Sensommatic: an efficient pipeline to mine and predict sensory receptor genes in the era of reference-quality genomes

Author:

Ryan Louise1ORCID,Lawless Colleen1ORCID,Hughes Graham M1ORCID

Affiliation:

1. School of Biology and Environmental Science, University College Dublin , Belfield, Dublin 4, Ireland

Abstract

Abstract Summary Sensory receptor gene families have undergone extensive expansion and loss across vertebrate evolution, leading to significant variation in receptor counts between species. However, due to their species-specific nature, conventional reference-based annotation tools often underestimate the true number of sensory receptors in a given species. While there has been an exponential increase in the taxonomic diversity of publicly available genome assemblies in recent years, only ∼30% of vertebrate species on the NCBI database are currently annotated. To overcome these limitations, we developed ‘Sensommatic’, an automated and accessible sensory receptor annotation pipeline. Sensommatic implements BLAST and AUGUSTUS to mine and predict sensory receptor genes from whole genome assemblies, adopting a one-to-many gene mapping approach. While designed for vertebrates, Sensommatic can be extended to run on non-vertebrate species by generating customized reference files, making it a scalable and generalizable tool. Availability and implementation Source code and associated files are available at: https://github.com/GMHughes/Sensommatic

Funder

Science Foundation Ireland

Publisher

Oxford University Press (OUP)

Reference24 articles.

1. Basic local alignment search tool;Altschul;J Mol Biol,1990

2. UniProt: the universal protein knowledgebase in 2023;Bateman;Nucleic Acids Research,2022

3. Accelerated profile HMM searches;Eddy;PLoS Comput Biol,2011

4. The era of reference genomes in conservation genomics;Formenti;Trends Ecol Evol,2022

5. A comparative genomics multitool for scientific discovery and conservation;Genereux;Nature,2020

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3