Genotyping-by-sequencing for biogeography

被引:9
|
作者
Vaux, Felix [1 ]
Dutoit, Ludovic [1 ]
Fraser, Ceridwen, I [2 ]
Waters, Jonathan M. [1 ]
机构
[1] Univ Otago, Dept Zool, Dunedin, New Zealand
[2] Univ Otago, Dept Marine Sci, Dunedin, New Zealand
关键词
GBS; genomic; phylogeography; RADseq; molecular ecology; species delimitation; SINGLE NUCLEOTIDE POLYMORPHISM; R-PACKAGE; POPULATION-STRUCTURE; GENOME SCANS; TOOL SET; SNP DATA; RADSEQ; INFERENCE; GENETICS; MARKERS;
D O I
10.1111/jbi.14516
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Aim Genotyping-by-sequencing (GBS) and similar reduced-representation sequencing methods, such as restriction site-associated DNA sequencing (RADseq), have been revolutionary for genetic analyses in biogeography. However, navigating the many different methodological and analytical approaches and numerous sources of potential error can be overwhelming. We provide an overview of key considerations for biogeographical research using GBS, from sample design through data filtering to the sharing of data, which should particularly assist new users. Taxon All taxa. Location Worldwide. Methods We review recent advances for GBS and compare differences among GBS methods and analytical approaches. We highlight the concerns most relevant for biogeographical research, and emphasise practical limitations for studies on non-model organisms. Results GBS methods vary substantially and recent literature demonstrates the need for careful study design and data filtering relevant to the study organism and hypothesis under investigation. Biogeographical research using non-model organisms or long-term sampling are likely to face some practical limitations compared to ideal GBS study designs. The methodological information recorded in published manuscripts often varies. We outline a general framework for planning and undertaking biogeographical research using GBS. Main conclusions GBS and similar approaches have grown rapidly in popularity for biogeographical research. Evaluating, recording and justifying decisions throughout a GBS workflow-across sampling, library preparation and sequencing, identifying and filtering samples and loci, biogeographical analyses, and sharing data-is crucial for improving scientific reproducibility and compatibility among GBS datasets. This review outlines ways to improve and simplify GBS research, thereby enhancing our capacity to use genomic data to address broad-scale biogeographical questions.
引用
收藏
页码:262 / 281
页数:20
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