Chromosome-level genome assembly of the Tyrrhenian tree frog (Hyla sarda).

IF 6.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Josephine R Paris, Roberta Bisconti, Andrea Chiocchio, Linelle Abueg, Dominic E Absolon, Tatiana Tilley, Nivesh Jain, Jennifer Balacco, Brian O'Toole, Erich D Jarvis, Giulio Formenti, Daniele Salvi, Daniele Canestrelli
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Abstract

The Tyrrhenian tree frog (Hyla sarda) is a small cryptically coloured amphibian found in Corsica, Sardinia, and the Tuscan Archipelago. Investigation into the species' evolutionary history has revealed phenotypic changes triggered by glaciation-induced range expansion, but understanding the genetic basis of this trait variation has been hampered by the lack of a reference genome. To address this, we assembled a chromosome-level genome of Hyla sarda using PacBio HiFi long reads, Bionano optical maps, and Hi-C data. The assembly comprises 13 assembled chromosomes, spanning a total length of 4.15 Gb with a scaffold N50 of 385 Mb, a BUSCO completeness of 94.60%, and a k-mer completeness of 98.30%. Approximately 75% of the genome consists of repetitive elements. We annotated 22,847 protein-coding genes with a BUSCO completeness of 94.60% and an OMArk completeness of 93.74%. This high-quality assembly provides a valuable resource for studying phenotypic evolution and its genomic basis during range expansion, and will assist future investigations into the population and conservation genomics of Hyla sarda.

Abstract Image

Abstract Image

第勒尼安树蛙(Hyla sarda)染色体水平基因组组装。
第勒尼安树蛙(Hyla sarda)是一种小型的神秘色彩的两栖动物,发现于科西嘉岛、撒丁岛和托斯卡纳群岛。对该物种进化史的研究揭示了由冰川引起的范围扩张引发的表型变化,但由于缺乏参考基因组,对这种性状变异的遗传基础的理解受到阻碍。为了解决这个问题,我们使用PacBio HiFi长读数、Bionano光学图和Hi-C数据组装了海拉藻的染色体水平基因组。该组装体包括13条组装染色体,全长4.15 Gb,支架N50为385 Mb, BUSCO完整性为94.60%,k-mer完整性为98.30%。大约75%的基因组由重复元素组成。我们注释了22,847个蛋白质编码基因,BUSCO完整性为94.60%,OMArk完整性为93.74%。这一高质量的组合为研究海苔在种群扩展过程中的表型进化及其基因组基础提供了宝贵的资源,并将有助于未来海苔种群和保护基因组学的研究。
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来源期刊
Scientific Data
Scientific Data Social Sciences-Education
CiteScore
11.20
自引率
4.10%
发文量
689
审稿时长
16 weeks
期刊介绍: Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.
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