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LU, Jian
Title:
Professor
Office Address: Wang Kezhen Building,Peking University, No.5 Yiheyuan Road, Haidian District,Beijing, P.R.China 100871
Lab Address: Wang Kezhen Building,Peking University, No.5 Yiheyuan Road, Haidian District,Beijing, P.R.China 100871
Lab Homepage: http://lujianlab.org/
Personal Homepage: http://evolution-pku.org/
Resume
Education
2002 - 2008 Ph.D. Evolutionary Biology, the University of Chicago
1999 - 2002 M.S. Genetics, Peking University
1995 -1999 B.S. Cell Biology and Genetics, Peking University
Professional Experience
2022 - current Changjiang Scholar Professor
2022 - current Professor,School of Life Sciences, Peking University
2020 - 2021 Tenured Associate Professor,School of Life Sciences, Peking University
2013 - 2021 Principal Investigator,School of Life Sciences, Peking University
2008 - 2013, Postdoc, Department of Molecular Biology and Genetics, Cornell University
Honors and Awards
2022年, 长江学者特聘教授
2021年, 全国科技系统抗击新冠肺炎疫情先进个人
2020年, 北京大学“抗击新冠肺炎疫情标兵”
2012年, 千人计划 “青年项目”
2006年, 国家优秀自费留学生奖学金(奖励金额:5000美元)

Editorial Activities
2018- Associate Editor, Science Bulletin

2020- Associate Editor, Molecular Biology and Evolution
Grant Review/Study Section Membership
Ad hoc grant reviewer for the National Natural Science Foundation of China (Major Program, Key Program, and Excellent Young Scholar Program), Ministry of Science and Technology of China (Budget evaluation), China Postdoctoral Science Foundation, and U.S.-Israel Binational Science Foundation


Ad hoc reviewer for the journals Molecular Biology and Evolution (>20 times), Nature Ecology & Evolution, Genome Research, PLOS Biology, PNAS, Nature Communications, Nature Protocols, Nucleic Acids Research, National Science Review, PLOS Genetics, Genome Biology and Evolution, Journal of Molecular Evolution, PLOS Computational Biology, Genetics, Molecular Genetics and Genomics, Gene, Communications Biology, Current Genomics, and Genomics, Proteomics & Bioinformatics
Meeting Organizers and Session Chairs
December 2020 Session Chair, GPB Frontier Symposium 2020, Beijing, China

August 2019 Session Chair, The 5th National Drosophila Conference of China, Dalian, China

August 2019 Organization Committee & Session Chair, The 14th International Bioinformatics Workshop (IBW), Beijing, China

April 2018 Session Chair, The 1st AsiaEvo Conference, Shenzhen, China

December 2017 Organizer, 2017 Beijing Area Fly Meeting, Beijing, China

June 2017 Session Chair, Beijing Normal University Symposium of Ecology and Evolutionary Biology, Beijing, China

April 2017 Organizer, Symposium of Ecology and Evolution at Peking-Taiwan University Day, Beijing, China

Editorial Activities
2018- Associate Editor, Science Bulletin

2020- Associate Editor, Molecular Biology and Evolution
Research Interests
Research Area
A central tenet in evolutionary biology is to decipher the genotype-phenotype relationships and the underlying evolutionary driving force. Our long-term goal seeks to elucidate how gene expression architecture evolves to cause phenotypic changes and environmental adaptation at the systems level. The advent of high-throughput sequencing-based functional genomics provides us with an unprecedented opportunity to address many fundamental issues related to gene expression regulation and evolution. Our research team at Peking University take an integrative genomics approach to dissect the molecular mechanisms and evolutionary principles of translational control, with a focus on the evolution and functions of the cis- and trans-acting elements and their interactions in translational regulation.
During the past five years, we have made a series of significant discoveries related to translational regulation, which is summarized as follows.


I) Adaptive evolution of uORFs and their function in translational regulation
uORFs are cis-acting elements in 5`UTRs of metazoan mRNAs that potentially inhibit translation initiation of downstream CDSs by sequestering ribosomes. To decipher the evolutionary principles of uORFs, we performed extensive mRNA-Seq and ribosome profiling to generate genome-wide maps of ribosome occupancy at the codon level during the life cycle of D. melanogaster (Zhang et al. 2018a). We demonstrate for the first time that the majority of the newly fixed uORFs in D. melanogaster, especially the translated ones, are driven by positive Darwinian selection. We also show that during Drosophila development, changes in the translation efficiency of uORFs, as well as the inclusion/exclusion of uORFs by alternative splicing or altering transcriptional initiation, are frequently exploited to influence the translation of CDSs inversely. Our results provide novel insight into the evolutionary principles of uORFs and their biological importance in translational regulation.

II) A-to-I RNA editing increases protein diversity in Drosophila
A-to-I RNA editing is an evolutionarily conserved mechanism by which ADAR recognizes double-stranded RNAs and convert adenosine into inosine. Since inosine is recognized as guanosine (G) by the cellular machinery, A-to-I editing is hypothesized to facilitate adaptive evolution by expanding transcriptomic and proteomic diversities (Gommans et al. 2009). To test this hypothesis, we systematically identified A-to-I RNA editing sites in the brains of three Drosophila species. We demonstrate for the first time that positive selection has caused excessive editing events that change protein sequences at the editome level (Duan et al. 2017), suggesting A-to-I RNA editing has important implications in evolution. We are currently testing whether A-to-I editing affects translation dynamics. Furthermore, we show that many of the adaptive nonsynonymous editing events are significantly linked in the same RNA molecules in Drosophila in which nonsynonymous editing are overall adaptive (Duan et al. 2018). This finding therefore highlights the necessity to consider the possible combinatory effect of editing on multiple sites when elucidating the functional consequences of RNA editing. Collectively, we are among the first to prove the hypothesis that A-to-I editing provides a driving force for adaptive evolution from different aspects. Our results suggest A-to-I RNA editing adds a layer of complexity to the proteome and provide valuable insights into the molecular mechanisms of adaptation.

III) Evolutionary principles of small RNAs and their function in translational regulation
miRNAs are small RNAs that suppress targets by degrading mRNAs or inhibiting translation. One of my longstanding interests is to decipher the evolutionary principles of miRNAs and their function. Previously, we found most newly emerged miRNAs are evolutionarily transient (Lu et al. 2008b) and many adaptive mutations are required to drive a new surviving miRNA to develop function (Lu et al. 2008a). Nevertheless, it remains unclear what factors affect the survival and function development for a new miRNA or target site. Recently, my group finds the genomic clustering helps new miRNAs survive and develop function in animals (Wang et al. 2016). We also show natural selection has driven miRNAs in the same cluster that have different origins to evolve convergently towards similar function. Moreover, we find the majority of evolutionarily conserved miRNAs in animals are caused by duplication, and functional diversification following miRNA duplications accelerates the recruitment of functional new targets (Luo et al. 2018a).

In line with the view that mammalian miRNAs inhibit their targets primarily by destabilizing mRNAs (Guo et al. 2010), we previously found that variation in miRNA target sites is associated with increased mRNA expression variation in human populations (Lu and Clark 2012). However, it is not well understood how miRNAs repress their targets at the genomic scale in Drosophila. To address this question, we recently performed extensive RNA-Seq and ribosome profiling experiments and find many miRNAs inhibit translation of the target genes in the major developmental stages of Drosophila (Zhang and Lu). Remarkably, we find extensive cross-talks between miRNAs and uORFs in suppressing translation of the targets, suggesting miRNAs and uORFs interact to regulate the translational programs in a fail-safe manner (Zhang and Lu). Meanwhile, we also found another class of small RNAs in Drosophila, tsRNAs (tRNA-derived small RNAs), preferentially suppress translation of key components of the general translational machinery by antisense pairing to their mRNAs, which further inhibits the global translational activities under cellular stress (Luo et al. 2018b). However, whether (and how) tsRNAs and miRNAs cross-talk to regulate cellular energy homeostasis and metabolic adaptation deserves further investigations.

IV) The biosynthetic cost of amino acids influences global mRNA translation and provides insights into cancer progression
Besides translational regulation at the RNA level, we further ask whether the global mRNA translation is affected by the biosynthetic costs of amino acids (AAs) which vary wildly. Consistent with previous observations that the biosynthetic costs of AAs constrain their usage in the protein sequences (Akashi and Gojobori 2002; Raiford et al. 2008), we found the mRNA expression levels are also inversely correlated with the average cost of AAs in the protein products in various human tissues, suggesting human gene expressions are optimized due to metabolic efficiency (Zhang et al. 2018b). We calculated the ECPAcell (Energy Cost Per Amino Acid) which incorporates the global mRNA expression levels to quantitatively characterize the use of 20 AAs during protein synthesis in human cells. To test whether changes in the usage of AAs in protein synthesis by altering global mRNA expression profiles affect the fitness of a cell, we compared the ECPAcell values in normal versus tumor tissues because 1) tumor cells demand more AAs for biomass synthesis, and 2) a tumor sample is a multi-step fast-evolving system where selective pressure on the tumor cells is pervasive. By analyzing gene expression data from The Cancer Genome Atlas, we find that cancer cells evolve to utilize amino acids more economically by optimizing the global mRNA expression profile in multiple cancer types. In ten cancer types, patients with lower ECPAcell showed significantly worse survival probability compared with those with higher ECPAcell. We further validate this pattern in experimental evolution of xenograft tumors. Our results suggest cancer cells that reprogram their genome-wide expression profiles to utilizing AAs more economically in protein synthesis gain advantage during proliferation, and that might be a common principle during cancer evolution.
Please see http://evolution-pku.org/ for details.
Representative Peer-Reviewed Publications
1. Peng MS#, *, Li JB#, Cai ZF#, Liu H#, Tang X#, Ying R, Zhang JN, Tao JJ, Yin TT, Zhang T, Hu JY, Wu RN, Zhou ZY, Zhang ZG, Yu L, Yao YG, Shi ZL, Lu XM, Lu J*, Zhang YP* (2021) The high diversity of SARS-CoV-2-related coronaviruses in pangolins alters potential ecological risks. Zoological Research. 42(6): 833–843. DOI: 10.24272/j.issn.2095-8137.2021.334 .

2. Sun Q, Shu C, Shi W, Luo Y, Fan G, Nie J, Bi Yu, Wang Q, Qi J, Lu J, Zhou Y, Shen Z, Meng Z, Zhang X, Yu Z, Gao S*, Wu L*, Ma J*, Hu S* (2021) VarEPS: an evaluation and prewarning system of known and virtual variations of SARS-CoV-2 genomes. Nucleic Acids Research. DOI: 10.1093/nar/gkab921 .

3. Wu Z, Jin Q, Wu G, Lu J, Li M, Guo D, Lan K, Feng L, Qian Z, Ren L, Tan W, Xu W, Yang W, Wang J*, Wang C (2021) SARS-CoV-2`s origin should be investigated worldwide for pandemic prevention. The Lancet. DOI: 10.1016/S0140-6736(21)02020-1 .

4. Wu CI*, Wen H, Lu J, Su X, Hughes AC, Zhai W, Chen C, Chen H, Li M, Song S, Qian Z, Wang Q, Chen B, Guo Z, Ruan Y, Lu X, Wei F, Jin L, Kang L, Xue Y, Zhao G, Zhang YP (2021) On the origin of SARS-CoV-2—The blind watchmaker argument. Science China Life Sciences. DOI: 10.1007/s11427-021-1972-1

5. Hu B#, Liu R#, Tang X#, Pan Y#, Wang M#, Tong Y#, Ye G#, Shen G#, Ying R#, Fu A, Li D, Zhao W, Peng J, Guo J, Men D, Yao X, Wang Y, Zhang H, Feng Z, Yu J, Chen L, Deng Z, Lu X, Zhang YP*, Li Y*, Liu B*, Yu L*, Li Y*, Lu J*, Liu T* (2021) The concordance between the evolutionary trend and the clinical manifestation of the two SARS-CoV-2 variants. National Science Review. nwab073. DOI: 10.1093/nsr/nwab073

6. Duan Y, Tang X, Lu J* (2021) Evolutionary driving forces of A-to-I editing in metazoans. WIREs RNA. e1666. DOI: 10.1002/wrna.1666

7. Feng Y#, Xu H#, Liu J#, Xie N, Gao L, He Y, Yao Y, Lv F, Zhang Y, Lu J, Zhang W, Li CY, Hu X*, Yang Z*, Xiao RP (2021) Functional and adaptive significance of promoter mutations that affect divergent myocardial expressions of TRIM72 in primates. Molecular Biology and Evolution. msab083. DOI: 10.1093/molbev/msab083

8. Zhang H, Wang Y, Wu X, Tang X, Wu C, Lu J* (2021) Determinants of genome-wide distribution and evolution of uORFs in eukaryotes. Nature Communications. 12: 1076

9. Tang X#, Ying R#, Yao X#, Li G, Wu C, Tang Y, Li Z, Kuang B, Wu F, Chi C, Du X, Qin Y, Gao S, Hu S, Ma J, Liu T, Pang X, Wang J, Zhao G, Tan W*, Zhang Y*, Lu X*, Lu J* (2021) Evolutionary analysis and lineage designation of SARS-CoV-2 genomes. Science Bulletin. DOI: 10.1016/j.scib.2021.02.012

10. Yu T, Huang X, Dou S, Tang X, Luo S, Theurkauf WE*, Lu J*, Weng Z* (2021) A benchmark and an algorithm for detecting germline transposon insertions and measuring de novo transposon insertion frequencies. Nucleic Acids Research. gkab010. DOI: 10.1093/nar/gkab010

11. Duan Y, Dou S, Porath HT, Huang J, Eisenberg E*, Lu J* (2021) A-to-I RNA editing in honeybees shows signals of adaptation and convergent evolution. iScience 24(1): 101983. DOI: 10.1016/j.isci.2020.101983

12. Ruan Y, Luo Z, Tang X, Li G, Wen H, He X, Lu X*, Lu J*, Wu CI* (2021) On the founder effect in COVID-19 outbreaks: how many infected travelers may have started them all?. National Science Review 8(1): nwaa246. DOI: 10.1093/nsr/nwaa246

13. Zhang H#, Wang Y#, Tang X, Dou S, Sun Y, Zhang Q, Lu J* (2021) Combinatorial regulation of gene expression by uORFs and microRNAs in Drosophila. Science Bulletin. 66(3): 225–228. DOI: 10.1016/j.scib.2020.10.012

14. Tang X#, Wu C#, Li X#, Song Y#, Yao X, Wu X, Duan Y, Zhang H, Wang Y, Qian Z, Cui J*, Lu J* (2020) On the origin and continuing evolution of SARS-CoV-2. National Science Review. 7(6): 1012–1023

15. Li T#, Tang X#, Wu C, Yao X, Wang Y, Lu X*, Lu J* (2020) The use of SARS-CoV-2-related coronaviruses from bats and pangolins to polarize mutations in SARS-Cov-2. SCIENCE CHINA Life Sciences. 63(10):1608-1611

16. Luo S#, Zhang H#, Duan Y#, Yao X, Clark AG*, Lu J* (2020) The Evolutionary Arms Race between Transposable Elements and piRNAs in Drosophila melanogaster. BMC Evolutionary Biology. DOI: 10.1186/s12862-020-1580-3

17. Zhang H#, Wang YR#, Lu J* (2019). Function and evolution of upstream ORFs in eukaryotes. Trends in Biochemical Sciences 44(9): 782-794. (Invited Review).

18. Wang YR#, Zhang H#, Lu J* (2019). Recent advances in ribosome profiling for deciphering translational regulation. Methods doi: 10.1016/j.ymeth.2019.05.011. (Invited Review, 被Faculty of 1000推荐).

19. Dou SQ#, Wang YR#, Lu J* (2019). Metazoan tsRNAs: biogenesis, evolution and regulatory functions. Non-Coding RNA 5(1): 18. (Invited Review).

20. Wu CC, Lu J* (2019). Diversification of transposable elements in arthropods and its impact on genome evolution. Genes 10(5).

21. Zhang H#, Wang YR#, Li J, Chen H, He XL, Zhang HW, Liang H*, Lu J* (2018). Biosynthetic energy cost for amino acids decreases in cancer evolution. Nature Communications 9(1):4124.

22. Zhang H#, Dou SQ#, He F, Luo JJ, Wei LP, and Lu J* (2018). Genome-wide maps of ribosomal occupancy provide insights into adaptive evolution and regulatory roles of uORFs during Drosophila development. PLOS Biology 16(7): e2003903.

23. Luo SQ#, He F#, Luo JJ#, Dou SQ#, Wang YR#, Guo AN, Lu J* (2018). Drosophila tsRNAs preferentially suppress general translation machinery via antisense pairing and participate in cellular starvation response. Nucleic Acids Research 46(10):5250-5268.

24. Luo JJ#, Wang YR#, Yuan J#, Zhao ZL, Lu J* (2018). MicroRNA duplication accelerates the recruitment of new targets during vertebrate evolution. RNA 24(6):787-802.

25. Duan YG#, Dou SQ#, Zhang H#, Wu CC, Wu MM, Lu J* (2018). Linkage of A-to-I RNA editing in metazoans and the impact on genome evolution. Molecular Biology and Evolution 35(1):132-148.

26. Duan YG#, Dou SQ#, Luo SQ#, Zhang H, Lu J* (2017). Adaptation of A-to-I RNA editing in Drosophila. PLOS Genetics 13(3):e1006648.

27. Luo SQ, Lu J* (2017). Silencing of transposable elements by piRNAs in Drosophila: an evolutionary perspective. Genomics, Proteomics & Bioinformatics 15(3):164-176.

28. Wang YR, Luo JJ, Zhang H, and Lu J* (2016). MicroRNAs in the same clusters evolve to coordinately regulate functionally related genes. Molecular Biology and Evolution 33(9):2232-47; author reply in 10.1093/molbev/msz121.

29. Yin S, Fan Y, Zhang H, Zhao Z, Hao Y, Li J, Sun C, Yang J, Yang Z, Yang X, Lu J, Xi JJ*. (2016). Differential TGFβ pathway targeting by miR-122 in humans and mice affects liver cancer metastasis. Nature Communications 7:11012.

30. Zhang XY, Zhu Y, Liu XD, Hong XY, Xu Y, Zhu P, Shen Y, Ji YS, Wen X, Zhang C, Zhao Q, Wang YC, Lu J, Guo HW*. (2015). Suppression of endogenous gene silencing by degradation of normal cytoplasmic RNA in Arabidopsis. Science 348(6230): 120-123.

31. Yu FL#, Lu J#, Liu XM#, Gazave E, Chang D, Raj S, Hunter-Zinck H, Blekhman R, Arbiza L, Hout C, Morrison A, Johnson AD, Bis J, Cupples LA, Psaty BM, Muzny D, Yu J, Gibbs RA, Keinan A, Clark G, Boerwinkle E* (2015). Population genomics analyses of 962 whole genomes of humans reveal natural selection in non-coding regions. PLOS One 10(3): e0121644.

32. Ye KX, Lu J, Ma F, Keinan A, Gu ZL* (2014). Extensive Pathogenicity of Mitochondrial Heteroplasmy in Healthy Human Individuals. Proceedings of the National Academy of Sciences of the United States of America 111(29): 10654-10659.

33. Ye KX*, Lu J, Raj SM, Gu ZL* (2013). Human expression QTLs are enriched in signals of environmental adaptation. Genome Biology and Evolution 5(9):1689-701.

34. Lu J* & Clark AG* (2012). Impact of microRNA regulation on variation in human gene expression. Genome Research 22(7): 1243–1254.

35. Zhou RC#, Ling SP#, Zhao WM#, Osada N, Chen SF, Zhang M, He ZW, Bao H, Zhong CR, Zhang B, Lu XM, Turissini D, Duke NC, Lu J*, Shi SH*, Wu CI* (2011). Population genetics in non-model organisms: II. Natural selection in marginal habitats revealed by deep sequencing on dual platforms. Molecular Biology and Evolution 28(10):2833-42.

36. Tang T#, Kumar S#, Shen Y, Lu J, Wu ML, Shi S, Li WH, Wu CI* (2010). Adverse interactions between micro-RNAs and target genes from different species. Proceedings of the National Academy of Sciences of the United States of America 107: 12935-12940.

37. Lu J, Clark AG* (2010). Population dynamics of PIWI-interacting RNAs (piRNAs) and their targets in Drosophila. Genome Research 20: 212-227.

38. Lu J, Shen Y,Wu QF, Kumar S, He B, Carthew RW, Wang SM*, Wu CI* (2008). The birth and death of microRNA genes in Drosophila. Nature Genetics 40: 351-355; author reply in 42: 9-10.

39. Lu J, Fu Y, Kumar S, Shen Y, Zeng K, Xu A, Carthew RW, Wu CI* (2008). Adaptive evolution of newly emerged micro-RNA genes in Drosophila. Molecular Biology and Evolution 25: 929-938.

40. Wang HY, Fu Y, McPeek MS, Lu X, Nuzhdin S, Xu A, Lu J, Wu ML, Wu CI* (2008). Complex genetic interactions underlying expression differences between Drosophila races: analysis of chromosome substitutions. Proceedings of the National Academy of Sciences of the United States of America 105: 6362-6367.

41. Wu QF, Kim YC, Lu J, Xuan ZY, Chen J, Zheng YL, Zhou T, Zhang MQ, Wu CI, Wang SM* (2008). Poly A- transcripts expressed in HeLa cells. PLOS ONE 3(7): e2803.

42. Clark AG, Eisen MB, Smith DR, Bergman CM, Oliver B, Markow TA et al (2007). Evolution of genes and genomes on the Drosophila phylogeny. Nature 450: 203-218 (Lu J is a coauthor of this paper).

43. Shapiro JA, Huang W, Zhang C, Hubisz MJ, Lu J, Turissini DA, Fang S, Wang HY, Hudson RR, Nielsen R, Chen Z, Wu CI* (2007). Adaptive genic evolution in the Drosophila genomes. Proceedings of the National Academy of Sciences of the United States of America 104: 2271-2276.

44. Lu J#, Tang T#, Tang H, Huang JZ, Shi SH*, Wu CI* (2006). The accumulation of deleterious mutations in rice genomes: a hypothesis on the cost of domestication. Trends in Genetics 22: 126-131.

45. Tang T#, Lu J#, Huang J, He J, McCouch SR, Purugganan MD, Shi SH*, Wu CI* (2006). Genomic variation in rice - Genesis of highly polymorphic linkage blocks during domestication. PLOS Genetics 2(11):e199.

46. Lu J, Wu CI* (2005). Weak selection revealed by the whole-genome comparison of the X chromosome and autosomes of human and chimpanzee. Proceedings of the National Academy of Sciences of the United States of America 102: 4063-4067.

47. Tang H, Wyckoff GJ, Lu J, Wu CI* (2004) A universal evolutionary index for amino acid changes. Molecular Biology and Evolution 21: 1548-1556.

48. Lu J, Li WH, Wu CI* (2003) Comment on Chromosomal speciation and molecular divergence-accelerated evolution in rearranged chromosomes. Science 302: 988.

49. Lu J, Lü J, Chen HX, Zhang WX, Dai ZH* (2002) Molecular phylogeny of Drosophila auraria species complex (in Chinese). Acta Genetica Sinica 29: 39-49.

50. Zhao Z, Lu J, Dai ZH* (2001). Genetic differentiation within Drosophila auraria species complex revealed by Random Amplified Polymorphic DNA (RAPD) (in Chinese). Acta Zoologica Sinica 47: 625-631.

Teaching
Genetics
Genetics Track
Molecular Biology
Laboratory Introduction