Systems Biology

DGRPool: A web tool leveraging harmonized Drosophila Genetic Reference Panel phenotyping data for the study of complex traits

1. Vincent Gardeux
2. Roel PJ Bevers
3. Fabrice PA David
4. Emily Rosschaert
5. Romain Rochepeau
6. Bart Deplancke

• Curated by eLife

  eLife Assessment

  Genetic analysis of complex traits in Drosophila provides a resource for exploring the relationship between genetic and phenotypic variation. The web tool DGRPool presented in this paper makes data and results from the Drosophila Genetic Reference Panel accessible that will enable downstream analyses of genetic association. The findings of this paper are considered to be important, with practical implications beyond a single subfield, supported by convincing evidence using appropriate and validated methodology in line with current state of the art.

Reviewed by eLife

Mitochondrial respiration atlas reveals differential changes in mitochondrial function across sex and age

1. Dylan C Sarver
2. Muzna Saqib
3. Fangluo Chen
4. G William Wong

• Curated by eLife

  eLife assessment

  This important study provides a comprehensive assessment of mitochondrial function across age and sex in mice. The strength of evidence supporting this resource is compelling, given the exhaustive number of tissues profiled and in-depth analyses performed.

Reviewed by eLife

A mathematical model for ketosis-prone diabetes suggests the existence of multiple pancreatic β-cell inactivation mechanisms

1. Sean A Ridout
2. Priyathama Vellanki
3. Ilya Nemenman

• Curated by eLife

  eLife assessment:

  This theoretical study makes a useful contribution to our understanding of a subtype of type 2 diabetes – ketosis-prone diabetes mellitus (KPD) – with a potential impact on our broader understanding of diabetes and glucose regulation. The article presents an ordinary differential equation-based model for KPD that incorporates a number of distinct timescales – fast, slow, as well as intermediate, incorporating a key hypothesis of reversible beta cell deactivation. The presented evidence is solid and shows that observed clinical disease trajectories may be explained by a simple mathematical model in a particular parameter regime.

Reviewed by eLife

Passive shaping of intra- and intercellular m6A dynamics via mRNA metabolism

1. David Dierks
2. Ran Shachar
3. Ronit Nir
4. Miguel Angel Garcia-Campos
5. Anna Uzonyi
6. Ursula Toth
7. Walter Rossmanith
8. Lior Lasman
9. Boris Slobodin
10. Jacob H Hanna
11. Yaron Antebi
12. Ruth Scherz-Shouval
13. Schraga Schwartz

• Curated by eLife

  eLife assessment

  This study presents a fundamental finding on how levels of m6A levels are controlled, invoking a consolidated model where degradation of modified RNAs in the cytoplasm plays a primary role in shaping m6A patterns and dynamics, rather than needing active regulation by m6A erasers and other related processes. The evidence is compelling and uses transcriptome-wide data and mechanistic modeling. However, it is possible that m6A-erasers will have roles in specific developmental contexts or conditions, so this model may not apply universally.

Reviewed by eLife

CausalXtract: a flexible pipeline to extract causal effects from live-cell time-lapse imaging data

1. Franck Simon
2. Maria Colomba Comes
3. Tiziana Tocci
4. Louise Dupuis
5. Vincent Cabeli
6. Nikita Lagrange
7. Arianna Mencattini
8. Maria Carla Parrini
9. Eugenio Martinelli
10. Hervé Isambert

• Curated by eLife

  eLife assessment

  In this fundamental study, the authors describe a new data processing pipeline that can be used to discover causal interactions from time-lapse imaging data. The utility of this pipeline was convincingly illustrated using tumor-on-chip ecosystem data. The newly developed pipeline could be used to better understand cell-cell interactions and could also be applied to perform temporal causal discovery in other areas of science, meaning this work could potentially have a wide range of applications.

Reviewed by eLife

Genome-wide conditional degron libraries for functional genomics

1. Eduardo Gameiro
2. Karla A. Juárez-Núñez
3. Jia Jun Fung
4. Susmitha Shankar
5. Brian Luke
6. Anton Khmelinskii

Reviewed by Review Commons

Transplantation of exogenous mitochondria mitigates myocardial dysfunction after cardiac arrest

1. Zhen Wang
2. Jie Zhu
3. Mengda Xu
4. Xuyuan Ma
5. Maozheng Shen
6. Jingyu Yan
7. Guosheng Gan
8. Xiang Zhou

• Curated by eLife

  eLife assessment

  This study presents valuable findings on how mitochondrial transplantation affects post-cardiac arrest myocardial dysfunction (PAMD). The authors demonstrate that mitochondrial transplantation enhances cardiac function, increases survival rates after the return of spontaneous circulation (ROSC). While the findings are promising, the organization of the paper, along with the analysis and interpretation of the results, are inadequate and need revision.

Reviewed by eLife

Unveiling Gene Perturbation Effects through Gene Regulatory Networks Inference from single-cell transcriptomic data

1. Clelia Corridori
2. Merrit Romeike
3. Giorgio Nicoletti
4. Christa Buecker
5. Samir Suweis
6. Sandro Azaele
7. Graziano Martello

Reviewed by Review Commons

Systems genomics of salinity stress response in rice

1. Sonal Gupta
2. Simon C Groen
3. Maricris L Zaidem
4. Andres Godwin C Sajise
5. Irina Calic
6. Mignon A Natividad
7. Kenneth L McNally
8. Georgina V Vergara
9. Rahul Satija
10. Steven J Franks
11. Rakesh K Singh
12. Zoé Joly-Lopez
13. Michael D Purugganan

• Curated by eLife

  eLife assessment

  Working with a diverse panel of field-grown rice accessions, this valuable study measures changes in transcript abundance, tests for patterns of selection on gene expression, and maps the genetic basis of variation in gene expression in normal and high salinity conditions. The authors provide solid evidence that salinity treatment increases the number of genes with mean expression levels away from the optimum, and that a relatively small number of genes are hotspots for genetic variants that affect genome-wide patterns of variation in gene expression under high salinity. The design, clarity, and interpretation of several statistical analyses can be improved, additional opportunities for integration among datasets and analyses could be realized, and genetic manipulation would be required to confirm the functional involvement of any specific genes in regulatory networks or organismal traits that confer adaptation to higher salinity conditions. The manuscript will not only be of interest to evolutionary biologists studying the genetics of complex traits, but it will also be a resource for plant biologists studying mechanisms of abiotic stress tolerance.

Reviewed by eLife

Inference of gene regulatory networks for overcoming low performance in real-world data

1. Yusuke Hiki
2. Yuta Tokuoka
3. Takahiro G. Yamada
4. Akira Funahashi

Reviewed by Arcadia Science