Ipsita Panigrahi , Tusar Kanti Behera , A.D. Munshi , S.S. Dey , A.B. Gaikwad , Manoranjan Senapati
{"title":"基于 SSR 标记的苦瓜(Momordica charantia L.)产量和产量性状 QTL 图谱绘制与遗传分析","authors":"Ipsita Panigrahi , Tusar Kanti Behera , A.D. Munshi , S.S. Dey , A.B. Gaikwad , Manoranjan Senapati","doi":"10.1016/j.sajb.2024.09.049","DOIUrl":null,"url":null,"abstract":"<div><div>The present study was conducted for QTL mapping for yield and other yield attributing traits in bitter gourd using Simple Sequence Repeat (SSR) markers. A total of 630 SSR markers were screened for polymorphism in two contrasting parents (DBGS-2 and Pusa Purvi), out of which only 35 were polymorphic. F<sub>1</sub> plants (10 individuals) in which hybridity was ascertained (using these polymorphic markers); were further employed for development of mapping population (F<sub>2</sub>) consisting of 120 plants. Higher variation was present in the mapping population as evident from the wider range value of the characters. Continuous frequency distribution classes combined with bell-shaped, symmetrical normal distribution curve, revealed the quantitative inheritance nature of the traits studied. Higher PCV than the GCV for all the traits, along with high difference between the PCV and GCV for majority of traits indicated higher influence of environment in expression of these traits in the mapping population. Presence of transgressive segregation was also noted for majority of the traits. Amongst the various linkage groups (LG), LG 4 had the maximum number of markers, covering 171.07 cM map distance. LG4 also possessed the maximum number (nine) of QTLs while LG1 had six. QTL mapping using polymorphic SSRs resulted in detection of a total of 28 QTLs for fourteen traits viz. yield per plant (kg), earliness or flower related traits (node to first female flower, node to first male flower, days to first male flower, male to female flower ratio), fruit traits (fruit number per plant, fruit diameter (cm), fruit length/ diameter ratio, pericarp thickness (mm) and number of seed per fruit) and vegetative traits (internodal length (cm), number of primary branches, leaf width (cm), length and width ratio). The LOD score of these QTLs ranged from 3.01 to 64.47, the total phenotypic variances (PVE) ranged from 1.52 to 34.57 % and additive effects ranged from –3.69 to 17.07. Of the total, nineteen were major QTLs, having PVE >10 %. Three QTLs were detected for yield per plant while a total of seven for the traits imparting earliness viz. days to first male flower, node to first female flower and node to first male flower. Amongst all the QTLs detected, qFrtLDR-4-1 (K) had the maximum LOD (64.47) and PVE (34.57 %) value. Two hotspots were detected with multiple QTLs clustered in the LG 1. The first hotspot possessed four QTLs [qLfW-1-1, qMFR-1-1 (K), qSPF-1-1, qNFmlF-1-1 (K)] while the second had two related to yield per plant [qYldpl-1-1 (K) and qYldpl-1-1]. Many of these QTLs are also being reported for the first time in bitter gourd. The findings of the present study can be used to fasten the bitter gourd improvement by utilizing these in MAS, DNA fingerprinting, genetic mapping, genomics analysis <em>etc</em>.</div></div>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"SSR markers based QTL mapping and genetic analysis for yield and yield-attributing traits in bitter gourd (Momordica charantia L.)\",\"authors\":\"Ipsita Panigrahi , Tusar Kanti Behera , A.D. Munshi , S.S. Dey , A.B. Gaikwad , Manoranjan Senapati\",\"doi\":\"10.1016/j.sajb.2024.09.049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The present study was conducted for QTL mapping for yield and other yield attributing traits in bitter gourd using Simple Sequence Repeat (SSR) markers. A total of 630 SSR markers were screened for polymorphism in two contrasting parents (DBGS-2 and Pusa Purvi), out of which only 35 were polymorphic. F<sub>1</sub> plants (10 individuals) in which hybridity was ascertained (using these polymorphic markers); were further employed for development of mapping population (F<sub>2</sub>) consisting of 120 plants. Higher variation was present in the mapping population as evident from the wider range value of the characters. Continuous frequency distribution classes combined with bell-shaped, symmetrical normal distribution curve, revealed the quantitative inheritance nature of the traits studied. Higher PCV than the GCV for all the traits, along with high difference between the PCV and GCV for majority of traits indicated higher influence of environment in expression of these traits in the mapping population. Presence of transgressive segregation was also noted for majority of the traits. Amongst the various linkage groups (LG), LG 4 had the maximum number of markers, covering 171.07 cM map distance. LG4 also possessed the maximum number (nine) of QTLs while LG1 had six. QTL mapping using polymorphic SSRs resulted in detection of a total of 28 QTLs for fourteen traits viz. yield per plant (kg), earliness or flower related traits (node to first female flower, node to first male flower, days to first male flower, male to female flower ratio), fruit traits (fruit number per plant, fruit diameter (cm), fruit length/ diameter ratio, pericarp thickness (mm) and number of seed per fruit) and vegetative traits (internodal length (cm), number of primary branches, leaf width (cm), length and width ratio). The LOD score of these QTLs ranged from 3.01 to 64.47, the total phenotypic variances (PVE) ranged from 1.52 to 34.57 % and additive effects ranged from –3.69 to 17.07. Of the total, nineteen were major QTLs, having PVE >10 %. Three QTLs were detected for yield per plant while a total of seven for the traits imparting earliness viz. days to first male flower, node to first female flower and node to first male flower. Amongst all the QTLs detected, qFrtLDR-4-1 (K) had the maximum LOD (64.47) and PVE (34.57 %) value. Two hotspots were detected with multiple QTLs clustered in the LG 1. The first hotspot possessed four QTLs [qLfW-1-1, qMFR-1-1 (K), qSPF-1-1, qNFmlF-1-1 (K)] while the second had two related to yield per plant [qYldpl-1-1 (K) and qYldpl-1-1]. Many of these QTLs are also being reported for the first time in bitter gourd. The findings of the present study can be used to fasten the bitter gourd improvement by utilizing these in MAS, DNA fingerprinting, genetic mapping, genomics analysis <em>etc</em>.</div></div>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0254629924006069\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0254629924006069","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
SSR markers based QTL mapping and genetic analysis for yield and yield-attributing traits in bitter gourd (Momordica charantia L.)
The present study was conducted for QTL mapping for yield and other yield attributing traits in bitter gourd using Simple Sequence Repeat (SSR) markers. A total of 630 SSR markers were screened for polymorphism in two contrasting parents (DBGS-2 and Pusa Purvi), out of which only 35 were polymorphic. F1 plants (10 individuals) in which hybridity was ascertained (using these polymorphic markers); were further employed for development of mapping population (F2) consisting of 120 plants. Higher variation was present in the mapping population as evident from the wider range value of the characters. Continuous frequency distribution classes combined with bell-shaped, symmetrical normal distribution curve, revealed the quantitative inheritance nature of the traits studied. Higher PCV than the GCV for all the traits, along with high difference between the PCV and GCV for majority of traits indicated higher influence of environment in expression of these traits in the mapping population. Presence of transgressive segregation was also noted for majority of the traits. Amongst the various linkage groups (LG), LG 4 had the maximum number of markers, covering 171.07 cM map distance. LG4 also possessed the maximum number (nine) of QTLs while LG1 had six. QTL mapping using polymorphic SSRs resulted in detection of a total of 28 QTLs for fourteen traits viz. yield per plant (kg), earliness or flower related traits (node to first female flower, node to first male flower, days to first male flower, male to female flower ratio), fruit traits (fruit number per plant, fruit diameter (cm), fruit length/ diameter ratio, pericarp thickness (mm) and number of seed per fruit) and vegetative traits (internodal length (cm), number of primary branches, leaf width (cm), length and width ratio). The LOD score of these QTLs ranged from 3.01 to 64.47, the total phenotypic variances (PVE) ranged from 1.52 to 34.57 % and additive effects ranged from –3.69 to 17.07. Of the total, nineteen were major QTLs, having PVE >10 %. Three QTLs were detected for yield per plant while a total of seven for the traits imparting earliness viz. days to first male flower, node to first female flower and node to first male flower. Amongst all the QTLs detected, qFrtLDR-4-1 (K) had the maximum LOD (64.47) and PVE (34.57 %) value. Two hotspots were detected with multiple QTLs clustered in the LG 1. The first hotspot possessed four QTLs [qLfW-1-1, qMFR-1-1 (K), qSPF-1-1, qNFmlF-1-1 (K)] while the second had two related to yield per plant [qYldpl-1-1 (K) and qYldpl-1-1]. Many of these QTLs are also being reported for the first time in bitter gourd. The findings of the present study can be used to fasten the bitter gourd improvement by utilizing these in MAS, DNA fingerprinting, genetic mapping, genomics analysis etc.