6920 Nucleic Acids Research, 2011, Vol. 39, No. 16 which now cover 21% of the genome sequence, to re-analyze publicly available genome-wide DNA methyla- tion and siRNA datasets. Our analysis indicates that although the majority of TE sequences are densely methylated, >25% are unmethylated at most or all sites, or show signiﬁcant DNA methylation only over one or two of the three types of sites (CG, CHG and CHH). Furthermore, methylated TE sequences are less often characterized by an abundance of matching siRNAs when located in heterochromatin than in euchromatin. These methylated TE sequences with no or few matching siRNAs tend to show higher levels of DNA methylation towards their extremities and are typically ﬂanked on both sides by methylated TE sequences that are targeted by siRNAs. These observations suggest the existence of local spreading of DNA methylation from siRNA- targeted TE sequences. Further, we show that in euchromatin, both methylated and unmethylated TE sequences are most abundant close to genes. However, this preference is less pronounced for methylated, siRNA-targeted TE sequences upstream of genes. Based on these ﬁndings, we propose that the negative impact of siRNA-targeted TE sequences on the expression of neigh- boring genes which has been observed in Arabidopsis thaliana and Arabidopsis lyrata (8) results at least in part from local spreading of DNA methylation into promoter regions. MATERIALS AND METHODS Sequences The A. thaliana Release 5 genomic sequence was down- loaded from TIGR web site (http://ftp.tigr.org/pub/data/ a_thaliana/ath1/). Annotations Release 7 was obtained from TAIR as a dump of their database. The three TE reference sequence sets (Opt, Maxsize and OptCoding) used in addition to Repbase Update (RU) were described previously (7). TE detection pipeline TE sequence models were detected using the following com- bination of softwares: BLASTER (9,10), RepeatMasker (11), Censor (12,13). Satellite repeats were detected using RepeatMasker, Tandem Repeat Finder [TRF; (14) and mreps (15)]. The Torque resource manager was used to provide control over batch jobs and distributed compute nodes (http://www.clusterresources.com/pages/products/ torque-resource-manager.php). Results were stored in a MySQL database (http://www.mysql.com/). Each program was run independently. Parameters were chosen to make detection as sensitive as possible. The rate of false positives was minimized by running the TE detec- tion softwares on 200-kb fragments of genomic sequence shufﬂed by di-nucleotides using the program shufﬂe [HMMer Package; (16)]. For each of the programs BLASTER, RepeatMasker and Censor, the highest score obtained for these di-nucleotide shufﬂed chunks was used as a threshold to ﬁlter out the results obtained on the true genome chunks. Simple repeats were removed from the TE annotation. TE models <20 bp were discarded. RepeatMasker was run with the MaskerAid (17) search engine with sensitive parameters (‘–cutoff 200 –w –s –gccalc –nolow –no_is’). We found MaskerAid to be more sensitive and much faster than Cross-match, under sensitive parameters. Censor was used at high sensitivity with parameter ‘–s –ns’. BLASTER now uses WU- BLAST as a search engine, and has also been set to more sensitive parameters, (inspired from MaskerAid settings). We used Blaster with parameters ‘–W –S 4’. The RMBLR procedure (9) has been replaced by a new procedure, called ‘combinedBLR’, which now combines the results obtained from BLASTER, RepeatMasker and Censor and gives them to MATCHER for chaining. To do this, we normalized alignment scores to be the hit length times the identity percentage. The MATCHER program has been developed to map match results onto query sequences by ﬁrst ﬁltering overlapping hits. When two matches overlap on the genomic (query) sequence, the one with the best alignment score is kept, the other is truncated so that only non-overlapping regions remain on the match. As a result of this procedure a match is totally removed only if it is included in a longer one with a best score. Long insertions or deletions in the query or subject could result in two matches, instead of one with a long gap. Thus the remaining matches are chained by dynamic programming. A score is calculated by summing match scores and subtracting a gap penalty (0.05 times the gap length) as well as a mismatch penalty (0.2 times the mismatch length region), as described previously (18). The chaining algorithm [(19), pp. 325–329] is modiﬁed to produce local alignments. A match is associated with a chain of other matches only if this results in a higher score. The best-scoring chain is kept and the search is repeated minus this chain until no more chain is found. This algo- rithm is run independently for matches on strand +/+, +/ and /+. A maximum of 20 bp of overlap is allowed between matches. The chaining algorithm enables the recovery of TE sequences containing long insertions. Although BLASTER, RepeatMasker and Censor are front ends of the same WU-BLAST program, they cover respectively 21, 18 and 19 Mb of the genome sequence, when the RU TE reference set is used (Supplementary Table S3). Note that without any score threshold, they appear to have a high false positive rate (cover 90, 18 and 23 Mb, respectively). To reduce the false positive rates we rely on a statistical procedure to set their par- ameters at very high-sensitive values. Supplementary Table S4 shows TE-detection overlaps between the three softwares. BLASTER appears to be the most sensitive, followed by Censor and then RepeatMasker. This is a consequence of the different BLAST parameters used by these programs. When results obtained by the three programs are combined, TE coverage (excluding satellite) is increased to 21.7 Mb. The Arabidopsis genome contains several regions where TE sequences cluster, often as a result of nested insertions. These are particularly challenging to detect and classic annotation algorithms may fail to connect fragments of split TEs. This prompted us to implement a ‘long join’ procedure, which is based on age estimates of TE