Wheat (Triticum aestivum L.) is a staple food and major source of dietary calories in Pakistan. Improving wheat varieties with higher grain yield and disease resistance is a prime objective. The knowledge of genetic behaviour of germplasm is key. To achieve this objective, elite wheat varieties were crossed in 4 by 3, line × tester design, and tested in 2019 in a triplicate yield trial to estimate genetic variance, general and specific combining ability, mid-parent heterosis and stripe rust (Puccinia striiformis L.). High grain 3358 kg·ha–1 was recorded in F1 hybrid (ZRG-79 × PAK-13). Analysis of variance (ANOVA) revealed significant genotypic variance in grain yield. Broad sense heritability (H2) was recorded in the range of 28 to 100 %. General combining ability (GCA) significant for grain yield in parents except FSD-08 and PS-05 was recorded, while specific combining ability (SCA) was recorded to be highly significant for grain yield only in two crosses (ZRG-79 × NR-09 and ZRG-79 × PAK-13). Mid-parent heterosis was estimated in the range of –28 to 62.6 %. Cross combinations ZRG-79 × PAK-13 depicted highly significant mid-parent heterosis (62.6 %). Highly significant correlation was observed among spike length, spikelets per spike, plant height and 1000-grain weight. Rust resistance index was recorded in the range of 0 to 8.5. These findings suggest exploitation of GCA for higher grain yield is important due to the presence of additive gene action and selection in the filial generations will be effective with improved rust resistance, while cross combinations ZRG-79 × PAK-13 high GCA are best suited for hybrid development. Wheat (Triticum aestivum L.) is an important cereal cropworldwide playing a crucial role in the daily dietary and nutritionalrequirement not only for human beings but also foranimals. It is the major food for one third of world populationand its chief use is the flour for making bread. It is grownaround all continents. Increasing human population, climatechange and global pandemics have an overwhelming impacton food security, especially wheat on crop with current inadequategenetic improvement of wheat to meet future demand.In Pakistan, wheat is grown in an area of 9.2 million ha withthe production of around 25.5 m tonnes and hardly meets the total requirement of the country. But thisfigure is continuously under fluctuation because of stagnantyield of cultivars, disease impact, drought, and floods. Apartfrom these factors, injudicious selection of parental selectionfor a breeding program without prior knowledge of geneticbehaviour in germplasm and lack of indigenous breedingprograms for genetic improvement of wheat is another constraintin the yield.Genetic recombination in germplasm by hybridization isa robust conventional breeding tool for obtaining transgressivesegregants and genetic variation, which provides meansof selection of ideotypes. Gene action and combining abilityanalysis are a most reliable biometric procedure for the studyof genetic behaviour of yield and yield-related components. General combining ability is the averageperformance of genotypes in a series of cross combinations,while specific combining ability is the performance of a particulargenotype in a specific cross combination. Mode ofselection depends based on genetic action in traits of interest.In self-pollinated crops, especially in wheat, plant breedersare usually interested in selection of segregants having additivegene action with high specific combining ability. Additivegene action boosts yield and yield components by cumulativeaddition of genes. Dominance genetic variance exploits heterosisin cross combinations and specific combining abilityprovides the presence of dominant or non-additive gene actionin a particular trait  and provides optimalparental identification . Equalmagnitude of both general and specific combining ability ina breeding population means preponderance of both additiveand dominant genes for the traits of interest; selection in thiscase is most effective for variety development . The term combining ability was first introduced andfurther refined as general combining ability (GCA) and specificcombining ability (SCA) by Sprague and Tatum (1942).GCA distinguishes between the mean performances of parentsin cross combinations whiles SCA is the deviation ofindividual crosses from the average performance of the parentsinvolved. GCA and SCA represent the additive and nonadditiveportions of genotypic variance respectively . The estimates from GCA and SCA provide anassessment of relative merits of the individual genotypes incross combinations to guide selection and testing schemes.Thus, line × tester analysis is among the genetic-statisticalapproaches developed to assist in selection of parents based ontheir combining ability and the potential to produce promisingsegregating populations . According toGCA and SCA impacts, positive values are desirable for mostcrop plants characteristics, such as growth and yield-relatedattributes. Negative GCA and SCA impacts, on the otherhand, are desirable for characters where minimum values areessential and appealing, such as early flowering.Heterosis is a phenomenon where F1 hybrids are superiorin traits as compared to their parental genotypes. There areseveral theories that explain the genetic basis of heterosis,including over-dominance, dominance, and genetic balance.The over-dominance theory of heterosis, first proposed byShull and East (1908), suggests that heterozygous individuals,since they carry two different alleles, have an advantage overhomozygous individuals as they carry two identical alleles fora particular gene. This advantage is thought to mean that thetwo different alleles can supplement with each other, leadingto a vigorous phenotype in F1 hybrids. The dominance theory,presented by Jones (1917), suggests that hybrid vigour iscaused by dominant alleles that are more valuable than therecessive alleles. According to this theory, F1 hybrids accedetwo copies of the dominant allele, resulting in a vigorousphenotype. The third heterosis theory is the “Lerner’s geneticbalance theory”, suggested by Lerner (1954), that describesthat heterosis is the result of a balance between the expressionof genes that promote growth and those that hamper growth.In F1 hybrids, the expression of growth-promoting genes isincreased, whereas the expression of growth-retarding genesis decreased, leading to better growth and development.Heterotic studies for increasing wheat grain yield have beenan interest of early wheat researchers. Mid-parent heterosisis the percent of the increase or decrease in the F1 value ascompared to the average value of both parents for any metrictrait. In the early green revolution era Pal and Alam (1938)reported mid-parent heterosis (MPH) in wheat. After thegreen revolution and introduction of semi-dwarf wheat varieties,various wheat researchers reported MPH heterosisin wheat . Barbosa-Neto et al. (1996) reported MPH in soft redwinter wheat in the range of –20 to 57 %. Liu et al. (1999),Dreisigacker et al. (2005), Basnet et al. (2019) reported MPHin CIMMYT wheat varieties in the range of 9.5 to 14 %.Wheat crop faces numerous challenges that cause yieldlosses, including stripe rust (Puccinia striiformis f. sp. tritici), which is a major disease in areas where cool to mild warmtemperature prevails during the months of February and Marchin the wheat-growing season. Under conducive environmentalconditions, disease causes yield losses ranging from 10 to70 % depending upon susceptibility of genotypes . Development of cultivars containing genetic resistanceis the most cost-effective and environmentally friendlystrategy to mitigate yield losses by stripe rust . Stripe rust spores continue to mutate and evolve newvirulent races causing damage to previously resistant cultivars. Wheat crop in Pakistan has faced severedamage caused by stripe rust pathogen in recent years . Due to climate change and rapid mutation instripe rust pathogen, new races overwintering on alternativehost barberry in hilly areas at high altitudes evolve . Under these circumstances, the already resistantgenotypes become susceptible .There are two types of resistance mechanism against rustpathogens in wheat, vertical resistance, and horizontal resistance.Vertical resistance is conferred by a single gene toa specific pathogenic race of rust, while horizontal resistanceinvolves the use of multiple genes that provide broad spectrumdisease resistance against multiple pathogenic races of rust.There are several resistance genes present in the Pakistanibread wheat varieties that confer resistance against yellow rust,which include Yr5, Yr10, Yr15, Yr17, and Yr18. Qamar et al.(2014) reported Lr34/Yr18 gene complex that confers broadspectrum resistance against yellow rust and leaf rust in mostof Pakistani wheat varieties. Intikhab et al. (2021) reportedthe presence of Lr46/Yr29 gene complex in Punjab-2011 andPirsabak-2005 cultivars that confer resistance against striperust. Khan S.N. et al. (2022) reported the presence of Yr17 andYr5 gene complex in Pakistani wheat varieties Punjab-2011and Pirsabak-2005. Utilization of these resistance sources inthe breeding program for development of varieties resistantagainst stripe rust is an ultimate objective to ensure high yieldon sustainable basis.Various biometrical techniques and breeding designs areused for genetic evaluation and genetic behaviour of germplasmto be utilized in crop breeding programs, but line × testeranalysis is an efficient mating design providing reliable informationabout GCA and SCA that ultimately depicts the modeof gene action in a particular trait . GCAand SCA are important to apprehend the genetic architectureof quantitative traits and create the road map for initiation ofan efficient breeding program .Several studies investigating the GCA and SCA effectshave been conducted in wheat. Zhao et al. (2013) reportedsignificant effects for both GCA and SCA for yield and itscomponents and inferred that selecting parental genotypeswith high GCA and SCA effects could lead to the developmentof high-yielding wheat hybrids. Similarly, researchers assessedthe GCA and SCA effects in spring wheat and durum wheatF1 hybrids by using line × tester model for combining abilityestimate and concluded that GCA effects were more importantthan SCA effects for grain yield and yield-related traits, andselection of parental genotypes with high GCA effects couldincrease the prospective yield of wheat hybrids . They found thatboth GCA and SCA effects were significant for grain yieldand its components and suggested that selecting parents withhigh GCA and SCA effects could lead to the development ofhigh-yielding wheat hybrids. Selecting parents with high GCAand SCA effects can improve the yield potential and diseaseresistance of wheat hybrids, and the use of line × tester designscan provide valuable information about the genetic effects ofparents and their hybridsThe objectives of this study is to elucidate the general andspecific combing ability, heterotic potential, and stripe rust(Puccinia striiformis f. sp. tritici) resistance behaviour ofindigenous elite wheat varieties and their breeding population.Experimental site and plant material. The research was carriedout at the experimental site of a wheat research program,National Agricultural Research Center, Islamabad Pakistanduring 2017–2018 wheat growing season. The soil type of thesite is clay loam from 0 to 20 cm, and at the 20–40 cm depthit is moderate clay loam. Five widely adopted approved wheatvarieties were used as lines  and three widelyadopted, registered and approved varieties for rainfed areasof Pakistan were used as a tester, namely, NARC-2009,Pakistan-2013 and Borlaug-2016 (Table 1). These testers arewidely adopted and due to their ability to withstand rainfed anddrought-prone areas of Pakistan their leaves have the abilityto stay green during high terminal heat and drought stress.Field experiment and crossing scheme. Eight parents werehybridized to produced 15 F1 cross combinations accordingto line × tester crossing fashion as described by Kempthorne(1957) during 2017–2018 wheat growing season and crossingwas conducted during March 2018. 15 cross combinationsand seven parents were planted in Randomized CompleteBlock Design (RCBD) with three replications during 2018–2019 wheat growing season. In every replication, parents andF1 hybrids were sown in 1 m length with row-to-row spacing25 cm and plant-to-plant spacing 15 cm. The experimentwas conducted in an irrigated field and a total of 6 irrigationswere applied after sowing to harvesting time. Recommendeddoses of fertilizers, i. e. 120 kg N · ha–1 and 80 kg P · ha–1, wereapplied. Half of the fertilizers were used at the time of soilpreparation, the second half was applied at the time of tillering,and weedicides were used for eradication of broad leaves and narrow leavesweeds respectively according to the doses mentioned by themanufacturer. Herbicide was applied before the jointing stageof the crop. Leaf area was measured when leaves were fullyturgid and green.Data collection. Grain yield and some yield-related parameterswere measured in parents and hybrid combinations.Grain yield per plant was measured in grams and 1000-grainweight was measured after counting 500 grains of each wheatgrain sample on a counting tray once and the second samplewas repeated for the other 500 grains.Canopy temperature was measured by using a portablethermal gun . Readingsfor canopy temperature were taken at three Feeks stages like booting, kernel water ripening and grainmilking stages . All readings were taken at the angle of 30° and above 50 cm of the crop canopy,avoiding land temperature by pointing thermal gum only atthe canopy. The observations were taken between 11:00 amand 14:00 pm under stagnant air conditions and clear sky asdescribed by . Observations for Normalizeddifference vegetative index (NDVI) were recorded 50 cmabove the canopy by using a hand-held Green Seeker with anoptical sensor unit  at three stages ofbooting and grain filling between 11:00 hours to 14:00 hourswith clear sky . Values of NDVI rangefrom –1  to +1 (the strongestgreen vegetative stage) .Statistical analysis. Data for other traits  were recorded from6 randomly selected plants. Data recorded were arranged inmean data and subjected to Analysis of Variance (ANOVA)accordingto Steel and Torrie (1980) and Line × Tester analysis,according to Kempthorne (1957), combining ability andgene action were studied  byusing R Package agricolae . Genotypic variance and phenotypicvariance were estimated as mentioned by Almutairi (2022) inMS Excel 2016, by using the following formula:Environmental variance was estimated according to Comstockand Robinson (1952). Broad sense heritability was calculatedby using the following formula as described by Burtonand Devane (1953):Heterosis was estimated in percentage increase or decreaseof the F1 hybrids value over mid-parental value by followingthe formula as described by Fonseca and Patterson (1968):Disease observations and scoring. Observations for striperust were recorded at the time of appearance of disease anddata were recorded when rust pathogen was fully developedon leaves of a susceptible check cultivar and leaves’ surfacewas fully covered with rust’s spores. Disease observation wasrecorded in three replicates of each parental line and F1 hybridsaccording to the Cobb Scale method as described byPeterson et al. (1948). The severity of disease was expressedas the percentage of leaf area covered, and 0 % score wasgiven when there was no infection on the leaf and 100 %score was considered when the leaf area was fully coveredwith rust spores and infection. Readings of percent severitywere recorded with the following descriptions for scoringand response values: , response values, coefficient of infection(CI), average coefficient of infection (ACI), country averagerelative percentage attack (CARPA) and rust resistanceindex (RRI) according to Akhtar et al. (2002). The followingformula was used for the calculation of RRI:RRI was calculated by considering the scale of 0 to 9 fromCARPA, where 0 represents a most susceptible genotypeand 9 represents a highly resistant response of the genotypeto rust pathogen.Analysis of variance (ANOVA)Analysis of variance (ANOVA) results presented in Table 1show that the lines  had statistically significant differencesfor all the trails. The testers  showed statisticaldifferences for days to heading, plant height, peduncle length,spike length, days to maturity, grains per spike, 1000-grainweight and grain yield, while non-significant results forflag leaf area, tillers per plant and spikelets per spike wereshown. Interaction of line × tester was significant in case ofplant height, flag leaf area, peduncle length, days to maturity,grains per spike and 1000-grain weight. Parents  used in this study provided a broad range of expressionfor various characters as shown in Table 2. There weresignificant differences ( p ≤ 0.05) among the means of genotypes(Table 3) for days to heading (DH), highly significant( p ≤ 0.01) for plant height (PH), flag leaf area (FLA), tillers perplant (TPP), peduncle length (PL), spikelets per spike (SPS),days to maturity (DM), grains per spike (GPS), thousand grainweight (TGW), grain yield (GY) and NDVI value.The values for days to heading (DH) were maximum in thetester  PAK-13 (119 days) and minimum in the lines PB-11, PS-05 and MRJ-08 (117 days). DH are thekey indicator of earliness in crop production. Plant breedersare keen to create new varieties of wheat genotypes with earlymaturity. So, early heading is a desirable trait. Delayed headingleads to a reduction in yield  and earlyheading increases the grain filling duration, which ultimatelyresults in high yield . Plant height (PH)was the highest in the female parent FSD-08 (103 cm) andthe lowest in the male parent NR-09 (83 cm). Minimum PHis preferred due to expected lodging losses. Similarly, thetester NR-09 (83 cm) can be assessed for developing droughttolerant variety with reduced plant height for future breedingprograms. Likewise, minimum flag leaf area (FLA) is alsodesirable for drought tolerance due to reduced transpirationlosses from a reduced area exposed to sunlight. The testers PAK-13 and BOR-16 showed the minimum values offlag leaf area: 29.57 and 29.83 cm2, respectively. Pedunclelength was longest in the female parent PS-05 (16.67 cm) andshortest in the male parent NR-09 (7.20 cm). PS-05 producedthe maximum grain yield (2531.8 kg · ha–1) while minimumgrain yield (1696.1 kg · ha–1) was recorded in ZRG-79.Mean performance of parents and their cross combinationsMean performance for line, testers and cross combinationsfor days to maturity (DH) ranged from 117 to 119 days. Theparental lines FSD-08, PB-11, PS-05, MRJ-08, ZRG-79 andBOR-16 were revealed to have 117 DH, while NR-09 andPAK-13 had 118 and 119 days to heading, respectively (seeTable 2). Among F1 hybrids Zargoon-79 × Pakistan-2013 had119 days for heading while the rest of the cross combinationsshowed 117 DH. The grand means for parents, crosses, linesand testers were 117.67, 117.56, 117.27 and 118.33, respectively.The coefficient of variance 0.67 % obtained for DHwas also in the acceptable range.Average minimum plant height was recorded in NARC-2009 (83 cm) followed by cross combination of Punjab-2011 ×Pakistan-2013 (86 cm), and maximum plant height of 104 cmwas recorded in the cross-combination Faisalabad-2008 ×Borlaug-2016 followed by one of parent viz. Faisalabad-2008(103 cm). Grand mean, coefficient of variance (CV) and leastsignificant variance (LSD) for plant height of lines, testers andtheir parental combinations was revealed to be 95.92 cm, 3.64and 5.73, respectively.The cross-combination Punjab-2011 × Pakistan-2013showed minimum value (26.8 cm2) for flag leaf area followedby the lines Pakistan-2013 (29.5 cm2) and Borlaug-2016(29.8 cm2). Maximum leaf area was recorded in the linePunjab-2011 (39.2 cm2) followed by the F1 combination,Faisalabad-2008 × Pakistan-2013 (36.9 cm2). Grand mean,CV, LSD and standard error for leaf area of lines, testers andcross combinations was recorded as 10.46, 5.7 and 2.0 cm2respectively.Maximum 13 tillers per plant (TPP) was recorded in thetester Pakistan-2013 followed by 12.3 tillers in Borlaug-2016while minimum 7.6 tillers were observed in the female parentPunjab-2011 followed by Pirsabak-2005 (8.33). In thecross combinations a maximum of 10 tillers was recorded inPunjab-2011 × NARC-2009 and Miraj-2008 × NARC-2009and grand mean for TTP was recorded as 9.49 with CV, LSDand SE 11.66, 3.61 and 1.27 respectively.Maximum peduncle length was observed in the line Pirsabak-2005 while minimum peduncle length was recordedin the tester parent NARC-2009. Grand mean for pedunclelength was observed to be 11.96 cm with CV 9.7 % and LSD(α 0.05) value 1.9.Mean performance for spike length (SL) was observed12.36 cm in parents and their cross combinations. MaximumSL was observed in cross combinations Miraj-2008 ×Pakistan-2013 followed by Miraj-2008 × Borlaug-2016, butminimum SL was observed in the parental line Faisalabad-2008.Grand mean for spikelets per spike (SPS) for parents andcross combination was recorded as 20.33 with a maximumof 21.9 spikelets observed in Pakistan-2013 in addition to theF1 hybrid combination of Miraj-2008 × Pakistan-2013 and inthe Pirsabak-2005 × Pakistan-2013. Grains per spike (GPS)was recorded maximum in parental line Punjab-2011. Averagethousand grain weight was calculated to be 34.52 withhigher TGW in Faisalabad-2008 (43.73 g) and the crosscombination of Faisalabad-2008 × Pakistan-2013 (43.53 g),and lower value for TGW was depicted by the parental lineNARC-2009 (22.47 g). Average grain yield was obtainedin all the parents and cross combinations (2344.5 kg · ha–1),while average GY was higher in crosses as compared to theparents’ grain yield, the maximum was recorded in the crosscombination ZRG- 79 × PAK-13 (3358 kg · ha–1), followed byPB-11 × NR-09 (2820 kg · ha–1), while minimum grain yieldwas recorded in the cross combination of ZRG-79 × NR-09(1372 kg · ha–1).Maximum normalized differences in vegetative index(NDVI) value was observed in the parental line PS-05 (0.73)followed by PB-11 × PAK-13 and PS-05 × NR-09 with thesame value. Average NDVI value for parents and crosses wasrevealed to be 0.67; lines, testers and crosses also containedsimilar values for NDVI.There were significant differences among the means ofcrosses combinations for almost all the traits studies exceptDH, TPP an SL. The lines  also depictedhighly significant differences in all the parameters under considerationexcept SL. The testers  also revealedhighly significant differences for all the traits except for FLA,SL, SPS, and NDVI. Interaction of lines × testers depictedhighly significant differences in their mean performance forthe traits of PH, FLA, PL, DM, GPS, TGW and NDVI value.Estimates of genetic variance componentsEstimation of genotypic variance, phenotypic variance, environmentalvariance, variance due to general combining ability,variance due to specific combining ability and variance dueto GCA over SCA is mentioned in Table 4.Phenotypic variance was depicted more as compared togenotypic variance in some traits, i. e. PH, FLA, SL, DM,and GY, while only GY showed high environmental variance.Broad sense heritability (H2) was estimated in the rangeof 28.11 % (GY) to 100 % (CT). PH, PL, GPS, TGW, NDVIvalue and CT showed broad sense heritability of more than91 %, while DH and GY depicted less heritability. The traitswith high genetic variance, low environmental variance andhigh broad sense heritability have preponderance of additivegenes and these are stable characters and selection in the filialgenerations can be made by keeping eye on these traits. Grainyield (GY) and DH attained low broad sense heritability andshowed that environmental influence is more important forthe expression of these traits. Selection in the filial generationshould be made for these traits by considering diseaseincidence and drought proxy parameters, i. e. NDVI and CTvaluesProportional contribution of lines, testers,and their interactions to total varianceProportional contribution of total variance for yield andyield-related metric traits for lines, testers and their crosscombinations was estimated . For DH, PH, TPP andCT it was recorded to be higher as compared to the testersand combinations of both lines and testers. Contribution ofL×T to total variance was recorded as high in FLA, PL, SL,SPS, DM, GPS and NDVI value, while variance contributionof testers to TGW and GY was estimated higher as comparedto the lines and L×T combinations.General combining abilityGeneral combining ability (GCA) estimates for all the traitsare given in Table 5. Both positive and negative GCA effectswere observed for lines and testers. For DH, the value of GCAeffects ranged between 0.00 and 0.56. As a good general combiner,significant positive (0.56) and negative (–0.56) GCAeffectswere observed for lines Zargoon-79 and Pirsabak-2005,respectively. Similarly, in the testers, positive and significant(0.51) GCA effect was observed for Pakistan-2013 only (seeTable 5). Patel et al. (2020) demonstrated ( p ≤ 0.01) significantnegative and desirable GCA effects in lines and non-additivegene action was primarily involved in days to heading.For plant height, negative general combining ability effectsare more important since more emphasis is placed upon selectionfor short stature in segregating the population because itultimately turns out that a short stature line is more responsiveto fertilizer and tolerant to lodging. In this study, GCA effectsranged between –5.82 and 3.24 for PH. Significant positive(3.07) and negative (–5.82) GCA effects were observedfor the lines Pirsabak-2005 and Punjab-2011, respectively.Similarly, highly significant positive (3.24) was estimated forthe tester BOR-16 and highly significant but negative (–2.56)GCA effects were observed for the testers PAK-13, respectively.These results are in accordance with the results of.For flag leaf area (FLA), negative general combining abilityeffects are more important because FLA is much influencedby transpiration losses due to disclosure to sunlight, whicheventually affects the grain yield. Hence, more emphasis isretained on the selection of genotypes with smaller FLA.From that, among the female parents, Pirsabak-2005 andPunjab-2011 showed a highly significant negative GCA effect:–2.16 and –2.10, respectively. On the other side, no significantGCA effects were observed among the testers for FLA. Theseresults confirm the findings of .In case of tillers per plant (TPP), GCA effects ranged between–0.58 and 0.98. As a good general combiner, highlysignificant positive (0.98) GCA effects were observed only forthe line MRJ-08 while there were no significant GCA effectsamong the testers for TPP. To begin with, TPP is a significantyield-boosting characteristic that contributes to increased grainyield. A higher number of tillers per plant confirms optimalplant populations and as a result higher grain yield . For this point of view, the female line MRJ-08showed better performance. These findings are in accordancewith the results of .GCA effects ranging between –1.16 and 1.39 were observedfor peduncle length (PL). Highly significant positive (1.39)and negative (–0.76) GCA effects were observed for the lines FSD-08 and ZRG-09, respectively. In the same way,highly significant positive (0.65) and negative (–1.16) GCAeffects were observed for the testers BOR-16 and PAK-13, respectively. Likewise, in PH, shorter PL is preferred becausean increase in PL ultimately increases the PH and we prefera plant with short stature. In current study, two female parents,ZRG-79 (–0.76) and MRJ-08 (–0.70), showed negative generalcombining ability. Also, one male parent, PAK-13, showedsuperior general combining ability for this trait. So, it can beconcluded that the above-mentioned parents are desirable foruse in the breeding program. The findings of  supported the results.Greater spike length (SL) and larger number of spikeletsper spike (SPS) are essential for enhanced yield. Among parents,one line , MRJ-08, showed significant positivevalues(0.77) for SPS. One tester, Pakistan-2013, exhibitedhigh GCA for SPS. These results were quite close to thefindings of . Number of grains per spike (GPS) is also animportantfactor for enhanced grain yield. Therefore, positiveGCA effects are more important due to positive contributionof grain yield. Among male parents, only NR-09 showedpositive and higher values (3.26) of GCA effects for GPS.Among female parents, MRJ-08 and PS-05 showed positiveand higher values, i. e. 2.90 and 2.02 respectively. It shouldbe noted that values of male parents were higher than thoseof female parents. These findings match with the results of. These results are different fromthe findings of Nazir et al. (2005).For grain yield per plant (GY), only one female parentMRJ-08, and among the male parents, BOR-16 and NR-09,exhibited positive general combining ability effects. Similarresults were also found by .Specific combining abilitySpecific combining ability (SCA) estimates for all the traitsare given in Table 6. Both positive and negative SCA effectswere observed among the crosses.As for SCA effects for DH, all the fifteen crosses were ofnon-significant nature with positive and negative magnitude(see Table 6). The result indicates the involvement of bothadditive and non-additive genetic effects in the inheritance ofDH, with greater proportion of additive genetic effect. Lineswith maximum SCA effects can be used in development ofhybrid cultivars. Only six among fifteen crosses depicted negativeSCA effects for plant height. If parents with tallness arethe ideal ones, then the crosses FSD-08 × NR-09, FSD-08 ×PAK- 13, PB-11 × NR-09, PB-11 × PAK-13, PS-05 × BOR-16and MRJ-08 × BOR-16 would be considered good. However,the remaining crosses exhibited higher SCA effects. Thesefindings confirmed the results of . Furthermore,non-additive type of gene action is detected for PH and supportedby . Also, our results concur withAli F.K.H. and Abdulkhaleq (2019) for plant height.GCA effects for flag leaf area range from negative –3.80 topositive 3.33. Roughly 50 % of the crosses showed smallervalues of SCA effects for flag leaf area, which is desirable.As less flag leaf area is required for drought tolerance, thecrosses with significant SCA effects, i. e. FSD-08 × BOR-16and PB-11 × PAK-13 may be used in a future breeding programbecause they have high negative SCA values contributingtowards minimum FLA. However, the remaining crossesexhibited higher positive SCA effects for FLA. Comparableresults have also been stated by .Negative SCA effects are needed to reduce the pedunclelength (PL). In this study, two crosses showed significantlynegative SCA effects. FSD-08 × NR-09 and MRJ-08 × BOR- 16are the best hybrids for reduced PL. Similar results were reportedby .In case of spike length (SL), all the fifteen crosses were ofnon-significant nature with positive and negative magnitude(see Table 6). For a number of SPS, positive specific combiningability effects were shown in 6 out of 15 crosses but onlytwo crosses, FSD-08 × NR-09 and PB-11 × BOR-16, havesignificant GCA effects. These hybrids performed best andcan be suggested for future breeding programs. These resultsare in the conformity with those of .For grain yield per plant, SCA effects found varied muchamong crosses. The poorest cross with respect to SCA forgrain yield per plant was ZRG-79 × PAK-13 whereas the crossthat appeared to be the best and the most promising specificcombination was ZRG-79 × NR-09. Positive specific combiningability effects were displayed in 8 out of 15 crosses.But only ZRG-79 × NR-09 showed such significant positiveeffects among crosses. Similar results were also reported by.Mid-parent heterosis estimation for grain yieldMid-parental heterosis (MPH) for GY was estimated for15 F1 hybrids . F1 hybrids ZRG-79 × PAK-13 showedhigher mid-parental value (62 %) followed by FSD-08 ×PAK- 13, ZRG-79 × BOR-16, and PB-11 × NR-09, whichrevealed mid-parent heterosis value above 30 % . Cross combinations PS- 05 × PAK- 13,MRJ- 08 × NR-09, MRJ-08 × PAK-13, FSD- 08 × NR- 09 depictedmid-parental heterosis value more than 15 %. Threecross combinations, ZRG-79 × NR-09, MRJ-08 × BOR- 16and PB-11 × BOR-16, depicted negative heterosis.Cross combinations with more than 30 % mid-parentalheterosis can be used in hybrid breeding in wheat. Heteroticstudies for increasing wheat grain yield has been an interestof early wheat researchers. Pal and Alam (1938) reportedmid-parent heterosis in the pre-green revolution era. After theintroduction of semi-dwarf wheat in the post-green revolutionera, various wheat researchers reported mid-parent heterosisin wheat, i. e. . Barbosa-Neto et al. (1996) reported MPH in red softwinter wheat in the range of –20 to 57 %. Liu et al. (1999),Dreisigacker et al. (2005), Basnet et al. (2019) studied MPHin CIMMYT wheat varieties and reported MPH in the rangeof 9.5 to 14 %. Parental lines and tester used in present studieshave CIMMYT background and the majority of the genotypesexhibited similar results for MPH. However, crosses combinationZRG-79 × PAK-13 has one indigenous parent ZRG-79and exhibited a high percentage of MPH. These finding candemonstrate that crosses among parents with CIMMYT backgroundhave low heterotic potential and additive gene actiongoverned the GY potential in these cross combinations andselection in the filial generation will be key for transgressive segregants, but in case of crosses among indigenous parentsand genotypes with a CIMMYT parent it will be good sourceof hybrid breeding.Correlation study of agronomic traitsCorrelation study among yield and related traits under rainfedconditions of eight parents and 15 wheat crosses is mentionedin Figure 3. High significance was observed between PH andTGW with the value of 0.9 ( p < 0.001), SL and SPS had acorrelation coefficient value of 0.72 ( p <0.001) followed byDH and DM with 0.57 ( p <0.01). PL also showed highlysignificant and positive correlation with TGW and PH . PL and TGW also revealedsignificant but negative correlation with DH –0.6 and –0.5,respectively ( p < 0.01).Positive and significant correlation among PH and PL withTGW showed that the higher the plant height the higher thethousand grain weight and peduncle length. Careful considerationshould be made while selecting the genotypes with stiffand strong stem girth to avoid lodging. Correlation betweenSL and SPS revealed that an increase in spike length leadsto an increase in spikelets per spike, genotypes with longspikes will be a good selection criterion for increasing yielddue to the increase in number of spikelets per spike. Positiveand significant correlation among DH and DM depicted thatgenotypes with early DH would mature earlier, so selectionof genotypes with early flowering is good for early maturityand short duration variety development. Significant but negativecorrelation between TGW and DH indicated that a delayin days to flowering leads to a reduced TGW and vice versa.TGW showed negative correlation with TPP and these findingsare in line with the results of Almutairi (2022). Low correlationof GY with other parameters in wheat was also reportedby Gowda et al. (2010).Stripe rust responses of parental linesand their cross combinationsThe response to stripe rust (Puccinia striiformis f. sp. tritici)on parental lines used in the study and their offspring(crosses) is recorded for disease scoring, coefficient of infection(CI), average coefficient of infection (ACI), country averagerelative percentage attack (CARPA) and rust resistanceindex (RRI) (Table 7). All the parental lines showed moderateresistant (MR) to highly resistant (R) reaction against striperust (Pst). The female parents (lines) FSD-08, PB-11, PS-05,MRJ-08 and ZRG-79 showed 20M, 20M, 5M, 30M and 40Mscores respectively, while the pollen parents (testers) viz.PAK-13, BOR-16 and NR-09 depicted 10MR, 5R and 40Mresponse against stripe rust. All these parents showed a slowrusting response against rust pathogen that is under the controlof multiple genesCross combinations of these parental lines showed a variedresponse, moderately resistant to moderately susceptible reaction against stripe rust. The F1 hybrids combinations PS- 05 ×PAK-13, PS-05 × BOR-16 and PS-05 × NR-09 showed 10MR,10MR and 5MR reaction, the crosses FSD-08 × PAK- 13,FSD-08 × BOR-16, PB-11 × PAK-13, PB-11 × BOR-16, andMRJ-08 × BOR-16 showed 20M reaction, the cross combinationMRJ-08 × PAK-13 showed 30M reaction, while the restof the crosses showed moderately susceptible to susceptiblereaction against stripe rust.Average coefficient of infection (ACI) for the parentsPS- 05, PAK-13, BOR-16 and FSD-08 was recorded as 2.0,6.7, 4.3 and 14.0 respectively and these varieties revealeda very good level of resistance against stripe rust. Rust resistanceindex (RRI) of these parents was also high (ranged 5.8to 8.5), which indicated a good resistance response of thesevarieties. Among the cross combinations, PS-05 × BOR-16,MRJ-08 × PAK-13, PB-11 × BOR-16, PB-11 × PAK-13 andPS-05 × NR-09 depicted ACI values of 4.0, 8.3, 12.0, 13.1, and14.7, respectively. These F1 hybrids had a resistant responseto stripe rust. RRI value of the F1 hybrids  was higher (ranging from 5.6 to 8.1).The higher the RRI value and the lower the ACI valuemeans of genotypes with a resistant response to the diseasepathogen and under the influence of slow rusting genes, theslower the disease progress and the lesser the yield losses.Genotypes with higher RRI values (>5.0) represent moderatelyresistant to highly resistant response against rust pathogen.The parental genotypes viz. PS-05, PAK-13 and BOR-16had higher values for RRI showing a highly resistant response against stripe rust pathogen.Cross combinations revealed an intermediate responseagainst stripe rust as compared to parents, especially testes,and resistant genes are under the control of additive geneaction. These results indicate that repeated backcross can bea better strategy for accumulation of resistant genes in thesecross combinations. Selection in these cross combinations byfollowing backcrosses with recurrent parents is efficient fordisease resistance in the filial generations. These results arevery much in line with the findings of Afzal et al. (2009) andMahmoud et al. (2015).According to these findings, it can be concluded that highergeneral combining ability and low broad sense heritabilityfor grain yield suggest the presence of additive genes, andexploitation of general combining ability for high grain yieldis important due to presence of additive gene action, and selectionin the filial generations and family rows will be effective. For development of heterotic population, it is important toexploit specific combining ability for dominant gene actionby crossing indigenous genotypes with exotic germplasmwith improved rust resistance, which will be a useful futurebreeding strategyThe authors declare no conflict of interest.Afzal S.N., Haque M.I., Ahmedani M.S., Munir M., Firdous S.S.,Rauf A., Ahmad I., Rattu A.R., Fayyaz M. Resistance potential ofwheat germplasm (Triticum aestivum L.) against stripe rust diseaseunder rainfed climate of Pakistan. Pak. J. Bot. 2009;41(3):1463-1475.Ahmad M.W., Ahmed M.S., Tahir H.N. Combining ability analysis forachene yield and related traits in sunflower (Helianthus annuus L.).Chil. J. Agric. Res. 2012;72(1):21-26. DOI 10.4067/S0718-58392012000100004Ahmadi J.A., Zali A., Yazdi-Samadi B., Talaie A., Ghannadha M.R.,Saeidi A. A study of combining ability and gene effect in breadwheat under drought stress condition by diallel method. Iranian J.Agric. Sci. 2003;34(1):1-8.Akhtar M.A., Ahmad I., Mirza J.I., Rattu A.R., Hakro A.A., Jaffery A.H.Evaluation of candidate lines against stripe and leaf rusts under nationaluniform wheat and barley yield trial 2000–2001. Asian J.Plant Sci. 2002;1:450-453. DOI 10.3923/ajps.2002.450.453.Ali F.K.H., Abdulkhaleq D.A. Inheritance of some growth and yieldtraits in bread wheat using line × tester analysis. J. Zankoy Sulaimani.2019;21(2):131-149. DOI 10.17656/jzs.10763.Ali Y., Khan M.A., Hussain M., Sabir W., Atiq M., Aatif H.M., AhmadS., Ijaz M., Ahmad J.N. Virulence analysis of leaf and striperust populations in Pakistan through avirulence to virulence formula.Arch. Phytopathol. Plant Prot. 2020;53(17-18):844-855. DOI10.1080/03235408.2020.1802565Almutairi M.M. Genetic parameters estimation for some wild wheatspecies and their F1 hybrids grown in different regions of SaudiArabia. Saudi J. Biol. Sci. 2022;29(1):521-525. DOI 10.1016/j.sjbs.2021.09.015.Arshad M., Chowdhry M.A. Impact of environment on the combiningability of bread wheat genotypes. Pak. J. Biol. Sci. 2002;5(12):1316-1320. DOI 10.3923/pjbs.2002.1316.1320Arzu K. Gene action and combining ability in line × tester populationof safflower (Carthamus tinctorius L.). Turk. J. Field Crops. 2017;22(2):197-203. DOI 10.17557/tjfc.356216.Awan S.I., Malik F.A., Siddique M. Combining ability analysis in intervarietalcrosses for component traits in hexaploid wheat. J. Agric.Soc. Sci. 2005;1(4):316-317.Babar M., Ullah H., Afridi K., Raza H., Ali S., Ali M., Subhan G.,Khan J., Khan H. Line × tester analysis for combining ability andidentification of gene action in F2 populations of bread wheat. Int. J.Agric. Biol. 2022;27(6):381-392. DOI 10.17957/IJAB/15.1938.Barbosa-Neto J., Sorrells M., Cisar G. Prediction of heterosis in wheatusing coefficient of parentage and RFLP-based estimates of geneticrelationship. Genome. 1996;39(6):1142-1149. DOI 10.1139/g96-144.Basnet B.R., Crossa J., Dreisigacker S., Pérez-Rodríguez P., Manes Y.,Singh R.P., Rosyara U.R., Camarillo-Castillo F., Murua M. Hybridwheat prediction using genomic, pedigree, and environmental covariablesinteraction models. Plant Genome. 2019;12(1):180051.DOI 10.3835/plantgenome2018.07.0051.Burton G., Devane H. Estimating heritability in tall fescue (Festucaarundinacea), from replicated clonal material. Agron. J. 1953;45(10):478-481. DOI 10.2134/agronj1953.00021962004500100005x.Chen X., Penman L., Wan A., Cheng P. Virulence races of Pucciniastriiformis f. sp. tritici in 2006 and 2007 and development of wheatstripe rust and distributions, dynamics, and evolutionary relationshipsof races from 2000 to 2007 in the United States. Can. J.Plant. Pathol. 2010;32(3):315-333. DOI 10.1080/07060661.2010.499271.Chowdhary M.A., Sajad M., Ashraf M.I. Analysis on combining abilityof metric traits in bread wheat, Triticum aestivum. J. Agric. Res.2007:45(1):11-17.Comstock R., Robinson H. Genetic parameters, their estimation andsignificance. In: Proceedings of the Sixth International GrasslandCongress . Pennsylvania: StateCollege, 1952;248-291.De Mendiburu F., Simon R. Agricole – ten years of an open sourcestatistical tool for experiments in breeding, agriculture and biology.PeerJ PrePrints. 2015:3:e1404v1. DOI 10.7287/peerj.preprints.1404v1.Dragov R.G. Combining ability for quantitative traits related to productivityin durum wheat. Vavilov J. Genet. Breed. 2022;26(6):515-523. DOI 10.18699/VJGB-22-63.Dreisigacker S., Melchinger A., Zhang P., Ammar K., Flachenecker C.,Hoisington D., Warburton M.L. Hybrid performance and heterosisin spring bread wheat, and their relations to SSR-based genetic distancesand coefficients of parentage. Euphytica. 2005;144:51-59.DOI 10.1007/s10681-005-4053-2.Fakthongphan J., Graybosch R.A., Baenziger P.S. Combining abilityfor tolerance to pre-harvest sprouting in common wheat (Triticumaestivum L.). Crop Sci. 2016;56(3):1025-1035. DOI 10.2135/cropsci2015.08.0490.FAOSTAT. Food and Agriculture Organization of the United Nations.Rome : FAOSTAT, 2016.Fasahat P., Rajabi A., Rad J.M., Derera J. Principles and utilizationof combining ability in plant breeding. Biom. Biostat. Int. J. 2016;4(1):1-22. DOI 10.15406/bbij.2016.04.00085.Fellahi Z.E.A., Hannachi A., Bouzerzour H., Boutekrabt A. Line × testermating design analysis for grain yield and yield related traits in breadwheat (Triticum aestivum L.). Int. J. Agron. 2013;2013:201851. DOI10.1155/2013/201851.Figueroa M., Dodds P.N., Henningsen E.C. Evolution of virulence inrust fungi – multiple solutions to one problem. Curr. Opin. PlantBiol. 2020;56:20-27. DOI 10.1016/j.pbi.2020.02.007.Fonseca S., Patterson F.L. Hybrid vigour in seven parent diallel crossesin common wheat (Triticum aestivum L.). Crop Sci. 1968;8(1):85-89. DOI 10.2135/cropsci1968.0011183X000800010025xGorjanović B.M., Kraljević-Balalić M.M. Inheritance of plant height,spike length and number of spikelets per spike in durum wheat. Proc.Nat. Sci. Matica Srpska Novi Sad. 2007;112:27-33. DOI 10.2298/ZMSPN0712027G.Gowda M., Kling C., Würschum T., Liu W., Maurer H.P., Hahn V.,Reif J.C. Hybrid breeding in durum wheat: heterosis and combiningability. Crop Sci. 2010;50(6):2224-2230. DOI 10.2135/cropsci2009.10.0637.Hallauer A.R., Carena M.J., Miranda Filho J.D. Quantitative Geneticsin Maize Breeding: Handbook of plant breeding. Springer, 1988.Hasnain Z., Abbas G., Saeed A., Shakeel A., Muhammad A., RahimM.A. Combining ability for plant height and yield relatedtraits in wheat (Triticum aestivum L.). J. Agric. Res. 2006;44(3):167-173.Hassan G., Muhammad F., Afridi S.S., Khalil I.H. Combining abilityin F1 generations of diallel cross for yield components in wheat.SarhadJ. Agric. 2007;23(4):937-942.Intikhab A., Awan S.I., Mur L.A.J., Saeed M.S., Ahmed M.S. Molecularand phenotypic analysis of bread wheat varieties in relation todurable rust resistance. Int. J. Agric. Biol. 2021;26(2):329-336. DOI10.17957/IJAB/15.1841.Iqbal A., Khalil I.H., Shah S.M., Kakar A.M.S. Estimation of heritability,genetic advance and correlation for morphological traits inspring wheat. Sarhad J. Agric. 2017;33(4):674-679. DOI 10.17582/journal.sja/2017/33.4.674.679Iqbal M.M. Combining ability analysis in wheat. Pak. J. Agric. Sci.2007;44(1):1-5.Ishaq M., Ahmad G., Afridi K., Ali M., Khan T.U., Shah I.A., AhmadB., Ahmad N., Ahmad I., Saleem A., Miraj M. Combining ability and inheritance studies for morphological and yield contributingattributes through line × tester mating design in wheat (TriticumaestivumL.). Pure Appl. Biol. 2018;7(1):160-168.Javaid M.M., Zulkiffal M., Ali Y., Mehmood A., Ahmed J., Hussain M.,Muhammad F., Sabir W., Tanveer M.H., Yasin O. Impact of environmentaland pathogenic variability on breaking of host rust resistancein wheat cultivars under changing climatic conditions. Adv. Zool.Bot. 2018;6(1):31-40. DOI 10.13189/azb.2018.060104.Jones D.F. Dominance of linked factors as a means of accounting forheterosis. Proc. Natl. Acad. Sci. USA. 1917;3(4):310-312. DOI10.1073/pnas.3.4.310.Kaushik P. Line × tester analysis for morphological and fruit biochemicaltraits in eggplant (Solanum melongena L.) using wild relativesas testers. Agronomy. 2019;9(4):185. DOI 10.3390/agronomy9040185.Kempthorne O. An Introduction to Genetic Statistics. New York: JohnWiley and Sons, 1957.Khan A., Ahmad M., Shah M.K.N., Ahmed M. Genetic manifestationof physio-morphic and yield related traits conferring thermotolerancein wheat. Pak. J. Bot. 2020;52(5):1545-1552. DOI 10.30848/PJB2020-5(27).Khan S.N., Hassan G., Khan M.R., Facho Z.H., Singh D., Sandhu K.S.,Sanaullah M., Imtiaz M., Ali S. Field assessment and molecularmarkers-based characterization of yellow rust resistance in wheathybrid progenies. J. Anim. Plant Sci. 2022;32(1):127-137. DOI10.36899/JAPS.2022.1.0409.Knott D.R. Heterosis in seven wheat hybrids. Can. J. Plant Sci. 1965;45:499-501.Kumar R., Silva L. Light ray tracing through a leaf cross section. Appl.Opt. 1973;12(12):2950-2954. DOI 10.1364/AO.12.002950.Large E.C. Growth stages in cereals illustration of the Feekes scale.Plant Pathol. 1954;3(4):128-129. DOI 10.1111/j.1365-3059.1954.tb00716.x.Lerner I.M. Genetic Homeostasis. New York: John Wiley and Sons,1954Liu Z., Pei Y., Pu Z. Relationship between hybrid performance andgenetic diversity based on RAPD markers in wheat (Triticum aestivumL.). Plant Breed. 1999;118(2):119-123. DOI 10.1046/j.1439-0523.1999.118002119.x.Mahantashivayogayya K., Hanchinal R., Salimath P. Combining abilityin dicoccum wheat. Karnataka J. Agric. Sci. 2004;17(3):451-454.Mahmoud A.F., Hassan M.I., Amein K.A. Resistance potential of breadwheat genotypes against stripe rust disease under Egyptian climate.Plant Pathol. J. 2015;31(4):402-413. DOI 10.5423/PPJ.OA.12.2014.0127.Malik M.F.A., Awan S.I., Ali S. Genetic behaviour and analysis ofquantitative traits in five wheat genotypes. J. Agric. Soc. Sci. 2005;1(4):313-315.Nazir S., Khan A.S., Ali Z. Combining ability analysis for yield contributingtraits in bread wheat. J. Agric. Soc. Sci. 2005;1:129-132.Okello D.K., Manna R., Imanyowoha J., Pixley K., Edema R. Agronomicperformance and breeding potential of selected inbred linesfor improvement of protein quality of adapted Ugandan maize germplasm.African Crop Sci. J. 2006;14(1):37-47.Pal B., Alam N. The effect of certain external factors upon the manifestationof hybrid vigour in wheat. Proc. Indian Acad. Sci. 1938;7:109-124. DOI 10.1007/BF03051095Patel P.U., Patel B.C., Sidapara M.P., Sharma D.D. Combining abilityand gene action studies for yield and its component traits in breadwheat (Triticum aestivum L.). Int. J. Curr. Microbiol. Appl. Sci.2020;9:2463-2469.Peterson R.F., Campbell A.B., Hannah A.E. A diagrammatic scale forestimating rust intensity on leaves and stems of cereals. Can. J. Res.1948;26(5):496-500. DOI 10.1139/cjr48c-033.Qamar M., Ahmad S.D., Rabbani M.A., Shinwari Z.K., Iqbal M. Determinationof rust resistance genes in Pakistani bread wheats. Pak. J.Bot. 2014;46(2):613-617.Rashid M., Cheema A.A., Ashraf M. Line × tester analysis in Basmatirice. Pak. J. Bot. 2007;39(6):2035-2042.Rashmi K., Prasad L.C., Prasad R., Thakur P., Chandra K. Inheritancestudy of yield traits and spot blotch disease resistance in wheat underepiphytotic environment. Plant Arch. 2020;20(2):6590-6594.Raza W., Ghazanfar M.U., Rehman A.U., Fayyaz M. Screening ofwheat germplasm against stripe rust disease under field conditionsin Pakistan. Plant Prot. 2018;2(3):87-92.Reynolds M.P., Singh R.P., Ibrahim A., Ageeb O.A.A., Larque-SaavedraA., Quick J.S. Evaluating the physiological traits to complementempirical selection for wheat in warm environments. Euphytica.1998;100:85-94. DOI 10.1023/A:1018355906553.Saeed A., Chowdhry M.A., Saeed N., Khaliq I., Johar M.Z. Line × testeranalysis for some morpho-physiological traits in bread wheat. Int. J.Agric. Biol. 2001;3(4):444-447.Saeed M.S., Chowdhry M.A., Ahsan M. Genetic analysis for some metrictraits in Aestivum species. Asian J. Plant Sci. 2005;4(4):413-416.DOI 10.3923/ajps.2005.413.416.Shamsuddin A K. Genetic diversity in relation to heterosis and combiningability in spring wheat. Theor. Appl. Genet. 1985;70:306-308.Sharma A., Garg D. Combining ability over environments in breadwheat (Triticum aestivum L.). J. Maharasahtra Agric. Univ. 2005;30(2):153-156.Shull G.H., East E.M. The composition of a field of maize. J. Hered.1908;4(1):296-301. DOI 10.1093/jhered/os-4.1.296.Singh R.K., Chaudhary B.D. Biometrical Methods in Quantitative GeneticAnalysis. New Delhi: Kalyani Publ., 1977.Singh S., Singh L., Singh D., Kumar R. Combining ability in commonwheat (Triticum aestivum L.) grown in sodic soil. Progress. Agric.2003;3:78-80.Sprague G.F., Tatum L.A. General vs. specific combining ability insingle crosses of corn. Agron. J. 1942;34(10):923-932.Steel R.G.D., Torrie J.H. Principles and Procedures of Statistics. NewYork: McGraw Hill Book Company Inc., 1980.Sultana S.R., Ali A., Ahmad A., Mubeen M., Zia-Ul-Haq M., Ahmad S.,Ercisli S., Jaafar H.Z. Normalized Difference Vegetation Index as atool for wheat yield estimation: a case study from Faisalabad, Pakistan.Sci. World J. 2014;2014:725326. DOI 10.1155/2014/725326.The R Project for Statistical Computing. A language and environmentfor statistical computing R foundation for Statistical Computing Departmentof Agronomy, Faculty of Agriculture of the University ofthe Free State. Vienna, Austria, 2017. www.r-project.org.Tilley M.S., Heiniger R.W., Crozier C.R. Tiller initiation and its effectson yield and yield components in winter wheat. Agron. J.2019;111(3):1323-1332. DOI 10.2134/agronj2018.07.0469.Uddin M.N., Ellison F.W., O’Brien L., Latter B.D.H. Heterosis inF1 hybrids derived from crosses of adapted Australian wheats. Aust.J. Agric. Res. 1992;43(5):907-919. DOI 10.1071/AR9920907.Ullah N., Ullah H., Afridi K., Alam M., Jadoon S.A., Khan W.U., AhmadM., Uddin H. Genetic variability, heritability and correlationanalysis among morphological and yield traits in wheat advancedlines. Biol. Divers. Conserv. 2018;11(1):166-180.Zhao Y., Zeng J., Fernando R., Reif J.C. Genomic prediction of hybridwheat performance. Crop Sci. 2013;53(3):802-810. DOI 10.2135/cropsci2012.08.0463


Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacterales with resistance to carbapenems or third-generation cephalosporins. The aim of the present study was to investigate the in vitro activity of the novel siderophore cephaloporin cefiderocol (CID) and four comparator β-lactam-β-lactamase-inhibitor combinations and to give insights into the genetic background of CID-resistant isolates. In total, 301 clinical Enterobacterales and non-fermenting bacterial isolates were selected for this study, including randomly chosen isolates  and challenge isolates . Isolates displayed CID MIC50/90 values of 0.12/0.5 mg/L (set I) and 0.5/1 mg/L (set II). Overall, the CID activity was superior to the comparators against A. baumannii, Stenotrophomonas maltophilia and set II isolates of P. aeruginosa. There were eight CID-resistant isolates detected (MIC > 2 mg/L): A. baumannii (n = 1), E. cloacae complex (n = 5) and P. aeruginosa (n = 2). Sequencing analyses of these isolates detected the acquired β-lactamase (bla) genes blaNDM-1, blaSHV-12 and naturally occurring blaOXA-396, blaACT-type and blaCMH-3. In conclusion, CID revealed potent activity against clinically relevant organisms of multidrug-resistant Enterobacterales and non-fermenters. Antimicrobial resistance poses a global threat to public health. Of great concern are  Acinetobacter baumannii (carbapenem-resistant), Pseudomonas aeruginosa (carbapenem-resistant) and the order of Enterobacterales (carbapenem-resistant and ESBL-producing) [Stenotrophomonas maltophilia [The emergence of antibiotic-resistant bacteria has been described as one of the biggest threats to global health and food safety ,2. It isoducing) . Variousoducing) ,7. New aoducing) ,9. Howevtophilia ,9. P. aeruginosa [A. baumannii (CRAB), P. aeruginosa and S. maltophilia, as well as carbapenem-resistant Enterobacterales [Klebsiella pneumoniae or OXA-23 in A. baumannii), show the weak hydrolysis of CID [P. aeruginosa and Enterobacter cloacae complex, which could otherwise cause resistance development under therapy [Cefiderocol (CID) is a novel parenteral cephalosporin carrying a catechol moiety at the 3-position side chain . It has ruginosa . It is tcterales , with his of CID . Further therapy ,15,16. C therapy ,18. In vitro data of CID from Germany are scarce. In our previous study published in 2020, CID was found to inhibit 97.2% of a randomly chosen collection of 213 Gram-negative clinical isolates of different species at the investigational susceptibility breakpoint of ≤2 mg/L . The isoThe present study aimed (I) to investigate the in vitro activity of CID against Gram-negative pathogens recovered from patients during a more recent multicentre surveillance study conducted by the PEG in 2016/17 and (II) to compare it with the susceptibility against novel β-lactam–β-lactamase-inhibitor (BL-BLI) combinations. 50 and MIC90) and the number and percent of susceptible and resistant isolates were calculated with the available breakpoints of the European Committee on Antimicrobial Susceptibility Testing (EUCAST) (P. aeruginosa) of ≤2 mg/L or the non-species-related pharmacokinetic–pharmacodynamic (PK/PD) breakpoint of ≤ 2 mg/L was applied .MIC distribution data of CID are presented in (EUCAST) . OverallEnterobacterales isolates, CID inhibited 98.2% (109/111)  was determined for a respiratory E. cloacae complex isolate (PEG-16-51-23) that originated from a nosocomial infection. Sequencing revealed that this isolate encoded the extended-spectrum β-lactamase SHV-12. There were two more isolates detected with CID MICs > 2 mg/L: an NDM-1-encoding P. aeruginosa (PEG-16-96-12) and another E. cloacae complex (PEG-16-75-70) harbouring blaSHV-12 (both MICs 4 mg/L). Among the 111 109/111) . In compP. aeruginosa isolates, with 89.7% of the isolates being inhibited at the respective breakpoint (R > 8 mg/L). The susceptibility rates of P. aeruginosa against the other agents were comparable to that seen with the Enterobacterales: 98.3% (CID), 96.6% (IMR), 94.8% (CTV) and 91.4% (CTT)  was more active than CTT (1/4 mg/L), CTV (2/8 mg/L), IMR (0.5/2 mg/L) or MEV (1/≥ 16 mg/L). Of the nine A. baumannii isolates, all were inhibited by CID at ≤0.5 mg/L. Based on the MIC50/90 values, all comparator compounds were less active with MIC50 values of 0.5–≥ 16 mg/L and MIC90 values of ≥16 mg/L. Two OXA-23-encoding A. baumannii isolates (PEG-16-19-60 and PEG-16-22-42) were resistant to IMR (R > 2 mg/L) and exhibited MEV MICs of 16 mg/L. Among the S. maltophilia (n = 17) isolates, CID MICs ranged from ≤0.03 to 2 mg/L, with MIC50/90 values of 0.06 mg/L and 0.5 mg/L. In comparison, all four comparators were less active in S. maltophilia with MIC50/90 values of ≥16 mg/L. Compared to Enterobacterales, MEV was less effective against the 58 4% (CTT) . Based o50/90 and susceptibility/resistance rates, where applicable).The results of set II isolates are displayed together with set I in P. aeruginosa) of ≤2 mg/L or the non-species-related PK/PD breakpoint (A. baumannii) of ≤2 mg/L was applied. There were five isolates detected with MICs > 2 mg/L A. baumannii , E. cloacae complex  and P. aeruginosa . Whole-genome sequencing analysis detected the presence of carbapenemase gene blaNDM-1 in the A. baumannii isolate together with disrupted oprD and piuA genes. The resistant P. aeruginosa isolate harboured blaOXA-396, a variant of the chromosomal class D OXA-50-group in this species, together with the class A β-lactamase PDC-8, and carried a disrupted oprD. The three E. cloacae complex isolates were only positive for class C ACT-type β-lactamases or CMH-3, which naturally occur in E. cloacae.The CID MICs ranged from ≤0.03 to 32 mg/L, with an overall susceptibility rate of 95.3% (101/106) if the specifies-specific EUCAST susceptibility breakpoint , 51.3% (CTV), 46.2% (IMR) and 35.9% (MEV), while CID inhibited 97.4% (38/39) of P. aeruginosa isolates. Among the CRAB isolates, CID revealed the most potent activity compared to the other compounds with MIC50/90 values of 0.12/2 mg/L as opposed to ≥16/≥16 mg/L.Among the 53 Enterobacterales isolates, 100% were susceptible to MEV, 98.1% were susceptible to both CTV and IMR and 77.4% were susceptible to CTT. With a susceptibility rate of 94.3% (50/53), CID exhibited slightly lower activity compared to CTV and IMR in Enterobacterales. Overall, the comparator agents were similar or less effective in the 39 The CID MIC distributions of ESBL-producing isolates, carbapenemase-producing isolates and colistin-resistant isolates from set I and II are summarized in 50/90 values of 0.5/1 mg/L. There was no difference in CID MIC distribution with regard to different resistance genes, with the exception of two blaNDM-1-encoding isolates (A. baumannii and P. aeruginosa) and two SHV-12-encoding E. cloacae complex isolates with CID MICs > 2 mg/L. With the exception of CTT, the comparator compounds revealed similar activity against ESBL-producing isolates compared to CID. The MIC50/90 values were 0.25/0.5 mg/L for CTV, 0.12/0.25 mg/L for IMR and ≤0.06/0.12 mg/L for MEV. The CID susceptibility in 47 ESBL-encoding isolates ranged from ≤0.03 mg/L to ≥64 mg/L, with MICThe overall CID susceptibility of the 47 ESBL-encoding Enterobacterales isolates was 95.7% (45/47). CTV, IMR and MEV were able to inhibit 100% of the isolates at their respective breakpoints, with only the CTT susceptibility being lower at 85.1%. 50/90 values were 0.5/2 mg/L. Fourteen of fifteen carbapenemase-producing A. baumannii isolates (93.3%) were inhibited at a CID concentration ≤ 2 mg/L. Regarding carbapenemase-producing P. aeruginosa isolates, 91.7% (11/12) exhibited CID susceptibility. CID-resistant isolates of both species (A. baumannii PEG-16-19-65 and P. aeruginosa PEG-16-96-12) encoded blaNDM-1 and revealed MIC values of the comparator substances of 16 mg/L each. With the exception of one A. baumannii isolate, all carbapenemase-encoding isolates were susceptible to colistin. The colistin-resistant isolate (MIC 8 mg/L) was susceptible to CID but resistant to all of the other tested compounds. Overall, the comparators revealed reduced activity in carbapenemase-encoding isolates compared to CID with MIC50/90 values greater or equal to their highest concentration tested. Among the 30 carbapenemase-producing isolates, CID MICs ranged from ≤0.03 to 32 mg/L, with 93.3% (28/30) of the isolates being inhibited at a concentration of ≤2 mg/L. The MIC50/90 values of 0.25/1 mg/L. Based on MIC50/90 values, CID activity was comparable to CTT (0.5/2 mg/L), CTV (0.5/4 mg/L) and IMR (0.25/1 mg/L). The distribution of MEV MICs revealed a lower MIC50 value compared to the other compounds (MIC50/90s: ≤0.06/2 mg/L). All colistin-resistant P. aeruginosa isolates (n = 14) were inhibited by CID and the comparator substances. The two colistin-resistant A. baumannii isolates (PEG-16-36-64 and PEG-16-50-50) were inhibited by a CID concentration < 2 mg/L but revealed different MIC results with regard to the comparator substances. PEG-16-36-64 was susceptible against all the other substances (MIC range 0.25–0.5 mg/L), while the blaOXA-23-like-positive PEG-16-50-50 exhibited MIC values of 16 mg/L against CTT, CZA, IMR and MEV.In colistin-resistant isolates (n = 37), CID MICs ranged from ≤ 0.03 to 4 mg/L, with MICA. baumannii and P. aeruginosa, as well as Enterobacterales species with acquired resistance against carbapenems or third-generation cephalosporins, all possessing a high risk of severely limited treatment options. In contrast to resistance against third-generation cephalosporins, carbapenem resistance is still rarely encountered in Enterobacterales species such as E. coli and K. pneumoniae in Germany. For example, the surveillance study originated by the Paul-Ehrlich-Society for Infection Therapy in 2016/17 revealed resistance rates of 0% against imipenem and meropenem in 571 E. coli isolates and 1.6% (5/318) against both substances in K. pneumoniae isolates. According to the annual surveillance data for Germany reported to the European Centre for Disease Prevention and Control (ECDC), the rates of carbapenem-resistant E. coli and K. pneumoniae isolates were 0.0% and 0.8% in 2021  compared to resistance rates against third-generation cephalosporins of 9.1%  and 10.4% (678/6538) (Surveillance Atlas of Infectious Diseases (europa.eu); data source: invasive isolates). In Acinetobacter spp. and P. aeruginosa, carbapenem-resistance was more frequently detected with 4.3% (26/605) and 14.8% (425/2864), respectively.The WHO has designated antimicrobial resistance as one of the top ten global public health threats. Of great concern are carbapenem-resistant non-fermenting Gram-negative bacteria such as A. baumannii, MBL-producing organisms and S. maltophilia, which is intrinsically resistant against multiple antimicrobial agents, including carbapenems [The antimicrobial agents compared in this study are considered promising compounds in the treatment of infections with the above-mentioned organisms when no other options are available. In contrast to the comparators, CID possesses activity against a variety of Gram-negative species and β-lactamases of all Ambler classes, including OXA-encoding bapenems . Unlike 50/90s 0.12/0.5 mg/L) and 95.3%  at ≤2 mg/L  were inhibited by CID at a concentration of ≤2 mg/L, while there was only one isolate detected among fourteen CRAB isolates (set II) with an MIC of >2 mg/L. However, due to the small sample size of S. maltophilia and A. baumannii, these data should be considered with caution. Naas et al. investigated a total number of 103 S. maltophilia and 161 A. baumanni isolates and reported comparable CID activity against both species and almost identical MIC50/90 values of 0.06 mg/L and 0.25 mg/L [S. maltophilia [50/90 values of 0.06/0.25 mg/L. However, studies on CRAB yielded conflicting results. A recent study by Mushtaq et al. investigated 99 A. baumannii isolates encoding various OXA-β-lactamases, with the majority being OXA-23 (n = 41), as well as NDM enzymes (n = 20) [A. baumannii (n = 25), while isolates harbouring OXA-58 or OXA-23 were all susceptible (n = 75) [Our study observed more potent CID activity against parators . Similar.25 mg/L . Karlowstophilia . They deA. baumannii and P. aeruginosa) and SHV-12 (E. cloacae complex), or the naturally occurring β-lactamases such as class C ACT-type, CMH-3 (both E. cloacae), as well as PDC-8 together with class D OXA-396 (P. aeruginosa)  . The cor0.5 mg/L ,27. In oruginosa ,29. FurtblaNDM-1 might be an exception to this and requires further investigation. CID activity was superior to the comparators against A. baumannii, S. maltophilia and challenge isolates of P. aeruginosa. In addition to ESBL-producing isolates, the majority of CP-producing and colistin-resistant isolates were inhibited at a CID concentration ≤2 mg/L, indicating good activity of CID in clinically relevant organisms. In conclusion, CID revealed potent activity against Enterobacterales and non-fermenting Gram-negative bacterial isolates from Germany. The association of CID non-susceptibility with a particular resistance determinant seemed to be unlikely, while the presence of In total, 301 Gram-negative bacterial isolates were investigated in this study. All isolates were obtained from patient samples collected at 22 German microbiological laboratories during a multicentre surveillance study conducted by the PEG in 2016/17. The majority of laboratories were affiliated with tertiary-care medical centres. Two sets of isolates were selected: random samples (set I) and challenge organisms (set II).E. coli (n = 52), K. pneumoniae (n = 34) and E. cloacae complex (n = 25) isolates. The non-fermenting bacteria included A. baumannii (n = 9), P. aeruginosa (n = 58) and S. maltophilia (n = 17) isolates. Set I included 195 isolates  which encompassed 111 Enterobacterales and 84 non-fermenting bacteria which were obtained from the respiratory tract (n = 117) and from blood culture (n = 78). Isolates were randomly selected; routine clinical isolates, also including ESBL- and carbapenemase-producing isolates; as well as colistin-resistant isolates. The Enterobacterales included E. coli and five K. pneumoniae isolates were ESBL producers, which were investigated via PCR/Sanger sequencing or whole-genome sequencing in different reference laboratories as part of the PEG study. All of the ESBL K. pneumoniae isolates as well as five ESBL E. coli isolates carried the blaCTX-M-15 gene. Additionally, three of these K. pneumoniae isolates also encoded SHV-40 (n = 1) or SHV-28 (n = 2). The remaining ESBL E. coli isolates carried blaCTX-M-1 (n = 4) or blaCTX-M-27 (n = 1). Few isolates of set I encoded carbapenemases: K. pneumoniae (n = 1) encoded VIM-1, A. baumannii (n = 2) encoded OXA-23 and P. aeruginosa (n = 1) encoded NDM-1. Seven Isolates were colistin-resistant (E. cloacae (n = 3), E. coli (n = 1) and K. pneumoniae (n = 3)).Among the Enterobacterales, ten A. baumannii and P. aeruginosa isolates with a meropenem MIC above 8 mg/L and Enterobacterales that were either ertapenem-resistant (R > 0.5 mg/L) and/or possessed a meropenem MIC of >0.12 mg/L . In contrast to set I, isolates of set II were especially enriched for ESBL- and carbapenemase-producing isolates as well as colistin-resistant isolates. The investigation of resistance genes was part of the multicentre study conducted by the PEG and was performed via PCR/Sanger sequencing or whole-genome sequencing in different reference laboratories [A. baumannii isolates of this set encoded the following β-lactamases: NDM-1 (n = 1), OXA-58 (n = 1), or OXA-23 (n = 11). The E. coli isolates of this set produced CTX-M-1 (n = 3), CTX-M-14 (n = 2), CTX-M-15 (n = 9), CTX-M-15 plus CTX-M-27 (n = 1), CTX-M-27 (n = 3), or CTX-M-55 (n = 1). P. aeruginosa isolates of this set encoded the following β-lactamases: GIM-1 (n = 2), IMP-7 (n = 2), IMP-13 (n = 1), VIM-1 (n = 2), VIM-2 (n = 3) and VIM-5 (n = 1). K. pneumoniae isolates of this set encoded the following β-lactamases: CTX-M-3 (n = 1), CTX-M-15 (n = 10) and VIM-1 (n = 1). One E. cloacae complex isolate encoded OXA-48.Set II comprised 53 Enterobacterales and 53 non-fermenting bacteria with either confirmed carbapenemases or ESBL genes or with phenotypic colistin resistance or „meropenem non-susceptibility”. „Meropenem-non-susceptible” isolates included ratories ,31. A. bThe verification of species identification was performed via matrix-assisted laser desorption ionization–time of flight (MALDI-TOF) mass spectrometry .5 CFU/mL (range 2–8 × 105). Panels were incubated at 35 ± 1°C for 18 ± 2 h. The MICs were read visually and, as far as possible, interpreted according to the species-specific clinical breakpoints approved by the EUCAST , I  and R (resistant) [P. aeruginosa of ≤2 mg/L (S) and >2 mg/L (R) were applied. For other species, the EUCAST-approved pharmacokinetic–pharmacodynamic  breakpoints were applied (≤2 mg/L (S) and >2 mg/L (R)). Reference strains E. coli ATCC 25922 and P. aeruginosa ATCC 27853 were used for quality control. The following antimicrobial agents were tested with the noted ranges: ceftazidime–avibactam (CTV) (0.12/4–8/4 mg/L), ceftolozane–tazobactam (CTT) (0.25/4–8/4 mg/L), imipenem–relebactam (IMR) (0.03/4–8/4 mg/L), meropenem–vaborbactam (MEV) (0.25/8–8/8 mg/L) and cefiderocol 0.06–32 mg/L). MICs were determined using the broth microdilution procedure with geometric twofold serial dilutions according to the international standard ISO 20776-1 [ mg/L. MIsistant) . For CIDIsolates with CID MICs > 2 mg/L were sent to the International Health Management Associates (IHMA) for whole-genome sequencing.p < 0.05 was assumed. The statistical significance of differences in susceptibility rates was judged by comparing 95% confidence intervals (CIs). Intervals were constructed using the Newcombe–Wilson method without continuity correction. If no rate was contained in the CI of the other one, significance of


Tenacibaculum haliotis strain RA3-2T , isolated from Korean wild abalone . As the only strain for this Tenacibaculum species worldwide, the information is of use for comparative genomic analyses delineating Tenacibaculum species.Here, we present the draft genome sequence of  Tenacibaculum isolates are associated with fish (Tenacibaculum crassostreae from the Pacific oyster (Crassostrea gigas)  (Most ith fish . Two mola gigas)  and Tenahannai) .T. haliotis strain, RA3-2T. A sample of RA3-2T was obtained from the Japanese Biological Resource Centre in glass ampoules (L-dried). The strain was grown on marine agar 2216 (BD Difco). The plates were incubated at 20°C for 3 days .DNA was extracted from three colonies using the InstaGene matrix (Bio-Rad) per the manufacturer’s instructions. The 16S rRNA gene was PCR amplified using the universal primer pair 27F and 1492R (The NucleoSpin soil kit (Macherey-Nagel GmbH & Co. KG), purified genomic DNA, and the NanoDrop Lite spectrophotometer were used to measure the DNA concentration (Thermo Fisher Inc.). The genome was sequenced by Macrogen. A DNA library was prepared using the TruSeq Nano DNA kit and sequenced using the Illumina NovaSeq 6000 platform  to generate 31,942,898 paired-end reads with an average length of 151 bp.https://www.bioinformatics.babraham.ac.uk/projects/fastqc/). The next-generation sequencing reads were preprocessed using Geneious Prime v.2020.2.2 software , with a total of 2,977,857 bp and 30.7% G+C content. The quantitated assembly quality indicated a minimum contig length of 1,346 bp, a maximum length of 486,103 bp, and an average length of 102,684 bp. The draft genome sequence contained 2,728 coding DNA sequences (CDSs) with protein, 2,794 genes, 8 pseudogenes, and 61 RNAs , as determined by the NCBI Prokaryotic Genome Annotation Pipeline (PGAP) v.6.2 (https://github.com/ncbi/pgap) using the best-placed reference protein set, with GeneMarkS-2+ as the annotation method. The predicted tRNAs were verified using tRNAscan-SE v.2.0  rea v.5.2.0 . The assin silico genome analysis, genes were discovered with predicted associations to secretion systems (type I [T1SS] and T9SS), as detected using TXSScan . Iron-related protein families were identified  using FeGenie v.1.0 (Using ie v.1.0 . Using tie v.1.0 .JAOBTH000000000. The version described here is JAOBTH010000000. The sequences are publicly available under the BioProject accession number PRJNA877611, BioSample accession number SAMN30712836, and SRA accession number SRR22752080. The GenBank accession number for the 16S rRNA gene sequence is OP381101.This whole-genome shotgun project was deposited at DDBJ/ENA/GenBank under the accession number


Introduction: Varicella-zoster virus (VZV) reactivation was not listed as a side effect of any vaccine until introduction of COVID-19 vaccines. Since COVID-19 vaccines were introduced, several case reports described the link between COVID-19 vaccination and VZV reactivation. In our study we aimed to investigate how often patients developed VZV reactivation after mRNA COVID-19 vaccine compared to influenza vaccine.We used the TriNetX platform and its global health research network containing aggregated de-identified information of electronic health records on over 100 million patients from scores of healthcare organizations. Three patient groups were identified:st mRNA COVID-19 vaccine 12/20/2020-12/20/2022Patients receiving their 1nd mRNA COVID-19 vaccine 12/20/2020-12/20/2022Patients receiving their 2Patients receiving influenza vaccine 12/20/2018-12/20/2022Propensity Score Matching was used for age, gender, and Zoster vaccine status.We examined the prevalence of VZV reactivation in each group during the first 21 days following vaccination.st mRNA COVID-19 vaccine or the Influenza vaccine, 0.04% in the COVID-19 vaccine group and 0.15% in the influenza group, odds ratio (OR) 0.24 (95% CI 0.20-0.29), were diagnosed with VZV reactivation within 21 days. Among 445,382 patients in each matched group receiving either their 2nd mRNA COVID-19 vaccine or their influenza vaccine, 0.04% in the COVID-19 vaccine group and 0.13% in the Influenza group, OR 0.27 (95% CI 0.22-0.32), were diagnosed with VZV reactivation within 21 days. There was a lower risk of VZV reactivation after 1st or 2nd dose of mRNA COVID-19 vaccine than influenza vaccine.Out of 444,016 patients in each matched group receiving either their 1st or 2nd dose of mRNA COVID-19 vaccination is smaller than VZX reactivation after influenza vaccine. The risk of VZV reactivation after mRNA COVID-19 vaccine is very low and hesitance to receive COVID-19 vaccine due to concern of VZV reactivation is not substantiated.The risk of VZV reactivation after the 1David C. Kaelber, MD, PhD, MPH, FAAP, FACP, FACMI, FAMIA, Becton, Dickinson and Company: Advisor/Consultant|Dynavax Technologies Corporation: Advisor/Consultant|Merck Sharp & Dohme Corporation: Advisor/Consultant


Under many kinds of stress, eukaryotic cells rapidly decrease the overall translation level of the majority of mRNAs. However, some molecular mechanisms of protein synthesis inhibition like phosphorylation of eukaryotic elongation factor 2 (eEF2), which are known to be functional in animals and yeast, are not implemented in plants. We suggest that there is an alternative mechanism for the inhibition of protein synthesis in plant cells and possibly, in other eukaryotes, which is based on the discrete fragmentation of 18S rRNA molecules within small ribosomal subunits. We identified four stress-induced small RNAs, which are 5’- and 3’-terminal fragments of 18S rRNA. In the present work, we studied the induction of 18S rRNA discrete fragmentation and phosphorylation of the α-subunit of eukaryotic initiation factor 2 (eIF2α) in germinated wheat embryos in the presence of glyphosate, which imitates the condition of amino acid starvation. Using northern and western blotting, we have shown that stress-induced 18S rRNA fragments started to accumulate in wheat embryos at glyphosate concentrations that did not evoke eIF2α phosphorylation. It was also found that cleavage of 18S rRNA near the 5’-terminus began much earlier than eIF2α phosphorylation, which became noticeable only at higher concentration (500 μM) of glyphosate. This result suggests that discrete fragmentation of 18S rRNA may constitute a regulatory mechanism of mRNA translation in response to stress and may occur in plant cells in parallel with and independently of eIF2α phosphorylation. The identified small 5’- and 3’-terminal fragments of 18S rRNA that accumulate during various stresses may serve as stress resistance markers in the breeding of economically important plant crops. Protein biosynthesis is a very energy-intensive process,so under stress conditions, the translation of most cellularmRNAs is inhibited in order to save energy and resources andto ensure preferential synthesis of stress proteins. Several molecularmechanisms of protein synthesis inhibition have beendescribed in mammalian and yeast cells. One of these mechanismsis the eukaryotic translation elongation factor 2 (eEF2)phosphorylation, which is carried out by a highly specific proteinkinase in response to a sharp decrease in cytosolic ATPconcentration levels. Phosphorylation inactivates mammalianeEF2 by preventing it from binding to the ribosome . However, plants do not exhibit endogenous kinaseactivity for eEF2 either under normal conditions , or under stress .The second mechanism known in animals to reduce the levelof mRNA translation is triggered under conditions of aminoacid starvation and is mediated by eIF4E-binding proteins(4E-BPs), which prevent eIF4E from binding to the m7Gcapstructure of mRNA . However,no clear homologs of these eIF4E-BPs have yet been foundin plants , nor were anyorthologues of the 4E-BPs genes found in plant genomes.Another important mechanism of eukaryotic protein synthesisinhibition is the phosphorylation of the α-subunit ofeukaryotic initiation factor 2 (eIF2α) by specific protein kinases.This process in mammalian and yeast cells leads tothe blocking of GDP → GTP exchange protein eIF2B and toa sharp inhibition of the mRNA translation initiation . However, recycling of the ternary complex inplant cells can occur without the participation of eIF2B , and eIF2α phosphorylation in plant systemsin vitro does not lead to strong inhibition of protein synthesis. In addition, of the four protein kinases that phosphorylate theeIF2α in mammalian cells, only pGCN2-kinase was foundin plants, and the phosphorylation of eIF2α in plants is not auniversal response to all stress types .Thus, the mechanisms of protein biosynthesis suppressiondue to the phosphorylation of translational factors, which arewell described for mammals and yeast, are either used to alimited extent or are not realized at all in plant cells. We suggestthat another mechanism of protein synthesis inhibitioncan function in plants, which is triggered by certain abiotic andbiotic stresses. In our understanding, this mechanism is associatedwith the cleavage at certain sites of the 18S rRNA as partof 40S ribosomal subunits (40S RS). Previously, we describedthe process of 18S rRNA cleavage, leading to 5′-terminal fragmentsformation of 132–134 nt. and of 54–57 nt. , as well as a 3′-terminalfragment of 100 nt. . Our data arequite consistent with the data of full-transcriptome analysis,which showed that breaks in 28S-, 18S-, and 5.8S-rRNA donot occur randomly, but discretely, which leads to the fact thatsome fragments of ribosomal RNA are detected in the cell significantlymore often than other fragments .The process of RNA cleavage is widely used by cells duringthe processing of ribosomal RNA from their precursor duringribosome biogenesis . In addition, in proandeukaryotic organisms, the mechanism of protein biosynthesissuppression is realized due to the cleavage of the 28SrRNA molecule from the large (60S) ribosomal subunit alongthe sarcin-ricin loop with the cleavage of the 3′-terminal EndorRNA-fragment . Toxins of plants , fungi (α-sarcin) and bacteria (Shiga toxin) actthis way . Possibly similar endonucleasesand/or glycosylases  are activatedin plant cells during stress, but targeting 18S rRNA in 40S RSinstead of 28S rRNA in 60S RS, and thus leading to temporaryor permanent suppression of mRNA translation.In this work, we have shown that in the case of glyphosatemediatedamino acid starvation, when the only specific eIF2αkinase of plants (pGCN2-kinase) is activated, in addition toplant eIF2α phosphorylation, another protective mechanismis triggered in plant cells, namely, discrete fragmentation of18S rRNA. It was shown that the accumulation in plants of18S rRNA 5′-terminal fragments of 75 nucleotides (75nt-5′18S) and 134 nucleotides (134nt-5′18S) begins earlier thanthe activation of pGCN2 kinase and becomes noticeable atrelatively low concentrations of glyphosate when plant eIF2αphosphorylation does not occur at all.Plant material and treatment. Wheat (Triticum aestivum L.cv. Kazakhstanskaya 10) seeds were sterilized in 70 % (v/v)ethanol for 2 min, then in 2 % (w/v) NaOCl for 20 min, andwashed thoroughly with sterile water. Seeds were germinatedat 26 ºС on sterile filter paper soaked in water. After 18 hours,viable embryos were isolated by spatula from swollen seedsand placed in 1 % glucose solution containing 50 U/ml penicillin,50 μg/ml chloramphenicol, and 50 μg/ml nystatin. Afterthis, embryos were divided into equal portions (1 g), whichwere subjected to treatment with glyphosate (simulation ofamino acid starvation) or without any additives (control).Synthesis of probes. DIG-labeling of de novo synthetizedoligodeoxyribonucleotides 5′18S (5′-ACAAGCATATGACTACTGGCAGGATCAACCAGGTA) and 3′18S (5′-CAATGATCCTTCCGCAGGTTCACCTACGGAAACCT)was carried out using DIG Oligonucleotide 3′-End LabelingKit (Roche) according to the manufacturer’s manual. Probes(5′18S-DIG and 3′18S-DIG) were used for northern blottingNorthern blotting. Total RNA was extracted from planttissues with Tri-reagent (Sigma Aldridge) and analyzed on10 % PAGE with 8 M urea in Tris-borate buffer . RNAs were blottedto a nylon membrane (Roche) equilibrated in 0.1x TBEusing a semi-dry blotter (Sci-Plas) at 250 mA for 30 min.The membrane was dried and irradiated with UV light for2 min at 10 mJ/cm2 in a crosslinker (UVP). Hybridization ofDIG-labeled probes and subsequent chemiluminescent banddetection was performed with DIG Luminescent DetectionKit for Nucleic Acids (Roche) according to the manufacturer’sprocedure. The hybridization temperature was 55 °C.Anti-Digoxigenin-AP Fab fragment conjugates (Roche) wereused to detect bound DIG-labeled probes. The blots weredeveloped using a commercial alkaline phosphatase substrateCSPD (Roche).SDS-polyacrylamide gel electrophoresis (SDS-PAGE)and immunoblotting. Frozen embryos were ground toa powder in a mortar and then homogenized in Laemmlisample buffer . Proteins were separated by12.5 % SDS-PAGE with 0.1 % SDS. The separated proteinswere transferred to a nitrocellulose membrane (GVS) thatwas afterwards stained with Ponceau S (Sigma-Aldrich). Theantibodies against human phospho-eIF2α (S51) produced inrabbit  were used for theimmune-detection of phosphorylated T. aestivum (Ta) eIF2α(TaeIF2(αP)). Then horseradish peroxidase-conjugated antirabbitsecondary antibodies produced in donkey  were used.The effect of glyphosate concentration on 18S rRNA fragmentationin wheat embryos. Since the mechanisms ofmRNA translation inhibition mediated by 4E-BPs and eEF2Kare not implemented in plants, it is believed that the mainresponse in plants to amino acid starvation is eIF2α phosphorylationwith pGCN2 kinase . To testwhether the process of discrete fragmentation of 18S rRNAis also induced under these conditions, the herbicide glyphosatewas used. Glyphosate targets 5-enolpyruvoylshikimate3-phosphate synthase, which catalyzes the key penultimatereaction in the shikimate pathway .Therefore, it inhibits the synthesis of many aromatic plantmetabolites including the amino acids tryptophan, tyrosine,and phenylalanine and leads to pGCN2 kinase activationand phosphorylation of the plant eIF2α .Germinated wheat embryos were treated with glyphosate atvarious concentrations, after which the content of 18S rRNAsmall fragments and the phosphorylation status of TaeIF2αwere assessed in their cells. The results are present in Figure 1.Phosphorylation of TaeIF2α becomes noticeable only atrelatively high concentrations (0.5 and 5 μM) of glyphosate, at which wheatembryos stopped to grow . Theappearance of 3′-terminal fragments 100nt-3′18S and 70nt-3′18S was observed at the same concentrations of glyphosate. At the same time,5′-terminal fragments of 18S rRNA, 134nt-5′18S and 75nt-5′18S, began to accumulate in noticeable amounts even atvery low concentrations (5 μM) of glyphosate .The results of semi-quantitative optical densitometry analysisfor this experiment are presented in Table 1. Since the 134nt-5′18S fragment can be a precursor of 75nt-5′18S, and the100nt-3′18S fragment can act as a precursor for 70nt- 3′18S,it is reasonable to estimate the sum of these small 18S rRNAfragments.The dynamics of glyphosate influence on 18S rRNA fragmentationin wheat embryos. Then, we assessed how quicklywheat embryos respond to glyphosate treatment by measuringthe time dependence of TaeIF2α phosphorylation and of discretefragmentation of 18S rRNA. For this, a glyphosateconcentrationof 500 μM was chosen, which induced quite effectivephosphorylation of TaeIF2α, as well as a significantincrease in the content of 18S rRNA small fragments: 134nt-5′18S, 75nt-5′18S, 100nt-3′18S and 70nt-3′18S . The results of the experiment are shown in Figure 2.The results of semi-quantitative optical densitometry analysisof the data presented in Figure 2 are shown in Table 2.Data presented in Figure 2 and Table 2 show that TaeIF2αphosphorylation begins 45 min after the start of glyphosatetreatment , and TaeIF2αP becomes quite noticeable after 60 minof such treatment .The 3′-terminal fragmentation of 18S rRNA is observedafter 3 hours after the start of glyphosate treatment: fragments100nt-3′18S and 70nt-3′18S become detectable as faintlyvisiblebands on track 7 of Figure 2, b (right panel). Theamount of these 3′-coterminal fragments is significantly lowerthan after 10 hours of the same treatment with glyphosate.As for fragmentation from the 5′-terminus of 18S rRNA,the amount of both 5′-coterminal fragments, 134nt-5′18Sand 75nt-5′18S, is significantly increased as early as by the15th min after the start of treatment of wheat embryos withglyphosate . Notably, the amountof the fragment 134nt-5′18S is higher than that of 75nt-5′18Sfragment during 30–45 min of incubation with glyphosate.By 60 min of incubation their amounts become almost equaland after that, the amount of 75nt-5′18S fragment becomeshigher (by 90 min) and even obviously prevalent by 180 min. Similar interrelation can be seenin Figure 1, b (right panel) regarding the applied concentrationsof glyphosate.These observations suggest that cleavage at 134th nucleotidemay happen more quickly and this site is more susceptibleat the beginning of stress. The cleavage site at 75th nucleotidebecomes more prevalent with an increase of stress durationand severity. The cleavage sites at the 3′-terminal segmentof 18S rRNA occur only at very high severity and durationof stress. Therefore, there seemingly exist several differentmechanisms for the cleavage at 5′- and 3′-termini of 18SrRNA, which may result in several different consequencesfor the functioning of 40S RS.No phosphorylation of eIF2α was observed in plants underosmotic and oxidative stresses , heatshock and during unfolded protein response in plants . At the same time, during these stresses a significantdecrease in the translation level of most mRNAs is observedwith exception only for those templates that are responsiblefor the synthesis of stress proteins . Most likely, in plants, other mechanismsof protein biosynthesis suppression are realized,than eIF2α phosphorylation . In addition,eIF2α phosphorylation is not the only possible mechanism ofresponse to some types of stress in different eukaryotic cells.For example, when yeast cells are exposed to harsh ultravioletlight, phosphorylation of eIF2α is observed, as well as a suppressionof the overall level of protein synthesis. However,inhibition of mRNA translation upon exposure to UV lightoccurs even in cells containing a mutant form of eIF2α that isnot capable of phosphorylation .We postulate that the process of discrete fragmentationof 18S rRNA observed under glyphosate mediated amino acid starvation may lead to a decrease in the level of mRNAtranslation. This molecular mechanism can be realized inparallel with the known mechanism of translational regulationmediated by eIF2α phosphorylation and independentlyof it.Understanding the molecular mechanisms of plant adaptationto stresses can make it possible to increase the efficiencyof breeding work to obtain genetic lines and varieties ofeconomically important plant species that are characterizedby increased resistance to certain stresses.This paper presents data indicating that in plant cells the imitationof amino acid starvation induces, in addition to eIF2αphosphorylation, another cellular response that involves thecleavage of the 18S rRNA molecule with the formation ofdiscrete 5′- and 3′-terminal fragments. At the same time,3′-terminal fragments of 18S rRNA appear only at lethalconcentrations of glyphosate and after a prolonged period ofstress (3 hours or more). In contrast, 5′-terminal fragments of18S rRNA began to accumulate in wheat embryos at relativelylow glyphosate concentrations, at which wheat embryos couldcontinue development, and already 15 min after the start ofglyphosate treatment. Thus, the process of 18S rRNA fragmentationin wheat embryo 40S RS is triggered even underconditions where eIF2α phosphorylation does not occur. Wesuggest that such cleavage of the 18S rRNA molecule, whichis activated during amino acid starvation, may result in eitherglobal or selective suppression of mRNA translation.The authors declare no conflict of interest.Altschuler M., Mascarenhas J.P. Heat shock proteins and effects of heatshock in plants. Plant Mol. Biol. 1982;1(2):103-115. DOI 10.1007/BF00024974.Baird Th.D., Wek R.C. Eukaryotic initiation factor 2 phosphorylationand translational control in metabolism. Adv. Nutr. 2012;3:307-321.DOI 10.3945/an.112.002113Ballard D.J., Peng H.-Y., Das J.K., Kumar A., Wang L., Ren Y.,Xiong X., Ren X., Yang J.-M., Song J. Insights into the pathologicroles and regulation of eukaryotic elongation factor-2 kinase. Front.Mol. Biosci. 2021;8:839. DOI 10.3389/fmolb.2021.727863.Browning K.S., Bailey-Serres J. Mechanism of cytoplasmic mRNAtranslation. Arabidopsis Book. 2015;13:e0176Chen Z., Sun Y., Yang X., Wu Z., Guo K., Niu X., Wang Q., Ruan J.,Bu W., Gao S. Two featured series of rRNA-derived RNA fragments(rRFs) constitute a novel class of small RNAs. PLoS One. 2017;12:e0176458. DOI 10.1371/journal.pone.0176458Echevarria-Zomeno S., Yanguez E., Fernandez-Bautista N., Castro-Sanz A.B., Ferrando A., Castellano M.M. Regulation of translationinitiation under biotic and abiotic stresses. Int. J. Molec. Sci. 2013;14:4670-4683. DOI 10.3390/ijms14034670.Endo Y. Mechanism of action of ricin and related toxins on the inactivationof eukaryotic ribosomes. Cancer Res. Treat. 1988;37:75-89.DOI 10.1007/978-1-4613-1083-9_5.Gallie D.R., Le H., Caldwell C., Tanguay R., Hoang N.X., BrowningK.S. The phosphorylation state of translation initiation factorsis regulated developmentally and following heat shock in wheat.J. Biol. Chem. 1997;272:1046-1053. DOI 10.1074/jbc.272.2.1046.Gallie D.R., Le H., Caldwell C., Browning K.S. Analysis of translationelongation factors from wheat during development and followingheat shock. Biochem. Biophys. Res. Comm. 1998;245:295-300. DOI10.1006/bbrc.1998.8427.Henras A.K., Plisson-Chastang C., O’Donohue M.F., Chakraborty A.,Gleizes P.E. An overview of pre-ribosomal RNA processing ineukaryotes.Wiley Interdiscip. Rev. RNA. 2015;6(2):225-242. DOI10.1002/wrna.1269.Hernandez G., Altmann M., Lasko P. Origins and evolution of themechanisms regulating translation initiation in eukaryotes. TrendsBiochem. Sci. 2010;35(2):63-73. DOI 10.1016/j.tibs.2009.10.009.Immanuel T.M., Greenwood D.R., MacDiarmid R.M. A critical reviewof translation initiation factor eIF2α kinases in plants – regulatingprotein synthesis during stress. Funct. Plant Biol. 2012;39(9):717-735. DOI 10.1071/FP12116.Kamauchi S., Nakatani H., Nakano C., Urade R. Gene expression inresponse to endoplasmic reticulum stress in Arabidopsis thaliana.FEBS J. 2005;272(13):3461-3476. DOI 10.1111/j.1742-4658.2005.04770.x.Kast A., Klassen R., Meinhardt F. rRNA fragmentation induced bya yeast killer toxin. Mol. Microbiol. 2014;91(3):606-617. DOI10.1111/mmi.12481.Knutsen J.H., Rødland G.E., Bøe C.A., Håland T.W., Sunnerhagen P.,Grallert B., Boye E. Stress-induced inhibition of translation independentlyof eIF2α phosphorylation. J. Cell Sci. 2015;128(23):4420-4427. DOI 10.1242/jcs.176545.Laemmli U.K. Cleavage of structural proteins during the assembly ofthe head of bacteriophage T4. Nature. 1970;227(5259):680-685.DOI 10.1038/227680a0.Lageix S., Lanet E., Pouch-Pelissier M.N., Espagnol M.C., Robaglia C.,Deragon J.M., Pelissier T. Arabidopsis eIF2α kinase GCN2 is essentialfor growth in stress conditions and is activated by wounding.BMC Plant Biol. 2008;8:134. DOI 10.1186/1471-2229-8-134.Padgette S.R., Kolacz K.H., Delannay X., Re D.B., LaVallee B.J., TiniusC.N., Rhodes W.K., Otero Y.I., Barry G.F., Eichholtz D.A., PeschkeV.M., Nida D.L., Taylor N.B., Kishore G.M. Development, identificationand characterization of a Glyphosate-tolerant soybean line.Crop Sci. 1995;35(5):1451-1461. DOI 10.3389/fpls.2016.01009Ruberti C., Kim S.J., Stefano G., Brandizzi F. Unfolded protein responsein plants: one master, many questions. Curr. Opin. Plant Biol.2015;27:59-66. DOI 10.1016/j.pbi.2015.05.016.Shaikhin S.M., Smailov S.K., Lee A.V., Kozhanov E.V., Iskakov B.K.Interaction of wheat germ translation initiation factor 2 with GDPand GTP. Biochimie. 1992;74(5):447-454. DOI 10.1016/0300-9084(92)90085-s.Smailov S.K., Lee A.V., Iskakov B.K. Study of phosphorylation oftranslation elongation factor 2 (EF-2) from wheat germ. FEBS Lett.1993;321(2-3):219-223. DOI 10.1016/0014-5793(93)80112-8.Zhang Y., Wang Y., Kanyuka K., Parry M.A., Powers S.J., Halford N.G.GCN2-dependent phosphorylation of eukaryotic translation initiationfactor-2alpha in Arabidopsis. J. Exp. Bot. 2008;59(11):3131-3141. DOI 10.1093/jxb/ern169Zhanybekova S.S., Polimbetova N.S., Nakisbekov N.O., Iskakov B.K.Detection of a new small RNA, induced by heat shock, in wheat seedribosomes. Biochemistry (Moscow). 1996;61:862-870.Zhigailov A.V., Alexandrova A.M., Nizkorodova A.S., Stanbekova G.E.,Kryldakov R.V., Karpova O.V., Polimbetova N.S., Halford N.G.,Iskakov B.K. Evidence that Phosphorylation of the α-subunit ofeIF2 does not essentially inhibit mRNA translation in wheat germcell-free system. Front. Plant Sci. 2020;11:936. DOI 10.3389/fpls.2020.00936.Zhigailov A.V., Polimbetova N.S., Borankul R.I., Iskakov B.K. Investigationof discrete fragmentation of 18S rRNA within 40S ribosomalsubparticles of plant cells. Vestnik KazNU. Biological Series.2013;2:81-87. (in Russian)Zhigailov A.V., Polimbetova N.S., Doshchanov Kh.I., Iskakov B.K.Detection in plant cells of a new 75-nucleotide cytoplasmic RNAcorresponding to the 5′-terminal fragment of 18S RNA. VestnikKazNU.Biological and Medical Series. 2014;1:191-194. (in Russian)Yu Ch.-Y., Cho Y., Sharma O., Kanehara K. What’s unique? The unfoldedprotein response in plants. J. Exp. Botany. 2021:erab513.DOI 10.1093/jxb/erab513.


Gordonia phage Nebulosus was isolated from soil on Gordonia terrae and is a siphovirus. The genome is 52,175 bp in length, has 62% GC content, and encodes 96 protein-coding genes. Nebulosus encodes a partitioning system, ParABS, which is likely involved in lysogeny maintenance.The temperate  Gordonia terrae 3,612 on PYCa agar plates, and incubated at 30°C for 2 days. Plaques were purified after seven rounds of plaque purification using standard methods  (A DNA phenol-chloroform extraction method was performed on a high-titer lysate . DNA wasGTGGTTA) . The genGTGGTTA) , 7.http://cobamide2.bio.pitt.edu) and PECAAN (https://blog.kbrinsgd.org/) (http://phages.wustl.edu/starterator) (–The Nebulosus genome was auto-annotated using GLIMMER v3.02 and GeneMark v2.5 within DNA Master v.5.23.6 (gd.org/) , 12. Traterator) . Putativterator) –15. Threerator) –, 17. A merator) – (7). Neberator) –.Streptomyces kanamyceticus kanamycin biosynthetic gene cluster  downstream from the DNA polymerase I (gp46) with strong HHpred hits to a domain of unknown function DUF6197) found in a 7 found i


In the published article, there was an error in the legend for in vivo. Scale bar, 500μm.”“HucMSC-Exosomes accelerate wound healing. (A) Schematic overview of the study design. (B) Microscope image of huc-MSCs. The scale bar is 500 µm. (C) Flow cytometry analysis of HLA, CD29, CD34, CD45, CD73, CD90 and CD105 expression on the huc-MSC surface. (D) Transmission electron microscopy image of hucMSC-Exosomes. Scale bar, 100 nm. (E) Density plot of hucMSC-Exosomes. (F) Western blot of hucMSC-Exosome markers (G) Representative images of wound closure process of hucMSC-Exosomes treatment and PBS control. The scale bar is 4 mm. (H) Wound closure rate of hucMSC-Exosomes treatment and PBS control group. Two-tailed unpaired t-test (n=6). Error bar: mean standard deviation. ns, not significant, *p < 0.05, ***p < 0.001, ****p < 0.0001. (I) H & E and Masson staining of wounds seven days after injury. Scale bar = 1mm. (J) Uptake of hucMSC-Exosome by skin wound The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.