In this paper, for the first time, we propose a high-throughput and energy-efficient Processing-in-DRAM-accelerated genome assembler called PIM-Assembler based on an optimized and hardware-friendly genome assembly algorithm. PIM-Assembler can assemble large-scale DNA sequence dataset from all-pair overlaps. We first develop PIM-Assembler platform that harnesses DRAM as computational memory and transforms it to a fundamental processing unit for genome assembly. PIM-Assembler can perform efficient X(N)OR-based operations inside DRAM incurring low cost on top of commodity DRAM designs (~5% of chip area). PIM-Assembler is then optimized through a correlated data partitioning and mapping methodology that allows local storage and processing of DNA short reads to fully exploit the genome assembly algorithm-level's parallelism. The simulation results show that PIM-Assembler achieves on average 8.4× and 2.3 wise× higher throughput for performing bulk bit-XNOR-based comparison operations compared with CPU and recent processing-in-DRAM platforms, respectively. As for comparison/addition-extensive genome assembly application, it reduces the execution time and power by ~5× and ~ 7.5× compared to GPU.