Quantitative Trait Locus Mapping for Plant Height and Branch Number in CCRI70 Recombinant Inbred Line Population of Upland Cotton (Gossypium hirsutum).

Upland cotton accounts for a high percentage (95%) of the world's cotton production. Plant height (PH) and branch number (BN) are two important agronomic traits that have an impact on improving the level of cotton mechanical harvesting and cotton yield. In this research, a recombinant inbred line (RIL) population with 250 lines developed from the variety CCRI70 was used for constructing a high-density genetic map and identification of quantitative trait locus (QTL). The results showed that the map harbored 8298 single nucleotide polymorphism (SNP) markers, spanning a total distance of 4876.70 centimorgans (cMs). A total of 69 QTLs for PH (9 stable) and 63 for BN (11 stable) were identified and only one for PH was reported in previous studies. The QTLs for PH and BN harbored 495 and 446 genes, respectively. Combining the annotation information, expression patterns and previous studies of these genes, six genes could be considered as potential candidate genes for PH and BN. The results could be helpful for cotton researchers to better understand the genetic mechanism of PH and BN development, as well as provide valuable genetic resources for cotton breeders to manipulate cotton plant architecture to meet future demands.

Genetic linkage analysis of stable QTLs in Gossypium hirsutum RIL population revealed function of GhCesA4 in fiber development.

INTRODUCTION: Upland cotton is an important allotetrapolyploid crop providing natural fibers for textile industry. Under the present high-level breeding and production conditions, further simultaneous improvement of fiber quality and yield is facing unprecedented challenges due to their complex negative correlations. OBJECTIVES: The study was to adequately identify quantitative trait loci (QTLs) and dissect how they orchestrate the formation of fiber quality and yield. METHODS: A high-density genetic map (HDGM) based on an intraspecific recombinant inbred line (RIL) population consisting of 231 individuals was used to identify QTLs and QTL clusters of fiber quality and yield traits. The weighted gene correlation network analysis (WGCNA) package in R software was utilized to identify WGCNA network and hub genes related to fiber development. Gene functions were verified via virus-induced gene silencing (VIGS) and clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 strategies. RESULTS: An HDGM consisting of 8045 markers was constructed spanning 4943.01 cM of cotton genome. A total of 295 QTLs were identified based on multi-environmental phenotypes. Among 139 stable QTLs, including 35 newly identified ones, seventy five were of fiber quality and 64 yield traits. A total of 33 QTL clusters harboring 74 QTLs were identified. Eleven candidate hub genes were identified via WGCNA using genes in all stable QTLs and QTL clusters. The relative expression profiles of these hub genes revealed their correlations with fiber development. VIGS and CRISPR/Cas9 edition revealed that the hub gene cellulose synthase 4 (GhCesA4, GH_D07G2262) positively regulate fiber length and fiber strength formation and negatively lint percentage. CONCLUSION: Multiple analyses demonstrate that the hub genes harbored in the QTLs orchestrate the fiber development. The hub gene GhCesA4 has opposite pleiotropic effects in regulating trait formation of fiber quality and yield. The results facilitate understanding the genetic basis of negative correlation between cotton fiber quality and yield.

Hub Genes in Stable QTLs Orchestrate the Accumulation of Cottonseed Oil in Upland Cotton via Catalyzing Key Steps of Lipid-Related Pathways.

Upland cotton is the fifth-largest oil crop in the world, with an average supply of nearly 20% of vegetable oil production. Cottonseed oil is also an ideal alternative raw material to be efficiently converted into biodiesel. However, the improvement in kernel oil content (KOC) of cottonseed has not received sufficient attention from researchers for a long time, due to the fact that the main product of cotton planting is fiber. Previous studies have tagged QTLs and identified individual candidate genes that regulate KOC of cottonseed. The regulatory mechanism of oil metabolism and accumulation of cottonseed are still elusive. In the current study, two high-density genetic maps (HDGMs), which were constructed based on a recombinant inbred line (RIL) population consisting of 231 individuals, were used to identify KOC QTLs. A total of forty-three stable QTLs were detected via these two HDGM strategies. Bioinformatic analysis of all the genes harbored in the marker intervals of the stable QTLs revealed that a total of fifty-one genes were involved in the pathways related to lipid biosynthesis. Functional analysis via coexpression network and RNA-seq revealed that the hub genes in the co-expression network that also catalyze the key steps of fatty acid synthesis, lipid metabolism and oil body formation pathways (ACX4, LACS4, KCR1, and SQD1) could jointly orchestrate oil accumulation in cottonseed. This study will strengthen our understanding of oil metabolism and accumulation in cottonseed and contribute to KOC improvement in cottonseed in the future, enhancing the security and stability of worldwide food supply.

Genome-wide characterization of trichome birefringence-like genes provides insights into fiber yield improvement.

Cotton is an important fiber crop. The cotton fiber is an extremely long trichome that develops from the epidermis of an ovule. The trichome is a general and multi-function plant organ, and trichome birefringence-like (TBL) genes are related to trichome development. At the genome-wide scale, we identified TBLs in four cotton species, comprising two cultivated tetraploids (Gossypium hirsutum and G. barbadense) and two ancestral diploids (G. arboreum and G. raimondii). Phylogenetic analysis showed that the TBL genes clustered into six groups. We focused on GH_D02G1759 in group IV because it was located in a lint percentage-related quantitative trait locus. In addition, we used transcriptome profiling to characterize the role of TBLs in group IV in fiber development. The overexpression of GH_D02G1759 in Arabidopsis thaliana resulted in more trichomes on the stems, thereby confirming its function in fiber development. Moreover, the potential interaction network was constructed based on the co-expression network, and it was found that GH_D02G1759 may interact with several genes to regulate fiber development. These findings expand our knowledge of TBL family members and provide new insights for cotton molecular breeding.

Fine mapping and candidate gene analysis of qFL-A12-5: a fiber length-related QTL introgressed from Gossypium barbadense into Gossypium hirsutum.

KEY MESSAGE: The fiber length-related qFL-A12-5 identified in CSSLs introgressed from Gossypium barbadense into Gossypium hirsutum was fine-mapped to an 18.8 kb region on chromosome A12, leading to the identification of the GhTPR gene as a potential regulator of cotton fiber length. Fiber length is a key determinant of fiber quality in cotton, and it is a key target of artificial selection for breeding and domestication. Although many fiber length-related quantitative trait loci have been identified, there are few reports on their fine mapping or candidate gene validation, thus hampering efforts to understand the mechanistic basis of cotton fiber development. Our previous study identified the qFL-A12-5 associated with superior fiber quality on chromosome A12 in the chromosome segment substitution line (CSSL) MBI7747 (BC4F3:5). A single segment substitution line (CSSL-106) screened from BC6F2 was backcrossed to construct a larger segregation population with its recurrent parent CCRI45, thus enabling the fine mapping of 2852 BC7F2 individuals using denser simple sequence repeat markers to narrow the qFL-A12-5 to an 18.8 kb region of the genome, in which six annotated genes were identified in Gossypium hirsutum. Quantitative real-time PCR and comparative analyses led to the identification of GH_A12G2192 (GhTPR) encoding a tetratricopeptide repeat-like superfamily protein as a promising candidate gene for qFL-A12-5. A comparative analysis of the protein-coding regions of GhTPR among Hai1, MBI7747, and CCRI45 revealed two non-synonymous mutations. The overexpression of GhTPR resulted in longer roots in Arabidopsis, suggesting that GhTPR may regulate cotton fiber development. These results provide a foundation for future efforts to improve cotton fiber length.

Genome-wide artificial introgressions of Gossypium barbadense into G. hirsutum reveal superior loci for simultaneous improvement of cotton fiber quality and yield traits.

INTRODUCTION: The simultaneous improvement of fiber quality and yield for cotton is strongly limited by the narrow genetic backgrounds of Gossypium hirsutum (Gh) and the negative genetic correlations among traits. An effective way to overcome the bottlenecks is to introgress the favorable alleles of Gossypium barbadense (Gb) for fiber quality into Gh with high yield. OBJECTIVES: This study was to identify superior loci for the improvement of fiber quality and yield. METHODS: Two sets of chromosome segment substitution lines (CSSLs) were generated by crossing Hai1 (Gb, donor-parent) with cultivar CCRI36 (Gh) and CCRI45 (Gh) as genetic backgrounds, and cultivated in 6 and 8 environments, respectively. The kmer genotyping strategy was improved and applied to the population genetic analysis of 743 genomic sequencing data. A progeny segregating population was constructed to validate genetic effects of the candidate loci. RESULTS: A total of 68,912 and 83,352 genome-wide introgressed kmers were identified in the CCRI36 and CCRI45 populations, respectively. Over 90 % introgressions were homologous exchanges and about 21 % were reverse insertions. In total, 291 major introgressed segments were identified with stable genetic effects, of which 66(22.98 %), 64(21.99 %), 35(12.03 %), 31(10.65 %) and 18(6.19 %) were beneficial for the improvement of fiber length (FL), strength (FS), micronaire, lint-percentage (LP) and boll-weight, respectively. Thirty-nine introgression segments were detected with stable favorable additive effects for simultaneous improvement of 2 or more traits in Gh genetic background, including 6 could increase FL/FS and LP. The pyramiding effects of 3 pleiotropic segments (A07:C45Clu-081, D06:C45Clu-218, D02:C45Clu-193) were further validated in the segregating population. CONCLUSION: The combining of genome-wide introgressions and kmer genotyping strategy showed significant advantages in exploring genetic resources. Through the genome-wide comprehensive mining, a total of 11 clusters (segments) were discovered for the stable simultaneous improvement of FL/FS and LP, which should be paid more attention in the future.

Linkage and association analyses reveal that hub genes in energy-flow and lipid biosynthesis pathways form a cluster in upland cotton.

Upland cotton is an important allotetraploid crop that provides both natural fiber for the textile industry and edible vegetable oil for the food or feed industry. To better understand the genetic mechanism that regulates the biosynthesis of storage oil in cottonseed, we identified the genes harbored in the major quantitative trait loci/nucleotides (QTLs/QTNs) of kernel oil content (KOC) in cottonseed via both multiple linkage analyses and genome-wide association studies (GWAS). In 'CCRI70' RILs, six stable QTLs were simultaneously identified by linkage analysis of CHIP and SLAF-seq strategies. In '0-153' RILs, eight stable QTLs were detected by consensus linkage analysis integrating multiple strategies. In the natural panel, thirteen and eight loci were associated across multiple environments with two algorithms of GWAS. Within the confidence interval of a major common QTL on chromosome 3, six genes were identified as participating in the interaction network highly correlated with cottonseed KOC. Further observations of gene differential expression showed that four of the genes, LtnD, PGK, LPLAT1, and PAH2, formed hub genes and two of them, FER and RAV1, formed the key genes in the interaction network. Sequence variations in the coding regions of LtnD, FER, PGK, LPLAT1, and PAH2 genes may support their regulatory effects on oil accumulation in mature cottonseed. Taken together, clustering of the hub genes in the lipid biosynthesis interaction network provides new insights to understanding the mechanism of fatty acid biosynthesis and TAG assembly and to further genetic improvement projects for the KOC in cottonseeds.

Multi-environment Evaluations Across Ecological Regions Reveal That the Kernel Oil Content of Cottonseed Is Equally Determined by Genotype and Environment.

Cotton is the fifth-largest oil crop in the world. A high kernel oil content (KOC) and high stability are important cottonseed attributes for food security. In this study, the phenotype of KOC and the genotype-by-environment interaction factors were collectively dissected using 250 recombinant inbred lines, their parental cultivars sGK156 and 901-001, and CCRI70 across multi-environments. ANOVA and correlation analysis showed that both genotype and environment contributed significantly to KOC accumulation. Analyses of additive main effect multiplicative interaction and genotype-by-environment interaction biplot models presented the effects of genotype, environment, and genotype by environment on KOC performance and the stability of the experimental materials. Interaction network analysis revealed that meteorological and geographical factors explained 38% of the total KOC variance, with average daily rainfall contributing the largest positive impact and cumulative rainfall having the largest negative impact on KOC accumulation. This study provides insight into KOC accumulation and could direct selection strategies for improved KOC and field management of cottonseed in the future.

Identification and analysis of oil candidate genes reveals the molecular basis of cottonseed oil accumulation in Gossypium hirsutum L.

KEY MESSAGE: Based on the integration of QTL-mapping and regulatory network analyses, five high-confidence stable QTL regions, six candidate genes and two microRNAs that potentially affect the cottonseed oil content were discovered. Cottonseed oil is increasingly becoming a promising target for edible oil with its high content of unsaturated fatty acids. In this study, a recombinant inbred line (RIL) cotton population was constructed to detect quantitative trait loci (QTLs) for the cottonseed oil content. A total of 39 QTLs were detected across eight different environments, of which five QTLs were stable. Forty-three candidate genes potentially involved in carbon metabolism, fatty acid synthesis and triacylglycerol biosynthesis processes were further obtained in the stable QTL regions. Transcriptome analysis showed that nineteen of these candidate genes expressed during  the developing cottonseed ovules and may affect the cottonseed oil content. Besides, transcription factor (TF) and microRNA (miRNA) co-regulatory network analyses based on the nineteen candidate genes suggested that six genes, two core miRNAs (ghr-miR2949b and ghr-miR2949c), and one TF GhHSL1 were considered to be closely associated with the cottonseed oil content. Moreover, four vital genes were validated by quantitative real-time PCR (qRT-PCR). These results provide insights into the oil accumulation mechanism in developing cottonseed ovules through the construction of a detailed oil accumulation model.

Quantitative Trait Loci and Transcriptome Analysis Reveal Genetic Basis of Fiber Quality Traits in CCRI70 RIL Population of Gossypium hirsutum.

Upland cotton (Gossypium hirsutum) is widely planted around the world for its natural fiber, and producing high-quality fiber is essential for the textile industry. CCRI70 is a hybrid cotton plant harboring superior yield and fiber quality, whose recombinant inbred line (RIL) population was developed from two upland cotton varieties (sGK156 and 901-001) and were used here to investigate the source of high-quality related alleles. Based on the material of the whole population, a high-density genetic map was constructed using specific locus-amplified fragment sequencing (SLAF-seq). It contained 24,425 single nucleotide polymorphism (SNP) markers, spanning a distance of 4,850.47 centimorgans (cM) over 26 chromosomes with an average marker interval of 0.20 cM. In evaluating three fiber quality traits in nine environments to detect multiple environments stable quantitative trait loci (QTLs), we found 289 QTLs, of which 36 of them were stable QTLs and 18 were novel. Based on the transcriptome analysis for two parents and two RILs, 24,941 unique differentially expressed genes (DEGs) were identified, 473 of which were promising genes. For the fiber strength (FS) QTLs, 320 DEGs were identified, suggesting that pectin synthesis, phenylpropanoid biosynthesis, and plant hormone signaling pathways could influence FS, and several transcription factors may regulate fiber development, such as GAE6, C4H, OMT1, AFR18, EIN3, bZIP44, and GAI. Notably, the marker D13_56413025 in qFS-chr18-4 provides a potential basis for enhancing fiber quality of upland cotton via marker-assisted breeding and gene cloning of important fiber quality traits.

Disequilibrium evolution of the Fructose-1,6-bisphosphatase gene family leads to their functional biodiversity in Gossypium species.

BACKGROUND: Fructose-1,6-bisphosphatase (FBP) is a key enzyme in the plant sucrose synthesis pathway, in the Calvin cycle, and plays an important role in photosynthesis regulation in green plants. However, no systemic analysis of FBPs has been reported in Gossypium species. RESULTS: A total of 41 FBP genes from four Gossypium species were identified and analyzed. These FBP genes were sorted into two groups and seven subgroups. Results revealed that FBP family genes were under purifying selection pressure that rendered FBP family members as being conserved evolutionarily, and there was no tandem or fragmental DNA duplication in FBP family genes. Collinearity analysis revealed that a FBP gene was located in a translocated DNA fragment and the whole FBP gene family was under disequilibrium evolution that led to a faster evolutionary progress of the members in G. barbadense and in At subgenome than those in other Gossypium species and in the Dt subgenome, respectively, in this study. Through RNA-seq analyses and qRT-PCR verification, different FBP genes had diversified biological functions in cotton fiber development (two genes in 0 DPA and 1DPA ovules and four genes in 20-25 DPA fibers), in plant responses to Verticillium wilt onset (two genes) and to salt stress (eight genes). CONCLUSION: The FBP gene family displayed a disequilibrium evolution pattern in Gossypium species, which led to diversified functions affecting not only fiber development, but also responses to Verticillium wilt and salt stress. All of these findings provide the foundation for further study of the function of FBP genes in cotton fiber development and in environmental adaptability.

Examining two sets of introgression lines across multiple environments reveals background-independent and stably expressed quantitative trait loci of fiber quality in cotton.

KEY MESSAGE: Background-independent (BI) and stably expressed (SE) quantitative trait loci (QTLs) were identified using two sets of introgression lines across multiple environments. Genetic background more greatly affected fiber quality traits than environmental factors. Sixty-one SE-QTLs, including two BI-QTLs, were novel and 48 SE-QTLs, including seven BI-QTLs, were previously reported. Cotton fiber quality traits are controlled by QTLs and are susceptible to environmental influence. Fiber quality improvement is an essential goal in cotton breeding but is hindered by limited knowledge of the genetic basis of fiber quality traits. In this study, two sets of introgression lines of Gossypium hirsutum × G. barbadense were used to dissect the QTL stability of three fiber quality traits (fiber length, strength and micronaire) across environments using 551 simple sequence repeat markers selected from our high-density genetic map. A total of 76 and 120 QTLs were detected in the CCRI36 and CCRI45 backgrounds, respectively. Nine BI-QTLs were found, and 78 (41.71%) of the detected QTLs were reported previously. Thirty-nine and 79 QTLs were SE-QTLs in at least two environments in the CCRI36 and CCRI45 backgrounds, respectively. Forty-eight SE-QTLs, including seven BI-QTLs, were confirmed in previous reports, and 61 SE-QTLs, including two BI-QTLs, were considered novel. These results indicate that genetic background more strongly impacts on fiber quality traits than environmental factors. Twenty-three clusters with BI- and/or SE-QTLs were identified, 19 of which harbored favorable alleles from G. barbadense for two or three fiber quality traits. This study is the first report using two sets of introgression lines to identify fiber quality QTLs across environments in cotton, providing insights into the effect of genetic backgrounds and environments on the QTL expression of fiber quality and important information for the genetic basis underlying fiber quality traits toward QTL cloning and molecular breeding.

Genome-wide quantitative trait loci reveal the genetic basis of cotton fibre quality and yield-related traits in a Gossypium hirsutum recombinant inbred line population.

Cotton is widely cultivated globally because it provides natural fibre for the textile industry and human use. To identify quantitative trait loci (QTLs)/genes associated with fibre quality and yield, a recombinant inbred line (RIL) population was developed in upland cotton. A consensus map covering the whole genome was constructed with three types of markers (8295 markers, 5197.17 centimorgans (cM)). Six fibre yield and quality traits were evaluated in 17 environments, and 983 QTLs were identified, 198 of which were stable and mainly distributed on chromosomes 4, 6, 7, 13, 21 and 25. Thirty-seven QTL clusters were identified, in which 92.8% of paired traits with significant medium or high positive correlations had the same QTL additive effect directions, and all of the paired traits with significant medium or high negative correlations had opposite additive effect directions. In total, 1297 genes were discovered in the QTL clusters, 414 of which were expressed in two RNA-Seq data sets. Many genes were discovered, 23 of which were promising candidates. Six important QTL clusters that included both fibre quality and yield traits were identified with opposite additive effect directions, and those on chromosome 13 (qClu-chr13-2) could increase fibre quality but reduce yield; this result was validated in a natural population using three markers. These data could provide information about the genetic basis of cotton fibre quality and yield and help cotton breeders to improve fibre quality and yield simultaneously.

Dissecting the genetic basis of fiber quality and yield traits in interspecific backcross populations of Gossypium hirsutum × Gossypium barbadense.

Fiber quality and yield are important traits of cotton. Quantitative trait locus (QTL) mapping is a prerequisite for marker-assisted selection (MAS) in cotton breeding. To identify QTLs for fiber quality and yield traits, 4 backcross-generation populations (BC1F1, BC1S1, BC2F1, and BC3F0) were developed from an interspecific cross between CCRI36 (Gossypium hirsutum L.) and Hai1 (G. barbadense L.). A total of 153 QTLs for fiber quality and yield traits were identified based on data from the BC1F1, BC1S1, BC2F1 and BC3F0 populations in the field and from the BC2F1 population in an artificial disease nursery using a high-density genetic linkage map with 2292 marker loci covering 5115.16 centimorgans (cM) from the BC1F1 population. These QTLs were located on 24 chromosomes, and each could explain 4.98-19.80% of the observed phenotypic variations. Among the 153 QTLs, 30 were consistent with those identified previously. Specifically, 23 QTLs were stably detected in 2 or 3 environments or generations, 6 of which were consistent with those identified previously and the other 17 of which were stable and novel. Ten QTL clusters for different traits were found and 9 of them were novel, which explained the significant correlations among some phenotypic traits in the populations. The results including these stable or consensus QTLs provide valuable information for marker-assisted selection (MAS) in cotton breeding and will help better understand the genetic basis of fiber quality and yield traits, which can then be used in QTL cloning.

GWAS Analysis and QTL Identification of Fiber Quality Traits and Yield Components in Upland Cotton Using Enriched High-Density SNP Markers.

It is of great importance to identify quantitative trait loci (QTL) controlling fiber quality traits and yield components for future marker-assisted selection (MAS) and candidate gene function identifications. In this study, two kinds of traits in 231 F6:8 recombinant inbred lines (RILs), derived from an intraspecific cross between Xinluzao24, a cultivar with elite fiber quality, and Lumianyan28, a cultivar with wide adaptability and high yield potential, were measured in nine environments. This RIL population was genotyped by 122 SSR and 4729 SNP markers, which were also used to construct the genetic map. The map covered 2477.99 cM of hirsutum genome, with an average marker interval of 0.51 cM between adjacent markers. As a result, a total of 134 QTLs for fiber quality traits and 122 QTLs for yield components were detected, with 2.18-24.45 and 1.68-28.27% proportions of the phenotypic variance explained by each QTL, respectively. Among these QTLs, 57 were detected in at least two environments, named stable QTLs. A total of 209 and 139 quantitative trait nucleotides (QTNs) were associated with fiber quality traits and yield components by four multilocus genome-wide association studies methods, respectively. Among these QTNs, 74 were detected by at least two algorithms or in two environments. The candidate genes harbored by 57 stable QTLs were compared with the ones associated with QTN, and 35 common candidate genes were found. Among these common candidate genes, four were possibly "pleiotropic." This study provided important information for MAS and candidate gene functional studies.