Analysis of BAC-end sequences (BESs) and development of BES-SSR markers for genetic mapping and hybrid purity assessment in pigeonpea (Cajanus spp.)

<p>Abstract</p> <p>Background</p> <p>Pigeonpea [<it>Cajanus cajan </it>(L.) Millsp.] is an important legume crop of rainfed agriculture. Despite of concerted research efforts directed to pigeonpea improvement, stagnated productivity of pigeonpea during last several decades may be accounted to prevalence of various biotic and abiotic constraints and the situation is exacerbated by availability of inadequate genomic resources to undertake any molecular breeding programme for accelerated crop improvement. With the objective of enhancing genomic resources for pigeonpea, this study reports for the first time, large scale development of SSR markers from BAC-end sequences and their subsequent use for genetic mapping and hybridity testing in pigeonpea.</p> <p>Results</p> <p>A set of 88,860 BAC (bacterial artificial chromosome)-end sequences (BESs) were generated after constructing two BAC libraries by using <it>Hin</it>dIII (34,560 clones) and <it>Bam</it>HI (34,560 clones) restriction enzymes. Clustering based on sequence identity of BESs yielded a set of >52K non-redundant sequences, comprising 35 Mbp or >4% of the pigeonpea genome. These sequences were analyzed to develop annotation lists and subdivide the BESs into genome fractions (e.g., genes, retroelements, transpons and non-annotated sequences). Parallel analysis of BESs for microsatellites or simple sequence repeats (SSRs) identified 18,149 SSRs, from which a set of 6,212 SSRs were selected for further analysis. A total of 3,072 novel SSR primer pairs were synthesized and tested for length polymorphism on a set of 22 parental genotypes of 13 mapping populations segregating for traits of interest. In total, we identified 842 polymorphic SSR markers that will have utility in pigeonpea improvement. Based on these markers, the <it>first </it>SSR-based genetic map comprising of 239 loci was developed for this previously uncharacterized genome. Utility of developed SSR markers was also demonstrated by identifying a set of 42 markers each for two hybrids (ICPH 2671 and ICPH 2438) for genetic purity assessment in commercial hybrid breeding programme.</p> <p>Conclusion</p> <p>In summary, while BAC libraries and BESs should be useful for genomics studies, BES-SSR markers, and the genetic map should be very useful for linking the genetic map with a future physical map as well as for molecular breeding in pigeonpea.</p

Development and use of genic molecular markers (GMMs) for construction of a transcript map of chickpea (Cicer arietinum L.)

A transcript map has been constructed by the development and integration of genic molecular markers (GMMs) including single nucleotide polymorphism (SNP), genic microsatellite or simple sequence repeat (SSR) and intron spanning region (ISR)-based markers, on an inter-specific mapping population of chickpea, the third food legume crop of the world and the first food legume crop of India. For SNP discovery through allele re-sequencing, primer pairs were designed for 688 genes/expressed sequence tags (ESTs) of chickpea and 657 genes/ESTs of closely related species of chickpea. High-quality sequence data obtained for 220 candidate genic regions on 2–20 genotypes representing 9 Cicer species provided 1,893 SNPs with an average frequency of 1/35.83 bp and 0.34 PIC (polymorphism information content) value. On an average 2.9 haplotypes were present in 220 candidate genic regions with an average haplotype diversity of 0.6326. SNP2CAPS analysis of 220 sequence alignments, as mentioned above, provided a total of 192 CAPS candidates. Experimental analysis of these 192 CAPS candidates together with 87 CAPS candidates identified earlier through in silico mining of ESTs provided scorable amplification in 173 (62.01%) cases of which predicted assays were validated in 143 (82.66%) cases (CGMM). Alignments of chickpea unigenes with Medicago truncatula genome were used to develop 121 intron spanning region (CISR) markers of which 87 yielded scorable products. In addition, optimization of 77 EST-derived SSR (ICCeM) markers provided 51 scorable markers. Screening of easily assayable 281 markers including 143 CGMMs, 87 CISRs and 51 ICCeMs on 5 parental genotypes of three mapping populations identified 104 polymorphic markers including 90 markers on the inter-specific mapping population. Sixty-two of these GMMs together with 218 earlier published markers (including 64 GMM loci) and 20 other unpublished markers could be integrated into this genetic map. A genetic map developed here, therefore, has a total of 300 loci including 126 GMM loci and spans 766.56 cM, with an average inter-marker distance of 2.55 cM. In summary, this is the first report on the development of large-scale genic markers including development of easily assayable markers and a transcript map of chickpea. These resources should be useful not only for genome analysis and genetics and breeding applications of chickpea, but also for comparative legume genomics

Redundancy modelling and array yield analysis for repairable embedded memories

Embedded memories currently occupy more than 50% of the chip area for typical SOC integrated circuits. Defects in memory arrays can therefore significantly degrade manufacturing yield. In such a setting, repairable embedded memories are desirable because they help improve the memory array yield of an IC. We have developed an array yield analysis tool that provides realistic yield estimates for both single repairable memories, as well as for ICs containing multiple, possibly different, repairable embedded memories. Our approach uses pseudo-random fault bit-maps, which are generated based on memory area, defect density, and fault distribution. In order to accommodate a wide range of industrial memory and redundancy organizations, we have developed a flexible memory model. It generalizes the traditional simple memory matrix model with partitioning into regions, grouping of columns and rows, and column-wise and row-wise coupling of the spares. Our tool is used to determine an optimal amount of spare columns and rows for a given memory, as well as to determine the effectiveness of various repair algorithms

Yield analysis for repairable embedded memories

Repairable embedded memories help improve the overall yield of an IC. We have developed a yield analysis tool that provides realistic yield estimates for both single repairable memories, as well as for ICs containing multiple, possibly different, repairable embedded memories. Our approach uses pseudo-randomly generated fault bit-maps, which are based on memory area size, defect density, and fault distribution. In order to accommodate a wide range of industrial memory and redundancy organizations, we have developed a flexible memory model. It generalizes the traditional simple memory matrix model with partitioning into regions, grouping of columns and rows, and column-wise and row-wise coupling of the spares. Our tool is used to determine an optimal amount of spare columns and rows for a given memory, as well as to determine the effectiveness of various repair algorithms