The domestic Bactrian camels were treated as one of the principal means of locomotion between the eastern and western cultures in history. However, whether they originated from East Asia or Central Asia remains elusive. To address this question, we perform whole-genome sequencing of 128 camels across Asia. The extant wild and domestic Bactrian camels show remarkable genetic divergence, as they were split from dromedaries. The wild Bactrian camels also contribute little to the ancestry of domestic ones, although they share close habitat in East Asia. Interestingly, among the domestic Bactrian camels, those from Iran exhibit the largest genetic distance and the earliest split from all others in the phylogeny, despite evident admixture between domestic Bactrian camels and dromedaries living in Central Asia. Taken together, our study support the Central Asian origin of domestic Bactrian camels, which were then immigrated eastward to Mongolia where native wild Bactrian camels inhabit.

The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global research in both academia and industry. With the explosively accumulated multi-omics data at ever-faster rates, CNCB-NGDC is constantly scaling up and updating its core database resources through big data archive, curation, integration and analysis. In the past year, efforts have been made to synthesize the growing data and knowledge, particularly in single-cell omics and precision medicine research, and a series of resources have been newly developed, updated and enhanced. Moreover, CNCB-NGDC has continued to daily update SARS-CoV-2 genome sequences, variants, haplotypes and literature. Particularly, OpenLB, an open library of bioscience, has been established by providing easy and open access to a substantial number of abstract texts from PubMed, bioRxiv and medRxiv. In addition, Database Commons is significantly updated by cataloguing a full list of global databases, and BLAST tools are newly deployed to provide online sequence search services. All these resources along with their services are publicly accessible at https://ngdc.cncb.ac.cn.

Spotting off-targets from gene editing: Unintended genomic modifications limit the potential therapeutic use of gene-editing tools. Available methods to find off-targets generally do not work in vivo or detect single-nucleotide changes. Three papers in this issue report new methods for monitoring gene-editing tools in vivo (see the Perspective by Kempton and Qi). Wienert et al. followed the recruitment of a DNA repair protein to DNA breaks induced by CRISPR-Cas9, enabling unbiased detection of off-target editing in cellular and animal models. Zuo et al. identified off-targets without the interference of natural genetic heterogeneity by injecting base editors into one blastomere of a two-cell mouse embryo and leaving the other genetically identical blastomere unedited. Jin et al. performed whole-genome sequencing on individual, genome-edited rice plants to identify unintended mutations. Cytosine, but not adenine, base editors induced numerous single-nucleotide variants in both mouse and rice. Science , this issue p. 286 , p. 289 , p. 292 ; see also p. 234

The National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support the global academic and industrial communities. With the rapid accumulation of multi-omics data at an unprecedented pace, CNCB-NGDC continuously expands and updates core database resources through big data archiving, integrative analysis and value-added curation. Importantly, NGDC collaborates closely with major international databases and initiatives to ensure seamless data exchange and interoperability. Over the past year, significant efforts have been dedicated to integrating diverse omics data, synthesizing expanding knowledge, developing new resources, and upgrading major existing resources. Particularly, several database resources are newly developed for the biodiversity of protists (P10K), bacteria (NTM-DB, MPA) as well as plant (PPGR, SoyOmics, PlantPan) and disease/trait association (CROST, HervD Atlas, HALL, MACdb, BioKA, BioKA, RePoS, PGG.SV, NAFLDkb). All the resources and services are publicly accessible at https://ngdc.cncb.ac.cn.

Background: Microarrays revolutionized biological research by enabling gene expression comparisons on a transcriptome-wide scale. Microarrays, however, do not estimate absolute expression level accurately. At present, high throughput sequencing is emerging as an alternative methodology for transcriptome studies. Although free of many limitations imposed by microarray design, its potential to estimate absolute transcript levels is unknown. Results: In this study, we evaluate relative accuracy of microarrays and transcriptome sequencing (RNA-Seq) using third methodology: proteomics. We find that RNA-Seq provides a better estimate of absolute expression levels. Conclusion: Our result shows that in terms of overall technical performance, RNA-Seq is the technique of choice for studies that require accurate estimation of absolute transcript levels.