TY  - JOUR
AU  - Kumar, Sandeep
AU  - Saini, Dinesh Kumar
AU  - Jan, Farkhandah
AU  - Jan, Sofora
AU  - Tahir, Mohd
AU  - Đalović, Ivica
AU  - Latković, Dragana
AU  - Khan, Mohd Anwar
AU  - Kuma, Sundeep
AU  - Vikas, V. K.
AU  - Kumar, Upendra
AU  - Kumar, Sundip
AU  - Dhaka, Narendra Singh
AU  - Dhankher, Om Parkash
AU  - Rustgi, Sachin
AU  - Mir, Reyazul Rouf
PY  - 2023
UR  - http://fiver.ifvcns.rs/handle/123456789/3562
AB  - Yellow or stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici (Pst) is an important disease of wheat that threatens wheat production. Since developing resistant cultivars offers a viable solution for disease management, it is essential to understand the genetic basis of stripe rust resistance. In recent years, meta-QTL analysis of identified QTLs has gained popularity as a way to dissect the genetic architecture underpinning quantitative traits, including disease resistance. Systematic meta-QTL analysis involving 505 QTLs from 101 linkage-based interval mapping studies was conducted for stripe rust resistance in wheat. For this purpose, publicly available high-quality genetic maps were used to create a consensus linkage map involving 138,574 markers. This map was used to project the QTLs and conduct meta-QTL analysis. A total of 67 important meta-QTLs (MQTLs) were identified which were refined to 29 high-confidence MQTLs. The confidence interval (CI) of MQTLs ranged from 0 to 11.68 cM with a mean of 1.97 cM. The mean physical CI of MQTLs was 24.01 Mb, ranging from 0.0749 to 216.23 Mb per MQTL. As many as 44 MQTLs colocalized with marker–trait associations or SNP peaks associated with stripe rust resistance in wheat. Some MQTLs also included the following major genes- Yr5, Yr7, Yr16, Yr26, Yr30, Yr43, Yr44, Yr64, YrCH52, and YrH52. Candidate gene mining in high-confidence MQTLs identified 1,562 gene models. Examining these gene models for differential expressions yielded 123 differentially expressed genes, including the 59 most promising CGs. We also studied how these genes were expressed in wheat tissues at different phases of development
PB  - Springer Nature
T2  - BMC Genomics
T1  - Comprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat
SP  - 259
VL  - 24
DO  - 10.1186/s12864-023-09336-y
ER  - 

@article{
author = "Kumar, Sandeep and Saini, Dinesh Kumar and Jan, Farkhandah and Jan, Sofora and Tahir, Mohd and Đalović, Ivica and Latković, Dragana and Khan, Mohd Anwar and Kuma, Sundeep and Vikas, V. K. and Kumar, Upendra and Kumar, Sundip and Dhaka, Narendra Singh and Dhankher, Om Parkash and Rustgi, Sachin and Mir, Reyazul Rouf",
year = "2023",
abstract = "Yellow or stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici (Pst) is an important disease of wheat that threatens wheat production. Since developing resistant cultivars offers a viable solution for disease management, it is essential to understand the genetic basis of stripe rust resistance. In recent years, meta-QTL analysis of identified QTLs has gained popularity as a way to dissect the genetic architecture underpinning quantitative traits, including disease resistance. Systematic meta-QTL analysis involving 505 QTLs from 101 linkage-based interval mapping studies was conducted for stripe rust resistance in wheat. For this purpose, publicly available high-quality genetic maps were used to create a consensus linkage map involving 138,574 markers. This map was used to project the QTLs and conduct meta-QTL analysis. A total of 67 important meta-QTLs (MQTLs) were identified which were refined to 29 high-confidence MQTLs. The confidence interval (CI) of MQTLs ranged from 0 to 11.68 cM with a mean of 1.97 cM. The mean physical CI of MQTLs was 24.01 Mb, ranging from 0.0749 to 216.23 Mb per MQTL. As many as 44 MQTLs colocalized with marker–trait associations or SNP peaks associated with stripe rust resistance in wheat. Some MQTLs also included the following major genes- Yr5, Yr7, Yr16, Yr26, Yr30, Yr43, Yr44, Yr64, YrCH52, and YrH52. Candidate gene mining in high-confidence MQTLs identified 1,562 gene models. Examining these gene models for differential expressions yielded 123 differentially expressed genes, including the 59 most promising CGs. We also studied how these genes were expressed in wheat tissues at different phases of development",
publisher = "Springer Nature",
journal = "BMC Genomics",
title = "Comprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat",
pages = "259",
volume = "24",
doi = "10.1186/s12864-023-09336-y"
}

Kumar, S., Saini, D. K., Jan, F., Jan, S., Tahir, M., Đalović, I., Latković, D., Khan, M. A., Kuma, S., Vikas, V. K., Kumar, U., Kumar, S., Dhaka, N. S., Dhankher, O. P., Rustgi, S.,& Mir, R. R.. (2023). Comprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat. in BMC Genomics
Springer Nature., 24, 259.
https://doi.org/10.1186/s12864-023-09336-y

Kumar S, Saini DK, Jan F, Jan S, Tahir M, Đalović I, Latković D, Khan MA, Kuma S, Vikas VK, Kumar U, Kumar S, Dhaka NS, Dhankher OP, Rustgi S, Mir RR. Comprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat. in BMC Genomics. 2023;24:259.
doi:10.1186/s12864-023-09336-y .

Kumar, Sandeep, Saini, Dinesh Kumar, Jan, Farkhandah, Jan, Sofora, Tahir, Mohd, Đalović, Ivica, Latković, Dragana, Khan, Mohd Anwar, Kuma, Sundeep, Vikas, V. K., Kumar, Upendra, Kumar, Sundip, Dhaka, Narendra Singh, Dhankher, Om Parkash, Rustgi, Sachin, Mir, Reyazul Rouf, "Comprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat" in BMC Genomics, 24 (2023):259,
https://doi.org/10.1186/s12864-023-09336-y . .

TY  - JOUR
AU  - Rasool, Bushra
AU  - Summuna, Baby
AU  - Đalović, Ivica
AU  - Shah, Tariq Ahmed
AU  - Sheikh, Parveez Ahmed
AU  - Gupta, Sachin
AU  - Tyagi, Sandhya
AU  - Bilal, Sierra
AU  - Varshney, Rajeev K.
AU  - Abidi, Ishfaq
AU  - Kumar, Jitendra
AU  - Penmetsa, Varma
AU  - Khanday, Imtiyaz
AU  - Kumar, Upendra
AU  - Sofi, Parvaze Ahmad
AU  - Khan, Mohd Anwar
AU  - Bhat, Mohd Ashraf
AU  - Wani, Fehim Jeelani
AU  - Thudi, Mahendar
AU  - Mir, Reyazul Rouf
PY  - 2023
UR  - http://fiver.ifvcns.rs/handle/123456789/3385
AB  - Fusarium wilt (FW) caused by the Fusarium oxysporum f. sp. ciceri is a devastating disease of chickpea (Cicer arietinum L.). To identify promising resistant genotypes and genomic loci for FW resistance, a core set of 179 genotypes of chickpea was tested for FW reactions at seedling and reproductive stages under field as well as controlled conditions in the greenhouse. Our results revealed that at seedling stage, most of the genotypes were found resistant whereas, at the reproductive stage majority of the genotypes were found susceptible. Genotyping using a 50K Axiom®Cicer SNP Array and trait data of FW together led to the identification of 26 significant (p≤E-05) marker-trait associations (MTAs) for FW resistance. Among 26 MTAs, 12 were identified using trait data recorded in the field (3 at seedling and 9 at reproductive stage) and 14 MTAs were identified using trait data recorded under controlled conditions in the greenhouse (6 at seedling and 8 at reproductive stage). The phenotypic variation explained by these MTAs varied from 11.75 to 15.86% with an average of 13.77%. Five MTAs were classified as major, explaining more than 15% phenotypic variation for FW and two MTAs were declared stable, being identified in either two environments or at two growth stages. One of the promising stable and major MTAs (Affx_123280060) detected in field conditions at reproductive stage was also detected in greenhouse conditions at seedling and reproductive stages. The stable and major (>15% PVE) MTAs can be used in chickpea breeding programmes.
PB  - The American Phytopathological Society (APS) Publications
T2  - Phytopathology
T1  - Delineating Marker-trait Associations for Fusarium Wilt in Chickpea using Axiom® Cicer SNP Array
DO  - 10.1094/PHYTO-05-22-0164-FI
DO  - 1943-7684
ER  - 

@article{
author = "Rasool, Bushra and Summuna, Baby and Đalović, Ivica and Shah, Tariq Ahmed and Sheikh, Parveez Ahmed and Gupta, Sachin and Tyagi, Sandhya and Bilal, Sierra and Varshney, Rajeev K. and Abidi, Ishfaq and Kumar, Jitendra and Penmetsa, Varma and Khanday, Imtiyaz and Kumar, Upendra and Sofi, Parvaze Ahmad and Khan, Mohd Anwar and Bhat, Mohd Ashraf and Wani, Fehim Jeelani and Thudi, Mahendar and Mir, Reyazul Rouf",
year = "2023",
abstract = "Fusarium wilt (FW) caused by the Fusarium oxysporum f. sp. ciceri is a devastating disease of chickpea (Cicer arietinum L.). To identify promising resistant genotypes and genomic loci for FW resistance, a core set of 179 genotypes of chickpea was tested for FW reactions at seedling and reproductive stages under field as well as controlled conditions in the greenhouse. Our results revealed that at seedling stage, most of the genotypes were found resistant whereas, at the reproductive stage majority of the genotypes were found susceptible. Genotyping using a 50K Axiom®Cicer SNP Array and trait data of FW together led to the identification of 26 significant (p≤E-05) marker-trait associations (MTAs) for FW resistance. Among 26 MTAs, 12 were identified using trait data recorded in the field (3 at seedling and 9 at reproductive stage) and 14 MTAs were identified using trait data recorded under controlled conditions in the greenhouse (6 at seedling and 8 at reproductive stage). The phenotypic variation explained by these MTAs varied from 11.75 to 15.86% with an average of 13.77%. Five MTAs were classified as major, explaining more than 15% phenotypic variation for FW and two MTAs were declared stable, being identified in either two environments or at two growth stages. One of the promising stable and major MTAs (Affx_123280060) detected in field conditions at reproductive stage was also detected in greenhouse conditions at seedling and reproductive stages. The stable and major (>15% PVE) MTAs can be used in chickpea breeding programmes.",
publisher = "The American Phytopathological Society (APS) Publications",
journal = "Phytopathology",
title = "Delineating Marker-trait Associations for Fusarium Wilt in Chickpea using Axiom® Cicer SNP Array",
doi = "10.1094/PHYTO-05-22-0164-FI, 1943-7684"
}

Rasool, B., Summuna, B., Đalović, I., Shah, T. A., Sheikh, P. A., Gupta, S., Tyagi, S., Bilal, S., Varshney, R. K., Abidi, I., Kumar, J., Penmetsa, V., Khanday, I., Kumar, U., Sofi, P. A., Khan, M. A., Bhat, M. A., Wani, F. J., Thudi, M.,& Mir, R. R.. (2023). Delineating Marker-trait Associations for Fusarium Wilt in Chickpea using Axiom® Cicer SNP Array. in Phytopathology
The American Phytopathological Society (APS) Publications..
https://doi.org/10.1094/PHYTO-05-22-0164-FI

Rasool B, Summuna B, Đalović I, Shah TA, Sheikh PA, Gupta S, Tyagi S, Bilal S, Varshney RK, Abidi I, Kumar J, Penmetsa V, Khanday I, Kumar U, Sofi PA, Khan MA, Bhat MA, Wani FJ, Thudi M, Mir RR. Delineating Marker-trait Associations for Fusarium Wilt in Chickpea using Axiom® Cicer SNP Array. in Phytopathology. 2023;.
doi:10.1094/PHYTO-05-22-0164-FI .

Rasool, Bushra, Summuna, Baby, Đalović, Ivica, Shah, Tariq Ahmed, Sheikh, Parveez Ahmed, Gupta, Sachin, Tyagi, Sandhya, Bilal, Sierra, Varshney, Rajeev K., Abidi, Ishfaq, Kumar, Jitendra, Penmetsa, Varma, Khanday, Imtiyaz, Kumar, Upendra, Sofi, Parvaze Ahmad, Khan, Mohd Anwar, Bhat, Mohd Ashraf, Wani, Fehim Jeelani, Thudi, Mahendar, Mir, Reyazul Rouf, "Delineating Marker-trait Associations for Fusarium Wilt in Chickpea using Axiom® Cicer SNP Array" in Phytopathology (2023),
https://doi.org/10.1094/PHYTO-05-22-0164-FI . .