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Special Issue "Mendel's and Wallace's 200 Year Anniversary–Modern Synthesis in the Genomics Era"

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: 15 April 2024 | Viewed by 234

Special Issue Editor

Special Issue Information

Dear Colleagues,

The years 2022 and 2023, respectively, mark Gregor Mendel's and Alfred Russel Wallace's 200-year anniversaries. Interestingly, the first centennial commemoration matched the “modern synthesis”, which refers to the early 20th century convergence of classical Wallace/Darwin selection theory with the allelic-based Mendelian genetics to explain the origin of biodiversity. Despite these efforts, each paradigm led to somehow different interpretations of the underlying genetic bases of traits under selection: the variance-focused Fisherian polygenetic conception on the one hand, and on the other hand the more deterministic single gene with major effects scenario. Separate sub-disciplines, the quantitative genetics and the molecular biology fields, ultimately embraced each paradigm. Despite quantitative genetics and genomics having better converged in recent decades, this interplay has not always been bidirectional. For example, molecular markers have largely served as tools to test the quantitative genetics hypothesis, yet until more recently, quantitative genetics theory has provided the framework to map underlying genes and molecular networks and predict their phenotypic consequences via modern polygenic risk scores and genomic prediction models. These latter innovations have partly been possible thanks to better sequencing and computer power. Consequently, it is expected and necessary that quantitative genetics and molecular biology continue converging, for instance, throughout the omics, big data and machine learning paradigms. Therefore, this Special Issue aims at presenting an overview of the 21st century “modern synthesis”, as a celebration of Mendel's and Wallace's 200-year anniversary, by compiling innovative trans-disciplinary research and methodologies across diverse study systems with the common denominator of pushing the integration of the fields of quantitative genetics and molecular biology via omics, modeling and big data tools.

Dr. Andrés J. Cortés
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • biodiversity
  • quantitative genetics
  • molecular genetics
  • comparative genomics
  • modeling
  • big data
  • omics
  • genomic prediction
  • machine learning

Published Papers

This special issue is now open for submission.
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