<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kale, Sandip M.</style></author><author><style face="normal" font="default" size="100%">Pardeshi, Varsha C.</style></author><author><style face="normal" font="default" size="100%">Kadoo, Narendra Y.</style></author><author><style face="normal" font="default" size="100%">Ghorpade, Prakash B.</style></author><author><style face="normal" font="default" size="100%">Jana, Murari M.</style></author><author><style face="normal" font="default" size="100%">Gupta, Vidya S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Development of genomic simple sequence repeat markers for linseed using next-generation sequencing technology</style></title><secondary-title><style face="normal" font="default" size="100%">Molecular Breeding</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Flax</style></keyword><keyword><style  face="normal" font="default" size="100%">Microsatellite isolation</style></keyword><keyword><style  face="normal" font="default" size="100%">Next-generation sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">SSR</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUN</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">1</style></number><publisher><style face="normal" font="default" size="100%">SPRINGER</style></publisher><pub-location><style face="normal" font="default" size="100%">VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS</style></pub-location><volume><style face="normal" font="default" size="100%">30</style></volume><pages><style face="normal" font="default" size="100%">597-606</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Linseed (Linum usitatissimum L.) is regarded as a cash crop of tomorrow because of the presence of nutraceutically important alpha-linolenic acid (ALA) and lignan. However, only limited breeding progress has been made in this crop, mainly due to the lack of sufficient genetic and genomic resources. Among these, simple sequence repeats (SSR) are useful DNA markers for diversity analysis, genetic mapping and tagging traits because of their co-dominant and highly polymorphic nature. In order to develop SSR markers for linseed, we used three microsatellite isolation methods, viz., PCR Isolation of Microsatellite Arrays (PIMA), 5'-anchored PCR method, and Fast Isolation by AFLP of Sequences COntaining repeats (FIASCO). The amplified products from these methods were pooled and sequenced using the 454 GS-FLX platform. A total of 36,332 reads were obtained, which assembled into 2,183 contigs and 2,509 singlets. The contigs and the singlets contained 1,842 microsatellite motifs, with dinucleotide motifs as the most abundant repeat type (54%) followed by trinucleotide motifs (44%). Based on this, 290 SSR markers were designed, 52 of which were evaluated using a panel of 27 diverse linseed genotypes. Among the three enrichment methods, the 5'-anchored PCR method was most efficient for isolation of microsatellites, while FIASCO was most efficient for developing SSR markers. We show the utility of next-generation sequencing technology for efficiently discovering a large number of microsatellite markers in non-model plants.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">3.251
</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Rajput, Vinay</style></author><author><style face="normal" font="default" size="100%">Pramanik, Rinka</style></author><author><style face="normal" font="default" size="100%">Malik, Vinita</style></author><author><style face="normal" font="default" size="100%">Yadav, Rakeshkumar</style></author><author><style face="normal" font="default" size="100%">Samson, Rachel</style></author><author><style face="normal" font="default" size="100%">Kadam, Pradnya</style></author><author><style face="normal" font="default" size="100%">Bhalerao, Unnati</style></author><author><style face="normal" font="default" size="100%">Tupekar, Manisha</style></author><author><style face="normal" font="default" size="100%">Deshpande, Dipti</style></author><author><style face="normal" font="default" size="100%">Shah, Priyanki</style></author><author><style face="normal" font="default" size="100%">Shashidhara, L. S.</style></author><author><style face="normal" font="default" size="100%">Boargaonkar, Radhika</style></author><author><style face="normal" font="default" size="100%">Patil, Dhawal</style></author><author><style face="normal" font="default" size="100%">Kale, Saurabh</style></author><author><style face="normal" font="default" size="100%">Bhalerao, Asim</style></author><author><style face="normal" font="default" size="100%">Jain, Nidhi</style></author><author><style face="normal" font="default" size="100%">Kamble, Sanjay</style></author><author><style face="normal" font="default" size="100%">Dastager, Syed</style></author><author><style face="normal" font="default" size="100%">Karmodiya, Krishanpal</style></author><author><style face="normal" font="default" size="100%">Dharne, Mahesh</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Genomic surveillance reveals early detection and transition of delta to omicron lineages of SARS-CoV-2 variants in wastewater treatment plants of Pune, India</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental Science and Pollution Research </style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Bioinformatics pipeline</style></keyword><keyword><style  face="normal" font="default" size="100%">COVID-19</style></keyword><keyword><style  face="normal" font="default" size="100%">Early warning</style></keyword><keyword><style  face="normal" font="default" size="100%">India</style></keyword><keyword><style  face="normal" font="default" size="100%">Next-generation sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Omicron</style></keyword><keyword><style  face="normal" font="default" size="100%">Public health</style></keyword><keyword><style  face="normal" font="default" size="100%">SARS-CoV-2</style></keyword><keyword><style  face="normal" font="default" size="100%">wastewater</style></keyword><keyword><style  face="normal" font="default" size="100%">Wastewater-based epidemiology</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2023</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">30</style></volume><pages><style face="normal" font="default" size="100%">118976-118988</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;
	The COVID-19 pandemic has emphasized the urgency for rapid public health surveillance methods to detect and monitor the transmission of infectious diseases. The wastewater-based epidemiology (WBE) has emerged as a promising tool for proactive analysis and quantification of infectious pathogens within a population before clinical cases emerge. In the present study, we aimed to assess the trend and dynamics of SARS-CoV-2 variants using a longitudinal approach. Our objective included early detection and monitoring of these variants to enhance our understanding of their prevalence and potential impact. To achieve our goals, we conducted real-time quantitative polymerase chain reaction (RT-qPCR) and Illumina sequencing on 442 wastewater (WW) samples collected from 10 sewage treatment plants (STPs) in Pune city, India, spanning from November 2021 to April 2022. Our comprehensive analysis identified 426 distinct lineages representing 17 highly transmissible variants of SARS-CoV-2. Notably, fragments of Omicron variant were detected in WW samples prior to its first clinical detection in Botswana. Furthermore, we observed highly contagious sub-lineages of the Omicron variant, including BA.1 (similar to 28%), BA.1.X (1.0-72%), BA.2 (1.0-18%), BA.2.X (1.0-97.4%) BA.2.12 (0.8-0.25%), BA.2.38 (0.8-1.0%), BA.2.75 (0.01-0.02%), BA.3 (0.09-6.3%), BA.4 (0.24-0.29%), and XBB (0.01-21.83%), with varying prevalence rates. Overall, the present study demonstrated the practicality of WBE in the early detection of SARS-CoV-2 variants, which could help track future outbreaks of SARS-CoV-2. Such approaches could be implicated in monitoring infectious agents before they appear in clinical cases.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">56</style></issue><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">&lt;p&gt;Foreign&lt;/p&gt;
</style></custom3><custom4><style face="normal" font="default" size="100%">&lt;p&gt;
	5.8&lt;/p&gt;
</style></custom4></record></records></xml>