Assessing the genetic diversity of rice originating from Bangladesh, Assam and West Bengal

Acknowledgements This work was funded by BBSRC research project BB/J00336/1. FS and a part of the proportion of the cost of the Illumina genotyping was funded by a Beachell-Borlag International Fellowship. The authors would like to acknowledge the help of Dr MK Sarmah in collecting seed samples of the landraces and improved cultivars from Assam used in this study and Dr. Ma. Elizabeth B. Naredo and Ms. Sheila Mae Q. Mercado for handling of IRGC accessions and preparation of DNAs for genotyping. All rice seeds used here were obtained with MTA agreements and seed and dry leaves imported into the UK under import licence IMP⁄SOIL⁄18⁄2009 issued by Science and Advice for Scottish Agriculture.Peer reviewedPublisher PD

SPRITE and ASSAM: web servers for side chain 3D-motif searching in protein structures

Similarities in the 3D patterns of amino acid side chains can provide insights into their function despite the absence of any detectable sequence or fold similarities. Search for protein sites (SPRITE) and amino acid pattern search for substructures and motifs (ASSAM) are graph theoretical programs that can search for 3D amino side chain matches in protein structures, by representing the amino acid side chains as pseudo-atoms. The geometric relationship of the pseudo-atoms to each other as a pattern can be represented as a labeled graph where the pseudo-atoms are the graph's nodes while the edges are the inter-pseudo-atomic distances. Both programs require the input file to be in the PDB format. The objective of using SPRITE is to identify matches of side chains in a query structure to patterns with characterized function. In contrast, a 3D pattern of interest can be searched for existing occurrences in available PDB structures using ASSAM. Both programs are freely accessible without any login requirement. SPRITE is available at http://mfrlab.org/grafss/sprite/while ASSAM can be accessed at http://mfrlab.org/grafss/assam/

Old age poverty in the Indian States: What do the household data tell us?

In the absence of any official measures of old age poverty, this paper uses National Sample Survey household-level data to investigate the extent and nature of living standards and incidence of poverty among elderly in sixteen major states in India. We construct both individual and household-level poverty indices for the elderly and examine the sensitivity of these poverty indices to different equivalence scales and size economies in consumption. Our analysis highlights the complex nature of old age poverty in the Indian states. While poverty estimates taking into account equivalence scale and size economies in consumption suggest that households with elderly members are less poor than others, the interpretation of this result is more complex. Further analysis suggests that the results are partly a function of differences in demographic composition of the households and a possible survivorship bias due to positive correlation between household incomes and life expectancy. After correcting for the possible sources of bias (including the survivorship bias), there is evidence that poverty is increased by the presence of older elderly (75 and above) in all states. Meanwhile, the conclusion that households with elderly aged sixty and above are less poor appears to be robust across most states