BackgroundPigeonpea [Cajanus cajan (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.ResultsA set of 88,860 BAC (bacterial artificial chromosome)-end sequences (BESs) were generated after constructing two BAC libraries by using HindIII (34,560 clones) and BamHI (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 first 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.ConclusionIn 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.

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Soaring prices of fossil fuels, geo-political issues and environmental pollution associated with fossil fuel use has led to worldwide interest in the production and use of bio-fuels. Both the developed and developing countries have developed a range of policies to encourage production of combustible fuels from plants that triggered public and private investments in bio-fuel crop research and development, and bio-fuels production. In this article, we discuss the potential benefits of bio-fuels in increasing the farmers' incomes, reducing environment pollution, the crop options and research and development interventions required to generate feedstocks to produce bio-fuels to meet projected demand without compromising food/fodder security in developing countries.

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A dverse climatic conditions and the need to sustain food production for increasing human populations in the 21st century and beyond require plant breeders to look for novel traits in conserved germplasm. Searching for optimal traits within vast germplasm resources is a challenging task and is complicated by the presence of genetically similar accessions. Frankel (1984) proposed a methodology for efficient utilization of plant genetic resources by sampling a small set of diverse accessions and maintaining them as core collections. To be most useful, the design of a good core collection should avoid including both duplicate accessions and genetically similar accessions (Brown, 1995;Jansen and van Hintum, 2007). Efficient marker systems for unraveling the diversity of the collection and appropriate sampling strategies to retain maximum diversity are the two basic requirements for ABSTRACT Sampling core collections containing a diverse set of entries has been practiced over the last two decades for a number of crops and has become a vital component of modern day crop improvement programs. A diverse, multipurpose core collection should represent the maximum genetic diversity available in an entire germplasm collection with a small number of entries. Selection of genetically distant entries that represent the maximum diversity of the entire germplasm collection is a challenging task that has been improved over the years. In this study, we introduce the similarity elimination (SimEli) method to sample genetically distant entries for the development of core collections, which was used to sample a diverse core collection of mulberry accessions using phenotypic markers. The performance of the SimEli method was compared with that of the PowerCore algorithm for phenotypic markers and with that of the Core Hunter and genetic distance optimization (GDOpt) algorithms for simple sequence repeat (SSR) markers. The SimEli method effectively selected genetically distant entries, whereas PowerCore proved efficient for selecting outliers among a small number of entries. However, the SimEli method outperformed the Core Hunter algorithm in selecting distant entries with high mean and minimum entry to nearest entry distance values. The Core Hunter collections retained a greater number of alleles than did collections developed using the SimEli method only when increased weight was given to Shannon's diversity index when using Core Hunter. The SimEli method is more userfriendly, involves simple steps, and requires less computational time than other leading programs for the development of core collections.