Displaying 51 - 60 of 60

Construction of high-density SNP- and SSR-based genetic map and identification of candidate genes for fiber quality and yield traits using an introgressed recombinant inbred line population of Upland cotton

Furong, Wang
Yu, Chen
Chunyun, Zhang
Jingxia, Zhang
Zhangqiang, Song
Jun, Zhang
Fiber quality and yield are two main improved target traits in cotton breeding. QTL fine mapping and candidate genes identifying for these important agronomic traits would be beneficial to cotton breeding. In this present work, we constructed a high-density genetic map to identify QTLs associated with fiber quality and yield traits using an introgressed recombinant in-bred line (RIL) population consisting of 254 individuals. This map spanned a total distance of 3,426.57cM including 3556 SLAF-based SNP and 199 SSR markers. QTLs mapping were conducted with the phenotypic data collected from 7 environments. A total of 104 QTLs including 67 QTLs for fiber quality and 37 QTLs for yield traits were identified. Some of the QTLs were co-located in 19 QTL-clusters and distributed on 12 chromosomes. Twenty-four of the QTLs were detected in three or more environments and determined as stable QTLs. Further, by combining DNA re-sequence, RNA-seq and qPCR analysis, we identified six candidate genes for stable QTLs, including Gh_A03G1147 (GhPEL5), Gh_D07G1598 (GhCSLC6) and Gh_D13G1921 (GhTBL5) for fiber-length QTLs, Gh_D03G0919 (GhCOBL4), Gh_D09G1659 (GhMYB4) and Gh_D09G1690 (GhMYB85) for lint-percentage QTL. Our results provide comprehensive insight for understanding the genetic base of formation of fiber quality and yield traits and would be helpful for MAS-assisted cotton genetic improvement.

Cotton genomics is providing rational ways for gene finding and genetic improvement

Xianlong, Zhang
Cotton provides natural fiber resources for spinning, and is used by human beings for thousands of years. Traditional breeding methods contributed so much to cotton improvement, but breeders are not able to develop new variety with expectation. Cotton genomics, although complex as a tetraploid, developed so fast recently. The draft genomes for A, D, AD1 and AD2 are published in the recent years, which promoted GWAS analysis of cotton economic traits, with lots of genes identified. The evolution of genomes is described, many structural variations and gene mutations were identified, which will be very helpful for investigating interaction between genes and map-based cloning. We predict more and more genes will be cloned later on, which will be useful for molecular design breeding. Recently the 3D genome of cotton was studied, inter-subgenomic chromatin interactions has revealed the spatial proximity of homoeologous genes, possibly associated with their coordinated expression. The 3D genome study provides a new way in understanding genome structure and transcriptional regulation. The previous publications are surely advanced the knowledge of cotton genomics, but a reference-scale genome should be work out for more exactly designing a variety or molecular assisted breeding.

Development of Reniform Nematode Resistance in Cotton through Molecular Breeding

Buyyarapu, Ramesh
McPherson, Mustafa
Mahill, Joel
Parliament, Kelly
Pellow, John
Blackburn, Donald
The reniform nematode (RN), Rotylenchulus reniformis Linford & Oliveira, has emerged as one of the major pests of cotton contributing to severe yield losses in United States. Discontinuation of nematicides such as TEMIK® has necessitated development of varieties with host RN resistance. Although RN resistance had been previously identified in diploid K-genome species, Gossypium longicalyx, and in Inca GB713, a tetraploid wild Mexican race belonging to G. barbadense species; the lack of commercial cotton cultivars with natural host resistance to reniform nematode is currently limiting cotton yield gain. Previously, QTL regions associated with RN resistance from the resistant sources were identified using Simple Sequence Repeat (SSR) markers. More recently, single nucleotide polymorphisms (SNPs) are the marker of choice for high throughput, automatable screening of large populations. Here we report SNP markers associated with RN resistance from the Inca GB713 source. An interspecific mapping population was constructed by crossing an upland RN susceptible genotype with Inca GB713 and was used for phenotyping, genotyping and trait mapping purposes. Two QTLs, a major QTL on chromosome 21 and a minor QTL on chromosome 18 were identified and had explained up to 37% of total phenotypic variation in RN resistance. Leveraging Marker Assisted Selection (MAS) of these closely linked SNP markers and evaluation for linkage drag, the development of improved commercial cultivars with RN resistance was expedited through molecular breeding.

Genetic basis of the agronomic traits of white and brown fiber upland cotton in China revealed by a genome-wide association study

Chong, Huang
Tianwang, Wen
Mi, Wu
Xianlong, Zhang
Zhongxu, Lin
Gossypium hirsutum L. represents the largest source of textile fibre, and China is one of the largest cotton producing and consuming countries in the world. To investigate the genetic architecture of the agronomic traits of white fiber upland cotton in China, a diverse and nation-wide population containing 503 G. hirsutum accessions was collected for GWAS on 16 agronomic traits. The accessions were planted in four places from 2012 to 2013 for phenotyping. The CottonSNP63K array and a published high-density map based on this array were used for genotyping. A total of 324 SNPs and 160 candidate quantitative trait loci (QTL) regions were identified as significantly associated with the 16 agronomic traits. A network was established for multi-effects in QTLs and inter-associations among traits. Thirty-eight associated regions had pleiotropic effects controlling more than one trait. To understand the genetic basis of brown fibre cotton, an F2 population was constructed to genetically map the dark brown fiber gene in an introgression line with mutant dark brown fiber derived from an interspecific hybridization between Gossypium hirsutum cv. Handan208 and G. barbadense Pima90-53. On the other hand, in order to comprehensively reveal the genetic basis of brown fiber, 100 accessions with light to dark brown fibers were collected, together with 109 re-sequenced white fiber accessions randomly selected from Upland cotton, to construct an association mapping panel. The 100 brown fiber accessions were genotyped by re-sequencing, and phenotyped with 21 of the 109 white fiber accessions in three environments to map quantitative trait loci (QTL) related to fiber color, yield and quality traits by genome-wide association study (GWAS). The brown fibre region, Lc1, was fine-mapped and dissected it into two loci, qBF-A07-1 and qBF-A07-2. The qBF-A07-1 locus mediates the initiation of brown fibre generation, whereas the shade of the brown fibre is affected by the interaction between qBF-A07-1 and qBF-A07-2. Haploid analysis of the signals significantly associated with these two loci showed that most tetraploid modern brown cotton accessions exhibit the introgression signature of G. barbadense. Ten quantitative trait loci (QTLs) for fibre yield and 19 QTLs were identified for fibre quality and found that qBF-A07-2 negatively affects fibre yield and quality through an epistatic interaction with qBF-A07-1. This study sheds light on the genetics of fibre colour and lint-related traits in brown fibre cotton, which will guide the elite cultivars breeding of brown fibre cotton.

Moving beyond a single reference genome: GenoMagic, a novel solution to describe and manage genomic variation

Barad, Omer
Baruch, Kobi
Chomet, Paul
Shem-Tov, Doron
Next Generation sequencing technologies have opened the door to multiple genome analyses and an increased understanding of the variations present in populations. To date, most of the germplasm analyses have relied on the comparison of sequence reads to one reference genome assembly, limiting our understanding of genomic variation. NRGene has developed novel analytics and approaches to efficiently denovo-assemble genomes and to describe the relevant variation across germplasm using a pan-genome approach. We are promoting a pangenome consortium, led by Dr. Tianzhen Zhang, that will enable full genome comparative analyses for tetraploid cotton germplasm. The longer-term goal is for the pan-genome to serve as a reference to fully catalog the diversity in Gossypium through sequence-based haplotypes. This talk will focus on the need and advantage of a pan-genome and sequence-based haplotypes for breeding and gene discovery applications.

Multivariate analysis of the cotton seed ionome reveals integrated genetic signatures of abiotic stress response

Pauli, Duke
Ziegler, Greg
Ren, Min
Jenks, Matthew A.
Hunsaker, Douglas J.
Zhang, Min
Baxter, Ivan
Gore, Michael A.
Heat and drought represent two of the most common abiotic stresses that plants encounter in modern agricultural production systems and can cause significant economic losses. As climate change continues to increase the frequency and severity of these conditions, the development of stress-resilient cultivars becomes pivotal to sustaining crop yields. To meet these challenges, a better understanding of the genetic control of physiological responses to these environmental conditions is needed. In light of this, we evaluated an upland cotton (Gossypium hirsutum L.) recombinant inbred line (RIL) mapping population under water-limited and well-watered conditions in a hot, arid environment across three years. Ionomic profiling, the rapid quantification of elemental concentrations in a given sample, was used to phenotype seed subsamples from the population. Additionally, soil samples taken from throughout the entire field site were also assayed to better model the soil elemental heterogeneity and account for this variability in subsequent analyses. The elements profiled in seeds exhibited moderate to high heritabilities as well as strong phenotypic and genotypic correlations between elements. Both types of correlations maintained their strength and direction despite the imposed irrigation regimes. Quantitative trait loci (QTL) mapping results from a Bayesian classification method identified multiple genomic regions where QTL for individual elements colocalized, suggesting that genetic control of the ionome is highly interrelated. To more fully exploit this shared genetic architecture, multivariate QTL mapping was implemented among groups of biochemically related elements. This analysis revealed both additional as well as pleiotropic QTL responsible for the coordinated control of phenotypic variation for elemental accumulation in seeds. To further leverage these data to gain insight into the physiological status of the plants, machine learning algorithms that utilized only ionomic data were used to predict the irrigation under which RIL lines were grown. The best performing method, which was support vector machines, produced a prediction accuracy of 97.7% providing empirical evidence that ionome can capture the physiological status of the plant. Taken together, these results demonstrate the extent to which the seed ionome is genetically interrelated and predictive of plant physiological response to adverse environmental conditions.

Prospects for genomic selection in cotton breeding: an Australian case study

Gapare, Washington
Liu, Shiming
Conaty, Warren
Zhu, Qian-Hao
Gillespie, Vanessa
Llewellyn, Danny
Stiller, Warwick
Wilson, Iain
Genomic selection (GS) has successfully been used in plant breeding to improve selection effi¬ciency and reduce breeding time and cost. We are currently investigating the use of GS to improve breeding for agronomic traits in CSIRO’s cotton breeding program. A training population of 923 upland cotton accessions phenotyped for fibre length and strength was genotyped with a CottonSNP63K array and 18,123 single nucleotide markers were polymorphic. We used these data to investigate the potential for GS as a breeding tool in cotton to predict fibre length and strength traits. Preliminary results and challenges will be discussed.

Research Progress of Short-season Cotton in China

Fan, Shuli
Ma, Qifeng
Wang, Long
Short-season cotton varieties were cultivated to increase cropping index, and they also were introduced to the short frost-free areas for expanding the cotton planting area in China. The report described 1) the selection basis of early maturity traits of cotton varieties, 2) genetic characteristics of early maturity traits in cotton varieties, 3) early maturity related gene cloning and 4) early maturity cotton breeding. In terms of selection of early maturity traits, seedling period, boll period, node of first fruiting branch, plant height and yield percentage before frost were mainly controlled by genetic inheritance, which could be used as an indicator of early maturity. In the aspects of early maturity genetic traits, the heritability of flowering stage was controlled by both additive and dominant genes. The genetic analysis of the Upland cotton showed that there were significant additive effects at flowering period and boll opening period. Node of first fruiting branch, plant height and mature period showed additive and dominant effects significantly, but dominated by the dominant effect. The genetic map was constructed using early maturity cotton varieties, which mainly focused on seedling period, bud period, flowering period, flower and boll period, growth period, yield percentage before frost, the first fruit branch node, node of first fruiting branch, boll opening period. At the same time, cotton flowering related genes such as FPF1 (FLOWERING PROMOTING FACTOR 1), SOC1 (SUPPRESSOR OF OVEREXPRESSION OF CO 1), CO (CONSTANS), LFY (LEAFY) and AP1 (APETALA1) were cloned and their function needs to be further verified. Hybridization breeding was mainly applied in early maturity cotton breeding. The parents should be complementary, one of the parents is an extremely early mature type or the two parents are more mature materials which often appear of the super-separation in the maturity. The selection of parents should have high general combining abilities. The application of short-season cotton was summarized in China's Yellow River cotton area, the Yangtze River cotton area and the northwest inland cotton area, and the main problems and countermeasures were overviewed briefly,, which provided a reference for short-season cotton breeding in research and utilization.

Technology is driving the re-integration of plant and animal breeding to their mutual benefit

Hickey, J. M.
Gaynor, R.C.
Gottardo, P.
Jenko, J.
Gorjanc, G.
The world population is predicted to reach 9 billion within the next 35 years, requiring a 70-100% increase in food production relative to current levels. Breeding of livestock and crops is one of the key routes through which this increased production, efficiency and sustainability can be delivered. Although plant and animal breeding have similar objectives and have similar roots, the two fields, and their respective concepts and technology, have diverged over the past 100 or so years. The advent of genomic selection and other technology such as genome editing and surrogate sires is driving a reconnection between plant and animal breeding. Genomic selection, with its roots in animal breeding, has transformed that field and is well on the way to doing so in plant breeding. If genome editing is to be successful in animal breeding perhaps deeper physiological understanding, as is common in plant breeding, will need to be brought to the fore explicitly or implicitly. The statistical models, experimental designs, genotyping and phenotyping technologies, and many other underpinning tools, methods, and technologies can be common to both fields in the future and thus create the opportunity for synergy at the research, training and implementation stage. Finally, surrogate sire technology coupled with genomic selection may mean that an idealised blueprint for a modern animal or plant breeding program could be almost identical and will be inspired by the best of what classical and modern animal and plant breeding offer. Keywords: animal breeding, plant breeding, breeding program design, genomic selection, genome editing, surrogate sire

Testing and validating alleles (or QTLs) conferring resistance to reniform nematode, Rotylenchulus reniformis, from M713 Ren4 in a different genetic background.

Koebernick, Jenny
Patel, Jinesh
Kaplan, Gulsah
Auburn University’s cotton breeding program was initiated on the industry need for reniform nematode, Rotylenchulus reniformis, resistance. The program participated in a series of joint efforts to identify and breed for potential resistant germplasm. In 2013, M713 Ren 1-5 were screened and a diallel was initiated to combine potential resistance with good yield. One particular cross, M713 Ren4 x UA 103, was advanced in a single boll descent by hand-selfing each generation to the F5. In 2017, a field trial was performed in Belle Mina, Al, to evaluate six promising F5 lines, the parents and two commercial checks under reniform nematode pressure. All lines had significantly higher yield than the commercial checks, while four lines were higher than the M713 parent. It is postulated that M713 Ren4 contains introgression segments of QTLs on chromosome 21 (Renbarb1 and Renbarb2) from GB713 that provides resistance to reniform. In recent studies, Renbarb1 and Renbarb2 are resolve in one locus (Renbarb2) and marker BNL3729 strongly associated with the resistant phenotype. To validate this, progenies from these six lines will be genotyped by using five markers spanning around QTL (Renbarb2) along with BNL3729.