DEVELOPMENT OF GENE-BASED BREEDING (GBB) FOR CROPS OF AGRICULTURAL IMPORTANCE

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: COMPLETE
• Funding Source: HATCH
• Reporting Frequency: Annual
• Accession No.: 1022603
• Project Start Date: Apr 6, 2020
• Project End Date: Mar 25, 2025
• Program Code: [(N/A)]- (N/A)

Recipient Organization
TEXAS A&M UNIVERSITY
750 AGRONOMY RD STE 2701
COLLEGE STATION,TX 77843-0001

Performing Department
Soil & Crop Sciences

Non Technical Summary
The world's population will approach 9.6 billion by 2050. To feed this population, agricultural productivity must be increased by 45% - 50% over the next 30 years. To address the global food challenge, several proposals have been made and attempted, including crop genetic improvement through research, development and applications of molecular technologies. These technologies have contributed to crop improvement, but the genetic gain in staple crops such as wheat and rice remains stagnated or has only slightly increased. Nevertheless, the level of the reported genetic gain cannot meet the demand of food, feed, clothing and biofuel for the projected global population. This project aims to develop and extend a novel plant breeding technology, designated gene-based breeding (GBB), to the crops of importance to U.S. agriculture, with an emphasis on corn and cotton. GBB was first proposed by the director of this project in 2014 and has been studied and demonstrated to be multiple-fold more powerful and more efficient for enhanced plant breeding. It has been shown that the present best cultivars could be continuously improved by 118% through GBB. In this period of the project, We will acomplish three research objectives. First, we will further develop the GBB that we previously developed for inbred line and hybrid cultivar breeding in corn through extended analysis of the genes controlling corn grain yield and extend it to application in nationwide corn breeding programs, Then, we will demonstrate the utility and efficiency of the GBB for enhanced and accelerated breeding in maize through developing super-high-yielding hybrids by GBB that are competitive for commercial production. Finally, we will also further develop the GBB that we previously developed for enhanced breeding in cotton by extended analysis of genes controlling cotton fiber quality and yield, and extend it to application in nation-wide cotton breeding programs. Given its potential, ability and efficiency for enhanced plant breeding, this project will make GBB in practical use for enhanced breeding in corn and cotton, thus promoting research, development and application of GBB in all field crops such as wheat and soybean, in vegetable crops such as tomato and potato, in fruit crops and trees such as watermelon and apple, and in livestock such as cow and chicken. Therefore, the finding and achievements of this project will promote the next green revolution, thus helping feed the world.

Animal Health Component

20%

Research Effort Categories

Basic

50%

Applied

20%

Developmental

30%

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
201	0199	1081	60%
202	0120	1080	20%
206	0001	1040	20%

Knowledge Area
206 - Basic Plant Biology; 202 - Plant Genetic Resources; 201 - Plant Genome, Genetics, and Genetic Mechanisms;

Subject Of Investigation
0120 - Land; 0199 - Soil and land, general; 0001 - Administration;

Field Of Science
1040 - Molecular biology; 1081 - Breeding; 1080 - Genetics;

Keywords

gene-based breeding (gbb)

gene

grain yield

fiber trait

inbred line

hybrid

maize

cotton

Goals / Objectives
The goals of this hatch project are to develop gene-based breeding (GBB) systems in crops important to Texas and U.S. agricultural production, with an emphasis on maize and cotton. In the past period of my hatch project, we have developed GBB for maize inbred and hybrid grain yield breeding and GBB for cotton fiber length breeding using individual breeding populations developed from bi-parental crosses. In this period of the project, we will particularly accomplish the following three research objectives:To enhance and extend the GBB system developed for maize inbred and hybrid breeding by integrated analysis of maize diverse inbred lines representing the gene pool and diversity of the U.S. public maize breeding programs;To demonstrate the utility and efficiency of the GBB system for enhnaced and accelerated breeding in maize through developing super-high-yielding hybrids by GBB that are competitive for commercial production in Texas and beyond; andTo enhance and extend the GBB system developed for enhanced breeding in cotton through integrated analysis of cotton cultivars, breeding lines and germplasm lines that are widely used in the U.S. cotton breeding programs. The completed project will result in enhanced GBBs that are suitable for enhanced and accelerated breeding for specific and across environments and for specific and across populations in different U.S. breeding programs in maize and cotton. Furthermore, the completed project will also lead to development of the very first group of super-high-yielding maize hybrid varieties by GBB that are competitive for Texas and U.S. maize production. Finally, the methodologies and concepts of GBB will be applicable to enhanced breeding of hybrid and inbred varieties for many other crops and livestock because the genes controlling their agronomic traits can be also genome-wide high-throughput cloned using our gene cloning technology.

Project Methods
This project will accomplish three research objectives.Objective 1: To enhance and extend the GBB system developed for maize inbred and hybrid breeding by integrated analysis of maize diverse inbred lines representing the gene pool and diversity of the U.S. public maize breeding programsAll maize cultivars grown in the U.S. are heterotic hybrids. We previously developed GBB for inbred breeding (Zhang et al. 2020) and GBB for hybrid breeding (Zhang et al. 2019); however, they were developed using bi-parental populations or hybrid populations derived from more related inbred lines. This objective is to identify the favorable alleles and/or heterotic genotypes or the genic SNPs/InDels for more grain yield genes and to identify the grain yield genes whose effects are genotype-consistent and genotype-specific for GBB. We developed six inbred parent/hybrid populations: four test-cross inbred parent/hybrid (TCIH) populations, one immortalized F2-like hybridization inbred parent/hybrid (USIFIH) population and one factorially-crossed inbred parent/hybrid (USFIH) population. The TCIH populations were developed from three bi-parental inbred line populations crossed with four diverse inbred lines and the USIFIH and USFIH populations were developed from 302 diverse inbred lines representing the gene pool and diversity of the U.S. public maize breeding programs. These 302 diverse inbred lines include 36 stiff stalk (SS), 112 non-stiff stalk (NSS), 74 tropical and subtropical (TS), 64 mixed, 9 popcorn and 7 sweet corn lines. We phenotyped the 302 inbred lines and their 302 hybrids of the USIFIH population for 20 agronomic traits at two locations. We sampled the developing ears and ear leaf tissues from the USIFIH population. In this objective, we will first sequence the maize genes, including the 9,007 genes controlling grain yield and 12 grain yield and quality component traits that we previously cloned, while we further phenotype the population for the 20 agronomic traits at multiple environments. Then, we will identify and functionally validate the genes controlling the 20 agronomic traits using our high-throughput gene and QTL cloning technology (Zhang et al. 2016). Third, we will analyze the genes controlling the 20 agronomic traits to identify their favorable alleles and heterotic genotypes and to determine their expression profiles and networks. Finally, the utility and efficiency of the genes controlling the agronomic traits for GBB will be tested across environments and across populations using the NFAs, genic SNPs/InDels and/or expression profiles and networks of the genes controlling the objective traits. The environments will include different U.S. maize production states and the populations include, but are not limited to, the four TCIH populations and the USFIH population. Therefore, these experiments will result in the favorable alleles and heterotic genotypes, genic SNPs/InDels and expression profiles and networks of the genes controlling the 20 agronomic traits that are necessary for parent selection and cross design for GBB. These experiments will also result in a toolbox of genes and associated phenotype prediction models necessary for accurate progeny selection for GBB for individual environments and across environments, and for individual and different populations.Objective 2: To demonstrate the utility and efficiency of the GBB system for enhanced and accelerated breeding in maize through developing super-high-yielding hybrids by GBB that are competitive for commercial production in Texas and beyondThis objective will be accomplished by two phases. In the first phase (2020 - 2023), the 302 U.S. diverse inbred lines that could yield 45,451 half-diallel hybrids, and the inbred lines of the TCIH populations will be used for hybrid breeding with GBB. In the second phase (2023 - 2025), 1,500 diverse inbred lines will be selected from the U.S. maize inbred line collection and used for hybrid breeding with GBB, which will yield 1,124,250 half-diallel hybrids. For GBB in the first phase, since the inbred line parents have already been genotyped for the NFAs, genic SNP/InDel and expression profile and network of the genes controlling grain yield, the genic datasets will be directly used to predict the grain yields of all 45,451 possible half-diallel hybrids using the prediction model trained and validated in Objective 1. They could be individually or jointly used for hybrid grain yield prediction. We showed that when the jointed predicted phenotypes were used for hybrid selection, the top 10% high-yielding hybrids selected by GBB were essentially completely consistent with those selected by replicated field trials. From the first phase of GBB, we will select 10 highest-yielding hybrids (0.02%) and 10 lowest-yielding hybrids for further verification. In the second phase, we will first genotype the 1,500 inbred lines for the NFAs, genic SNP/InDel and expression profile and network of the genes controlling grain yield using the genic toolbox developed in Objective 1 and then predict the grain yields of all 1,124,250 possible half-diallel hybrids derived from the inbred lines using the prediction model trained and validated in Objective 1. Approximately 50 highest-yielding hybrids (0.004%) and 50 lowest-yielding hybrids will be selected for further verification. At this point, the selected highest- and lowest-yielding hybrids will be actually made and tested in grain yield through replicated field trials at multiple environments, with the commercial hybrids recently released at the trial locations as checks. Comparison will be made between the predicted and observed grain yields of the hybrids to verify the utility and efficiency of the developed GBB. The highest-yielding hybrids will be selected for regional and national hybrid variety testing trials, from which the hybrids competitive for commercial production will be selected.Objective 3: To enhance and extend the GBB developed for enhanced cotton breeding through integrated analysis of the cultivars, breeding line and germplasm lines widely used in U.S. breeding programsWe previously developed GBB for enhanced cotton fiber length (upper-half mean length, UHML) breeding. The GBB was developed using a bi-parental population derived from a cross of Upland cotton (Gossypium hirsutum) x Sea Island cotton (G. babardense), for which we identified the favorable alleles of 226 of the 474 fiber length genes. The favorable alleles of the genes controlling other fiber traits have not been identified yet, even though they are essential for GBB using the NFAs and/or genic SNPs/InDels of the genes. Furthermore, Upland cotton produced about 95% of the U.S. and world cotton. Therefore, we will select 300 - 500 Upland cotton varieties, breeding lines and/or germplasm lines that are able to represent the genetic variation and gene pool of U.S. cotton, phenotype them for fiber yield and quality traits in multiple environments, genotype them using the 10,854 genes controlling these fiber yield and quality traits that we cloned and profile their expressions in developing fibers. The SNPs/InDels contained in the fiber trait genes will be identified, from which the genic SNPs/InDels that statistically significantly influence fiber traits will be identified by the candidate gene approach of the genome-wide association study (GWAS). The favorable alleles and heterotic genotypes of the fiber trait genes will be determined. Finally, the utility and efficiency of the NFAs, genic SNPs/InDels and expression files of the fiber trait genes for GBB will be tested and validated using different pedigree breeding populations. These experiments will substantially enhance the GBB that we developed for cotton fiber trait breeding and result in a toolbox for enhanced breeding through GBB for different populations across environments in different U.S. cotton breeding programs.

Progress 04/06/20 to 09/30/20

Outputs
Target Audience:Gene-based breeding (GBB) is a novel, extremely powerful and efficient technology for plant breeding by design by making full use of the genes controlling the objective traits through the entire process of breeding, including parent selection, cross design and progeny selection. GBB allows accurately selecting the breeding parents that are the most desirable to meet the breeding objectives, designing cross that maximally recombines the favorable alleles and heterotic genotypes of the genes controlling the objective traits from the breeding parents into progeny and accurately selecting the individuals from the breeding progeny that has the greatest potential in high yield, high quality and high tolerance to biotic and abiotic stresses. It has been shown in cotton that the present best varieties could be further improved by 73 - 118% through GBB. It has been shown in corn that GBB is hundred-fold more powerful and more efficient than the present breeding methods for hybrid variety breeding. For instance, a hybrid variety breeder can screen a million of hybrids for the best hybrid within one year and at cost of approximately $150,000 (including labor and supplies) through GBB, while such a number of hybrid screening work will take a breeder thousands of years at a cost of hundreds of million dollars through the current breeding method. Therefore, this project is largely targeted to the following audience: Cotton and maize breeders: This project will be working in collaboration with cotton and maize breeders, including Dr. C. Wayne Smith (cotton breeder), Dr. Stave Hague (cotton breeder), Dr. Wenwei Xu (maize breeder) and Dr. Seth Murray (maize breeder), Texas A&M University, College Station, Texas. Therefore, the GBB, toolkits, knowledge and methods developed through this project will be directly and immediately transferred into their cotton and maize breeding programs, thus revolutionizing the current plant breeding methods and helping feed the world. Crop and livestock breeders: The GBB, toolkits, concepts, knowledge and methods developed through this project will be applicable to enhanced breeding of all crops, vegetables, fruit trees and livestock. These crop and livestock breeders will be likely interested in development of GBB for their crops and livestock. Students: The world's population will approach 9.6 billion by 2050 and to feed this population, agricultural production must be increased by 45% - 50% over the next 30 years. Nevertheless, the genetic gain in major crops remains stagnated or has only slightly increased. The level of the reported genetic gain cannot meet the demand of food, feed, clothing and biofuel for the projected global population. GBB, knowledge and tools developed through this project will be extended to classrooms to teach and train students - the next-generation breeders in application of GBB for enhanced breeding to help feed the world. Molecular biologists in plants, animals and humans: Molecular biologists in plants, animals and humans have studied and are continuing to study biology of plants, animals and humans in an isolated manner, such as one gene at a time and one gene for a trait. This project will demonstrate that most traits are actually controlled by multiple genes and the phenotype of a trait is the consequence of interaction among the genes controlling the trait. Therefore, it is essential to understand the molecular mechanisms underlying a trait and develop approaches efficient to manipulate the trait using most, if not all, of the genes controlling the traits. Moreover, this project will provide genes for comprehensive molecular studies of traits important to maize and cotton. Biotechnological scientists: The genes, knowledge and toolkits for GBB achieved in this project provide gene sources, knowledge and toolkits essential for biotechnological scientists to design strategies and methods for crop improvement through marker-assisted selection, RNAi gene regulation, gene editing and genetic engineering. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?The goals of this project are to develop gene-based breeding (GBB) systems in crops important to Texas and U.S. agricultural production, with an emphasis on maize (corn) and cotton. Once GBB is developed, the current plant and animal breeding methods will be revolutionized in potential, productivity and efficiency and substantially improved superior inbred line and hybrid varieties will be developed by design according to breeding objectives, thus promoting the next green revolution and helping feed the world. This project has trained 1 postdoctoral scientist, 13 graduate students and a number of students in classroom in the period of this progress report: Postdocs: Yun-Hua Liu 2. Graduate Students: Daman Bhangu, Ph.D. in Plant Breeding, graduated in 2020 Mehmet Dogan, M.S. in Plant Breeding, graduated in 2020 Gali Bai, M.S. in Molecular and Environmental Plant Sciences, Graduated in 2020 Selfinaz K Velioglu, M.S. in Plant Breeding, graduated in 2020 Jamshaid Ali Junaid, Ph.D. in Plant Breeding, graduated in 2020 Jingjia Li, Ph.D. in Ecosystem Science and Management, graduated in 2020 Homa Zarghami, Ph.D. in Molecular and Environmental Plant Sciences, 2015 - present Ali Ullrich, M.S. in Plant Breeding, 2016 - present Mustafa Cilkiz, Ph.D. in Molecular and Environmental Plant Sciences, 2017 - present Xuan Lin, Ph.D. in Molecular and Environmental Plant Science, 2017 - present Salma Bibi, M.S. in Molecular and Environmental Plant Science, 2017 - present Alper Adak, Ph.D. in Plant Breeding, 2017 - present Ozge Ekinci, M.S. in Plant Breeding, 2020 - present 3. Classroom teaching: SCSC, GENE, BIOT and MEPS 654 - Analysis of Complex Genomes (lectures) SCSC 685 (602) - Directed Studies MEPS 691(618) - Research SCSC 691 (606) - Research How have the results been disseminated to communities of interest?The results and achievements of this project have been disseminated to communities of interest through numerous methods: Published the results and achievements of this project in publicly readily accessible, internationally-well recognized peer-reviewed journals, including Genomics, Scientific Reports, Molecular Genetics and Genomics, Plant Science, and professional book. Presented the results and achievements of this project at national and international professional conferences such as the International Plant & Animal Genome (PAG) Conference. Incorporated the findings and discoveries of this project into the classroom teaching such as SCSC, GENE and MEPS 654 - Analysis of Complex Genomes (lectures). Incorporated the findings and discoveries of this project into training of students, postdoctoral associates and junior scientists. We trained 13 graduate students and 1 postdoctoral scientist during this period of the project. Directly delivered the new knowledge, resources and tools developed in this project to users such as breeders and researchers nationwide through collaboration. Released the Phenotype Prediction Toolkit 4.0 (PPTK 4.0) software, 40,866 rice high-density and high-quality SNPs, 740 genic SNPs and favorable alleles for the 474 GFL (cotton fiber length) genes and 181 ZmF1GY genes that enable accurate prediction of grain yields of F1 hybrids from their parents through peer-reviewed publication; and 474 GFL genes controlling cotton fiber length through GenBank, National Center for Biotechnology Information (NCBI). What do you plan to do during the next reporting period to accomplish the goals? Prepare 4 - 5 manuscripts from the results obtained in the previous years and publish them in peer-reviewed renowned journals; Extend the gene-based breeding (GBB) system developed for enhanced and accelerated breeding for grain yield to other agronomic traits in cotton and corn; Promote the gene-based breeding (GBB) system in application in maize and cotton breeding programs nationwide and worldwide; and Continue the practice of GBB in cotton and corn.

Impacts
What was accomplished under these goals? During this period of the project, we have accomplished the followings under these goals: We invented a novel method as simple and rapid as finger counting for accurate prediction of the phenotypes of complex traits for gene-based breeding (GBB). This method has been tested and demonstrated in corn and cotton. We, for the first time, deciphered the molecular mechanisms underlying quantitative genetics by molecularly dissecting three quantitative traits from three diverse plant species using the genes controlling the traits. The three traits are corn grain yield, cotton fiber length and ginseng (Panax ginseng) ginsenoside biosynthesis. We, for the first time, demonstrated the utility and efficiency of GBB for enhanced and accelerated breeding using corn and cotton as the experimental species. We identified 181 ZmF1GY genes that enable accurate prediction of grain yield performance of offspring (F1 hybrids) from parents and tested their ability, utility and efficiency for GBB within an environment, across environments and across populations for enhanced and accelerated development of superior hybrids in corn. We, for the first time, discovered the variation of gene numbers within a bi-parental population and determined the genetics of gene number variation using corn as the experimental species. Gene interaction or epistasis is a universal phenomenon in all living organisms, but its variation and genetics largely remain unknown. We, for the first time, deciphered the genetics and variation of gene interaction using corn as the experimental species. We analyzed the genome sequences (7.0x) of the USDA corn genome-wide association study (GWAS) panel, identified 7,518,820 SNPs and selected 1,537,073 high-quality SNPs with a missing data rate of < 0.1, a minor allele frequency (MAF) of > 0.1 and base calling quality of Q > 30. We dissected the genetic diversity and population structure of the USDA GWAS panel and identified the loci of the genes controlling seven corn ear traits, including grain weight per plant, ear weight per plant, ear length, kernel row length, ear diameter, number of kernel rows, and cob diameter. We developed a population consisting of over 1,000 F1 hybrids from the USDA corn GWAS inbred lines and 51 recently-released PVP corn inbred lines. This F1 hybrid population will be used for three research purposes: i) To optimize the corn GBB that we have developed and make it applicable for enhanced and accelerated corn breeding nation-wide and world-wide; ii) to species-wide clone the genes controlling heterosis of >20 agronomic traits; and iii) comprehensively decipher the molecular mechanisms underlying the heterosis of these traits. We continued to decipher the molecular mechanisms of plant vernalization and flowering using chickpea as the experimental species and prepared manuscripts from the results of the studies for peer-reviewed publication. Molecularly and genetically dissected the genetic variation, diversity and population structure of the USDA rice mini-core collection selected from over 18,000 germplasm lines that USDA collected worldwide using high-density and high-quality SNPs. We prepared the manuscript from our cowpea QTL mapping project for publication in peer-reviewed journals.

Publications

• Type: Journal Articles Status: Published Year Published: 2020 Citation: Liu, Y.-H., Xu, Y., Zhang, M.P., Sze, S.-H., Smith, C.W., Xu, S., and Zhang, H.-B. (2020) Accurate prediction of fiber length using its contributing genes for gene-based breeding in cotton. Frontiers in Plant Science 11:583277.
• Type: Journal Articles Status: Published Year Published: 2020 Citation: Zhang, M.P., Liu, Y.-H., Xu, W., Smith, C.W., Murray, S.C., and Zhang, H.-B. (2020) Analysis of the genes controlling three quantitative traits in three diverse plant species reveals the molecular basis of quantitative traits. Scientific Reports 10:10074.
• Type: Journal Articles Status: Published Year Published: 2020 Citation: Angira, B., Zhang, Y., Scheuring, C.F., Zhang, Y.D., Masor, L., Coleman, R.J., Liu, Y.-H., Singh, B.B., Zhang, H.-B., Hays, D.B., and Zhang, M.P. (2020) Quantitative trait loci influencing days to flowering and plant height in cowpea, Vigna unguiculata (L.) Walp. Mol Genet Genomics 295:1187-1195.
• Type: Journal Articles Status: Accepted Year Published: 2020 Citation: Song, J.-M., Arif, M., Zi, Y., Sze, S.-H., Zhang, M., and Zhang, H.-B. (2020) Molecular and genetic dissection of the USDA rice mini-core collection using high-density SNP markers. Plant Science (accepted).
• Type: Book Chapters Status: Awaiting Publication Year Published: 2020 Citation: Zhang, M.P., Liu, Y.-H., and Zhang, H.-B. (2020) Molecular breeding for improving yield in maize: recent advances and future perspectives, Chapter 23 In M.A. Hossain (ed.), Molecular Breeding in Wheat, Maize and Sorghum: Strategies for Improving Abiotic Stress Tolerance and Yield. CABI, Wallingford, United Kingdom (in press).
• Type: Theses/Dissertations Status: Published Year Published: 2020 Citation: Bai, Gali (2020) Genome-wide association studies of ear traits in maize. M.S. Thesis, Texas A&M University, College Station, Texas.
• Type: Theses/Dissertations Status: Published Year Published: 2020 Citation: Dogan, Mehmet (2020) QTL analysis of end-use quality in a mapping population from two Texas wheat. M.S. Thesis, Texas A&M University, College Station, Texas.
• Type: Theses/Dissertations Status: Published Year Published: 2020 Citation: Bhangu, Drutdamm (2020) Proof of concept: novel gene based breeding vs field based breeding in improving fiber quality traits in cotton. Ph.D. dissertation, Texas A&M University, College Station, Texas.
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Zhang, M.P., Liu, Y.-H., Xu, W., Smith, C.W., Murray, S., and Zhang, H.-B. (2020) The genes controlling a quantitative trait are multiple-fold more likely to form a co-expression network in plants. International Plant & Animal Genome Conference XXVIII, W1065.
• Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Zhang, H.-B., Zhang, M.P., Liu, Y.-H., Qi, X., and Su, X. (2020) The DNA Jigsaw Puzzle Structure Model as the molecular basis of biology: variation and interaction of genome constituting elements. International Plant & Animal Genome Conference XXVIII, W550