Tajikistan represents a core region of the biodiversity hotspot in Central Asian mountains and has exceptional vascular plant diversity. However, the species diversity of the country faces urgent conservation challenges. There has been a lack of a comprehensive and multidimensional assessment to inform strategic conservation planning. Therefore, this study integrated 4 key biodiversity indices including species richness (SR), phylogenetic diversity (PD), threatened species richness (TSR), and endemic species richness (ESR) to map species diversity distribution patterns, identify conservation gaps, and elucidate their effects of climatic factors. This study revealed that species diversity shows a clear trend of decreasing from the western region to the eastern region of Tajikistan. The central–western mountains (specifically the Gissar-Darvasian and Zeravshanian regions) emerge as irreplaceable biodiversity hotspots. However, we found a severe spatial mismatch between these priority areas and the existing protected areas (PAs). Protection coverage for all hotspots was alarmingly low, ranging from 31.00% to 38.00%. Consequently, a critical 64.80% of integrated priority areas fall outside of the current PAs, representing a major conservation gap. This study identified precipitation seasonality and isothermality as the principal drivers, collectively explaining over 50.00% of the diversity variation and suggesting high vulnerability to hydrological shifts. Furthermore, we detected significant geographic sampling bias in the public biodiversity databases, with the most critical hotspot being systematically under-sampled. This study provides a robust scientific basis for conservation action, highlighting the urgent need to strategically expand PAs in the under-protected southwestern region and to mitigate critical sampling gaps through targeted data digitization and field surveys. These measures are indispensable for securing Tajikistan’s unique biodiversity and achieving the Kunming-Montreal Global Biodiversity Framework Target 3 (“30×30 Protection”).

The increasing incidence of fungal phytopathogens poses a significant challenge to agricultural sustainability, necessitating the development of environmental alternatives to synthetic fungicides and mitigating their ecological impact. This study explores the efficiency of Nocardiopsis alba B57 to produce secondary metabolites with antifungal and plant growth-promoting properties. Untargeted metabolomics using ultra-high-performance liquid chromatography (UPLC-MS/MS) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses identified key metabolites (e.g., carbapenem, menaquinone, and fumiquinazoline) in the co-culture environment with fungal pathogens. Additionally, principal component analysis and OPLS-DA differentiated monoculture and co-culture metabolic profiles, revealed carbapenem biosynthesis as a highly enriched pathway. The comprehensive metabolomics data and the statistical analysis of the identified metabolites confirmed that co-culturing of B57 and fungal strains showed upregulated metabolites (e.g., carbapenem and menaquinone). However, other metabolites (e.g., mupirocin) were downregulated and significantly suppressed. These changes in metabolic activity reflect the organism’s adaptive and competitive responses during the co-culture conditions with fungal pathogens and influence plant hormone signaling (e.g., auxin and cytokinin), promoting plant growth and disease resistance. These findings underscore B57’s adaptive biosynthetic response to co-culture conditions, supporting its use as a sustainable biocontrol agent and boosting crop productivity.

Understanding genotype-environment interactions and trait relationships is pivotal for guiding breeding efforts aimed at stabilizing cotton varieties across diverse environments while boosting yield and fiber quality. The study aimed to assess genotypic variability and stability in 10 agronomic and fiber quality traits across four environments (Anyang in 2020 and 2021 and Weixian in 2020 and 2021) for three parental lines (ZR014121, CCRI60, and EZ60) and their corresponding 498 recombinant inbred lines (RILs) populations. The results indicated that the analysis of variance showed significant genotype and genotype-by-environment effects for all measured traits. Analysis of correlation revealed highly significant positive correlations between seed cotton yield and each of boll weight (r = 0.95), lint yield (r = 0.90), and between boll weight and lint yield (r = 0.90), while highly significant negative correlations were noticed between fiber maturity and fiber elongation (r = −0.52) and between fiber length and lint percentage (r = −0.38). Furthermore, the weighted average of absolute scores (WAASB) was calculated for each trait, revealing moderate to high stability for some yield traits and fiber quality parameters. Also, the multi-trait stability index (MTSI) applied to these RILs populations identified G13 as the most stable line (MTSI = 5.5) and S23 as the least stable (MTSI = 12.1). Selecting 25 RILs with the lowest MTSI values (5.5–6.47) revealed elite stable lines with favorable trait values, providing a valuable genetic resource for developing high-performance cotton cultivars in diverse environments.

Fiber length (FL) is one of the primary factors used to determine the quality of cotton fibers, serving as a primary target for the domestication and breeding of cotton plants through artificial selection. While many studies have identified quantitative trait loci (QTLs) associated with fiber length, few efforts have explored the mechanisms underlying the development of cotton fibers through fine mapping or the validation of related candidate genes. In a previous study, qFL-A12 - 2 was identified as a QTL on chromosome A12 that was associated with higher levels of fiber quality in the MBI7747 (BC 4 F 3:5 ) chromosome segment substitution line (CSSL). For fine mapping the QTL, a single-segment substitution line (CSSL-023) screened from BC 5 F 2 was backcrossed with the recurrent parental CCRI45 line to establish a large segregation population. Subsequently, 2092 individual BC 6 F 2 specimens were utilized in a fine-mapping effort employing highly dense simple sequence markers, which narrowed qFLA12 - 2 to a 0.65 Mb genomic region in Gossypium hirsutum containing 12 annotated genes. The most promising candidate gene within this interval was identified through qRT-PCR and complete coding sequence comparative analyses as GhALMT12_A12 , which encodes an aluminum-activated malate transporter. Two non-synonymous mutations were identified when the protein-coding portions of GhALMT12_A12 were compared among the Hai1, MBI7747, and CCRI45 varieties. Verification of GhALMT12_A12 silencing by VIGS in cotton revealed that the FL of silenced plants was significantly shorter than that of the control plants. When overexpressed, GhALMT12_A12 significantly enhanced Arabidopsis resistance to salt stress and drought conditions through altering ion transport. The outcomes underscore the notable function of GhALMT12_A12 in developing cotton fibers, providing a fundamental basis for scholars aiming at augmenting the length of cotton fibers.

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.

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 con-structed 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 signif-icant 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. (c) 2023 The Authors. Published by Elsevier B.V. on behalf of Cairo University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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.

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.

Fiber quality traits, especially fiber strength, length, and micronaire (FS, FL, and FM), have been recognized as critical fiber attributes in the textile industry, while the lint percentage (LP) was an important indicator to evaluate the cotton lint yield. So far, the genetic mechanism behind the formation of these traits is still unclear. Quantitative trait loci (QTL) identification and candidate gene validation provide an effective methodology to uncover the genetic and molecular basis of FL, FS, FM, and LP. A previous study identified three important QTL/QTL cluster loci, harboring at least one of the above traits on chromosomes A01, A07, and D12 via a recombinant inbred line (RIL) population derived from a cross of Lumianyan28 (L28) × Xinluzao24 (X24). A secondary segregating population (F2) was developed from a cross between L28 and an RIL, RIL40 (L28 × RIL40). Based on the population, genetic linkage maps of the previous QTL cluster intervals on A01 (6.70–10.15 Mb), A07 (85.48–93.43 Mb), and D12 (0.40–1.43 Mb) were constructed, which span 12.25, 15.90, and 5.56 cM, with 2, 14, and 4 simple sequence repeat (SSR) and insertion/deletion (Indel) markers, respectively. QTLs of FL, FS, FM, and LP on these three intervals were verified by composite interval mapping (CIM) using WinQTL Cartographer 2.5 software via phenotyping of F2 and its derived F2:3 populations. The results validated the previous primary QTL identification of FL, FS, FM, and LP. Analysis of the RNA-seq data of the developing fibers of L28 and RIL40 at 10, 20, and 30 days post anthesis (DPA) identified seven differentially expressed genes (DEGs) as potential candidate genes. qRT-PCR verified that five of them were consistent with the RNA-seq result. These genes may be involved in regulating fiber development, leading to the formation of FL, FS, FM, and LP. This study provides an experimental foundation for further exploration of these functional genes to dissect the genetic mechanism of cotton 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.

[Objective] The aim of this study is to explore the elite gene/quantitative trait loci（QTL） resources of yield and fiber quality, and to provide useful information for developing cotton varieties with high yield and excellent fiber quality.[Methods] A superior chromosome segment substitution line MBI9626, and a high-yield and wide-adaptability upland cotton CCRI 36 were selected to construct a secondary segregation population BC 6 F 2 which contained 152 individuals. And 109 selected simple sequence repeat（SSR） markers were used to genotyping parents and the population, and QTL mapping for yield and fiber quality traits was conducted based on genotype data and phenotype data. [Results] Genotyping resutts showed MBI9626 recovered to 94.8% of the genetic background of CCRI 36. A total of 28 QTLs related to yield and fiber quality traits were detected in BC 6 F 2 , BC 6 F 2:3 , and BC 6 F 2:4 populations, which were distributed on 6 chromosomes. Among them, there are 16 QTLs related to yield, accounting for 2.25%-6.14% of the phenotypic variation, including 6 stable QTLs; 12 QTLs related to quality traits, accounting for 2.49%-12.30% of the phenotypic variation, including 2 stable QTLs. There were 19 newly discovered QTLs, including 5 stable QTLs. And 233 genes were identified in a QTL cluster with 6 QTLs on D3 chromosome. Based on gene ontology（GO） cluster and Kyoto encyclopedia of genes and genomes（KEGG）analysis and TM-1 transcriptome data, 6 candidate genes were screened to be involved in fiber development, namely GH＿D03G1428、GH＿D03G1466, GH＿D03G1518, GH＿D03G1570, GH＿D03G1586, and GH＿D03G1640. [Conclusion] Twentyeight stable QTLs related to cotton yield and fiber quality were identified and would lay a solid foundation for fine mapping and cloning of candidates genes and marker assisted selection.

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.

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.

利用陆海渐渗系群体对纤维强度主效QTLs进行单标记检测及聚合效应检测.前期,以陆海渐渗系'中棉所36'(CCRI36)×'海1'(Hail)BC5F3:5中的一个稳定优质系MBI9915为母本,轮回亲本'中棉所36'为父本构建次级分离群体BC6F2和BC6F2∶3,定位出了纤维品质性状相关的QTL.在此基础上,构建渐渗系衍生群体BC9F2和BC9F2∶3,利用与已经定位到的5个纤维强度QTLs紧密连锁的SSR标记在BC9F2、BC9F2∶3群体中进行分子标记辅助选择效果检测及不同QTL间聚合效应检测.结果表明qFS-A05-1、qFS-D10-1、qFS-D10-2和qFS-D10-4等4个QTLs在两世代遗传效应显著,单标记辅助选择效果明显.qFS-A05-1×qFS-D10-2、qFS-A05-1×qFS-D10-4、qFS-D10-1×qFS-D10-2、qFS-D10-1×qFS-D10-4 和 qFS-D10-2×qFS-D10-4 等五组QTLs位点的聚合呈显著累加效应;并筛选出纤维品质优良的单双片段优良单株.本研究进一步明确了纤维强度QTL的聚合能显著提高纤维强度,为培育高产优质棉花新品种的高效精准育种提供了科学依据.

为了进一步揭示高产优质棉花品种的纤维产量和品质性状之间的遗传关系,筛选高产优质的陆地棉新品系,以纤维品质优异的中棉所127与高产的中棉所60杂交并自交构建的F2、F2:3分离群体和重组自交系F6:8群体为材料,运用简单相关分析、多元逐步回归分析和通径分析对纤维产量与品质性状进行分析评价.简单相关分析结果表明,纤维上半部平均长度在3个群体中均与衣分呈极显著负相关,断裂比强度在2个低世代群体中均与衣分呈极显著负相关,纤维上半部平均长度在3个群体中均和断裂比强度呈极显著正相关,铃重与其他各性状在3个群体中的相关性差异较大.在多元逐步回归分析中,F2和F2:3群体断裂比强度均与衣分呈负相关关系.通径分析结果表明,在F2群体中,断裂比强度对衣分的直接负效应最大;F2:3群体中纤维上半部平均长度、断裂比强度和马克隆值对衣分的直接效应均为负,其中纤维上半部平均长度的直接效应最大.综合简单相关分析、多元逐步回归分析和通径分析的结果认为,主要的品质性状纤维上半部平均长度和断裂比强度与产量性状衣分存在负相关关系.进一步通过对重组自交系F6:8群体和F2、F2:3分离群体的表型数据分析,筛选出8个从低世代分离群体到重组自交系群体均表现稳定,衣分较高,纤维上半部平均长度在29.10 mm以上、断裂比强度在29.80 cN·tex-1以上的优质品系,为高产优质棉花新品种的选育及基础研究提供了资源材料.

中棉所135在四川省植棉区生育期132 d,株型松散,呈塔形,铃长卵圆形;抗枯萎病、耐黄萎病;抗棉铃虫、高抗红铃虫.2018―2019年四川省棉花品种区域试验中,该品种平均籽棉和皮棉产量分别为3797.88 kg·hm-2和1541.19 kg·hm-2.介绍了中棉所135的选育过程、特征特性、纤维品质及其栽培技术要点.

Verticillium wilt is the second serious vascular wilt caused by the phytopathogenic fungus Verticillium dahliae Kleb. It has distributed worldwide, causing serious yield losses and fiber quality reduction in cotton production. The pathogen has developed different mechanisms like the production of cell wall degrading enzymes, activation of virulence genes and protein effectors to succeed in its infection. Cotton plant has also evolved multiple mechanisms in response to the fungus infection, including a strong production of lignin and callose deposition to strengthen the cell wall, burst of reactive oxygen species, accumulation of defene hormones, expression of defense-related genes, and target-directed strategies like cross-kingdom RNAi for specific virulent gene silencing. This review summarizes the recent progress made over the past two decades in understanding the interactions between cotton plant and the pathogen Verticillium dahliae during the infection process. The review also discusses the achievements in the control practices of cotton verticillium wilt in recent years, including cultivation practices, biological control, and molecular breeding strategies. These studies reveal that effective management strategies are needed to control the disease, while cultural practices and biological control approaches show promising results in the future. Furthermore, the biological control approaches developed in recent years, including antagonistic fungi, endophytic bacteria, and host induced gene silencing strategies provide efficient choices for integrated disease management.

在湖南省植棉区,中棉所131夏播生育期为103.9 d,植株塔形,叶片中等大小,花药白色,吐絮畅,对脱叶剂敏感,耐枯萎病,耐黄萎病,抗棉铃虫.在2019―2020年湖南省机采棉区域试验中,该品种平均籽棉和皮棉产量分别为3814.43 kg·hm-2和1501.38 kg·hm-2,纤维品质为Ⅱ型.本文介绍了中棉所131的选育过程及其特征特性、产量、纤维品质表现和栽培要点.

介绍中棉所127的选育过程及其特征特性、产量、纤维品质以及栽培要点.

Background Pectin is a key substance involved in cell wall development, and the galacturonosyltransferases (GAUTs) gene family is a critical participant in the pectin synthesis pathway. Systematic and comprehensive research on GAUTs has not been performed in cotton. Analysis of the evolution and expression patterns of the GAUT gene family in different cotton species is needed to increase knowledge of the function of pectin in cotton fiber development. Results In this study, we have identified 131 GAUT genes in the genomes of four Gossypium species ( G. raimondii , G. barbadense , G. hirsutum , and G. arboreum ), and classified them as GAUT-A , GAUT-B and GAUT-C , which coding probable galacturonosyltransferases. Among them, the GAUT genes encode proteins GAUT1 to GAUT15. All GAUT proteins except for GAUT7 contain a conserved glycosyl transferase family 8 domain (H-DN-A-SVV-S-V-H-T-F). The conserved sequence of GAUT7 is PLN (phospholamban) 02769 domain. According to cis -elemet analysis, GAUT genes transcript levels may be regulated by hormones such as JA, GA, SA, ABA, Me-JA, and IAA. The evolution and transcription patterns of the GAUT gene family in different cotton species and the transcript levels in upland cotton lines with different fiber strength were analyzed. Peak transcript level of GhGAUT genes have been observed before 15 DPA. In the six materials with high fiber strength, the transcription of GhGAUT genes were concentrated from 10 to 15 DPA; while the highest transcript levels in low fiber strength materials were detected between 5 and 10 DPA. These results lays the foundation for future research on gene function during cotton fiber development. Conclusions The GAUT gene family may affect cotton fiber development, including fiber elongation and fiber thickening. In the low strength fiber lines, GAUTs mainly participate in fiber elongation, whereas their major effect on cotton with high strength fiber is related to both elongation and thickening.