Genomics

Raman2RNA: Live-cell label-free prediction of single-cell RNA expression profiles by Raman microscopy

1. Koseki J. Kobayashi-Kirschvink
2. Shreya Gaddam
3. Taylor James-Sorenson
4. Emanuelle Grody
5. Johain R. Ounadjela
6. Baoliang Ge
7. Ke Zhang
8. Jeon Woong Kang
9. Ramnik Xavier
10. Peter T. C. So
11. Tommaso Biancalani
12. Jian Shu
13. Aviv Regev

Reviewed by Arcadia Science

Integrating bulk and single cell RNA-seq refines transcriptomic profiles of individual C. elegans neurons

1. Alec Barrett
2. Erdem Varol
3. Alexis Weinreb
4. Seth R Taylor
5. Rebecca M McWhirter
6. Cyril Cros
7. Berta Vidal
8. Manasa Basaravaju
9. Abigail Poff
10. John A Tipps
11. Maryam Majeed
12. Chen Wang
13. Emily A Bayer
14. Molly Reilly
15. Eviatar Yemini
16. HaoSheng Sun
17. Oliver Hobert
18. David M Miller
19. Marc Hammarlund

• Curated by eLife

  eLife Assessment

  This paper uses a new computational method that integrates bulk sequencing and single-cell sequencing data to provide refined gene expression datasets for 52 neuron classes in C. elegans. The paper's findings are convincing, presenting an approach that alleviates a key shortcoming of single-cell RNA sequencing. While the datasets have some limitations that the authors acknowledge, the new methodology and refined datasets will be important resources for those interested in understanding how gene expression shapes neuronal morphology and physiology.

Reviewed by eLife

10,239 whole genomes with multiomic and clinical health information as the Korean Multiomics Reference dataset

1. Kyungwhan An
2. Sungwon Jeon
3. Yoonsung Kwon
4. Yookyung Choi
5. Changhan Yoon
6. Yeonsu Jeon
7. Jihun Bhak
8. Dong-Hyun Shin
9. Hyoung-Jin Choi
10. Hyomin Lee
11. Yeo Jin Kim
12. Eun-Seok Shin
13. Hyojung Ryu
14. Asta Blazyte
15. Sangsoo Park
16. Juok Cho
17. Dan Bolser
18. Soobok Joe
19. Jin Ok Yang
20. Jongbum Jeon
21. Jong-Hwan Kim
22. Jungeun Kim
23. Dooyoung Jung
24. Yun Sung Cho
25. Kiyuk Chang
26. Eun Ho Choo
27. Eunmin Kim
28. Sang Yeub Lee
29. Weon Kim
30. Min Gyu Kang
31. Ae-Young Her
32. Suk Chon
33. Jeong-Taek Woo
34. Sang Youl Rhee
35. Siwoo Lee
36. Hyo-Jeong Ban
37. Hee-Jeong Jin
38. Younghwa Baek
39. Yong Min Ahn
40. Sang Jin Rhee
41. Min Ji Kim
42. Sang Yeol Lee
43. Chan-Mo Yang
44. Se-Hoon Shim
45. Seong-Jin Cho
46. Shin Gyeom Kim
47. Hyung-Tae Jung
48. Byung-Joo Ham
49. Yoon Young Choi
50. Jae-Ho Cheong
51. Seung-Ki Kim
52. Ji Hoon Phi
53. Seung Ah Choi
54. Heon Yung Gee
55. Sun Young Joo
56. Jinsei Jung
57. Wonsuk Shin
58. Sang-Hyuk Lee
59. Borah Kim
60. Woojae Myung
61. Chong Kun Cheon
62. Dong Uk Kim
63. Seok-Soo Byun
64. Gangnam Jin
65. Hojune Lee
66. Kyun Shik Chae
67. Chang Geun Kim
68. Bonghee Lee
69. Jaesuk Lee
70. Kwangwoo Kim
71. Semin Lee
72. Neung-Hwa Park
73. Haeyoung Jeong
74. George M. Church
75. Jong Bhak

Reviewed by Arcadia Science

Single-cell co-mapping reveals relationship between chromatin state and gene expression in early zebrafish development

1. Vivek Bhardwaj
2. Alberto Griffa
3. Helena Viñas Gaza
4. Peter Zeller
5. Alexander van Oudenaarden

• Curated by eLife

  eLife Assessment

  In this valuable study, the authors examine transcription and chromatin dynamics during early zebrafish development by simultaneously profiling histone modifications and full-length transcriptomes in thousands of single cells, providing solid analysis that chromatin and transcriptional states are initially weakly correlated in early embryonic cells and become progressively more aligned as differentiation proceeds. The work also supports a model in which promoter-anchored cis-spreading of H3K27me3 contributes to stable gene silencing during development. Future functional perturbations and orthogonal validations will be important to determine the causal contribution of Polycomb spreading to fate commitment. Overall, the dataset and accompanying analyses provide a robust resource and a quantitative framework for studying chromatin-transcription relationships during vertebrate embryogenesis.

  [Editors' note: this paper was reviewed by Review Commons.]

Reviewed by eLife, Review Commons

Nanopore genome skimming with Illumina polishing yields highly accurate mitogenome sequences: a case study of Niphargus amphipods

1. Alice Salussolia
2. Ninon Lecoquierre
3. Fabio Stoch
4. Jean-François Flot

Reviewed by Peer Community In Zoology

Breaking Through Biology's Data Wall: Expanding the Known Tree of Life by Over 10x using a Global Biodiscovery Pipeline

1. Oliver Vince
2. Phoebe Oldach
3. Valerio Pereno
4. Marcus H Y Leung
5. Carla Greco
6. Gus Minto-Cowcher
7. Saif Ur-Rehman
8. Keith Y K Kam
9. William Chow
10. Emma Bolton
11. Bupe R Mwambingu
12. Nadine L Greenhalgh
13. Ineke E Knot
14. Leif Christoffersen
15. Marlon Clark
16. Robert Pecoraro
17. Aaron W Kollasch
18. Tanggis Bohnuud
19. Matthew Bakalar
20. Philipp Lorenz
21. Glen Gowers

Reviewed by Arcadia Science

Mechanistic dissection of GRHL2 and PR transcriptional co-regulation in breast cells

1. M.T. Aarts
2. A. Nordin
3. C. Cantù
4. A.L. van Boxtel
5. R. van Amerongen

Reviewed by Review Commons

Multimodal single-cell analyses reveal distinct fusion-regulated transcriptional programs in Ewing sarcoma

1. Olivia G Waltner
2. April A Apfelbaum
3. Emma D Wrenn
4. Shruti S Bhise
5. Sami B Kanaan
6. Rula Green Gladden
7. Mark A Mendoza
8. Roger Volden
9. Zev Kronenberg
10. Anand Patel
11. Michael Dyer
12. Jay F Sarthy
13. Elizabeth R Lawlor
14. Scott N Furlan

• Curated by eLife

  eLife Assessment

  This valuable study presents an analysis of the gene regulatory networks that contribute to tumour heterogeneity and tumor plasticity in Ewing sarcoma, with key implications for other fusion-driven sarcomas. The authors convincingly employed orthogonal approaches, including single-cell sequencing and xenografts, to reveal the existence and plasticity of specific gene regulatory networks (e.g., TGF-beta signaling) within Ewing sarcoma, as well as significant differences that exist between cell lines and patient tumors.

Reviewed by eLife

A high-coverage genome from a 200,000-year-old Denisovan

1. Stéphane Peyrégne
2. Diyendo Massilani
3. Yaniv Swiel
4. Michael James Boyle
5. Leonardo N. M. Iasi
6. Arev P. Sümer
7. Alba Bossoms Mesa
8. Cesare de Filippo
9. Bence Viola
10. Elena Essel
11. Sarah Nagel
12. Julia Richter
13. Antje Weihmann
14. Barbara Schellbach
15. Hugo Zeberg
16. Johann Visagie
17. Maxim B. Kozlikin
18. Michael V. Shunkov
19. Anatoly P. Derevianko
20. Kay Prüfer
21. Benjamin M. Peter
22. Matthias Meyer
23. Svante Pääbo
24. Janet Kelso

Reviewed by preLights

Beyond the transcript: chromatin implications in trans-splicing in Trypanosomatids

1. Romina Trinidad Zambrano Siri
2. Paula Beati
3. Lucas Inchausti
4. Pablo Smircich
5. Guillermo Daniel Alonso
6. Josefina Ocampo

Reviewed by Review Commons