RestrictionDigest: A powerful Perl module for simulating genomic restriction digests

Background: Reduced-representation sequencing technology iswidely used in genotyping for its economical and efficient features. A popular way to construct the reduced-representation sequencing libraries is to digest the genomic DNA with restriction enzymes. A key factor of this method is to determine the restriction enzyme(s). But there are few computer programs which can evaluate the usability of restriction enzymes in reduced-representation sequencing. SimRAD is an R package which can simulate the digestion of DNA sequence by restriction enzymes and return enzyme loci number as well as fragment number. But for linkage mapping analysis, enzyme loci distribution is also an important factor to evaluate the enzyme. For phylogenetic studies, comparison of the enzyme performance across multiple genomes is important. It is strongly needed to develop a simulation tool to implement these functions. Results: Here, we introduce a Perl module named RestrictionDigest with more functions and improved performance. It can analyze multiple genomes at one run and generate concise comparison of enzyme performance across the genomes. It can simulate single-enzyme digestion, double-enzyme digestion and size selection process and generate comprehensive information of the simulation including enzyme loci number, fragment number, sequences of the fragments, positions of restriction sites on the genome, the coverage of digested fragments on different genome regions and detailed fragment length distribution. Conclusions: RestrictionDigest is an easy-to-use Perl module with flexible parameter settings.With the help of the information produced by the module, researchers can easily determine the most appropriate enzymes to construct the reduced-representation libraries to meet their experimental requirements.

Investigation of H19/RsaI Polymorphism in Children With Low Birth Weight in Pernambuco, Brazil

Background: H19 is a strong candidate gene for influencing birth weight variation and is exclusively imprinted maternally. In an attempt to understand the relationship of this gene polymorphism with low birth weight children, we investigated association of H19/RsaI polymorphism with low birth weight and normal birth weight in children and their mothers. Objectives: The aim of our study was to establish the association between H19 gene polymorphism and LW in children born in Pernambuco, state of Brazil. Patients and Methods: It were selected 89 children, 40 low birth weight (LW) and 49 normal birth weight (NW) and 71 mothers (40 mothers of newborns NW and 31 mothers of newborns LW) attended at Dom Malan Hospital, Petrolina, Pernambuco - Brazil. Peripheral blood samples were collected from patients and genomic DNA was extracted and detected by electrophoresis agarose gel, stained by Blue Green Loading Dye. DNA PCR amplification was done using the primers H1 (sense) and H3 (antisense). PCR products were digested with RsaI and electrophoresed on agarose gel stained by ethidium bromide. Statistical analyses were performed using the program BioEstat version 5.0. Results: The RsaI polymorphism in the H19 gene showed that genotype frequencies did not differ statistically between low birth weight (AA = 12.5%, AB = 45%, BB = 42.5%) and control (AA = 8.6% AB = 36.73%, BB= 55.10% groups) and the allele frequencies were not significantly different (P = 0.2897). We also did not observe any association between maternal H19 allele polymorphism and low birth weight newborns (P =0.7799) or normal birth weight children (P = 0.8976). Conclusions: The small size of sample may be the explanation for these results; future studies with more patients are needed to confirm the effect of H19/RsaI polymorphism on birth weight of LW newborns.