Our kind is facing many pressing health related issues, including cancer, high blood pressure, diabetes, addiction, aging, depression, psychiatric disorders, like schizophrenia and learning problems, etc. Why are we focusing on reproduction? Individual fates are mostly determined at the moment of fertilization, determining whether we are male or female, have certain genetic diseases, and have a higher risk of contracting such diseases. Many of these diseases are inherited; however, genome-wide studies have mostly failed to explain the genetic cause. Scientists termed this, "missing heritability" of “complex" diseases. We do not know during reproduction what is by nature, what is by nurture, how it is selected, and what carries the information (DNA, RNA, histone modification, or metabolite), can we change it, and if yes, how? We believe that reproduction is the root of our children’s health and essential for the future of our species. By studying the basic principles regulating reproduction, we believe our findings will improve human and animal health in a broader scope than focusing on a single disease.

2. Why do we study RNA regulation?

It was the dogma that stated RNA’s main function is to facilitate the information stored within DNA into proteins. In reality, RNA functions much further beyond that. The discovery of RNA interference, miRNA, piRNA, and Crisper/Cas9 reminds us of RNA’s ancient origin. Based on the “RNA world hypothesis”, RNA evolved with sophisticated regulations and functions, preceding the origin of life 3.5 billion years ago.

The effects of an animal’s environment during adolescence, such as traumatic stress and a high fat diet, can be passed down to the next generation through small non-coding RNAs in sperm. The mysterious piRNAs are likely to act beyond regulating gene expression during spermatogenesis. We believe that the current known RNA-regulations in germ lines just represent the tip of the iceberg.

3. What are the steps of graduate school training?

Inspired by Professor Russell Ackoff, I laid out a road map for trainees into three levels beginning with newbie to well-trained.

Level I: Technical proficient, data level

Generate and process data in publication quality. The key to this level is to pay attention to details, and to research every step and reagent of the protocol. At this level, students are able to optimize, troubleshoot, and adjust the protocol to different amounts of input, different antibody, etc.

Trainees become useful to the lab once they reach level 1. Any effort before that is a waste of reagent. Most good graduate students reach level 1 during their undergraduate studies. If not, efforts must be made to reach that level at least before their PhD qualifying exam.

Level 2: Problem solving, information level

Use experiments to address a scientific question. The key to reach this level is the understanding of how to design experiments, including setting up controls and replicates so that a conclusive answer can be reached.

Level 2 trainees are poised to move into the next round and experience the joy of being a scientist. Even if they do not want to continue training, level 2 trainees are able to use their acquired skills to find a job.

Level 3: Research driven, knowledge level

Drive and initiate a project. The key to reach this level is to understand the big picture of why a question is important, apply deductive thinking, and master the standards of the field.

Level 3 students are qualified to graduate and to stay in science. Their ability to solve a complicated question makes them valuable employees in and outside of academia. If they want to stay in academia, please refer to the question "why postdoc".

4. Why did I develop this road map?

This road map was solely developed for training purposes. As a mentor, I need to understand the level of my students to adjust training plans. For example, in my lab, reaching level 1 requires certification. Growing to level 2 requires coaching from a mentor and practice at the bench or computer. Upgrading to level 3 requires thinking, reading, and discussing with a mentor. At the transition from level 2 to level 3, some people, especially people with family, are able to work smartly at regular hours and remain productive because thinking about their projects can happen anywhere.

5. How can trainees benefit from this road map?

For trainees, this road map should also be used to help your training. Here I listed three examples of using the road map wisely, and two forbidden taboos while using the road map.

(1) Self-evaluate where you are on the path.

(2) Judge the quality of a scientific publication. A paper may be composed of contents with different quality. For example, its morphological characterization may be at level 3, but its bioinformatic analysis is at level 1. You can learn to judge and absorb the good parts.

(3) Develope trust with your PI. Now that you understand what it takes to be a PI, his or her advice should be more valuable to follow if it conflicts with advice from your peers.

(4) Do not use this road map to evaluate others, especially your peers, which is just a waste of time and has the danger of feeding your ego.

(5) Even if I list the standards here, you are not able to evaluate people that are at a higher level than you. When you are at level 2, you may be able to tell whether people are at level 1, but cannot tell whether people are at level 3. So do not do that to your PI.

6. Could you provide an example on how you evaluate your students?

If a trainee shows me an ugly western blotting picture with a high background and little signals, the trainee has not yet reached level 1. If the western blotting picture is in good quality, but fails to include proper controls, the trainee has not yet reached level 2. If the trainee showed me a series of experiments without any logic connecting them, failed to reach any conclusion in the end, or their results did not support the claimed conclusion, then the trainee has not reached level 3.

7. Is there a higher level than level 3?

Yes. If you have reached level 3, just to keep your ego under control, there are 2 more levels.

Level 4: Dot connecting, understanding level

Initiate a field or at least an area in the field, comprehend by analogy, and always stay at the cutting edge of science. The key to reach this level is to have a broad knowledge and inductive thinking.

Level 5: Philosopher, wisdom level

Fundamentally shake the old frames of thought and guide people to perceive the universe and their life towards the truth. People at this level are simple, open-minded, and enlightened.

At level 3, you can stay and succeed in your field. However, a scientific field has its lifespan. Reaching level 4 allows you to survive beyond your field, and at level 5 you become immortal. Reaching level 4 requires talent and a nurturing environment. Level 5 scientists are very rare.

8. Why postdoc?

Ideally, PhD students at level 3 are qualified to start their own lab. In reality, the candidates outnumber the independent positions, and you are probably not the only one to reach level 3 in your field. Therefore, you need to show your competitiveness to survive in science. Postdoc training prepares you for that. You should take this opportunity to demonstrate that you can publish efficiently, that you are equipped with a unique angle that is hard for other people to compete with, and that you have the necessary professional skills. I made a presentation regarding the academic postdoc phase back to 2013. Most of the contents still hold true.

https://prezi.com/av_vnknj_hws/tsinghua-reunion/

Not every PhD student reaches level 3 during their PhD training. If you have reached level 2 but failed to reach level 3 due to the limitations of the place where you received the training, then postdoc is the only chance for you to upgrade to level 3. Other than the problems of the trainees themselves, there are two scenarios that promote the failure to reach level 3 by the end of their PhD:

(1) If the PIs of the trainees have not reached level 3, or if they are laid back on mentoring, it is unlikely for you to have strong publication. A new lab is more likely to give you an opportunity to resume the training.

(2) The second is due to over-coaching. If the PI holds your hand at every step and the trainees totally rely on coaching, these trainees will reach a pseudo-level 3 with a good publication. Pseudo level 3 trainees do not have the ability to initiate or propose another good project in their field. In this case, I advise you to not join a big lab, since you may get lost without coaching.

9. What are the professional skills needed to succeed in academia?

Other than doing great science, mastering the following two professional skills will bring you from success to triumph. One is effective communication. The other is leadership. These two skills will enable you to convey your science and authorities to your trainees, your collaborators, your colleagues, your grant and manuscript reviewers, and the public. These two skills facilitate your science. However, doing great science is of primary importance, in the same way you cannot be a good cook without good food.

10. Should I switch my field from PhD to postdoc?

Postdoc is your last chance to switch fields before your faculty position. Switching fields is difficult. Yet, I highly recommend it for ambitious PhD students, or at least switching model organisms. A new field equips you with a new angle. At the interface between two fields, you will see what other people cannot and you will have a broader toolkit than others.

In a new field, you will need to go through the first three levels again. It takes time. The farther you jump across fields, the longer it takes before you can be productive. Well-funded and established PIs can afford this lagging phase, and a new PI will coach you through it quickly. By going through levels 1 through 3 again, your weaknesses and holes will get exposed, allowing you to fix them and have a more solid background before running your own lab. This process will also advance your understanding of the learning process, preparing you to be a better coach.

11. Why do scientists work hard?

Few people are born to work hard and there are many obstacles in the way. For example, people surrounding us may reinforce the tendency for leisure by advising us to have fun with them. TV dramas, parties, and games are distracting and tempting. In many cases, it seems silly to do more work. Why do scientists, from graduate students to established professors, work hard?

Being scientists is a unique career because we sit at the interface between the known and unknown. Known is what we already have, and in the known world, you do less, while others need to do more. Unknown is a realm of infinite possibility, you are “creating” something new by bringing “unknown" to the “known" world. You not only receive the training on how to convert unknown to known, but you also own the credits of your work since you are the first to find these treasures. You will carry your accomplishments with you throughout your life, enabling you to compete for fellowships/grants, find great jobs/labs, and earn respects/honors. Therefore, in science, hard work is particularly rewarding.

12. Why dedicate ourselves to science?

The knowledge we gain from science is constantly updated. What we believe to be true often turns out to be wrong, and what we disapprove of keeps coming back. In the end, what we demonstrate now will be trivial after 100 years. Why then should we still dedicate our career to science? I believe that there are three joys of being a scientist that go way beyond money, power, and fame.

(1) Benefiting others. The knowledge and understanding we gain from our research can be applied to relieve the pain of humans and animals. This sounds like a stretch from a basic scientist, however, when Drs. Andrew Fire and Craig Mello worked on RNA interference in worms, and when Drs. Jennifer Doudna and Emmanuelle Charpentier worked on Crisper/Cas9 in bacteria, they had no idea their research would change the world.

(2) Touching truth. The discoveries we make are not new, they have been there as they always have. These laws and principles exist beyond time and space. When we touch or come close to the “immortal world”, no words can express the ecstasy, the peace, and the wisdom of the moment.

(3) Nurturing youth. We provide smart trainees the opportunities and participate in their growth to become useful people. It is especially rewarding when their original curiosity is awakened during the training, allowing them to realize their internal value, to resist evaluation from the outside, and thus live a happy life.

13. How to be a successful graduate student or postdoc?

Find a wise mentor to trust and to follow. Learn their attitudes, scientific habits, and how they think. The best part of graduate school is that you have someone willing to mentor you. It is much faster than figuring things out by yourselves.

14. How to choose a wise mentor?

Wise mentors are not necessarily famous, and vice versa. A mentor needs to have the following characteristics for it to be worth following him/her during the best days of your life:

(1) Good scientist, at least at level 3.

(2) Good coach. A good mentor will fix your problems and guide you to the higher levels.

(3) Advocating for you. A wise mentor understands your success is their success. When you perform well, a wise mentor will give you opportunities to be better.

15. Why choose a new lab over an established lab?

Working in a new lab, your PI’s success depends on your success. Therefore, new PIs heavily invest their time, energy, and resources on the founding members of their labs. They work side by side with you, and they will always be there to discuss ideas and data. One to one training from your mentor is the fastest way to reach higher levels. By working in an established lab, your PI’s name will help you to gain more attention. However, in the end, people judge you based on your own abilities rather than your mentor’s. Of course, it would be ideal to find an established PI who can work side by side with you. When you are able to take care of science, science will take care of you. I advise you to find the place best for your own scientific training.

16. What are the new challenges for trainees and mentors?

(1) Materialistic outlook. We are born in an era where a materialistic outlook has seriously influenced education. People are judged based on their money, power, and fame. In these money-centered societies, the salary of trainees does not sound attractive for many smart and ambitious people.

Mentors needs to face the anxiety of trainees and bring peace and value to the lab. Instead of combatting human material desires, I think mentors need to reawaken their trainees’ original curiosity toward life, the universe, and the truth. This is inside all of us and brings us joy, peace, and simpleness. It doesn’t matter to me whether the trainees want to pursue science or money in the end, as long as they will be able to make their own decisions and control their own life.

(2) Overwhelming data and information. Previously, we were limited by data. With high throughput methods, such as deep sequencing, we are now limited by how to mine the information and knowledge out of data. Also, new papers are published every day but their quality varies. In the old days, a student was able to grasp the big picture of the field by reading papers. Now, it is almost impossible.

Mentors need to embrace the large quantities of data and information. I think the best way to take advantage without drawing is to upgrade ourselves to level 4. We need to provide a nurturing environment for trainees, or at least not nip their potentials to reach level 4. We also need develop new ways to teach our trainees with structured knowledge and inductive thinking. The road map I developed serves one purpose to help my students judge the quality of a paper.

(3) Critical peers. Science originated as a hobby of the nobles and soon became a profession with the appearance and rapid-growth of the scientific community. Peer review is at the heart of science. Even if we have all the intention to provide fair and helpful comments to each other, the time we can spend on reading other people’s work is limited.

Mentors need to appreciate the expertise and limitation of our scientific community. I think before we seek feedback from our peers, we need to put more effort into communicate efficiently to help our peers understand our results and our proposals. This way we effectively utilize their time and brains with respect. We also need to intentionally prepare our trainees with these professional skills. For example, this type of training in my lab starts with “how to write a clear email with the right tone?”.

17. Any advice to undergrads who are interested in research?

Before level 1 you are not useful to the lab. However, most mentors are nice and willing to give smart and motivated students the training opportunities. If you are lucky enough to join a lab, I advise you to prepare for at least 100 hours to dedicate to a particular experiment. Once you reach level 1 in one experiment, you will understand what it takes and will easily progress to level 1 for the work in another lab.

18. How do you give a good presentation?

First of all, why should you care? A good presentation that engages the audience may bring two main benefits.

1) You sell yourself and your science. A good presentation may attract trainees that may want to work with you (PIs may gain good postdocs or grad students, whereas postdocs and grad students may gain good undergrad students or technicians). It may also raise interest from those higher up, including funders, reviewers, scientific editors, or job recruiters.

2) You gain scientific input. After a good talk, you may receive good comments and feedback on how to improve your work and may even get proposals for collaborations. I cannot count how many times I have received good ideas and collaborations from the engaged audience, both inside and outside of my field.

Secondly, how do you prepare for the presentation?

1) Determine the content in your presentation. The content you present will be influenced by two main factors: the audience and the amount of time you are allotted.

After you find out who your audience is, you should not only tailor the background introduction to them, but also ask yourself why should they care? Determining if they are there to learn a new concept or method, follow a topic they are already interested in, or just simply see how I pursue an unknown question would help in best adjusting the presentation to them so that they get the most out of it.

A good rule of thumb is to make a take home message for each 10 min of your talk (1 message for a 10 min talk, 2 messages for a 20 min talk, 3 messages for a 30 min talk, etc.).

2) Provide an anecdote (a Li lab secret). Telling the audience a personal story allows them to get to know you better. It is a chance to convey your passion and commitment to your work, or you can simply engage an audience by telling them drama to make them curious or simply telling a joke that makes them laugh.

3) Tell a story. By presenting your research in a way of storytelling, you provide a logical flow of the process that will ultimately help them to understand the overall talk better. What is your problem? What is the current gap? What did you do? What did you discover? What are the options for the next step? You can go from one point to the next smoothly by telling a story.

4) Prevent the audience from getting distracted.

a. Keep the slides as simple as possible. Delete everything that you are not going to talk about. Make your own model figures to avoid extraneous factors. Also, always use sides with a white background.

b. Check your spelling and formatting. Make sure all the fonts and positions are consistent.

c. Give a title summary for each slide so that if people get distracted they can quickly catch up by reading the title.

d. Make sure you are on time. The key is practice, practice, and more practice.

Third, how to present? The key is being relaxed and confident.

1) Dress properly and professionally. Dressing properly may give you confidence. You should avoid clothing with words or too much information on it.

2) Strike a power pose. Before the talk, practice a power pose to give you more confidence. If you do not know a power pose, google one.

3) Smile. Relax and just smile.

4) Pause. You do not have to talk all the time. You also do not have to present all the time. I sometimes use an empty slide to draw attention back to myself.

5) Make eye contact and encourage questions. Maintaining eye contact may make the audience more engaged. Although some people do not like to be disrupted, I think taking questions in the middle of the talk will help you understand your audience and adjust your pace and content when you present the following slides.

6) Voice. I will make a separate section to discuss this issue.

19. How do you build a strong relationship with your mentor and colleagues?

4 key things come together to help you build a strong relationship that leads to trustworthy communication.

Competence: the ability to create personal credibility, bring knowledge and experience, and become the go-to person for information/expertise (preparation, research, review of your own mistakes).

Reliability: delivery of something you promise, even when you have to overcome obstacles to reach expectations in a timely fashion (you may be always late for a meeting or miss deadlines. This is a lack of reliability).

Commitment: making extra effort and seeking solutions to become a valuable asset.

Objectivity: ability to disconnect from personal life, push back effectively in an agreeable and courteous manner, take an unpopular stance, and tell someone they are wrong in a constructive manner based on data or information.

These 4 components can be applied to both personal and professional relationships. Every strong relationship has some element. For example, when you ask your friend for a favor and expect the favor to be executed with high standards, all 4 components must play a role.

20. What are the four types of "non-trainable" people?

Science can accommodate people much more diverse than other careers. You can see scientists that are emotional, indifferent, extroverted, introverted, selfish, generous, graceful, insecure, arrogant, humble, patient, impetuous, fashionable, or sloppy. I believe every person has the potential to be a good scientist, at least to level 3. However, due to limited time and resources, there are four types of people I do not mentor.

(1) Lack of passion. These people are not interested in science. I would advise them to find something they are truly passionate about because only when you do what you are passionate about, you can enjoy what you are doing.

(2) Wrong attitude. These people think they work for the PI, not for themselves. Also, they just want to have regular working hours without thinking about it after work, and when the PI motivates them they believe the PI is trying to squeeze them. I advise them to refer to “why we work hard?”. If you do not believe you are working for yourself, I suggest you to find a 9 to 5 job.

*These are people who received solid scientific training (have reached at least level 2), and decided to choose science as a job as a technician or senior research associate. They bring value to the lab and I have lots of respect to them. But for young students and postdocs, you cannot hold an attitude as an employee.

(3) No self-discipline. Few people are born to be a good scientist. People need to receive training to excel in science, which means they should be prepared to change. When mentors point out their bad habits or bad patterns, these people maintain their bad habits. An analogy like this is: a doctor tells a patient that due to their heart problem drinking will be dangerous for them, but the patient cannot control themselves or do not want to give up the fun of drinking. Since it is their own choice, there is nothing the doctor can do, and neither can the mentor. I advise these people to find a job that will minimize the negative effects of their habits and maximize their strengths.

(4) Too weak. These people cannot handle failure and frustrations. Many of the times, you are doing something no one has done before. An experiment may not work, an idea may be wrong, a project may be a dead end, a whole area may be out of funding, a manuscript may fail to convince the reviewers, a grant may not always be funded, etc…… People in science need to be able to handle these stresses and persist until success.

21. How do course-learning and research-learning differ from each other?

Labs in college courses differ from research in a number of important ways. For one, there is no textbook for research projects, instead you learn from a mentor, who could be a graduate student, a Postdoc or the professor. There is no concept of a passing grade as you are expected to be the guru of your research subjects. Likewise, your progress over the course of a research project is not tested periodically, but you have unlimited chances to reach there.

Beyond the surface-level differences are a few concepts that separate the two, the first being self-initiative. Course-learning requires little self-initiative. There are predetermined tasks defined by the professor, with expected results students achieve. Research labs, in contrast, investigate novel ideas which exist outside of the current understanding. It is up to the researcher to make and execute their own plans as there are multiple directions to pursue. It is up to the researchers to set their own goals and formulate their own path to a new discovery.

The fundamental difference lies in the subjects and the ways of thinking. The course-learning handles the “known”, while the research-learning handles the “unknown”. While both include logical thinking in terms of making and following a plan, critical and creative thinking dominates research. By doing research, you will learn to challenge your own results, the norm, and the “known”, and learn to be comfortable to approach “unknown” creatively.

22. How to better understand research-learning by comparing cooking and research?

Cooking and doing experiments for research may seem like two very different activities, but there are actually some similarities between the two. Here are a few:

(1) Both require following a recipe or protocol: When you cook a meal or conduct a scientific experiment, you typically follow a set of instructions or a recipe. In cooking, the recipe provides a list of ingredients and a set of steps to follow in order to create a dish. In research, the protocol outlines the steps that need to be taken to conduct the experiment and collect data.

(2) Both involve trial and error: Cooking and research both involve a degree of trial and error. When cooking, you may need to adjust the amount of certain ingredients or change the cooking time to get the desired result. In research, you may need to adjust the experimental conditions or methods in order to obtain meaningful results.

(3) Both require creativity: While cooking and research both require following a set of instructions, there is also room for creativity in both activities. In cooking, you can experiment with different flavors, ingredients, and cooking techniques to create a unique dish. In research, you may need to think creatively to design experiments that can answer your research questions.

(4) Both involve attention to detail: Whether you're cooking or doing research, it's important to pay close attention to the details. In cooking, small changes in ingredient measurements or cooking times can have a big impact on the final product. In research, small changes in experimental conditions or data collection methods can also have a significant impact on the results.

(5) Both require patience: Cooking a meal or conducting an experiment can take time, and it may require multiple attempts to get it right. In both activities, it's important to stay patient and focused on the end result.

Language English

简体中文