Evolutionary Biology

No evidence for disassortative mating based on HLA in a small-scale, endogamous population

1. Gillian L Meeks
2. Brooke Scelza
3. Katherine. M Kichula
4. Catrinel Berevoescu
5. Kristin Hardy
6. Ticiana DJ Farias
7. Genelle F Harrison
8. Nicholas R Pollock
9. Neus Font-Porterias
10. Sean Prall
11. Paul J Norman
12. Brenna M Henn

• Curated by eLife

  eLife Assessment

  This important study addresses the long-debated hypothesis that humans preferentially choose partners with dissimilar immune genes, using data from a small-scale society that allows comparison between arranged and self-chosen partnerships. Across multiple analyses controlling for genome-wide relatedness and examining functional immune diversity, the authors find no evidence of HLA/MHC-based (dis)assortative mating, suggesting that immune gene variation has limited influence on mate choice in this relatively homogeneous population and that the observed patterns instead reflect selection acting directly on immune loci. While the strength of the evidence is compelling for this population, several conclusions rely on indirect reconstruction methods and imputed data for a very complex region of the genome, which may limit how firmly some claims can be supported.

Reviewed by eLife

Wing shape evolution is not constrained by ancestral genetic covariances in the invasive Drosophila suzukii

1. Antoine Fraimout
2. Stéphane Chantepie
3. Nicolas Navarro
4. Céline Teplitsky
5. Vincent Debat

Reviewed by Peer Community in Evolutionary Biology

Evolutionary adaptation proceeds through a small number of phenotypic modules

1. Mohammad Hossein Donyavi
2. Reza Ghelich
3. Kara Schmidlin
4. Grant Kinsler
5. Kerry Geiler-Samerotte

Reviewed by Arcadia Science

Evidence of latency reshapes our understanding of Ebola virus reservoir dynamics

1. John T. McCrone
2. Guy Baele
3. Ifeanyi F. Omah
4. Eddy Kinganda-Lusamaki
5. Joseph A. Brew
6. Luiz M. Carvalho
7. Nicola F. Müller
8. Gytis Dudas
9. Placide Mbala-Kingebeni
10. Marc A. Suchard
11. Andrew Rambaut

Reviewed by Rapid Reviews Infectious Diseases, PREreview

The population structure of invasive Lantana camara is shaped by its mating system

1. P Praveen
2. Rajesh Gopal
3. Uma Ramakrishnan

• Curated by eLife

  eLife Assessment

  The submission by Praveen et al. reports important findings describing the structure of genetic and colour variation in its native range for the globally invasive weed Lantana camara. Whilst the importance of the research question and the scale of the sampling is appreciated, the analysis, which is currently incomplete, requires further tests to support the claims made by the authors.

Reviewed by eLife

Heterozygote advantage cannot explain MHC diversity, but MHC diversity can explain heterozygote advantage

1. Joshua L Cherry

• Curated by eLife

  eLife Assessment

  This valuable study re-evaluates a published simulation model on the role of heterozygote advantage in shaping MHC diversity. By modifying key modeling assumptions, the author argues that the original conclusions depend on a narrow and potentially unrealistic parameter range. While the work is in principle solid, the robustness of this claim is viewed differently by the reviewers. The manuscript further proposes an alternative modeling framework in which expansion of the MHC gene family allows homozygotes to outperform heterozygotes, thereby challenging the idea that heterozygote advantage alone can account for high allelic diversity at MHC loci. The topic is highly relevant for eco-immunology and evolutionary genetics, although a clearer delineation of the model's scope would help readers assess its broader implications.

Reviewed by eLife

Contrasting evolutionary forces of specialization and admixture underlie the genomic and phenotypic diversity of Yarrowia lipolytica

1. Sergio Izquierdo-Gea
2. Javier Vicente
3. Tomás A. Peña
4. Pablo Villarreal
5. Francisco A. Cubillos
6. Cécile Neuvéglise
7. Jorge Barriuso
8. Ignacio Belda
9. Javier Ruiz

Reviewed by Arcadia Science

Identification and comparison of orthologous cell types from primate embryoid bodies shows limits of marker gene transferability

1. Jessica Jocher
2. Philipp Janssen
3. Beate Vieth
4. Fiona C Edenhofer
5. Tamina Dietl
6. Anita Térmeg
7. Paulina Spurk
8. Johanna Geuder
9. Wolfgang Enard
10. Ines Hellmann

• Curated by eLife

  eLife Assessment

  The authors make an important contribution to comparative functional genomics by developing a semi-automated computational pipeline that integrates classification and marker-based cluster annotation to identify orthologous cell types. Using a single-cell RNA-seq dataset of induced pluripotent stem cells and derived embryonic bodies from four primate species: humans, orangutans, cynomolgus macaques, and rhesus macaques, the authors provide convincing evidence that cell type-specific marker genes are substantially less transferable across species than broadly expressed genes, with transferability declining as phylogenetic distance increases. This study establishes a key framework and reference dataset for comparative single-cell analyses and encourages more rigorous evaluation of marker gene transferability across species.

Reviewed by eLife

An interpretable neural network unveils higher-order epistasis in large protein sequence-function relationships

1. Palash Sethi
2. Juannan Zhou

• Curated by eLife

  eLife Assessment

  In this important work, the authors present a new transformer-based neural network designed to isolate and quantify higher-order epistasis in protein sequences. They provide solid evidence that higher-order epistasis can play key roles in protein function. This work will be of interest to the communities interested in modeling biological sequence data and understanding mutational effects.

Reviewed by eLife

Separating selection from mutation in antibody language models

1. Frederick A Matsen
2. Will Dumm
3. Kevin Sung
4. Mackenzie M Johnson
5. David H Rich
6. Tyler N Starr
7. Yun S Song
8. Julia Fukuyama
9. Hugh K Haddox

• Curated by eLife

  eLife Assessment

  This fundamental study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides convincing evidence that separating selection from the nucleotide-level mutation process improves performance over the objectives of protein language models inspired by natural language processing. This paper should be of interest to computational immunologists, but also to the broader community interested in deep learning for biological sequence data and evolution.

Reviewed by eLife