Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism

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Not AvailableA complete annual cycle of micrometeorological measurements were carried out to characterize the dynamics of radiation and energy balance over a grassland ecosystem at Central Arid Zone Research Institute experimental area at Chandan, Jaisalmer, India from INSAT-linked ISRO-AMS (Agro-Met Station). The daytime average dekadal latent flux for actual evapotranspiration (AET) showed substantially lower magnitude (15-115 Wm-2) (AET: 0.3 mmd-1 to 2.5 mmd-1) with prominent peak coincident to south-west monsoon and peak growth stage. Sensible heat fluxes showed a large variation from 54 to 340 Wm-2 with peak during summer and minimum during winter and monsoon seasons. More than 70% energy balance closure (EBC) was observed. The non-closure of energy balance periods were characterized by strong local advections in summer. The daytime average net radiation showed bimodal behavior (195 to 420 Wm-2) with primary peak in spring-summer and secondary peak coincident to the start of the withdrawal of south-west monsoon. Significant complementary exponential relation (Y=0.045 e12.13X, R2 = 0.65) was found between dekadal albedo and Bowen ratio which was generally high (1.5 to 5.3) with intermittent dips (0.3 to 1.3) coincident to wet spells. Similarly, the dekadal albedo showed a higher magnitude (0.15 to 0.39), recording the highest (0.39) in the month of April and the lowest (0.15) in the month of September post-monsoon period when green grass growth was maximum.Not Availabl

Early estimation of sugarcane area of Uttar Pradesh using remote sensing and ground truth

Uttar Pradesh contributes largest acreage of sugarcane (more than 40 per cent) to the national crop acreage; hence an early estimate of the crop acreage becomes paramount importance which was done using AWiFS data. Multi-date data of Resourcesat-2 AWiFS from February to November 2012 and January to November, 2013 for the 27 districts of Uttar Pradesh (U.P) was used to develop the procedure for early estimation of sugarcane acreage. The districts selected were having an area greater than 10 thousand ha and contribute 98.7 per cent of the state sugarcane acreage. The ground truth was collected during July/August and October 2012-13.The classification accuracy vis-a-vis critical data set requirement and identification of ratoon and freshly planted crop was also attempted. Early estimation of sugarcane acreage during month of June can be made possible by using multi-date AWiFS data upto May in case of Uttar Pradesh. The estimated acreage was 18.1 lakh ha which were 30 per cent underestimated in comparison to crop acreage estimation using data upto Nov. 3, 2012 which was 26.1 lakh ha. The error in early estimation of the crops was reduced by about 50 per cent as the estimated crop acreage during May was19.5 lakh ha whereas using AWiFS data upto Nov. 3, 2013 was 22.6 lakh ha. Therefore, on the basis of model output for two years, early estimation in June showed under estimation of 22 percent compared to final estimate in November

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Not AvailableUttar Pradesh contributes largest acreage of sugarcane (more than 40 per cent) to the national crop acreage; hence an early estimate of the crop acreage becomes paramount importance which was done using AWiFS data. Multi-date data of Resourcesat-2 AWiFS from February to November 2012 and January to November, 2013 for the 27 districts of Uttar Pradesh (U.P) was used to develop the procedure for early estimation of sugarcane acreage. The districts selected were having an area greater than 10 thousand ha and contribute 98.7 per cent of the state sugarcane acreage. The ground truth was collected during July/August and October 2012-13.The classification accuracy vis-a-vis critical data set requirement and identification of ratoon and freshly planted crop was also attempted. Early estimation of sugarcane acreage during month of June can be made possible by using multi-date AWiFS data upto May in case of Uttar Pradesh. The estimated acreage was 18.1 lakh ha which were 30 per cent underestimated in comparison to crop acreage estimation using data upto Nov. 3, 2012 which was 26.1 lakh ha. The error in early estimation of the crops was reduced by about 50 per cent as the estimated crop acreage during May was19.5 lakh ha whereas using AWiFS data upto Nov. 3, 2013 was 22.6 lakh ha. Therefore, on the basis of model output for two years, early estimation in June showed under estimation of 22 percent compared to final estimate in November.Not Availabl

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The study area is located between 23.5o and 30.5o N and 76.5 o to 84.5 o E bordered by the Indo gangetic plains. It covers about 24093 km2 geographical area.Total 400 ground truth data was collected using the handheld GPS during the crop season in all the district of the study area. The satellite data of the same period consisted of 56 m spatial resolutions were used for the analysisUttar Pradesh contributes largest acreage of sugarcane (more than 40 per cent) to the national crop acreage; hence an early estimate of the crop acreage becomes paramount importance which was done using AWiFS data. Multi-date data of Resourcesat-2 AWiFS from February to November 2012 and January to November, 2013 for the 27 districts of Uttar Pradesh (U.P) was used to develop the procedure for early estimation of sugarcane acreage. The districts selected were having an area greater than 10 thousand ha and contribute 98.7 per cent of the state sugarcane acreage. The ground truth was collected during July/August and October 2012-13.The classification accuracy vis-a-vis critical data set requirement and identification of ratoon and freshly planted crop was also attempted. Early estimation of sugarcane acreage during month of June can be made possible by using multi-date AWiFS data upto May in case of Uttar Pradesh. The estimated acreage was 18.1 lakh ha which were 30 per cent underestimated in comparison to crop acreage estimation using data upto Nov. 3, 2012 which was 26.1 lakh ha. The error in early estimation of the crops was reduced by about 50 per cent as the estimated crop acreage during May was19.5 lakh ha whereas using AWiFS data upto Nov. 3, 2013 was 22.6 lakh ha. Therefore, on the basis of model output for two years, early estimation in June showed under estimation of 22 percent compared to final estimate in NovemberNot Availabl

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Not AvailableUttar Pradesh contributes largest acreage of sugarcane (more than 40 per cent) to the national crop acreage; hence an early estimate of the crop acreage becomes paramount importance which was done using AWiFS data. Multi-date data of Resourcesat-2 AWiFS from February to November 2012 and January to November, 2013 for the 27 districts of Uttar Pradesh (U.P) was used to develop the procedure for early estimation of sugarcane acreage. The districts selected were having an area greater than 10 thousand ha and contribute 98.7 per cent of the state sugarcane acreage. The ground truth was collected during July/August and October 2012-13.The classification accuracy vis-a-vis critical data set requirement and identification of ratoon and freshly planted crop was also attempted. Early estimation of sugarcane acreage during month of June can be made possible by using multi-date AWiFS data upto May in case of Uttar Pradesh. The estimated acreage was 18.1 lakh ha which were 30 per cent underestimated in comparison to crop acreage estimation using data upto Nov. 3, 2012 which was 26.1 lakh ha. The error in early estimation of the crops was reduced by about 50 per cent as the estimated crop acreage during May was19.5 lakh ha whereas using AWiFS data upto Nov. 3, 2013 was 22.6 lakh ha. Therefore, on the basis of model output for two years, early estimation in June showed under estimation of 22 percent compared to final estimate in November.Not Availabl