Xiaofeng Wei

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development.

With the application and development of high-throughput sequencing technology in life and health sciences, massive multi-omics data brings the problem of efficient management and utilization. Database development and biocuration are the prerequisites for the reuse of these big data. Here, relying on China National GeneBank (CNGB), we present CNGB Sequence Archive (CNSA) for archiving omics data, including raw sequencing data and its further analyzed results which are organized into six objects, namely Project, Sample, Experiment, Run, Assembly and Variation at present. Moreover, CNSA has created a correlation model of living samples, sample information and analytical data on some projects. Both living samples and analytical data are directly correlated with the sample information. From either one, information or data of the other two can be obtained, so that all data can be traced throughout the life cycle from the living sample to the sample information to the analytical data. Complying with the data standards commonly used in the life sciences, CNSA is committed to building a comprehensive and curated data repository for storing, managing and sharing of omics data. We will continue to improve the data standards and provide free access to open-data resources for worldwide scientific communities to support academic research and the bio-industry. Database URL: https://db.cngb.org/cnsa/.

Description

Accurate and up-to-date data on the frequency of haemoglobinopathies among the populations of Guangxi Zhuang Autonomous Region, where haemoglobinopathies are most endemic in China, are required. In our study, a total of 5789 samples obtained from members of the Han, Zhang, and Yao ethnic groups in six geographical areas of Guangxi Province were analysed systematically in terms of both haematological and molecular parameters. The results presented that the total heterozygote frequency of thalassaemias and other haemoglobinopathies was 24.51%, of which 17.55% was due to alpha-thalassaemia, 6.43% to beta-thalassaemia, 0.38% to structural haemoglobin variants, and 0.16% to delta-thalassaemia. The mutational spectrum among the local population for each type of disorder was described, including the first report on the true prevalence of three silent alpha thalassemia defects, -alpha(3.7)/(4.78%), -alpha(4.2)/(1.61%) and Hb Westmead (alpha(WS)alpha/) (1.57%) and of delta-thalassemia resulting from five novel and two rare mutations never before identified in Chinese individuals. Comparison of the frequencies of alpha-globin mutations among the ethnic groups showed that there was a statistically significant difference between the Han (15.71%) and Zhuang (20.12%), and between the Han (15.71%) and Yao (20.84%) ethnic groups. In addition, we have performed the first extensive study of haematological parameters of the Hb Westmead mutation using a group of Chinese subjects with compound heterozygosity for this variant and an alpha-thalassaemia deletion. The knowledge gained in this study will enable us to estimate the health burden in this high-risk population and to elucidate the various genetic alterations that underlie haemoglobinopathies.