About

Michael Tang is an Assistant Clinical Professor of Medicine at UC San Diego. His research focuses on HIV/AIDS, including the assessment of models for CD4 depletion, the impact of HIV on COVID-19 outcomes, and the effects of co-administration of antiretroviral drugs such as Tenofovir alafenamide and rifabutin. His work involves understanding the epidemiology, treatment, and public health aspects of HIV, with contributions to the evaluation of HIV-related interventions and the immune response in affected populations. Dr. Tang has authored multiple publications in reputable journals, contributing to the fields of communicable diseases, public health, and infectious diseases.

Research topics

• Biology
• Genetics
• Evolutionary biology
• Botany
• Computational biology

Selected publications

• The circadian clock gates lateral root development

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-01-15

  article

  Abstract Lateral root (LR) formation remodels root architecture, yet how temporal information integrates with hormonal cues remains unclear. We show that the circadian clock component EARLY FLOWERING 3 (ELF3) acts as a temporal gatekeeper of root organogenesis in Arabidopsis thaliana . Time-resolved transcriptomics, imaging, and genetics reveal that ELF3 restrains hormone-induced pericycle proliferation by maintaining rhythmic expression of key regulators under callus-inducing conditions. Loss of ELF3 disrupts rhythmic gene expression, enhancing callus growth and accelerating LR development. ELF3 functions through its target LNK1 to regulate the MADS-box genes AGL14 and AGL20 . Notably, callus-inducing signals partially restore rhythmicity in elf3 mutants, revealing feedback from hormonal signaling to the circadian system. These findings identify ELF3 as an integrator of circadian and hormonal inputs that temporally constrains root developmental plasticity.

  PublisherDOI

• A sorghum pangenome reference improves global crop trait discovery

  Nature · 2026-03-11 · 6 citations

  articleOpen access

  Although the green revolution adapted a handful of crops to homogeneous and high-input industrialized agriculture, much of the global population still relies on the local production of variable crop cultivars by low-input smallholder farms. This diversity of unhomogenized crops1, like that of the grain and bioenergy crop sorghum2–5, offers raw materials for genetic gain and cultivar improvement. However, breeding efforts can be constrained by highly specialized traits and breeding targets6. Here, to bridge this diversity, we constructed a 33-member pangenome reference and a diversity panel across 1,984 cultivars and landraces. We leveraged these resources to explore the complex interplay among historical contingency, ongoing adaptation and previously uncharacterized structural diversity. Specifically, our analyses conclusively demonstrated multiple nested and deeply diverged structural variants in the domestication gene SHATTERING1, which distinguish the previously established multicentric origin of sorghum. We then applied landscape genomics to reveal how gene flow and secondary contact created the complex genetic mosaic in contemporary breeding networks. As proof of concept for pangenome-accelerated trait discovery, we connected biosynthetic gene cluster structural variation to phenotypic leaf concentration of the cyanogenic glucoside dhurrin. Combined, these approaches will accelerate breeding and trait discovery and provide a framework for similar applications in other crops. A pangenome reference for the phenotypically diverse crop sorghum aims to help accelerate future efforts to breed crops that are better adapted to changing environments.

  PublisherDOI

• Fluorescence <i>in situ</i> hybridization signals in a duckweek nucleus rendered by 3D structured illumination microscopy

  Open MIND · 2026-01-01

  other

  Taking advantage of the uniquely low rDNA copy number in the aquatic duckweed plant Spirodela polyrhiza, we resolved the complete 5S rDNA architecture at a nucleotide level.

  DOI

• Expanded aus-NAM data

  Figshare · 2026-04-22

  datasetOpen access

  This dataset contains genotyping-by-sequencing (GBS)–derived genotype data and whole-genome sequence (WGS)–derived parental variants for an aus-derived nested association mapping (aus-NAM) population in rice (<i>Oryza sativa</i>). The population comprises 14 biparental families sharing the elite japonica cultivar Taichung 65 (T65) as a common parent crossed with diverse aus donors.GBS data are provided as filtered HapMap files generated using the TASSEL-GBS pipeline and standard quality filters (minor allele frequency, missing data, and heterozygosity). In addition, high-density parental SNPs were projected onto recombinant inbred lines using GBS markers as anchors, enabling analyses across multiple marker densities.These datasets were used for genomic prediction and genome-wide association studies to evaluate the effects of marker density and training population size, supporting reproducible research in quantitative genetics and breeding.<b>Files included:</b>14 family-level HapMap genotype files (GBS-derived):<br>filt_informsites_maf_maxmiss_thin64_WNAM02–WNAM40.hmp.txtParental variant dataset (WGS-derived):<br>Parents_WRC_pcp_mini_thin64_nohets.hmp.txtSupplemental Data Tables 1 and 2

  PublisherDOI

• SorghumBase: a knowledgebase for sorghum genomics, phenomics, and stakeholder engagement

  Genetics · 2026-01-19 · 1 citations

  articleOpen access

  Centralizing valuable community data and resources into a user-friendly interface and accessible repository has become essential for agricultural science; embracing Findable Accessible, Interoperable, and Reusable (FAIR) principles is now standard for effective databases. SorghumBase (https://www.sorghumbase.org) is a knowledgebase designed for the sorghum research community. The SorghumBase team curates genomic, transcriptomic, variation, and phenotypic information and aggregates community events, providing rich visualizations and bulk data access. The modular framework of the database is built with open-access software to yield a robust, modifiable, and sustainable data infrastructure. Release 9 of SorghumBase includes: (i) 88 sorghum reference genomes and an updated pan-gene index, (ii) over 100 million variants have been mapped onto the 2 genomes, BTx623 and Tx2783, (iii) assignment of 41 million Reference Cluster SNP identifiers (rsIDs) from BTx623 across the pan-genome, (iv) updated gene search homology, gene expression, and germplasm visualizations and features, (v) added and standardized 234 phenotypic data from 40 community-generated GWAS studies and 148 traits from the Sorghum QTL Atlas (Oz Sorghum), (vi) improved news, funding, and a research content management system for community access and interaction, (vii) outreach materials including training documents and videos, and (viii) community engagement initiatives through training and working groups. SorghumBase serves as a hub for sorghum data and stakeholder engagement while promoting community standards to drive research and multi-omics breeding approaches.

  PublisherOA PDFDOI

• Plant genome assembly and annotation

  Current Opinion in Plant Biology · 2026-02-11

  articleOpen access1st authorCorresponding

  Plant genome biology is entering a new era defined by fully phased, chromosome-scale, telomere-to-telomere assemblies, enabled by the convergence of long-read sequencing technologies, improved assembly algorithms, and powerful scaffolding strategies. Gapless, haplotype-resolved genomes are now feasible even for polyploid species, shifting the bottleneck from assembly to annotation and interpretation. Genome annotation remains one of the greatest opportunities and challenges in plant biology. While ab initio methods still form the backbone of structural prediction, evidence-based frameworks that integrate RNA sequencing, chromatin accessibility, methylation, and 3D genome data are rapidly advancing the field. At the same time, artificial intelligence-driven protein-coding gene predictors are redefining ab initio gene finding, and large-scale orthology networks continue to improve functional inference. The next frontier is extending annotation beyond protein-coding genes into regulatory and structural dimensions, a goal increasingly enabled by single-cell and multi-omic technologies. Looking forward, the integration of AI, multi-omics, and large language models promises to standardize and automate workflows from DNA isolation to functional annotation. These innovations will accelerate fundamental plant biology discovery, enable next-generation biodiversity conservation, and transform strategies for crop improvement and biotechnology.

  PublisherDOI

• Expanded aus-NAM data

  Figshare · 2026-04-22

  datasetOpen access

  This dataset contains genotyping-by-sequencing (GBS)–derived genotype data and whole-genome sequence (WGS)–derived parental variants for an aus-derived nested association mapping (aus-NAM) population in rice (<i>Oryza sativa</i>). The population comprises 14 biparental families sharing the elite japonica cultivar Taichung 65 (T65) as a common parent crossed with diverse aus donors.GBS data are provided as filtered HapMap files generated using the TASSEL-GBS pipeline and standard quality filters (minor allele frequency, missing data, and heterozygosity). In addition, high-density parental SNPs were projected onto recombinant inbred lines using GBS markers as anchors, enabling analyses across multiple marker densities.These datasets were used for genomic prediction and genome-wide association studies to evaluate the effects of marker density and training population size, supporting reproducible research in quantitative genetics and breeding.<b>Files included:</b>14 family-level HapMap genotype files (GBS-derived):<br>filt_informsites_maf_maxmiss_thin64_WNAM02–WNAM40.hmp.txtParental variant dataset (WGS-derived):<br>Parents_WRC_pcp_mini_thin64_nohets.hmp.txtSupplemental Data Tables 1 and 2

  PublisherDOI

• Genome sequence assembly of the 5S rDNA loci informs haplotype specificity and evolution in the greater duckweed Spirodela polyrhiza

  Communications Biology · 2026-01-26 · 1 citations

  articleOpen access

  Despite the rapid expansion of information on eukaryotic genomes, data on ribosomal DNA (rDNA) loci encoding ribosomal RNAs, crucial for the biogenesis of ribosomes, are absent in almost all cases due to difficulties in assembling the long regions of tandemly repeated DNA units. Taking advantage of the uniquely low rDNA copy number in the aquatic plant Spirodela polyrhiza, we resolved the species' complete 5S rDNA architecture at a nucleotide level. A combination of in situ hybridization, extra-long DNA reads, and conventional DNA sequencing allowed the assembly of near-complete loci sequences of 40,878 bp, specific for one haplotype of chromosome ChrSp6, and of 110,911 bp specific for a haplotype of ChrSp13. The completely resolved 5S rDNA locus of ChrSp6 contains 40 copies of tandemly repeated gene units with an intergenic spacer (NTS) of 400 bp for one haplotype, and more than 60 highly homogenized gene copies for the second haplotype. The ChrSp13 locus contains 5S rDNA clusters with NTSs of 1,056 or 1,069 bp arranged in two sub-clusters. The G/C-rich 5S rDNA arrays in both loci are embedded in A/T-enriched chromosome regions. This work advances our understanding of the basic principles of rDNA organization and evolution of rRNA genes in plants by revealing the molecular architecture and evolutionary dynamics of 5S rDNA loci.

  PublisherOA PDFDOI

• Efficient genomic prediction at reduced training size and moderate marker density in an expanded aus-NAM population of rice

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-05-01

  article

  Abstract Genomic selection (GS) can accelerate genetic gain in crops, but its effectiveness depends on training population design and marker density. Nested association mapping (NAM) populations provide a structured framework that captures broad allelic diversity within a controlled genetic background. Here, we evaluated genomic prediction (GP) and genome-wide association study (GWAS) performance in an expanded aus-NAM population of rice comprising 1,818 recombinant inbred lines across 14 families and 11 agronomic traits, using genotyping-by-sequencing (GBS) markers and projected whole-genome sequence variants. Prediction accuracy plateaued at moderate marker densities (∼20k SNPs) and with training populations of ∼500 lines (∼40–60% of the available pool), with trait heritability emerging as the strongest determinant of predictive performance rather than model choice or marker density. In contrast, GWAS resolution continued to improve with increasing marker density, enabling detection of additional loci, including a chromosome 12 locus associated with heading date, while consistently recovering well-characterized genes such as EARLY HEADING DATE 1 (Ehd1) and SEMIDWARF 1 (SD1) . These contrasting patterns indicate that GP reaches near-optimal performance once genome-wide variation is adequately represented, whereas GWAS benefits from higher marker density through improved locus resolution. The present study establishes a benchmark for implementing breeding programs involving japonica/indica crosses using GP in a single environment.

  PublisherDOI

• Transcriptomic stress responses in <i>Vaccinium</i> spp. F1 hybrids: Implications for temperature‐resilient cranberry breeding using a crop wild relative

  Plants People Planet · 2026-02-03

  articleOpen access

  Societal Impact Statement Climate extremes threaten the sustainability of cranberry production, a culturally and economically important North American crop. This study demonstrates that wild cranberries ( Vaccinium oxycoccos ) harbor genetic variation that may enhance cold stress resilience when introduced into cultivated cranberry through hybridization. By identifying gene expression patterns associated with temperature tolerance, this research supports the development of climate‐resilient cranberry varieties and highlights the importance of conserving crop wild relatives. These insights advance sustainable agriculture and food security by informing breeding strategies that can help protect berry production in the face of increasing environmental stress. Summary Cranberry ( Vaccinium macrocarpon ) is an important North American fruit crop with vulnerability to temperature extremes and a relatively recent domestication history. Hybridization with a cold‐adapted crop wild relative (CWR), Vaccinium oxycoccos , offers a strategy for improving temperature stress tolerance. We conducted RNA sequencing (RNA‐seq) on V. macrocarpon and F1 hybrids between V. macrocarpon and V. oxycoccos subjected to acute heat and cold stress, capturing early transcriptional responses up to 30 min (heat) and 95 min (cold) after treatment onset. We then evaluated differences in responses across genotypes and stress conditions. Differential expression analysis and functional profiling revealed cold‐induced differences in pathways related to photosynthesis, ribosomes, defense, and hormone signaling. No subgenome‐specific functional specialization was observed. Two F1 hybrids exhibited suggestive cold resilience, with expression changes elevated at 60 min but declining by 95 min. Hybrids also displayed substantial regulatory variation under stress and transgressive downregulation of photosynthesis genes under ambient conditions. These findings suggest that V. oxycoccos introgression could be utilized in breeding cold‐tolerant cranberry cultivars. Variation observed between F1 hybrids reflects the diversity introduced through CWR germplasm and provides opportunities for selection. Conservation of V. oxycoccos and other CWRs remains critical for future crop improvement.

  PublisherDOI

Recent grants

• NIH Grant F32GM068381

  NIH · $131k · 2006

Frequent coauthors

• Joanne Chory

  Salk Institute for Biological Studies

  62 shared

• Jeremiah J. Minich

  54 shared

• Todd C. Mockler

  Donald Danforth Plant Science Center

  54 shared

• Eric E. Allen

  Scripps Institution of Oceanography

  52 shared

• Rob Knight

  University of California, San Diego

  44 shared

• Emily Kunselman

  Scripps Institution of Oceanography

  40 shared

• Joseph Vechinski

  Hubbs-Sea World Research Institute

  40 shared

• Benjamin W. Frable

  40 shared

Labs

• Michael Tang | UCSD ProfilesPI

Education

• M.D.

  University of California, San Diego

• B.S.

  University of California, San Diego