Location: Crop Germplasm Research2017 Annual Report
The goal of this project is to develop genomic and genetic tools, materials, and information critically lacking for effectively exploiting cotton genetic variation in Gossypium germplasm characterization and cotton genetic improvement programs. Objective 1 reflects our commitment to continue the development of portable DNA markers (simple sequence repeat or SSR and single nucleotide polymorphism or SNP) and molecular descriptors (core sets of well-defined DNA markers) and make them available to the cotton research community. Objective 2 reflects our unique participation in the development of Upland cotton genome sequence and community database resources. A complete reference genome sequence of the Upland cotton genetic standard (G. hirsutum acc. TM-1) will unprecedentedly facilitate the process of gene mining in Gossypium germplasm for commercial improvement. A centralized public database (CottonGen) with user-friendly bioinformatic tools will make coordinated analysis and dissemination of research data and information more effective for the cotton research community. Work under Objective 3 will identify genes or novel alleles, genomic regions or quantitative trait loci (QTLs) for value-added priority traits, utilizing the genomic and genetic tools developed under the first two objectives. Superior cotton lines will be identified for developing breeding populations with novel variability for traits of interest. Collaborative work with key members/organizations of the cotton research community is necessary and will be done; all such work will be of mutual benefit and will be conducted so as to assure complementarity and lack of duplication. Specifically, during the next five years the project will focus on the following three objectives. Objective 1: Develop new genetic markers to augment current core sets of mapped SSR and SNP markers for high-throughput characterization of the genetic diversity within and among Gossypium germplasm accessions in the National Cotton Germplasm Collection. Sub-obj. 1A: Develop new SSR and SNP primers, and evaluate for polymorphism. Sub-obj. 1B: Identify and validate core cotton SSR and SNP markers. Objective 2: Collaborate with other public national and international researchers to sequence and analyze the tetraploid genome of G. hirsutum genetic standard genotype Texas Marker-1 (TM-1), and coordinate the activities of a public database to maintain and disseminate sequence and other genetic information to the research community. Sub-obj. 2A: Develop and analyze TM-1 genome sequence. Sub-obj. 2B: Coordinate the activities of CottonGen. Objective 3: Identify key genes and genomic regions of cotton that govern or are closely linked with priority traits, including fiber yield and quality, as well as biotic and abiotic stress tolerance. Sub-obj. 3A: Apply cotton genomic tools to identify and characterize QTLs or alleles from cotton genetic resources, maintained under the sister project, that govern key agronomic or fiber traits. Sub-obj. 3B: Apply the preceding information to identify superior parents for developing breeding populations with novel sources of variability for traits of interest.
New genetic markers will be created to augment current core sets of mapped SSR and SNP markers developed for high-throughput characterization of the genetic diversity within the National Cotton Germplasm Collection (objective 1). Genomic DNA will be isolated from species of G. hirsutum, G. barbadense, G. arboreum, and G. raimondii; and cotton sequence reads will be generated employing next–generation sequencing (NGS) technologies (Illumina GAIIx or HiSeq system). A high-throughput simplified one-enzyme system will be used to simultaneously discover and genotype SNP loci. The information will be used to develop A and D genome-specific SNP markers that will be made available to members of the research community via CottonGen (Sub-objective 1A). New polymorphic SSR and SNP markers will be mapped to the 26 chromosomes of the tetraploid cotton genome (sub-objective 1B). Genetic mapping of markers (SSR and SNP) will be conducted using the 186 RILs of the publicly available mapping population TM-1 x 3-79 RIL. The G. hirsutum genome will be sequenced in collaboration with national and international researchers (sub-objective 2A). Working closely with BGI and Cotton Research Institute (CRI), an integrated assembly strategy that includes large insert BAC libraries, sub-genome alignments, and chromosomal anchoring through the restriction site associated DNA (RAD)-seq analysis are being developed and tested. The TM-1 reference genome sequence will be made available to the broader plant research community via GenBank and CottonGen. The activities of the database CottonGen will be supported and coordinated through a cooperative agreement with Cotton Incorporated (sub-objective 2B). CottonGen is being built using the open-source Tripal database infrastructure to incorporate new datasets such as annotated transcriptome, genome sequence, marker-trait-locus and breeding data, as well as enhanced tools for easy querying and visualizing research data. Most technical aspects of building and maintaining CottonGen are handled by the database team at Washington State. The ARS group at College Station is responsible for determining what functionality, content, and data integration is desired of the database. Genomic tools will be used to identify QTLs or alleles governing key agronomic or fiber traits (sub-objective 3A). Validation of the growing numbers of QTLs reported in cotton will be accomplished by aligning genomic locations and comparing genetic effects of QTLS in order to make the QTLs useful. Once it is determined that specific chromosomal regions contain genes that make a significant contribution to the expression of a trait, fine-mapping of the most promising genomic regions will be used to identify polymorphisms in coding and/or regulatory regions. Diagnostic DNA markers that are associated with traits of interest will be used to screen the Collection, and lines possessing combinations of desirable QTLs will be used for developing breeding populations with novel sources of variability (sub-objective 3B).
The cotton germplasm known as TM-1 is accepted by the worldwide cotton research/breeding community as a standard for intensive study which will yield findings of direct relevance to cotton improvement. Project work in FY 2017 made significant progress in defining a number of genetically-controlled traits in TM-1; the work was done cooperatively with colleagues in a major Chinese Research Academy (Objective 2). Work was also done to determine the genetic sequence of a commonly grown cotton type (CRI-12); more than 3 million genetic markers known as single nucleotide polymorphism or SNP markers were developed (Objectives 1 and 2). Work advanced in FY 2017 on better defining the details of the genetic diversity of cotton, including development of what is known as genetic maps. Work was accomplished that better linked genetically the relationships of cotton to light (photoperiod) with important traits including fiber quality and tolerance to both biologically-based (e.g., pests, diseases) and environmental (e.g., drought) stresses (Objective 3). Project scientists also made significant progress in the area of defining genetic control of fiber development (Objective 3). The project continued support of the CottonGen database (managed by Cotton Incorporated) which serves the broad cotton community worldwide; data obtained from project work in FY 2017 were added to the database including more than 200,000 genetic tools known as molecular markers developed from analysis of six cotton species (Objective 2). In addition, about 750 molecular tools known as quantitative trait loci (QTL) were developed from cotton and added to CottonGen (Objective 2). During the year, CottonGen was accessed more than 100,000 times by thousands of cotton researchers, breeders, etc., from more than 100 nations (Objective 2). Project leadership and support of CottonGen, and project contributions to the database, are critical to the ongoing success of this resource which is much valued by the cotton research and breeding communities (Objective 2).
1. Genetic parameters associated with bacterial blight in cotton. Bacterial blight is a serious threat to cotton production in the U.S. and other cotton-producing regions of the world. Use of modern genetic tools to define the genetic parameters associated with the pathogen and to facilitate development of blight-resistant cotton types likely represent the most effective long-term strategy for managing the disease. ARS researchers at College Station, Texas, working in collaboration with colleagues at Texas A&M University and Cornell University, used genetic sequencing to define the genetic make-up of two strains of bacterial blight. The knowledge gained from the bacterial work was linked with knowledge previously developed on the genetic make-up of cotton. It was established that when cotton is infected by the bacteria, the two organisms compete for utilization of sugars which are necessary for survival and vigor of both. This accomplishment has identified critical interactions between the cotton host and the bacterial pathogen, and has identified a productive area for genetic exploitation/manipulation to develop new cotton types that will be resistant to bacterial blight and thus minimize the adverse effects of the disease on cotton production worldwide.
Kushanov, F.N., Pepper, A.E., Yu, J., Buriev, Z.T., Shermatov, S.E., Saha, S., Ulloa, M., Jenkins, J.N., Abdukarimov, A., Abdurakhmonov, I.Y. 2016. Development, genetic mapping and QTL association of cotton PHYA, PHYB, and HY5-specific CAPS and dCAPS markers. BioMed Central (BMC) Genetics. 17:141.
Cox, K.L., Meng, F., Wilkins, K.E., Li, F., Wang, P., Booher, N.J., Carpenter, S., Chen, L., Zheng, H., Gao, X., Zheng, Y., Fei, Z., Yu, J., Isakeit, T., Wheeler, T., Frommer, W.B., He, P., Bogdanove, A.J., Shan, L. 2017. TAL effector driven induction of a SWEET gene confers susceptibility to bacterial blight of cotton. Nature Communications. 8:15588.
Reddy, U., Nimmakayala, P., Abburi, V., Reddy, C., Saminathan, T., Percy, R.G., Yu, J., Frelichowski, J.E., Udall, J., Page, J., Zhang, D., Shehzad, T., Paterson, A. 2017. Genome-wide divergence, haplotype distribution and population demographic histories for Gossypium hirsutum and Gossypium barbadense as revealed by genome-anchored SNPs. Nature Scientific Reports. 7:41285.