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HALPER facilitates the identification of regulatory element orthologs across species.
Zhang, Xiaoyu; Kaplow, Irene M; Wirthlin, Morgan; Park, Tae Yoon; Pfenning, Andreas R.
Afiliação
  • Zhang X; Department of Computer Science.
  • Kaplow IM; Department of Computational Biology.
  • Wirthlin M; Neuroscience Institute.
  • Park TY; Department of Computational Biology.
  • Pfenning AR; Neuroscience Institute.
Bioinformatics ; 36(15): 4339-4340, 2020 08 01.
Article em En | MEDLINE | ID: mdl-32407523
ABSTRACT

SUMMARY:

Diverse traits have evolved through cis-regulatory changes in genome sequence that influence the magnitude, timing and cell type-specificity of gene expression. Advances in high-throughput sequencing and regulatory genomics have led to the identification of regulatory elements in individual species, but these genomic regions remain difficult to align across taxonomic orders due to their lack of sequence conservation relative to protein coding genes. The groundwork for tracing the evolution of regulatory elements is provided by the recent assembly of hundreds of genomes, the generation of reference-free Cactus multiple sequence alignments of these genomes, and the development of the halLiftover tool for mapping regions across these alignments. We present halLiftover Post-processing for the Evolution of Regulatory Elements (HALPER), a tool for constructing contiguous regulatory element orthologs from the outputs of halLiftover. We anticipate that this tool will enable users to efficiently identify orthologs of regulatory elements across hundreds of species, providing novel insights into the evolution of traits that have evolved through gene expression. AVAILABILITY AND IMPLEMENTATION HALPER is implemented in python and available on github https//github.com/pfenninglab/halLiftover-postprocessing. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Genômica Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Genômica Idioma: En Ano de publicação: 2020 Tipo de documento: Article