Dissecting Source-Sink Relationship of Subtending Leaf for Yield and Fiber Quality Attributes in Upland Cotton (Gossypium hirsutum L.)

Abstract

Photosynthesis as a source is a significant contributor to the reproductive sink affecting cotton yield and fiber quality. Moreover, carbon assimilation from subtending leaves adds up a significant proportion to the reproductive sink. Therefore, this study aimed to address the source-sink relationship of boll subtending leaf with fiber quality and yield related traits in upland cotton. A core collection of 355 upland cotton accessions was subjected to subtending leaf removal treatment effects across 2 years. The analysis of variance suggested a significant effect range in the source-sink relationship under subtending leaf removal effects at different growth stages. Further insight into the variation was provided by the correlation analysis and principal component analysis. A significant positive correlation between different traits was observed and the multivariate analysis including hierarchical clustering and principal component analysis (PCA) categorised germplasm accessions into three groups on the basis of four subtending leaf removal treatment effects across 2 years. A set of genotypes with the lowest and highest treatment effects has been identified. Selected accessions and the outcome of the current study may provide a basis for a further study to explore the molecular mechanism of source-sink relationship of boll subtending leaf and utilization of breeding programs focused on cotton improvement.

1. Introduction

Cotton, Gossypium spp., is widely accepted as the major fiber source globally and is cultivated across most of the tropical and subtropical parts of the world [1]. Among the prominent cotton producers, China, USA, India, Pakistan, and Uzbekistan are considered major shareholders [2,3]. The major limitations in cotton productivity are the biotic and abiotic stresses, including drought, heat, salinity, insect pests, diseases, and weeds, particularly during the early development stages [4]. Cotton is generally considered a resilient crop against stressors. However, viral infestations such as the Cotton Leaf Curl Virus Disease (CLCuD) have become major threats during the last two decades due to heavy infestations across South Asia and some parts of the USA [5]. Additionally, cotton growth and development may be highly challenged due to future climate change scenarios [6]. Upcoming climate changes are likely to play a prominent role in the change in cotton crop productivity patterns either positively or/and negatively. Fluctuating temperatures may significantly influence cotton growth and development due to a higher impact on respiration, transpiration rate, and photosynthesis, ultimately influencing fruit production [7].

The fiber quality attributes, including fiber length, strength, fineness, uniformity, and elongation, are the key desirable factors for optimizing textile processing and producing high-quality textile products [8]. A higher lint production is also considered as one of the most critical factors among major cotton production systems focusing on enhancing profitability [9]. Several cotton yield components play a significant role in enhancing lint yield, including bolls per plant, boll weight, seeds per boll, and ginning out percentage [10,11]. During the recent era, most of the improved cotton varieties being cultivated face a narrow genetic base due to the extensive unidirectional artificial selection by breeders for yield enhancement [12]. It became a serious concern nowadays, as narrow or limited genetic diversity may lead to a deficient allelic availability for a continued genetic improvement of cotton [13,14]. Hence, it is worth understanding the genetic basis of various domesticated traits and maintaining diversity among species to be utilized as a source in future breeding programs aimed at cotton improvement [14,15,16].

Since fibers in cotton are exclusively acclaimed as natural fibers and are made up of cellulose, with a polysaccharide 1,4-d-glucopyranose structural unit [17]. It is assumed that there must be a fundamental linkage among photosynthate assimilation, storage, and plant growth in terms of their strong relation as a source-sink [18]. Hence, a potential connection between carbon utilization and transport from photosynthate assimilation source tissues to the non-photosynthetic tissues is considered a sink [19]. Furthermore, fiber quality in cotton, including length, strength, and fineness, is extensively influenced by the photosynthate concentration in assimilates. During favorable conditions in the presence of adequate nutrients, light, and moisture, the cotton boll under-development may be assumed to acquire almost 60% or more assimilates required for fiber growth solely through subtending the leaf nearest to it [20,21]. Translocation becomes essential through other plant parts to supplement the remaining 40% development [22]. Therefore, an early vegetative growth is preferred in order to overcome the increased competition of different bolls as sinks are required to get translocated during the upcoming reproductive phase. Many published reports concluded that until the 12th node, the vegetative growth rate is usually enhanced, resulting in the derived carbohydrate transport towards reproductive units (bolls), unless any significant translocation among branches is accomplished [23,24].

Around 60–87% carbon in mature cotton boll is detained through CO₂ assimilation across the boll development, and as this process is carried out, the subtending leaf has a significant contribution for photosynthate accumulation, ultimately leading to increased biomass in seed cotton [20,21,24]. In this process, bolls and subtending leaves are linked in a sink-and-source-relationship to utilize photosynthate accumulation [25,26]. We can interpret their relationship as coordination among vegetative and reproductive growth phases in cotton with a substantial impact on the yield and quality of cotton produce [27]. Numerous studies on source-sink relationships have reported that an earlier and efficient sink development may lead to a robust and more substantial reproductive growth potential [28]. Higher yields are attributed to the substantial photosynthesis rate within the functional leaves, which is considered a source activity and is essential and effective for efficient photosynthates distribution through the reproductive parts [29,30].

A competition prevails for photosynthates across different plant development stages (Stewart 1989). The leaf is assumed to play an essential role in plant growth and development and is known as “powerhouse” in the plants due to its functionality as food synthesis in the presence of chlorophyll (Gitelson et al. 2003). Numerous leaf traits have been reported to show a substantially significant role in yield [31]. Considering the cotton plant as a reference, the leaf life cycle starts with bud initiation, acting as a carbohydrate exporter within a few days [32]. As the boll emerges, it starts extracting its maximum nutrition mostly from its subtending leaf [33].

The multivariate analysis has been extensively used as an important and mostly primarily acceptable method to estimate genetic variability and diversity in a more accurate manner [34]. It can also determine possible patterns of dissimilarities and potential genetic relationships within a specific germplasm collection [35]. The multivariate analyses have been extensively utilized globally by different crop improvement programs [36] on various crops such as wheat [35], maize [37,38], and sorghum [39].

The present-day improved cotton cultivars are assumed to be developed using limited germplasm sources as parents [40]. Due to the lack of extensive studies to explore the relationship between source-sink so far, this has made it difficult for a clear understanding in this regard and we are still handicapped in developing an optimal rationale for source-sink relationship manipulations. Hence, the current study has been planned to investigate the source-sink relationship of subtending leaves with boll influencing fiber quality and yield traits of upland cotton accessions during the years 2018 and 2019. The main objectives of the current study were aimed at: (a) The assessment of variability and diversity of the studied germplasm in response to the source-to-sink relationship; (b) Exploration of genotypes expressing minimum and maximum source-sink dependency. This study will be helpful in providing a deep insight into the source-sink relationship of subtending leaf with its boll and effect on yield and fiber quality. It will also provide a baseline for possible source-to-sink manipulations for cotton improvement yield and fiber quality.

2. Materials and Methods

A diverse collection containing 355 upland cotton accessions taken from the gene bank of the Institute of Cotton Research of CAAS has been considered plant material and utilized for the study. The collection comprised 331 cultivars developed and originated from China, whereas 24 cultivars were introduced from different countries. The Chinese accessions have been further subdivided into the five groups concerning the ecological areas of their origin, including 162 accessions from the Yellow River region (YR), 51 accessions from the Yangtze River Region (YZR), 98 accessions from the northwest in the land region (NW), 20 accessions from the Liaoning province (LN), and the foreign group consisted of 20 accessions from the USA, while four accessions were from countries of Central Asia. These cotton accessions have been planted following a triplicated randomized complete blocked design (RCBD) in the factorial arrangement at the field area of CRI, Anyang Henan during the sowing season in 2018 and 2019. Sowing was carried out on 30 April during both years viz., 2018 and 2019. The plot size was maintained as 3.5 m length of each accession in each replication and for each treatment.

After germination, thinning was carried out to maintain the plant population by keeping 10 plants in each row. The chemical control was applied at peak flowering and the boll setting period, whereas all other agronomic and plant protection practices were practiced following local recommendations. Five guarded plants from each line were selected randomly and tagged to be considered for further study. The start of the blooming flower tagging in all the experimental plots was carried out beginning from July 10, onward to August 10. Each flower during this period has been tagged from its blooming date. The boll subtending leaf removal has been carried out for the tagged leaves, as they reach 35 the days’ bolls represented as T₁, 40 days’ bolls as T₂, 50 days’ bolls as T₃, 60 days’ bolls as T₄, and one check as the control where the subtending leaf was kept unremoved (Table 1). The subtending leaf removal was carried out by hand on 20 bolls from each replication per accession from each treatment from the five selected and tagged plants. On maturity, picking was carried out to pick 20 bolls from every five plants for each treatment. The fiber quality for the nine traits was recorded for the picked bolls using a high volume instrument (HVI) in the Laboratory of Quality and Safety Risk Assessment for Cotton Products (Anyang), Ministry of Agriculture, People’s Republic of China. The traits considered for the current study included boll weight (BW), seed weight (SW), ginning outturn (GOT%), fiber weight (FW), fiber length (FL), fiber uniformity (FU), fiber fineness (MIC), fiber strength (FS), and fiber elongations (FE).

The effect of source (subtending leaves) to sink (boll) was estimated by comparing different treatments (removal of subtending leaves at multiple growth stages as shown in Table 1) with the control. Additionally, differences were considered as the source-sink effect of the corresponding trait.

Subtending Leaf Effect(E) = Control− Treatment (Mean)

where E is the subtending leaf effect or tolerance indice, control is the treatment with unremoved subtending leaf, whereas treatment is used for the corresponding treatment with the removed subtending leaf on different dates post anthesis (DPA).

The effects E1, E2, E3, and E4 were calculated using the same formula as above with the recorded values for each trait under study and their corresponding control values across both years.

3. Results

The variation existing for the removal of subtending leaf effects in the core germplasm of upland cotton (355 accessions) was estimated using the mixed linear model. The four treatment effects of subtending leaf removal derived for each trait were compared to dissect the source-sink relationship of subtending leaf with the yield and fiber quality. The differences were then termed as a source-sink effect for each trait under study. The summary statistics of the data collected is revealed in Figure 1. It showed that a high range of values existed regarding the removal of subtending leaf treatment effects in year 2018 as compared to 2019. Furthermore, the yield related traits particularly SW, BW, FW, and GOT showed more variation effects across both years in comparison to the fiber quality traits.

The overdispersion parameter estimated by the maximum likelihood using the generalized linear model (GLM) for fiber quality and yield related traits in 355 upland cotton accessions, under four treatment effects (E1–E4) across 2 years (2018 and 2019), are represented as Supplementary Tables S1–S9. From these results, the effect summary and effect tests have been concluded, since ANOVA (Table 2) suggested significant L-R chi-square values along with Log Worth values as represented in the summary effect plots in Table 2 among the genotypes for all traits. Whereas, the treatment effects have been significant for yield traits viz., boll weight (BW), fiber weight (FW), ginning outturn (GOT), and seed weight (SW). In contrast, fiber quality traits viz., fiber length (FL), fiber uniformity (FU), micronaire (MIC), fiber strength (FS), and fiber elongation (FE) showed non-significant treatment effects for the source-sink relationship. Furthermore, ANOVA also depicted a significant variation within the growing seasons viz., 2018 and 2019 for BW, FW, SW, FS, and FE. The significant variation of traits in different growing seasons depicted a significant environmental influence. However, GOT, FL, FU, and MIC did not show significant differences in the two seasons as the source-sink effect.

4. Discussion

The source-sink relationship in plants is critical for the end-product as yield, and is a complicated phenomenon affecting the cotton yield and fiber quality. To understand the dynamics of the source-sink relationship, the core germplasm of upland cotton accessions was evaluated. The subtending leaf was considered a primary source, affecting the yield and fiber quality in cotton [26]. The effects of subtending leaf removal were subjected to multivariate data across 2 years and four subtending removal treatment effects related to fiber quality and yield traits. In addition, the corresponding variation in core germplasm was evaluated using the generalized linear model (GLM), correlations, PCA, and clustering. It is generally assumed that the subtending leaf is the major contributor to biomass accumulation in cotton bolls [42]. Hence, subtending leaves act as a source for their corresponding bolls, acting as a sink. This source-sink relationship is reflected as the coordination of vegetative and reproductive growth, and cotton development influences yield and fiber quality in cotton [43]. Considering a very basic and simple example, we look at a plant with two organs viz., leaf and root. Leaves are involved in carrying out the photosynthesis process and can be considered the sole source of carbon, whereas roots are sinks for carbon and dependent on the leaf to support their growth and development. In contrast, we can consider roots as sources of nutrients and nitrogen, which they get from the soil and provide to the leaves, acting as net sinks in this scenario. Each plant cell utilizes carbon for respiration, growth of essential metabolites, building up proteins, various enzymes, and other genetic materials [44]. Hence, we can assume that mature leaves involved actively in photosynthesis have a relatively small carbon-sink activity. On the contrary, roots have a small nitrogen-sink activity and higher nitrogen-source activity, making them net sources for nitrogen (Burnett 2019).

Moreover, checking the photosynthesis through subtending leaves has been created by shading across flowering and the boll formation stage [45,46,47]. However, no clear and state-of-the-art experiment was reported to determine the source-sink relationship between subtending leaves with cotton boll, which is ultimately crucial to fiber yield enhancement in cotton [48]. Previously, a few studies have reported that the variation of starch and sucrose in cotton fibers have a remarkable association with fiber quality [49]. The portioning of photosynthates during the boll development stage (ovule or the fiber development) were primarily from the subtending leaves of the boll (Ryser 1992), and the content of sucrose and starch in cotton subtending leaves was higher than hexose [49,50]. Therefore, it is pertinent to examine the content and variation of sucrose and starch that might affect the fiber quality. In our study, all the genotypes depicted considerable variations when analyzed for fiber quality traits of FE, FU, FS, MIC, and FL and yield related traits such as BW, FW, SW, and GOT. The correlation matrix is used to investigate the dependence between multiple variables [51]. The significant positive associations among fiber quality parameters, i.e., FU, FL, FS, FE, and MIC, were observed in our study, which is in line with previously published statistics [52,53]. Similar to earlier findings, the current investigation found negative correlations among yield related and fiber quality traits. For instance, highly significant negative correlations have been exhibited by FE with SW and FS with FW and GOT [54]. However, GOT% revealed a highly significant positive correlation with MIC, as reported previously [55,56]. MIC depicting a significant negative correlation with FL has also been reported previously [57,58]. One of the liable mechanisms behind such negative correlations is repulsive linkage [58]. In these instances, superior genotypes harboring desirable traits related to yield and fiber quality can be utilized as recurrent parents to engulf negative correlations in selection-breeding programs [54]. In previous findings, FS and MIC revealed a positive correlation with each other as in the current study [59]. A biplot analysis has been implemented to understand the multivariate relationships among fiber quality and yield contributing traits across 355 upland cotton accessions concerning the association between germplasm accessions and the observed traits.

5. Conclusions

In the current study, insight into the variation of source-sink effects suggested a significant range of variation, as well as a positive correlation between different traits in core germplasm accessions under treatment effects across years. The treatment effect through the principal component analysis and hierarchical clustering methods divided accessions into three groups, based on four treatments across 2-year data. Our results depicted a significant variation among the core germplasm for the treatment effect through yield traits as well as for fiber length, and provide a basis for further studies to explore the source-sink relationship of subtending leaf with yield and fiber quality. A set of cotton accessions with higher treatment effect, which is considered to have a strong source-sink relationship and lower compensation effect along with a set of genotypes exhibiting a lower treatment and higher compensation effect, has been selected from this study. The reported results and selected genotypes based on their source-sink relationships can be further utilized in breeding programs to understand and evaluate the molecular mechanism behind the source-sink relationship in terms of carbon accumulation.

Acknowledgments

We acknowledge the Gene Bank of the Institute of Cotton Research of Chinese Academy of Agricultural Sciences for providing the seeds of the 355 accessions for research experiments.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/plants10061147/s1, Supplementary Tables S1 to S9 Over-dispersion parameter estimated by Maximum Likelihood using Generalized Linear Model (GLM) for Fiber quality and yield contributing traits in 355 upland cotton accessions under four treatment Effects (E1-E4) across two years 2018 and 2019. Supplementary Table S10. Eigenvalues contributing to different PCs for studied traits related to Source-Sink Effects across years 2018 and 2019. Supplementary Table S10 Loading Matrix Associated with the principal components for studied traits, treatment effects (E1-E4) and years 2018 and 2019.

Author Contributions

Conceptualization, F.S. and Q.M.; methodology, N.M., X.W., T.M., and Q.M.; software, N.M. and M.S.I.; validation, N.M., Z.S., M.F.N., and G.H.J.; formal analysis, N.M., Z.S., and M.S.I.; investigation, N.M. and T.M.; resources, F.S. and Q.M.; data curation, N.M., X.W., and M.F.N.; writing—original draft preparation, N.M.; writing—review and editing, N.M., M.F.N., X.W., M.S.I., Z.S., G.H.J., Q.M., and F.S.; visualization, G.H.J. and M.S.I.; supervision, F.S. and Q.M.; project administration, F.S.; funding acquisition, F.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Project of National Natural Sciences Foundation of China (grant no. 31701474) and Key Scientific Research Projects in Henan Colleges and Universities (17B180001).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data supporting the reported results will be available and provided at a reasonable request.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Footnotes

References

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