With the development of molecular marker technology in the 1980s, the fate of plant breeding has changed. Different types of molecular markers have been developed and advancement in sequencing technologies has geared crop improvement. To explore the knowledge about molecular markers, several reviews have been published in the last three decades; however, all these reviews were meant for researchers with advanced knowledge of molecular genetics. This review is intended to be a synopsis of recent developments in molecular markers and their applications in plant breeding and is devoted to early researchers with a little or no knowledge of molecular markers. The progress made in molecular plant breeding, genetics, genomic selection and genome editing has contributed to a more comprehensive understanding of molecular markers and provided deeper insights into the diversity available for crops and greatly complemented breeding stratagems. Genotyping-by-sequencing and association mapping based on next-generation sequencing technologies have facilitated the identification of novel genetic markers for complex and unstructured populations. Altogether, the history, the types of markers, their application in plant sciences and breeding, and some recent advancements in genomic selection and genome editing are discussed.

Until now, little attention has been paid to the geographic distribution and evaluation of genetic diversity of durum wheat from the Central Fertile Crescent (modern-day Turkey and Syria). Turkey and Syria are considered as primary centers of wheat diversity, and thousands of locally adapted wheat landraces are still present in the farmers’ small fields. We planned this study to evaluate the genetic diversity of durum wheat landraces from the Central Fertile Crescent by genotyping based on DArTseq and SNP analysis. A total of 39,568 DArTseq and 20,661 SNP markers were used to characterize the genetic characteristic of 91 durum wheat land races. Clustering based on Neighbor joining analysis, principal coordinate as well as Bayesian model implemented in structure, clearly showed that the grouping pattern is not associated with the geographical distribution of the durum wheat due to the mixing of the Turkish and Syrian landraces. Significant correlation between DArTseq and SNP markers was observed in the Mantel test. However, we detected a non-significant relationship between geographical coordinates and DArTseq (r = -0.085) and SNP (r = -0.039) loci. These results showed that unconscious farmer selection and lack of the commercial varieties might have resulted in the exchange of genetic material and this was apparent in the genetic structure of durum wheat in Turkey and Syria. The genomic characterization presented here is an essential step towards a future exploitation of the available durum wheat genetic resources in genomic and breeding programs. The results of this study have also depicted a clear insight about the genetic diversity of wheat accessions from the Central Fertile Crescent.

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Lentil (Lens culinaris Medik.) is an excellent source of protein and carbohydrates and is also rich in essential trace elements for the human diet. Selenium (Se) is an essential micronutrient for human health and nutrition, providing protection against several diseases and regulating important biological systems. Dietary intake of 55 μg of Se per day is recommended for adults, with inadequate Se intake causing significant health problems. The objective of this study was to identify and map quantitative trait loci (QTL) of genes controlling Se accumulation in lentil seeds using a population of 96 recombinant inbred lines (RILs) developed from the cross “PI 320937” × “Eston” grown in three different environments for two years (2012 and 2013). Se concentration in seed varied between 119 and 883 μg/kg. A linkage map consisting of 1,784 markers (4 SSRs, and 1,780 SNPs) was developed. The map spanned a total length of 4,060.6 cM, consisting of 7 linkage groups (LGs) with an average distance of 2.3 cM between adjacent markers. Four QTL regions and 36 putative QTL markers, with LOD scores ranging from 3.00 to 4.97, distributed across two linkage groups (LG2 and LG5) were associated with seed Se concentration, explaining 6.3–16.9% of the phenotypic variation.

turkey; b Department of Field crops, Faculty of agriculture, Bolu abant İzzet Baysal university, Bolu, turkey; c State Key laboratory for conservation and utilization of Subtropical agro-bioresources, South china agricultural university, guangzhou, pR china; d cRea Research center for cereal and industrial crops, Bologna, italy;

IntroductionLentil, Lens culinaris Medic., is an important cool season food legume in the old world. It is a self-pollinated, diploid (2n = 2x = 14) with a genome size of 4063 Mbp (Arumuganathan and Earl, 1991). The origin of cultivated lentil is the

Artificial intelligence has been prevalent recently as its use in the medical field is noticed to be increased. However, middle east countries like Syria are deficient in multiple AI implementation methods in the field of medicine. So, holding these AI implementation methods in the medical field is necessary, which may be incredibly beneficial for making diagnosis more accessible and help in the treatment. This paper intends to determine AI's knowledge, attitude, and practice among doctors and medical students in Syria. A questionnaire conducted an online cross-sectional study on the google form website consisting of demographic data, knowledge, and perception of AI. There were 1,494 responses from both doctors and medical students. We included Syrian medical students and doctors who are currently residing in Syria. Of the 1,494 participants, 255 (16.9%) are doctors, while the other 1,252 (83.1%) are undergraduate medical students. About 1,055 (70%) participants have previous knowledge about AI. However, only 357 (23.7%) participants know about its application in the medical field. Most have shown positive attitudes toward its necessity in the medical field; 689 (45.7%) individuals strongly agree, and 628 (41.7%) agree. The undergraduate students had 3.327 times more adequate knowledge of AI than students in the first year. In contrast, the undergraduate 6th-year students had 2.868 times the attitude toward AI higher than students in the first year. The residents and assistant professors had 2.371 and 4.422 times the practice of AI higher than students, respectively. Although most physicians and medical students do not sufficiently understand AI and its significance in the medical field, they have favorable views regarding using AI in the medical field. Syrian medical authorities and international organizations should suggest including artificial intelligence in the medical field, particularly when training residents and fellowship physicians.

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