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Tang, K.

Publications and source records attributed to Tang, K..

3 recordsLinked to original sources

De novo assemblies of high-quality reference transcriptomes identifies Rosaceae-common and Rosa-specific encoding genes

Roses are important plants for human beings with important economical and biological traits like continuous flowering, flower architecture, color and scent, that current model plants do not feature, thus are becoming ideal models for studying these traits. Due to high heterozygosity of rose genomes likely caused by frequent inter-species hybridization, a high-quality and well-annotated genome for Rosa plants is not available yet. Developing genetic and genomic tools with high quality has become necessary for further roses breeding and for disentangling the molecular genetic mechanisms underlying roses domestication. We here generated the high quality and comprehensive reference transcriptomes for Rosa chinensis Old Blush (OB) and R. wichuriana Basyes Thornless (BT), two roses contrasting at several important traits. These reference transcriptomes showed transcripts N50 above 2000bp. The two species shared about 23310 transcripts (N50 = 2364bp), among which about 8975 orthologs were conserved within genera of Rosa. Rosa plants shared about 5049 transcripts (Rosaceae-common) with these from Malus, Prunus, Rubus, and Fragaria. Finally, a pool of 417 transcripts unique to Rosa plants (Rosa-specific) was identified. These Rosaceae-common and Rosa-specific transcripts should facilitate the phylogenetic analysis of Rosaceae plants and investigation of Rosa-specific traits. The data reported here should provide the fundamental genomic tools and knowledge critical for understanding the biology and domestication of roses.

plant biology

Genome-wide Variants of Eurasian Facial Shape Differentiation and a prospective model of DNA based Face Prediction

It is a long standing question as to which genes define the characteristic facial features among different ethnic groups. In this study, we use Uyghurs, an ancient admixed population to query the genetic bases why Europeans and Han Chinese look different. Facial traits were analyzed based on high-dense 3D facial images; numerous biometric spaces were examined for divergent facial features between European and Han Chinese, ranging from inter-landmark distances to dense shape geometrics. Genome-wide association analyses were conducted on a discovery panel of Uyghurs. Six significant loci were identified four of which, rs1868752, rs118078182, rs60159418 at or near UBASH3B, COL23A1, PCDH7 and rs17868256 were replicated in independent cohorts of Uyghurs or Southern Han Chinese. A prospective model was also developed to predict 3D faces based on top GWAS signals, and tested in hypothetic forensic scenarios.

genetics

HOMINID: A framework for identifying associations between host genetic variation and microbiome composition

Recent studies have uncovered a strong effect of host genetic variation on the composition of host-associated microbiota. Here, we present HOMINID, a computational approach based on Lasso linear regression, that given host genetic variation and microbiome composition data, identifies host SNPs that are correlated with microbial taxa abundances. Using simulated data we show that HOMINID has accuracy in identifying associated SNPs, and performs better compared to existing methods. We also show that HOMINID can accurately identify the microbial taxa that are correlated with associated SNPs. Lastly, by using HOMINID on real data of human genetic variation and microbiome composition, we identified 13 human SNPs in which genetic variation is correlated with microbiome taxonomic composition across body sites. In conclusion, HOMINID is a powerful method to detect host genetic variants linked to microbiome composition, and can facilitate discovery of mechanisms controlling host-microbiome interactions.\n\nAvailability and implementationSoftware, code, tutorial, installation and setup details, and synthetic data are available in the project homepage: https://github.com/blekhmanlab/hominid.\n\nReal dataset used here is from Blekhman et al. (Blekhman et al. 2015); 16S rRNA gene sequence data and OTU tables are available on the HMP DACC website (www.hmpdacc.org), and host genetic data are deposited in dbGaP under project number phs000228.

genomics