scholarly journals Gene prediction by multiple syntenic alignment

2005 ◽  
Vol 2 (1) ◽  
pp. 38-47
Author(s):  
Said S. Adi ◽  
Carlos E. Ferreira

Summary Given the increasing number of available genomic sequences, one now faces the task of identifying their functional parts, like the protein coding regions. The gene prediction problem can be addressed in several ways. One of the most promising methods makes use of similarity information between the genomic DNA and previously annotated sequences (proteins, cDNAs and ESTs). Recently, given the huge amount of newly sequenced genomes, new similarity-based methods are being successfully applied in the task of gene prediction. The so-called comparative-based methods lie in the similarities shared by regions of two evolutionary related genomic sequences. Despite the number of different gene prediction approaches in the literature, this problem remains challenging. In this paper we present a new comparative-based approach to the gene prediction problem. It is based on a syntenic alignment of three or more genomic sequences. With syntenic alignment we mean an alignment that is constructed taking into account the fact that the involved sequences include conserved regions intervened by unconserved ones. We have implemented the proposed algorithm in a computer program and confirm the validity of the approach on a benchmark including triples of human, mouse and rat genomic sequences.

2013 ◽  
Vol 647 ◽  
pp. 471-475
Author(s):  
Ling Ke Wang ◽  
Ji Xian Meng ◽  
Hai Peng Zhu ◽  
Xin Zhong Lu

Identification of protein-coding regions is a hot research area at present. After using mapping methods to turn symbolic genomic sequences into numeric sequences, we need to do the transform to show the period-3 component of protein-coding regions. In this paper, we find twofast algorithms relying on discrete Fourier transform and the extension of Signal Noise Ratio to compute the period-3 component of protein-coding regions.


1995 ◽  
Vol 248 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Eric E. Snyder ◽  
Gary D. Stormo

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Mireia Vilardell ◽  
Genis Parra ◽  
Sergi Civit

Classically, gene prediction programs are based on detecting signals such as boundary sites (splice sites, starts, and stops) and coding regions in the DNA sequence in order to build potential exons and join them into a gene structure. Although nowadays it is possible to improve their performance with additional information from related species or/and cDNA databases, further improvement at any step could help to obtain better predictions. Here, we present WISCOD, a web-enabled tool for the identification of significant protein coding regions, a novel software tool that tackles the exon prediction problem in eukaryotic genomes. WISCOD has the capacity to detect real exons from large lists of potential exons, and it provides an easy way to use globalPvalue called expected probability of being a false exon (EPFE) that is useful for ranking potential exons in a probabilistic framework, without additional computational costs. The advantage of our approach is that it significantly increases the specificity and sensitivity (both between 80% and 90%) in comparison to other ab initio methods (where they are in the range of 70–75%). WISCOD is written in JAVA and R and is available to download and to run in a local mode on Linux and Windows platforms.


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Ayako Nishizawa ◽  
Kazuki Kumada ◽  
Keiko Tateno ◽  
Maiko Wagata ◽  
Sakae Saito ◽  
...  

AbstractPreeclampsia is a pregnancy-induced disorder that is characterized by hypertension and is a leading cause of perinatal and maternal–fetal morbidity and mortality. HLA-G is thought to play important roles in maternal–fetal immune tolerance, and the associations between HLA-G gene polymorphisms and the onset of pregnancy-related diseases have been explored extensively. Because contiguous genomic sequencing is difficult, the association between the HLA-G genotype and preeclampsia onset is controversial. In this study, genomic sequences of the HLA-G region (5.2 kb) from 31 pairs of mother–offspring genomic DNA samples (18 pairs from normal pregnancies/births and 13 from preeclampsia births) were obtained by single-molecule real-time sequencing using the PacBio RS II platform. The HLA-G alleles identified in our cohort matched seven known HLA-G alleles, but we also identified two new HLA-G alleles at the fourth-field resolution and compared them with nucleotide sequences from a public database that consisted of coding sequences that cover the 3.1-kb HLA-G gene span. Intriguingly, a potential association between preeclampsia onset and the poly T stretch within the downstream region of the HLA-G*01:01:01:01 allele was found. Our study suggests that long-read sequencing of HLA-G will provide clues for characterizing HLA-G variants that are involved in the pathophysiology of preeclampsia.


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