocompatibility complex (MHC) region. We present a high resolution analysis of a new recombination hot spot in the mouse genome which maps to mouse chromosome 8 C-D. Haplotype diversity analysis across 40 different strains of mice has enabled us to map recombination breakpoints to a 1-kb interval. This hot spot has a recombination intensity that is 10-to 100-fold above the genome average and has a mean gene conversion tract length of 371 bp. This meiotically active locus happens to be flanked by a transcribed region encoding a non-protein-coding RNA polymerase II transcript and the previously characterized repair site. Many of the primary DNA sequence features that have been reported for the mouse MHC hot spots are also shared by this hot spot locus and in addition, along with three other MHC hot spot loci, we show a new parallel feature of association of the crossover sites with the nuclear matrix.Most of the advances in our understanding of meiosis and recombination have come from studies of lower eukaryotes, in particular Saccharomyces cerevisiae. Recombination initiates via programmed double-strand breaks at the leptotene interval which are resected and undergo strand exchange and finally give rise to double Holliday junctions by the mid-pachytene interval. Mature crossover products follow around the end of pachytene (14,24). It is generally believed that a similar process operates in higher eukaryotes, including mammals. The rate of recombination is not a uniform function of the physical distance between two markers, leading to the concept of recombination hot spots and cold spots (36). In mice and humans, regions are generally termed as hot spots if their recombination frequency significantly exceeds 1 centimorgan (cM)/ Mb. There are three methods that have been used to map hot spots in mammals. The classical method is to correlate physical distances with genetic distances established by standard pedigree-based linkage analysis. The resolution of this method is limited by the density of markers, the number of individuals examined, and the number of recombination events that occur in a typical pedigree. Methods based on linkage disequilibrium (LD), which refers to the nonrandom association of alleles at linked sites, take into account ancestral recombination events, which would be far greater than those observed from any pedigree-based linkage study, leading to a finer mapping of recombination hot spots. Most measures of LD quantify the degree of association between pairs of markers which decreases as a function of physical distance between them due to increased probability of recombination between the markers. However, both of these techniques do not have the resolution to characterize crossovers at a molecular level. The ...
ABSTRACT:High resolution satellite images are associated with large variance and thus, per pixel classifiers often result in poor accuracy especially in delineation of horticultural crops. In this context, object oriented techniques are powerful and promising methods for classification. In the present study, a semi-automatic object oriented feature extraction model has been used for delineation of horticultural fruit and plantation crops using Erdas Objective Imagine. Multi-resolution data from Resourcesat LISS-IV and Cartosat-1 have been used as source data in the feature extraction model. Spectral and textural information along with NDVI were used as inputs for generation of Spectral Feature Probability (SFP) layers using sample training pixels. The SFP layers were then converted into raster objects using threshold and clump function resulting in pixel probability layer. A set of raster and vector operators was employed in the subsequent steps for generating thematic layer in the vector format. This semi-automatic feature extraction model was employed for classification of major fruit and plantations crops viz., mango, banana, citrus, coffee and coconut grown under different agro-climatic conditions. In general, the classification accuracy of about 75-80 per cent was achieved for these crops using object based classification alone and the same was further improved using minimal visual editing of misclassified areas. A comparison of on-screen visual interpretation with object oriented approach showed good agreement. It was observed that old and mature plantations were classified more accurately while young and recently planted ones (3years or less) showed poor classification accuracy due to mixed spectral signature, wider spacing and poor stands of plantations. The results indicated the potential use of object oriented approach for classification of high resolution data for delineation of horticultural fruit and plantation crops. The present methodology is applicable at local levels and future development is focused on up-scaling the methodology for generation of fruit and plantation crop maps at regional and national level which is important for creation of database for overall horticultural crop development.
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