Jia Li

Jia Li — PhD student
Joined the group in 2020

My study interest is to evaluate the impact of environmental changes on the evolutionary history of organisms. The desert locust (Schistocerca gregari) is one of the most notorious migratory pests in the world, which would be an ideal model. Since the second half of last year, a transnational locust catastrophe of exceptional severity spreads across Africa and then moves towards Asia. The locust swarm has eaten the amount of food that can feed millions of people. Depending on the population density, the locusts can reflect two alternative phases: the long-living solitarious phase or the swarming gregarious phase. The gregarious phase can appear after hours of gathering and is soon consolidated to keep locust swarms together. During the process of phase change, many biological and phenotypic traits will be changed, including the body color, morphology, behavior, immune responsiveness. We sequenced the first genome of the desert locust, comprising 8.8 Gbp. We still lack the knowledge about which mechanisms affect the locust swarming behavior, a social experience, and the effective measures to disband locust swarms by disrupting the consolidated swarming behavior. Thus, I try to use the desert locust genome, transcriptomic and epigenetic data of the two transformation phases to generate a broad comparative genomics framework to study the biological and phenotypic changes during the transformation.

Ghent Unversity
Jan.2020 to present: PhD student, Bioinformatics & Evolutionary Genomics, Department of Plant Systems Biology, VIB, Gent, Belgium.
BGI Academy of Marine Sciences
Jul.2016 to Dec.2019: Bioinformatician. Charge for animals’ bioinformatics analysis.
Feb.2014 to Jun.2016: Intern. Charge for aquatic animals’ bioinformatics analysis.
University of Chinese Academy of Sciences
Sep.2013 to Jul.2016: Master of Engineering in Bioengineering, BGI Education Center
South China Agricultural University
Sep.2008 to Jul.2012: Bachelor of Science in Animal Biotechnology, College of Animal Sciences


  1. Li, J., Van de Peer, Y., & Li, Z. (2023). Inference of ancient polyploidy using transcriptome data. In Y. Van de Peer (Ed.), Polyploidy : methods and protocols (Vol. 2545, pp. 47–76). https://doi.org/10.1007/978-1-0716-2561-3_3
    Polyploidizations, or whole-genome duplications (WGDs), in plants have increased biological complexity, facilitated evolutionary innovation, and likely enabled adaptation under harsh conditions. Besides genomic data, transcriptome data have been widely employed to detect WGDs, due to their efficient accessibility to the gene space of a species. Age distributions based on synonymous substitutions (so-called KS age distributions) for paralogs assembled from transcriptome data have identified numerous WGDs in plants, paving the way for further studies on the importance of WGDs for the evolution of seed and flowering plants. However, it is still unclear how transcriptome-based age distributions compare to those based on genomic data. In this chapter, we implemented three different de novo transcriptome assembly pipelines with two popular assemblers, i.e., Trinity and SOAPdenovo-Trans. We selected six plant species with published genomes and transcriptomes to evaluate how assembled transcripts from different pipelines perform when using KS distributions to detect previously documented WGDs in the six species. Further, using genes predicted in each genome as references, we evaluated the effects of missing genes, gene family clustering, and de novo assembled transcripts on the transcriptome-based KS distributions. Our results show that, although the transcriptome-based KS distributions differ from the genome-based ones with respect to their shapes and scales, they are still reasonably reliable for unveiling WGDs, except in species where most duplicates originated from a recent WGD. We also discuss how to overcome some possible pitfalls when using transcriptome data to identify WGDs.
  2. Verlinden, H., Sterck, L., Li, J., Li, Z., Yssel, A., Gansemans, Y., … Vanden Broeck, J. (2020). First draft genome assembly of the desert locust, Schistocerca gregaria. F1000RESEARCH, 9. https://doi.org/10.12688/f1000research.25148.1
    Background: At the time of publication, the most devastating desert locust crisis in decades is affecting East Africa, the Arabian Peninsula and South-West Asia. The situation is extremely alarming in East Africa, where Kenya, Ethiopia and Somalia face an unprecedented threat to food security and livelihoods. Most of the time, however, locusts do not occur in swarms, but live as relatively harmless solitary insects. The phenotypically distinct solitarious and gregarious locust phases differ markedly in many aspects of behaviour, physiology and morphology, making them an excellent model to study how environmental factors shape behaviour and development. A better understanding of the extreme phenotypic plasticity in desert locusts will offer new, more environmentally sustainable ways of fighting devastating swarms. Methods: High molecular weight DNA derived from two adult males was used for Mate Pair and Paired End Illumina sequencing and PacBio sequencing. A reliable reference genome of Schistocerca gregaria was assembled using the ABySS pipeline, scaffolding was improved using LINKS. Results: In total, 1,316 Gb Illumina reads and 112 Gb PacBio reads were produced and assembled. The resulting draft genome consists of 8,817,834,205 bp organised in 955,015 scaffolds with an N50 of 157,705 bp, making the desert locust genome the largest insect genome sequenced and assembled to date. In total, 18,815 protein-encoding genes are predicted in the desert locust genome, of which 13,646 (72.53%) obtained at least one functional assignment based on similarity to known proteins. Conclusions: The desert locust genome data will contribute greatly to studies of phenotypic plasticity, physiology, neurobiology, molecular ecology, evolutionary genetics and comparative genomics, and will promote the desert locust’s use as a model system. The data will also facilitate the development of novel, more sustainable strategies for preventing or combating swarms of these infamous insects.

Other publications

  1. Li, J., Bian, C., Yi, Y. et al. 2021. Temporal dynamics of teleost populations during the Pleistocene: a report from publicly available genome data. BMC Genomics 22, 490.

  2. Peng, C., Huang, Y., Bian, C., Li, J., Liu, J., Zhang, K., ... & Shi, Q, 2021. The first Conus genome assembly reveals a primary genetic central dogma of conopeptides in C. betulinus. Cell discovery, 7(1), pp.1-14.

  3. Sun, C., Li, J., Dong, J., Niu, Y., Hu, J., Lian, J., Li, W., Li, J., Tian, Y., Shi, Q. and Ye, X., 2020. Chromosome‐level genome assembly for the largemouth bass Micropterus salmoides provides insights into adaptation to fresh and brackish water. Molecular Ecology Resources, (00): 1–15.

  4. Xu, G., Bian, C., Nie, Z., Li, J., Wang, Y., Xu, D., ... & Xu, P., 2020. Genome and population sequencing of a chromosome-level genome assembly of the Chinese tapertail anchovy (Coilia nasus) provides novel insights into migratory adaptation. GigaScience, 9(1), p.giz157.

  5. Bian, C., Li, J., ... & Shi, Q., 2019. Whole genome sequencing of the blue tilapia (Oreochromis aureus) provides a valuable genetic resource for biomedical research on tilapias. Marine drugs, 17(7), p.386.

  6. Zhang, S., Li, J., Qin, Q., Liu, W., Bian, ... & Shi, Q., 2018. Whole-genome sequencing of Chinese yellow catfish provides a valuable genetic resource for high-throughput identification of toxin genes. Toxins, 10(12), p.488.

  7. Lin, Q., Qiu, Y., Gu, R., Xu, M., Li, J., Bian, C., ... & Shi, Q., 2017. Draft genome of the lined seahorse, Hippocampus erectus. GigaScience, 6(6), p.gix030.

  8. Liu, K., Xu, D., Li, J., Bian, C., ... & Xu, P., 2017. Whole genome sequencing of Chinese clearhead icefish, Protosalanx hyalocranius. GigaScience, 6(4), p.giw012.

  9. Li, J., Bian, C., Hu, Y., Mu, X., Shen, X., Ravi, V., Kuznetsova, ... & Shi, Q., 2016. A chromosome-level genome assembly of the Asian arowana, Scleropages formosus. Scientific data, 3(1), pp.1-8.

  10. Li, J., You, X., Bian, C., Yu, H., Coon, S.L. and Shi, Q., 2016. Molecular evolution of aralkylamine N-acetyltransferase in fish: A genomic survey. International journal of molecular sciences, 17(1), p.51.

  11. Ao, J., Li, J., You, X., Mu, Y., ... & Chen, X., 2015. Construction of the high-density genetic linkage map and chromosome map of large yellow croaker (Larimichthys crocea). International journal of molecular sciences, 16(11), pp.26237-26248.