CNEFinder: finding conserved non-coding elements in genomes

Abstract

MotivationConserved non-coding elements (CNEs) represent an enigmatic class of genomic elements which, despite being extremely conserved across evolution, do not encode for proteins. Their functions are still largely unknown. Thus, there exists a need to systematically investigate their roles in genomes. Towards this direction, identifying sets of CNEs in a wide range of organisms is an important first step. Currently, there are no tools published in the literature for systematically identifying CNEs in genomes.ResultsWe fill this gap by presenting CNEFinder; a tool for identifying CNEs between two given DNA sequences with user-defined criteria. The results presented here show the tool’s ability of identifying CNEs accurately and efficiently. CNEFinder is based on a k-mer technique for computing maximal exact matches. The tool thus does not require or compute whole-genome alignments or indexes, such as the suffix array or the Burrows Wheeler Transform (BWT), which makes it flexible to use on a wide scale.Availability and implementationFree software under the terms of the GNU GPL (https://github.com/lorrainea/CNEFinder).

CNEr: A toolkit for exploring extreme noncoding conservation

“…A summary of these resources is available in the review by Polychronopoulos et al [6]. To our knowledge, there are only two tools available for the identification of conserved elements: PHAST [19] and CNEFinder [20]. The former relies on multiple sequence alignments, the preparation of which can be tedious and computationally intensive, unless available at UCSC website.…”

A survey of k-mer methods and applications in bioinformatics

“…2 D) [56] . These methods enable comparative analysis of k-mer occurrences and distributions across genomes, facilitating the identification of conserved regions, gene families, regulatory motifs, and genomic rearrangements to better understand evolutionary relationships [51] , [111] , [112] , [113] . One primary application of k-mers in comparative genomics is constructing phylogenetic trees by quantifying the genetic distance between species based on k-mer frequencies [114] , [115] , [116] , [117] , [118] .…”

Range Shortest Unique Substring Queries

“…If α = β the answer (α, 1) is trivial. So, in the rest we assume that α < β. and a query [α, β] = [5,16], we need to find a shortest substring of T with exactly one occurrence in [5,16]. The output here is (p, ) = (10, 2), because T [10,11] = ac is the shortest substring of T with exactly one occurrence in [5,16].…”

“…Range query data structures have also been considered specifically for strings [1,3,4,12]. For instance, in bioinformatics applications we are often interested in finding regularities in certain regions of a DNA sequence [5,17]. In the Range-LCP problem, defined by Amir et al [3], the task is to construct a data structure over T to be able to answer the following type of online queries efficiently.…”