For this application, I had to submit the following: CV, one-page cover letter, two-page research statement, two-page teaching statement, one-page research-TGI statement and one-page DEI statement. Figures and references are usually good to have in the statements but I have excluded them here out of convenience. Slides for the talks can be found here.

Cover Letter

Dear search committee,

I am applying for the position of Assistant Professor in Plant Genetics, Genomics, and Breeding (ID: XXXXXX) at St Louis University (SLU). I find the position exciting as it offers a great opportunity to start a research group within a vibrant community of renowned faculty members in the Department of Biology. I am eager to apply modern quantitative genetics to dissect the complex genetic architecture of Resource Use Efficiencies (RUE) in plants by using maize as a model system. I think this strategy is the best for conducting interdisciplinary research, supporting the vision of the Taylor Geospatial Institute (TGI) as the national leader in geospatial research, and contributing to the development of geospatial research in St Louis. Possible research areas include the integration of GEM in genomic selection models, development of efficient genetic introgression strategies, and optimization of phenomic selection methods for RUE traits. The research outcome will generate novel insights in the underlying genetics of RUE, deeper understanding of complex GEM interactions, and new tools for the plant breeding community. In addition, phenomics-focused research has a tremendous potential for a complete integration between plant genetics and artificial intelligence. I would like to demonstrate my leadership in developing an independent research program, if given the opportunity to grow as an Assistant Professor.

I believe I would fit well here because my experience in research, teaching, mentoring, breeding, and collaboration is useful toward the data-driven role in delivering quality research and education. Brief summaries of my experience are provided here but the details can be found in my CV. My research expertise includes quantitative genetics, breeding, domestication, statistics, simulation and programming. I have taught in undergraduate and graduate courses, and mentored students in their independent research projects. I have been working on establishing a breeding program for purslane to be grown under controlled environments. I have collaborated with many academic researchers locally and internationally, and industry partners of various backgrounds. I appreciate the value of interdisciplinary research and I plan to use my liaison experience with collaborators, funders and stakeholders to deliver research impacts through an integrative effort. Overall, I would describe myself as a resourceful scientist who understands the technical details in biology, statistics and programming, as well as is able to translate the knowledge into mentoring, teaching and communication.

My visions and plans for research, teaching/mentoring and diversity/equity/inclusion can be found in their respective statements. I have included the contact information for my references in the following page due to the upload limit in the application submission portal. Thank you very much for your time and consideration. I look forward to hearing back from you.

Regards,
XXX

Research statement

I am a plant quantitative geneticist with a strong interest in interdisciplinary, collaborative research. I am trained in maize evolutionary genetics and modern crop breeding during my graduate and postdoctoral careers, respectively. I am excited to apply modern quantitative genetics and other disciplines to understand the complex genetic architecture of resource use efficiencies in plants. The research outcome is useful toward delivering sustainable crop improvement in quality, yield, and stress tolerance to meet the growing needs for climate resilience, nutrition, and economy. Here, I will describe my research experience and propose a research program at St Louis University.

During my PhD training at the University of Wisconsin-Madison, I studied the evolution of the genetic architecture of domestication traits in maize from its predecessor teosinte. I worked in several projects on fine-mapping and characterization of domestication quantitative trait loci (QTLs) and genes. These projects led me to understand domestication at the level of individual genes in great depth, as well as the fine-scale interactions between them. Subsequently, I undertook a polygenic approach by quantifying the changes in the genetic variances for multiple traits in maize and teosinte. The results demonstrated the trade-offs and genetic constraints during maize domestication, which offered a renewed perspective on how ancient farmers were able to convert a wild, largely inedible grass into a major crop known as maize. Collectively, I view domestication as an evolutionary process that encompasses genetic changes at various scales (large versus small effects) and sources (standing versus novel variants) over a long period of time. Thus, oligogenic and polygenic models are ideal for studying domestication from contrasting angles.

In my postdoctoral work at the Scotland’s Rural College, I examined crop breeding from the angle of genetic diversity management in modern crops. My research work revolved around statistical analyses of modern crop data and development of novel analytical tools. (1) I developed the Origin Specific Genomic Selection (OSGS) approach to introgress novel diversity into modern breeding populations. Its utility was demonstrated in the barley Nested Association Mapping (NAM) population. (2) I evaluated the Plant Variety Rights (PVR) system of Distinctness, Uniformity and Stability (DUS) by comparing the pre-existing morphological approach to a more efficient genomic approach. (3) I built the R/magicdesign package and magicdesignee Shiny app for designing and testing crossing schemes in Multi-parental Advanced Generation Inter Cross (MAGIC) populations. (4) I developed the Regression of ALLeles over Years (RALLY) method to detect selection signature in breeding populations by modeling the changes in allele frequencies as a logistic distribution. (5) I am now developing a novel approach for mapping genetical and non-genetical interactions as variance-controlling QTLs (vQTLs), investigating phantom epistasis in modern wheat hybrids, establishing a purslane production system in vertical farm, applying genomic selection in mutation breeding, and improving the statistical models in crop variety trials.

I am proposing for a research group with a focus on applying modern quantitative genetics to dissect the complex genetic architecture of Resource Use Efficiencies (RUE) in plants to tackle the grand challenges surrounding climate change, food security and sustainability. RUE includes, but is not limited to, efficiencies in photosynthesis and use of water, nutrients, soil and microbiome. Maize and teosinte are excellent model plants for this purpose because maize is an important crop worldwide and teosinte has a rich genetic diversity in traits pertinent to RUE. Much of the genetic diversity in RUE traits has been lost in modern maize due to selection during domestication and improvement9. In addition, RUE is best studied from the perspective of Genetic x Environment x Management (GEM) as they both involve complex, multi-dimensional interactions between genetic and non-genetic (environment, management practices) factors. We will use community resources such as the maize and teosinte nested association mapping population (maizeNAM, teoNAM) as the starting points for our research program. Our research outcome will not only improve our understanding of the genetics of RUE traits, but will also generate relevant knowledge in breeding toward sustainability and climate resilience. Our research group will explore the following three Research Areas (RA).

RA1. Integrating GEM in Genomic Selection (GS) models. Understanding GEM in RUE traits is key to improving plant breeding and maximizing crop performance under the threats of climate change. However, GEM is challenging to disentangle due to the experimental scale needed to evaluate all possible GEM combinations. Through the use of innovative trial designs and state-of-the-art GEM models, we can overcome the experimental barriers. For example, the Factor Analytic Linear Mixed Model (FA-LMM) reduces the complexity of environmental covariates by identifying the underlying latent covariates to fit in the GS model. This approach allows the model to fit large number of environmental covariates that are otherwise computationally impractical. Alternatively, in the maize Genomes to Fields (G2F) project, it has been shown that Deep Learning (DL) can be used to account for GEM in yield predictions, but the DL model performance remains similar to standard GS models. While these approaches are promising, there are still many opportunities to improve GEM modeling in GS. On the other hand, GEM has been well studied at the level of individual genes, such as the wild allele of teosinte branched1 (tb1) that shows higher phenotypic plasticity than the domesticated allele under a common maize background. By leveraging information from the literature, we can incorporate GEM modeling in GS and improve our mechanistic understanding of GEM interaction in RUE traits.

RA2. Developing efficient genetic introgression strategies. Crop wild relatives are valuable genetic resources in breeding due to their high RUE in enabling the plants to adapt to wide environments including marginal lands. Alleles from wild relatives are often used in pre-breeding; however, the process is neither efficient nor straightforward. Marker Assisted Selection (MAS) is commonly used for introgressing one or few alleles, which is not applicable for complex traits like RUE. While phenotypic and Genomic Selection (GS) are good for handling complex traits, they often perform poorly in selecting wild alleles. In one case, selection in a triple cross of one landrace and two elite wheat lines led to a reconstitution of the elite parent genome. A recently developed method known as Origin Specific Genomic Selection (OSGS) combines the best of both MAS and GS5. OSGS partitions favorable alleles according to parental origins and allows us to introgress wild alleles more effectively. There is room for extending OSGS to account for multiple traits and parents. In addition, genetic simulations are often used to evaluate model performances and selection decisions. We can couple innovative methods like OSGS with simulations to design better genetic introgression strategies for RUE traits.

RA3. Optimizing Phenomic Selection (PS) methods for RUE traits. PS was recently developed as an alternative to GS where it derives the relationship for model prediction from the endophenotypes (phenome) instead of molecular markers (genome). Phenome taken from near infrared spectra, satellite image, transcriptome, proteome or metabolome can capture the complex GEM interactions that are otherwise missed in the genome. Therefore, the phenome is likely a better predictor for phenotypic traits with strong GEM interactions like RUE. However, the current results in PS are mixed and opens up opportunities to optimize the methods and models. We will (1) investigate PS in RUE traits under multiple factorial combinations of GEM, (2) evaluate PS across different developmental time points and quantify the trait phenomic architecture, and (3) develop a method for simulating the phenome on top of existing genetic simulation approaches. While the predictive abilities of PS vs GS remain to be seen, PS has the advantage of being easier to integrate into an artificial intelligence-based system.

My plans for a successful research program involve research, dissemination, funding, collaboration, engagement and training. I intend to use my broad research experience to formulate clear research directions for the group. There will be practical opportunities in greenhouse, field and basic laboratory work, as well as analytical opportunities in statistics, simulation and programming. The research outcomes will be disseminated through publications, talks, posters, websites and outreach participation. These outputs will be crucial in supporting grant applications to secure extramural funding and sustain the growth of the research group. Our research and grant applications will be assisted by collaboration with partners of complementary expertise to encourage creativity and broaden our research topics. Given the wider interest of our work, engagement with various stakeholders such as breeders, seed industries and growers is essential to guide our research direction. I highly value a strong training component in my research group for everyone to achieve research excellence and independence. There will be training opportunities in conducting research, presenting results, teaching classes, writing/reviewing manuscripts, writing grants, building collaboration and liaising with stakeholders. Good training is the key to building capacity in a research group that can better contribute to the university, industry and society.

Teaching statement

Education is a life-long process that plays an important role in shaping who we are. As a member of the academia, I strive to deliver quality education in undergraduate and graduate courses, as well as research mentoring. I am excited to demonstrate my teaching commitment in both undergraduate and graduate level courses at St Louis University (SLU) and Department of Biology. My diverse research background offers immediate relevance to teaching courses in the undergraduate and graduate degrees in Biology. I can teach in any area related to quantitative genetics and plant breeding, including theories and applications of genetics, genomics, statistics, programming, agriculture and experimental designs. If needed, I can contribute to the development of new courses in relevant areas too. I can adapt my teaching to a wide-array of settings including large lecture-based and small discussion-based courses using offline/online methods.

My teaching vision involves training students to learn effectively and develop critical thinking skills. Having experienced the Malaysian, American, German and British education systems, I favor the holistic liberal arts approach for teaching. This approach helps the students to keep up with the new and fast emerging scientific knowledge in this era. For instance, genomic selection and gene editing with CRISPR-cas9 only arose around two and one decade ago, respectively. Even though some of us may not have been taught about new topics in our formal education, we are able to understand the concepts easily because we have been trained as quick learners. It is important to train the new generation to be efficient learners so that they are equipped with the skills to face any uncertainties in the future.

I plan to deliver my teaching vision through a circular approach of adaptation, analogy and assessment. (1) I strive to adapt my teaching style and course content to the student’s needs. Because everyone is unique, it is important to provide the space for each individual to develop learning styles that match their strengths. For example, I have experienced a regional difference (US versus UK) in the preference for focusing on the figures or texts when reading a scientific article. A good figure conveys the experimental results clearly while a good text brings out the authors’ narrative of the results. Just as one prefers to read an original book while another prefers to watch a movie adaptation, neither approach is superior to the other. (2) I try to use good analogies in explaining concepts that can be hard to grasp. Analogies allow us to use prior knowledge to understand unfamiliar concepts and thus makes the topics more relatable and attractive. For example, genotype imputation can be confusing at first encounter, but a parallel can be drawn using many things that we do in daily life such as guessing whether the rain will continue or stop based on cloud cover and wind direction. (3) I rely on assessments to gauge student’s learning progress, needs and interests. A combination of short assessments (e.g. clicker questions, weekly quizzes and surveys) and post-mortems are effective in troubleshooting any learning issues and identifying new areas of interest. The outcome feeds back into the cycle to promote an engaging learning environment for the students.

Over the years, I have demonstrated and refined my teaching philosophies in the several teaching opportunities. In 2013, I began my first formal teaching experience as a Teaching Assistant (TA) for an undergraduate course in General Genetics at the University of Wisconsin (UW) - Madison. My primary responsibility was to provide support to the students in understanding lecture materials through discussions. I gave short recaps of the lectures and led the discussion sessions. I maintained two-way communications by assessing the students’ understanding through short questions and providing them with flexible opportunities to ask questions anytime in class, emails and face-to-face meetings. Later in 2021, I was invited as a guest lecturer for the XXIII International Master in Plant Genetics, Genomics and Breeding organized by CIHEAM Zaragoza in Spain. Specifically, I was tasked to deliver 8 hours of lecture and practical for the section on “IBD, IBS, Genetic Distance, Population Structure”. Due to the ongoing pandemic and travel restrictions, the entire section was conducted online. This experience was more challenging than usual because of the lack of visual interactions between the students and me. To circumvent the challenge, I requested the students to speak out anytime or type their questions in the chat boxes or emails. In the practical sessions, we had computational analyses in R. To keep everyone up to speed, I divided the analyses into multiple small sections to walk the students through carefully and debug as needed. In the take-home exercise, I wrote a few short answer questions to help guide the students along their analyses in R. The questions were focused on the answers’ justifications as a way to stimulate the students into thinking critically and understanding how the analyses worked. I was excited to find the teaching materials useful in the students’ own research projects as they came up with questions on analyzing their datasets. Recently in 2022, I served as a guest lecturer for the 4th year undergraduate class in Genetic Improvement of Crops organized by the University of Edinburgh. The class was offered as an elective for students who were enrolled in the Global Academy of Agriculture and Food Security program. I delivered 5 hours of lecture and practical for sections on “Conventional and Advanced Breeding Methods” and “Plant Variety Rights”. Guest lecturing can be challenging because there is a limited time to know the students and adapt the class materials to their background. For example, in contrary to what I was previously told, I learned in a practical session that the students did not have a strong knowledge of programming in R. Upon realizing that, I made an impromptu adjustment to spend extra time in teaching the students on how to use R before diving further into the initial plan in data analysis. Currently, I am working with a team of educators to design new modules on Horticultural Biotechnology and Plant Biotechnology, which are undergraduate and graduate courses, respectively. This opportunity allows me to understand and partake in new curriculum development, and it has been a great learning experience.

My mentoring vision is to provide support and space for professional growth so that the mentees can achieve research independence and excellence. I aim to cultivate a healthy environment for my research group where people can come to receive training appropriate to their levels (e.g. technicians, undergraduate/graduate students, postdoctoral researchers, visiting scholars) and contribute to the training of others. Research capacity is often enhanced by collaborating with field experts. Similarly, within my research group, I believe that having members who are well supported and trained can add creativity into their research projects and take their research quality to the next level.

I plan to approach mentoring through discussion, training, troubleshooting and reward. (1) Initially, I discuss with the mentees to identify their interests in the possible project options and provide a big picture understanding of the chosen project. The project is then broken down into multiple parts so that the mentees can focus on one at a time. (2) Next, I provide technical training by demonstrating the process and explaining the steps as we go. If the specific skills are not within my knowledge, I connect the mentees to the right person who could be either in our group or not. Once this is done, I leave the mentees to work independently while checking in occasionally and making myself available for help. (3) As many research projects go, experimental complications and failures are inevitable. It is important to emphasize that this is part of the process and that I am always there to support and troubleshoot together. (4) I firmly believe in encouragement and positive reinforcement as a way to recognize mentees’ hard work and perseverance. Overall, the goals of these plans are to help mentees learn and develop projects’ ownerships over time.

My PhD projects led me to 16 direct and indirect undergraduate research mentorships and 1 PhD research supervision. In 2013, I worked with an undergraduate researcher on diversity sequencing and expression analysis in multiple maize lines. In Fall 2015, I worked with a visiting scholar and an undergraduate to investigate a QTL for the maize prolificacy trait (number of ears on a branch) and found a different allele that was selected during domestication. In Summer 2016, I worked with a visiting undergraduate to test for interactions in staminate ear (spikelet sex) QTLs and identified significant interactions with the major domestication gene, teosinte branched1 (tb1). I mentored several undergraduates to work on semi-high-throughput seed imaging, germination test and data analysis. I contributed in the development of a comprehensive undergraduate research training experience using the teosinte nested association mapping (teoNAM) population. All participating students worked on independent research projects from start to finish, including field trial management, trait phenotyping, data curation, QTL mapping and result presentation. The undergraduates presented their results in meetings, symposiums and the Maize Genetics Conference in 2017. All research projects resulted in four journal publications and two chapters in my PhD dissertation with contributing undergraduates as co-authors. Currently, I am mentoring a visiting undergraduate student on “ryegrass speed vernalization and speed breeding”, and I am co-supervising a PhD student on “rapid domestication of purslane for vertical farming”. I plan to bring my research mentoring approach and build on my experience to deliver a strong research and teaching program with holistic training.

Research and Taylor Geospatial Institute statement

My research vision involves applying modern quantitative genetics to understand the complex genetic architecture of Resource Use Efficiencies (RUE) in plants. RUE encompasses use efficiencies in light, water, nutrient, soil and microbiome, which are all important breeding targets for developing climate resilient crops and supporting regenerative agriculture. At Saint Louis University (SLU), I plan to achieve my research vision through three approaches, including quantitative genetic modelling of Genetic-by-Environment-by-Management (GEM) interactions in RUE traits, genetic introgression of RUE traits from landrace and wild relatives into modern breeding germplasm, and optimization of phenomic selection methods for RUE traits. These proposed plans will contribute to the missions of the Taylor Geospatial Institute (TGI) by leveraging geospatial and remote sensing technologies and data in our research program.

A key objective of TGI is to advance knowledge and encourage innovation in geospatial science and its applications in diverse research fields. Our research program aligns with this mission by improving our understanding on how phenotypic trait variations within plant populations are produced from the interactions involving genetic factors, heterogeneous environmental conditions and agronomy practices. We will integrate genomic data with high-resolution geospatial information in our research projects to understand marker-trait relationships and develop tailored breeding strategies for improved crop varieties.

Remote sensing technologies such as satellite imagery, unmanned aerial vehicles (UAVs), and ground- or lab-based sensors are widely used in High-Throughput Phenotyping (HTP) and real-time monitoring of crop growth, health and phenotypic characteristics across spatial and temporal scales. Collectively, the resulting data are known as the phenome. Recent developments in statistical genetics enable us to use the phenome for modeling genetic relationships between different genotypes to make predictions on phenotypic traits. In addition, the phenome offers an advantage over standard genomic prediction/selection by also capturing environmental and interaction (e.g. GEM) effects. Therefore, the phenome is important for predicting variations in RUE traits across diverse landscapes as RUE traits are likely to harbor strong GEM interactions given the intrinsic dependency of these traits on environmental conditions.

Our research program can contribute to TGI’s mission of fostering interdisciplinary collaboration and knowledge exchange. Various expertise is available among TGI’s members, such as geospatial science, engineering, computer science, environmental science, agronomy and genetics. By connecting with leaders from various fields, we can diversify our research perspectives and methodologies to better tackle complex agricultural and environmental challenges. Furthermore, collaborative proposals add significant values toward securing funding supports from state, federal and industrial sources.

Research aside, integration of TGI’s infrastructure with SLU facility such as the Department of Biology greenhouse can enhance undergraduate learning and outreach initiatives significantly. This strategy enriches the curriculum and provides the students with hands-on experience in monitoring plant development, analyzing experimental treatment effects, and understanding spatial and temporal patterns. Students will be better equipped with the skills for real-world applications in geospatial science. Outreach programs enable us to engage with wider public and demonstrate cross-disciplinary research between geospatial science and plant genetics. Overall, our research program has the potential to significantly advance the TGI’s missions and expand on the applications of geospatial and remote sensing technologies in plant breeding, genetics and genomics. Partnership between our research program and TGI will lead to stronger contributions toward enhancing agricultural productivity and sustainability, and improving food security in a rapidly changing world.

Diversity, equity and inclusion (DEI) statement

When I first left my home country for college, I feared not being able to fit in only to find that I was showered with a warm welcome by the communities in Bloomington, IN. I met with kind neighbors who offered directions and rides, and friendly strangers on the streets who greeted passers-by. I participated in many local activities such as furniture giveaway, picnic, apple picking and Thanksgiving dinner. These activities were organized by the Bloomington International Students Ministries (BISM) as part of their goals in welcoming global diversity. These overwhelming receptions helped me greatly in adapting to the American culture and highlighted the importance of diversity, equity and inclusion (DEI) in creating a comfortable space for everyone. In return, I am committed to promoting DEI wherever possible.

I had many opportunities to contribute toward DEI when I was a graduate student at the University of Wisconsin-Madison. During the six years in my PhD, I directly and indirectly mentored 15 undergraduate students from various backgrounds, of which 7 were women, 3 were non-White minorities, and 2 were non-Americans. The students started out as research assistants to fulfill their research credits, and continued with their projects either for multiple semesters or until they graduated. As a research mentor, I encouraged and assisted them in making scientific presentations, especially those who lacked prior experience. The students presented their work in lab meetings, symposiums and conferences, as well as contributed to publications. These efforts were important, especially to the minorities, in engaging the students with broader research and career development. Apart from the students, I helped two visiting professors and a postdoctoral researcher in settling down after coming from halfway across the globe. I assisted them in finding housing, setting up utilities, and navigating through the university administrations.

Going forward, I aspire to further strengthen my commitments in promoting DEI at multiple levels including my research group, department and university. To cultivate diversity at work, it is important to keep the door open to various minority groups in science, including, but not limited to, women, persons of color, LGBT+, disabled and first-generation students. In addition to having open doors, there is also a need to enable the paths for diversity to exist across all work levels. I strive to uphold equity at work by ensuring that everyone is given sufficient support to achieve fair and equal outcomes. This process can be challenging as it requires careful consideration of everyone’s background and not every disadvantage is apparent. Keys to safeguarding inclusion lies within good communications and cultural exchange. Being inclusive provides a sense of belonging to everyone and a better understanding of each other. Overall, diversity, equity and inclusion are inseparable as they go hand-in-hand toward creating a shared platform for everyone to shine.

Here, I am extending my multi-cultural experience that spans three continents toward building my plans for promoting DEI. D: I intend to remove the recruitment barrier into research and education by reaching out to various communities through outreach programs. Outreach can nurture scientific interest in kids from various minority backgrounds and bridge the gaps in higher education. I will join a DEI committee to contribute through a team effort. Recruitment for my research group members will be advertised in multiple platforms (e.g. job boards, career fairs, social media and emails) to reach out to a diverse pool of candidates. I will provide academic and career support to everyone through advice and opportunities in training and grants. E: I plan to deliver a fair education to every student. Some students may suffer from various disadvantages due to their backgrounds. I strive to be an observant educator who can identify and address the students’ needs. To achieve a fair recruitment process, I will evaluate not only the candidates’ research interest and abilities, but also consider any shortcomings that they might have faced. I: I will be flexible in engaging the students and establish a curriculum that avoids fitting the students into a box so that everyone can develop their own learning styles. As a research group leader, I will be accommodating individuals’ needs for parental leaves, family care, health care (including mental health), preparation for examinations, vacations and others. I will ensure sufficient cover support on research projects and protect the ownership of each group member in their projects. I will also encourage inclusive social events to build a healthy and positive research community.

Modesty and humility are important values in building a DEI-friendly environment. I will continue to improve my flexibility and willingness to listen to everyone, and step up for others as needed. As the DEI standards evolve over time, I am offering my best to keep up with the changes and uphold the highest standards of DEI. I strongly believe that DEI values are essential for maintaining a productive research group and delivering quality education.