**1. Introduction**

Cotton is a miracle of the plant realm as it fulfills most of the vital needs and provides more than 90% of the world's total production of fiber for the textile industry and edible oil for almost half of the world's population [1]. It has been observed that more than 50% of cotton around the globe is affected by abiotic stress such as salinity, drought, and heat stress that lead to deficient production of this field crop, especially when affected at the seedling stage [2]. Cotton growth requires sufficient fresh water for better fiber quality, but if it faces drought or heat stress the fiber production is reduced [3]. Many new drought tolerant cultivars of cotton have been introduced with improved plant growth, and even other genetically engineered genotypes of cotton by breeding techniques are being cultivated that can tolerate many abiotic stresses [4]. However, the genetic basics and amendments behind these stresses need to be evaluated more to combat these problems from the genetic roots. Cotton is divided into eight genomes (groups) from A to G and K including 45 diploids and the basic seven tetraploid [5,6]. Evolutionary data based on DNA sequencing suggested that about six to seven million years, ago due to trans-oceanic dispersal, D genome divergence gave rise to the A genome and in America (primarily Mexico), it became a separate lineage [7,8]. An incredible diversification occurred over this

**Citation:** Rani, S.; Baber, M.; Naqqash, T.; Malik, S.A. Identification and Genetic Mapping of Potential QTLs Conferring Heat Tolerance in Cotton (*Gossypium hirsutum* L.) by Using Micro Satellite Marker's Approach. *Agronomy* **2022**, *12*, 1381. https://doi.org/10.3390/ agronomy12061381

Academic Editors: Channapatna S. Prakash, Ali Raza, Xiling Zou and Daojie Wang

Received: 8 April 2022 Accepted: 26 May 2022 Published: 8 June 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

time that resulted in the worldwide spread of the Gossypium species. Domestication of wild varieties of cotton by human beings resulted in lot of change in all phenotypic and genotypic characteristics.

In terms of production, Pakistan is at the fourth position among the cotton growers of the world; raw cotton exported from Pakistan holds third position in the world as per records of 2012–2013 [9]. Pakistan is more prone to climate changes due to its geographical location [10]. Heat stress is a combination of different intricate functions of intensity duration of temperature. Because of its geographical position, in Pakistan during the summer in some locations, the temperature reaches up to 50 ◦C and the scorching heat adversely affects cotton plants. Cotton is cultivated in hot areas in Pakistan [11]. High temperature affects growth and development of the plant as well as fiber quality traits [12,13]. Episodes of periodic heat stress and increase in average temperature for the full season enhances the detrimental effects on almost all the factors of plant growth, and that is the reason there is great reduction in the seed number, fiber quality, and content [14]. Cotton yield is suppressed when the plant faces heat and drought stress due to decreased plant transpiration and reduced biomass accumulation, resulting in an inadequate yield [15]; these stresses adversely affect cell elongation, differentiation, and division and also suppress stomatal conductance [16].

The cotton plant has a wide range of adaptability [17], but high temperature is one of the major constraints in cotton productivity and greatly reduces seed cotton yield and quality, which can be addressed by breeding methods. Marker-assisted selection fastens the breeding technology with an accurate approach towards the desired phenotypic traits among the breeding population [18], and it requires detection and analysis of genetic variations using advanced genetic approaches, leading to phenotypic traits of quantitative and agro-economic importance [19]. Genomic selection (GS) and MAS developed by molecular markers techniques has made it possible to map quantitative trait loci (QTL) and identifying QTLs for high-temperature stress and breeding heat-tolerant varieties is an effective way to address this issue. MAS methodology has been used globally to acquire ordered and swift ways for cotton improvement on large scales internationally, with both highly demanded attributes like high seed production and excellent quality of fiber [20]. For dissection of QTLs related to traits with complex genetic patterns of inheritance, molecular marker use has been an efficient tool and these markers have also facilitated MAS breeding [21].

Both agronomic and economically important traits are approached by researchers for obtaining the aim of better yield of cotton [22]. The main challenging goal for current cotton breeders is to further enhance cotton production. However, this aim is hindered by the use of locally available germplasm and extreme environmental fluctuations that influence yield attributing traits [23,24]. Certain different genes cause different expressions of characters regarding tolerance of heat stress at vegetative and reproductive growth stages [25]. Genes attributing to relative water content, stomatal conductance, especially along with Percent Boll set on the First Position along Sympodia (PBF), Percent Boll set on the second Position along Sympodia (PBS), Cell Injury (CIY), Boll Number (BON), Total number of Buds (TNB), Size of Petiole (SOP), Total number of Flowers (TNF), Length of Bract (LOB), Length of Petal (cm) (LOP), Length of Staminal Column (LOS), Length of Pistil (LPI), and Proline Con. (μg mL−1) (PCO) have been reported as crucial for heat stress determination [26,27]. Therefore, during the selection of heat tolerant varieties, both vegetative and reproductive traits should be considered equally.

Molecular genetic methods, especially molecular markers, have been applied widely in cotton in recent couple of decades. Recently, the development of molecular markers was accelerated with the release of assembled genome sequences of *G. hirsutum* [28,29]. Numerous genetic linkage maps including the intraspecific map of *G. hirsutum* have been constructed using restriction fragment length polymorphisms (RFLPs), simple sequence repeats (SSRs), and single nucleotide polymorphisms (SNPs). Thousands of quantitative trait loci (QTLs) for yield and fiber quality in cotton have been documented in Cotton

QTLdb, Release 2.3 [30,31]. However, there are few studies about the simultaneous dissection of the genetic basis underlying complex traits and their genetic correlations in multiple upland cotton populations by QTL mapping. In the situation of changing weather and elevating temperature around the globe, it is of the utmost importance to recognize QTLs for morphological, architectural, and physiological traits that are directly or indirectly affected by high heat stress at some stages of cotton plant development. This study was conducted to identify and map quantitative trait loci (QTLs) conferring heat tolerance in an Intraspecific cross and used microsatellite markers to identify polymorphism between two upland cotton cultivars in the scorching heat of Multan (Pakistan) during summer. QTL identified in this project could be helpful for future cotton growers of high-temperature regions in the world.

In this study, F2 populations were used, which were derived from hybridization of two *G. hirsutum* normal lines (MNH-886 and MNH-814). The corresponding genetic linkage map was constructed using 175 polymorphic SSR markers. QTL mapping was implemented with the integration of the genotypic and phenotypic data of twenty-three agronomic and economic traits contributing towards heat tolerance; the aim of this study was to (a) screen cotton cultivars for heat tolerance, (b) select diverse cultivars as parental lines and then their assessment by SSRs for parental survey, (c) develop the segregating/mapping population (F2) of selected parents and collect phenotypic trait data at different time intervals, (d) survey the F2 population by polymorphic markers obtained from the parental survey, (e) evaluate phenotypic traits with the association of genotypic markers (SSR) data, (f) identify QTLs directing heat tolerance by QTL cartographer software, and (g) construct a genetic linkage map of *Gossypium* from the obtained information. The outcomes of this study will help plant breeders to produce heat-resistant varieties that will help farmers and countries with agriculture-dependent economies, especially in high-temperature areas around the globe.

#### **2. Materials and Methods**

This study was conducted to identify and map QTLs conferring heat tolerance in an Intraspecific cross and used microsatellite markers to identify polymorphism between two upland cotton cultivars in the scorching heat of Multan (Pakistan) during summer. QTL identified in this project could be helpful for future cotton growers of high temperature regions in the world. The research was arranged at Cotton Research Station (CRS) Multan to coincide the reproductive phase with higher temperature. The field work encompassed 14 cultivars sown in Randomized Complete Block Design (RCBD) replicated three times during the year 2012. All fourteen cultivars were tagged randomly altogether to evaluate 23 morphological and physiological parameters contributing to heat tolerance for identifying the genomic regions under plant breeding techniques; F2 generation was observed for screening purposes. The cultivars named as CIM-557, CIM-573, NN-3, Cyto-108, NIAB-852, CIM-588, BH-172, GH-102, NIAB-2008, MNH 886, CIM-554, Shahbaz-12, MNH-2007, and MNH 814 were chosen for screening of heat tolerance based on different agronomic traits related to heat, and their genomic basics were screened out. Different morpho-physiological characters included plant height (PH), fully dehiscent anther (FDA %), Total number of sympods (TNS), Total Number of Nodes (TNN), Pollen Viability (%) (POV), First Sympodial Node Number (FSN), First Sympodial Node Height (cm) (FSH), Sympodial Node Number bearing first effective boll (SNF), Sympodial Node Height (cm) bearing first effective boll (SNH), Sympodial Node Number bearing Last effective boll (SNL), Sympodial Node Height (cm) bearing last effective boll (SNB), Percent Boll set on First Position along Sympodia (PBF), Percent Boll set on second Position along Sympodia (PBS), Cell Injury (CIY), Boll Number (BON), Total number of Buds (TNB), Size of Petiole (SOP), Total number of Flowers (TNF), Length of Bract (LOB), Length of Petal (cm) (LOP), Length of Staminal Column (LOS), Length of Pistil (LPI), and Proline Con. (μg mL<sup>−</sup>1) (PCO).
